• Transactions of Materials Processing
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• v.9 no.6
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• pp.644-652
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• 2000

Tube hydroforming is recently drawing attention of automotive industries due to its several advantages over conventional methods. It can produce wide range of products such as subframes, engine cradles, and exhaust manifolds with cheaper production cost by reducing overall number of processes. h successful tube hydroforming depends on the reasonable combination of the internal pressure and axial load at the tube ends. This paper deals with the optimal process design of hydroforming process using the genetic algorithm and neural network. An optimization technique is used in order to minimize the tube thickness variation by determining the optimal loading path in the tube expansion forming and the tube T-shape forming process.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.22 no.50
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• pp.183-193
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• 1999

The problem of discovering association rules has received considerable research attention and several fast algorithms for mining association rules have been developed. In this paper, we propose an efficient algorithm for mining quantitative association rules with item constraints. For categorical attributes, we map the values of the attribute to a set of consecutive integers. For quantitative attributes, we can partition the attribute into values or ranges. While such constraints can be applied as a post-processing step, integrating them into the mining algorithm can reduce the execution time. We consider the problem of integrating constraints that are boolean expressions over the presence or absence of items containing quantitative attributes into the association discovery algorithm using Apriori concept.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.12
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• pp.1009-1014
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• 2001

The ladder diagram (LD) for programmable logic controllers (PLCs) ar responsible for much important roles in advance industrial automation. As automated systems become more complex the design procedures of the system become more difficult as well. Hence. the design automation issues based on discrete event models(DEMs) are receiving more attention. One of the popular ways of tackling these problems is employing Petri nets. In this paper, we use the modified automation Petri net(MAPN) to model the manufacturing system and the modified token passing logic (MTPL) method conversion (ECC) algorithm based on the MAPN and the MTPL Finally, an example of the manufacturing system is provided to illustrate the proposed ECC algorithm.

• Journal of Electrical Engineering and information Science
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• v.2 no.5
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• pp.1-8
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• 1997

The main purpose of the Boolean equivalence problem is to verify that two Boolean expressions have the same functionality. Simulation has been extensively used as the standard method for the equivalence problem. Obviously, the number of tests required to perform a satisfactory coverage grows exponentially with the number of input variables. However, formal methods as opposed to simulation are getting more attention from the community. We propose a new algorithm called the Cover-Merge Algorithm based on a derivational method using the concept of cover and merge for the equivalence problem and investigate its theoretical aspects. Because of the difficulty of the problem, we emphasize simplification techniques in order to reduce the search space or problem size. Heuristics based on types of merges are developed to speed up the derivation process by allowing simplifications. In comparison with widely used technique called Binary Decision Diagram or BDD, the algorithm proposed outperforms BDD in nearly all cases of input including standard benchmark problems.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.65-70
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• 1989

Lately, at an epock of a full-scale satellite launching plan of Korea, T.T.C(Tracking, Telemetery & Command) is a indispensable part. In this paper, particular attention is given to orbit determination problem of the role of T.T.C. A near-earth satellite is modeled, batch and extended sequential estimation algorithm (ESEA) are compared using range data. As a result, ESEA show effectiveness.

• Journal of KIISE
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• v.42 no.5
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• pp.609-620
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• 2015

Viewers of videos are likely to absorb more information from the part of the screen that attracts visual attention. This fact has led to the visual attention models that are being used in producing and evaluating videos. In this paper, we investigate the factors that are significant to visual attention and the mathematical form of the visual attention model. We then estimated the visual attention probability using the statistical design of experiments. The analysis of variance (ANOVA) verifies that the motion velocity, distance from the screen, and amount of defocus blur affect human visual attention significantly. Using the response surface modeling (RSM), we created a visual attention score model that concerns the three factors, from which we calculate the visual attention probabilities (VAPs) of image pixels. The VAPs are directly applied to existing gradient based 3D effect perception measurement. By giving weights according to our VAPs, our algorithm achieves more accurate measurement than the existing method. The performance of the proposed measurement is assessed by comparing them with subjective evaluation as well as with existing methods. The comparison verifies that the proposed measurement outperforms the existing ones.

• Journal of the Korean Society for Precision Engineering
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• v.29 no.12
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• pp.1304-1312
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• 2012

According to the successful development of hybrid vehicle, hybridization of construction equipments like excavator, wheel loader, and backhoe etc., is gaining increasing attention. However, hybridization of excavator and commercial vehicle is very different. Therefore a specialized energy management control algorithm for excavator should be developed. In this paper, hybridization of excavators is investigated and a new energy management control algorithm is proposed. Four control parameters, i.e., lower baseline, upper baseline, idling generation speed, and idling generation torque, are newly introduced and a new operating principle using those four control parameters is proposed. The use of Genetic Algorithm for the optimization of the four control parameters from the view point of minimization of fuel consumption for standard excavating operation is suggested. In order to verify the proposed algorithm, dedicated simulation program of hybrid excavator was developed. The proposed algorithm is applied to a specific hydraulic excavator and 20.7% improvement of fuel consumption is achieved.

• Journal of Electrical Engineering and Technology
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• v.13 no.5
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• pp.1852-1863
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• 2018

Direct current(DC) systems have recently attracted attention due to the increase in DC loads and distributed generations, such as renewable energy sources. Among these technologies, there has been much research into DC distribution systems or DC microgrids. Within this body of research, the main topics have been about optimum control and operation methods in terms of improving power efficiency. When DC systems are controlled and operated using power electronic devices such as converters, it is necessary to design and analyze them by considering the power electronics sections. For this reason, we propose a scalable DC system analysis algorithm, which considers various system configurations depending on the operating mode and location of the converter. The algorithm consists of power flow fault current calculations, and the results of the algorithm can be used for designing DC systems. The algorithm is implemented using MATLAB with defined input and output data. The verification of the algorithm is mainly performed using ETAP software, and the accuracy of the algorithm analysis can be confirmed through the results.

• Journal of Korean Port Research
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• v.7 no.1
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• pp.13-24
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• 1993

The rapid progress of the intermodal freight transportation in recent years has induced fierce competition among the adjacent hub ports for container transport. This brings increased attention to the evaluation of the port competitive ability. But it is not easy to evaluate the port competitive ability because this belongs to ill-defined system which is composed of ambiguous interacting attributes. Paying attention to this point, this paper deals the competitive ability of container port in Far-East Asia by fuzzy integral evaluation which is adequate to interacting ambiguous attribute problem. For this, the proposed fuzzy evaluation algorithm is applied to the real problem, based on the factors such as cargo volumes, costs, services, infrastructure and geographical sites These are extracted from the precedent study of port competitive ability, etc. The results show that the port evaluation factors come in following order ; services, costs, infrastructure, geographical sites and cargo volumes. There are some interactions(interaction coefficient, ${\lambda}=-0.664$ between evaluation attributes. The port competitive ability comes in following order : Singapore, Hongkong, Kobe, Kaoshiung and Busan. According to the sensitivity analysis, the rank between Busan and Kaoshiung changes when ${\lambda}=0.7$. From the analysis of the results, we confirmed that the proposed fuzzy evaluation algorithm is very effective in the complex-fuzzy problem which is composed of hierarchical structure with interacting attributes.

• The Journal of the Acoustical Society of Korea
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• v.20 no.4
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• pp.48-53
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• 2001

In this paper, selectively attentive learning method has been proposed to improve the learning speed of multilayer Perceptron based on the error backpropagation algorithm. Three attention criterions are introduced to effectively determine which set of input patterns is or which portion of network is attended to for effective learning. Such criterions are based on the mean square error function of the output layer and class-selective relevance of the hidden nodes. The acceleration of learning time is achieved by lowering the computational cost per iteration. Effectiveness of the proposed method is demonstrated in a speaker adaptation task of isolated word recognition system. The experimental results show that the proposed selective attention technique can reduce the learning time more than 60% in an average sense.