• Transactions of Materials Processing
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• v.7 no.5
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• pp.489-495
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• 1998

Spinning is a chipless forming method for producing axially symmetric parts by using axial-radial motions of a spinning roller. This process has still some advantages in such a view point that a variety of complex shapes which can not be formed in a press can be easily spun at a low cost although it is one of the oldest forming methods for spinning mainly cookware parts for a long time. This study is to investigate the optimum roller path in order to obtain the maximum spinnability in producing cylindrical cups of Aluminum(A1050-H16) sheet metal. Working conditions applicable to any size of blank were predetermined through preliminary spinning tests. 9 types of roller path were proposed and experiments were carried out. The modified involute curve was shown to give the maximum drawing ration and more uniform quality of spun cups as compared with other results of this study. in addition thickness distribution and dimensional accuracy of spun cups were examined and discussed.

• Proceedings of the KIPE Conference
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• 2001.10a
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• pp.126-131
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• 2001

This paper deals with implementation of inverter systems for DC power regeneration, which can regenerate the excessive DC power from DC bus line to AC supply in substations for traction systems. From the viewpoint of both power capacity and switching losses, a three-phase square-wave inverter system is adopted. To control the regenerated power, the magnitude and phase of fundamental output voltages should be appropriately controlled in spite of the variation of input DC voltage. Inverters are operated with modified a-conduction mode to fix the potential of each arm. The overall system consists of the line-to-line voltage and line current sensors, an actual power calculator using d-q transformation method, a complex power controller with PI control scheme, a gating signal generator for modified $\alpha-conduction\;mode\;with\;\delta\;and\;\alpha$, a DPLL for frequency followup, and power circuit.

• ETRI Journal
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• v.36 no.3
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• pp.333-342
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• 2014

Most hyper-ellipsoidal clustering (HEC) approaches use the Mahalanobis distance as a distance metric. It has been proven that HEC, under this condition, cannot be realized since the cost function of partitional clustering is a constant. We demonstrate that HEC with a modified Gaussian kernel metric can be interpreted as a problem of finding condensed ellipsoidal clusters (with respect to the volumes and densities of the clusters) and propose a practical HEC algorithm that is able to efficiently handle clusters that are ellipsoidal in shape and that are of different size and density. We then try to refine the HEC algorithm by utilizing ellipsoids defined on the kernel feature space to deal with more complex-shaped clusters. The proposed methods lead to a significant improvement in the clustering results over K-means algorithm, fuzzy C-means algorithm, GMM-EM algorithm, and HEC algorithm based on minimum-volume ellipsoids using Mahalanobis distance.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.49 no.1
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• pp.59-63
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• 2000

For the Mo-tip field emitter array, the method by which the geometrical structure of the gate insulator wall could be modified in order to improve field emission properties(turn-on voltage and gate leakage current). The device having a gate insulator of complex shape, which means the combined geometrical structure with round shape made by wet etching and vertical shape made by dry etching processes, was fabricated and the field emission properties of the three kinds of devices were compared. As a result, the electric field applied to tip apex could be increased and gate leakage current could be decreased by employing the gate insulator having geometrical wall structure of mixed shape. Finally, the obtained empirical results were analyzed by simulation of electric field distribution at/near the tip apex and gate insulator using SNU-FEAT simulator.

• Journal of the Korean Society for Precision Engineering
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• v.3 no.1
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• pp.50-59
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• 1986

Adaptive Model Following Control (AMFC) technique is applied to develop a robot manipulator control system, which can deal successfully with the complex dvnamics of the manipulator. Main concerns of this study are put on the problem reducing the chatter amplitude of control signal yielded by the unit vector control law that was proposed [10] previously for AMFC of the manipulatro, and the effect- iveness of the algorithm when implemented practically. To see the effectiveness of modified method, computer simulations using new and old control law are carried out and compared, and the modified one id implemented in RHINO XR-II robot system recon- structed partially to enable torque control.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.31A no.9
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• pp.18-25
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• 1994

Previously. TCM decoder has been using the Viterbi algorithm that was complex. In order to reduce the complexity of decoder. we proposed the “modified decoding algorithm using the path back method” and the modified decoding algorithm which extends the previous decoding algorithm to be able to applied to TCM decoder in this paper. On the gaussian and impulsive noise channel. Monte-Carlo simulation is used for analyzing the TCM performance and proving the efficiency of proposed decoding algorithm.

• Journal of the Korean Ceramic Society
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• v.37 no.3
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• pp.240-246
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• 2000

The microwave dielectric properties of the complex perovskite (Pb0.5Ca0.5)(Fe0.5Ta0.5)O3 ceramics were investigated with the porosity and the dielectric mixing rule. Assuming that the specimens were mixtures of real dielectrics and pores, with 3-0 connectivity, the ionic polarizabilities modified by Maxwell's equation were more close to the theoretical values rather than those modified by Wiener's equation in porous specimens. The theoretical dielectirc loss were obtained with the infrared reflectivity spectra from 50 to 4000cm-1, which were calculated by Kramers-Kronig analysis and classical osciallator model. The relative tendency of dielectric loss calculated from the theoretical value and Maxwell's equation in the specimens with different porosities was in good agreement with the one by the post resonant method.

• Journal of Navigation and Port Research
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• v.29 no.2
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• pp.141-146
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• 2005

For a long time, genetic algorithms have been recognized as a new method to solve difficult and complex problems and the performance of genetic algorithms depends on genetic operators, especially crossover operator. Various problems like the traveling salesman problem, the transportation problem or the job shop problem, in logistics engineering can be modeled as a sequencing problem This paper proposes modified genetic crossover operators to be used at various sequencing problems and uses the traveling salesman problem to be applied to a real world problem like the delivery problem and the vehicle routing problem as a benchmark problem Because the proposed operators use parental information as well as network information, they could show better efficiency in performance and computation time than conventional operators.

• 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 the Institute of Convergence Signal Processing
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• v.2 no.1
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• pp.44-52
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• 2001

This paper describes an off-line method for recognizing totally unconstrained handwritten digits using modified chaotic neural networks(MCNN). The chaotic neural networks(CNN) is modified to be a useful network for solving complex pattern problems by enforcing dynamic characteristics and learning process. Since the MCNN has the characteristics of highly nonlinear dynamics in structure and neuron itself, it can be an appropriate network for the robust classification of complex handwritten digits. Digit identification starts with extraction of features from the raw digit images and then recognizes digits using the MCNN based classifier. The performance of the MCNN classifier is evaluated on the numeral database of Concordia University, Montreal, Canada. For the relative comparison of recognition performance, the MCNN classifier is compared with the recurrent neural networks(RNN) classifier. Experimental results show that the classification rate is 98.0%. It indicates that the MCNN classifier outperforms the RNN classifier as well as other classifiers that have been reported on the same database.