• Journal of Korean Society of Industrial and Systems Engineering
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• v.27 no.1
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• pp.64-73
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• 2004

This paper addresses a problem of machining determination of input quantity in a multi-stage flexible flow system with non-identical parallel machines considers a subcontracting, machining restraint, and machine yield. We develop a nonlinear programing with the objective of minimizing the sum of in-house processing cost and subcontracting cost. To solve this model, we introduce a single-processor parallel genetic algorithm(SPGA) to improve a weak point for the declined robustness of simple algorithm(SGA). The efficiency of the SPGA is examined in comparison with the SGA for the same problem. In of examination the SPGA is to provide the excellent solution than the solution of the SGA.

• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.2097-2098
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• 2006

In this study, we introduce the hybrid optimization of fuzzy inference systems that is based on Hierarchical Fair Competition-based Parallel Genetic Algorithms (HFCGA). HFCGA is a kind of multi-populations of Parallel Genetic Algorithms(PGA), and it is used for structure optimization and parameter identification of fuzzy set model. It concerns the fuzzy model-related parameters as the number of input variables, a collection of specific subset of input variables, the number of membership functions, and the apexes of the membership function. In the hybrid optimization process, two general optimization mechanisms are explored. The structural optimization is realized via HFCGA method whereas in case of the parametric optimization we proceed with a standard least square method as well as HFCGA method as well. A comparative analysis demonstrates that the proposed algorithm is superior to the conventional methods.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.48 no.6
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• pp.322-329
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• 1999

In this paper a practical series-parallel compensated UPS is suggested, which has high input power factor and sinusoidal output voltage regulation capability. Compared to conventional cascaded UPS, the size can be reduced significantly with high quality input and output waveforms. The front converter and the main inverter can be considered decoupled, hence the front converter and the main inverter can be designed independent of each other. In this paper, analysis and experimental results for an l KVA prototype are presented.

• Journal of the Korean Society of Radiology
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• v.8 no.6
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• pp.357-364
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• 2014

The filtered back projection in the image reconstruction algorithms for the clinic computed tomography system has been widely used. Noise of the reconstructed image was examined under the input noise for parallel and fan beam geometries. The reconstruction images of $512{\times}512$ size were carried out under 360 and 720 projection by the Visual C++ for parallel beam and fan beam, respectively, and those agreed with the original Shepp-Logan head phantom very much. Noise was generated because of intrinsic restriction (finite number of projections) for the image reconstruction algorithm, filtered back projection, when no input noise was applied. Because the result noise was rapidly increased under 0.5% input noise ratio, technologies for reducing noise in CT system and image processing is important.

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.201-203
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• 2007

The paper concerns the successive optimization for structure and parameters of fuzzy inference systems that is based on parallel Genetic Algorithms (PGA) and information data granulation (IG). PGA is multi, population based genetic algorithms, and it is used tu optimize structure and parameters of fuzzy model simultaneously, The granulation is realized with the aid of the C-means clustering. The concept of information granulation was applied to the fuzzy model in order to enhance the abilities of structural optimization. By doing that, we divide the input space to form the premise part of the fuzzy rules and the consequence part of each fuzzy rule is newly' organized based on center points of data group extracted by the C-Means clustering, It concerns the fuzzy model related parameters such as the number of input variables to be used in fuzzy model. a collection of specific subset of input variables, the number of membership functions according to used variables, and the polynomial type of the consequence part of fuzzy rules, The simultaneous optimization mechanism is explored. It can find optimal values related to structure and parameter of fuzzy model via PGA, the C-means clustering and standard least square method at once. A comparative analysis demonstrates that the Dnmosed algorithm is superior to the conventional methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.1A
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• pp.114-121
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• 2000

The problem of an input-buffered switch is the HOL(head-of-line) blocking which limits the maximum throughput but it is easy to implement in hardware. However, HOL blocking can be eliminated using aVOQ(virtual-output-queueing) technique. 0 this paper, we propose a new cell-scheduling algorithm for aninput-buffered ATM switch. The proposed algorithm, called PPIM(Probabilistic Parallel Iterative Matching), imposesa weight to every request based on the reserved bandwidth. It is shown that the input-buffered ATM switch withthe proposed PPIM algorithm not only provides high throughput and low delay but it also reduces the jitter,compared with the existing WPIM(Weighted PIM).

• Journal of Power Electronics
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• v.19 no.3
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• pp.665-675
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• 2019

Renewable energy based on photovoltaic systems is beginning to play an important role to supply power to remote areas all over the world. Owing to the lower output voltage of photovoltaic arrays, high gain DC-DC converters with a high efficiency are required in practice. This paper presents a novel interleaved DC-DC boost converter with a high voltage gain, where the input terminal is interlaced in parallel and the output terminal is staggered in series (IPOSB). The IPOSB configuration can reduce input current ripples because two inductors are interlaced in parallel. The double output capacitors are charged in staggered parallel and discharged in series for the load. Therefore, IPOSB can attain a high step-up conversion and a lower output voltage ripple. In addtion, the output voltage can be automatically divided by two capacitors, without the need for extra sharing control methods. At the same time, the voltage stress of the power devices is lowered. The inrush current problem of capacitors is restrained by the inductor when compared with high gain converters with a switching-capacitor structure. The working principle and steady-state characteristics of the converter are analyzed in detail. The correctness of the theoretical analysis is verified by experimental results.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.05a
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• pp.13-16
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• 2000

In fuzzy expert systems or database systems that have huge volumes of fuzzy data or large fuzzy rules, the inference time is much increased. Therefore, a high performance parallel fuzzy computing environment is needed. In this paper, we propose a parallel fuzzy inference mechanism in parallel computing environment. In this, fuzzy rules are distributed and executed simultaneously. The ONE_TO_ALL algorithm is used to broadcast the fuzzy input vector to the all nodes. The results of the MIN/MAX operations are transferred to the output processor by the ALL_TO_ONE algorithm. By parallel processing of fuzzy rules or data, the parallel fuzzy inference algorithm extracts effective parallel ism and achieves a good speed factor.

• Proceedings of the Optical Society of Korea Conference
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• 1990.02a
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• pp.121-125
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• 1990

Optical Hough transform technique is introduced to obtain the straight line features in parallel from the input scene images. Experimental results are also provided to demonstrate the advantage of such optical parallel processor over the digital one. Peaks in optical Hough space are free from quantization noise and thus easy to detect.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10a
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• pp.721-723
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• 1987

An Adaptation algorithm is presented and a convergence criterion is derived for parallel model reference adaptive bilinear systems. The output error converges asymptotically to zero, and the parameter estimates are bounded for stable reference models. The convergence criterion depends only upon the input sequence and a priori estimates of the maximum parameter values.