• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.5
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• pp.417-425
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• 2003

H.264, which is the latest video coding standard of both ITU-T(International Telecommunication Union-Telecommunication standardization sector) and MPEG(Moving Picture Experts Group), adopts new video coding tools such as variable block size motion estimation, multiple reference frames, quarter-pel motion estimation/compensation(ME/MC), 4${\times}$4 Integer DCT(Discrete Cosine Transform), and Rate-Distortion Optimization, etc. These new video coding tools provide good coding of efficiency compared with existing video coding standards as H.263, MPEG-4, etc. However, these new coding tools require the increase of encoder complexity. Therefore, in order to apply H.264 to many real applications, fast algorithms are required for H.264 coding tools. In this paper, when encoder MacroBlock(MB) mode is decided by rate-distortion optimization tool, fast mode decision algorithm by skipping variable block size ME/MC and spatial-predictive coding, which occupies most encoder complexity, is proposed. In terms of computational complexity, the proposed method runs about 4 times as far as JM(Joint Model) 42 encoder of H.264, while the PSNR(peak signal-to-noise ratio)s of the decoded images are maintained.

• Advances in Energy Research
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• v.6 no.1
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• pp.55-73
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• 2019

The cost incurred by voltage sag effect in power networks has always been of important concern for discussions. Due to the environmental constraints, fossil fuel shortage crisis and low efficiency of conventional power plants, decentralized generation and renewable based DG have become trends in recent decades; because DGs can reduce the voltage sag effect in distribution networks noticeably; therefore, optimum allocation of DGs in order to maximize their effectiveness is highly important in order to maximize their effectiveness. In this paper, a new method is proposed for calculating the cost incurred by voltage sag effect in power networks. Thus, a new objective function is provided that comprehends technical standards as minimization of the cost incurred by voltage sag effect, active power losses and economic criterion as the installation and maintenance costs of DGs. Considering operational constraints of the system, the optimum allocation of DGs is a constrained optimization problem in which Lightning Attachment procedure optimization (LAPO) is used to resolve it and is the optimum number, size and location of DGs are determined in IEEE 33 bus test system and IEEE 34 bus test system. The results show that optimum allocation of DGs not only reduces the cost incurred by voltage sag effect, but also improves the other characteristics of the system.

• Journal of the Institute of Convergence Signal Processing
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• v.4 no.2
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• pp.7-11
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• 2003

Nowadays, as digital technologies are rapidly developed and requirements for the various types of broadband multimedia services increases, the radio broadcasting is moving to digitalization. DAB(Digital Audio Broadcasting), as an alternation of existing analog radio broadcasting, is a new type of multimedia broadcasting system. DAB supports not only high-quality audio broadcasting but also various types of multimedia data services. In this paper, we investigate the performance optimization method of MOT Protocol, as the standard for additional services, to support the multimedia services in the DAB network. Because the performance of the MOT protocol is dependent on various parameters such as segment size, segment repetition and so on, we find those by simulation for performance optimization. According to simulation results, the suitable segment size is about 2Kbyte and segment repetition is 4 times for performance optimization.

• Smart Structures and Systems
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• v.29 no.4
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• pp.523-533
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• 2022

A novel metaheuristic search method, namely black widow optimization (BWO) is employed to increase the accuracy of slope stability analysis. The BWO is a recently-developed optimizer that supervises the training of an artificial neural network (ANN) for predicting the factor of safety (FOS) of a single-layer cohesive soil slope. The designed slope bears a loaded foundation in different distances from the crest. A sensitivity analysis is conducted based on the number of active individuals in the BWO algorithm, and it was shown that the best performance is acquired for the population size of 40. Evaluation of the results revealed that the capability of the ANN was significantly enhanced by applying the BWO. In this sense, the learning root mean square error fell down by 23.34%. Also, the correlation between the testing data rose from 0.9573 to 0.9737. Therefore, the postposed BWO-ANN can be promisingly used for the early prediction of FOS in real-world projects.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.3
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• pp.133-144
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• 2000

Genetic Algorithm(GA) has been known as a method of solving large-scaled optimization problems with complex constraints in various applications. Since a major drawback of the GA is that it needs a long computation time, the hardware implementations of Genetic Algorithm Processors(GAP) are focused on in recent studies. In this paper, a hardware-oriented GA was proposed in order to save the hardware resources and to reduce the execution time of GAP. Based on steady-state model among continuos generation model, the proposed GA used modified tournament selection, as well as special survival condition, with replaced whenever the offspring's fitness is better than worse-fit parent's. The proposed algorithm shows more than 30% in convergence speed over the conventional algorithm in simulation. Finally, by employing the efficient pipeline parallelization and handshaking protocol in proposed GAP, above 30% of the computation speed-up can be achieved over survival-based GA which runs one million crossovers per second (1㎒), when device speed and size of application are taken into account on prototype. It would be used for high speed processing such of central processor of evolvable hardware, robot control and many optimization problems.

• Journal of Korean Society of Steel Construction
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• v.23 no.4
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• pp.465-474
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• 2011

In this study, a microgenetic algorithm was used to find the optimum cross-section and shape of dome structures. The allowable stress and Euler buckling stress were considered constraints when the weight of the trusses was minimum. The design optimization of the truss structures involved arriving at the optimum sizes of the cross-section and geometric coordinate. The features of the proposed method, which helped in the modeling of and application to the optimal design of truss structures, were demonstrated using the microgenetic algorithm, by solving sample problems.

• Journal of the Optical Society of Korea
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• v.13 no.1
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• pp.92-97
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• 2009

In this paper, a conventional simulated annealing (SA) method for optimization of a kinoform computer generated hologram (CGH) is analyzed and the SA method is modified to reduce a reconstruction error rate (ER) of the CGH. The dependences of the quantization level of the hologram pattern and the size of the data on the ER are analyzed. To overcome saturation of the ER, the conventional SA method is modified as it magnifies a Fourier-transformed pattern in the intermediate step. The proposed method can achieve a small ER less than 1%, which is impossible in the conventional SA method.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.2 s.173
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• pp.319-328
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• 2000

This paper presents a new design method of the 1 generation wheel bearing unit using a numerical optimization technique in order to increase bearing fatigue life. For calculating the fatigue life, a method of load analysis is studied on the automotive wheel bearing system. The design variables selected are ball size, initial contact angle, number of balls, pitch diameter, pre-load, and distance between ball centers. The method of feasible directions in ADS (Automated Design Synthesis) is utilized to automatically find the optimum design variables. To validate the design method, a computer program is developed and applied to a practical passenger car model. The optimum design results demonstrated the effectiveness of the proposed design method showing that the system life of the optimally designed wheel bearing unit is enhanced in comparison with that of the initial ones within the given available design space.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2314-2316
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• 2000

In the construction of successful fuzzy models and/or controllers for nonlinear systems, identification of a good fuzzy Neural inference system is an important yet difficult problem, which is traditionally accomplished by trial and error process. In this paper, we propose a systematic identification procedure for complex multi-input single- output nonlinear systems with DNA coding method.DNA coding method is optimization algorithm based on biological DNA as are conventional genetic algothms (GAs). We also propose a new coding method for applying the DNA coding method to the identification of fuzzy Neural models. To acquire optimal TS fuzzy model with higher accuracy and economical size, we use the DNA coding method to optimize the parameters and the number of fuzzy inference system.

• Journal of Korean Institute of Industrial Engineers
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• v.22 no.4
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• pp.633-649
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• 1996

An interactive multicriteria method, which is called the Modified Pairwise Comparison Stochastic Cutting Plane (MPCSCP) method, is proposed for determining the best levels of the integer decision variables needed to optimize a stochastic computer simulation with multiple response functions. MPCSCP combines good features from interactive tradeoff cutting plane methods and response surface methodologies. The proposed method uses a simple pairwise man-machine interaction and searches an integer space uniformly by using the experimental design which evaluates the decision space centering around an integer center point. The characteristics of the proposed method are investigated through an extensive computational study. The parameter configurations examined in the study are (1) variability of the sampling errors, (2) the size of experimental design, (3) the relaxation of cutting planes, and (4) the levels of decision maker's inconsistency.