• Journal of applied mathematics & informatics
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• v.26 no.3_4
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• pp.811-818
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• 2008

Biological systems with both protein-protein and protein-gene interactions can be modeled by differential equations for concentrations of the proteins with time-delay terms because of the time needed for DNA transcription to mRNA and translation of mRNA to protein. Values of some parameters in the mathematical model can not be measured owing to the difficulty of experiments. Also values of some parameters obtained in a normal stress condition can be changed under pathological stress stimuli. Thus it is important to find the effective way of determining parameters values. One approach is to use optimization algorithms. Here we construct an optimal system used to find optimal parameters in the equations with nonnegative time delays and apply this optimization result to the Nuclear factor-${\kappa}B$ pathway.

• Journal of Electrical Engineering and Technology
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• v.4 no.4
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• pp.515-520
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• 2009

According to the operating characteristics of pump applications, they should exhibit high efficiency and energy saving capabilities throughout the whole operating process. A novel efficiency optimization control strategy is presented here to meet the high efficiency demand of a variable speed Permanent Magnet Synchronous Motor (PMSM). The core of this strategy is the excellent integration of mended maximum torque to the current control algorithm, based on the losses model during the dynamic and the grade search method with changed step by fuzzy logic during the steady. The performance experiments for the control system of a variable speed high efficiency PMSM have been completed. The test results verified that the system can reliably operate with a different control strategy during dynamic and steady operation, and the system exhibits better performance when using the efficiency-optimization control.

• Journal of Power Electronics
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• v.14 no.2
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• pp.362-368
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• 2014

This paper proposes a harmonic reduction approach for a pulse width modulation (PWM) AC-AC converters using Bee Colony Optimization (BCO). The optimal switching angles are provided by BCO to minimize harmonic distortions. The sequences of the PWM switching angles are considered as a technical constraint. In this paper, simulation results from various optimization techniques including BCO, Genetic Algorithm (GA), and Particle Swarm Optimization (PSO) are compared. The test results indicate that BCO can provide a better solution than the others in terms of power quality and power factor improvement. Lastly, experiments on a 200W AC-AC converter confirm the performance of the proposed switching pattern in reducing harmonic distortions of the output waveform.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.28B no.12
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• pp.75-82
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• 1991

We proposed an optimal parallel implementation of an optimization neural network with linear increase of speedup by using multicomputer system and presented performance analysis model of the system. We extracted the temporal-and the spatial-parallelism from the optimization neural network and constructed a parallel pipeline processing model using the parallelism in order to achieve the maximum speedup and efficiency on the CSP architecture. The results of the experiments for the TSP using the Transputer system, show that the proposed system gives linear increase of speedup proportional to the size of the optimization neural network for more than 140 neurons, and we can have more than 98% of effeciency upto 16-node system.

• Transactions of the Korean Society of Automotive Engineers
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• v.16 no.1
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• pp.175-180
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• 2008

Due to the global environment problems and the consumer's need for higher vehicle performance, it becomes very important for the global car makers to reduce vehicle weight. To reduce vehicle weight, many car makers have tried to use lightweight materials, for example, aluminum, magnesium, and plastics, for the vehicle structures and components. Especially, the ASF(aluminum space frame) is known for the excellent concept of the vehicle to satisfy structural rigidity, safety performance and weight reduction. In this research, the design of experiments and the multi-disciplinary optimization technique were utilized to meet the weight and structural rigidity target of the ASF. For the structural performance of the ASF, the locations and the size of aluminum extruded frames, aluminum cast nodes, and the aluminum sheets were optimized. As a result, the optimization design procedure has been set up to meet both structural and weight target of the ASF, and the assembled ASF showed good structural performance and weight reduction.

• Journal of the Korean Society for Precision Engineering
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• v.6 no.4
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• pp.71-83
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• 1989

The optimization in the machining process has been a long-standing goal of the manufacturing community. The optimization is composed of two main subjects;one is to select an optimum cutting condition, and the other is to detect the emergency situation and take necessary actions in real-time base. This paper proposes a reliable and practical guide system whose purpose is the optimization of cutting conditions, and the detection of tool failure in the machining process. The optimal cutting conditions are determined through the estimation of tool wear rate and the establishment of access- ible field from the measured cutting temperature and force. Tool breakage is detected by the normal force component acting on minor flank face extracted from on-line sensed feed force and radial force. In experiments, the proposed guide system has proved availability for the decision of reliable cutting conditions for the given tool-work system and the detection of tool breakage in ordinary cutting environments.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.7 s.172
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• pp.177-184
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• 2005

Recently, the engineering designer of injection mould has become more and more dependent on the CAE. In the design factors of injection mould, the shrinkage rate should be considered as one of the important performances to produce the reliable products. therefore the shrinkage rate can be mostly calculated by the MoldFlow and Pro-engineering. in the design process. However it is not easy to predict the shrinkage rate of a plastic injection mold in its design process because the analysis can take minutes to hours, the high computational costs of performing the analysis limit their use in design optimization. In this study, the surrogate models, DACE model, based on the Kriging in order to optimize the shrinkage rate of electric microwave oven window is used in lieu of the original models, facilitating design optimization.

• Analytical Science and Technology
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• v.6 no.3
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• pp.267-274
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• 1993

The iterative regression optimization strategy using two parameters is described and applied to the separation of amino acids and peptides by means of micellar liquid chromatography. The parameters examined are concentration of surfactant and 2-propanol. This approach results in a efficient optimization using a small number of initial experiments.

• Journal of Microbiology and Biotechnology
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• v.14 no.6
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• pp.1163-1169
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• 2004

An unstructured mathematical model is presented for lactic acid fermentation based on the energy balance. The proposed model reflects the energy metabolic state and then predicts the cell growth, lactic acid production, and glucose consumption rates by relating the above rates with the energy metabolic rate. Fermentation experiments were conducted under various initial lactic acid concentrations of 0, 30, 50, 70, and 90 g/l. Also, a genetic algorithm was used for further optimization of the model parameters and included the operations of coding, initialization, hybridization, mutation, decoding, fitness calculation, selection, and reproduction exerted on individuals (or chromosomes) in a population. The simulation results showed a good fit between the model prediction and the experimental data. The genetic algorithm proved to be useful for model parameter optimization, suggesting wider applications in the field of biological engineering.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.10a
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• pp.249-254
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• 2000

The contact forces between die components for the drawing of large size automotive panels introduce elastic deflections of the die components. Due to the deflections, the gap between blank holder and die varies locally resulting in nonuniform material flow. Such a nonuniform die gap usually requires correcting operation, so called die spotting, which is time consuming trial and error process. To reduce the die spotting time, the optimization of the blank holder bending deflection is needed. In this paper, we implemented an analysis procedure to predict the blank holder deflection. The analysis procedure and design of experiments techniques are applied to the optimization of balance block heights. The optimization results can be used as guidelines in actual die spotting process.