• Journal of the Korean Applied Science and Technology
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• v.37 no.6
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• pp.1738-1751
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• 2020

The skin is divided into three parts: the epidermis, the dermis, and the subcutaneous fat, and the stratum corneum, which is located at the top of the epidermis, acts as a barrier that prevents drug delivery. Nanoemulsions are known to be effective in transdermal delivery of drugs through intercellular lipids because of their unique small particle size. In this study, phase inversion temperature (PIT) nanoemulsion containing α-bisabolol was optimized using response surface methodology (RSM) for effective skin absorption of α-bisabolol. As a preliminary experiment, the 25-2 fractional factorial design method and the 23 full factorial design method were performed. Box-Behnken design was performed based on the results of the factorial design method. The content of surfactant (6.3~12.6%), co-surfactant (5.2~7.8%) and α-bisabolol (0.5~5.0%) were used as factors, and the dependent variable was the particle size of the nanoemulsion. PIT nanoemulsion optimization was performed according to the RSM results, and as a result, the optimal nanoemulsion formulation conditions were predicted to be 10.4% surfactant content, 6.3% co-surfactant content, and 5.0% α-bisabolol content. As a result of the skin absorption test, the final skin absorption rate of the PIT nanoemulsion was 35.11±1.01%, and the final skin absorption rate of the general emulsion as a control was 28.25±1.69%, confirming that the skin absorption rate of the PIT nanoemulsion was better.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.14 no.10
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• pp.939-944
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• 2004

The numerical methods including the performance analysis and the noise prediction of the centrifugal compressor impeller are coupled with the optimization design skill, which consists of response surface method, statistical approach, and genetic algorithm. The flow-field Inside of a centrifugal compressor is obtained numerically by solving Wavier-Stokes equations. and then the propagating noise is estimated from the distributed surface pressure by using Ffowcs Williams-Hawkings formulation. The quadratic response surface model with D-optimal 3-level factorial experimental design points is constructed to optimize the impeller geometry for the advanced centrifugal compressor. The statistical analysis shows that the quadratic model exhibits a reasonable fitting quality resulting in the impeller blade design with high performance and low far-field noise level. The influences of selected design variables, objective functions, and constraints on the impeller performance and the impeller noise are also examined as a result of the optimization process.

• Journal of the Korea Safety Management & Science
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• v.9 no.2
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• pp.215-233
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• 2007

Even though the ad hoc Shewhart methods remain controversial due to various mathematical flaws, there is little disagreement among researchers and practitioners when a set of process data has a skewness distribution. In the context and language of process control, the error related to the process data shows that time to signal increases when a control parameter shifts to a skewness direction. In real-world industrial settings, however, quality practitioners often need to consider a skewness distribution. To address this situation, we developed an enhanced design method to utilize advantages of the traditional attribute control chart and to overcome its associated shortcomings. The proposed design method minimizes bias, i.e., an average time to signal for the shift of process from the target value (ATS) curve, as well as it applies a variable sampling interval (VSI) method to an attribute control chart for detecting a process shift efficiently. The results of the factorial experiment obtained by various parameter circumstances show that the VSI c control chart using nearly unbiased ATS design provides the smallest decreasing rate in ATS among other charts for all experimental cases.

• International Journal of Korean Welding Society
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• v.1 no.1
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• pp.44-50
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• 2001

A genetic algorithm was applied to the arc welding process as to determine the near-optimal settings of welding process parameters that produce the good weld quality. This method searches for optimal settings of welding parameters through the systematic experiments without the need for a model between the input and output variables. It has an advantage of being capable to find the optimal conditions with a fewer number of experiments rather than conventional full factorial designs. A genetic algorithm was applied to the optimization of the weld bead geometry. In the optimization problem, the input variables were wire feed rate, welding voltage, and welding speed. The output variables were the bead height bead width, and penetration. The number of levels for each input variable is 16, 16, and 8, respectively. Therefore, according to the conventional full factorial design, in order to find the optimal welding conditions,2048 experiments must be performed. The genetic algorithm, however, found the near optimal welding conditions in less than 40 experiments.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.20 no.6
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• pp.521-527
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• 2010

This article presents a method to calculate the sound radiation of transmission gearbox housing by using Helmholtz integral. Rayleigh integral is used to verify the method. Half-space radiation is considered because the actual gearbox housing is on hard place like concrete. For optimization, orthogonal array is used as a fractional factorial design method. Sound Radiation is calculated with simple source like plate and sphere shape, then actual gearbox BEM model is applied to the method.

• Design & Manufacturing
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• v.15 no.1
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• pp.41-47
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• 2021

The Fine Blanking process is an effective precision shearing process that can obtain a smooth cutting surface and high product precision through a single blanking process. It is widely used in various manufacturing fields. However, shearing through this fine blanking process is only intended to minimize burrs, die rolls and fracture surfaces and does not completely remove them. Therefore, it is necessary to study the minimization of burrs, die rolls and fracture surfaces in the fine blanking process. In this study, a study was conducted on the relationship between the fracture surface and process conditions that occurred during product production using the fine blanking process. For this purpose, the shape of the V-ring indenter, the distance to the punch, and the pressure force, clearance, shear rate, and physical properties of the material were selected as process and design variables, and the relationship with the fracture surface according to each process and design condition was tested. It was analyzed through the Experimental Design Method.

• Proceedings of the KSME Conference
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• 2003.11a
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• pp.1430-1435
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• 2003

Satellite upper platform is optimized by response surface method which has non-gradient, semi-glogal, discrete and fast convergency characteristics. Sampling points are extracted by design of experiments using Central Composite Method and Factorial Design. Also response surface is generated by the various regression functions. Structure analysis is execuated with regard for static and dynamic environment in launching stage. As a result response surface method is superior to other optimization method with respect to optimum value and cost of computation time. Also a confidence is varified in the various regression models.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.30 no.7 s.250
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• pp.700-706
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• 2006

This study presents a numerical procedure to optimize the shape of dimple surface to enhance turbulent heat transfer in a rectangular channel. The response surface based optimization method is used as an optimization technique with Reynolds-averaged Wavier-Stokes analysis of fluid flow and heat transfer with shear stress transport (SST) turbulence model. The dimple depth-to-dimple print diameter ratio, channel height-to-dimple print diameter ratio, and dimple print diameter-to-pitch ratio are chosen as design variables. The objective function is defined as a linear combination of heat transfer related term and friction loss related term with a weighting factor. full factorial method is used to determine the training points as a mean of design of experiment. The optimum shape shows remarkable performance in comparison with a reference shape.

• 유체기계공업학회:학술대회논문집
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• 2004.12a
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• pp.285-288
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• 2004

This study presents a numerical procedure to optimize the shape of dimple surface to enhance turbulent heat transfer in rectangular channel. The response surface based optimization method is used as an optimization technique with Reynolds-averaged Wavier-Stokes analysis of fluid flow and heat transfer with shear stress transport (SST) turbulence model. The dimple depth-to -dimple print diameter ratio, channel height- to- dimple print diameter ratio. and dimple print diameter-to-pitch ratio are chosen as design variables. The objective function is defined as a linear combination of heat transfer coefficient and friction drag coefficient with a weighting factor. Full factorial method is used to determine the training points as a mean of design of experiment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.11
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• pp.3619-3637
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• 2022

Big data analytics offers endless opportunities for operational enhancement by extracting valuable insights from complex voluminous data. Hadoop is a comprehensive technological suite which offers solutions for the large scale storage and computing needs of Big data. The performance of Hadoop is closely tied with its configuration settings which depends on the cluster capacity and the application profile. Since Hadoop has over 190 configuration parameters, tuning them to gain optimal application performance is a daunting challenge. Our approach is to extract a subset of impactful parameters from which the performance enhancing sub-optimal configuration is then narrowed down. This paper presents a statistical model to analyze the significance of the effect of Hadoop parameters on a variety of performance metrics. Our model decomposes the total observed performance variation and ascribes them to the main parameters, their interaction effects and noise factors. The method clearly segregates impactful parameters from the rest. The configuration setting determined by our methodology has reduced the Job completion time by 22%, resource utilization in terms of memory and CPU by 15% and 12% respectively, the number of killed Maps by 50% and Disk spillage by 23%. The proposed technique can be leveraged to ease the configuration tuning task of any Hadoop cluster despite the differences in the underlying infrastructure and the application running on it.