• Computational Structural Engineering
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• v.10 no.2
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• pp.233-242
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• 1997

The main purpose of this paper is to investigate the dynamic optimal design of continuous beams. The computer-aided optimization technique is used to obtain the near-optimal parameters of continuous beam. The computer program is developed to obtain the natural frequency parameters and the forced vibration responses to a transit point load for the continuous beam with variable support spacing, mass and stiffness. The model test data is in good agreement with the computer calculation, which serves to validate the mathematical analysis. The optimization function to describe the design efficiency is defined as a linear combination of four dimensionless span characteristics; the maximum dynamic stress; the stress difference between span segments; the rms deflection under the transit point load; and the total span mass. Studies of three span beams show that the beam with near-optimal parameters can improve design efficiency when compared to a uniform beam with even spacing of the same total span length.

• Smart Structures and Systems
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• v.20 no.1
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• pp.61-74
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• 2017

One of the most reliable and simplest tools for structural vibration control in civil engineering is Tuned Mass Damper, TMD. Provided that the frequency and damping parameters of these dampers are tuned appropriately, they can reduce the vibrations of the structure through their generated inertia forces, as they vibrate continuously. To achieve the optimal parameters of TMD, many different methods have been provided so far. In old approaches, some formulas have been offered based on simplifying models and their applied loadings while novel procedures need to model structures completely in order to obtain TMD parameters. In this paper, with regard to the nonlinear decision-making of fuzzy systems and their enough ability to cope with different unreliability, a method is proposed. Furthermore, by taking advantage of both old and new methods a fuzzy system is designed to be operational and reduce uncertainties related to models and applied loads. To design fuzzy system, it is required to gain data on structures and optimum parameters of TMDs corresponding to these structures. This information is obtained through modeling MDOF systems with various numbers of stories subjected to far and near field earthquakes. The design of the fuzzy systems is performed by three methods: look-up table, the data space grid-partitioning, and clustering. After that, rule weights of Mamdani fuzzy system using the look-up table are optimized through genetic algorithm and rule weights of Sugeno fuzzy system designed based on grid-partitioning methods and clustering data are optimized through ANFIS (Adaptive Neuro-Fuzzy Inference System). By comparing these methods, it is observed that the fuzzy system technique based on data clustering has an efficient function to predict the optimal parameters of TMDs. In this method, average of errors in estimating frequency and damping ratio is close to zero. Also, standard deviation of frequency errors and damping ratio errors decrease by 78% and 4.1% respectively in comparison with the look-up table method. While, this reductions compared to the grid partitioning method are 2.2% and 1.8% respectively. In this research, TMD parameters are estimated for a 15-degree of freedom structure based on designed fuzzy system and are compared to parameters obtained from the genetic algorithm and empirical relations. The progress up to 1.9% and 2% under far-field earthquakes and 0.4% and 2.2% under near-field earthquakes is obtained in decreasing respectively roof maximum displacement and its RMS ratio through fuzzy system method compared to those obtained by empirical relations.

• Journal of Wetlands Research
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• v.13 no.3
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• pp.385-394
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• 2011

In this study, optimal parameters of diffusion-analogy GIUH were calculated by separating channel and hillslope from drainage structures in the basin. Parameters of the model were composed of channel and hillslope, each velocity($u_c$, $u_h$) and diffusion coefficient($D_c$, $D_h$). Tanbu subwatershed in Bocheong river basin as a target basin was classified as 4th rivers by Strahler's ordering scheme. The optimization technique was applied to the SCE-UA, the estimated optimal parameters are as follows. $u_c$ : 0.589 m/s, $u_h$ : 0.021 m/s, $D_c$ : $34.469m^2/s$, $D_h$ : $0.1333m^2/s$. As a verification for the estimated parameters, the error of average peak flow was about 11 % and the error of peaktime was 0.3 hr. By examining the variability of parameters, the channel diffusion coefficient didn't have significant effect on hydrological response function. by considering these results, the model is expected to be simplified in the future.

• Journal of Advanced Navigation Technology
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• v.16 no.5
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• pp.846-852
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• 2012

The result of imaging segmentation becomes different with the parameters involved in the segmentation algorithms; therefore, the parameters for the optimal segmentation have been found through a try and error. In this paper, we propose the method to find the best values of parameters involved in the area-based active contour method using three-way ANOVA. The segmentation result applied by three-way ANOVA is compared with the optimal segmentation which is drawn by user. We use the global consistency rate for comparing two segmentations. Finally, we estimate the main effects and interactions between each parameter using three-way ANOVA, and then calculate the point and interval estimate to find the best values of three parameters. The proposed method will be a great help to find the optimal parameters before working the motion segmentation using piecewise constant model.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.32 no.3
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• pp.209-216
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• 2008

The application of focused ion beam (FIB) depends on the optimal interaction of the operation parameters between operating parameters which control beam and samples on the stage during the FIB deposition process. This deposition process was investigated systematically in C precursor gas. Under the fine beam conditions (30kV, 40nm beam size, etc), the effect of considered process parameters - dwell time, beam overlap, incident beam angle to tilted surface, minimum frame time and pattern size were investigated from deposition results by the design of experiment. For the process analysis, influence of the parameters on FIB-CVD process was examined with respect to dimensions and constructed shapes of single and multi- patterns. Throughout the single patterning process, optimal conditions were selected. Multi-patterning deposition were presented to show the effect of on-stage parameters. The analysis have provided the sequent beam scan method and the aspect-ratio had the most significant influence for the multi-patterning deposition in the FIB processing. The bitmapped scan method was more efficient than the one-by-one scan type method for obtaining high aspect-ratio (Width/Height > 1) patterns.

• Magazine of the Korean Society of Agricultural Engineers
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• v.40 no.2
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• pp.59-68
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• 1998

This study was conducted to derive optimal design floods by generalized gamma distribution model of the annual maximum series at eight watersheds along Geum, Yeongsan and Seomjin river systems. Design floods obtained by different methods for evaluation of parameters and for plotting positions in the generalized gamma distribution model were compared by the relative mean errors and graphical fit along with 95% confidence limits plotted on gamma probability paper. The results were analyzed and summarized as follows. 1. Basic statistics and parameters were calculated by the generalized gamma distribution model using different methods for parameters. 2. Design floods according to the return periods were obtained by different methods for evaluation of parameters and for plotting positions in the generalized gamma distribution model. 3. It was found that design floods derived by sundry averages method for parameters and Cunnane method for plotting position in the generalized gamma distribution are much closer to those of the observed data in comparison with those obtained by the other methods for parameters and for plotting positions from the viewpoint of relative mean errors. 4. Reliability of design floods derived by sundry averages method in the generalized gamma distribution was acknowledged within 95% confidence interval.

• Proceedings of the KWS Conference
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• 2006.10a
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• pp.253-255
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• 2006

Grey relational analysis has been carried out to develop a new approach for optimization of Nd:YAG laser and MIG hybrid welding parameters. The quality of welded material depends on welding parameters. The parameters chosen for current study include wire type, shielding gas, laser energy, laser focus, traveling speed, and wire feed rate. The welding experiments were performed on 6K21-T4 aluminum alloy sheet. Functional demands on products may vary widely depending on their use. The ultimate tensile stress, width, and penetration were chosen as the optimization criterion. Practice based on an orthogonal array which is following Taguchi's method has been progressed. Base on the results of grey relational analysis, the optimal process parameters were obtained. This integrated work was judged and it is observed that the results obtained by using the optimal parameters are much improved compared to those obtained through initial setting.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.1006-1011
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• 2003

In this study, a novel systematic design procedure by Genetic Algorithm of a two stage relief valve is proposed. First of all, a mathematical model describing the dynamics of a balanced piston type relief valve has been derived. Governing equations such as dynamic equations for the main spool and the pilot spool and flow equations for each orifice are established. The mathematical model is verified by comparing the results of simulation with that of experiments. Furthermore, influences of the parameters on the dynamic characteristics of a relief valve have been investigated by simulation of the proposed model. Major design parameters on the valve response are determined, which affect the system response significantly. And then, using the determined parameters, the optimization of the two stage relief valve by Genetic Algorithm, which is a random search algorithm can find the global optimum without converging local optimum, is performed. The optimal design process of a two stage relief valve is presented to determine the major design parameters. Fitness function reflects the changing pressure according to parameters. It is shown that the genetic algorithms satisfactorily optimized the major design parameters of the two stage relief valve.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.10a
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• pp.501-506
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• 2002

In this study, a novel systematic design procedure by Genetic Algorithm of a two stage relief valve is proposed. First of all. a mathematical model describing the dynamics of a balanced piston type relief valve has been derived. Governing equations such as dynamic equations for the main spool and the pilot spool and flow equations for each orifice are established. The mathematical model is verified by comparing the results of simulation with that of experiments. Furthermore, influences of the parameters on the dynamic characteristics of a relief valve have been investigated by simulation of the proposed model. Major design parameters on the valve response are determined, which affect the system response significantly. And then, using the determined parameters, the optimization of the two stage relief valve by Genetic Algorithm, which is a random search algorithm can find the global optimum without converging local optimum, is performed. The optimal design process of a two stage relief valve is presented to determine the major design parameters. Fitness function reflects the changing pressure according to parameters. It is shown that the genetic algorithms satisfactorily optimized the major design parameters of the two stage relief valve.

• 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.