• Journal of The Korean Society of Agricultural Engineers
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• v.55 no.3
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• pp.25-33
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• 2013

In this study, the optimum mix proportions of rain garden structure concrete were decided and the mechanical properties were evaluated. Experimental parameters were blast furnace slag, hwang-toh, recycled aggregates and natural jute fibers. The target compressive strength and chloride ion penetration were more than 24 MPa and less than 1000 coulombs, respectively. The response surface method was used for statistical optimization of experimental results. The optimal mixing ratios of the blast furnace slag, hwang-toh, recycled coarse aggregate and jute fiber volume fraction were determined 59.98 %, 8.74 %, 12.12 % and 0.2 %, respectively. The compressive strength, flexural strength and chloride ion penetration test results of optimum mix ratio showed that the 24.56 MPa, 3.88 MPa and 999.08 columbs, respectively.

• Transactions on Electrical and Electronic Materials
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• v.13 no.3
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• pp.129-135
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• 2012

A number of surface mount technology (SMT) process variables including land design are considered for minimizing tombstone defect in flexible printed circuit assembly in high volume manufacturing. As SMT chip components have been reduced over the past years with their weights in milligrams, the torque that once helped self-centering of chips, gears to tombstone defects. In this paper, we have investigated the correlation of the assembly process variables with respect to the tombstone defect by employing statistically designed experiment. After the statistical analysis is performed, we have setup hypotheses for the root causes of tombstone defect and derived main effects and interactions of the process parameters affecting the hypothesis. Based on the designed experiments, statistical analysis was performed to investigate significant process variable for the purpose of process control in flexible printed circuit manufacturing area. Finally, we provide beneficial suggestions for find-pitch PCB design, screen printing process, chip-mounting process, and reflow process to minimize the tombstone defects.

• Communications for Statistical Applications and Methods
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• v.12 no.2
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• pp.443-451
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• 2005

The studied in this paper is a new algorithm for searching the maximum likelihood estimate(MLE) in which probability density function is not explicitly expressed. Newton-Raphson's root-finding routine and a nonlinear numerical optimization algorithm with constraint (so-called feasible sequential quadratic programming) are used. This algorithm is applied to the Wakeby distribution which is importantly used in hydrology and water resource research for analysis of extreme rainfall. The performance comparison between maximum likelihood estimates and method of L-moment estimates (L-ME) is studied by Monte-carlo simulation. The recommended methods are L-ME for up to 300 observations and MLE for over the sample size, respectively. Methods for speeding up the algorithm and for computing variances of estimates are discussed.

• Transactions of the Korean Society of Automotive Engineers
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• v.13 no.1
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• pp.119-125
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• 2005

The current automotive is seeking the improvement of performance, the prevention of environmental pollution and the saving of energy resources according to miniaturization and lightweight of the components. And the variance analysis on the basis of structure analysis and DOE is applied to the lower control am. We have proposed a statistical design model to evaluate the effect of structural modification by performing the practical multi-objective optimization considering weight, stress and fatigue lift. The lower control arm is performed the fatigue analysis using the load history of real road test. The design model is determined using the optimization of acquired load history with the fatigue characteristic. The characteristic function is made use of the optimization according to fatigue characteristics to consider constrained function in the optimization of DOE. The structure optimization of a lower control arm according to fatigue characteristics is performed. And the optimized design variable is D=47 m, T=36mm, W=12 mm. In the real engineering problem of considering many objective functions, the multi-objective optimization process using the mathematical programming and the characteristic function is derived an useful design solution.

• Structural Engineering and Mechanics
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• v.69 no.1
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• pp.21-31
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• 2019

Optimizing composite structures to exploit their maximum potential is a realistic application with promising returns. In this research, simultaneous maximization of the fundamental frequency and frequency separation between the first two modes by optimizing the fiber angles is considered. A high-fidelity design optimization methodology is developed by combining the high-accuracy of finite element method with iterative improvement capability of metaheuristic algorithms. Three powerful nature-inspired optimization algorithms viz. a genetic algorithm (GA), a particle swarm optimization (PSO) variant and a cuckoo search (CS) variant are used. Advanced memetic features are incorporated in the PSO and CS to form their respective variants-RPSOLC (repulsive particle swarm optimization with local search and chaotic perturbation) and CHP (co-evolutionary host-parasite). A comprehensive set of benchmark solutions on several new problems are reported. Statistical tests and comprehensive assessment of the predicted results show CHP comprehensively outperforms RPSOLC and GA, while RPSOLC has a little superiority over GA. Extensive simulations show that the on repeated trials of the same experiment, CHP has very low variability. About 50% fewer variations are seen in RPSOLC as compared to GA on repeated trials.

• International Journal of Concrete Structures and Materials
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• v.9 no.2
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• pp.185-206
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• 2015

This paper presents statistical models developed to study the influence of key mix design parameters on the properties of lightweight self-consolidating concrete (LWSCC) with expanded shale (ESH) aggregates. Twenty LWSCC mixtures are designed and tested, where responses (properties) are evaluated to analyze influence of mix design parameters and develop the models. Such responses included slump flow diameter, V-funnel flow time, J-ring flow diameter, J-ring height difference, L-box ratio, filling capacity, sieve segregation, unit weight and compressive strength. The developed models are valid for mixes with 0.30-0.40 water-to-binder ratio, high range water reducing admixture of 0.3-1.2 % (by total content of binder) and total binder content of $410-550kg/m^3$. The models are able to identify the influential mix design parameters and their interactions which can be useful to reduce the test protocol needed for proportioning of LWSCCs. Three industrial class ESH-LWSCC mixtures are developed using statistical models and their performance is validated through test results with good agreement. The developed ESH-LWSCC mixtures are able to satisfy the European EFNARC criteria for self-consolidating concrete.

• Journal of Radiation Industry
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• v.17 no.1
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• pp.111-118
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• 2023

The International Commission on Radiological Protection (ICRP) 103 recommends a cost-benefit analysis method as an auxiliary tool for scientific and rational decision-making for the principle of optimization of radiological protection. In order to conduct a cost-benefit analysis, the safety improvement of nuclear power by regulation must be measured and converted into monetary terms. The improvement of nuclear safety can be measured by reducing the radiation exposure dose of the people, and it is necessary to determine the coefficient to convert the radiation exposure dose into money. The monetary coefficient is calculated as the product of the statistical life value (VSL) and the nominal risk coefficient. In order to derive the monetary coefficient, the willingness to pay (WTP) can be estimated using the contingent valuation method (CVM), which quantifies the value of non-market goods by converting them into monetary units. WTP can be estimated based on the random utility model, which is the basic model for bivariate selection type conditional value measurement data. Statistical life value can be calculated using the estimated WTP and reduction in early mortality, and a monetary coefficient can be derived.

• Corrosion Science and Technology
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• v.21 no.6
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• pp.525-525
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• 2022

• Communications for Statistical Applications and Methods
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• v.10 no.2
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• pp.595-601
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• 2003

In this paper we propose an on line training method for classification based on least squares support vector machine. Proposed method enables the computation cost to be reduced and the training to be peformed incrementally, With the incremental formulation of an inverse matrix in optimization problem, current information and new input data can be used for building the new inverse matrix for the estimation of the optimal bias and Lagrange multipliers, so the large scale matrix inversion operation can be avoided. Numerical examples are included which indicate the performance of proposed algorithm.

• Advances in nano research
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• v.14 no.3
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• pp.225-234
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• 2023

In this study, we aim to use big data resources and statistical analysis to obtain a reliable instruction to reach high-quality and high yield agricultural yields. In this regard, soil type data, raining and temperature data as well as wheat production in each year are collected for a specific region. Using statistical methodology, the acquired data was cleaned to remove incomplete and defective data. Afterwards, using several classification methods in machine learning we tried to distinguish between different factors and their influence on the final crop yields. Comparing the proposed models' prediction using statistical quantities correlation factor and mean squared error between predicted values of the crop yield and actual values the efficacy of machine learning methods is discussed. The results of the analysis show high accuracy of machine learning methods in the prediction of the crop yields. Moreover, it is indicated that the random forest (RF) classification approach provides best results among other classification methods utilized in this study.