• Journal of Environmental Health Sciences
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• v.43 no.1
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• pp.77-86
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• 2017

Objectives: The purpose of this study was to compare permeation characteristics in three skin types using oil-soluble benzoic acid and water-soluble caffeine after method condition optimization based on OECD guideline 428. Methods: A Franz diffusion cell, a reliable alternative method for skin permeation, was used. One-milliliter samples were taken and immediately replaced with fresh solution in the receptor chamber at regular time intervals (1, 2, 4, 7, 10 and 24 hr). The amount of test substances was measured by LC-MS/MS. Results: The permeation rate increased dose-dependently, and the permeation orders were $KeraSkin^{TM}$ > hairless mouse full skin > human cadaver epidermis for skin types, and benzoic acid solution > caffeine solution > benzoic acid cream > caffeine cream for type of test materials. Conclusion: According to the definitions of Marzulli, benzoic acid and caffeine would be classified as 'fast' and 'moderate' compared with the permeation of other chemical species. The setting conditions and permeation characteristics performed in this study are expected to contribute to future permeation studies.

• Journal of the Korean Association of Geographic Information Studies
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• v.8 no.3
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• pp.84-95
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• 2005

This paper presents solution heuristics to solving optimal multiple-viewpoint location problems that are based on topographic features. The visibility problem is to maximise the viewshed area for a set of viewpoints on digital elevation models (DEM). For this analysis, five areas are selected, and fundamental topographic features (peak, pass, and pit) are extracted from the DEMs of the study areas. To solve the visibility problem, at first, solution approaches based on the characteristics of the topographic features are explored, and then, a benchmark test is undertaken that solution performances of the solution methods, such as computing times, and visible area sizes, are compared with the performances of traditional spatial heuristics. The feasibility of the solution methods, then, are discussed with the benchmark test results. From the analysis, this paper can conclude that fundamental topographic features based solution methods suggest a new sight of visibility analysis approach which did not discuss in traditional algorithmic approaches. Finally, further research avenues are suggested such as exploring more sophisticated selection process of topographic features related to visibility analysis, exploiting systematic methods to extract topographic features, and robust spatial analytical techniques and optimization techniques that enable to use the topographic features effectively.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.38 no.12
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• pp.1403-1413
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• 2014

Structural optimization is widely accepted in industrial fields. Structural optimization pursues improved performance of the structures. Recently, structural optimization is actively utilized due to the well-developed commercial design software systems. Three popular commercial structural optimization systems are investigated and compared. They are MSC.Nastran, Genesis and OptiStruct. The performance of the systems is analyzed based on the quality of the optimum solution and the computational time. Linear static response size, shape and topology optimizations are explored and compared with some test examples. For fair comparison, the systems are run in the same environment and the optimization parameters affecting the performance are unified. The optimization results are analyzed and the performances and characteristics of each software system are discussed.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.6 s.177
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• pp.1529-1539
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• 2000

A newly developed optimization method which uses the genetic algorithm combined with the sensitivity analysis is presented in this paper. The genetic algorithm is a probabilistic method, searching the optimum at several points simultaneously, requiring only the values of the object and constraint functions. It has therefore more chances to find global solution and can be applied various problems. Nevertheless, it has such shortcomings that even it approaches the optimum rapidly in the early stage, it slows down afterward and it can't consider the constraints explicitly. It is only because it can't search the local area near the current points. The traditional method, on the other hand, using sensitivity analysis is of great advantage in searching the near optimum. Thus the combination of the two techniques makes use of the individual advantages, that is, the superiority both in global searching by the genetic algorithm and in local searching by the sensitivity analysis. Application of the method to the several test functions verifies that the method suggested is very efficient and powerful to find the global solutions, and that the constraints can be considered properly.

• Computers and Concrete
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• v.21 no.4
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• pp.441-449
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• 2018

FE models for complex or large-scaled structures that need detailed modeling of structural components are usually constructed using commercial analysis softwares. Updating of such FE model by conventional sensitivity-based methods is difficult since repeated computation for perturbed parameters and manual calculations are needed to obtain sensitivity matrix in each iteration. In this study, an FE model updating procedure avoiding such difficulties by using response surface (RS) method and a Pareto-based multiobjective optimization (MOO) was formulated and applied to FE models constructed with a commercial analysis package. The test building is a low-rise reinforced concrete building that has been seismically retrofitted. Dynamic properties of the building were extracted from vibration tests performed before and after the seismic retrofits, respectively. The elastic modulus of concrete and masonry, and spring constants for the expansion joint were updated. Two RS functions representing the errors in the natural frequencies and mode shape, respectively, were obtained and used as the objective functions for MOO. Among the Pareto solutions, the best compromise solution was determined using the TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) procedure. A similar task was performed for retrofitted building by taking the updating parameters as the stiffness of modified or added members. Obtained parameters of the existing building were reasonably comparable with the current code provisions. However, the stiffness of added concrete shear walls and steel section jacketed members were considerably lower than expectation. Such low values are seemingly because the bond between new and existing concrete was not as good as the monolithically casted members, even though they were connected by the anchoring bars.

• Journal of the Korean Operations Research and Management Science Society
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• v.19 no.1
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• pp.145-152
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• 1994

This paper deals with an economic design of acelerated life test under constant stresses where failure times are exponentially distributed. In this case the optimization criterion is the information amount per unit cost. Fisher's information matrix of exponential distribution's parameters and expected cost considering fixed and variable costs are obtained. The decision variable is the censoring time in the model. In the 2-level constant stress case, it is proved that the optimal solution exists and is unique under some condition. Numerical examples are also included.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.114-116
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• 2015

This paper presents a Stochastic Time-Cost Tradeoff analysis system (STCT) that identifies optimal construction methods for activities, hence reducing the project completion time and cost simultaneously. It makes use of schedule information obtained from critical path method (CPM), applies alternative construction methods data obtained from estimators to respective activities, computes an optimal set of genetic algorithm (GA) parameters, executes simulation based GA experiments, and identifies near optimal solution(s). A test case verifies the usability of STCT.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.109-110
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• 2015

This paper presents a computational method that identifies an exact set of optimal overlap rates between critical activities to meet job site specific needs by using rework cost-slope. The procedures to compute the exact solution are provided in peudocode algorithm. The method is coded into Exact Concurrent Construction Scheduling system that allows practitioners to make more informed decision in accordance with the site-specific condition involved in the overlapping of critical activities. Test cases verify the validity of the computational method and the usability of the system.

• The KIPS Transactions:PartB
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• v.16B no.4
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• pp.319-326
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• 2009

PSO(Particle Swarm Optimization) is an optimization algorithm in which simple particles search an optimal solution using shared information acquired through their own experiences. PSO applications are so numerous and diverse. Lots of researches have been made mainly on the parameter settings, topology, particle's movement in order to achieve fast convergence to proper regions of search space for optimization. In standard PSO, since each particle uses only information of its and best neighbor, swarm does not explore diverse regions and intended to premature to local optima. In this paper, we propose a new particle's movement strategy in order to explore diverse regions of search space. The strategy is that each particle moves according to relative weights of several better neighbors. The strategy of exploring diverse regions is effective and produces less local optimizations and accelerating of the optimization speed and higher success rates than standard PSO. Also, in order to raise success rates, we propose a strategy for checking whether swarm falls into local optimum. The new PSO algorithm with these two strategies shows the improvement in the search speed and success rate in the test of benchmark functions.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.41 no.7
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• pp.524-531
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• 2013

This work aims at developing a RTB (Rotor Track and Balance) system to alleviate imbalances originating from various sources encountered during blade manufacturing process and environmental factors. The analytical RTB model is determined based on the linear regression analysis to relate the RTB adjustment parameters and their track and vibration results. The model is validated using the flight test data of a full helicopter. It is demonstrated that the linearized model has been correlated well with the test data. A hybrid optimization problem is formulated to find the best solution of the RTB adjustment parameters using the genetic algorithm combined with the PSO (Particle Swarm Optimization) algorithm. The optimization results reveal that both track deviations and vibration levels under various flight conditions become decreased within the allowable tolerances.