• Structural Engineering and Mechanics
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• 제41권2호
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• pp.231-242
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• 2012

This research work aims to develop an optimal design using Finite Element (FE) and Genetic Algorithm (GA) methods to replace the traditional concrete and timber material by a Synthetic Polyurethane fibre glass composite material in railway sleepers. The conventional timber railway sleeper technology is associated with several technical problems related to its durability and ability to resist cutting and abrading action of the bearing plate. The use of pre-stress concrete sleeper in railway industry has many disadvantages related to the concrete material behaviour to resist dynamic stress that may lead to a significant mechanical damage with feasible fissures and cracks. Scientific researchers have recently developed a new composite material such as Glass Fibre Reinforced Polyurethane (GFRP) foam to replace the conventional one. The mechanical properties of these materials are reliable enough to help solving structural problems such as durability, light weight, long life span (50-60 years), less water absorption, provide electric insulation, excellent resistance of fatigue and ability to recycle. This paper suggests appropriate sleeper design to reduce the volume of the material. The design optimization shows that the sleeper length is more sensitive to the loading type than the other parameters.

• 한국농공학회논문집
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• 제56권4호
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• pp.9-19
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• 2014

The objective of this study was to evaluate of the Tank model in simulating runoff discharge from rural watershed in comparison to the SWAT (Soil and Water Assessment Tool) model. The model parameters of SWAT was calibrated by the shuffled complex evolution-university Arizona (SCE-UA) method while Tank model was calibrated by genetic algorithm (GA) and validated. Four dam watersheds were selected as the study areas. Hydrological data of the Water Management Information System (WAMIS) and geological data were used as an input data for the model simulation. Runoff data were used for the model calibration and validation. The determination coefficient ($R^2$), root mean square error (RMSE), Nash-Sutcliffe efficiency index (NSE) were used to evaluate the model performances. The result indicated that both SWAT model and Tank model simulated runoff reasonably during calibration and validation period. For annual runoff, the Tank model tended to overestimate, especially for small runoff (< 0.2 mm) whereas SWAT model underestimate runoff as compared to observed data. The statistics indicated that the Tank model simulated runoff more accurately than the SWAT model. Therefore the Tank model could be a good tool for runoff simulation considering its ease of use.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 하계종합학술대회 논문집 Ⅲ
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• pp.1303-1306
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• 2003

In this paper, In this paper, we modeled a virtual life(VL) that react to the user's action according to its own behavioral characteristics and grows itself. We established some conditions with which such a VL is designed. Genetic Algorithm is used for the growth process that changes the VL's properties. In this process, the parameter values of the VL's properties are encoded as one chromosome, and the GA operations change this chromosome. The VL's reaction to the user's action is determined by these properties as well as the general expectation of each reaction. These properties are evaluated through 5 fitness measures so as to deal with multi-objective criteria. Here, we present the simulation of the growth process, and show some experimental results.

• 한국전산유체공학회지
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• 제19권4호
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• pp.14-19
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• 2014

This study conducts shape optimization of rib turbulator on the internal cooling passage that has triangular cross-section of high pressure turbine nozzle. During optimization, various types of rib turbulator including angled, V-shaped, A-shaped and angled rib with intersecting rib are considered. Each type of rib turbulator is parameterized with attack angle(s), rib height, spacing ratio and bending/intersecting location. For optimization, Design of Experiment (DOE) and Kriging surrogate model are used to utilize computational resource more efficiently and Genetic Algorithm (GA) is used to search the optimum points. As a result, Pareto front of each type of rib turbulator with friction factor that relates to pressure drop in cooling passage and spatially averaged Nusselt number that relates to heat transfer on the wall is drawn and optimum points on the Pareto front are suggested.

• 상하수도학회지
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• 제30권2호
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• pp.179-185
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• 2016

In this study, the RDII predictions were compared using two methodologies, i.e., the RTK-based and regression methods. Long-term (1/1/2011~12/31/2011) monitoring data, which consists of 10-min interval streamflow and the amount of precipitation, were collected at the domestic study area (1.36 km2 located in H county), and used for the construction of the RDII prediction models. The RTK method employs super position of tri-triangles, and each triangle (called, unit hydrograph) is defined by three parameters (i.e., R, T and K) determined/optimized using Genetic Algorithm (GA). In regression method, the MovingAverage (MA) filtering was used for data processing. Accuracies of RDII predictions from these two approaches were evaluated by comparing the root mean square error (RMSE) values from each model, in which the values were calculated to 320.613 (RTK method) and 420.653 (regression method), respectively. As a results, the RTK method was found to be more suitable for RDII prediction during extreme rainfall event, than the regression method.

• Journal of Electrical Engineering and Technology
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• 제4권2호
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• pp.185-193
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• 2009

This paper presents a methodology for photovoltaic (PV) system allocation in distribution systems using a discrete particle swarm optimization (DPSO). The PV allocation problem is in the category of mixed integer nonlinear programming and its formulation may include multi-valued dis-crete variables. Thus, the PSO requires a scheme to deal with multi-valued discrete variables. This paper introduces a novel multi-level quantization scheme using a sigmoid function for discrete particle swarm optimization. The technique is employed to a standard PSO architecture; the same velocity update equation as in continuous versions of PSO is used but the particle's positions are updated in an alternative manner. The set of multi-level quantization is defined as integer multiples of powers-of-two terms to efficiently approximate the sigmoid function in transforming a particle's position into discrete values. A comparison with a genetic algorithm (GA) is performed to verify the quality of the solutions obtained.

• 대한산업공학회지
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• 제32권3호
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• pp.172-179
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• 2006

Over the past few years, a considerable number of studies have been conducted on modeling the bargaining game using artificial agents on within-model interaction. However, very few attempts have been made at study on between-model interaction. This paper investigates the interaction and co-evolutionary process among heterogeneous artificial agents in the bargaining game. We present two kinds of the artificial agents participating in the bargaining game. They play some bargaining games with their strategies based on genetic algorithm (GA) and reinforcement learning (RL). We compare agents' performance between two agents under various conditions which are the changes of the parameters of artificial agents and the maximal number of round in the bargaining game. Finally, we discuss which agents show better performance and why the results are produced.

• Structural Engineering and Mechanics
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• 제46권3호
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• pp.353-370
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• 2013

This paper presents a new method to study the impact factor of an old bridge based on the model updating technique. Using the genetic algorithm (GA) by minimizing an objective function of the residuals between the measured and predicted responses, the bridge and vehicle coupled vibration models were updated. Based on the displacement relationship and the interaction force relationship at the contact patches, the vehicle-bridge coupled system can be established by combining the equations of motion of both the bridge and vehicles. The simulated results show that the present method can simulate precisely the response of the tested bridge; compared with the other bridge codes, the impact factor specified by the bridge code of AASHTO (LRFD) is the most conservative one, and the value of Chinese highway bridge design code (CHBDC) is the lowest; for the large majority of old bridges whose road surface conditions have deteriorated, calculating the impact factor with the bridge codes cannot ensure the reliable results.

• Journal of the Optical Society of Korea
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• 제11권4호
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• pp.162-172
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• 2007

Scanning Laser Optical Tweezers(SLOT) is an optical instrument frequently employed on a microscope with laser being delivered through its various ports. In most SLOT systems, a mechanical tilt stage with a mirror on top is used to dynamically move the laser focal point in two-dimensions. The focal point acts as a tweezing spot, trapping nearby microscopic objects. By adding a mechanical translational stage with a lens, SLOT can be expanded to work in three-dimensions. When two mechanical stages operate together, the focal point can address a closed three-dimensional volume that we call a workspace. It would be advantageous to have a large workspace since it means one can trap and work on multiple objects without interruptions, such as translating the microscope stage. However, previous studies have paid less consideration of the volumetric size of the workspace. In this paper, we propose a new method for designing a SLOT such that its workspace is maximized through optimization. The proposed method utilizes a matrix based ray tracing method and genetic algorithm(GA). To demonstrate the performance of the proposed method, experimental results are shown.

• Molecular & Cellular Toxicology
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• 제5권1호
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• pp.14-22
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• 2009

In vitro cytotoxicity of 23 alkyl phenols (APs) on human cervical cancer cell lines (HeLa) was determined using the lactate dehydrogenase (LDH) cytotoxicity assay. Two different sets of descriptors were used to construct the calibration model based on Genetic Algorithm-Multiple Linear Regression (GA-MLR) based on the experimental data. A statistically robust Structure-Activity Relationships (QSAR) model was achieved ($R^2$=95.05%, $Q^2_{LOO}$=91.23%, F=72.02 and SE= 0.046) using three Dragon descriptors based on Me (0D-Constitutional descriptor), BELp8 (2D-Burden eigenvalue descriptor) and HATS8p (3D-GETAWAY descriptor). However, external validation could not fully prove its validity of the selected QSAR in characterization of the cytotoxicity of APs towards HeLa cells. Nevertheless, the cytotoxicity profiles showed a finding that 4-n-octylphenol (4-NOP), 4-tert-octyl-phenol (4-TOP), 4-n-nonylphenol (4-NNP) had a more potent cytotoxic effect than other APs tested, inferring that increased length and molecular bulkiness of the substituent had important influence on the LDH cytotoxicity.