• The Proceeding of the Korean Institute of Electromagnetic Engineering and Science
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• v.6 no.1
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• pp.17-27
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• 1995

In this paper, Finite Difference Time Domain (FDTD) method is used to analyze characteristics of the electromagnetically coupled broadband microstrip antenna, and to optimize the antenna parameters. By using short tuning stub in feedline, electromagnetically coupled microstrip antenna shows broadband (approximatcly equal 13%) characteristics, and the characteristics are varied as a function of length, width, and position of the tuning stub. Operating frequency, return loss, VSWR and input impedance are calculated by Fourier transforming the time domain results. Measurement data from fabricated electromagnetically coupled microstrip antenna are compared with FDTD results and are shown to be in good agreement. After optimization of the parameters, maximum bandwidth of about 15% is achieved.

• Journal of Electrical Engineering and Technology
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• v.2 no.1
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• pp.123-128
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• 2007

SPWPM traditional software development is surveyed and essential problems are investigated on the basis of system wireless link considerations. This paper presents the current state software planning tools for wireless LAN link optimization. The software directory is based on combination of MatLab and MapInfo software and measurement which gives the best grouping parameters to build up the software development. Among the requirements assumed, the WLAN site selections must be Line-of-sight (LOS) or near line of sight (NLOS) field strength prediction for either point to point or point to multi points. The results obtainable the out put of the program include two-dimensional (2D) and three dimensional (3D) plots for creating the link; design parameters through GUI representing the height and location for each antenna is depending on K-factor of the area and transmit antenna location.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.8
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• pp.1796-1803
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• 2013

In this paper, a novel particle swarm optimization method based on IE3D is used to design a mobile communication microstrip patch antenna. The aim of the paper is to design and fabricate an inset fed rectangular microstrip antenna and study the effect of antenna dimensions length (L), width (W) and substrate parameters relative dielectric constant (${\varepsilon}r$), substrate thickness on radiation parameters of band width. PSO algorism was applied to IE3D, low resistance against, band width and advantage, were improved.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.7 no.1
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• pp.12-23
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• 1995

Currents driven by irregular waves are modelled using numerical model with various empirical relations improved. Kitaigorodskii's equilibrium equation is refined to account for shoaling effect and used for checking the breaking condition. In order to compute the bottom friction realistically. equivalent roughness blights are estimated considering the ripple shape and bed load transport which may be significant the surf zone. Two sets of equations are employed to evaluate the ripple shape: one is suggested by Nielsen and the other by Madsen and Rogengaus. Both equations give similar shape of ripples. but Madsen et al. give lower value of ripple factor than Swart suggesting that the equivalent roughness becomes relatively small. Optimization technique is used to determine the proper values for the empirical parameters of $\kappa$-ι equations, and the longshore current velocity is computed using the values of empirical parameters determined by the optimization technique.

• 한국방재학회:학술대회논문집
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• 2008.02a
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• pp.723-726
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• 2008

It is not always easy to estimate the parameters in hydrologic models due to insufficient hydrologic data when hydraulic structures are designed or water resources plan are established, uncertainty analysis, therefore, are inevitably needed to examine reliability for the estimated results. With regard to this point, this study applies a Bayesian Markov Chain Monte Carlo scheme to the NWS-PC rainfall-runoff model that has been widely used, and a case study is performed in Soyang Dam watershed in Korea. The NWS-PC model is calibrated against observed daily runoff, and thirteen parameters in the model are optimized as well as posterior distributions associated with each parameter are derived. The Bayesian Markov Chain Monte Carlo shows a improved result in terms of statistical performance measures and graphical examination. The patterns of runoff can be influenced by various factors and the Bayesian approaches are capable of translating the uncertainties into parameter uncertainties. One could provide against an expected runoff event by utilizing information driven by Bayesian methods. Therefore, the rainfall-runoff analysis coupled with the uncertainty analysis can give us an insight in evaluating flood risk and dam size in a reasonable way.

• Transactions of the Korean Society of Automotive Engineers
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• v.14 no.5
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• pp.186-194
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• 2006

Traffic accident involved with the vulnerable pedestrian is one of the significant concerns, which has higher possibility of fatality than any other accident types. Worldwide significant efforts have been made to establish a vehicle safety regulation, which is internationally agreed, in order to reduce pedestrian casualties in pedestrian-vehicle collisions. One of the key issues in deriving the regulation is how to effectively select the parameter values associated with the regulation. This study firstly develops a method to optimize parameter values. An optimizing problem in terms of maximizing safety benefits, which are life-saving effects by the regulation, is formulated. Extensive actual accident data analysis and simulations are conducted to establish several statistical models to be used in the proposed optimization procedure. A set of parameter values that can produce maximizing life-saving effects is presented as the outcome of this study. It is expected that the proposed method would play a significant role in determining parameters as a decision support tool toward ensuring better pedestrian safety.

• Journal of the Korean Society for Precision Engineering
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• v.11 no.4
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• pp.138-147
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• 1994

Performance management of computer networks is intended to improve a given network performance in order for more efficient information exchange between subsystems of an integrated large-scale system. Improtance of performance management is growing as many function of the large- scale system depend on the quality of communication services provided by the network. The role of performance management is to manipulate the adjustable protocol parameters on line so that the network can adapt itself to a dynamic environment. This can be divided into two subtasks : performance evaluation to find how changes in protocol parameters affect the network performance and decision making to detemine the magnitude and direction of parameter adjustment. This paper is the second part of the two papers focusing on conceptual design, development, and evaluation of performance management for token bus networks. This paper specifically deals with the task of decision making which utilizes the principles of stochastic optimization and learning automata. The developed algorithm can adjuxt four timer settings of a token bus protocol based on the result of performance evaluation. The overall performance management has been evaluated for its efficacy on a network testbed.

• Nuclear Engineering and Technology
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• v.39 no.4
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• pp.337-348
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• 2007

A fuzzy neural network model is presented to predict residual stress for dissimilar metal welding under various welding conditions. The fuzzy neural network model, which consists of a fuzzy inference system and a neuronal training system, is optimized by a hybrid learning method that combines a genetic algorithm to optimize the membership function parameters and a least squares method to solve the consequent parameters. The data of finite element analysis are divided into four data groups, which are split according to two end-section constraints and two prediction paths. Four fuzzy neural network models were therefore applied to the numerical data obtained from the finite element analysis for the two end-section constraints and the two prediction paths. The fuzzy neural network models were trained with the aid of a data set prepared for training (training data), optimized by means of an optimization data set and verified by means of a test data set that was different (independent) from the training data and the optimization data. The accuracy of fuzzy neural network models is known to be sufficiently accurate for use in an integrity evaluation by predicting the residual stress of dissimilar metal welding zones.

• Smart Structures and Systems
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• v.24 no.2
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• pp.233-242
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• 2019

In this paper, an inverse approach based on uniform load surface (ULS) is presented for structural damage localization and quantification. The ULS is excellent approximation for deformed configuration of a structure under distributed unit force applied on all degrees of freedom. The ULS make use of natural frequencies and mode shapes of structure and in mathematical point of view is a weighted average of mode shapes. An objective function presented to damage detection is discrepancy between the ULS of monitored structure and numerical model of structure. Solving this objective function to find minimum value yields damage's parameters detection. The teaching-learning based optimization algorithm has been employed to solve inverse problem. The efficiency of present damage detection method is demonstrated through three numerical examples. By comparison between proposed objective function and another objective function which make use of natural frequencies and mode shapes, it is revealed present objective function have faster convergence and is more sensitive to damage. The method has good robustness against measurement noise and could detect damage by using the first few mode shapes. The results indicate that the proposed method is reliable technique to damage detection in structures.

• Progress in Superconductivity and Cryogenics
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• v.23 no.3
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• pp.41-44
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• 2021

We developed an optimization process of the pulsed laser deposition method to grow epitaxial CeCoIn₅ thin films on MgF₂ substrates. The effects of different deposition parameters on film growth were extensively studied by analyzing the measured X-ray diffraction patterns. All the deposited films contained small amounts of CeIn₃ impurity phase and misoriented CeCoIn₅, for which the c-axis of the unit cell is perpendicular to the normal vector of the substrate surface. The deposition temperature, target composition, laser energy density, and repetition rate were found effective in the formation of (00l)-oriented CeCoIn₅ as well as the undesired phases such as CeIn₃, misoriented CeCoIn₅ along the (112) and (h00). Our results provide a set of deposition parameters that produce high-quality epitaxial CeCoIn₅ thin films with sufficiently low amounts of impurity phases and can serve as a reference for future studies to optimize the deposition process further.