• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.23 no.1
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• pp.108-114
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• 2012

We propose a dispersive finite-difference time domain(FDTD) algorithm suitable for the electromagnetic analysis of the human body. In this work, the dispersion relation of the human body is modeled by a quadratic complex rational function(QCRF), which leads to an accurate and efficient FDTD algorithm. Coefficients(involved in QCRF) for various human tissues are extracted by applying a weighted least square method(WLSM), referred to as the complex-curve fitting technique. We also presents the FDTD formulation for the QCRF-based dispersive model in detail. The QCRFbased dispersive model is significantly accurate and its FDTD implementation is more efficient than the counterpart of the Cole-Cole model. Numerical examples are used to show the validity of the proposed FDTD algorithm.

• Journal of the Korea Society for Simulation
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• v.20 no.3
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• pp.79-88
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• 2011

In most existing warships combat simulation system, the tactics of a warship is manipulated by human operators. For this reason, the simulation results are restricted due to the stereotype of human operators. To deal with this, we have employed the genetic algorithm for supporting the evolutionary simulation environment. In which, the tactical decision by human operators is replaced by the human model with a rule-based chromosome for representing tactics so that the population of simulations are created and hundreds of simulation runs are continued on the basis of the genetic algorithm without any human intervention until to find emergent tactics which shows the best performance throughout the simulation. This paper proposes an evolutionary tactics generation methodology for the emergent tactics in many-to-many warship combat simulation. To do this, 3:3 warship combat simulation tests are performed.

• Journal of the Korea Society for Simulation
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• v.32 no.3
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• pp.67-74
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• 2023

A semiconductor fabrication facility(FAB) is one of the most capital-intensive and large-scale manufacturing systems which operate under complex and uncertain constraints through hundreds of fabrication steps. To improve fab performance with intuitive scheduling, practitioners have used weighted-sum scheduling. Since the determination of weights in the scheduling significantly affects fab performance, they often rely on simulation-based decision making for obtaining optimal weights. However, a large-scale and high-fidelity simulation generally is time-intensive to evaluate with an exhaustive search. In this study, we investigated three sampling methods (i.e., Optimal latin hypercube sampling(OLHS), Genetic algorithm(GA), and Decision tree based sequential search(DSS)) for the optimization. Our simulation experiments demonstrate that: (1) three methods outperform greedy heuristics in performance metrics; (2) GA and DSS can be promising tools to accelerate the decision-making process.

• Journal of The Korean Society of Inherited Metabolic disease
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• v.24 no.1
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• pp.17-25
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• 2024

Fabry disease (FD) is an X-linked lysosomal storage disorder. It is caused by mutations in the α-galactosidase A gene, which results in deficient or absent activity of α-galactosidase A (α-Gal A). This leads to a progressive accumulation of globotriaosylceramide (Gb3) in various tissues. Manifestations of Fabry disease include serious and progressive impairment of renal and cardiac function. In addition, patients experience pain, gastrointestinal disturbance, transient ischaemic attacks, and strokes. Additional effects on the skin, eyes, ears, lungs, and bones are often seen. Reduced life expectancy and deadly consequences are being caused by cardiac involvement. Chaperone therapy or enzyme replacement therapy (ERT) are two disease-specific treatments for FD. Thus, early detection of FD is critical for decreasing morbidity and mortality. Globotriaosysphingosine (lyso-Gb3) for identifying atypical FD variants and highly sensitive troponin T (hsTNT) for detecting cardiac involvement are both significant diagnostic indicators. This review aimed to offer a basic resource for the early diagnosis and update on the diagnosis of having FD. We will also provide a general diagnostic algorithm and information on ERT and its accompanying treatments.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.2
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• pp.236-244
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• 2005

In this study, we introduce a new topology of Fuzzy Polynomial Neural Networks(FPNN) that is based on fuzzy relation and evolutionally optimized Multi-Layer Perceptron, discuss a comprehensive design methodology and carry out a series of numeric experiments. The construction of the evolutionally optimized FPNN(EFPNN) exploits fundamental technologies of Computational Intelligence. The architecture of the resulting EFPNN results from a synergistic usage of the genetic optimization-driven hybrid system generated by combining rule-based Fuzzy Neural Networks(FNN) with polynomial neural networks(PNN). FNN contributes to the formation of the premise part of the overall rule-based structure of the EFPNN. The consequence part of the EFPNN is designed using PNN. As the consequence part of the EFPNN, the development of the genetically optimized PNN(gPNN) dwells on two general optimization mechanism: the structural optimization is realized via GAs whereas in case of the parametric optimization we proceed with a standard least square method-based learning. To evaluate the performance of the EFPNN, the models are experimented with the use of several representative numerical examples. A comparative analysis shows that the proposed EFPNN are models with higher accuracy as well as more superb predictive capability than other intelligent models presented previously.

• Journal of the Korea Society for Simulation
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• v.19 no.1
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• pp.143-151
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• 2010

Fingerprint classification is a step to increase the efficiency of an 1:N fingerprint recognition system and plays a role to reduce the matching time of fingerprint and to increase accuracy of recognition. It is difficult to classify fingerprints, because the ridge pattern of each fingerprint class has an overlapping characteristic with more than one class, fingerprint images may include a lot of noise and an input condition is an exceptional case. In this paper, we propose a novel approach to design a stochastic model and to accomplish fingerprint classification using a directional characteristic of fingerprints for an effective classification of various qualities. We compute the directional value by searching a fingerprint ridge pixel by pixel and extract a directional characteristic by merging a computed directional value by fixed pixels unit. The modified Markov model of each fingerprint class is generated using Markov model which is a stochastic information extraction and a recognition method by extracted directional characteristic. The weight list of classification model of each class is decided by analyzing the state transition matrixes of the generated Markov model of each class and the optimized value which improves the performance of fingerprint classification using GA (Genetic Algorithm) is estimated. The performance of the optimized classification model by GA is superior to the model before the optimization by the experiment result of applying the fingerprint database of various qualities to the optimized model by GA. And the proposed method effectively achieved fingerprint classification to exceptional input conditions because this approach is independent of the existence and nonexistence of singular points by the result of analyzing the fingerprint database which is used to the experiments.

• Journal of KIISE:Software and Applications
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• v.36 no.11
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• pp.875-890
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• 2009

Metabolimics interprets an organism as a network of functional units and an organism is represented by a metabolic pathway i.e., well-displayed graph. So a software tool for drawing pathway is necessary to understand it comprehensively. These tools have a problem that edge-crossings exponentially increase as the number of nodes grows. To apply automatic graph layout techniques to the genome-scale metabolic flow, it is very important to reduce unnecessary edge-crossing on a metabolic pathway layout. In this paper, we design and implement 2.5D metabolic pathway layout modules. Metabolic pathways are represented hierarchically by making use of the '2-layered layout algorithm' in 3D. It enhances the readability and reduces unnecessary edge-crossings by using 3D layout modules instead of 2D layout algorithms.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.3
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• pp.277-282
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• 2018

The goal of the secret message communication on the internet is to maintain invisibility and confidentiality. Digital steganography is a technique in which a secret message is inserted in a cover medium and transmitted to a destination so that a third party can not perceive the existence of the message itself. Steganography is an efficient method for ensuring confidentiality and integrity together with encryption techniques. In order to insert a secret (Hangul) message, I propose a image steganography method that the secret character is separated and converted into binary code with reference to the encryption table, the cover image is divided into two areas, and the secret message and the right l-LSB information of the second area are encrypted and crossed, concealing the k-LSB of the first region. The experimental results of the proposed method show that the PSNR value is 52.62 and the acceptable image quality level.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.5
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• pp.413-421
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• 2015

Since the first Cubesat was launched in 2003, there have been more than 230 Cubesats launched so far. Due to their small size and lightweight, Cubesats were launched by utilizing the empty space of regular launch vehicle. However, this launch method has a weakness that has been easily affecting by the schedule of major payloads. As a new solution to this problem, it has been proposed that a robot arm installed on ISS would be used to launch Cubesats. The orbits of Cubesat deployed from the ISS in various angles and directions are analyzed in this paper. We also analyze the possibility of collision between the Cubesat and ISS within the operational orbit of the CubeSat and eventually calculate the optimal angle of a robot arm, which maximizes the lifetime of Cubesat and minimizes the risk of collision between the Cubesat and ISS.

• The Transactions of the Korea Information Processing Society
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• v.6 no.4
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• pp.959-968
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• 1999

several papers have reported that parallel heuristics or hybrid approaches combining several heuristics can get better results. However, the parallelization and hybridization of any search methods on the single CPU type computer need enormous computation time. that case, we need more elegant combination method. For this purpose, we propose Fast Model of Parallel Heuristics(FMPH). FMPH is based on the island model of parallel genetic algorithms and takes local search to the elite solution obtained form each island(sub group). In this paper we introduce how can we adapt FMPH to the job-shop scheduling problem notorious as the most difficult NP-hard problem and report the excellent results of several famous benchmark problems.