• Proceedings of the KSMRM Conference
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• 2001.11a
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• pp.107-107
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• 2001

목적： 초상자성 nano-particle 조영제의 자기이완효과에 관한 out sphere 기전에 기초하여 각각의 자기장의 세기에서 T1/T2 자기이완율을 나타내는 NMRD profile을 수치적으로 simulation 하는 프로그램을 개발하고자 하였다. 대상 및 방법： 초상자성 nano-particle 조영제의 경우 초상자성 물질을 생체적합성 고분자로 표면 coating하기 때문에 상자성 조영제와는 달리 전적으로 "out sphere"기여도만을 고려하였고 또한 초상자성 물질의 경우 자기적 에너지의 크기가 매우 크기 때문에 상자성 조영제의 기전에서 사용되는 "low field"근사를 사용할 수 없으므로 Brillouin 함수로 표현되는 총자화에 대한 표현을 적용하였다. nano-particle내에 포함된 Fe 원자수에 따른 T1 및 T2 NMRD Profile과 온도에 따른 T1 및 T2 NMRD Profile 그리고 초상자성 nano-particle size에 따른 T1 및 T2 NMR Profile을 PC (CPU=800 Mhz, memory=128 MB) 환경하에서 symbolic computation tool 인 MathCad (MathCad, USA)를 사용하여 구현하였다.

• East Asian mathematical journal
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• v.16 no.2
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• pp.251-266
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• 2000

The problem of solution uniqueness to the task of determining unknown parameters of mathematical models from input-output observations is studied. This problem is known as structural identifiability problem. We offer a new approach for testing structural identifiability of linear state space models. The approach compares favorably with numerous methods proposed by other authors for two main reasons. First, it is formulated in obvious mathematical form. Secondly, the method does not involve unfeasible symbolic computations and thus allows to test identifiability of large-scale models. In case of non-identifiability, when there is a set of solutions to the task, we offer a method of computing functions of the unknown parameters which can be determined uniquely from input-output observations and later used as new parameters of the model. Such functions are called parametric functions capable of estimation. To develop the method of computation of these functions we use Lie group transformation theory. Illustrative example is given to demonstrate applicability of presented methods.

• Journal of the Society of Naval Architects of Korea
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• v.33 no.1
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• pp.161-172
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• 1996

Although conventional computer programs use efficient and precise optimization algorithms, they can not emulate the problem solving capabilities of human experts. A design optimization process involves a number of tasks which require human expertise and experience. Traditional optimization systems have concentrated on numerical aspects of a design process and have not been successful in integrating the numerical parts with human expertise. On the other hand, most knowledge-based systems focus on symbolic reasoning and have been little concerned with the numerical processes. The objective of this paper is to develop a knowledge-based multiobjective optimum design system which has the capabilities of knowledge processing and numerical computation by integrating the multiobjective optimization method and the knowledge-based system. The knowledge-based system for symbolic processing is developed. Rules for knowledge representation and the inference mechanism of the system are written in LISP. The knowledge-based multiobjective optimum design system is finally developed by integrating the multiobjective optimization method and the knowledge-based system by applying shell programming technique. The system is applied to an optimum design model of a LNG carrier in the preliminary design stage. It is found that the system well simulate design variables and objective functions of the design model.

• Journal of Korean Society for Quality Management
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• v.18 no.2
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• pp.18-24
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• 1990

The location of inspection stations is a significant component of production systems. In this paper, a prototype expert system is designed for deciding the optimal location of inspection stations. The production system is defined as a single channel of n serial operation stations. The potential inspection station can be located after any of the operation stations. Nonconforming units are generated from a compound binomial distribution with known parameters at any given operation station. Traditionally Dynamic programming, Zero-one integer programming, or Non-linear programming techniques are used to solve this problem. However a problem with these techniques is that the computation time becomes prohibitively large when t be number of potential inspection stations are fifteen or more. An expert system has the potential to solve this problem using a rule-based system to determine the near optimal location of inspection stations. This prototype expert system is divided into a static database, a dynamic database and a knowledge base. Based on defined production systems, the sophisticated rules are generated by the simulator as a part of the knowledge base. A generate-and-test inference mechanism is utilized to search the solution space by applying appropriate symbolic and quantitative rules based on input data. The goal of the system is to determine the location of inspection stations while minimizing total cost.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.49 no.7
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• pp.313-322
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• 2000

This paper presents optimal placement of minimal set of Phasor Measurement Units (PMU's) and observability analysis of the network with PMU's. In order to find a observable system, a symbolic method which directly assigns an appropriate symbol for measurement or pseudo-measurement to every entry of node-branch incidence matrix is proposed. It is much simpler and easier to analyze the observability of the network with PMU's than the conventional ones. For the optimal PMU placement problem, two approaches which are based on a modified Simulated-Annealing (SA) method and a Direct Combination method are proposed. Some case studies with IEEE sample system are made to show the performance of the proposed methods are almost alike and more effective than the conventional simulated-annealing method. It is also shown that the Direct Combination method is more effective than the modified simulated-annealing one in the sense of computation burden. The results of this study showed also that the accuracy of power system estimation and system observability can be improved the proposed PMU placements.

• Journal of the Society of Naval Architects of Korea
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• v.42 no.5 s.143
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• pp.534-541
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• 2005

Until now, Korean shipyards have accumulated a great amount of data. But they do not have appropriate tools to utilize the data in practical works. Engineering data contains experts' experience and know-how in its own. It is very useful to extract knowledge or information from the accumulated existing data by using data mining technique This paper treats an evolutionary computation based on genetic programming (GP), which can be one of the components to realize data mining. The paper deals with linear models of GP for the regression or approximation problem when given learning samples are not sufficient. The linear model, which is a function of unknown parameters, is built through extracting all possible base functions from the standard GP tree by utilizing the symbolic processing algorithm. In addition to a standard linear model consisting of mathematic functions, one variant form of a linear model, which can be built using low order Taylor series and can be converted into the standard form of a polynomial, is considered in this paper. The suggested model can be utilized as a designing tool to predict design parameters with small accumulated data.

• Journal of the Korean School Mathematics Society
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• v.10 no.1
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• pp.27-43
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• 2007

The aim of this paper is to develop a web-based learning system in order to motivate college students in the area of science and engineering to study college calculus. We designed and developed web-based contents, named MathBooster, using Mathematica, webMathematica and phpMath taking advantages of rapid computation and symbolic computation. The features of MathBooster consists of four parts: graphical representation of calculus concepts, textual illustrations of conceptual understanding, example-based step-by-step learning with phpMath, and quizzes with diagnostic feedback. After the MathBooster was practiced with engineering students, the formative evaluation was conducted with survey items composed in four categories: user responses, screen layout, practicing examples and diagnostic feedback in solving quizzes. The overall level of user satisfaction was statistically measured using SPSS. Those results indicate which parts of MathBooster are needed for future enhancement.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.8
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• pp.229-234
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• 2020

This paper presents the design and the implementation of CRESTIVE-DX, a concolic testing tool that distribute the concolic testing process over the embedded target system and the host system for efficient test generation of a target embedded program. CRESTIVE-DX conducts the execution of a target program on the target embedded system to consider possible machine-dependent behaviors of a target program execution, and conducts machine-independent parts, such as search-strategy heuristics, constraint solving, on host systems with high-speed computation unit, and coordinates their concurrent executions. CRESTIVE-DX is implemented by extending an existing concolic testing tool for C programs CREST. We conducted experiments with a test bed that consists of an embedded target system in the Arm Cortex A54 architecture and host systems in the x86-64 architecture. The results of experiments with Unix utility programs Grep, Busybox Awk, and Busybox Ed show that test input generation of CRESTIVE-DX is 1.59 to 2.64 times faster than that of CREST.

• Investigative Magnetic Resonance Imaging
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• v.7 no.1
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• pp.39-46
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• 2003

Purpose : To develop a theoretical model for magnetic relaxation behavior of the superparamagnetic nano-particle agent, which demonstrates multi-functionality such as liver- and lymp node-specificity. Based on the developed model, the computer simulation was performed to clarify the relationship between relaxation time and the applied magnetic field strength. Materials and Methods : The ultrasmall superparamagnetic iron oxide (USPIO) was encapsulated with biocompatiable polymer, to develop a relaxation model based on outsphere mechanism, which was resulting from diffusion and/or electron spin fluctuation. In addition, Brillouin function was introduced to describe the full magnetization by considering the fact that the low-field approximation, which was adapted in paramagnetic case, is no longer valid. The developed model describes therefore the T1 and T2 relaxation behavior of superparamagnetic iron oxide both in low-field and in high-field. Based on our model, the computer simulation was performed to test the relaxation behavior of superparamagnetic contrast agent over various magnetic fields using MathCad (MathCad, U.S.A.), a symbolic computation software. Results : For T1 and T2 magnetic relaxation characteristics of ultrasmall superparamagnetic iron oxide, the theoretical model showed that at low field (<1.0 Mhz), $\tau_{S1}(\tau_{S2}$, in case of T2), which is a correlation time in spectral density function, plays a major role. This suggests that realignment of nano-magnetic particles is most important at low magnetic field. On the other hand, at high field, $\tau$, which is another correlation time in spectral density function, plays a major role. Since $\tau$ is closely related to particle size, this suggests that the difference in R1 and R2 over particle sizes, at high field, is resulting not from the realignment of particles but from the particle size itself. Within normal body temperature region, the temperature dependence of T1 and T2 relaxation time showed that there is no change in T1 and T2 relaxation times at high field. Especially, T1 showed less temperature dependence compared to T2. Conclusion : We developed a theoretical model of r magnetic relaxation behavior of ultrasmall superparamagnetic iron oxide (USPIO), which was reported to show clinical multi-functionality by utilizing physical properties of nano-magnetic particle. In addition, based on the developed model, the computer simulation was performed to investigate the relationship between relaxation time of USPIO and the applied magnetic field strength.