• Proceedings of the Korean Information Science Society Conference
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• 2005.11a
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• pp.721-723
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• 2005

본 논문에서는 영상 기반 항해를 위하여 최적의 영상 샘플링을 획득하기 위한 영상 샘플링 알고리즘을 제안한다. 이를 위해 초기 과다 샘플링 된 영상열의 입력으로부터 장면 전역에 걸쳐 적절한 렌더링 품질을 보장하는 최소의 샘플링을 선택하는 감소 샘플링(decremental sampling)의 접근 방법을 기반으로 본 문제를 Set Covering 문제로 공식화한다. 각 시점으로부터 최상의 영상 품질을 보장하는 영역을 3D 와핑 알고리즘을 사용하여 포함 영역으로 표현하여, 이렇게 표현된 Set Covering 문제는 유전 알고리즘을 사용하여 최적화 문제로 설계한다. 실험 결과 본 논문에서 제안한 방법을 통해 최적 해를 구함으로서 만족할 만한 영상 기반 항해의 결과를 얻을 수 있었다.

• The Transactions of the Korea Information Processing Society
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• v.6 no.4
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• pp.952-958
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• 1999

This paper presented the application of GAs as a means of finding optimal solutions over a parameter space in the controller design for a fuzzy control system. The performance can involve a weighted combination of various performance characteristics such as rise-time, settling-time, settling-time, overshoot. The results obtained here are compared with those for a traditional design obtained using the root-locus method. In contrast to traditional methods, the GA-based method does not require the usual mathematical processess or mathematical model of the system. In this paper, the Ga-based Fuzzy control system combining Fuzzy control theory with the GA, that is known to be very effective in the optimization problem, will be proposed The effectiveness of the proposed control system will be demonstrated by computer simulations using task tracking position system in stable and unstable linear systems. It is shown that the GA-based controller is better than the traditional controller used It stable and unstable linear systems.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.8
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• pp.754-759
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• 2001

In this paper, we propose a TSK(Takagi-Sugeno-Kang)-type fuzzy classifier using PCA(Principal Component Analysis), FCM(Fuzzy c-Means) clustering, ANFIS(Adaptive Neuro-Fuzzy Inference System) and hybrid GA(Genetic Algorithm). First, input data is transformed to reduce correlation among the data components by PCA. FCM clustering is applied to obtain a initial TSK-type fuzzy classifier. Parameter identification is performed by AGA(Adaptive GA) and RLSE(Recursive Least Square Estimate). Finally, we applied the proposed method to Iris data classificationl problems and obtained a better performance than previous works.

• Journal of the Korean Society of Propulsion Engineers
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• v.17 no.4
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• pp.10-15
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• 2013

For design optimization, engineers should require the accurate information of design space and then explore the design space and carry out optimization. Recently, the total design framework, based on design of experiments and optimization, is widely used in industry areas to explore the design space above all. For optimizing turbofan engine design point, the response surface model is constructed by using the 7 level orthogonal array which satisfies the statistical uniformity and orthogonality and gets the dense design space information. The multi-objective genetic algorithm is used to find the optimal solution within the given constraints for finding global optimal one in response surface model. The optimal solution from response surface model is verified with GasTurb simulation result.

• The Journal of the Acoustical Society of Korea
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• v.15 no.2
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• pp.21-32
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• 1996

The performance of the energy density control algorithm for controlling a broadband noise is evaluated in a one-dimensional enclosure. To avoid noncausality problem of a control filter, which often happens in a frequency domain optimization, analyses presented in this paper are undertaken in the time domain. This approach provides the form of the causally constrained optimal controller. Numerical results are presented to predict the performance of the active noise control system, and indicate that imp개ved global attenuation of the broadband noise can be achieved by minimizing the energy density, rather than the squared pressure. It is shown that minimizing the energy density at a single location yields global attenuation results that are comparable to minimizing the potential energy. Furthermore, unlike the squared pressure control, the energy density control does not demonstrate any dependence on the error sensor location for this one-dimensional field. A practical implementation of the energy-based control algorithm is presented. Results show that the energy density control can be implemented using the two sensor technique with a tolerable margin of performance degradation.

• Journal of the Institute of Convergence Signal Processing
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• v.12 no.4
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• pp.341-347
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• 2011

This paper presents the performance evaluation. optimal design. and complex obstacle detection of an overlapped ultrasonic sensor ring by introducing a new concept of effective beam width. It is assumed that a set of ultrasonic sensors of the same type are arranged along a circle of nonzero radius at regular spacings with their beams overlapped. First, the global positional uncertainty of an overlapped ultrasonic sensor ring is expressed by the average value of local positional uncertainty over the entire obstacle detection range. The effective beam width of an overlapped ultrasonic sensor ring is assessed as the beam width of a single ultrasonic sensor having the same amount of global positional uncertainty, from which a normalized obstacle detection performance index is defined. Second. using the defined index, the design parameters of an overlapped ultrasonic sensor ring are optimized for minimal positional uncertainty in obstacle detection. For a given number of ultrasonic sensors, the optimal radius of an overlapped ultrasonic sensor ring is determined, and for a given radius of an overlapped ultrasonic sensor ring, the optimal number of ultrasonic sensors is determined. Third, the decision rules of positional uncertainty zone for multiple obstacle detection are provided based on the inequality relationships among obstacle distances by three adjacent ultrasonic sensors. Using the provided rules, the obstacle outline detection is performed in a rather complex environment consisting of several obstacles of different shapes.

• Journal of Korean Society of Transportation
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• v.25 no.6
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• pp.129-140
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• 2007

The planning procedure of a transit operation consists of design, operation, and evaluation according to the research characteristics. There are some review studies on the operation and evaluation procedure, but the research on the design procedure has not yet been organized systematically. In this study, the research on transit system design was reviewed and the model structure and its solution method were arranged. The decision variables of the design procedure are network structure, line spacing or position, stop spacing, dispatching headway, and fleet size. In the analytical research on design procedure, system total cost is generally used as the objective function. System total cost is comprised of user cost, which is the sum of user access, waiting, and travel cost, and operating cost. Total cost of the transit system, used as the objective function, has the unique minimum because it is differentiable. There is a certain decision variable that makes the derivative of the objective function equal to zero and the second derivative of the objective function is positive. Therefore the decision variable that makes the first derivative of the objective function zero is the optimum that minimizes the objective function, and each of the cost components of the objective function become the same. This study is expected to help understanding about the research on the design procedure of transit operation planning and to help be a catalyst for relevant research.

• Journal of KIISE:Software and Applications
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• v.30 no.1_2
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• pp.73-80
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• 2003

The Java programming language is designed for developing effective applications in a heterogeneous network environment. Major problem in Java is its performance. many attractive features of Java make the development of software easy, but also make it expensive to support ; applications written in Java are often much slower than their counterparts written in C or C++. To use Java`s attractive features without the performance penalty, sophisticated optimizations and runtime systems are required. Optimising Java bytecode has several advantages. First, the bytecode is independent of any compiler that is used to generate it. Second, the bytecode optimization can be performed as a pre=pass to Just-In-Time(JIT) compilation. Many attractive features of Java make the development of software easy, but also make it expensive to support. The goal of this work is to develop automatic construction of code optimizer for Java bytecode. We`ve designed and implemented a Bytecode Optimizer that performs the peephole optimization, bytecode-specific optimization, and method-inlining techniques. Using the Classfile optimizer, we see up to 9% improvement in speed and about 20% size reduction in Java class files, when compared to average code using the interpreter alone.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.35C no.12
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• pp.85-98
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• 1998

This paper proposes a new design method of neuro-FLC by the Lamarckian co-adaptation scheme that incorporates the backpropagation learning into the GA evolution in an attempt to find optimal design parameters (fuzzy rule base and membership functions) of application-specific FLC. The design parameters are determined by evolution and learning in a way that the evolution performs the global search and makes inter-FLC parameter adjustments in order to obtain both the optimal rule base having high covering value and small number of useful fuzzy rules and the optimal membership functions having small approximation error and good control performance while the learning performs the local search and makes intra-FLC parameter adjustments by interacting each FLC with its environment. The proposed co-adaptive design method produces better approximation ability because it includes the backpropagation learning in every generation of GA evolution, shows better control performance because the used COG defuzzifier computes the crisp value accurately, and requires small workspace because the optimization procedure of fuzzy rule base and membership functions is performed concurrently by an integrated fitness function on the same fuzzy partition. Simulation results show that the Lamarckian co-adapted FLC produces the most superior one among the differently generated FLCs in all aspects such as the number of fuzzy rules, the approximation ability, and the control performance.

• Journal of Korean Society of Steel Construction
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• v.24 no.6
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• pp.671-682
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• 2012

The use of sinusoidal corrugated web girder for the box-type girders and gable steel main frames has recently been increasing very much. The reasons are that the thin web of the girder affords a significant weight reduction compared with rolled beam and welded built-up girder, and that corrugation prevents the buckling failure of the web. Improvements of the automatic fabrication process makes mass production of the corrugated web and unit possible, and applications of this girder have been extended considerably. Thus, the research for the optimum design processer considering the production data is needed practically. For doing this research, we develope the discrete optimum structural design program in consideration of production list data for the research, and the program apply to the single girder under the uniform load and the concentrated load as numerical example. We consider objective function as minimum weight of the girder, and use slenderness ratio, stress of flanges and corrugated web, and the girder deflection as the constraint functions. And also the Genetic Algorithms is adopted to search the global minimum point by using the production list as a discrete design variable. Finally, to verify the optimality of the design, we conduct a comparison of the results of the discrete optimum design with those of the continuous one, and also analyze the characteristics of the optimum cross-section.