• Proceedings of the Computational Structural Engineering Institute Conference
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• 2000.04b
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• pp.449-457
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• 2000

The paper describes the study of global approximate optimization utilizing soft computing techniques such as genetic algorithms (GA's), neural networks (NN's), and fuzzy inference systems(FIS). GA's provide the increasing probability of locating a global optimum over the entire design space associated with multimodality and nonlinearity. NN's can be used as a tool for function approximations, a rapid reanalysis model for subsequent use in design optimization. FIS facilitates to handle the quantitative design information under the case where the training data samples are not sufficiently provided or uncertain information is included in design modeling. Properties of soft computing techniques affect the quality of global approximate model. Evolutionary fuzzy modeling (EFM) and adaptive neuro-fuzzy inference system (ANFIS) are briefly introduced for structural optimization problem in this context. The paper presents the success of EFM depends on how optimally the fuzzy membership parameters are selected and how fuzzy rules are generated.

• Proceedings of the Korea Electromagnetic Engineering Society Conference
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• 2005.11a
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• pp.153-156
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• 2005

This paper concerns an efficient iterative approach for eliminating coherent interference signals in linearly constrained adaptive arrays. The Alternate Mainbeam Nulling Algorithm[1] is implemented iteratively to find an optimum weight vector. The convergence parameters in the unit gain and null constraints are calculated using steepest descent method with gradient estimation. The nulling performance of the proposed method is compared with that of conventional ones. It is shown that the proposed method performs better than conventional ones when the power of the coherent signals is large compared with a desired signal. Also, it performs consistently well for more number of interferences.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.16 no.8
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• pp.745-757
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• 1991

In this paper, the theoretical convergence property of the individual tap LMS algorithm for equaliz action if analyzed, and the pefomances over seeral multipath time vaing mobile radio channels are investigaed. The individual tap adjusting method of the tapped-elay line equalizer using LMS algorithm is proved to have Wiener optimum solution. It has more rapid convergence speed and lowe bit error rates than conventional Tdl LMS and gradient lattice equlizer in time invariant or time variant multipath channels.

• Journal of Electrical Engineering and Technology
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• v.11 no.2
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• pp.499-507
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• 2016

Medical imaging techniques such as Magnetic Resonance Imaging (MRI), Computed Tomography (CT) and Ultrasound (US) produce a large amount of digital medical images. Hence, compression of digital images becomes essential and is very much desired in medical applications to solve both storage and transmission problems. But at the same time, an efficient image compression scheme that reduces the size of medical images without sacrificing diagnostic information is required. This paper proposes a novel threshold-based medical image compression algorithm to reduce the size of the medical image without degradation in the diagnostic information. This algorithm discusses a novel type of thresholding to maximize Compression Ratio (CR) without sacrificing diagnostic information. The compression algorithm is designed to get image with high optimum compression efficiency and also with high fidelity, especially for Peak Signal to Noise Ratio (PSNR) greater than or equal to 36 dB. This value of PSNR is chosen because it has been suggested by previous researchers that medical images, if have PSNR from 30 dB to 50 dB, will retain diagnostic information. The compression algorithm utilizes one-level wavelet decomposition with threshold-based coefficient selection.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2001.10a
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• pp.185-189
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• 2001

In order to prevent the production defects the optimum design of product, jig and fixture putting in the field is very significant manufacturing method. Drilling Jig is the device according to industrial demand for multi manufacturing products on the growing at alarming rate. In the field of design and making for machine tool working, welding, assembling with jig and fixture for mass production is a specific division. They require analysis of many kinds of important factors, theory and practice of machine tool operating process and jig & fixture structure, machining condition for tool making, tool materials, heat treatment of jig & fixture components, know-how and so on. In this study we designed and constructed a drilling jig of mass production and performed tryout under the Auto CAD, Auto Lisp database, that we made by database, and window environment. Especially this study is reveals with the analysis of part drawing, jig planning, jig design etc, and then the result of drill jig's making try out.

• Proceedings of the KSME Conference
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• 2007.05a
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• pp.354-359
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• 2007

A new level set based topology optimization employing inner-front creation algorithm is presented. In the conventional level set based topology optimization, the optimum topology strongly depends on the initial level set distribution due to the incapability of inner-front creation during optimization process. In the present work, an inner-front creation algorithm is proposed, in which the sizes, positions, and number of new inner-fronts during the optimization process can be globally and consistently identified. To update the level set function during the optimization process, the least-squares finite element method is employed. As demonstrative examples for the flexibility and usefulness of the proposed method, the level set based topology optimization considering lightweight design of 3D shell structure is carried out.

• Structural Engineering and Mechanics
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• v.62 no.3
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• pp.259-272
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• 2017

In this study, recently developed swarm intelligence algorithm called Social Spider Optimization (SSO) approach and its enhanced version of SSO algorithm with spider jump techniques is used to develop a structural optimization technique for steel space structures. The improved version of SSO uses adaptive randomness probability in generating new solutions. The objective function of the design optimization problem is taken as the weight of a steel space structure. Constraints' functions are implemented from American Institute of Steel Construction-Load Resistance factor design (AISC-LRFD) and Ad Hoc Committee report and practice which cover strength, serviceability and geometric requirements. Three steel space structures are optimized using both standard SSO and SSO with spider jump (SSO_SJ) algorithms and the results are compared with those available in the literature in order to investigate the performance of the proposed algorithms.

• Architectural research
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• v.11 no.1
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• pp.15-23
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• 2009

An application of the constrained adaptive topology optimization (CATO) algorithm is described for three-dimensional topology optimization of engineering structures. The enhanced assumed strain lower order solid finite element (FE) is used to evaluate the values of objective and constraint functions required in optimization process. The strain energy (SE) terms such as elastic and modal SEs are employed as the objective function to be minimized and the initial volume of structures is introduced as the constraint function. The SIMP model is adopted to facilitate the material redistribution and also to produce clearer and more distinct structural topologies. The linearly weighted objective function is introduced to consider both static and dynamic characteristics of structures. Several numerical tests are tackled and it is used to investigate the performance of the proposed three-dimensional topology optimization process. From numerical results, it is found to be that the CATO algorithm is easy to implement and extremely applicable to produce the reasonable optimum topologies for three dimensional optimization problems.

• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.2579-2581
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• 2005

The Tidal Power Plant Management is defined to devise the optimum operating plan and control generating output automatically to obtain maximum production by using adaptive control method. The method to use tidal level observation results is suggested as two(2) kinds of manner, that is the two(2) layer design method by power model simulation and power automatic control.

• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.781-784
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• 1998

An image segmentation approach based on the fuzzy worm searching and MIN-MAx clusterng algorithm is proposed in this paper. This algorithm deals with fuzzy worm value and min-max node at a gross scene level, which investigates the edge information including fuzzy worm action. But current segmentation methods based edge extraction methods generally need the mask information for the algebraic model, and take long run times at mask operation, wheras the proposed algorithm has single operation ccording to active searching of fuzzy worms. In addition, we also genetic min-max clustering using genetic algorithm to complete clustering and fuzyz searching on grey-histogram of image for the optimum solution, which can automatically determine the size of rnages and has both strong robust and speedy calculation. The simulation results showed that the proposed algorithm adaptively divided the quantized images in histogram region and performed single searching methods, significantly alleviating the increase of the computational load and the memory requirements.