• Journal of the Institute of Electronics Engineers of Korea CI
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• v.40 no.1
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• pp.39-49
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• 2003

Watermark detection has a crucial role in copyright protection of and authentication for multimedia and has classically been tackled by means of correlation-based algorithms. Nevertheless, when watermark embedding does not obey an additive rule, correlation-based detection is not the optimum choice. So a new detection algorithm is proposed which is optimum for non-additive watermark embedding. By relying on statistical decision theory, the proposed method is derived according to the Bayes decision theory, Neyman-Pearson criterion, and distribution of wavelet coefficients, thus permitting to minimize the missed detection probability subject to a given false detection probability. The superiority of the proposed method has been tested from a robustness perspective. The results confirm the superiority of the proposed technique over classical correlation- based method.

• Korean Journal of Ichthyology
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• v.21 no.2
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• pp.81-86
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• 2009

The spermiogenesis and mature spermatozoa of Pseudobagrus fulvidraco were described by means of scanning and transmission electron microscopy. Spermiogenesis is characterized by lateral development of the flagellum, nuclear rotation, deep nuclear fossa formation and compaction into thick granules. The spermatozoa exhibit a round head containing a nucleus that lacks an acrosome, and having a midpiece and a flagellum. The midpiece is small and has a short cytoplasm including several mitochondria separated from the tail by the cytoplasmic canal. The flagellum contains the 9+2 classical axoneme structure and has two axonemal fins. The presence of axonemal fins in the flagellum is a common character in Bagridae. The interrelationships among the Bagridae as well as other teleosts are herein discussed.

• Journal of the Korea Fashion and Costume Design Association
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• v.15 no.1
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• pp.59-74
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• 2013

Post-modern society leads us to accept diversity and variability instead of pursuit of the absolute truth, beauty or classical value systems, thus leading to hybrid phenomena. The purpose of this study is to analyze characteristics and expressive effects of hybrid expressions through which to provide conceptual bases for interpreting expanded meanings of fashion illustrations that express aesthetic concepts of hybrid culture. Hybrid refers to a condition on which diverse elements are mixed with each other, so any one element can not dominate others. It is often used to create something unique and new by a combination of unprecedented things. Hybrid can be classified into four categories: temporal hybrid, spatial hybrid, morphological hybrid and hybrid of different genres. Temporal hybrid from a combination of past and present in fashion illustration includes temporal blending by repetition and juxtaposition. Spatial hybrid shows itself in the form of inter-penetration and interrelationship by means of projection, overlapping, juxtaposition and multiple space. Morphological hybrid expresses itself through combination of heterogenous forms and restructuring of deformed forms. Hybrid of different genres in fashion illustration applies various graphic elements or photos within the space, and represents blending of arts and daily living. Such hybrid expressions in fashion illustrations reflect the phenomena of diversity and variability of post-modern society. Hybrid expressions in fashion illustrations predict endless possibility of expressing new images through combining various forms or casual elements and can develop toward a new creative technique.

• Structural Engineering and Mechanics
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• v.51 no.5
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• pp.793-808
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• 2014

The goal of this study is to evaluate and design steel plates with optimal material distributions achieved through a specific material topology optimization by using a CCARAT (Computer Aided Research Analysis Tool) as an optimizer, topologically optimally updating node densities as design variables. In typical material topology optimization, optimal topology and layouts are described by distributing element densities (from almost 0 to 1), which are arithmetic means of node densities. The average element densities are employed as material properties of each element in finite element analysis. CCARAT may deal with material topology optimization to address the mean compliance problem of structural mechanical problems. This consists of three computational steps: finite element analysis, sensitivity analysis, and optimality criteria optimizer updating node densities. The present node density based design via CCARAT using node densities as design variables removes jagged optimal layouts and checkerboard patterns, which are disadvantages of classical material topology optimization using element densities as design variables. Numerical applications that topologically optimize reinforcement material distribution of steel plates of a cantilever type are studied to verify the numerical superiority of the present node density based design via CCARAT.

• Journal of Electrical Engineering and Technology
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• v.13 no.4
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• pp.1724-1731
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• 2018

The conventional polynomial neural network (PNN) is a classical flexible neural structure and self-organizing network, however it is not free from the limitation of overfitting problem. In this study, we propose a space search-optimized polynomial neural network (ssPNN) structure to alleviate this problem. Ranking selection is realized by means of ranking selection-based performance index (RS_PI) which is combined with conventional performance index (PI) and coefficients based performance index (CPI) (viz. the sum of squared coefficient). Unlike the conventional PNN, L2-norm regularization method for estimating the polynomial coefficients is also used when designing the ssPNN. Furthermore, space search optimization (SSO) is exploited here to optimize the parameters of ssPNN (viz. the number of input variables, which variables will be selected as input variables, and the type of polynomial). Experimental results show that the proposed ranking selection-based polynomial neural network gives rise to better performance in comparison with the neuron fuzzy models reported in the literatures.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.227-230
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• 1993

Recently, the development of novel control methodology enables us to improve the performance of AC-machine drives by using pulse width modulation (PWM) technique. Usually, the dynamic characteristic of induction motor (IM) has been represented by the 5-th order nonlinear differential equation. This dynamics, however, can be reduced to 3-rd order dynamics by applying direct control of IM input current. This methodology concludes that it is much easier to control IM by means of the field-oriented methods employing the current controller. Therefore a precise current control is crucial to achieve a high control performance both in dynamic and steady state operations. This paper presents an adaptive fuzzy current controller with artificial neural network (ANN) for field-oriented controlled IM. This new control structure is able to adaptively minimize a current ripple while maintaining constant switching frequency. Especially the proposed controller employs neuro-computing philosophy as well as adaptive learning pattern recognizing principles with respect to variations of the system parameters. The proposed approach is applied to the IM drive system, and its performance is tested through various simulations. Simulation results show that the proposed system, compared among several known classical methods, has a superb performance.

• Advances in nano research
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• v.7 no.6
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• pp.379-390
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• 2019

Putting emphasis on the effect of existence of porosity in the functionally graded materials (FGMs) on the dynamic responses of waves scattered in FG nanobeams resulted in implementation of a novel porosity-based homogenization method for FGMs and show its applicability in a wave propagation problem in the presence of axial pre-load for the first time. In the employed porosity-dependent method, the coupling between density and Young's moduli is included to consider for the effective moduli of the FG nanobeam by the means of a more reliable homogenization technique. The beam-type element will be modeled via the classical theory of beams, namely Euler-Bernoulli beam theory. Also, the dynamic form of the principle of virtual work will be extended for such nanobeams to derive the motion equations. Applying the nonlocal constitutive equations of Eringen on the obtained motion equations will be resulted in derivation of the nanobeam's governing equations. Depicted results reveal that the dispersion responses of FG nanobeams will be decreased as the porosity volume fraction is increased which must be noticed by the designers of advanced nanosize devices who are interested in employment of wave dispersion approach in continuous systems for specific goals.

• Journal of Magnetics
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• v.21 no.4
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• pp.660-665
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• 2016

The electromagnetic apparatus plays an important role in high power electrical systems. It is of great importance to provide an effective approach for the optimization of the high power electromagnetic apparatus. However, premature convergence and few Pareto solution set of the optimization for electromagnetic apparatus always happen. This paper proposed a modified multi-objective particle swarm optimization algorithm based on the niche sorting strategy. Applying to the modified algorithm, this paper guarantee the better Pareto optimal front with an enhanced distribution. Aiming at shortcomings in the closing bounce and slow breaking velocity of electromagnetic apparatus, the multi-objective optimization model was established on the basis of the traditional optimization. Besides, by means of the improved multi-objective particle swarm optimization algorithm, this paper processed the model and obtained a series of optimized parameters (decision variables). Compared with other different classical algorithms, the modified algorithm has a satisfactory performance in the multi-objective optimization problems in the electromagnetic apparatus.

• Journal of Korea Society of Digital Industry and Information Management
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• v.17 no.3
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• pp.27-37
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• 2021

Highly informative heuristics in AI planning can help to a more efficient search a solutions. However, in general, to obtain informative heuristics from planning problem specifications requires a lot of computational effort. To address this problem, we propose a Partial Planning Graph(PPG) and Mixed Heuristics for solving planning problems more efficiently. The PPG is an improved graph to be applied to can find a partial heuristic value for each goal condition from the relaxed planning graph which is a means to get heuristics to solve planning problems. Mixed Heuristics using PPG requires size of each graph is relatively small and less computational effort as a partial plan generated for each goal condition compared to the existing planning graph. Mixed Heuristics using PPG can find partial interactions for each goal conditions in an effective way, then consider them in order to estimate the goal state heuristics. Therefore Mixed Heuristics can not only find interactions for each goal conditions more less computational effort, but also have high accuracy of heuristics than the existing max and additive heuristics. In this paper, we present the PPG and the algorithm for computing Mixed Heuristics, and then explain analysis to accuracy and the efficiency of the Mixed Heuristics.

• Earthquakes and Structures
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• v.16 no.4
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• pp.437-453
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• 2019

This study investigates a new optimal placement method for viscous dampers between structures in order to prevent pounding of adjacent structures with different dynamic characteristics under earthquake effects. A relative displacement spectrum is developed in two single degree of freedom system to reveal the critical period ratios for the most risky scenario of collision using El Centro earthquake record (NS). Three different types of viscous damper design, which are classical, stair and X-diagonal model, are considered to prevent pounding on two adjacent building models. The objective function is minimized under the upper and lower limits of the damping coefficient of the damper and a target modal damping ratio. A new algorithm including time history analyses and numerical optimization methods is proposed to find the optimal dampers placement. The proposed design method is tested on two 12-storey adjacent building models. The effects of the type of damper placement on structural models, the critical period ratios of adjacent structures, the permissible relative displacement limit, the mode behavior and the upper limit of damper are investigated in detail. The results of the analyzes show that the proposed method can be used as an effective means of finding the optimum amount and location of the dampers and eliminating the risk of pounding.