• Advances in Computational Design
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• v.8 no.1
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• pp.37-59
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• 2023

Squat reinforced concrete (SRC) shear walls are a critical part of the structure for both office/residential buildings and nuclear structures due to their significant role in withstanding seismic loads. Despite this, empirical formulae in current design standards and published studies demonstrate a considerable disparity in predicting SRC wall shear strength. The goal of this research is to develop and evaluate hybrid and ensemble artificial neural network (ANN) models. State-of-the-art population-based algorithms are used in this research for hybrid intelligence algorithms. Six models are developed, including Honey Badger Algorithm (HBA) with ANN (HBA-ANN), Hunger Games Search with ANN (HGS-ANN), fitness-distance balance coyote optimization algorithm (FDB-COA) with ANN (FDB-COA-ANN), Averaging Ensemble (AE) neural network, Snapshot Ensemble (SE) neural network, and Stacked Generalization (SG) ensemble neural network. A total of 434 test results of SRC walls is utilized to train and assess the models. The results reveal that the SG model not only minimizes prediction variance but also produces predictions (with R²= 0.99) that are superior to other models.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.2
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• pp.693-709
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• 2018

In this paper, we propose a compact Convolutional Neural Network (CNN)-based tracker in conjunction with a particle filter architecture, in which the CNN model operates as an accurate candidates estimator, while the particle filter predicts the target motion dynamics, lowering the overall number of calculations and refines the resulting target bounding box. Experiments were conducted on the Online Object Tracking Benchmark (OTB) [34] dataset and comparison analysis in respect to other state-of-art has been performed based on accuracy and precision, indicating that the proposed algorithm outperforms all state-of-the-art trackers included in the OTB dataset, specifically, TLD [16], MIL [1], SCM [36] and ASLA [15]. Also, a comprehensive speed performance analysis showed average frames per second (FPS) among the top-10 trackers from the OTB dataset [34].

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.7
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• pp.1377-1382
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• 2012

In this paper, we propose a novel recognition method that extract source data from encoded signal that are displayed on FND mounted on home appliances. First of all, it find a candidate FND region from sequential difference images taken by smartphone and extract segment image using clustering RGB value. After that, it normalize segment images to correct a slant error and recognize each segments using a relative distance. Experiments show the robustness of the recognition algorithm on smartphone.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.2
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• pp.837-856
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• 2016

Underwater image enhancement has received considerable attention in last decades, due to the nature of poor visibility and low contrast of underwater images. In this paper, we propose a new automatic underwater image enhancement algorithm, which combines nonsubsampled contourlet transform (NSCT) domain enhancement techniques with the mechanism of the human visual system (HVS). We apply the multiscale retinex algorithm based on the HVS into NSCT domain in order to eliminate the non-uniform illumination, and adopt the threshold denoising technique to suppress underwater noise. Our proposed algorithm incorporates the luminance masking and contrast masking characteristics of the HVS into NSCT domain to yield the new HVS-based NSCT. Moreover, we define two nonlinear mapping functions. The first one is used to manipulate the HVS-based NSCT contrast coefficients to enhance the edges. The second one is a gain function which modifies the lowpass subband coefficients to adjust the global dynamic range. As a result, our algorithm can achieve contrast enhancement, image denoising and edge sharpening automatically and simultaneously. Experimental results illustrate that our proposed algorithm has better enhancement performance than state-of-the-art algorithms both in subjective evaluation and quantitative assessment. In addition, our algorithm can automatically achieve underwater image enhancement without any parameter tuning.

• Journal of the Korea Society of Computer and Information
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• v.21 no.5
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• pp.41-47
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• 2016

This paper considers simple polygon search problem. How many searchers find a mobile intruder that is arbitrarily faster than the searcher within polygon art gallery? This paper uses the visibility graph that is connected with edges for mutually visible vertices. Given visibility graph, we select vertex u that is conjunction ${\Delta}(G)$ in $N_G(v)$ for $d_G(v){\leq}4$. We decide 1-searchable if $1{\leq}{\mid}u{\mid}{\leq}2$ and 2-searchable if ${\mid}u{\mid}{\geq}3$. We also present searcher's shortest path. This algorithm is verified by varies 1 or 2-searchable polygons.

• Journal of IKEEE
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• v.22 no.2
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• pp.227-232
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• 2018

Nowadays, image manipulation is enormously popular and easier than ever with tons of convenient images editing tools. After several simple operations, users can get visually attractive images which easily trick viewers. In this paper, we propose a fast algorithm which can detect the image splicing using the Markov features. The proposed algorithm reduces the computational complexity by removing unnecessary Markov features which are not used in the image splicing detection process. The performance of the proposed algorithm is evaluated using a famous image splicing dataset which is publicly available. The experimental results show that the proposed technique outperforms the state-of-the-art splicing detection methods.

• Smart Structures and Systems
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• v.17 no.2
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• pp.195-208
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• 2016

Seismic isolation systems are essentially designed to preserve structural safety, prevent occupants injury and properties damage. An active saturated LMI-based control design is proposed to attenuate seismic disturbances in base-isolated structures under saturation actuators. Using a mathematical model of an eight-storied building structure, an active control algorithm is designed. Performance evaluation of the controller is carried out in a simplified model version of a benchmark building system, which is recognized as a state-of-the-art model for numerical experiments of structures under seismic perturbations. Experimental results show that the proposed algorithm is robust with respect to model and seismic perturbations. Finally, the performance indices show that the proposed controller behaves satisfactorily and with a reasonable control effort.

• Journal of the military operations research society of Korea
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• v.8 no.2
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• pp.57-68
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• 1982

Bimatrix games are the two-person non-zero-sum non-cooperative games. These games were studied by Mills, Lemke, Howson, Millham, Winkels, and others. This paper is a systematic and synthetic survey relevant to bimatrix games. Among the many aspects of researches on bimatrix games, emphasis in this paper is placed on the relation of the equilibrium set to Nash subsets. Topics discussed are as follows: Properties of equilibrium point; The structure of equilibrium set; Relation of Nash subsets to equilibrium set; Algorithm for finding the equilibrium points; Concepts of solutions on bimatrix games.

• Journal of KSNVE
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• v.3 no.2
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• pp.127-135
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• 1993

The structural control systems for civil engineering structures have got considerable attention in recent years, since they become effective protective systems. The key idea behind structural control is to keep the response of a structure within certain bounds dictated by serviceability, structural safety, and reliability. Recent activities in control algorithm development and control system design and practical aspects of their applications are sumarized, followed by a discussion on prossible future directions.

• IE interfaces
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• v.10 no.2
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• pp.51-56
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• 1997

This paper concerns with the problem of mixed model assembly sequencing using neural net. In recent years, because of two characteristics of it, massive parallelism and learning capability, neural nets have emerged to solve the problems for which more conventional computational approaches have proven ineffective. This paper proposes a method using neural net that can consider line balancing and grouping problems simultaneously. In order to solve the mixed model assembly sequencing of the motor industry, this paper uses the modified ART1 algorithm.