• Smart Structures and Systems
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• 제30권6호
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• pp.583-599
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• 2022

In this paper, a multi-objective wireless sensor network configuration optimization method is proposed. The proposed method aims to determine the optimal information and lifespan wireless sensor network for structural health monitoring of large-scale infrastructures. In particular, cluster-based wireless sensor networks with multi-type of sensors are considered. To optimize the lifetime of the wireless sensor network, a cluster-based network optimization algorithm that optimizes the arrangement of cluster heads and base station is developed. On the other hand, based on the Bayesian inference, the uncertainty of the estimated parameters can be quantified. The coefficient of variance of the estimated parameters can be obtained, which is utilized as a holistic measure to evaluate the estimation accuracy of sensor configurations with multi-type of sensors. The proposed method provides the optimal wireless sensor network configuration that satisfies the required estimation accuracy with the longest lifetime. The proposed method is illustrated by designing the optimal wireless sensor network configuration of a cable-stayed bridge and a space truss.

• Journal of Families and Better Life
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• 제16권4호
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• pp.155-166
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• 1998

The purpose of this study was to develop ' the Behavior Problem Scale for Children and Adolescence' The 518 subjects were selected from 5th and 6th grades of elementary schools and first and second grades of middle schools in Pusan. Statistics used for data analysis were χ2 cramer's V, factor analysis multi-regression Pearson's r, Cronbach's a. The major finding of this study were as follows 1) 80 items of the 159 item scale were acceptable through item discriminant method The discriminant coefficients of the items(Cramer's V) ranged from .48 to .81. 2) 6 factors(shyness aggression hyperactivity withdrawal anxious immature) extracted from factor analysis,. Multi-regression analysis conducted to reduce the length of scale have drawn 42 items for 'the Behavior Problem Scale Children and Adolescence' 3) Reliability coefficients(Cronbach's a) of this scale was 94.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권10호
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• pp.5179-5196
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• 2019

To explore an effective non-invasion medical imaging diagnostics approach for hepatocellular carcinoma (HCC), we propose a method based on adopting the multiple technologies with the multi-parametric data fusion, transfer learning, and multi-scale deep feature extraction. Firstly, to make full use of complementary and enhancing the contribution of different modalities viz. multi-parametric MRI images in the lesion diagnosis, we propose a data-level fusion strategy. Secondly, based on the fusion data as the input, the multi-scale residual neural network with SPP (Spatial Pyramid Pooling) is utilized for the discriminative feature representation learning. Thirdly, to mitigate the impact of the lack of training samples, we do the pre-training of the proposed multi-scale residual neural network model on the natural image dataset and the fine-tuning with the chosen multi-parametric MRI images as complementary data. The comparative experiment results on the dataset from the clinical cases show that our proposed approach by employing the multiple strategies achieves the highest accuracy of 0.847±0.023 in the classification problem on the HCC differentiation. In the problem of discriminating the HCC lesion from the non-tumor area, we achieve a good performance with accuracy, sensitivity, specificity and AUC (area under the ROC curve) being 0.981±0.002, 0.981±0.002, 0.991±0.007 and 0.999±0.0008, respectively.

• Journal of the Korean Society for Precision Engineering
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• 제32권6호
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• pp.577-585
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• 2015

We fabricated multi-scale such as macro-, micro-, and multi-scale wrinkles by using repetitive volume dividing (RVD) method and thermal curing process. Also wrinkle surface was modified with coating of a self-assembled monolayer (SAM). We measured the contact angle of each wrinkled surface, and observed the behavior of droplets on sloping surface. Through experimental study, we found out that the contact angle was much higher in case of multi-scale and SAM coated wrinkles. And micro-scale wrinkle showed a high contact angle comparing with that of macro-scale wrinkle. Dynamic behaviors of a water droplet like sliding velocity on diverse wrinkled surfaces were dependent on their static contact angles. These results showed that hydro-dynamic characteristics were changed depending on the wrinkle structure and the material forming the wrinkle. These dynamic characteristics can be utilized in bio-chip, microfluidics, and many others in order to control easily chemical reactivity.

• Journal of Broadcast Engineering
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• 제20권4호
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• pp.521-532
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• 2015

This paper presents a piecewise image denoising with multi-scale block region detector based on quadtree structure for effective image restoration. Proposed piecewise image denoising method suggests multi-scale block region detector (MBRD) by dividing whole pixels of a noisy image into three parts, with regional characteristics: strong variation region, weak variation region, and flat region. These regions are classified according to total pixels variation between multi-scale blocks and are applied principal component analysis with local pixel grouping, bilateral filtering, and structure-preserving image decomposition operator called relative total variation. The performance of proposed method is evaluated by Experimental results. we can observe that region detection results generated by the detector seems to be well classified along the characteristics of regions. In addition, the piecewise image denoising provides the positive gain with regard to PSNR performance. In the visual evaluation, details and edges are preserved efficiently over the each region; therefore, the proposed method effectively reduces the noise and it proves that it improves the performance of denoising by the restoration process according to the region characteristics.

• Advances in biomechanics and applications
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• 제1권1호
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• pp.23-40
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• 2014

This paper examines the blood chamber of a left ventricular assist device (LVAD) under static loading conditions and standard operating temperatures. The LVAD's walls are made of a temperature-sensitive polymer (ChronoFlex C 55D) and are covered with a titanium nitride (TiN) nano-coating (deposited by laser ablation) to improve their haemocompatibility. A loss of cohesion may be observed near the coating-substrate boundary. Therefore, a micro-scale stress-strain analysis of the multilayered blood chamber was conducted with FE (finite element) code. The multi-scale model included a macro-model of the LVAD's blood chamber and a micro-model of the TiN coating. The theories of non-linear elasticity and elasto-plasticity were applied. The formulated problems were solved with a finite element method. The micro-scale problem was solved for a representative volume element (RVE). This micro-model accounted for the residual stress, a material model of the TiN coating, the stress results under loading pressures, the thickness of the TiN coating and the wave parameters of the TiN surface. The numerical results (displacements and strains) were experimentally validated using digital image correlation (DIC) during static blood pressure deformations. The maximum strain and stress were determined at static pressure steps in a macro-scale FE simulation. The strain and stress were also computed at the same loading conditions in a micro-scale FE simulation.

• Journal of Korea Multimedia Society
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• 제15권4호
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• pp.439-448
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• 2012

TFT-LCD panel images have non-uniform brightness, noise signal and defect signal. It is hard to divide defect signal because of non-uniform brightness and noise signal, so various divide methods have being developed. In this paper, we suggest method to divide defective regions on TFT-LCD panel image by estimating a menas of two different size of windows, which is suggested by Eikvil et al., and using difference of them. But in this method, the size of detectable defects is restricted by the size of window, hence it has inefficient problem that the size of window have to increase to divide a large defect region. To solve this problem we suggest an algorithm which can divide various size of defects, by using Multi-scale and restrict a detectable size of defects in each scale. To prove an efficiency of suggested algorithm, we show that resulting images of real TFT-LCD panel images and an artificial image with various defects.

• Steel and Composite Structures
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• 제20권3호
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• pp.693-718
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• 2016

This paper presents a finite element procedure based on Bridging multi-scale method (BMM) in order to incorporate the effect of local/cross-sectional deformations (e.g., flange local buckling and web crippling) on the global behaviour of thin-walled members made of fibre-reinforced polymer composite laminates. This method allows the application of local shell elements in critical regions of an existing beam-type model. Therefore, it obviates the need for using computationally expensive shell elements in the whole domain of the structure, which is otherwise necessary to capture the effect of the localized behaviour. Consequently, highly accurate analysis results can be achieved with this method by using significantly smaller finite element model, compared to the existing methods. The proposed method can be used for composite polymer laminates with arbitrary fibre orientation directions in different layers of the material, and under various loading conditions. Comparison with full shell-type finite element analysis results are made in order to illustrate the efficiency and accuracy of the proposed technique.

• Journal of Institute of Control, Robotics and Systems
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• 제19권11호
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• pp.968-973
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• 2013

In the transportation industry, especially in the shipbuilding process, 3D surface measurement of large-scale hull pieces is needed for fabrication and assembly. We suggest an efficient method for checking the shape of curved plates under the forming operation with short time by measuring 3D profiles along the multi lines of the target surface. For accurate profile reconstruction, 2D camera calibration and 3D calibration using gauge blocks were performed. The evaluation test shows that the measurement accuracy is within the boundary of tolerance required in the shipbuilding process.

• Proceedings of the Korea Information Processing Society Conference
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• 한국정보처리학회 2023년도 추계학술발표대회
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• pp.648-651
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• 2023

Video anomaly detection aims to detect abnormal events. Motivated by the power of transformers recently shown in vision tasks, we propose a novel transformer-based network for video anomaly detection. To capture long-range information in video, we employ a multi-scale transformer as an encoder. A convolutional decoder is utilized to predict the future frame from the extracted multi-scale feature maps. The proposed method is evaluated on three benchmark datasets: USCD Ped2, CUHK Avenue, and ShanghaiTech. The results show that the proposed method achieves better performance compared to recent methods.