• Steel and Composite Structures
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• v.46 no.1
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• pp.33-51
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• 2023

This research presents a multi-material topology optimization for functionally graded material (FGM) and nonFGM with elastic buckling criteria. The elastic buckling based multi-material topology optimization of functionally graded steels (FGSs) uses a Jacobi scheme and a Method of Moving Asymptotes (MMA) as an expansion to revise the design variables shown first. Moreover, mathematical expressions for modified interpolation materials in the buckling framework are also described in detail. A Solid Isotropic Material with Penalization (SIMP) as well as a modified penalizing material model is utilized. Based on this investigation on the buckling constraint with homogenization material properties, this method for determining optimal shape is presented under buckling constraint parameters with non-homogenization material properties. For optimal problems, minimizing structural compliance like as an objective function is related to a given material volume and a buckling load factor. In this study, conflicts between structural stiffness and stability which cause an unfavorable effect on the performance of existing optimization procedures are reduced. A few structural design features illustrate the effectiveness and adjustability of an approach and provide some ideas for further expansions.

• Convergence Security Journal
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• v.24 no.3
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• pp.13-21
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• 2024

Recently, with the rapid expansion of networks driven by the advancements of the Fourth Industrial Revolution, cybersecurity threats are becoming increasingly severe. Traditional signature-based Network Intrusion Detection Systems (NIDS) are effective in detecting known attacks but show limitations when faced with new threats such as Advanced Persistent Threats (APT). Additionally, deep learning models based on supervised learning can lead to biased decision boundaries due to the imbalanced nature of network traffic data, where normal traffic vastly outnumbers malicious traffic. To address these challenges, this paper proposes a network intrusion detection method based on one-class models that learn only from normal data to identify abnormal traffic. The effectiveness of this approach is validated through experiments using the Deep SVDD and MemAE models on the NSL-KDD dataset. Comparative analysis with supervised learning models demonstrates that the proposed method offers superior adaptability and performance in real-world scenarios.

• Journal of Information Processing Systems
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• v.13 no.3
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• pp.599-617
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• 2017

Due to the rapid growth and expansion of the Internet, the digital multimedia such as image, audio and video are available for everyone. Anyone can make unauthorized copying for any digital product. Accordingly, the owner of these products cannot protect his ownership. Unfortunately, this situation will restrict any improvement which can be done on the digital media production in the future. Some procedures have been proposed to protect these products such as cryptography and watermarking techniques. Watermarking means embedding a message such as text, the image is called watermark, yet, in a host such as a text, an image, an audio, or a video, it is called a cover. Watermarking can provide and ensure security, data authentication and copyright protection for the digital media. In this paper, a new watermarking method of still image is proposed for the purpose of copyright protection. The procedure of embedding watermark is done in a transform domain. The discrete cosine transform (DCT) is exploited in the proposed method, where the watermark is embedded in the selected coefficients according to several criteria. With this procedure, the deterioration on the image is minimized to achieve high invisibility. Unlike the traditional techniques, in this paper, a new method is suggested for selecting the best blocks of DCT coefficients. After selecting the best DCT coefficients blocks, the best coefficients in the selected blocks are selected as a host in which the watermark bit is embedded. The coefficients selection is done depending on a weighting function method, where this function exploits the values and locations of the selected coefficients for choosing them. The experimental results proved that the proposed method has produced good imperceptibility and robustness for different types of attacks.

• Journal of the Korean Vacuum Society
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• v.22 no.5
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• pp.231-237
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• 2013

New method of volume measurement for reference weights of a pressure balance using a gas pycnometer is proposed. The result of volume measurement of proposed method shows the uncertainties of approximately 0.2% at the level of confidence of 95% for reference weights in the ranges of 1 kg, 2 kg, and 5 kg. This measuring system consists of a sample chamber, an expansion chamber, a precision pressure gage, a precison thermometer, a vacuum pump, and helium as a medium gas. The measurement principle of this proposed method is based on Boyle's law. This method will contribute a reliability of the volume measurements of reference weights for a pressure balance to the national measurement standard.

• Journal of Broadcast Engineering
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• v.10 no.4 s.29
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• pp.505-514
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• 2005

Image upsampling can be performed in both spatial and frequency (transform) domain. In the spatial domain, various upsampling techniques are developed and 6-tap FIR interpolation filter is most well known method, which is embedded in many video coding standards. It can provide high subjective quality but shows low objective quality. In the transform domain, simple zero padding method can produce upsampled image easily. It shows better objective quality than 6-tap filtering, but it yields ringing effects which annoy eyes. In this paper, we present efficient upsampling method using frequency addition method in transform domain to provide better subjective and objective quality than conventional method Extensive simulation results show that the proposed algorithm produces visually fine images with high PSNR.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.4
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• pp.1254-1259
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• 2010

In this paper, Low Computational Adaptive Expanded Block Search Motion Estimation Method is proposed. Proposed method classifies ME blocks as Average Motion Block(AMB) and Local Motion Block(LMB) according to correlation of reference frame. It could reduce the computational complexity with performing Modified Fast Search(MFS). And accuracy of MV is also increased by 4 sub-blocks on LMB and Block Expansion(BE). The experimental results show that the proposed method has better performance that increased 1.8dB than Diamond Search and 0.6dB than Full Search with 7.5 % computation of Full Search. The proposed method could be applied to video compression and Frame Rate Conversion(FRC).

• Journal of the Korean Association of Geographic Information Studies
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• v.6 no.1
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• pp.12-23
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• 2003

The expansion of internet and the development of communication technology have brought about an explosive increasement of data. Further progress has led to the increasing demand for efficient and effective data analysis tools. According to this demand, data mining techniques have been developed to find out knowledge from a huge amounts of raw data. This paper suggests a generalization based classification method which explores rules from real world data appearing repeatedly. Also, it analyzed the relation between weather data and forest fire, and efficiently predicted through it as a prediction model by applying the suggested generalization based classification method to forest fire data. Additionally, the proposed method can be utilized variously in the important field of real life like the analysis and prediction on natural disaster occurring repeatedly, the prediction of energy demand and so forth.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.4
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• pp.69-75
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• 2014

A novel reversible data hiding method using pixel value ordering and prediction error expansion in the sub-block is resented in this paper. For each non-overlapping $2{\times}2$ sub-block, we divide into two groups. In the min group, the lowest value is changed to embed a secret bit and the highest value is changed in the max group. The experimental results show that the proposed method achieves a good visual quality and high capacity. The proposed method can embed 13,900 bits on average, it is higher 4,553 bits than the previous method and the visual quality is maintained 31.39dB on average.

• Journal of the Korean Society for Nondestructive Testing
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• v.31 no.1
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• pp.68-76
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• 2011

Acoustic emission(AE) has emerged as a powerful nondestructive tool to detect any further growth or expansion of preexisting defects or to characterize failure mechanisms. Recently, this kind of technique, that is an in-situ monitoring of inside damages of materials or structures, becomes increasingly popular for monitoring the integrity of large structures like a huge wind turbine blade. Therefore, it is required to find a symptom of damage propagation before catastrophic failure through a continuous monitoring. In this study, a new damage location method has been proposed by using signal mapping algorithm, and an experimental verification is conducted by using small wind turbine blade specimen; a part of 750 kW real blade. The results show that this new signal mapping method has high advantages such as a flexibility for sensor location, improved accuracy, high detectability. The newly proposed method was compared with traditional AE source location method based on arrival time difference.

• Journal of the Korean Society of Radiology
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• v.2 no.1
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• pp.23-29
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• 2008

The present study proposed a method that dissolves ultrasonographic images into multiple resolutions using wavelet conversion and a boundary detection filter and improves the quality of ultrasonographic images through boundary detection filtering. In order to reduce noises and strengthen edges, the proposed method adjusted selectivity coefficient by area step by step from a low resolution image obtained from wavelet converted images to a high resolution image and performed edge filtering in consideration of direction. Through this method, we generated a selective low pass filtering effect in areas except edges by decreasing the wavelet coefficient for pixels in spot areas, improved continuity by smoothing edges in the tangential direction, and enhanced contrast by thinning in the normal direction. Through an experiment, we compared the filtering method using a non linear anisotropic expansion model and the filtering method using wavelet contraction structure in single resolution.