• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.150-150
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• 2019

The development of prolong and severe drought can directly impact on the environment, agriculture, economics and society of country. A lot of efforts have been made across worldwide in the planning, monitoring and mitigation of drought. Currently, different drought indices such as the Palmer Drought Severity Index (PDSI), Standardized Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI) are developed and most commonly used to monitor drought characteristics quantitatively. However, it will be very meaningful and essential to develop a more effective technique for assessment and monitoring of onset and end of drought. Therefore, in this study, the hidden Markov Bayesian classifier (MBC) was employed for the assessment of onset and end of meteorological drought classes. The results showed that the probabilities of different classes based on the MBC were quite suitable and can be employed to estimate onset and end of each class for meteorological droughts. The classification results of MBC were compared with SPI and with past studies which proved that the MBC was able to account accuracy in determining the accurate drought classes. For more performance evaluation of classification results confusion matrix was used to find accuracy and precision in predicting the classes and their results are also appropriate. The overall results indicate that the MBC was effective in predicating the onset and end of drought events and can utilized for monitoring and management of short-term drought risk.

• Advances in aircraft and spacecraft science
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• v.3 no.3
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• pp.331-349
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• 2016

Stiff and light fibre reinforced composites as used in air- and space-craft applications tend to high sound emission. Therefore, the damping properties are essential for the entire structural and acoustic engineering. Viscous damping is an established and reasonably linear model of the dissipation behaviour. Commonly, it is assumed to be isotropic and constant over all modes. For anisotropic materials it depends on the fibre orientation as well as the elastic and thermal material properties. To portray the orthogonal anisotropic behaviour, a model for unidirectional fibre reinforced plastics (frp) has been developed based on the classical laminate theory by ADAMS and BACON starting in 1973. Their approach includes three damping coefficients - for longitudinal damping in fibre direction, damping transversal to the fibres and shear based dissipation. The damping of a laminate is then accumulated layer wise including the anisotropic stiffness. So far, the model has been applied mainly to thermoset matrix materials. In this study, an experimental parameter estimation for different thermoplastic frp with angle ply and cross ply layups was carried out by measuring free vibrations of cantilever beams. The results show potential and limits of the ADAMS/BACON damping criterion. In addition, a possibility of modelling the anisotropic damping is shown. The implementation in standard FEA software is used to study the influence of boundary conditions on the damping properties and numerically estimate the radiated sound power of thin-walled frp parts.

• Environmental Engineering Research
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• v.23 no.4
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• pp.420-429
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• 2018

Soil stabilization is a soil remediation technique that reduces the mobility of heavy metals in soils. Although it is a well-established technique, it is nonetheless essential to perform a follow-up chemical assessment via a leaching test to evaluate the immobilization of heavy metals in the soil matrix. Unfortunately, a standard chemical assessment is not sufficient for evaluation of the biological functional state of stabilized soils slated for agricultural use. Therefore, it is useful to employ a pyrosequencing-based microbial community analysis for the purpose. In this study, a recently stabilized site in the proximity of an exhausted mine was analyzed for bacterial diversity, richness, and relative abundance as well as the effect of environmental factors. Based on the Shannon and Chao1 indices and rarefaction curves, the results showed that the stabilized layer exhibited lower bacterial diversity than control soils. The prevalence of dominant bacterial populations was examined in a hierarchical manner. Relatively high abundances of Proteobacteria and Methylobacter tundripaludum were observed in the stabilized soil. In particular, there was substantial abundance of the Methylobacter genus, which is known for its association with heavy metal contamination. The study demonstrated the efficacy of (micro)biological assessment for aiding in the understanding and post-management of stabilized soils.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.1
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• pp.435-451
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• 2019

Impossible differential cryptanalysis is an essential cryptanalytic technique and its key point is whether there is an impossible differential path. The main factor of influencing impossible differential cryptanalysis is the length of the rounds of the impossible differential trail because the attack will be more close to the real encryption algorithm with the number becoming longer. We provide the upper bound of the longest impossible differential trails of several important block ciphers. We first analyse the national standard of the Russian Federation in 2015, Kuznyechik, which utilizes the 16-byte LFSR to achieve the linear transformation. We conclude that there is no any 3-round impossible differential trail of the Kuznyechik without the consideration of the specific S-boxes. Then we ascertain the longest impossible differential paths of several other important block ciphers by using the matrix method which can be extended to many other block ciphers. As a result, we show that, unless considering the details of the S-boxes, there is no any more than or equal to 5-round, 7-round and 9-round impossible differential paths for KLEIN, Midori64 and MIBS respectively.

• The Korean Journal of Applied Statistics
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• v.35 no.2
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• pp.327-333
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• 2022

Principal component analysis (PCA) is the most widely used technique in dimension reduction, however, it is very sensitive to outliers. A robust version of PCA, called robust PCA, was suggested by two seminal papers by Candès et al. (2011) and Chandrasekaran et al. (2011). The robust PCA is an essential tool in the artificial intelligence such as background detection, face recognition, ranking, and collaborative filtering. Also, the robust PCA receives a lot of attention in statistics in addition to computer science. In this paper, we introduce recent algorithms for the robust PCA and give some illustrative examples.

• Journal of Auto-vehicle Safety Association
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• v.13 no.4
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• pp.7-13
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• 2021

This paper presents an vulnerable road user (VRU) classification and tracking algorithm using vision and LiDAR sensor fusion method for urban autonomous driving. The classification and tracking for vulnerable road users such as pedestrian, bicycle, and motorcycle are essential for autonomous driving in complex urban environments. In this paper, a real-time object image detection algorithm called Yolo and object tracking algorithm from LiDAR point cloud are fused in the high level. The proposed algorithm consists of four parts. First, the object bounding boxes on the pixel coordinate, which is obtained from YOLO, are transformed into the local coordinate of subject vehicle using the homography matrix. Second, a LiDAR point cloud is clustered based on Euclidean distance and the clusters are associated using GNN. In addition, the states of clusters including position, heading angle, velocity and acceleration information are estimated using geometric model free approach (GMFA) in real-time. Finally, the each LiDAR track is matched with a vision track using angle information of transformed vision track and assigned a classification id. The proposed fusion algorithm is evaluated via real vehicle test in the urban environment.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.20 no.4
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• pp.429-453
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• 2022

Numerical modeling and scenario composition are needed to characterize the geological environment of the disposal site and analyze the long-term evolution of natural barriers. In this study, processes and features of the hydro-mechanical behavior of natural barriers were categorized and represented using the interrelation matrix proposed by SKB and Posiva. A hydro-mechanical coupled model was evaluated for analyzing stress field changes and fracture zone re-activation. The processes corresponding to long-term evolution and the hydro-mechanical mechanisms that may accompany critical processes were identified. Consequently, practical numerical methods could be considered for these geological engineering issues. A case study using a numerical method for the stability analysis of an underground disposal system was performed. Critical stress distribution regime problems were analyzed numerically by considering the strata's movement. Another case focused on the equivalent continuum domain composition under the upscaling process in fractured rocks. Numerical methods and case studies were reviewed, confirming that an appropriate and optimized modeling technique is essential for studying the stress state and geological history of the Korean Peninsula. Considering the environments of potential disposal sites in Korea, selecting the optimal application method that effectively simulates fractured rocks should be prioritized.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.11a
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• pp.705-708
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• 2010

An eigen color co-occurrence approach is proposed that exploits the correlation between color channels to identify the degree of image similarity. This method is based on traditional co-occurrence matrix method and histogram equalization. On the purpose of feature extraction, eigen color co-occurrence matrices are computed for extracting the statistical relationships embedded in color images by applying Principal Component Analysis (PCA) on a set of color co-occurrence matrices, which are computed on the histogram equalized images. That eigen space is created with a set of orthogonal axes to gain the essential structures of color co-occurrence matrices, which is used to identify the degree of similarity to classify an input image to be tested for various purposes. In this paper RGB, Gaussian color space are compared with grayscale image in terms of PCA eigen features embedded in histogram equalized co-occurrence features. The experimental results are presented.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.3
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• pp.8-13
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• 2023

We propose a method for removing interference and noise to estimate target information. In wireless channels, information signals are subject to interference and noise, making it is difficult to accurately estimate the desired signal. To estimate the desired information signal, it is essential to remove the noise and interference from the received signal, extracting only the desired signal. If the received signal noise and interference are not removed, the estimated information signal will have a large error in distance and direction, and the exact location of the target cannot be estimated. This study aims to accurately estimate the desired target in space. The objective is to achieve more presice target estimation than existing methods and enhance target resolution.An estimation method is proposed to improve the accuracy of target estimation. The proposed target estimation method obtains optimal weights using linear constraints and the minimum variance method. Through simulation, the performance of the proposed method and the existing method is analyzed. The proposed method successfully estimated all four targets, while the existing method only estimated two targets. The results show that the proposed method has better resolutiopn and superior estimation capability than the existing method.

• Steel and Composite Structures
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• v.47 no.1
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• pp.1-17
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• 2023

This paper deals with the free vibration behavior of rotating composite beams reinforced with carbon nanotubes (CNTs) under uniform thermal loads. The temperature-dependent beam material is assumed to be a mixture of single-walled carbon nanotubes (SWCNTs) in an isotropic matrix and five different functionally graded (FG) distributions of CNTs are considered according to the variation along the thickness, namely the UD-uniform, FG-O, FG-V, FG-Λ and FG-X distributions where FG-V and FG-Λ are unsymmetrical patterns. Considering the Timoshenko beam theory (TBT), a new finite element formulation of functionally graded carbon nanotube reinforced composite (FGCNTRC) beam is created for the first time. And the effects of several essential parameters including rotational speed, hub radius, effective material properties, slenderness ratio, boundary conditions, thermal force and moments due to temperature variation are considered in the formulation. By implementing different boundary conditions, some new results of both symmetric and non-symmetrical distribution patterns are presented in tables and figures to be used as benchmark for further validation. In addition, as an alternative advanced composite application for rotating systems exposed to thermal load, the positive effects of CNT addition in improving the dynamic performance of the system have been observed and the results are presented in several tables and figures.