• Journal of the Earthquake Engineering Society of Korea
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• v.20 no.6
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• pp.379-389
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• 2016

This study intends to evaluate the conservativeness of the fixed-base analysis as compared to the soil-structure interaction (SSI) analysis for the seismically isolated model of a nuclear power plant in Korea. To that goal, the boundary reaction method (BRM), combining frequency-domain and time-domain analyses in a twofold process, is adopted for the SSI analysis considering the nonlinearity of the seismic base isolation. The program KIESSI-3D is used for computing the reaction forces in the frequency domain and the program MIDAS/Civil is applied for the nonlinear time-domain analysis. The BRM numerical model is verified by comparing the results of the frequency-domain analysis and time-domain analysis for the soil-structure system with an equivalent linear base isolation model. Moreover, the displacement response of the base isolation and the horizontal response at the top of the structure obtained by the nonlinear SSI analysis using BRM are compared with those obtained by the fixed-base analysis. The comparison reveals that the fixed-base analysis provides conservative peak deformation for the base isolation but is not particularly conservative in term of the floor response spectrum of the superstructure.

• International Journal of Computer Science & Network Security
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• v.23 no.3
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• pp.177-186
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• 2023

Hyperspectral imaging technology is one of the most efficient and fast-growing technologies in recent years. Hyperspectral image (HSI) comprises contiguous spectral bands for every pixel that is used to detect the object with significant accuracy and details. HSI contains high dimensionality of spectral information which is not easy to classify every pixel. To confront the problem, we propose a novel RGB channel Assimilation for classification methods. The color features are extracted by using chromaticity computation. Additionally, this work discusses the classification of hyperspectral image based on Domain Transform Interpolated Convolution Filter (DTICF) and 3D-CNN with Bi-directional-Long Short Term Memory (Bi-LSTM). There are three steps for the proposed techniques: First, HSI data is converted to RGB images with spatial features. Before using the DTICF, the RGB images of HSI and patch of the input image from raw HSI are integrated. Afterward, the pair features of spectral and spatial are excerpted using DTICF from integrated HSI. Those obtained spatial and spectral features are finally given into the designed 3D-CNN with Bi-LSTM framework. In the second step, the excerpted color features are classified by 2D-CNN. The probabilistic classification map of 3D-CNN-Bi-LSTM, and 2D-CNN are fused. In the last step, additionally, Markov Random Field (MRF) is utilized for improving the fused probabilistic classification map efficiently. Based on the experimental results, two different hyperspectral images prove that novel RGB channel assimilation of DTICF-3D-CNN-Bi-LSTM approach is more important and provides good classification results compared to other classification approaches.

• Journal of the Korean Mathematical Society
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• v.54 no.2
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• pp.461-477
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• 2017

A dual substructuring method with a penalty term was introduced in the previous works by the authors, which is a variant of the FETI-DP method. The proposed method imposes the continuity not only by using Lagrange multipliers but also by adding a penalty term which consists of a positive penalty parameter ${\eta}$ and a measure of the jump across the interface. Due to the penalty term, the proposed iterative method has a better convergence property than the standard FETI-DP method in the sense that the condition number of the resulting dual problem is bounded by a constant independent of the subdomain size and the mesh size. In this paper, a further study for a dual iterative substructuring method with a penalty term is discussed in terms of its convergence analysis. We provide an improved estimate of the condition number which shows the relationship between the condition number and ${\eta}$ as well as a close spectral connection of the proposed method with the FETI-DP method. As a result, a choice of a moderately small penalty parameter is guaranteed.

• 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.

• Journal of KIISE:Software and Applications
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• v.33 no.8
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• pp.718-729
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• 2006

There has been increasing interest in automatic term recognition (ATR), which recognizes technical terms for given domain specific texts. ATR is composed of 'term extraction', which extracts candidates of technical terms and 'term selection' which decides whether terms in a term list derived from 'term extraction' are technical terms or not. 'term selection' is a process to rank a term list depending on features of technical term and to find the boundary between technical term and general term. The previous works just use statistical features of terms for 'term selection'. However, there are limitations on effectively selecting technical terms among a term list using the statistical feature. The objective of this paper is to find effective features for 'term selection' by considering various aspects of technical terms. In order to solve the ranking problem, we derive various features of technical terms and combine the features using machine-learning algorithms. For solving the boundary finding problem, we define it as a binary classification problem which classifies a term in a term list into technical term and general term. Experiments show that our method records 78-86% precision and 87%-90% recall in boundary finding, and 89%-92% 11-point precision in ranking. Moreover, our method shows higher performance than the previous work's about 26% in maximum.

• Journal of Positioning, Navigation, and Timing
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• v.5 no.4
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• pp.203-211
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• 2016

A Satellite Based Augmentation System (SBAS) is a system that provides positioning information with high and accurate reliability to users who require ensuring high safety such as airplane taking off and landing. A continuous performance evaluation on navigation safety facilities shall be performed to determine whether developed systems meet the required performance before and after the operation. In this paper, SBAS position domain analysis is discussed in relation to analysis items for performance evaluation. The performance evaluation on the SBAS in the position domain shall conduct analysis on accuracy, integrity, continuity, and availability, which are items in the required navigation performance (RNP). In the paper, position domain analysis was conducted with regard to the Wide Area Augmentation System (WAAS) in the USA and the European Geostationary Navigation Overlay Service (EGNOS), which were developed already and now under operation. The analysis result showed that each of the systems satisfied the APV-I performance requirements recommended by the International Civil Aviation Organization (ICAO) with regard to daily data. It is necessary to verify using long-term data, whether the performance requirements in the RNP items are satisfied for system certification.

• Journal of Korean Association for Spatial Structures
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• v.22 no.2
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• pp.57-64
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• 2022

In this paper, the physical model and governing equations of a shallow arch with a moving boundary were studied. A model with a moving boundary can be easily found in a long span retractable roof, and it corresponds to a problem of a non-cylindrical domain in which the boundary moves with time. In particular, a motion equation of a shallow arch having a moving boundary is expressed in the form of an integral-differential equation. This is expressed by the time-varying integration interval of the integral coefficient term in the arch equation with an un-movable boundary. Also, the change in internal force due to the moving boundary is also considered. Therefore, in this study, the governing equation was derived by transforming the equation of the non-cylindrical domain into the cylindrical domain to solve this problem. A governing equation for vertical vibration was derived from the transformed equation, where a sinusoidal function was used as the orthonormal basis. Terms that consider the effect of the moving boundary over time in the original equation were added in the equation of the transformed cylindrical problem. In addition, a solution was obtained using a numerical analysis technique in a symmetric mode arch system, and the result effectively reflected the effect of the moving boundary.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.2
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• pp.348-369
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• 2024

With the advancement of Industry 4.0 and Industrial Internet of Things (IIoT), manufacturing increasingly seeks automation and intelligence. Temperature and vibration monitoring are essential for machinery health. Traditional abnormal state detection methodologies often overlook the intricate frequency characteristics inherent in vibration time series and are susceptible to erroneously reconstructing temperature abnormalities due to the highly similar waveforms. To address these limitations, we introduce synergistic, end-to-end, unsupervised Frequency-Time Domain Memory-Enhanced Autoencoders (FTD-MAE) capable of identifying abnormalities in both temperature and vibration datasets. This model is adept at accommodating time series with variable frequency complexities and mitigates the risk of overgeneralization. Initially, the frequency domain encoder processes the spectrogram generated through Short-Time Fourier Transform (STFT), while the time domain encoder interprets the raw time series. This results in two disparate sets of latent representations. Subsequently, these are subjected to a memory mechanism and a limiting function, which numerically constrain each memory term. These processed terms are then amalgamated to create two unified, novel representations that the decoder leverages to produce reconstructed samples. Furthermore, the model employs Spectral Entropy to dynamically assess the frequency complexity of the time series, which, in turn, calibrates the weightage attributed to the loss functions of the individual branches, thereby generating definitive abnormal scores. Through extensive experiments, FTD-MAE achieved an average ACC and F1 of 0.9826 and 0.9808 on the CMHS and CWRU datasets, respectively. Compared to the best representative model, the ACC increased by 0.2114 and the F1 by 0.1876.

• Journal of the Korea Society of Computer and Information
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• v.21 no.8
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• pp.85-94
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• 2016

The purpose of this research is to clarify the effect that group art therapy with ceramics affects aggression and impulse for juvenile delinquent. The experimental domain of this study was implemented with 24 juvenile delinquent suspended from protective dispositions for them who were in long-term juvenile sheltered housing about for 12 years. These subjects were selected from among juvenile delinquent between 14 to 20 years age who were entrusted from court to the Juvenile Protection Education Institute located in G area. 12 people were randomly assigned each experimental domain and control domain; experimental group was implemented group art therapy with ceramics whereas there was anything to control group. The program was designed once a week and 90minutes each 12 sessions. The result of this study show that control group at variable related aggression was not significantly changed at posttest. In case of experimental group, here was significantly changed as a whole, also sub factor such as physical aggression showed considerable change so that the first hypothesis was supported In addition, experimental group showed the considerable change at sub factor of motor impulsiveness so that the second hypothesis was supported whereas control group at impulse variable was not significantly changed during pretest and posttest. This study results conclude that the juvenile delinquent participating group art therapy with ceramics represents the effect on reduction of aggression and motor impulsiveness. We expect this result will be used as further base line data for juvenile delinquent.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.28 no.11
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• pp.872-879
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• 2017

This work presents a cable fault monitoring system based on the differential frequency domain reflectometry using a compact impedance analyser which is composed of a direct digital synthesizer, an op amp and a gain/phase detector with a micro controller. The proposed system can replace expensive vector network analysers for frequency domain reflectometry and therefore be deployed in sensor networks for long term multi-point cable monitoring. Effectiveness of the system is experimentally confirmed by diagnosing the status of the power cable.