• Proceedings of the Computational Structural Engineering Institute Conference
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• 1998.04a
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• pp.127-134
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• 1998

The objectives of this paper is to analyze the reinforced concrete structures by using fiber model. In this study, the fiber modeling techniques including modeling of support conditions are studied. In order to verify the modeling techniques, analysis results obtained for reinforced concrete cantilever beam and reinforced concrete T-girder bridge under cyclic loading are compared with experimental results from full scale test. From the comparison, it is shown that the modeling techniques in this study can be well applied to the nonlinear failure analysis of reinforced concrete structures with porper modifications.

• Journal of the military operations research society of Korea
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• v.25 no.1
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• pp.133-140
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• 1999

Preprocessing for the -01 integer programming can reduce the size of problem instance as well as tighten its linear programming relaxations. In this research, the preprocessing techniques are classified into two categories. First, for the reduction of problem size, there are variable fixing and constraint elimination techniques. Second, for the reduction of feasible region, there are coefficient reduction and Euchidean reduction techniques. These methods are implemented and the effects are shown by experimental results.

• Journal of Electrical Engineering and Technology
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• v.10 no.4
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• pp.1886-1898
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• 2015

In today’s era of advanced technological developments, the threats to the authenticity and integrity of digital images, in a nutshell, the threats to the Image Forensics Research communities have also increased proportionately. This happened as even for the ‘non-expert’ forgers, the availability of image processing tools has become a cakewalk. This image forgery poses a great problem for judicial authorities in any context of trade and commerce. Block matching based image cloning detection system is widely researched over the last 2-3 decades but this was discouraged by higher computational complexity and more time requirement at the algorithm level. Thus, for reducing time need, various dimension reduction techniques have been employed. Since a single technique cannot cope up with all the transformations like addition of noise, blurring, intensity variation, etc. we employ multiple techniques to a single image. In this paper, we have used Fuzzy logic approach for decision making and getting a global response of all the techniques, since their individual outputs depend on various parameters. Experimental results have given enthusiastic elicitations as regards various transformations to the digital image. Hence this paper proposes Fuzzy based cloning detection and classification system. Experimental results have shown that our detection system achieves classification accuracy of 94.12%. Detection accuracy (DAR) while in case of 81×81 sized copied portion the maximum accuracy achieved is 99.17% as regards subjection to transformations like Blurring, Intensity Variation and Gaussian Noise Addition.

• Journal of Information Processing Systems
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• v.14 no.4
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• pp.807-823
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• 2018

Speaker verification system performance depends on the utterance of each speaker. To verify the speaker, important information has to be captured from the utterance. Nowadays under the constraints of limited data, speaker verification has become a challenging task. The testing and training data are in terms of few seconds in limited data. The feature vectors extracted from single frame size and rate (SFSR) analysis is not sufficient for training and testing speakers in speaker verification. This leads to poor speaker modeling during training and may not provide good decision during testing. The problem is to be resolved by increasing feature vectors of training and testing data to the same duration. For that we are using multiple frame size (MFS), multiple frame rate (MFR), and multiple frame size and rate (MFSR) analysis techniques for speaker verification under limited data condition. These analysis techniques relatively extract more feature vector during training and testing and develop improved modeling and testing for limited data. To demonstrate this we have used mel-frequency cepstral coefficients (MFCC) and linear prediction cepstral coefficients (LPCC) as feature. Gaussian mixture model (GMM) and GMM-universal background model (GMM-UBM) are used for modeling the speaker. The database used is NIST-2003. The experimental results indicate that, improved performance of MFS, MFR, and MFSR analysis radically better compared with SFSR analysis. The experimental results show that LPCC based MFSR analysis perform better compared to other analysis techniques and feature extraction techniques.

• The Journal of the Acoustical Society of Korea
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• v.15 no.2E
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• pp.76-84
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• 1996

The experimental testing results of the large-scale version of a forward-looking ultrasound imaging catheter(FLUIC) are presented, along with the fabrication techniques used, experimental methods, and comparisons of the measured and simulated results. The transducer model is verified by measuring the electrical impedance of the transducer. The pulse width, beamwidth, and the dynamic range for both transmit and pulse-echo response of the fabricated FLUIC are also analyzed. The experimental results conformed its forward-looking imaging capability and the sources of discrepancies between the simulated and experimental beam profiles are addressed.

• Journal of the Korean Society for information Management
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• v.11 no.2
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• pp.131-164
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• 1994

This study shows the design and implementation of cataloging expert system using pattern recognition techniques. This system attemps to demonstrate the feasibility of cataloging in KORMARC format from title page and copyright page without the intervention of humans. The prototype was implemented as a rule-based system in Turbo C. To demonstrate the function and capability of the system, experimental document-group and control document-group was analyzed. The hit ratio of experimental document-group is 94%. On the other hand, the hit ratio of control document-group is 93%, a little bit lower than the experimental group.

• Explosives and Blasting
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• v.38 no.3
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• pp.30-43
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• 2020

Rock dynamics is a relatively new discipline to study the mechanical behaviors of rock materials (or rock masses) under dynamic loading conditions. Many rock mechanics and rock engineering issues are concerned with the dynamic phenomena such as mining development, civil engineering, earthquake, military science, and various disasters. The significance of rock dynamic researches has been increased in these days. This paper introduces conventional experimental techniques for rock dynamic experimental methods and the particular characteristics of rock dynamic behaviors with several remarkable recent studies.

• Structural Engineering and Mechanics
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• v.45 no.6
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• pp.779-802
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• 2013

In this paper, adaptive neuro-fuzzy inference system (ANFIS) and artificial neural networks (ANNs) techniques are developed and applied to identify damage in a model steel girder bridge using dynamic parameters. The required data in the form of natural frequencies are obtained from experimental modal analysis. A comparative study is made using the ANNs and ANFIS techniques and results showed that both ANFIS and ANN present good predictions. However the proposed ANFIS architecture using hybrid learning algorithm was found to perform better than the multilayer feedforward ANN which learns using the backpropagation algorithm. This paper also highlights the concept of ANNs and ANFIS followed by the detail presentation of the experimental modal analysis for natural frequencies extraction.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.10a
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• pp.347-349
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• 2014

Model verification and validation (V&V) is a current research topic to build computational models with high predictive capability by addressing the general concepts, processes and statistical techniques. The hypothesis test for validity check is one of the model validation techniques and gives a guideline to evaluate the validity of a computational model when limited experimental data only exist due to restricted test resources (e.g., time and budget). The hypothesis test for validity check mainly employ Type I error, the risk of rejecting the valid computational model, for the validity evaluation since quantification of Type II error is not feasible for model validation. However, Type II error, the risk of accepting invalid computational model, should be importantly considered for an engineered products having high risk on predicted results. This paper proposes a technique named as the response-adaptive experimental design to reduce Type II error by adaptively designing experimental conditions for the validation experiment. A tire tread block problem and a numerical example are employed to show the effectiveness of the response-adaptive experimental design for the validity evaluation.

• Steel and Composite Structures
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• v.34 no.1
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• pp.35-51
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• 2020

Integral abutment bridges (IABs) are those bridges without expansion joints. A single row of steel H-piles (SHPs) is commonly used at the thin and stub abutments of IABs to form a flexible support system at the bridge ends to accommodate thermal-induced displacement of the bridge. Consequently, as the IAB expands and contracts due to temperature variations, the SHPs supporting the abutments are subjected to cyclic lateral (longitudinal) displacements, which may eventually lead to low-cycle fatigue (LCF) failure of the piles. In this paper, the potential of using finite element (FE) modeling techniques to estimate the LCF life of SHPs commonly used in IABs is investigated. For this purpose, first, experimental tests are conducted on several SHP specimens to determine their LCF life under thermal-induced cyclic flexural strains. In the experimental tests, the specimens are subjected to longitudinal displacements (or flexural strain cycles) with various amplitudes in the absence and presence of a typical axial load. Next, nonlinear FE models of the tested SHP specimens are developed using the computer program ANSYS to investigate the possibility of using such numerical models to predict the LCF life of SHPs commonly used in IABs. The comparison of FE analysis results with the experimental test results revealed that the FE analysis results are in close agreement with the experimental test results. Thus, FE modeling techniques similar to that used in this research study may be used to predict the LCF life of SHP commonly used in IABs.