• Smart Structures and Systems
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• v.5 no.6
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• pp.681-697
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• 2009

Limited, noisy data in vibration testing is a hindrance to the development of structural damage detection. This paper presents a method for optimizing sensor placement and performing damage detection using finite element model updating. Sensitivity analysis of the modal flexibility matrix determines the optimal sensor locations for collecting information on structural damage. The optimal sensor locations require the instrumentation of only a limited number of degrees of freedom. Using noisy modal data from only these limited sensor locations, a method based on model updating and changes in the flexibility matrix successfully determines the location and severity of the imposed damage in numerical simulations. In addition, a steel cantilever beam experiment performed in the laboratory that considered the effects of model error and noise tested the validity of the method. The results show that the proposed approach effectively and robustly detects structural damage using limited, optimal sensor information.

• Structural Engineering and Mechanics
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• v.60 no.6
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• pp.1039-1061
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• 2016

Based on Vlasov's torsional theory of open thin-walled members and the nonlinear constitutive relations of materials, a nonlinear analysis model to predict response of open thin-walled RC members subjected to pure torsion is proposed in the current study. The variation of the circulatory torsional stiffness and warping torsional stiffness over the entire loading process and the impact of warping shear deformation on the torsion-induced rotation of the member are considered in the formulation. The torque equilibrium differential equation is then solved by Runge-Kutta method. The proposed nonlinear model is then applied to predict the behavior of five U-shaped thin-walled RC members under pure torsion. Four of them were tested in an earlier experimental study by the authors and the testing data of the fifth one were reported in an existing literature. Results show that the analytical predictions based on the proposed model agree well with the experimental data of all five specimens. This clearly shows the validity of the proposed nonlinear model analyzing behavior of U-shaped thin-walled RC members under pure torsion.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.11
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• pp.4028-4042
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• 2021

Aiming at the problem of software defect prediction difficulty caused by insufficient software defect marker samples and unbalanced classification, a semi-supervised software defect prediction model based on a tri-training algorithm was proposed by combining feature normalization, over-sampling technology, and a Tri-training algorithm. First, the feature normalization method is used to smooth the feature data to eliminate the influence of too large or too small feature values on the model's classification performance. Secondly, the oversampling method is used to expand and sample the data, which solves the unbalanced classification of labelled samples. Finally, the Tri-training algorithm performs machine learning on the training samples and establishes a defect prediction model. The novelty of this model is that it can effectively combine feature normalization, oversampling techniques, and the Tri-training algorithm to solve both the under-labelled sample and class imbalance problems. Simulation experiments using the NASA software defect prediction dataset show that the proposed method outperforms four existing supervised and semi-supervised learning in terms of Precision, Recall, and F-Measure values.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.6
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• pp.1833-1848
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• 2022

Named entity recognition (NER) is an important basic task in the field of Natural Language Processing (NLP). Recently deep learning approaches by extracting word segmentation or character features have been proved to be effective for Chinese Named Entity Recognition (CNER). However, since this method of extracting features only focuses on extracting some of the features, it lacks textual information mining from multiple perspectives and dimensions, resulting in the model not being able to fully capture semantic features. To tackle this problem, we propose a novel Multi-view Semantic Feature Fusion Model (MSFM). The proposed model mainly consists of two core components, that is, Multi-view Semantic Feature Fusion Embedding Module (MFEM) and Multi-head Self-Attention Mechanism Module (MSAM). Specifically, the MFEM extracts character features, word boundary features, radical features, and pinyin features of Chinese characters. The acquired font shape, font sound, and font meaning features are fused to enhance the semantic information of Chinese characters with different granularities. Moreover, the MSAM is used to capture the dependencies between characters in a multi-dimensional subspace to better understand the semantic features of the context. Extensive experimental results on four benchmark datasets show that our method improves the overall performance of the CNER model.

• Structural Engineering and Mechanics
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• v.81 no.2
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• pp.163-178
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• 2022

This paper aimed to study the local bond-slip behavior between ultra-high-performance concrete (UHPC) and a reinforcing bar after exposure to high temperatures. A series of pull-out tests were carried out on cubic specimens of size 150×150×150 mm with deformed steel bar embedded for a fixed length of three times the diameter of the tested deformed bar. The experimental results of the bond stress-slip relationship were compared with the Euro-International Concrete Committee (CEB-Comite Euro-International du Beton)-International Federation for Prestressing (FIP-Federation Internationale de la Precontrainte) Model Code and with prediction models found in the literature. In addition, based on the test results, an empirical model of the bond stress-slip relationship was proposed. The evaluation and comparison results showed that the modified CEB-FIP Model code 2010 proposed by Aslani and Samali for the local bond stress-slip relationship for UHPC after exposure to high temperatures was more conservative. In contrast, for both room temperature and after exposure to high temperatures, the modified CEB-FIP Model Code 2010 local bond stress-slip model for UHPC proposed in this study was able to predict the test results with reasonable accuracy.

• Wind and Structures
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• v.21 no.1
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• pp.63-84
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• 2015

The shape of a tall building has significant impact on wind force generation and wind-induced dynamic response. To study the effect of recessed cavities, wind excitations on a wind-tunnel model of an H-section tall building were compared with those on a square-section building model. Characteristics of the fluctuating wind pressures on the side faces of the two tall buildings and their role in the generation of crosswind forces on the buildings were investigated with the space-time statistical tool of proper orthogonal decomposition (POD). This paper also compares the use of different pressure data sets for POD analysis in situations where pressures on two different surfaces are responsible for the generation of a wind force. The first POD mode is found to dominate the generation of crosswind excitation on the buildings.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.288_289
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• 2009

전력시스템은 시간이 지남에 따라서 부하의 증가와 다양한 설비기기의 투입, 지속적인 유지보수와 수요에 대한 예측이 필요하다. 이런 전력 시스템을 관리하기 위한 많은 애플리케이션들이 있으며 전력 시스템 애플리케이션을 위한 공통 정보모델 표준을 위한 IEC61970 국제 표준화 작업이 활발히 이루어지고 있다. 본 논문에서는 IEC61970 Part3 CIM(Common Information Model)의 적용을 위한 미들웨어 도입과 데이터베이스 모델 적용 방안에 대해서 알아본다.

• Proceedings of the KSME Conference
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• 2007.05a
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• pp.1037-1044
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• 2007

In an attempt to determine the correlations between the input acoustic impedance and the variations of the physical characteristics of the terminal elements, a five-lobe branched tube-network is mathematically developed and experimentally simulated using a lung simulator. The model takes into account some realistic conditions such as varying cross-sectional areas, flexible wall properties and branching. The effects of airway constrictions expressed by lobe stiffness variations on the impedance are determined for a range of frequencies up to 256 Hz. It is concluded that the developed model is capable of non-invasively predicting various physiological changes in the airway passages.

• The Korean Journal of Applied Statistics
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• v.24 no.5
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• pp.791-797
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• 2011

This paper considers the issue of seasonal cointegrating rank selection by information criteria as the extension of Cheng and Phillips (2009). The method does not require the specification of lag length in vector autoregression, is convenient in empirical work, and is in a semiparametric context because it allows for a general short memory error component in the model with only lags related to error correction terms. Some limit properties of usual information criteria are given for the rank selection and small Monte Carlo simulations are conducted to evaluate the performances of the criteria.

• Wind and Structures
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• v.8 no.2
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• pp.135-146
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• 2005

Divergent galloping-like motion of a dry inclined cable has been observed in a limited number of experimental studies, which, due to the uncertainties in its onset conditions, has induced serious concerns in the bridge stay cable design. A series of dynamic and static model wind tunnel tests have been carried out to confirm the existence of the phenomenon and clarify its excitation mechanism. The present paper focuses on exploring the spatial flow structure around an inclined cable. The pattern of resultant aerodynamic forces acting at different longitudinal locations of the model and the spatial correlation of the forces are examined. The results lead one step closer in revealing the physical nature of the phenomenon.