• Smart Structures and Systems
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• v.26 no.5
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• pp.591-603
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• 2020

Dynamic deflection monitoring is an essential and critical part of structural health monitoring for high-speed railway bridges. Two critical problems need to be addressed when using inclinometer sensors for such applications. These include constructing a general representation model of inclination-deflection and addressing the ill-posed inverse problem to obtain the accurate dynamic deflection. This paper provides a dynamic deflection monitoring method with the placement of optimal inclinometer sensors for high-speed railway bridges. The deflection shapes are reconstructed using the inclination-deflection transformation model based on the differential relationship between the inclination and displacement mode shape matrix. The proposed optimal sensor configuration can be used to select inclination-deflection transformation models that meet the required accuracy and stability from all possible sensor locations. In this study, the condition number and information entropy are employed to measure the ill-condition of the selected mode shape matrix and evaluate the prediction performance of different sensor configurations. The particle swarm optimization algorithm, genetic algorithm, and artificial fish swarm algorithm are used to optimize the sensor position placement. Numerical simulation and experimental validation results of a 5-span high-speed railway bridge show that the reconstructed deflection shapes agree well with those of the real bridge.

• Journal of Applied Biological Chemistry
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• v.59 no.4
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• pp.317-322
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• 2016

UV exposure induces matrix metalloproteinases (MMPs) and extracellular matrix-degrading enzymes expression. We studied the protective effect of Rubus occidentalis seed against UVB-generated skin photoaging using human fibroblast cells (CCD-986sk). We used an ELISA kit to measure the supernatents of procollagen type I and MMP-1 in CCD-986sk cells after they were exposed to UVB irradiation. The CCD-986sk cells that were used with RC-E/E after the UVB irradiation caused higher levels of type I procollagen and lesser levels of MMP-1 compared with the control group. Furthermore, the RC-E/E treated group showed lesser MMP-1 levels and higher procollagen type I levels than the untreated counterpart. Therefore, it can be concluded that Rubus occidentalis seed can prevent from skin photoaging.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.3
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• pp.188-192
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• 2012

In this study, a carbon nanotube (CNT) flexible strain sensor was fabricated with CNT based epoxy and rubber composites for tactile sensing. The flexible strain sensor can be fabricated as a long fibrous sensor and it also may be able to measure large deformation and contact information on a structure. The long and flexible sensor can be considered to be a continuous sensor like a dendrite of a neuron in the human body and we named the sensor as a biomimetic artificial neuron. For the application of the neuron in biomimetic engineering, an ANMS (Artificial Neuron Matrix System) was developed by means of the array of the neurons with a signal processing system. Moreover, a strain positioning algorithm was also developed to find localized tactile information of the ANMS with Labview for the application of an artificial e-skin.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.40 no.2
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• pp.10-18
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• 2003

This paper presents a method for designing guaranteed cost fuzzy filter with a desired H$_{\infty}$ disturbance rejection constraint of delayed fuzzy dynamic systems. This method not only guarantees an induced L$_2$ norm bound constraint on disturbance attenuation, but also minimizes an upper bound on a linear quadratic performance measure. A sufficient condition for the existence of guaranteed cost fuzzy filter with H$_{\infty}$ constraint is then presented in terms of linear matrix inequalities(LMIs). A simulation example is given to illustrate the design procedures and performances of the proposed methods.

• Journal of Magnetics
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• v.22 no.1
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• pp.34-42
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• 2017

Material defects in the Steam Generator Tubes (SGT) of sodium cooled fast breeder reactor (PFBR) can lead to leakage of water into sodium. The water and sodium reaction will lead to major accidents. Therefore, the examination of steam generator tubes for the early detection of defects is an important requirement for safety and economic considerations. In this work, the Magnetic Flux Leakage (MFL) based Non Destructive Testing (NDT) technique is used to perform the defect detection process. The rectangular notch defects on the outer surface of steam generator tubes are modeled using COMSOL multiphysics 4.3a software. The obtained MFL images are de-noised to improve the integrity of flaw related information. Grey Level Co-occurrence Matrix (GLCM) features are extracted from MFL images and taken as input parameter to train the neural network. A comparative study on characterization have been carried out using feed-forward back propagation (FFBP) and cascade-forward back propagation (CFBP) algorithms. The results of both algorithms are evaluated with Mean Square Error (MSE) as a prediction performance measure. The average percentage error for length, depth and width are also computed. The result shows that the feed-forward back propagation network model performs better in characterizing the defects.

• Journal of Power Electronics
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• v.13 no.6
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• pp.1080-1089
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• 2013

In this paper, the superposition principle of a heat sink temperature rise is verified based on the mathematical model of a plate-fin heat sink with two mounted heat sources. According to this, the distributed coupling thermal impedance matrix for a heat sink with multiple devices is present, and the equations for calculating the device transient junction temperatures are given. Then methods to extract the heat sink thermal impedance matrix and to measure the Epoxy Molding Compound (EMC) surface temperature of the power Metal Oxide Semiconductor Field Effect Transistor (MOSFET) instead of the junction temperature or device case temperature are proposed. The new thermal impedance model for the power converters in Switched Reluctance Motor (SRM) drivers is implemented in MATLAB/Simulink. The obtained simulation results are validated with experimental results. Compared with the Finite Element Method (FEM) thermal model and the traditional thermal impedance model, the proposed thermal model can provide a high simulation speed with a high accuracy. Finally, the temperature rise distributions of a power converter with two control strategies, the maximum junction temperature rise, the transient temperature rise characteristics, and the thermal coupling effect are discussed.

• International Journal of Quality Innovation
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• v.4 no.2
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• pp.101-122
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• 2003

With the development of the American Customer satisfaction index (ACSI), research on customer satisfaction measurement or evaluation methods have become significant in the last decade. Most of international customer satisfaction barometers or indices are evolved based on the cause and effect relationship model of ACSI. Of critical importance to validity of customer satisfaction indices is how to construct a measurement attribute or indicator model and provide an effective implementation method effectively. Quality Function Deployment (QFD) is a very useful tool for translating the customer voice into product design through quality engineering. In fact, this is a methodology for measuring and analyzing evaluation indicators by their relationship matrix. In this paper, we will make an effort to integrate the framework of QFD into the measurement problem of customer satisfaction, and also develop a new multi-phase QFD model for evaluation of Customer Satisfaction Index (CSI). From the houses of quality in this model, the evaluation indicators impacting on customer's global satisfaction are identified by means of their relationship matrix. Then the evaluation indicator hierarchy and its measurement method for the customer satisfaction index are presented graphically. Furthermore, survey data from the Chinese automobile maintenance sector and a relevant case study are utilized to show the implementation method of the QFD model used to measure and analyze of customer satisfaction.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.20 no.4
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• pp.1146-1153
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• 1996

The properties of FRP(fiber-reinforced plastics) depend not only on the characteristics of the matrix but also on the structure of fiber mat and the fiber type of reinforcement. Therefore it is very important to study the characteristics of reinforcement and matrix. In this paper, a method is proposed which can be used to measure the mean coeffcient of separation for the press molding of FRP, and the mean equivalent coefficient of separation is obtained from the separation coefficient. And the relationship between the mean equivalent coefficient of separation and the structure of fiber mat is discussed. The effects of corrlelation coefficient between separation and orientation on the mean equivalent coefficient are also presented.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.5
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• pp.2381-2399
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• 2019

Traditional recommendation algorithms on Collaborative Filtering (CF) mainly focus on the rating prediction with explicit ratings, and cannot be applied to the top-N recommendation with implicit feedbacks. To tackle this problem, we propose a new collaborative filtering approach namely Maximize MAP with Matrix Factorization (MFMAP). In addition, in order to solve the problem of non-smoothing loss function in learning to rank (LTR) algorithm based on pairwise, we also propose a smooth MAP measure which can be easily implemented by standard optimization approaches. We perform experiments on three different datasets, and the experimental results show that the performance of MFMAP is significantly better than other recommendation approaches.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.784-791
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• 2022

Tack coat is a thin layer of asphalt between the existing pavement and asphalt overlay. During construction, insufficient tack coat layering can later cause surface defects such as slippage, shoving, and rutting. This paper proposed a method for tack coat inspection improvement using an unmanned aerial vehicle (UAV) and deep learning neural network for automatic non-uniform assessment of the applied tack coat area. In this method, the drone-captured images are exploited for assessment using a combination of Mask R-CNN and Grey Level Co-occurrence Matrix (GLCM). Mask R-CNN is utilized to detect the tack coat region and segment the region of interest from the surroundings. GLCM is used to analyze the texture of the segmented region and measure the uniformity and non-uniformity of the tack coat on the existing pavements. The results of the field experiment showed both the intersection over union of Mask R-CNN and the non-uniformity measured by GLCM were promising with respect to their accuracy. The proposed method is automatic and cost-efficient, which would be of value to state Departments of Transportation for better management of their work in pavement construction and rehabilitation.