• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.39 no.3
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• pp.218-224
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• 2011

A modal method is presented for the investigation of the effects of measurement errors in damage detection for dynamic structural systems. The structural modifications to the baseline system result in the response changes of the perturbed structure, which are measured to determine a unique system in the inverse problem of damage detection. If the numerical modal data are exact, mathematical programming techniques can be applied to obtain the accurate structural changes. In practice, however, the associated measurement errors are unavoidable, to some extent, and cause significant deviations from the correct perturbed system because of the intrinsic instability of eigenvalue problem. Hence, a self-equilibrating inverse system is allowed to drift in the close neighborhood of the measured data. A numerical example shows that iterative procedures can be used to search for the damaged structural elements. A small set of selected degrees of freedom is employed for practical applicability and computational efficiency.

• Journal of Information Science Theory and Practice
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• v.2 no.4
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• pp.31-48
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• 2014

The proliferation of many interactive Topic Detection and Tracking (iTDT) systems has motivated researchers to design systems that can track and detect news better. iTDT focuses on user interaction, user evaluation, and user interfaces. Recently, increasing effort has been devoted to user interfaces to improve TDT systems by investigating not just the user interaction aspect but also user and task oriented evaluation. This study investigates the combination of the bag of words and named entities approaches implemented in the iTDT interface, called Interactive Event Tracking (iEvent), including what TDT tasks these approaches facilitate. iEvent is composed of three components, which are Cluster View (CV), Document View (DV), and Term View (TV). User experiments have been carried out amongst journalists to compare three settings of iEvent: Setup 1 and Setup 2 (baseline setups), and Setup 3 (experimental setup). Setup 1 used bag of words and Setup 2 used named entities, while Setup 3 used a combination of bag of words and named entities. Journalists were asked to perform TDT tasks: Tracking and Detection. Findings revealed that the combination of bag of words and named entities approaches generally facilitated the journalists to perform well in the TDT tasks. This study has confirmed that the combination approach in iTDT is useful and enhanced the effectiveness of users' performance in performing the TDT tasks. It gives suggestions on the features with their approaches which facilitated the journalists in performing the TDT tasks.

• Smart Structures and Systems
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• v.20 no.6
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• pp.683-696
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• 2017

In this study, the reliability of nonlinear ultrasonic modulation based fatigue crack detection is improved using a feature-level data fusion approach. When two ultrasonic inputs at two distinct frequencies are applied to a specimen with a fatigue crack, modulation components at the summation and difference of these two input frequencies appear. First, the spectral amplitudes of the modulation components and their spectral correlations are defined as individual features. Then, a 2D feature space is constructed by combining these two features, and the presence of a fatigue crack is identified in the feature space. The effectiveness of the proposed fatigue crack detection technique is experimentally validated through cyclic loading tests of aluminum plates, full-scale steel girders and a rotating shaft component. Subsequently, the improved reliability of the proposed technique is quantitatively investigated using receiver operating characteristic analysis. The uniqueness of this study lies in (1) improvement of nonlinear ultrasonic modulation based fatigue crack detection reliability using feature-level data fusion, (2) reference-free fatigue crack diagnosis without using the baseline data obtained from the intact condition of the structure, (3) application to full-scale steel girders and shaft component, and (4) quantitative investigation of the improved reliability using receiver operating characteristic analysis.

• Smart Structures and Systems
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• v.18 no.3
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• pp.501-523
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• 2016

Electromechanical impedance (EMI) based structural health monitoring is performed by measuring the variation in the impedance due to the structural local damage. The impedance signals are acquired from the piezoelectric patches that are bonded on the structural surface. The impedance variation, which is directly related to the mechanical properties of the structure, indicates the presence of local structural damage. Two traditional EMI-based damage detection methods are based on calculating the difference between the measured impedance signals in the frequency domain from the baseline and the current structures. In this paper, a new structural damage detection approach by analyzing the time domain impedance responses is proposed. The measured time domain responses from the piezoelectric transducers will be used for analysis. With the use of the Time Frequency Autoregressive Moving Average (TFARMA) model, a damage index based on Singular Value Decomposition (SVD) is defined to identify the existence of the structural local damage. Experimental studies on a space steel truss bridge model in the laboratory are conducted to verify the proposed approach. Four piezoelectric transducers are attached at different locations and excited by a sweep-frequency signal. The impedance responses at different locations are analyzed with TFARMA model to investigate the effectiveness and performance of the proposed approach. The results demonstrate that the proposed approach is very sensitive and robust in detecting the bolt damage in the gusset plates of steel truss bridges.

• Smart Structures and Systems
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• v.31 no.4
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• pp.325-334
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• 2023

Computer vision-based damage detection enables non-contact, efficient and low-cost bridge health monitoring, which reduces the need for labor-intensive manual inspection or that for a large number of on-site sensing instruments. By leveraging recent semantic segmentation approaches, we can detect regions of critical structural components and identify damages at pixel level on images. However, existing methods perform poorly when detecting small and thin damages (e.g., cracks); the problem is exacerbated by imbalanced samples. To this end, we incorporate domain knowledge to introduce a hierarchical semantic segmentation framework that imposes a hierarchical semantic relationship between component categories and damage types. For instance, certain types of concrete cracks are only present on bridge columns, and therefore the noncolumn region may be masked out when detecting such damages. In this way, the damage detection model focuses on extracting features from relevant structural components and avoid those from irrelevant regions. We also utilize multi-scale augmentation to preserve contextual information of each image, without losing the ability to handle small and/or thin damages. In addition, our framework employs an importance sampling, where images with rare components are sampled more often, to address sample imbalance. We evaluated our framework on a public synthetic dataset that consists of 2,000 railway bridges. Our framework achieves a 0.836 mean intersection over union (IoU) for structural component segmentation and a 0.483 mean IoU for damage segmentation. Our results have in total 5% and 18% improvements for the structural component segmentation and damage segmentation tasks, respectively, compared to the best-performing baseline model.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.16
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• pp.6837-6842
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• 2014

Background: Northern Thailand is a region with a high cervical cancer incidence. Combined high-risk HPV (hrHPV) DNA testing and cytology (co-testing) has increasingly gained acceptance for cervical cancer screening. However, to our knowledge, data from a population-based screening using co-testing have not been available in this region. This study therefore aimed to evaluate the performance of cytology and hrHPV test in women in northern Thailand. Materials and Methods: Cervical samples were collected for hybrid capture 2 (HC2) testing and liquid-based cytology from women aged 30 to 60 years who were residents in 3 prefectures of Chiang Mai in northern Thailand between May and September 2011. Women with positive cytology were referred to colposcopy, while women with positive for HC2 only were followed for 2 years. Results: Of 2,752 women included in this study, 3.0% were positive in both tests, 4.1% for HC2 only, and 1.3% had positive cytology only. At baseline screening, positive HC2 was observed in 70.6% among cytology-positive women compared with 4.3% among cytology-negative women. The prevalence of positive HC2 or cytology peaked in the age group 35-39 years and was lowest in the age group 55-60 years. High-grade squamous intraepithelial lesion or worse lesions (HSIL+) were histologically detected in 23.5% of women with positive baseline cytology and in 9.8% of women with positive baseline HC2 only on follow-up. All women with histologic HSIL+ had positive baseline HC2. Conclusions: The hrHPV test is superior to cytology in the early detection of high-grade cervical epithelial lesions. In this study, the prevalence of histologic HSIL+ on follow-up of women with positive hrHPV test was rather high, and these women should be kept under careful surveillance. In northern Thailand, hrHPV testing has a potential to be used as a primary screening test for cervical cancer with cytology applied as a triage test.

• IEIE Transactions on Smart Processing and Computing
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• v.1 no.3
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• pp.161-170
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• 2012

This paper presents an efficient and robust approach for determining the correspondence between unbalanced stereo images. The disparity vectors were used instead of feature points, such as corners, to calculate a correspondence relationship. For a faster and optimal estimation, the vectors were classified into several regions, and the homography of each region was calculated using the RANSAC algorithm. The correspondence image was calculated from the images transformed by each homography. Although it provided good results under normal conditions, it was difficult to obtain reliable results in an unbalanced stereo pair. Therefore, a balancing method is also proposed to minimize the unbalance effects using the histogram specification and structural similarity index. The experimental results showed that the proposed approach outperformed the baseline algorithms with respect to the speed and peak-signal-to-noise ratio. This work can be applied to practical fields including 3D depth map acquisition, fast stereo coding, 2D-to-3D conversion, etc.

• Industrial Engineering and Management Systems
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• v.12 no.4
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• pp.380-388
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• 2013

Large variation in electrocardiogram (ECG) waveforms continues to present challenges in defining R-wave locations in ECG signals. This research presents a procedure to extract the R-wave locations by forward-backward (FB) algorithm and classify the arrhythmic beat conditions by using RR intervals. The FB algorithm shows forward and backward searching rules from QRS onset and eliminates lower-amplitude signals near the baseline using a statistical process control concept. The proposed algorithm was trained the optimal parameters by using MIT-BIH arrhythmia database (MITDB), and it was verified by actual Holter ECG signals from a local hospital. The signals are classified into normal (N) and three arrhythmia beat types including premature ventricular contraction (PVC), ventricular flutter/fibrillation (VF), and second-degree heart block (BII) beat. This work produces 98.54% accuracy in the detection of R-wave location; 98.68% for N beats; 91.17% for PVC beats; and 87.2% for VF beats in the collected Holter ECG signals, and the results are better than what are reported in literature.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.93-96
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• 2005

We propose a computationally efficient sphere decoding (SD) algorithm with smart radius control (SRC). As a baseline algorithm for SD, we consider the modified Schnorr-Euchner (SE) algorithm [1] (hereafter, called as the MSE algorithm). In principle, the radius after zero-forcing decision feedback equalization (ZF-DFE) estimation can be reduced further if we select a new lattice vector closer to the received signal vector than the lattice vector corresponding to the ZF-DFE estimate does. In our case, we obtain such a better lattice vector by performing a sequence of alternating one-dimensional searches, starting from the ZF-DFE estimate. We then develop a novel SRC algorithm that adopts adaptively the additional radius reduction process according to the estimated signal-to-noise-power ratio (SNR) after ZF-DFE estimation. In addition, we analyze the effect of detection ordering on the complexity for SD. Column-norm ordering of the channel matrix and optimal ordering [1] are considered here. From our analyses, we see that SRC can reduce greatly the complexity for SD and the degree of complexity reduction gets significant as the SNR decreases, irrespective of detection ordering schemes used.

• Food Science and Biotechnology
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• v.17 no.5
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• pp.1038-1046
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• 2008

This study was carried out to develop a small-sized biosensor based on surface plasmon resonance (SPR) for the rapid identification of insecticide residues for food safety. The SPR biosensor module consists of a single 770 nm-light emitting diodes (LED) light source, several optical lenses for transferring light, a hemisphere sensor chip, photo detector, A/D converter, power source, and software for signal processing using a computer. Except for the computer, the size and weight of the sensor module are 150 (L)$\times$70 (W)$\times$120 (H) mm and 828 g, respectively. Validation and application procedures were designed to assess refractive index analysis, affinity properties, sensitivity, linearity, limits of detection, and robustness which includes an analysis of baseline stability and reproducibility of ligand immobilization using carbamate (carbofuran and carbaryl) and organophosphate (cadusafos, ethoprofos, and chlorpyrifos) insecticide residues. With direct binding analysis, insecticide residues were detected at less than the minimum 0.01 ppm and analyzed in less than 100 sec with a good linear relationship. Based on these results, we find that the binding interaction with active target groups in enzymes using the miniaturized SPR biosensor could detect low concentrations which satisfy the maximum residue limits for pesticide tolerance in Korea, Japan, and the USA.