60 resultados para Empirical Mode Decomposition, vibration-based analysis, damage detection, signal decomposition
Resumo:
Because of its superior time resolution, ultra-wide bandwidth (UWB) transmission can be a highly accurate technique for ranging in indoor localization systems. Nevertheless, the presence of obstructions may deteriorate the ranging performance of the system. Indoor environments are often densely populated with people. However, t h e effect of the human body presence has been scarcely investigated so far within the UWB ranging context. In this work, we investigate this effect by conducting UWB measurements and analyzing the ranging performance of the system. Two measurement campaigns were performed in the 3-5.5 GHz band, in an anechoic chamber and a laboratory environment. The range estimates were obtained by employing the threshold-based first peak detection technique. Analysis results revealed that the human body significantly attenuates the direct-path signal component. On the other hand, in this study it does not introduce a significant range error since the length difference between the diffracted paths around the body and the direct-path is less than the spatial resolution of the measurement setup. © 2012 IEEE.
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A homogenous detection of pathogen (Giardia lamblia cysts) based on the catalytic growth of gold nanoparticles (AuNPs) has been studied. In this study, centrifugal filters were employed as tools to concentrate and separate the pathogen cells, and moreover amplify the detection signal. The catalytic growth of gold nanoparticles was verified to be positively related to gold seeds concentration. On this basis, homogenous detection of the pathogenic bacteria in liquid phase was established by means of conjugating antibody to gold seeds. Under the given experimental condition, detection limit of G. lamblia cysts was determined as low as 1.088 × 103 cells ml-1. The additional nonspecific binding tests were also conducted to verify the detection specificity. This sensing platform has been proved to be a sensitive, reliable and simple method for large-scale pathogen detection, and provide valuable insight for the development of gold nanocrystals based colorimetric biosensors.
Resumo:
Scour around bridge foundations is one of the leading causes of bridge failure. Up until recently, the monitoring of this phenomenon was primarily based around using underwater instrumentation to monitor the progression of scour holes as they develop around foundation systems. Vibration-based damage detection techniques have been used to detect damage in bridge beams. The application of these vibration based methods to the detection of scour has come to the fore in research in recent years. This paper examines the effect that scour has on the frequency response of a driven pile foundation system, similar to those used to support road and rail bridges. The effect of scour on the vibration characteristics of the pile is examined using laboratory and field testing. It is clear that there is a very clear reduction in the natural frequency of the pile as the severity of scour increases. It is shown that by combining state-of-the-art geotechnical techniques with relatively simple finite element modelling approaches, it is possible to accurately predict the natural frequency of the pile for a given scour depth. Therefore, the paper proposes a method that would allow the estimation of scour depth for a given observed pile frequency.
Resumo:
Previous research on damage detection based on the response of a structure to a moving load has reported decay in accuracy with increasing load speed. Using a 3D vehicle – bridge interaction model, this paper shows that the area under the filtered acceleration response of the bridge increases with increasing damage, even at highway load speeds. Once a datum reading is established, the area under subsequent readings can be monitored and compared with the baseline reading, if an increase is observed it may indicate the presence of damage. The sensitivity of the proposed approach to road roughness and noise is tested in several damage scenarios. The possibility of identifying damage in the bridge by analysing the acceleration response of the vehicle traversing it is also investigated. While vehicle acceleration is shown to be more sensitive to road roughness and noise and therefore less reliable than direct bridge measurements, damage is successfully identified in favourable scenarios.
Resumo:
Freshwater and brackish microalgal toxins, such as microcystins, cylindrospermopsins, paralytic toxins, anatoxins or other neurotoxins are produced during the overgrowth of certain phytoplankton and benthic cyanobacteria, which includes either prokaryotic or eukaryotic microalgae. Although, further studies are necessary to define the biological role of these toxins, at least some of them are known to be poisonous to humans and wildlife due to their occurrence in these aquatic systems. The World Health Organization (WHO) has established as provisional recommended limit 1 μg of microcystin-LR per liter of drinking water. In this work we present a microsphere-based multi-detection method for five classes of freshwater and brackish toxins: microcystin-LR (MC-LR), cylindrospermopsin (CYN), anatoxin-a (ANA-a), saxitoxin (STX) and domoic acid (DA). Five inhibition assays were developed using different binding proteins and microsphere classes coupled to a flow-cytometry Luminex system. Then, assays were combined in one method for the simultaneous detection of the toxins. The IC50's using this method were 1.9 ± 0.1 μg L−1 MC-LR, 1.3 ± 0.1 μg L−1 CYN, 61 ± 4 μg L−1 ANA-a, 5.4 ± 0.4 μg L−1 STX and 4.9 ± 0.9 μg L−1 DA. Lyophilized cyanobacterial culture samples were extracted using a simple procedure and analyzed by the Luminex method and by UPLC–IT-TOF-MS. Similar quantification was obtained by both methods for all toxins except for ANA-a, whereby the estimated content was lower when using UPLC–IT-TOF-MS. Therefore, this newly developed multiplexed detection method provides a rapid, simple, semi-quantitative screening tool for the simultaneous detection of five environmentally important freshwater and brackish toxins, in buffer and cyanobacterial extracts.
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Energy harvesting from ambient vibration is a promising field, especially for applications in larger infrastructures such as bridges. These structures are more frequently monitored for damage detection because of their extended life, increased traffic load and environmental deterioration. In this regard, the possibility of sourcing the power necessary for the sensors from devices embedded in the structure, thus cutting the cost due to the management of battery replacing over the lifespan of the structure, is particularly attracting. Among others, piezoelectric devices have proven to be especially effective and easy to apply since they can be bonded to existing host structure. For these devices the energy harvesting capacity is achieved directly from the variation in the strain conditions from the surface of the structure. However these systems need to undergo significant research for optimisation of their harvesting capacity and for assessing the feasibility of application to various ranges of bridge span and load. In this regard scaled bridge prototypes can be effectively used not only to assess numerical models and studies in an inexpensive and repeatable way but also to test the electronic devices under realistic field conditions. In this paper the theory of physical similitude is applied to the design of bridge beams with embedded energy harvesting systems and health monitoring sensors. It will show both how bridge beams can be scaled in such a way to apply and test energy harvesting systems and 2) how experimental data from existing bridges can be applied to prototypes in a laboratory environment. The study will be used for assessing the reliability of the system over a train bridge case study undergoing a set load cycles and induced localised damage.
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Many of the bridges currently in use worldwide are approaching the end of their design lives. However, rehabilitating and extending the lives of these structures raises important safety issues. There is also a need for increased monitoring which has considerable cost implications for bridge management systems. Existing structural health monitoring (SHM) techniques include vibration-based approaches which typically involve direct instrumentation of the bridge and are important as they can indicate the deterioration of the bridge condition. However, they can be labour intensive and expensive. In the past decade, alternative indirect vibration-based approaches which utilise the response of a vehicle passing over a bridge have been developed. This paper investigates such an approach; a low-cost approach for the monitoring of bridge structures which consists of the use of a vehicle fitted with accelerometers on its axles. The approach aims to detect damage in the bridge while obviating the need for direct instrumentation of the bridge. Here, the effectiveness of the approach in detecting damage in a bridge is investigated using a simplified vehicle-bridge interaction (VBI) model in theoretical simulations and a scaled VBI model in a laboratory experiment. In order to identify the existence and location of damage, the vehicle accelerations are recorded and processed using a continuous Morlet wavelet transform and a damage index is established. A parametric study is carried out to investigate the effect of parameters such as the bridge span length, vehicle speed, vehicle mass, damage level and road surface roughness on the accuracy of results.
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As a newly invented parallel kinematic machine (PKM), Exechon has attracted intensive attention from both academic and industrial fields due to its conceptual high performance. Nevertheless, the dynamic behaviors of Exechon PKM have not been thoroughly investigated because of its structural and kinematic complexities. To identify the dynamic characteristics of Exechon PKM, an elastodynamic model is proposed with the substructure synthesis technique in this paper. The Exechon PKM is divided into a moving platform subsystem, a fixed base subsystem and three limb subsystems according to its structural features. Differential equations of motion for the limb subsystem are derived through finite element (FE) formulations by modeling the complex limb structure as a spatial beam with corresponding geometric cross sections. Meanwhile, revolute, universal, and spherical joints are simplified into virtual lumped springs associated with equivalent stiffnesses and mass at their geometric centers. Differential equations of motion for the moving platform are derived with Newton's second law after treating the platform as a rigid body due to its comparatively high rigidity. After introducing the deformation compatibility conditions between the platform and the limbs, governing differential equations of motion for Exechon PKM are derived. The solution to characteristic equations leads to natural frequencies and corresponding modal shapes of the PKM at any typical configuration. In order to predict the dynamic behaviors in a quick manner, an algorithm is proposed to numerically compute the distributions of natural frequencies throughout the workspace. Simulation results reveal that the lower natural frequencies are strongly position-dependent and distributed axial-symmetrically due to the structure symmetry of the limbs. At the last stage, a parametric analysis is carried out to identify the effects of structural, dimensional, and stiffness parameters on the system's dynamic characteristics with the purpose of providing useful information for optimal design and performance improvement of the Exechon PKM. The elastodynamic modeling methodology and dynamic analysis procedure can be well extended to other overconstrained PKMs with minor modifications.
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Android is becoming ubiquitous and currently has the largest share of the mobile OS market with billions of application downloads from the official app market. It has also become the platform most targeted by mobile malware that are becoming more sophisticated to evade state-of-the-art detection approaches. Many Android malware families employ obfuscation techniques in order to avoid detection and this may defeat static analysis based approaches. Dynamic analysis on the other hand may be used to overcome this limitation. Hence in this paper we propose DynaLog, a dynamic analysis based framework for characterizing Android applications. The framework provides the capability to analyse the behaviour of applications based on an extensive number of dynamic features. It provides an automated platform for mass analysis and characterization of apps that is useful for quickly identifying and isolating malicious applications. The DynaLog framework leverages existing open source tools to extract and log high level behaviours, API calls, and critical events that can be used to explore the characteristics of an application, thus providing an extensible dynamic analysis platform for detecting Android malware. DynaLog is evaluated using real malware samples and clean applications demonstrating its capabilities for effective analysis and detection of malicious applications.
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The mechanisms underlying the parsing of a spatial distribution of velocity vectors into two adjacent (spatially segregated) or overlapping (transparent) motion surfaces were examined using random dot kinematograms. Parsing might occur using either of two principles. Surfaces might be defined on the basis of similarity of motion vectors and then sharp perceptual boundaries drawn between different surfaces (continuity-based segmentation). Alternatively, detection of a high gradient of direction or speed separating the motion surfaces might drive the process (discontinuity-based segmentation). To establish which method is used, we examined the effect of blurring the motion direction gradient. In the case of a sharp direction gradient, each dot had one of two directions differing by 135°. With a shallow gradient, most dots had one of two directions but the directions of the remainder spanned the range between one motion-defined surface and the other. In the spatial segregation case the gradient defined a central boundary separating two regions. In the transparent version the dots were randomly positioned. In both cases all dots moved with the same speed and existed for only two frames before being randomly replaced. The ability of observers to parse the motion distribution was measured in terms of their ability to discriminate the direction of one of the two surfaces. Performance was hardly affected by spreading the gradient over at least 25% of the dots (corresponding to a 1° strip in the segregation case). We conclude that detection of sharp velocity gradients is not necessary for distinguishing different motion surfaces.
Resumo:
The purpose of this article is twofold. First, we introduce a novel definition of financial networks obtained from time series data from the stock market. Second, we demonstrate that these networks can be used as an index with the property to reflect critical states of the market, respectively, crashes sufficiently. Our work aims to advocate a network-based analysis in the context of the stock market, because such a collective phenomenon can not only be economically described by networks but also analyzed as demonstrated in this article. (C) 2010 Wiley Periodicals, Inc. Complexity 16: 24-33, 2010
Resumo:
Background. Differentiation of embryonic stem cells (ESCs) into specific cell types with minimal risk of teratoma formation could be efficiently directed by first reducing the differentiation potential of ESCs through the generation of clonal, self-renewing lineage-restricted stem cell lines. Efforts to isolate these stem cells are, however, mired in an impasse where the lack of purified lineage-restricted stem cells has hindered the identification of defining markers for these rare stem cells and, in turn, their isolation. Methodology/Principal Findings. We describe here a method for the isolation of clonal lineage-restricted cell lines with endothelial potential from ESCs through a combination of empirical and rational evidence-based methods. Using an empirical protocol that we have previously developed to generate embryo-derived RoSH lines with endothelial potential, we first generated E-RoSH lines from mouse ESC-derived embryoid bodies (EBs). Despite originating from different mouse strains, RoSH and E-RoSH lines have similar gene expression profiles (r(2) = 0.93) while that between E-RoSH and ESCs was 0.83. In silico gene expression analysis predicted that like RoSH cells, E-RoSH cells have an increased propensity to differentiate into vasculature. Unlike their parental ESCs, E-RoSH cells did not form teratomas and differentiate efficiently into endothelial-like cells in vivo and in vitro. Gene expression and FACS analysis revealed that RoSH and E-RoSH cells are CD9(hi), SSEA-1(-) while ESCs are CD9(lo), SSEA-1(+). Isolation of CD9(hi), SSEA-1(-) cells that constituted 1%-10% of EB-derived cultures generated an E-RoSH-like culture with an identical E-RoSH-like gene expression profile (r(2) = 0.95) and a propensity to differentiate into endothelial-like cells. Conclusions. By combining empirical and rational evidence-based methods, we identified definitive selectable surface antigens for the isolation and propagation of lineage-restricted stem cells with endothelial-like potential from mouse ESCs.
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Objective: Waveform analysis has been used to assess vascular resistance and predict cardiovascular events. We aimed to identify microvascular abnormalities in patients with impaired glucose tolerance (IGT) using ocular waveform analysis. The effects of pioglitazone were also assessed. Methods: Forty patients with IGT and twenty-four controls were studied. Doppler velocity recordings were obtained from the central retinal, ophthalmic and common carotid arteries, and sampled at 200 Hz. A discrete wavelet-based analysis method was employed to quantify waveforms. The resistive index (RI),was also determined. Patients with IGT were randomised to pioglitazone or placebo and measurements repeated after 12 weeks treatment. Results: In the ocular waveforms, significant differences in power spectra were observed in frequency band four (corresponding to frequencies between 6.25 and 12.50 Hz) between groups (p
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The integration of detailed information on feeding interactions with measures of abundance and body mass of individuals provides a powerful platform for understanding ecosystem organisation. Metabolism and, by proxy, body mass constrain the flux, turnover and storage of energy and biomass in food webs. Here, we present the first food web data for Lough Hyne, a species rich Irish Sea Lough. Through the application of individual-and size-based analysis of the abundance-body mass relationship, we tested predictions derived from the metabolic theory of ecology. We found that individual body mass constrained the flux of biomass and determined its distribution within the food web. Body mass was also an important determinant of diet width and niche overlap, and predator diets were nested hierarchically, such that diet width increased with body mass. We applied a novel measure of predator-prey biomass flux which revealed that most interactions in Lough Hyne were weak, whereas only a few were strong. Further, the patterning of interaction strength between prey sharing a common predator revealed that strong interactions were nearly always coupled with weak interactions. Our findings illustrate that important insights into the organisation, structure and stability of ecosystems can be achieved through the theoretical exploration of detailed empirical data.
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omega Ori (HD37490, HR1934) is a Be star known to have presented variations. In order to investigate the nature and origin of its short-term and mid-term variability, a study is performed of several spectral lines (Halpha, Hdelta, HeI 4471, 4713, 4921, 5876, 6678, CII 4267, 6578, 6583, Mg II 4481, Si III 4553 and Si II 6347), based on 249 high signal-to-noise high-resolution spectra taken with 8 telescopes over 22 consecutive nights during the MuSiCoS (Multi SIte COntinuous Spectroscopy) campaign in November-December 1998. The stellar parameters are revisited and the projected rotational velocity (v sin i = 179 km s(-1)) is redetermined using several methods. With the MuSiCoS 98 dataset, a time series analysis of line-profile variations (LPVs) is performed using the Restricted Local Cleanest (RLC) algorithm and a least squares method. The behaviour of the velocity of the centroid of the lines, the equivalent widths and the apparent vsini for several lines, as well as Violet and Red components of photospheric lines affected by emission (red He i lines, Si II 6347, CII 6578, 6583) are analyzed. The non-radial pulsation (NRP) model is examined using phase diagrams and the Fourier-Doppler Imaging (FDI) method. The LPVs are consistent with a NRP mode with l = 2 or 3, \m\ = 2 with frequency 1.03 cd(-1). It is shown that an emission line outburst occurred in the middle of the campaign. Two scenarios are proposed to explain the behaviour of a dense cloud, temporarily orbiting around the star with a frequency 0.46 c d(-1), in relation to the outburst.