Vision-based systems are promising tools for displacement measurement in civil structures, possessing advantages over traditional sensors instrumentation cost, installation efforts and capacity terms of frequency range spatial resolution. Approximately one hundred papers to date have appeared on this subject, investigating topics like system development improvement, the viability field applications potential structural condition assessment. The main contribution paper is present a literature...

Vision-based monitoring receives increased attention for measuring displacements of civil infrastructure such as towers and bridges. Currently, most field applications rely on artificial targets video processing convenience, leading to high installation effort focus only single-point displacement measurement, example, at mid-span a bridge. This study proposes low-cost non-contact vision-based system multipoint measurement based consumer-grade camera acquisition custom-developed package...

Optics-based tracking of civil structures is not new, due to historical application in surveying, but automated applications capable at rates that capture dynamic effects are now a hot research topic structural health monitoring. Recent innovations show promise true non-contacting monitoring capability avoiding the need for physically attached sensor arrays. The paper reviews recent experience using Imetrum Dynamic Station (DMS) commercial optics-based system on Humber Bridge and Tamar...

Information on deformation is critical for bridge condition evaluation, but accurate characterization, usually via discrete displacement measurements, remains a challenging task. Vision-based systems are promising tools, possessing advantages of easy installation, low cost, and adequate resolution in time frequency domains. However, vision-based monitoring faces several field challenges might fail to achieve the required level working performance some real-world test conditions (e.g.,...

Abstract Applying a subpixel refinement technique in vision‐based displacement sensing can significantly improve the measurement accuracy. However, digital image signals from camera are highly sensitive to drastically varying lighting conditions field measurements of structural displacement, causing pixels expressing tracking target have nonuniform grayscale intensity changes different recording video frames. Traditional feature points‐based techniques neither robust nor accurate enough this...

This paper proposes a randomized subspace learning based anomaly detector (RSLAD) for hyperspectral imagery (HSI). Improved from robust principal component analysis, the RSLAD assumes that background matrix is low-rank, and sparse with small portion of nonzero columns (i.e., column-wise). It also anomalies do not lie in column aims to find detect anomalies. First, random techniques including sampling Hadamard projections are implemented construct coarse reduced computational cost. Second,...

Multiple window (MW) time-frequency analysis (TFA) is a newly developed technique to estimate time-varying spectrum for random nonstationary signals with low bias and variance. In this paper, the authors describe application of MW-TFA techniques electroencephalogram (EEG) compare results those conventional spectrogram. They find that provides them not only variance (TF) distribution EEG but also TF coherence estimation between single realization recorded from two sites. performance using...

The engineering education and research sectors are interlinked, there exists a need within both for readily deployable low-cost systems. Smartphones affordable easy to use technology available almost everyone. Images or video frames taken with smartphone cameras, of structures subjected loadings, can be analysed measure structural deformations. Such applications very useful university students researchers when performing tests in laboratory environments. This paper investigates the...

Mapping sea ice and open water in the oceans is significant for many applications. Accurate robust classification methods of are demand by services. Convolutional neural networks (CNNs) becoming increasingly popular research communities due to availability large image datasets high-performance computing systems. As (ConvNets) have achieved great success on tasks, we pursue this method patches from synthetic aperture radar (SAR) imagery into water. In study use with three dimensions (HH...

Bridge displacement, particularly due to specific loading events, is increasingly seen as a data signal that potentially contains information useful for bridge management. The lack of convenient fixed reference location historically made displacement measurement challenging in field conditions, but recent developments image processing have enabled low-cost, camera-based measurements. Even so, logistical challenges remain. These include organising access locate the camera, stabilising camera...

Oscillatory states in the electroencephalogram (EEG) reflect rhythmic synchronous activity large networks of neurons. Time-frequency (TF) methods, which quantify spectral content EEG as a function time, are well suited tools for study spontaneous and induced changes oscillatory states. The use these methods provides insights into temporal dynamics both humans experimental animals, aids neuronal mechanisms that generate activity. Further TF coherence analysts, quantifies consistency phase...

Elevational gradients are the focus of development and evaluation general theories on biodiversity. However, elevational studies microorganisms underlying mechanisms remain understudied, especially at regional scales. Here, we examined stream bacterial fungal communities along an gradient 990-4600 m with a geographic distance up to 500 km in southeastern Tibetan Plateau further analyzed their patterns drivers three biodiversity indicators, including species richness, ecological uniqueness,...