Including Vibration Characteristics Within Compressive Sensing Formulations for Structural Monitoring of Beams

2017 ◽  
Author(s):  
Vaahini Ganesan ◽  
Tuhin K. Das ◽  
Jeffrey L. Kauffman ◽  
Nazanin Rahnavard
Keyword(s):  
Boundary Conditions ◽  
Compressive Sensing ◽  
Continuous Monitoring ◽  
Structural Changes ◽  
Vibration Monitoring ◽  
High Data ◽  
Data Volume ◽  
Spatial Domains ◽  
Temporal And Spatial ◽  
Detection And Localization

Vibration-based monitoring of mechanical structures often involves continuous monitoring that result in high data volume and instrumentation with a large array of sensors. Previously, we have shown that Compressive Sensing (CS)-based vibration monitoring can significantly reduce both volume of data and number of sensors in temporal and spatial domains respectively. In this work, further analysis of CS-based detection and localization of structural changes is presented. Incorporating damping and noise handling in the CS algorithm improved its performance for frequency recovery. CS-based reconstruction of deflection shape of beams with fixed boundary conditions is addressed. Formulation of suitable bases with improved conditioning is explored. Restricting hyperbolic terms to lower frequencies in the basis functions improves reconstruction. An alternative is to generate an augmented basis that combines harmonic and hyperbolic terms. Incorporating known boundary conditions into the CS problem is studied.

scholarly journals Evidence toward the potential absence of relationship between temporal and spatial heartbeats perception

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Betka Sophie ◽  
Łukowska Marta ◽  
Silva Marta ◽  
King Joshua ◽  
Garfinkel Sarah ◽  
...  
Keyword(s):  
Bayesian Statistics ◽  
State Anxiety ◽  
Discrimination Task ◽  
Spatial Perception ◽  
The Body ◽  
Temporal Perception ◽  
Heartbeat Perception ◽  
Sampling Locations ◽  
Spatial Domains ◽  
Temporal And Spatial

AbstractMany interoceptive tasks (i.e. measuring the sensitivity to bodily signals) are based upon heartbeats perception. However, the temporal perception of heartbeats—when heartbeats are felt—varies among individuals. Moreover, the spatial perception of heartbeats—where on the body heartbeats are felt—has not been characterized in relation to temporal. This study used a multi-interval heartbeat discrimination task in which participants judged the timing of their own heartbeats in relation to external tones. The perception of heartbeats in both time and spatial domains, and relationship between these domains was investigated. Heartbeat perception occurred on average ~ 250 ms after the ECG R-wave, most frequently sampled from the left part of the chest. Participants’ confidence in discriminating the timing of heartbeats from external tones was maximal at 0 ms (tone played at R-wave). Higher confidence was related to reduced dispersion of sampling locations, but Bayesian statistics indicated the absence of relationship between temporal and spatial heartbeats perception. Finally, the spatial precision of heartbeat perception was related to state-anxiety scores, yet largely independent of cardiovascular parameters. This investigation of heartbeat perception provides fresh insights concerning interoceptive signals that contribute to emotion, cognition and behaviour.

scholarly journals Compressive Sensing Based Sampling and Reconstruction for Wireless Sensor Array Network

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Ming Yin ◽  
Kai Yu ◽  
Zhi Wang
Keyword(s):  
Compressive Sensing ◽  
Sensor Array ◽  
Superior Performance ◽  
Wireless Sensor ◽  
Prototype System ◽  
Reconstruction Method ◽  
Compressed Sampling ◽  
Data Volume ◽  
Simulation Results ◽  
Sparsity Structure

For low-power wireless systems, transmission data volume is a key property, which influences the energy cost and time delay of transmission. In this paper, we introduce compressive sensing to propose a compressed sampling and collaborative reconstruction framework, which enables real-time direction of arrival estimation for wireless sensor array network. In sampling part, random compressed sampling and 1-bit sampling are utilized to reduce sample data volume while making little extra requirement for hardware. In reconstruction part, collaborative reconstruction method is proposed by exploiting similar sparsity structure of acoustic signal from nodes in the same array. Simulation results show that proposed framework can reach similar performances as conventional DoA methods while requiring less than 15% of transmission bandwidth. Also the proposed framework is compared with some data compression algorithms. While simulation results show framework’s superior performance, field experiment data from a prototype system is presented to validate the results.

scholarly journals Assessing the Effect of Drought on Winter Wheat Growth Using Unmanned Aerial System (UAS)-Based Phenotyping

2021 ◽  
Vol 13 (6) ◽  
pp. 1144
Author(s):  
Mahendra Bhandari ◽  
Shannon Baker ◽  
Jackie C. Rudd ◽  
Amir M. H. Ibrahim ◽  
Anjin Chang ◽  
...  
Keyword(s):  
Winter Wheat ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Vegetation Indices ◽  
Grain Filling ◽  
Unmanned Aerial Systems ◽  
High Temporal Resolution ◽  
Wheat Growth ◽  
Spatial Domains ◽  
Temporal And Spatial

Drought significantly limits wheat productivity across the temporal and spatial domains. Unmanned Aerial Systems (UAS) has become an indispensable tool to collect refined spatial and high temporal resolution imagery data. A 2-year field study was conducted in 2018 and 2019 to determine the temporal effects of drought on canopy growth of winter wheat. Weekly UAS data were collected using red, green, and blue (RGB) and multispectral (MS) sensors over a yield trial consisting of 22 winter wheat cultivars in both irrigated and dryland environments. Raw-images were processed to compute canopy features such as canopy cover (CC) and canopy height (CH), and vegetation indices (VIs) such as Normalized Difference Vegetation Index (NDVI), Excess Green Index (ExG), and Normalized Difference Red-edge Index (NDRE). The drought was more severe in 2018 than in 2019 and the effects of growth differences across years and irrigation levels were visible in the UAS measurements. CC, CH, and VIs, measured during grain filling, were positively correlated with grain yield (r = 0.4–0.7, p < 0.05) in the dryland in both years. Yield was positively correlated with VIs in 2018 (r = 0.45–0.55, p < 0.05) in the irrigated environment, but the correlations were non-significant in 2019 (r = 0.1 to −0.4), except for CH. The study shows that high-throughput UAS data can be used to monitor the drought effects on wheat growth and productivity across the temporal and spatial domains.

scholarly journals Large Dataset Classification Using Parallel Processing Concept

2020 ◽  
Vol 4 (4) ◽  
pp. 191
Author(s):  
Mohammad Aljanabi ◽  
Hind Ra'ad Ebraheem ◽  
Zahraa Faiz Hussain ◽  
Mohd Farhan Md Fudzee ◽  
Shahreen Kasim ◽  
...  
Keyword(s):  
Big Data Analytics ◽  
Large Data ◽  
Business Analytics ◽  
Healthcare Applications ◽  
Current Increase ◽  
High Data ◽  
Huge Data ◽  
Data Volume ◽  
Effective Decision Making ◽  
Experimental Findings

Much attention has been paid to large data technologies in the past few years mainly due to its capability to impact business analytics and data mining practices, as well as the possibility of influencing an ambit of a highly effective decision-making tools. With the current increase in the number of modern applications (including social media and other web-based and healthcare applications) which generates high data in different forms and volume, the processing of such huge data volume is becoming a challenge with the conventional data processing tools. This has resulted in the emergence of big data analytics which also comes with many challenges. This paper introduced the use of principal components analysis (PCA) for data size reduction, followed by SVM parallelization. The proposed scheme in this study was executed on the Spark platform and the experimental findings revealed the capability of the proposed scheme to reduce the classifiers’ classification time without much influence on the classification accuracy of the classifier.

scholarly journals Lateral boundary conditions for a local anisotropic ice-flow model

2002 ◽  
Vol 35 ◽  
pp. 503-509 ◽  
Author(s):  
Olivier Gagliardini ◽  
Jacques Meyssonnier
Keyword(s):  
Boundary Conditions ◽  
Flow Model ◽  
Ice Sheet ◽  
Lateral Boundary ◽  
Local Flow ◽  
Ice Flow ◽  
Lateral Boundary Conditions ◽  
Potential Applications ◽  
Two Dimensional Flow ◽  
Spatial Domains

AbstractA local two-dimensional flow model which accounts for the anisotropic behaviour of polar ice and the evolution of its strain-induced anisotropy is briefly reviewed. Due to its complexity, it is not yet possible to use this model to simulate the flow of a whole ice sheet, and its potential applications are presently restricted to limited spatial domains around existing drilling sites. In order to calculate the local flow of ice, boundary conditions must be applied on the lateral edges of the studied domain. Since these limits correspond to fictitious sections of the ice sheet, the type of boundary condition to adopt is not obvious. In the present paper, different kinds of boundary conditions of the Dirichlet type, applied at the lateral boundary of an idealized ice sheet of simplified geometry, are discussed. This will serve as a first step towards the coupling of the local flow model with a global ice-sheet flow model.

The Dynamic Boundaries of The Self: Serial Dependence In Embodied Sense of Agency

2021 ◽  
Author(s):  
Yoni Stern ◽  
Inbar Ben-Yehuda ◽  
Danny Koren ◽  
ADAM ZAIDEL ◽  
Roy Salomon
Keyword(s):  
The Self ◽  
Sense Of Agency ◽  
Embodied Experience ◽  
Serial Dependence ◽  
Actual Movement ◽  
Spatial Domains ◽  
Temporal And Spatial ◽  
Embodied Self ◽  
External Stimuli ◽  
Over Time

The feeling of control over one’s actions, termed the Sense of Agency (SoA), delineates one’s experience as an embodied self. Although, this embodied experience is typically perceived as stable over time, recent theoretical accounts highlight the experience-dependent and dynamic nature of the embodied self. In this study we examined how recent experiences modulate SoA (i.e., serial dependence), and disambiguated the unique contributions of previous stimuli and choices on subsequent SoA judgments. In addition, we examined whether these effects persist across different domains of perceptual alteration. We analyzed two independent datasets of the Virtual Hand (VH) task (N = 100 participants) in which a sensorimotor conflict is introduced between the presented visual feedback and the actual movement performed. In Dataset 1, which included only temporal alterations, we found that previous stimuli recalibrate current perception, increasing the likelihood of the current choice to be different than the previous choice. Whereas previous choices induce a repetition bias increasing the likelihood to repeat choices across trials. Thus, previous external stimuli and self-generated choices exert opposing influences on SoA. We replicated these findings in Dataset 2, in which the VH task was tested with alterations in both temporal and spatial domains. In addition, we discovered that previous stimuli from a different perceptual domain exert a recalibration effect similar to stimuli from the same domain. Thus, SoA is constantly shaped by our previous subjective choices and objective stimuli experienced even across different perceptual domains. This highlights how SoA may act as unifying construct organizing our experience of the self over time and across perceptual experiences.

scholarly journals Asymptotic boundary conditions for the analysis of hydrodynamic stability of flows in regions with open boundaries

2019 ◽  
Vol 34 (1) ◽  
pp. 15-29 ◽  
Author(s):  
Andrey V. Boiko ◽  
Kirill V. Demyanko ◽  
Yuri M. Nechepurenko
Keyword(s):  
Boundary Conditions ◽  
Hydrodynamic Stability ◽  
Constant Velocity ◽  
Eigenvalue Problems ◽  
Main Flow ◽  
New Approach ◽  
Asymptotic Boundary ◽  
Open Boundaries ◽  
Temporal And Spatial ◽  
Parallel Approximation

Abstract A new approach to formulation of asymptotic boundary conditions for eigenvalue problems arising in numerical analysis of hydrodynamic stability of such shear flows as boundary layers, separations, jets, wakes, characterized by almost constant velocity of the main flow outside the shear layer or layers is proposed and justified. This approach makes it possible to formulate and solve completely the temporal and spatial stability problems in the locally-parallel approximation, reducing them to ordinary algebraic eigenvalue problems.

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