Continuous-time signal processing

Kinetic Step Box was developed with the purpose for analyzing body movements by detecting vertical Ground Reaction ForcesThe objective is to test on validity and reliability of vertical Ground Reaction Forces measurement from Kinetic Step Box compared with Standard Force Plate13 females and 7 males performed sitting to standing posture on Kinetic Step Box and Standard Force Plate for 3 sets of

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This dataset presents the acceleration values of the spreader with the attached containers that are being unloaded from a container ship, as well as detected impacts to the vertical cell guides and other containers during hooking procedures inside the ship for 102 cycles. This dataset was partially used in a recent publication:

https://www.mdpi.com/1424-8220/22/7/2752

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The code synthesizes a transfer function with real poles from tabulated frequency response data. The reproducible run of this capsule will synthesize the impedance matrix of a 500-kV double-circuit overhead power transmission line and also that of a 250-kV dc submarine power cable.

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For the interaction of humans with machines but also for the interaction of machines with the environment, e.g. in robotic manipulation tasks, large area sensors like sensor skins are of high interest. Capacitive sensor have become widely used for touch sensor and proximity sensors and are well suited for such large area sensing.

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 It is the key problem of machine condition monitoring to judge whether the rolling bearing has a fault or not and judge the fault location according to the noise signal. Aiming at this problem, a rolling bearing fault identification method is proposed based on Wavelet Frequency Band Subdivision (WFBS), Principal Component Analysis (PCA) and Multi-Level Clustering (MLC).

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<p>The proliferation of efficient edge computing has enabled a paradigm shift of how we monitor and interpret urban air quality. Coupled with the dense spatiotemporal resolution realized from large-scale wireless sensor networks, we can achieve highly accurate realtime local inference of airborne pollutants. In this paper, we introduce a novel Deep Neural Network architecture targeted at latent time-series regression tasks from continuous, exogenous sensor measurements, based on the Transformer encoder scheme and designed for deployment on low-cost power-efficient edge processors.

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BRT Dataset for IEEE VTS

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1.Visualization of convolutional neural network layers for one participant at ROI 301 * 301

2.Convolutional neural network structure analysis in Matlab

3.Convolutional neural network Matlab code

4.Videos of brightness mode (B-mode) ultrasound images from two participants during the recorded walking trials at 5 different speeds

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WITH the advancement in sensor technology, huge amounts of data are being collected from various satellites. Hence, the task of target-based data retrieval and acquisition has become exceedingly challenging. Existing satellites essentially scan a vast overlapping region of the Earth using various sensing techniques, like multi-spectral, hyperspectral, Synthetic Aperture Radar (SAR), video, and compressed sensing, to name a few.

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WITH the advancement in sensor technology, huge amounts of data are being collected from various satellites. Hence, the task of target-based data retrieval and acquisition has become exceedingly challenging. Existing satellites essentially scan a vast overlapping region of the Earth using various sensing techniques, like multi-spectral, hyperspectral, Synthetic Aperture Radar (SAR), video, and compressed sensing, to name a few.

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