KONISHI, TSUYOSHI, KATO, TAKUYA, GOTO, HIROOMI · Institutional Repository of Xi'an Institute of Optics and Fine Mechanics, Chinese Academy of Sciences (Xian Institute of Optics and Precision Mechanics) · 2010
Provided is a waveform reconstruction device capable of easily reconstructing the accurate time waveform of an optical signal without using an ultrafast time gate or a reference light source. More specifically, a waveform reconstruction device (140) is provided with a phase spectrum calculation unit (143) which calculates the power spectrum of an output optical signal with respect to each of input optical signals with multiple intensities when the phase spectrum of each of the input optical signals with multiple intensities is assumed to have a given phase spectrum, by simulating the propagation of the input optical signal through an optical fiber using the parameter relating to self-phase modulation of the optical fiber, and calculates, as the phase spectrum of the input optical signal, the given phase spectrum in which the difference value between the calculated power spectrum and a measured power spectrum is less than or equal to a predetermined threshold value, and a waveform reconstruction unit (144) which reconstructs the time waveform of the input optical signal by frequency/time transforming the calculated phase spectrum and the power spectrum of the input optical signal.
Cited by 2
Amartya Banerjee, Jesse Burstyn, Audrey Girouard et al. · 2011
We present WaveForm, a system that enables a Video Jockey (VJ) to directly manipulate video content on a large display on a stage, from a distance. WaveForm implements an in-air multitouch gesture set to layer, blend, scale, rotate, and position video content on the large display. We believe this leads to a more immersive experience for the VJ user, as well as for the audience witnessing the VJ's performance during a live event.
Cited by 4
Jiming Wang, Liren Liu, Dong Zhao et al. · 2005
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Tristan Van Leeuwen, Mark Schmidt, Michael Friedl et al. · 2011
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Yanna Zhao, Miao Zhang, Yonghong Duan et al. · Figshare · 2023
Event waveforms data that detected in Changning area, China from July 6, 2019 to August 21, 2019. Folders in compressed files are all named by event occurrence time.
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Valerio Sbragaglia (820730), Francesco Lamanna (820731), Audrey M. Mat (820732) et al. · Figshare · 2015
<p>Waveform (24 h) analysis throughout the 10 days of experiment for a representative lobster (<b>A</b>) and averaged for the 14 lobsters used during the study (<b>B</b>). Activity is reported as displacement (cm) out of the burrow. Black and white bars represent darkness and light hours, respectively. Shadowed areas represent scotophase. Vertical lines represent the standard error of the mean and the horizontal line represents the MESOR. Arrows in <b>B</b> stay for the sampling points at which eyestalk were dissected for the RT-qPCR experiment.</p>
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Shing-hong Liu, Chu-chang Tyan · 2013
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Yingfan Chen · Zenodo (CERN European Organization for Nuclear Research) · 2020
The zip file contains the entire waveform-watcher app, an application built to support XENONnT commissioning capable of visualizing waveform of events built from particle interactions in the XENON experiment.
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PubMed · 2005
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David Cockerell · The Journal of the Acoustical Society of America · 1979
First Page
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Kluwer Academic Publishers eBooks · 2006
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Ronald Rickenbach · 1988
Broadly speaking, my thesis show is about forms in nature, but more specifically it focuses on waveform variations. Even though it was not a consideration when I was doing the tree drawings, they exhibit many examples of waveforms. Since my Master’s program and thesis focused on sculpture, the three-dimensional work was produced with waveform variations in mind.
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Oxford University Press eBooks · 2023
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Megan Elizabeth Slinkard · OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) · 2020
Abstract not provided.
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Marcus Nyström · OSF Preprints (OSF Preprints) · 2025
This repository contains example data and code related to the article Nyström, M., ·Niehorster, D. C., Hessels, R. S., · Andersson, R., Skrok, M. K., ·Konklewski-Pilewicz, R., · Stremplewski, P., Nowakowski, M., Lipinski, J., Tamborski, S., Szkulmowska, A., Szkulmowski, M., & · Hooge, I. T. C. (accepted for publication in Behavior Research Methods), "Do eye trackers estimate eyeball rotation? Relation between tracked eye image feature and estimated saccadic waveform"
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Leijie Jiang (12004315), Keyu Guo (14113056), Xin Liu (43569) et al. · Figshare · 2025
<div> To enable the optical remote sensing satellite to flexibly adjust the camera’s focal length for clearer imaging, a low-power position monitoring and control system suitable for space environments is designed, which is highly significant for aerospace devices with limited energy resources. A novel constant voltage drive circuit is proposed for driving the stepper motor. The differential linear driving and receiving circuit is presented to collect data from the linear encoder. By using the linear encoder to provide feedback on the current focal length, both open-loop and closed-loop focusing functions are achieved. The performances of the designed system are implemented on a field programmable gate array (FPGA) circuit board. The experimental results demonstrate that the developed system consumes approximately of power, has a strong load-carrying capacity, and achieves a focusing control precision of over the entire motion range of to . </div>
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National Cancer Institute · Definitions · 2020
Ope n Pe e r Re v ie w on Qe ios
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Liora Benhamou (306362), Maya Bronfeld (306363), Izhar Bar-Gad (306364) et al. · Figshare · 2015
<p>A and B: normalized average waveforms of HFP (blue) and LFB (red) neurons in primates (A) and rats (B). Inset: X represents the valley to peak duration, Y the valley width and Z the zero-cross parameter. C and D Bar plots representing waveform parameters in HFP (blue) and LFB (red) neurons in primates (C) and in rats (D).</p>
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Alessio Piatanesi, Stefano Lorito · 2014
Abstract The aim of this work is to infer the slip distribution and rupture velocity along the rupture zone of the 26 December 2004 Sumatra–Andaman earthquake from available tide gage records of the tsunami. We selected waveforms from 14 stations, distributed along the coast of the Indian Ocean. Then we subdivided the fault plane into 16 subfaults (both along strike and downdip) following the geometry and mech-anism proposed by Banerjee et al. (2005) and computed the corresponding Green’s functions by numerical solution of the shallow-water equations through a finite-difference method. The slip distribution and rupture velocity were determined simul-taneously by means of a simulated annealing technique. We compared the recorded and synthetic waveforms in the time domain, using a cost function that is a trade-off between the L1 and L2 norms. Preliminary tests on a synthetic dataset, together with a posteriori statistical analysis of the model ensemble enabled us to assess the ef-fectiveness of the method and to quantify the model uncertainty. The main finding is that the best source model features a nonuniform distribution of coseismic slip, with high slip values concentrated into three main patches: the first is located in the southern part of the fault, off the coast of the Aceh Province; the second between 6.5 N and 11 N; and the third at depth, between 11 N and 14 N. Furthermore, we estimated that the rupture propagated at an average speed of 2.0 km/sec.
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Garrow, Ella · Zenodo (CERN European Organization for Nuclear Research) · 2025
First dataset taken with digitiser.
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