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matlab-based particle-tracking algorithm defocustracker  (MathWorks Inc)


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    MathWorks Inc matlab-based particle-tracking algorithm defocustracker
    Matlab Based Particle Tracking Algorithm Defocustracker, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/particle-tracking+algorithm/10__1103_slash_physrevapplied__23__024031-74-18-18
    Average 90 stars, based on 1 article reviews
    matlab-based particle-tracking algorithm defocustracker - by Bioz Stars, 2026-11
    90/100 stars

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    other:

    Article Title: Timing deficiencies in amnestic Mild Cognitive Impairment: Disentangling clock and memory processes.
    Article Snippet: The experiment was programmed using Psychtoolbox-3 [40–42] in Matlab R2014b.

    Article Title: High-energy-density acoustofluidic device using a double-parabolic ultrasonic transducer
    Article Snippet: The particle motion was tracked under a stopped-flow condition at a frame rate of 4420 Hz using the MATLAB-based particle-tracking algorithm DefocusTracker [40–42].

    Article Title: Teaching Electric Drives Control Course: Incorporation of Active Learning Into the Classroom
    Article Snippet: This paper describes an attempt to improve the educational methods of an electrical drives control lecture course by incorporating active learning strategies into the classroom.. The proposed active learning strategy is based on the combined use of both sample-guided and student-oriented learning approaches and student learning assessments.. The main objective of this initiative is to rapidly and easily equip undergraduate engineering students with more practical knowledge of advanced adjustable speed drives control strategies through the use of a minimal number of flexible DSP-based setups.

    Article Title: Milling chatter monitoring under variable cutting conditions based on time series features
    Article Snippet: Chatter monitoring is an important task while ensuring machining quality and improving machining efficiency.. Under variable cutting conditions, cutting parameters often change, and the cutting state and traditional time-frequency domain cutting features will also change significantly.. In order to achieve precise monitoring of chatter under such cutting conditions, this article proposes a time series method named recurrence plot (RP) that can reflect the non-stationary characteristics and state differences of the signal system to analyze the cutting force signal in the cutting process.



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