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implementation of the adaptive-threshold spike detection method (sth)  (MathWorks Inc)


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    MathWorks Inc implementation of the adaptive-threshold spike detection method (sth)
    Implementation Of The Adaptive Threshold Spike Detection Method (Sth), 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/adaptive+thresholding+method/pm29478038-110-16-16
    Average 90 stars, based on 1 article reviews
    implementation of the adaptive-threshold spike detection method (sth) - by Bioz Stars, 2026-09
    90/100 stars

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    Article Snippet: The reported P-values for linear regression fits were corrected using the Bonferroni–Holm post hoc test for multiple comparisons (Holm, 1979) using the MATLAB implementation ‘Bonferroni-Holm Correction for Multiple Comparisons’ (https://www.mathworks.com/matlabcentral/ fileexchange/28303-bonferroni-holm-correction-for-multiplecomparisons).

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    Article Snippet: The reported P -values for linear regression fits were corrected using the Bonferroni–Holm post hoc test for multiple comparisons ( ) using the MATLAB implementation ‘Bonferroni-Holm Correction for Multiple Comparisons’ ( https://www.mathworks.com/matlabcentral/fileexchange/28303-bonferroni-holm-correction-for-multiple-comparisons ).

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    Article Snippet: Modeling of cardiomyocyte action potential recording with OCEANs The cell- OCEAN interface model was adapted from a MATLAB implementation of the Luo- Rudy model (GitHub permalink: https:// github.com/meeravarshneya1234/ventricular_myocyte_models/ tree/a57aaf7a632b3808fe0fe93355c2a8d9eed16dd0/Luo_ Rudy91_Model).

    Article Title: Cost optimization for Computer Numerical Control machining workshop: A queueing modeling approach using the meta-heuristic techniques.
    Article Snippet: ISA Transactions 161 (2025) 178–199 A 0 a Contents lists available at ScienceDirect ISA Transactions journal homepage: www.elsevier.com/locate/isatrans Research article Cost optimization for Computer Numerical Control machining workshop: A queueing modeling approach using the meta-heuristic techniques Parmeet Kaur Chahal, Kamlesh Kumar ∗ Department Of Mathematics, Central University of Jammu, Samba, Jammu & Kashmir, 181143, India A R T I C L E I N F O Keywords: Computer Numerical Control (CNC) machining workshop Bernoulli’ s phase repairs Recovery policy (Q) Control F -policy Reneging Feedback Particle Swarm Optimization(PSO) Ant Colony Optimization(ACO) Flower Pollination Algorithm(FPA) A B S T R A C T This research paper introduces an innovative approach to optimize repair of failed Computer Numerical Control (CNC) machines within CNC machining workshops by leveraging queueing theory.. The proposed model addresses a spectrum of real-world scenarios encountered in manufacturing environments, including CNC machine failures, robotic server breakdowns, reneging behavior of failed CNC machines, and mechanisms to handle unsatisfactory repairs.. In this system, failed CNC machines are attended by a single robotic server following a first come first served protocol, while also accounting for potential breakdowns of the robotic server during servicing.

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    Image process for a 7 mm probe with a nominal amplitude of 70%: (a) Cropped image (grayscale frame from the recorded video); (b) binarized image using the adaptive thresholding method; (c) binarized image using Otsu’s method; (d) final binary image obtained using a hybrid procedure of the two methods; (e) total vapor amount over time from the high-speed image sequence. The unit of measure of the y -axis is mm 2 since the backlighting visualization provides a 2D representation of the vapor phase.

    Journal: Ultrasonics Sonochemistry

    Article Title: High-speed imaging and coumarin dosimetry of horn type ultrasonic reactors: Influence of probe diameter and amplitude

    doi: 10.1016/j.ultsonch.2025.107362

    Figure Lengend Snippet: Image process for a 7 mm probe with a nominal amplitude of 70%: (a) Cropped image (grayscale frame from the recorded video); (b) binarized image using the adaptive thresholding method; (c) binarized image using Otsu’s method; (d) final binary image obtained using a hybrid procedure of the two methods; (e) total vapor amount over time from the high-speed image sequence. The unit of measure of the y -axis is mm 2 since the backlighting visualization provides a 2D representation of the vapor phase.

    Article Snippet: Two different functions available on Matlab were used: the adaptive thresholding method and the Otsu’s method , .

    Techniques: Sequencing