1,744,674 research outputs found

    r-karimi/cryoEM_vesicle_segmentation: v1.0.0

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    Persian Visions: A Lecture with Dr. Pamela Karimi

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    Dr. Pamela Karimi, Assistant Professor of Art History at University of Massachusetts Dartmouth, will lecture on contemporary Iranian art as it relates to the exhibition Persian Visions. Her primary field of research is art, architecture, and visual culture of the modern Middle East. A reception will follow in the Peeler lobby.https://scholarship.depauw.edu/peeler_event/1148/thumbnail.jp

    On stability and stabilization of singular uncertain Takagi-Sugeno fuzzy systems

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    Link to a related website: https://re.public.polimi.it/bitstream/11311/1028786/2/On%20stability%20and%20stabilization_11311-1028786_Karimi.pdf, Open Access via UnpaywallAbstract not availableM. Chadli, H.R. Karimi, P. Sh

    Anti-Entropic Rescue Theory – Abstract Jafar Karimi

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    The Anti-Entropic Rescue Theory, proposed by Jafar Karimi, is a cross-disciplinary conceptual framework integrating modern astrophysics, complex systems theory, and social sciences. This registration includes the abstract and keywords of the revised and corrected version of the theory, establishing intellectual ownership and providing a timestamp for the conceptual framework. The theory proposes that complex systems—from collapsing stars to human societies—can restore order in the face of destabilizing (entropic) forces through intrinsic and extrinsic rescue mechanisms. Future updates will include the full article and supporting references. Note: This is the revised version of the theory previously registered in OSF. The current PDF, wiki content, and metadata reflect the corrected terminology and conceptual refinements. Date created: September 7, 2025 Date modified: September 11, 202

    Identification of lti time-delay systems with missing output data using GEM algorithm

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    This paper considers the parameter estimation for linear time-invariant (LTI) systems in an input-output setting with output error (OE) time-delay model structure. The problem of missing data is commonly experienced in industry due to irregular sampling, sensor failure, data deletion in data preprocessing, network transmission fault, and so forth; to deal with the identification of LTI systems with time-delay in incomplete-data problem, the generalized expectation-maximization (GEM) algorithm is adopted to estimate the model parameters and the time-delay simultaneously. Numerical examples are provided to demonstrate the effectiveness of the proposed method. © 2014 Xianqiang Yang and Hamid Reza Karimi
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