Category: 7. Maths

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  • A MaskFormer EfficientNet instance segmentation approach for crowd counting

    A MaskFormer EfficientNet instance segmentation approach for crowd counting

  • Goel, S., Koundal, D. & Nijawan, R. Learning models in crowd analysis: A review. Arch. Comput. Methods Eng. 32, 943–961 (2024).

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  • Fan, Z. et al. A survey of crowd counting and…

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  • A comprehensive case study of deep learning on the detection of alpha thalassemia and beta thalassemia using public and private datasets

    A comprehensive case study of deep learning on the detection of alpha thalassemia and beta thalassemia using public and private datasets

    Data collection and preprocessing

    The study begins by gathering datasets from two sources:

    Private datasets

    These are obtained from clinical records, which include genetic markers, blood test results, and…

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  • Enhancing IoT security with a DNA-based lightweight cryptography system

    Enhancing IoT security with a DNA-based lightweight cryptography system

  • Namasudra, S., Devi, D., Kadry, S., Sundarasekar, R. & Shanthini, A. Towards DNA based data security in the cloud computing environment. Comput. Commun. 151, 539–547. https://doi.org/10.1016/j.comcom.2019.12.041 (2020).

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  • Enhanced anomaly network intrusion detection using an improved snow ablation optimizer with dimensionality reduction and hybrid deep learning model

    Enhanced anomaly network intrusion detection using an improved snow ablation optimizer with dimensionality reduction and hybrid deep learning model

    This paper proposes a novel EAID-OADRHM technique. The proposed method presents a new approach for perceiving and migrating attacks in cybersecurity. It encompasses various phases, including min–max scaling normalization, dimensionality…

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  • Contrasting dynamics of past climate states and critical transitions via dimensional analysis

    Contrasting dynamics of past climate states and critical transitions via dimensional analysis

    Empirical mode decomposition (EMD)

    The Empirical Mode Decomposition (EMD) conforms with the class of adaptive decomposition methods and it allows us to decompose a time series s(t) (e.g., \(\delta ^{13}\)C or \(\delta ^{18}\)O) into a finite…

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  • Exploring the role of EMT in ovarian cancer progression using a multiscale mathematical model

    Exploring the role of EMT in ovarian cancer progression using a multiscale mathematical model

  • Tiwari, N., Gheldof, A., Tatari, M. & Christofori, G. Emt as the ultimate survival mechanism of cancer cells. In Seminars in cancer biology, vol. 22, 194–207 (Elsevier, 2012).

  • Felipe Lima, J., Nofech-Mozes, S., Bayani, J. & Bartlett, J. M. Emt…

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  • R-function method and variational method for the bending problem of functionally graded plates with fixed supports and complex shapes

    R-function method and variational method for the bending problem of functionally graded plates with fixed supports and complex shapes

    The Modified First-Order Shear Deformation Theory (MFSDT) proposed by Thai and others is an extension of the classical first-order shear deformation theory. In the Modified First-Order Shear Deformation Theory, the transverse displacement \(w\)

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  • An automatic sustained attention prediction (ASAP) method for infants and toddlers using wearable device signals

    An automatic sustained attention prediction (ASAP) method for infants and toddlers using wearable device signals

  • Reynolds, G. D. & Romano, A. C. The development of attention systems and working memory in infancy. Front. Syst. Neurosci. https://doi.org/10.3389/fnsys.2016.00015 (2016).

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