Category: 7. Maths
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Life-long phishing attack detection using continual learning
This section covers a detailed discussion of our methodology to identify and mitigate the performance drop. We analyzed our dataset features using low-dimensional principal component analysis (PCA) embedding of samples to visualize the difference in distribution. We transformed features into 1-D and 2-D PCA as shown in Figs. 1 and 2, respectively. Figure 1 shows…
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Unveiling the drives behind tetracycline adsorption capacity with biochar through machine learning
Statistical results of biochar characteristics This study utilized a combination of box plots and normal distribution curves to illustrate the distribution patterns of continuous data (see Fig. 1). The composite plot comprises two sections—the left segment illustrates the box plot, whereas the right segment manifests the normal distribution curve of the data. The box plot depicts…
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Numerical simulation for impact of implement of reflector and turbulator within the solar system in existence of nanomaterial
To gain more heat flux from the solar system, parabolic reflector has been applied in present work. Concentrated solar systems can absorb high levels of solar irradiation and can be utilized in industrial applications. To increase the thermal output of the solar unit, the absorber can be equipped with a turbulator. For present work, a…
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Classifying seismograms using the FastMap algorithm and support-vector machines
Data We assess the performance of FastMapSVM using seismograms from two data sets. All seismograms used in this paper record ground velocity at a sampling rate of 100 s−1 and are bandpass filtered between 1 Hz and 20 Hz before analysis using a zero-phase Butterworth filter with four poles; we refer to this frequency band…
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Machine learning-based guilt detection in text
In this study, we introduce guilt detection, a novel task in Natural Language Processing aimed at detecting guilt in text. We also developed a dataset and a set of baseline classifiers for this task. Guilt is a complex emotion that arises when individuals contemplate past wrongdoings or failings to uphold their own moral standards1. It…
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Active learning for prediction of tensile properties for material extrusion additive manufacturing
Training dataset The training dataset, which was taken from Pourali and Peterson as well as experiments that led to the determination of print parameters to use in that study, was first investigated for correlations between print parameters (inputs) and mechanical properties (outputs) and for correlations between different mechanical properties36. A heatmap, shown in Fig. 3, was…
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Refining skin lesions classification performance using geometric features of superpixels
Rehman, A. et al. Microscopic melanoma detection and classification: A framework of pixel-based fusion and multilevel features reduction. Microsc. Res. Tech. 83, 410–423 (2020). Article PubMed Google Scholar Wang, M., Liu, X., Gao, Y., Ma, X. & Soomro, N. Superpixel segmentation: A benchmark. Signal Process. Image Commun. 56, 28–39 (2017). Article Google Scholar Thapar, P. et…
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Identifying oscillatory brain networks with hidden Gaussian graphical spectral models of MEEG
Gaussian graphical spectral (GGS) model and MAP1 inverse solution with Hermitian graphical LASSO (hgLASSO) GGS model and interpretations of functional connectivity The PSP processes myriad fulfills some frequency-domain mixing conditions and consequently Gaussianity in the complex-valued follows for brain oscillations \({\varvec{\iota}}\left(t,f\right)\)4,28,90,91. Then, without loss of generality, the Gaussian graphical spectral (GGS) model (Eq. 8) with complex-valued…
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Learning models for classifying Raman spectra of genomic DNA from tumor subtypes
In this section we describe the sample preparation procedures, the Raman measurements, and the statistical approaches developed to analyse the experimental data (see also15,23). Experimental procedures Ag/SiNW substrate fabrication Au catalyzed SiNWs have been grown on Si wafers by plasma enhanced chemical vapor deposition (PECVD) using SiH\(_4\) and H\(_2\) as precursors at a total pressure…
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Epidemic thresholds and human mobility
Epidemic threshold For simplicity, we first compute the epidemic threshold for a system with the same transmission and recovery rates (\(\beta\) and \(\gamma\) respectively) across the N nodes of the system. In the subsequent sections we lift this restriction and analyze more general situations. As explained in the introduction, we assume that the mobility coefficients…