Functions in nhppp. by Thomas A. Trikalinos (5785877)

“…We developed it to facilitate the sampling of event times in discrete event and statistical simulations. The package’s functions are based on three algorithms that provably sample from a target NHPPP: the time-transformation of a homogeneous Poisson process (of intensity one) via the inverse of the integrated intensity function; the generation of a Poisson number of order statistics from a fixed density function; and the thinning of a majorizing NHPPP via an acceptance-rejection scheme. …”

Structural diagram of the overall SCF-YOLO algorithm. by Yazhou Li (277980)

RTC-F solar cell: (a) <i>I</i>-<i>U</i> and (b) <i>P</i>-<i>U</i> characteristics. by Ziad M. Ali (12516532)

PWP201 solar module: (a) <i>I</i>-<i>U</i> and (b) <i>P</i>-<i>U</i> characteristics. by Ziad M. Ali (12516532)

Risk and density functions for standard relapse from remission condition to disease <i>b</i> condition (similar shapes for standard relapse to disease <i>a</i>). by Benoîte de Saporta (20454662)

PyNoetic’s classification module supports a range of popular and widely used ML classification models with just a single line of function call. by Gursimran Singh (575288)

Subjects:

MAE versus the number of iterations for different Gaussian noise levels: (a) <i>σ</i> = 10⁻² and (b) <i>σ</i> = 10⁻³. by Limin Ma (556873)

The result for the risk assessment on A, B, C bank using different features. by Jiaqing Huang (5018492)

Line chart plotted using the k-value selection algorithm: (A) system 1; (B) system 2; (C) system 3. by Jingnan Yan (20727331)

Data Sheet 1_Simplified two-compartment neuron with calcium dynamics capturing brain-state specific apical-amplification, -isolation and -drive.pdf by Elena Pastorelli (7024235)

“…This work provides the computational community with a two-compartment spiking neuron model that supports the proposed forms of brain-state-specific activity. A machine learning evolutionary algorithm, guided by a set of fitness functions, selected parameters defining neurons that express the desired apical dendritic mechanisms. …”

<b>A Multi-Pathology Ballistocardiogram Dataset for Cardiac Function Monitoring and Arrhythmia Assessment</b> by Jing Zhan (20716673)

“…Denoised BCG signal (Column 3), derived using the Enhanced Singular Value Thresholding (ESVT) algorithm.</p><p dir="ltr"><b>5 Signal visualization</b></p><p dir="ltr">(1) File name: signal.pdf</p><p dir="ltr">(2) Content: A graphical representation of the signals from signal.csv. …”

The results of LASSO regression algorithm. by Xue Fu (549661)

Comparison of Stage II-B and Stage II-A. by Ferhat Yuna (21519851)

Feto-placental vasculatures with non-central (A) and centralised (B) umbilical artery insertion. by Diana C. de Oliveira (9220729)

Adding a new function module. by Yukako Yamane (9034133)

(a) Random initialized population distribution (b) Good point set initialized population distribution. by Tengfei Ma (597633)

Bangdiwala’s agreement charts for item 18 (A), 19 (B) and 22 (C) comparing item scores between the Paper-based support and the Tablet. by Dominique Vincent-Genod (20552594)

Horizontal central profiles produced for the 128-th row of the restored images with different Gaussian noise levels: (a) <i>σ</i> = 10⁻² and (b) <i>σ</i> = 10<sup>−3</su... by Limin Ma (556873)

3D profiles of <i>β</i> and λ with respect to the MAE for different Gaussian noise levels: (a) <i>σ</i> = 10⁻² and (b) <i>σ</i> = 10⁻³. by Limin Ma (556873)

Vertical central profiles produced for the 128-th column of the restored images with different Gaussian noise levels: (a) <i>σ</i> = 10⁻² and (b) <i>σ</i> = 10<sup>−3</s... by Limin Ma (556873)