Composition spectrum of primary ilmenite based on microanalysis of the elemental composition of the grains with an EDS sensor. by Gabriel Prates Hallal (19555976)

Data for Figs 3–9. by Xiaogang Li (299205)

Classification of PavCA Index scores with the k-Means algorithm where k = 3. by Camille Godin (21445879)

Supplementary Material for: Implementation of machine learning algorithms to screen for advanced liver fibrosis in metabolic dysfunction-associated steatotic liver disease (MASLD):... by Dabbah S. (19947807)

Top-rated mode of transport based on the SEU algorithm (SEU scores from 0 to 40). by Johannes Weyer (13392175)

List of the time used by each algorithm. by JiaMing Gong (20427837)

“…To this end, this paper proposes an entropy-based dynamic ensemble classification algorithm (EDAC) to consider data streams with class imbalance and concept drift simultaneously. …”

Abbreviations used in the algorithm. by Richa Jain (6550391)

The comparison of results from the proposed architecture and state-of-the-art algorithms on the UNSW-B15, NSL-KDD and KDDCUP’99 dataset. by Abdullah Asım Yılmaz (20715311)

RealBench: A Repo-Level Code Generation Benchmark Aligned with Real-World Software Development Practices by RealBench RealBench (22275393)

“…<br><br><br></pre><p dir="ltr">This repository contains the implementation of **RealBench**, a comprehensive benchmark and evaluation framework for repository-level code aligned with real-world software development practices.…”

The experiment of test results for LSTM based EO. by Rizk M. Rizk-Allah (18625751)

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The flowchart of the LSTM based EO for power forecasting. by Rizk M. Rizk-Allah (18625751)

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Image processing algorithm. by Madison Shoraka (22171205)

The run time for each algorithm in seconds. by Edward Antonian (21453161)

“…The goal of this paper is to examine several extensions to KGR/GPoG, with the aim of generalising them a wider variety of data scenarios. The first extension we consider is the case of graph signals that have only been partially recorded, meaning a subset of their elements is missing at observation time. …”

Frequency-dependent pre- and post- synaptic plasticity in rate-based models. by Toviah Moldwin (10866708)

Mean values of different benchmark functions. by Jalal- ud-Din (21474307)

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Detail of benchmark functions comparison. by Jalal- ud-Din (21474307)

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Average execution time (in seconds) of different benchmark functions. by Jalal- ud-Din (21474307)

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Stander deviation values of different benchmark functions. by Jalal- ud-Din (21474307)

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Comparison of different crossover operators. by Jalal- ud-Din (21474307)

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Types of machine learning algorithms. by Md. Merajul Islam (12646837)

“…</p><p>Results</p><p>The XGB-based model outperformed the other models, with the accuracy and AUC respectively 81.73% and 0.802 for stunting, 76.15% and 0.622 for wasting, and 79.13% and 0.712 for underweight. …”