Dataset: EEG-Controlled Exoskeleton for Walking and Standing - A Longitudinal Study of Healthy Individuals حسب Shantanu Sarkar (20848745)

"…The validation process focuses on key aspects, including data synchronization, electrode location validation, and the validation of both EEG and MRI data.…"

Disproportionality Analysis of Fondaparinux-Associated Adverse Events Based on the FDA Adverse Event Reporting System (FAERS) حسب fengjiao kang (22627709)

"…Instead, this dataset provides the cleaned and structured data that were used as input for the statistical algorithms in the paper.…"

Supplementary Material حسب Afshin Kouhkord (18929446)

"…Additionally, the detailed fabrication process of the acousto-microfluidic chip is described, along with data-driven surrogate modeling data-sheets. …"

Database of Electromyography and Digit Force during Precision Grasping of Objects at Different Weights حسب Salman Khan (18105799)

"…The data acquisition process and preliminary analysis steps are mentioned in this study. …"

A multi-paradigm and longitudinal EEG dataset including the “sixth-finger” and “affected-hand” motor imagery of stroke patient حسب Zhuang Wang (22542833)

"…The dataset comprehensively covers the complete longitudinal stages of stroke rehabilitation: pre-training, post-training, and follow-up periods. The data materials include: 1) raw EEG data, 2) preprocessed data, and 3) patient clinical information. …"

Table 2_Application of digital-intelligent technologies in physical education: a systematic review.xlsx حسب Qiying Zhong (21776771)

"…Challenges remain in algorithmic accuracy, data privacy, and unequal access to digital resources.…"

Table 1_Application of digital-intelligent technologies in physical education: a systematic review.xlsx حسب Qiying Zhong (21776771)

"…Challenges remain in algorithmic accuracy, data privacy, and unequal access to digital resources.…"

Figures for heart attack prediction using ML حسب Krishnaraj Chadaga (20563994)

"…<p dir="ltr">Heart attack prediction using machine learning involves analyzing biomarkers such as cholesterol levels, blood pressure, heart rate, glucose levels, and inflammatory markers like C-reactive protein to assess risk. Advanced algorithms, including logistic regression, decision trees, random forests, and deep learning models, process this data to identify patterns linked to heart attacks. …"

Predictors of evacuation behavior: dataset on respondents’ route choice and web interaction حسب Dajana Snopková (20191691)

"…Empirical data on human evacuation behavior are invaluable for adjusting and training computational algorithms that simulate evacuation processes, including agent-based modeling. …"

Source codes for cancer diagnosis and prognosis حسب Fatih Gurcan (18117955)

"…<p dir="ltr">This code is developed to analyze the performance of various classification algorithms and resampling methods on cancer diagnostic and prognostic datasets, encompassing data preprocessing, model training, and evaluation processes.…"

Scientific Machine Learning for Spatiotemporal Dynamics: Modeling and Control حسب Xin-Yang Liu (21088832)

"…These advancements collectively enable accurate, efficient, and scalable solutions, bridging the gap between data-driven methods and physics-based algorithms for modeling and controlling spatiotemporal dynamics.…"

Institutions in the Complexity-Relatedness Framework حسب İbrahim Tuğrul Çınar (12058328)

"…<br>Variable construction and filters (5‑year rolling averages, presence matrix, complexity algorithm, relatedness density, normalisation) follow the manuscript.manuscript_numarali</li></ul><p dir="ltr">Variables (grouped overview)</p><ul><li>Identifiers: <code>reg_nuts2</code>, <code>NUTS1</code>, <code>NUTS0</code>, <code>prio_year</code></li><li>Outcomes / initial levels: <code>gdp_c_gr3</code>, <code>gva_c_gr3</code>, <code>totalemp_gr3</code> (3‑year growth rates), <code>lngdp_c</code>, <code>lngva_c</code></li><li>Controls: <code>cap_stock</code>, <code>gfcf</code>, <code>lnhwork</code> (hours worked, log), <code>capdens**</code> (capital intensity variants used in robustness), <code>population density</code> proxy (see manuscript tables)manuscript_numarali</li><li>Composite capability indices & spatial averages:</li><li><ul><li><code>tcrd_mean</code> (CD‑Mean),</li><li><code>fdenseqi_geo</code> (CDQ‑Geo),</li><li><code>tcrd_eqi</code> (CDQ),</li><li><code>_W1</code> / <code>_W0</code> suffixes = within‑NUTS‑1 / within‑country averages.…"

Preprocessed Spatial Dynamic Wind Power Forecasting (SDWPF) Dataset from Baidu KDD Cup 2022 Challenge حسب Yuan Shi (22779782)

"…</p><p dir="ltr">This processed dataset is suitable for research and development in wind power forecasting models, offering a clean and standardized input for machine learning algorithms.…"

Table 1_Development of an upper limb muscle strength rehabilitation assessment system using particle swarm optimisation.xlsx حسب Chuangan Zhou (21684530)

"…Simultaneously, triaxial kinematic data of the glenohumeral joint were obtained via an MPU6050 inertial measurement unit, processed through quaternion-based orientation estimation. …"

Table 1_On the construction of a large-scale database of AI-assisted annotating lung ventilation-perfusion scintigraphy for pulmonary embolism (VQ4PEDB).docx حسب Amir Jabbarpour (21731339)

"…Data extraction was performed at two hospitals in Canada and at multiple sites in the United States, followed by a rigorous de-identification process. …"

Table 2_On the construction of a large-scale database of AI-assisted annotating lung ventilation-perfusion scintigraphy for pulmonary embolism (VQ4PEDB).docx حسب Amir Jabbarpour (21731339)

"…Data extraction was performed at two hospitals in Canada and at multiple sites in the United States, followed by a rigorous de-identification process. …"

pointpairs.json حسب Juan Wang (115708)

"…This data represents the pairwise correspondence of single reflections traced via OptiX, specifically recording the point-to-point mapping relationships generated by single reflection events in the optical simulation process, which can support the verification and optimization of specular surface reconstruction algorithms.…"

Coupling machine learning and group contribution method to predict density and viscosity of ionic liquid-inorganic solvent-water ternary mixtures حسب Sulei Ma (18629684)

"…<p>Accurate prediction of the physical properties of mixed systems is essential for efficient industrial design and process optimization. This study explores the use of a hybrid approach that combines the group contribution (GC) method with advanced machine learning (ML) algorithms to predict the density and viscosity of ternary mixtures comprising ionic liquids (ILs), inorganic solvents (ICs), and water. …"

<b>Leveraging protected areas for dual goals of biodiversity conservation and zoonotic</b> <b>risk reduction</b> حسب Li Yang (13558573)

"…</p><p dir="ltr"><br></p><p dir="ltr"><b>Data Description</b></p><p dir="ltr">1. Code:</p><p dir="ltr">The analysis is divided into two main parts:</p><p dir="ltr">Part 1 (Step1_Spatial analysis.Rmd): Processes zonation maps to identify HCN and HZR areas, overlays them to derive HCN-HZR areas, and calculates distributions across taxonomic groups, protected areas, and countries.…"

Climate anomalies due to Cerrado native vegetation loss حسب Argemiro Leite-Filho (10283801)

"…Our methodology includes the following steps: (1) using machine learning algorithms to model climate variability across the Brazilian Cerrado, (2) evaluating model accuracy, (3) applying a detrending procedure to remove trends related to other factors than deforestation, and (4) validating the detrending process to ensure its reliability.…"