Database of Electromyography and Digit Force during Precision Grasping of Objects at Different Weights by 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 by 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 by 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 by Qiying Zhong (21776771)

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

Figures for heart attack prediction using ML by 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 by 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 by 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 by 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.…”

Preprocessed Spatial Dynamic Wind Power Forecasting (SDWPF) Dataset from Baidu KDD Cup 2022 Challenge by 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 by 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 by 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 by 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 by 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 by 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> by 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 by 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.…”

Underwater Visual and Visual-Inertial Datasets (UVVID) by Fletcher Thompson (7373813)

“…</p><p dir="ltr">Datasets also include post-processed forms of external data sources, such as <a href="https://www.lirmm.fr/aqualoc/" rel="noreferrer" target="_blank">AQUALOC</a> and the <a href="https://cirs.udg.edu/caves-dataset/" rel="noreferrer" target="_blank">Underwater Caves Dataset</a>. …”

Supplementary file 1_Machine learning provides reconnaissance-type estimates of carbon dioxide storage resources in oil and gas reservoirs.docx by Emil Attanasi (21188924)

“…ML algorithms are computationally efficient because they do not impose the strong assumptions on the data-generating process that standard statistical or engineering procedures require. …”

Supplementary file 2_Machine learning provides reconnaissance-type estimates of carbon dioxide storage resources in oil and gas reservoirs.docx by Emil Attanasi (21188924)

“…ML algorithms are computationally efficient because they do not impose the strong assumptions on the data-generating process that standard statistical or engineering procedures require. …”

Supplementary materials for PhD thesis - "Ontology mapping with intelligent agents on the Semantic Web : the theory and practice of agent belief and consenus building" by Miklos Nagy (22007560)

“…<br><br>A series of algorithms have been developed in order to validate the proposed theory on how to approach domain independence in the ontology mapping process. …”