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. …”

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.…”

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. …”

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. …”

<b>dGenhancer v2</b>: A software tool for designing oligonucleotides that can trigger gene-specific Enhancement of Protein Translation. by Adam Master (20316450)

“…<br> An excel-based calculator - dGenhancer can be used to search for putative 5’UTR cis-acting elements, which functional activity could be determined by Gibbs energy-dependent secondary structure formation. …”

Spatial Analysis Reveals Targetable Macrophage-Mediated Mechanisms of Immune Evasion in Hepatocellular Carcinoma Minimal Residual Disease by Renumathy Dhanasekaran (14962092)

“…In this procedure, DNA-barcoded antibodies targeted tissue antigens and were visualized through iterative hybridization with complementary fluorescent DNA oligonucleotides. Our algorithmic pipeline processed the raw imaging data to segment and identify single cells, accurately localize them within tissues, and quantify their marker expressions. …”

Dataset for "Self-Supporting Shell Lattices: Explicit Design Method and Neural Accelerated Evolutionary Optimization" (Virtual and Physical Prototyping) by Haoran Hu (22579169)

“…The proposed optimization framework effectively mitigates the data dependency inherent in traditional machine-learning aided genetic algorithms, demonstrating strong potential for complex, high-dimensional optimization tasks.…”

Comparative analysis of clinical characteristics between ovarian cancer and ovarian cyst patients by Li (20568581)

“…This study aims to integrate serum biomarkers with clinical features to construct efficient diagnostic prediction models and staging prediction algorithms for ovarian cancer. This multidimensional prediction model has the potential to improve early diagnosis rates of ovarian cancer, optimize treatment decision-making processes, reduce unnecessary surgical interventions, and provide scientific basis for individualized treatment plans, ultimately improving patient prognosis and quality of life. …”

Table 1_Erannis jacobsoni disturbance detection based on unmanned aerial vehicle red edge spectral features.docx by Liga Bai (22156009)

“…This study aims to provide with rapid and precise pest occurrence data, enabling timely and effective control measures to preserve and enhance the agroforestry ecological environment. …”

Image 2_Erannis jacobsoni disturbance detection based on unmanned aerial vehicle red edge spectral features.jpg by Liga Bai (22156009)

“…This study aims to provide with rapid and precise pest occurrence data, enabling timely and effective control measures to preserve and enhance the agroforestry ecological environment. …”

Image 1_Erannis jacobsoni disturbance detection based on unmanned aerial vehicle red edge spectral features.jpg by Liga Bai (22156009)

“…This study aims to provide with rapid and precise pest occurrence data, enabling timely and effective control measures to preserve and enhance the agroforestry ecological environment. …”

<b>R</b><b>esidual</b> <b>GCB-Net</b>: Residual Graph Convolutional Broad Network on Emotion Recognition by Qilin Li (535447)

“…<p dir="ltr">Electroencephalogram (EEG) data are commonly applied in the emotion recognition research area. …”