Box plot of Unity ML experiments using visual information, audio samples and combination of visual information and audio samples. by Enoch Solomon (21416703)

Subjects:

Dendrogram of the stock prices. by Muhammad Hilal Alkhudaydi (21560690)

“…Investors will always look for a portfolio that can handle the required amount of risk while still producing the desired level of expected returns. This article uses feature-based models to investigate the primary elements that contribute to the optimal composition of a specific portfolio. …”

Descriptive statistics on stock prices. by Muhammad Hilal Alkhudaydi (21560690)

“…Investors will always look for a portfolio that can handle the required amount of risk while still producing the desired level of expected returns. This article uses feature-based models to investigate the primary elements that contribute to the optimal composition of a specific portfolio. …”

Correlation heatmap of the principal components. by Muhammad Hilal Alkhudaydi (21560690)

“…Investors will always look for a portfolio that can handle the required amount of risk while still producing the desired level of expected returns. This article uses feature-based models to investigate the primary elements that contribute to the optimal composition of a specific portfolio. …”

Table_1_Construction of a risk screening and visualization system for pulmonary nodule in physical examination population based on feature self-recognition machine learning model.X... by Fang Tian (360682)

Predicting the Shear Viscosity of Carbonated Aqueous Amine Solutions and Their Blends by Using an Artificial Neural Network Model by Ali Aminian (9580734)

“…A total of 1682 amine + CO₂ + water viscosity data sets for primary, secondary, and tertiary amines and 220 data points for further accuracy examinations were used. …”

All online review text data. by Yuandi Jiang (16540833)

“…The findings showed: 1) Museum visitors were highly concentrated in eastern coastal regions, with spatial distribution evolving from single-core to multi-core clusters, gradually expanding into central areas (e.g., Henan, Hubei, Shaanxi). 2) Museum image perception has shifted from object-centered to more human-centered experiences, with significant differences across the various categories. 3) Over 75% of visitors reported positive experiences, with ethnography museums showing the highest satisfaction in 2024 (<i>Pro</i> = 0.922), whereas history museums consistently had the lowest. 4) Satisfaction drivers were dynamic, with 85.26% of perception themes significantly correlated with satisfaction (<i>p</i> < 0.01), with rich collections, distinctive features, immersive experiences, and diverse visitation forms identified as the primary contributors to positive visitor experiences. …”

Data_Sheet_1_Determination of phage load and administration time in simulated occurrences of antibacterial treatments.docx by Steffen Plunder (14022498)

Proposed model tuned hyperparameters. by Subathra Gunasekaran (19492680)

“…To select the most informative features for effective segmentation, we utilize an advanced meta-heuristics algorithm called Advanced Whale Optimization (AWO). …”

The workflow of the proposed model. by Subathra Gunasekaran (19492680)

“…To select the most informative features for effective segmentation, we utilize an advanced meta-heuristics algorithm called Advanced Whale Optimization (AWO). …”

ResNeXt101 training and results. by Subathra Gunasekaran (19492680)

“…To select the most informative features for effective segmentation, we utilize an advanced meta-heuristics algorithm called Advanced Whale Optimization (AWO). …”

Proposed model specificity and DSC outcomes. by Subathra Gunasekaran (19492680)

“…To select the most informative features for effective segmentation, we utilize an advanced meta-heuristics algorithm called Advanced Whale Optimization (AWO). …”

Accuracy comparison of proposed and other models. by Subathra Gunasekaran (19492680)

“…To select the most informative features for effective segmentation, we utilize an advanced meta-heuristics algorithm called Advanced Whale Optimization (AWO). …”

Architecture of ConvNet. by Subathra Gunasekaran (19492680)

“…To select the most informative features for effective segmentation, we utilize an advanced meta-heuristics algorithm called Advanced Whale Optimization (AWO). …”

Comparison of state-of-the-art method. by Subathra Gunasekaran (19492680)

“…To select the most informative features for effective segmentation, we utilize an advanced meta-heuristics algorithm called Advanced Whale Optimization (AWO). …”

Proposed model sensitivity outcome. by Subathra Gunasekaran (19492680)

“…To select the most informative features for effective segmentation, we utilize an advanced meta-heuristics algorithm called Advanced Whale Optimization (AWO). …”

Proposed ResNeXt101 operational flow. by Subathra Gunasekaran (19492680)

“…To select the most informative features for effective segmentation, we utilize an advanced meta-heuristics algorithm called Advanced Whale Optimization (AWO). …”

Proposed IDS architecture. by Saad Hammood Mohammed (20623506)

Data_Sheet_1_Construction and Interpretation of Prediction Model of Teicoplanin Trough Concentration via Machine Learning.docx by Pan Ma (400070)

Trace, Machine Learning of Signal Images for Trace-Sensitive Mass Spectrometry: A Case Study from Single-Cell Metabolomics by Zhichao Liu (191718)

“…To bridge this gap, we here developed “Trace”, a software framework that incorporates machine learning (ML) to automate feature selection and optimization for the extraction of trace-level signals from HRMS data. …”