Modeling effect of 3DM interaction design models. by Hua Song (113155)

“…In this study, an interactive 3D modeling design model based on Bezier curve and Harris corner detection algorithm is constructed. First, the output image is denoised, and then the improved Harris corner detection algorithm is used to obtain the feature points, which ensures the clarity of the image while extracting the key features. …”

Delaunay triangulation process. by Hua Song (113155)

“…In this study, an interactive 3D modeling design model based on Bezier curve and Harris corner detection algorithm is constructed. First, the output image is denoised, and then the improved Harris corner detection algorithm is used to obtain the feature points, which ensures the clarity of the image while extracting the key features. …”

Table 1_Identification of anoikis-related genes and immune infiltration characteristics in Sjögren’s syndrome based on machine learning.xlsx by Lei Wang (6656)

“…Concurrently, a mouse model of SS was established and validated through in vivo experiments. Immune cell infiltration in SS tissues was evaluated using CIBERSORT, and correlations between characteristic genes and immune cell profiles were analyzed. …”

Table 2_Identification of anoikis-related genes and immune infiltration characteristics in Sjögren’s syndrome based on machine learning.xlsx by Lei Wang (6656)

“…Concurrently, a mouse model of SS was established and validated through in vivo experiments. Immune cell infiltration in SS tissues was evaluated using CIBERSORT, and correlations between characteristic genes and immune cell profiles were analyzed. …”

Table 1_WGCNA-ML-MR integration: uncovering immune-related genes in prostate cancer.docx by Jing Lv (128179)

“…Furthermore, a machine learning algorithm was used to screen for core genes and construct a diagnostic model, which was then validated in an external validation dataset. …”

Image 1_WGCNA-ML-MR integration: uncovering immune-related genes in prostate cancer.tif by Jing Lv (128179)

“…Furthermore, a machine learning algorithm was used to screen for core genes and construct a diagnostic model, which was then validated in an external validation dataset. …”

Table 1_Identification and validation of the diagnostic biomarker MFAP5 for CAVD with type 2 diabetes by bioinformatics analysis.xlsx by Qiang Shen (473659)

“…Next, we intersected the differential genes and module genes of CAVD with the differential genes of diabetes, and the obtained genes were used for subsequent analysis. ML algorithms and the PPI network yielded a total of 12 genes, 10 of which showed a higher diagnostic value. …”

Table 1_Integrating machine learning and multi-omics analysis to reveal nucleotide metabolism-related immune genes and their functional validation in ischemic stroke.doc by Tianzhi Li (12052463)

“…Core immune-related genes were determined using LASSO regression, SVM-RFE, and Random Forest algorithms. …”

4D water droplet collision datasets by Yuhe Zhang (18089881)

“…<p dir="ltr">We share the simulated water droplet collision datasets modeled with the Navier-Stokes Cahn-Hilliard equations. This data is used to validate our deep-learning 4D reconstruction algorithm, as reported in "4D-ONIX for reconstructing 3D movies from sparse X-ray projections via deep learning" [1]. …”

Fungal Virulence Factors Datasets for IBD-Specific Antifungal Drug Discovery by Shuo Feng (22236412)

“…However, current databases contain limited numbers of fungal virulence factors, lack effective predictive algorithms, and do not directly provide protein structural information relevant for drug discovery. …”

Grading System by Eirini Katsadaki (22478770)

“…The results show that the system without geodesic distance performs better on general texts, indicating that the addition of geographic features can introduce noise in cases where geographic relevance is not immediately important. In terms of accuracy, Decision Tree was the best performing algorithm for the system without geodesic distance, whereas K-Nearest Neighbors (KNN) was the best performing model for the system with geodesic distance, which indicates that different feature sets may benefit from different learning strategies. …”

Supplementary file 1_Reinforcement learning based estimation of shortest paths in dynamically changing transportation networks.pdf by Hoang Dat Pham (20836880)

“…The above traditional algorithms have been put to successful use for fixed networks with static link costs. …”

Comparison of experimental and simulated data across frequency differences and tactile Conditions, with audio and tactile input spread profiles. by Farzaneh Darki (22076051)

“…<b>C-D:</b> The -dependent profiles for the auditory input spread and tactile input spread (modeled as exponential decays) were derived using an optimization algorithm minimizing the mean squared error between experimental and computational data from Experiment 1. …”

Canopy Height Monitoring Data and Model of Hainan Tropical Rainforest National Park by Zixuan Qiu (14013837)

“…</p><p dir="ltr">The data in the folder (Code) includes the training code and prediction code for four machine learning algorithms (BP, CNN, GBDT, RF).…”

Presentation_1_Predicting cerebral edema in patients with spontaneous intracerebral hemorrhage using machine learning.pdf by Jiangbao Xu (19791462)

“…The most relevant variables were selected using Support Vector Machine Recursive Feature Elimination (SVM-RFE) and Least Absolute Shrinkage and Selection Operator (LASSO) algorithms. …”

Significantly enriched Gene Ontology (GO) terms among the genes showing significant results in the ancestry-specific TWAS. by Jenna C. Carlson (3950024)

“…P-values were adjusted to maintain an experiment-wide type 1 error rate of 0.05 within ancestry group using the g:SCS algorithm which accounts for the dependent structure of functionally annotated gene sets.…”

DataSheet1_Machine learning’s effectiveness in evaluating movement in one-legged standing test for predicting high autistic trait.docx by Yoshimasa Ohmoto (19862184)

“…A model to identify the participants belonging to High autistic trait group and Low autistic trait group was developed using a support vector machine (SVM) algorithm with 16 explanatory variables. …”

Image 5_How math shapes the world of life science animation.tif by Rafael Oliveira (6619367)

“…Furthermore, the article offers a practical dimension to this theoretical understanding by providing a comprehensive example of code written in JavaScript for generating an animation, also using HTML and CSS. This code example is designed to be easy to comprehend, even to those with limited programming experience, fostering the integration of animations into life science education. …”

Image 1_How math shapes the world of life science animation.jpeg by Rafael Oliveira (6619367)

“…Furthermore, the article offers a practical dimension to this theoretical understanding by providing a comprehensive example of code written in JavaScript for generating an animation, also using HTML and CSS. This code example is designed to be easy to comprehend, even to those with limited programming experience, fostering the integration of animations into life science education. …”

Image 6_How math shapes the world of life science animation.jpeg by Rafael Oliveira (6619367)

“…Furthermore, the article offers a practical dimension to this theoretical understanding by providing a comprehensive example of code written in JavaScript for generating an animation, also using HTML and CSS. This code example is designed to be easy to comprehend, even to those with limited programming experience, fostering the integration of animations into life science education. …”