CIAHS-Data.xls by Yingchang Li (22195585)

“…This method identifies inherent natural grouping points within the data through the Jenks optimization algorithm, maximizing between-class differences while minimizing within-class differences37. …”

Table 1_An interpretable machine learning model for predicting mortality risk in adult ICU patients with acute respiratory distress syndrome.docx by Wanyi Li (70701)

“…This study used eight machine learning algorithms to construct predictive models. Recursive feature elimination with cross-validation is used to screen features, and cross-validation-based Bayesian optimization is used to filter the features used to find the optimal combination of hyperparameters for the model. …”

Aluminum alloy industrial materials defect by Ying Han (20349093)

“…</p><h2>Description of the data and file structure</h2><p dir="ltr">This is a project based on the YOLOv8 enhanced algorithm for aluminum defect classification and detection tasks.…”

Data Sheet 1_Emerging trends in IoT for aquatic systems: a systematic literature review.pdf by Carlos Cohen-Manrique (22780142)

“…Following PRISMA guidelines, the studies were categorized into four thematic areas: IoT applications in aquatic environments, data transmission technologies, algorithms for process optimization and data analysis, and sensor fusion techniques. …”

Supplementary Data: Biodiversity and Energy System Planning - Queensland 2025 by Andrew Rogers (17623239)

“…</p><h2>3. VRE Siting Algorithm and Optimization</h2><p><br></p><p dir="ltr">The VRE siting model uses a cost-minimization optimization approach to select the most cost-efficient project sites to meet a projected energy mix target.…”

Polar perspectives: a deep dive into geo-referencing historical Antarctic photos by Felix Dahle (19724405)

“…This study addresses this challenge by developing an automated geo-referencing workflow that leverages recent advancements in machine-learning-based tie-point matching. We use the algorithm LightGlue, to establish tie-points between geo-referenced Sentinel-2 satellite imagery and historical non-geo-referenced aerial images. …”

Effect of atmospheric turbulence anisoplanatism toward LEO satellite-to-ground laser communications link by Qingfang Jiang (21374513)

“…To enhance the accuracy of centroid positioning, a sub-pixel interpolation algorithm based on Zernike moments is proposed, further enhanced through a gray-gradient-weighted refinement strategy. …”

Vibration Nondestructive Testing of Continuous Welded Rails: A Finite Element Analysis by Alireza Enshaeian (20360253)

“…<p>This paper presents a finite element model for the dynamic vibration of continuous-welded rails (CWR) under different longitudinal stresses and base conditions. The model supports the physical principles of a vibration-based nondestructive testing (NDT) technique aimed at inferring the lateral and vertical strength, and the neutral temperature of CWR. …”

Towards a raw-data dynamic structural model with its descriptive applications by Lukáš Malec (21373862)

“…The analytical formulas for the score vector as well as blocks of the Hessian matrix are solved employing the differential, a viable alternative to matrix derivatives. Optimal terms have been used in the maximum likelihood (ML) technique based on a modified Newton iteration algorithm, undergoing selections from different calculus applications. …”

Effect of Atmospheric Turbulence Anisoplanatism on LEO Satellite-to-Ground Laser Communications Link by Qingfang Jiang (21374513)

“…To enhance the accuracy of centroid positioning, a sub-pixel interpolation algorithm based on Zernike moments is proposed, further enhanced through a gray-gradient-weighted strategy.Experimental results from LEO-SGLC scenarios indicate that single-path measurements consistent with the expected statistical properties of atmospheric turbulence.However, low correlation coefficients between different measurement paths were 0.0151 and 0.1667 respectively,demonstrate significant anisoplanatism. …”

Table1_GTasm: a genome assembly method using graph transformers and HiFi reads.DOCX by Junwei Luo (7593224)

“…</p>Results<p>Here we introduce GTasm, an assembly method that uses graph transformer network to find optimal assembly results based on assembly graphs. …”

Data Sheet 1_Risk factors for misclassification in predicting EGFR mutation status using PET/CT imaging in non-small cell lung cancer patients.docx by Jiali Li (436886)

“…</p>Results<p>The PCS-nomogram model, constructed using the partial least squares generalized linear models (plsRglm) algorithm, achieved optimal performance in predicting EGFR mutations in NSCLC patients (training cohort: area under the curve [AUC] = 0.80; validation cohort: AUC = 0.82). …”

Data Sheet 1_Predictive model for sarcopenia in chronic kidney disease: a nomogram and machine learning approach using CHARLS data.docx by Renjie Lu (2021845)

“…Four machine learning algorithms were utilized, with the optimal model undergoing hyperparameter optimization to evaluate the significance of predictive factors.…”

Data Sheet 5_Multidimensional dietary assessment and interpretable machine learning models predict the risk of prediabetes/diabetes and osteoporosis comorbidity in older adults.pdf by Yuwen ShangGuan (22633190)

“…An online risk prediction tool was developed based on the optimized random forest model for real-time individual comorbidity risk calculation.…”

Data Sheet 7_Multidimensional dietary assessment and interpretable machine learning models predict the risk of prediabetes/diabetes and osteoporosis comorbidity in older adults.pdf by Yuwen ShangGuan (22633190)

“…An online risk prediction tool was developed based on the optimized random forest model for real-time individual comorbidity risk calculation.…”

Data Sheet 6_Multidimensional dietary assessment and interpretable machine learning models predict the risk of prediabetes/diabetes and osteoporosis comorbidity in older adults.pdf by Yuwen ShangGuan (22633190)

“…An online risk prediction tool was developed based on the optimized random forest model for real-time individual comorbidity risk calculation.…”

<b>Functional excitation-inhibition ratio indicates near-critical oscillations across frequencies</b> by Marina Diachenko (19739092)

“…We recently introduced an algorithm to determine a functional E/I ratio based on the critical brain dynamics that emerge in neuronal networks balancing between order and disorder. …”

Data Sheet 3_Multidimensional dietary assessment and interpretable machine learning models predict the risk of prediabetes/diabetes and osteoporosis comorbidity in older adults.pdf by Yuwen ShangGuan (22633190)

“…An online risk prediction tool was developed based on the optimized random forest model for real-time individual comorbidity risk calculation.…”

Table 1_Multidimensional dietary assessment and interpretable machine learning models predict the risk of prediabetes/diabetes and osteoporosis comorbidity in older adults.docx by Yuwen ShangGuan (22633190)

“…An online risk prediction tool was developed based on the optimized random forest model for real-time individual comorbidity risk calculation.…”

Data Sheet 1_Multidimensional dietary assessment and interpretable machine learning models predict the risk of prediabetes/diabetes and osteoporosis comorbidity in older adults.pdf by Yuwen ShangGuan (22633190)

“…An online risk prediction tool was developed based on the optimized random forest model for real-time individual comorbidity risk calculation.…”