S1 Graphical abstract - حسب José M. Rivera-Arbeláez (12418512)

"…The software uses a shape-detection algorithm to single out and track the movement of pillars’ tips for the most common shapes of EHT platforms. …"

Comparison against the commercial scanner. حسب Swathi Lakshmi Balasubramanian (12078093)

Table1_Enhanced classification and severity prediction of major depressive disorder using acoustic features and machine learning.pdf حسب Lijuan Liang (4277053)

"…</p>Methods<p>120 participants aged 16–25 participated in this study, included 64 MDD group and 56 HC group. We used the Covarep open-source algorithm to extract a total of 1200 high-level statistical functions for each sample. …"

PyPEFAn Integrated Framework for Data-Driven Protein Engineering حسب Niklas E. Siedhoff (11133851)

"…Here, we present a general-purpose framework (PyPEF: pythonic protein engineering framework) for performing data-driven protein engineering using machine learning methods combined with techniques from signal processing and statistical physics. …"

<b>AI for imaging plant stress in invasive species </b>(dataset from the article https://doi.org/10.1093/aob/mcaf043) حسب Erola Fenollosa (20977421)

"…<p dir="ltr">This dataset contains the data used in the article <a href="https://academic.oup.com/aob/advance-article/doi/10.1093/aob/mcaf043/8074229" rel="noreferrer" target="_blank">"Machine Learning and digital Imaging for Spatiotemporal Monitoring of Stress Dynamics in the clonal plant Carpobrotus edulis: Uncovering a Functional Mosaic</a>", which includes the complete set of collected leaf images, image features (predictors) and response variables used to train machine learning regression algorithms.…"

DataSheet1_Development of a Multilayer Deep Neural Network Model for Predicting Hourly River Water Temperature From Meteorological Data.docx حسب Reza Abdi (3636907)

"…We trained the LR and DNN algorithms on Google’s TensorFlow model using Keras artificial neural network library on Python. …"

MCCN Case Study 2 - Spatial projection via modelled data حسب Donald Hobern (21435904)

"…This study demonstrates: 1) Description of spatial assets using STAC, 2) Loading heterogeneous data sources into a cube, 3) Spatial projection in xarray using different algorithms offered by the <a href="https://pypi.org/project/PyKrige/" rel="nofollow" target="_blank">pykrige</a> and <a href="https://pypi.org/project/rioxarray/" rel="nofollow" target="_blank">rioxarray</a> packages.…"

Code and Data for 'Fabrication and testing of lensed fiber optic probes for distance sensing using common path low coherence interferometry' حسب Radu Stancu (21165068)

"…'model_example_1.py' and 'mode_example_2.py' provide examples of how to use the function to model a particular probe and to explore the parameter space, respectively.…"

Map Matching on Low Sampling Rate Trajectories Through Deep Inverse Reinforcement Learning and Multi Intention Modeling حسب Reza Safarzadeh (18072472)

"…</li><li>`evaluation_metrics`: Contains functions for evaluating the performance of the map matching model. …"

Data Sheet 1_Machine learning models integrating intracranial artery calcification to predict outcomes of mechanical thrombectomy.pdf حسب Guangzong Li (16696443)

"…Eleven ML algorithms were trained and validated using Python, and external validation and performance evaluations were conducted. …"

Barro Colorado Island 50-ha plot aerial photogrammetry orthomosaics and digital surface models for 2018-2023: Globally and locally aligned time series. حسب Vicente Vasquez (13550731)

"…</p><p dir="ltr">The data products included here are 4-band orthomosaics rasters, one per flight date, with standard RGB as the first three bands and the digital surface model as the fourth band.</p><p dir="ltr">The original drone imagery was first processed independently for each date using Agisoft Metashape Pro 2.0 Python API (Agisoft LLC), employing a standardized workflow (Vasquez 2023). …"

PySilsub—a toolbox for silent substitution حسب Joel Martin (11864048)

"…Device settings that will produce lights to selectively stimulate the photoreceptor(s) of interest can be found using a variety of analytic and algorithmic approaches. …"

Spatiotemporal Soil Erosion Dataset for the Yarlung Tsangpo River Basin (1990–2100) حسب peng xin (21382394)

"…The corrected bias functions were then applied to adjust the years (2020–2100) of daily rainfall data using the "ibicus" package, an open-source Python tool for bias adjustment and climate model evaluation. …"

MOMA compared to MFA-derived estimates, carbon yield efficiencies and CBA co-factor profile comparison across unconstrained, manually curated and experimentally constrained solutio... حسب Laura de Arroyo Garcia (9226096)

"…MFA ranges were extracted from a pre-existing dataset (Long et al., 2019), using a Python algorithm to select the minimal and maximal flux ranges.…"

An Ecological Benchmark of Photo Editing Software: A Comparative Analysis of Local vs. Cloud Workflows حسب Pierre-Alexis DELAROCHE (22092572)

"…Performance Profiling Algorithms Energy Measurement Methodology # Pseudo-algorithmic representation of measurement protocol def capture_energy_metrics(workflow_type: WorkflowEnum, asset_vector: List[PhotoAsset]) -> EnergyProfile: baseline_power = sample_idle_power_draw(duration=30) with PowerMonitoringContext() as pmc: start_timestamp = rdtsc() # Read time-stamp counter if workflow_type == WorkflowEnum.LOCAL: result = execute_local_pipeline(asset_vector) elif workflow_type == WorkflowEnum.CLOUD: result = execute_cloud_pipeline(asset_vector) end_timestamp = rdtsc() energy_profile = EnergyProfile( duration=cycles_to_seconds(end_timestamp - start_timestamp), peak_power=pmc.get_peak_consumption(), average_power=pmc.get_mean_consumption(), total_energy=integrate_power_curve(pmc.get_power_trace()) ) return energy_profile Statistical Analysis Framework Our analytical pipeline employs advanced statistical methodologies including: Variance Decomposition: ANOVA with nested factors for hardware configuration effects Regression Analysis: Generalized Linear Models (GLM) with log-link functions for energy modeling Temporal Analysis: Fourier transform-based frequency domain analysis of power consumption patterns Cluster Analysis: K-means clustering with Euclidean distance metrics for workflow classification Data Validation and Quality Assurance Measurement Uncertainty Quantification All energy measurements incorporate systematic and random error propagation analysis: Instrument Precision: ±0.1W for CPU power, ±0.5W for GPU power Temporal Resolution: 1ms sampling with Nyquist frequency considerations Calibration Protocol: NIST-traceable power standards with periodic recalibration Environmental Controls: Temperature-compensated measurements in climate-controlled facility Outlier Detection Algorithms Statistical outliers are identified using the Interquartile Range (IQR) method with Tukey's fence criteria (Q₁ - 1.5×IQR, Q₃ + 1.5×IQR). …"

<b>Rethinking neighbourhood boundaries for urban planning: A data-driven framework for perception-based delineation</b> حسب Shubham Pawar (22471285)

"…/svi_module/output_data/images \<br> --perception-type beautiful \<br> --output-file efficientnet_b4_beautiful_glasgow_embeddings.nc \<br> --extract-embeddings<br></pre></pre><p dir="ltr"><b>Output:</b></p><ul><li><code>perception_module/output_data/efficientnet_b4_beautiful_glasgow_embeddings.nc</code> - NetCDF file with perception scores and embeddings</li></ul><p dir="ltr"><b>Note:</b> Demo data is provided in <code>perception_module/output_data/</code> to test clustering without running Steps 1-2.</p><p dir="ltr"><b>Model Training:</b> See <a href="https://file+.vscode-resource.vscode-cdn.net/c:/Users/smp3/git/perception_based_neighbourhoods/perception_module/readme.md" target="_blank">perception_module/readme.md</a> for instructions on training models using Place Pulse data.…"

A paired dataset of multi-modal MRI at 3 Tesla and 7 Tesla with manual hippocampal subfield segmentations on 7T T2-weighted images حسب Shuyu Li (18401358)

"…We assessed the image quality using MRIQC. </p><p dir="ltr">The dataset is freely accessible on IEEE DataPort, a data repository created by IEEE and can be found at the following URL: <a href="https://ieeexplore.ieee.org/document/10218394/algorithms?…"

Brain-in-the-Loop Learning for Intelligent Vehicle Decision-Making حسب Xiaofei Zhang (16483224)

"…In this paper, we utilize functional near-infrared spectroscopy (fNIRS) signals as real-time human risk-perception feedback to establish a brain-in-the-loop (BiTL) trained artificial intelligence algorithm for decision-making. …"

Predictive Analysis of Mushroom Toxicity Based Exclusively on Their Natural Habitat. حسب Enrico Bertozzi (22461709)

"…The analysis was conducted in a Jupyter Notebook environment, using Python and libraries such as Scikit-learn and Pandas. …"

NanoDB: Research Activity Data Management System حسب Lorenci Gjurgjaj (19702207)

"…Cross-Platform Compatibility: Works on Windows, macOS, and Linux. In a Python environment or as an executable. Ease of Implementation: Using the flexibility of the Python framework all the data setup and algorithm can me modified and new functions can be easily added. …"