Performance of pairing prediction versus training set size and number of pairs per species. by Guillaume Marmier (7495823)

“…<p><b>A</b>: Fraction of pairs correctly identified (TP fraction) versus training set size, for DCA-, MI-, and Mirrortree-based methods. The three pairing scores corresponding to each of these three methods are employed in two ways: either within each species we find the chain B with optimal pairing score with each chain A (dashed lines), or within each species we employ the Hungarian matching algorithm to find the one-to-one pairing of chains A and B that optimizes the sum of the pairing scores (solid lines). …”

BOFdat Step 3: Identifying species-specific metabolic end goals. by Jean-Christophe Lachance (6619307)

Flowchart of software workflow. by Gavrielle R. Untracht (11820311)

Methodology block diagram. by Gahao Chen (21688843)

“…Six machine learning algorithms - Random Forest (RF), AdaBoost, Light Gradient Boosting Machine (LightGBM), eXtreme Gradient Boosting (XGBoost), Categorical Boosting (CatBoost), and Tabular Prior-data Fitted Network version 2.0 (TabPFN-V2) - were implemented with five-fold cross-validation to optimize model hyperparameters. …”

Rendered image volumes in the MIPAV GUI. by Andrew Lauziere (14192836)

Video_1_Cabbage and Weed Identification Based on Machine Learning and Target Spraying System Design.MP4 by Xueguan Zhao (13197201)

“…According to the results of the support vector machine classification test, the feature vector comprised of the point-to-line ratio, maximum inscribed circle radius, and fitted curve coefficient had the highest identification accuracy of 95.7%, with a processing time of 33 ms for a single-frame image. …”

Examples of model selection methods for the PHMM. by Tianshu Li (1527088)

Untitled Item by Caio Vieira Arasaki (15508650)

“…PLA design can be formulated as an interactive optimization problem with many conflicting factors. Incorporating Decision Makers' (DM) preferences during the search process may help the algorithms to find more adequate solutions for their profiles. …”

<b>Road intersections Data with branch information extracted from OSM</b> & <b>C</b><b>odes to implement the extraction </b>&<b> I</b><b>nstructions on how to </b><b>reproduce each... by Zihao Tang (19794537)

“…Each script plays a specific role in the overall process:</p><ul><li><b>bufferThin.py</b>: Implements a thinning algorithm to generate a skeleton of buffered road geometry.…”

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.…”

Data_Sheet_1_Determination of spectral resolutions for multispectral detection of apple bruises using visible/near-infrared hyperspectral reflectance imaging.docx by Insuck Baek (13502608)

“…<p>This study demonstrates a method to select wavelength-specific spectral resolutions to optimize a line-scan hyperspectral imaging method for its intended use, which in this case was visible/near-infrared imaging-based multiple-waveband detection of apple bruises. …”

DataSheet1_Real-Time Characterization of Finite Rupture and Its Implication for Earthquake Early Warning: Application of FinDer to Existing and Planned Stations in Southwest China.... by Jiawei Li (559407)

“…<p>Earthquake early warning (EEW) not only improves resilience against the risk of earthquake disasters, but also provides new insights into seismological processes. The Finite-Fault Rupture Detector (FinDer) is an efficient algorithm to retrieve line-source models of an ongoing earthquake from seismic real-time data. …”

Nutritional strategies in the rehabilitation of musculoskeletal injuries in athletes: a systematic integrative review - PROTOCOL by Diego A. Bonilla (9086201)

“…</p> <p><br></p> <p><em><strong>2.4. Selection process</strong></em></p> <p>After executing Boolean algorithms, filters were used in the different databases to select potentially eligible articles. …”

The Geography of Oxia Planum 03 CTX DEM Mosaic by Peter Fawdon (10016036)

“…</div><div><br></div><div><b>Topographic contours</b><br></div><div>Topographic contours were created at 25 m intervals from a CTX DEM down sampled to 100 m/pix, and contours shorter than 1500 m were removed and the lines smoothed using the PAEK algorithm at a tolerance of 200 m (USGS & MRCTR GIS Lab, 2018).…”

Figures and Tables by Divya C D (22799186)

“…Robots Comput. Vision XXXI: Algorithms and Techniques, Burlingame, CA, USA, Jan. 23–24, 2012.…”