Location of the selected monitoring stations in the Northeast of Italy and the respective pollen time series for the year 2022. by Sofia Tagliaferro (20291213)

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Distribution of the median Root Mean Square Error (RMSE) values for pollen/station by imputation method. by Sofia Tagliaferro (20291213)

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Distribution of median Root Mean Square Error (RMSE) for the Variation Index by pollen/station. by Sofia Tagliaferro (20291213)

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Scheme depicting the original dataset of daily pollen concentrations for the period 2018–2022 and time series extracted for the simulation study. by Sofia Tagliaferro (20291213)

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Association estimates (Exp(β) representing ratios of geometric means) with 95%CI between the Root Mean Square Error (RMSE) and covariates (imputation method, % of NAs, and gap leng... by Sofia Tagliaferro (20291213)

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Example of generation of missing values (NAs) and resulting dataset for <i>Alnus</i> BZ2. by Sofia Tagliaferro (20291213)

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Predicting CO₂ Solubility in Diverse Ionic Liquids: A Data-Driven Approach Using Machine Learning Algorithms by Zahra Bastami (21474755)

Predicting CO₂ Solubility in Diverse Ionic Liquids: A Data-Driven Approach Using Machine Learning Algorithms by Zahra Bastami (21474755)

NSGA-III algorithm flow chart. by Manxian Yang (20521600)

“…In addressing the issue of scheduling multiple machines across multiple fields, a two-stage optimization method, referred to as the BNSGA-III algorithm, is introduced. This algorithm integrates the NSGA-III algorithm with Beluga Whale Optimization (BWO), adaptive parameter adjustment, and Adaptive Inversion Crossover (AIC). …”

A more realistic variant of capacitated vehicle routing problem: Methodology and a case study by Yu Wu (54264)

“…<p>Motivated by a real-life daily urban logistics delivery task, we study a more realistic variant of capacitated Vehicle Routing Problem. …”

Data augmentation is applied both geometrically and in terms of intensity. Geometrically, the images are mirrored, flipped, rotated, and randomly cropped. For intensity augmentatio... by Yide Di (20969124)

Characteristics of study participants. by Maeva El Bouchikhi (20442436)

Yearly publication trends of reviewed studies. by Richard Apau (19681534)

“…As image steganography gains relevance, techniques for detecting hidden messages have emerged. …”

DataSheet1_Design of a temperature-feedback controlled automated magnetic hyperthermia therapy device.pdf by Anirudh Sharma (1295760)

Performance characteristics for the three models in the testing datasets (20% from 2012–2018, and 2020). by Cynthia Lokker (3813832)

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Example depiction of the autoML process. by Cynthia Lokker (3813832)

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Prospective evaluation of model performance in >5000 articles retrieved from PubMed. by Cynthia Lokker (3813832)

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Characteristics of the dataset, preprocessing, and feature extraction steps employed by AutoML in the training of the model selected from each dataset experiment^b'*'. by Cynthia Lokker (3813832)

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Fig 1 - by Cynthia Lokker (3813832)

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Parameters and features used in the training of models using automated ML. by Cynthia Lokker (3813832)

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