S2 File - by Michael Bonert (3751348)

Clinical history. by Michael Bonert (3751348)

Neuroanatomical site overlap. by Michael Bonert (3751348)

Table_1_bSRWPSO-FKNN: A boosted PSO with fuzzy K-nearest neighbor classifier for predicting atopic dermatitis disease.docx by Yupeng Li (507508)

“…</p>Methods<p>This paper establishes a medical prediction model for the first time on the basis of the enhanced particle swarm optimization (SRWPSO) algorithm and the fuzzy K-nearest neighbor (FKNN), called bSRWPSO-FKNN, which is practiced on a dataset related to patients with AD. …”

Segmentation, trace denoising and spike extraction framework. by Changjia Cai (10647521)

adjoint-elastic-registration.zip from Organ registration from partial surface data in augmented surgery from an optimal control perspective by Stéphane Cotin (3944129)

“…After a discussion about the existence of solutions, we analyse the necessary optimality conditions and use them to derive a suitable optimization algorithm. …”

Data_Sheet_1_Multiclass Classification Based on Combined Motor Imageries.pdf by Cecilia Lindig-León (7889777)

PathOlOgics_RBCs Python Scripts.zip by Ahmed Elsafty (16943883)

“…This process generated a ground-truth binary semantic segmentation mask and determined the bounding box coordinates (XYWH) for each cell. …”

Table_1_Near infrared spectroscopy for cooking time classification of cassava genotypes.docx by Massaine Bandeira e Sousa (7866242)

“…The accuracy of the optimal scenario for classifying samples with a cooking time of 30 minutes reached RCal2  = 0.86 and RVal2 = 0.84, with a Kappa value of 0.53. …”

Contextual Dynamic Pricing with Strategic Buyers by Pangpang Liu (18886419)

“…This underscores the rate optimality of our policy. Importantly, our policy is not a mere amalgamation of existing dynamic pricing policies and strategic behavior handling algorithms. …”

DataSheet_1_Near infrared spectroscopy for cooking time classification of cassava genotypes.docx by Massaine Bandeira e Sousa (7866242)

“…The accuracy of the optimal scenario for classifying samples with a cooking time of 30 minutes reached RCal2  = 0.86 and RVal2 = 0.84, with a Kappa value of 0.53. …”

Parameter settings. by Yang Gao (18005)

“…The study proposes a movie recommendation algorithm framework that integrates Knowledge Graph Embedding via Dynamic Mapping Matrix (TransD) and Artificial Intelligence Generated Content (AIGC)-based generative semantic modeling. …”

Fusion framework. by Yang Gao (18005)

“…The study proposes a movie recommendation algorithm framework that integrates Knowledge Graph Embedding via Dynamic Mapping Matrix (TransD) and Artificial Intelligence Generated Content (AIGC)-based generative semantic modeling. …”

Generation steps of user profiles. by Yang Gao (18005)

“…The study proposes a movie recommendation algorithm framework that integrates Knowledge Graph Embedding via Dynamic Mapping Matrix (TransD) and Artificial Intelligence Generated Content (AIGC)-based generative semantic modeling. …”

Table_1_iRNA5hmC: The First Predictor to Identify RNA 5-Hydroxymethylcytosine Modifications Using Machine Learning.docx by Yuan Liu (88411)

“…In this predictor, we introduced a sequence-based feature algorithm consisting of two feature representations, (1) k-mer spectrum and (2) positional nucleotide binary vector, to capture the sequential characteristics of 5hmC sites. …”

Seed mix selection model by Bethanne Bruninga-Socolar (10923639)

“…Classic genetic algorithms consider a population of chromosomes and apply principles of natural selection (selection, mutation, and crossover processes) to generate optimal solutions. …”

Minisymposterium: Muq-Hippylib: A Bayesian Inference Software Framework Integrating Data with Complex Predictive Models under Uncertainty by Ki-Tae Kim (10184066)

“…The central questions are: How do we optimally learn from data through the lens of models? …”

SI2-SSI: Integrating Data with Complex Predictive Models under Uncertainty: An Extensible Software Framework for Large-Scale Bayesian Inversion by Omar Ghattas (4387300)

“…The central questions are: How do we optimally learn from data through the lens of models? …”

SI2-SSI: Integrating Data with Complex Predictive Models under Uncertainty: An Extensible Software Framework for Large-Scale Bayesian Inversion by Umberto Villa (8400192)

“…The central questions are: How do we optimally learn from data through the lens of models? …”

Massive Mixed Models in Julia by Phillip M. Alday (2814652)

“…Keeping everything in one language makes it much easier for experimentation of potential computational enhancements, such as optimizing the storage of various matrices and intermediate quantities. …”