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Modeling and predicting students’ engagement behaviors using mixture Markov models
(Springer, 2022)
Students’ engagements reflect their level of involvement in an ongoing learning processwhich
can be estimated through their interactions with a computer-based learning or assessment
system. A pre-requirement for stimulating ...
On the concept of infinitesimal position vector fields in Galilean spacetimes
(World Scientific, 2022)
We introduce two different ways to establish the concept of infinitesimal position vector field between “infinitesimally nearby” observers in a Galilean spacetime as well as show their mathematical equivalence. We also use ...
On the geometry of stationary Galilean spacetimes
(Springer, 2021)
In this work we introduce a new family of non-relativistic spacetimes: standard stationary Galilean spacetimes, which constitute the local geometric model of stationary Galilean spacetimes. We also study the geodesic ...
Use of recommendation models to provide support to dyslexic students
(Elsevier, 2024)
Dyslexia is the most widespread specific learning disorder and significantly impair different cognitive domains. This, in turn, negatively affects dyslexic students during their learning path. Therefore, specific support ...
Deep Ordinal Classification in Forest Areas Using Light Detection and Ranging Point Clouds
(MDPI, 2024)
Recent advances in Deep Learning and aerial Light Detection And Ranging (LiDAR) have offered the possibility of refining the classification and segmentation of 3D point clouds to contribute to the monitoring of complex ...
Rigidity results for complete spacelike submanifolds in plane fronted waves
(Springer, 2022)
New rigidity results for complete non-compact spacelike submanifolds of arbitrary codimension in plane fronted waves are obtained. Under appropriate assumptions, we prove that a complete spacelike submanifold in these ...
Unemployment Rate Prediction Using a Hybrid Model of Recurrent Neural Networks and Genetic Algorithms
(MDPI, 2024)
Unemployment, a significant economic and social challenge, triggers repercussions that affect individual workers and companies, generating a national economic impact. Forecasting the unemployment rate becomes essential for ...
Graph-Based Feature Selection Approach for Molecular Activity Prediction
(American Chemical Society, 2022)
In the construction of QSAR models for the prediction of molecular
activity, feature selection is a common task aimed at improving the results and
understanding of the problem. The selection of features allows elimination ...
Effective Feature Selection Method for Class-Imbalance Datasets Applied to Chemical Toxicity Prediction
(American Chemical Society, 2021)
During the drug development process, it is common to carry out toxicity tests and adverse effect studies, which are essential to guarantee patient safety and the success of the research. The use of in silico quantitative ...
Cooperative coevolutionary instance selection for multilabel problems
(Elsevier, 2021)
Multilabel classification as a data mining task has recently attracted greater research interest. Many
current data mining applications address problems having instances that belong to more than one
class, which requires ...