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Improving prediction of students’ performance in intelligent tutoring systems using attribute selection and ensembles of different multimodal data sources
(Springer, 2021)
The aim of this study was to predict university students’ learning performance using different sources of performance and multimodal data from an Intelligent Tutoring System. We collected and preprocessed data from 40 ...
A new approach for optimal time-series segmentation
(Elsevier, 2020)
This paper proposes a new optimal approach, called OSTS, to improve the segmentation of time series. The proposed method is based on A* algorithm and it uses an improved version of the well-known Salotti method for obtaining ...
Local-based k values for multi-label k-nearest neighbors rule
(Elsevier, 2022)
Multi-label learning is a growing field in machine learning research. Many applications address instances that simultaneously belong to many categories, which cannot be disregarded if optimal results are desired. Among the ...
Semantic segmentation of 3D car parts using UAV-based images
(Elsevier, 2022)
Environment understanding in real-world scenarios has gained an increased interest in research and industry. The advances in data capture and processing allow a high-detailed reconstruction from a set of multi-view images ...
A new approach for optimal offline time-series segmentation with error bound guarantee
(Elsevier, 2021)
This paper proposes a new optimal approach, called OSFS, based on feasible space (FS) Liu et al. (2008)[, that minimizes the number of segments of the approximation and guarantees the error bound using the L∞-norm. On the ...
SI(FS)2: Fast simultaneous instance and feature selection for datasets with many features
(Elsevier, 2021)
Data reduction is becoming increasingly relevant due to the enormous amounts of data that are constantly being produced in many fields of research. Instance selection is one of the most widely used methods for this task. ...
Instance selection for multi-label learning based on a scalable evolutionary algorithm
(IEEE, 2021)
Multi-label classification has recently attracted
greater research interest as a data mining task. Many current ap-
plications in data mining address problems having instances that
belong to more than one class, which ...
A novel backtracking approach for two-axis solar PV tracking plants
(Elsevier, 2020)
Solar tracking is a technique required to increase energy production in multiple photovoltaic (PV) facilities. In these plants, during low-elevation solar angle hours, shadows appear between the collectors causing a dramatic ...
Improvement of small wind turbine control in the transition region
(MDPI, 2020)
Wind energy conversion systems are very challenging from the control system viewpoint. The control difficulties are even more challenging when wind turbines are able to operate at variable speed and variable pitch. The ...
Reflection-aware generation and identification of square marker dictionaries
(MDPI, 2022)
Square markers are a widespread tool to find correspondences for camera localization because of their robustness, accuracy, and detection speed. Their identification is usually based on a binary encoding that accounts for ...