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Bridging Theory and Practice: An Innovative Approach to Android Programming Education through Nutritional Application Development and Problem-Based Learning
(MDPI, 2023-11-08)
This study introduces an innovative Problem-Based Learning (PBL) methodology to enhance the teaching of Android programming, focusing on addressing nutritional challenges. Conducted within the Computer Science degree at ...
A revisited branch-and-cut algorithm for large-scale orienteering problems
(Elsevier, 2024-02)
The orienteering problem is a route optimization problem which consists of finding a simple cycle that maximizes the total collected profit subject to a maximum distance limitation. In the last few decades, the occurrence ...
Fuzzy classification with distance-based depth prototypes: High-dimensional unsupervised and/or supervised problems
(Elsevier, 2023-11)
Supervised and unsupervised classification is crucial in many areas where different types of data sets are common, such as biology, medicine, or industry, among others. A key consideration is that some units are more typical ...
Price of Anarchy with multiple information sources under competition
(Elsevier, 2023-11)
We characterize the Price of Anarchy (PoA) in a single channel under the presence of K competing
sources. As performance metric we consider the Age of Information, which measures the freshness
of information in a remote ...
Dynamic selection of the best base classifier in one versus one
(Elsevier, 2015-05-19)
Class binarization strategies decompose the original multi-class problem into several binary sub-problems. One versus One (OVO) is one of the most popular class binarization techniques, which considers every pair of classes ...
NewOneVersusOneAll method: NOV@
(Elsevier, 2014-04-19)
Binarization strategies decompose the original multi-class dataset into multiple two-class subsets, learning a different binary model for each new
subset. One-vs-All (OVA) and One-vs-One (OVO) are two of the most well-known ...
Undirected cyclic graph based multiclass pair-wise classifier: Classifier number reduction maintaining accuracy
(Elsevier, 2015-08-13)
Supervised Classification approaches try to classify correctly the new unlabelled examples based on a set of well-labelled samples. Nevertheless, some classification methods were formulated for binary classification problems ...
K nearest neighbor equality: giving equal chance to all existing classes
(Elsevier, 2011-07-23)
The nearest neighbor classification method assigns an unclassified point to the class of the nearest case of a set of previously classified points. This rule is independent of the underlying joint distribution of the sample ...
Classifier Subset Selection to construct multi-classifiers by means of estimation of distribution algorithms
(Elsevier, 2015-01-24)
This paper proposes a novel approach to select the individual classifiers to take part in a Multiple-Classifier System. Individual classifier selection is a key step in the development of multi-classifiers. Several works ...
Blood Cell Revolution: Unveiling 11 Distinct Types with ‘Naturalize’ Augmentation
(MDPI, 2023-12-10)
Artificial intelligence (AI) has emerged as a cutting-edge tool, simultaneously accelerating, securing, and enhancing the diagnosis and treatment of patients. An exemplification of this capability is evident in the analysis ...