Location-based services have permeated Smart academic institutions, enhancing the quality of higher education. Position information of people and objects can predict different potential requirements and provide relevant services to meet those needs. ...
Computational intelligence and neuroscience
Jul 9, 2022
In this paper, melody and harmony are regarded as the task of machine learning, and a piano arranger timbre recognition system based on AI (Artificial Intelligence) is constructed by training a series of samples. The short-time Fourier transform spec...
The existence of unlinkable (NIL) entities is a major hurdle affecting the performance of Named Entity Linking approaches, and, consequently, the performance of downstream models that depend on them. Existing approaches to deal with NIL entities focu...
We demonstrate the capabilities of two model-agnostic local post-hoc model interpretability methods, namely breakDown (BD) and shapley (SHAP), to explain the predictions of a black-box classification learning model that establishes a quantitative rel...
Computational intelligence and neuroscience
Jul 8, 2022
In modern times, the organizational managements greatly depend on decision-making (DM). DM is considered the management's fundamental function that helps the businesses and organizations to accomplish their targets. Several techniques and processes a...
IEEE transactions on neural networks and learning systems
Jul 6, 2022
Conventional multiview clustering methods seek a view consensus through minimizing the pairwise discrepancy between the consensus and subviews. However, pairwise comparison cannot portray the interview relationship precisely if some of the subviews c...
Coronavirus (COVID-19) creates an extensive range of respiratory contagions, and it is a kind of ribonucleic acid (RNA) virus, which affects both animals and humans. Moreover, COVID-19 is a new disease, which produces contamination in upper respirati...
Fuzzy rule-based models (FRBMs) are sound constructs to describe complex systems. However, in reality, we may encounter situations, where the user or owner of a system only owns either the input or output data of that system (the other part could be ...
Recently, semisupervised feature selection has gained more attention in many real applications due to the high cost of obtaining labeled data. However, existing methods cannot solve the "multimodality" problem that samples in some classes lie in seve...
MOTIVATION: Single-cell Chromatin ImmunoPrecipitation DNA-Sequencing (scChIP-seq) analysis is challenging due to data sparsity. High degree of sparsity in biological high-throughput single-cell data is generally handled with imputation methods that c...