Allegories are enriched categories generalizing a category of sets and binary relations. In this paper, we extend a new, recently-introduced conceptual data model based on allegories by adding support for modal operators and developing a modal interpretation of the model in any allegory satisfying certain additional (but natural) axioms. The possibility of using different allegories allows us t...

The mode of a distribution provides an important summary of data and is often estimated based on some non-parametric kernel density estimator. This article develops a new data analysis tool called modal linear regression in order to explore highdimensional data. Modal linear regression models the conditional mode of a response Y given a set of predictors x as a linear function of x. Modal linea...

In [H1], we develop a fixpoint semantics, the least model semantics, and an SLDresolution calculus in a direct way for positive modal logic programs in basic serial monomodal logics. In [H2], we extend the results and generalize the methods of [H1] for multimodal logics, giving a framework for developing semantics for positive logic programs in serial multimodal logics. In [H3], we report on ou...

Introduction: Learning is a dominant phenomenon in human life. Learners are different from each other in terms of attitudes and cognitive styles which effect on the learning of people. In this connection, VARK learning style assess the students base their individual abilities and method for obtaining much information from environment in dimensions of visual, aural, read/write, and kinesthetic. ...

AbstractCost-effective depth and infrared sensors as alternatives to usual RGB are now a reality, have some advantages over in domains like autonomous navigation remote sensing. As such, building computer vision deep learning systems for data crucial. However, large labeled datasets these modalities still lacking. In such cases, transferring knowledge from neural network trained on well-labeled...