A shape-based method for multi-view 3-D object representation and recognition is introduced and explored in this paper. 3-D objects are recognised by a small number of images taken from different views. The paper addresses the issue of automatic selection of the best and the optimum number of views for each object. The object boundary of each view is considered as a 2-D shape and is represented...

The federated view selection problem (FVSP) is an optimization technique designed to enhance query performance in a federated data warehouse environment through the materialization of select views given resource constraints and storage restrictions. Current research focuses on single-instance heuristics, which have difficulty scaling. In this work, we introduce two commonly used cooperative heu...

Materialized view selection is one of the crucial decisions in designing a data warehouse for optimal efficiency. Static selection of views may materialize certain views that are not beneficial as the data and usage trends change over time. On the contrary, dynamic selection of views works better only for queries demanding a high degree of aggregation. These facts point to the need for a techni...

In recent years, the question of whether prospective parents might have a moral obligation to select against disability in their offspring has piqued the attention of many prominent philosophers and bioethicists, and a large literature has emerged surrounding this question. Rather than looking to the most common arguments given in support of a positive response to the abovementioned question, s...

In this paper, we present a new framework to determine up front orientations and detect salient views of 3D models. The salient viewpoint to human preferences is the most informative projection with correct upright orientation. Our method utilizes two Convolutional Neural Network (CNN) architectures to encode category-specific information learnt from a large number of 3D shapes and 2D images on...

XML data warehouses form an interesting basis for decision-support applications that exploit complex data. However, native XML database management systems currently bear limited performances and it is necessary to design strategies to optimize them. In this paper, we propose an automatic strategy for the selection of XML materialized views that exploit a data mining technique, more precisely th...

Mutual information (MI) based approaches are a popular feature selection paradigm. Although the stated goal of MI-based feature selection is to identify a subset of features that share the highest mutual information with the class variable, most current MI-based techniques are greedy methods that make use of low dimensional MI quantities. The reason for using low dimensional approximation has b...

Existing unsupervised feature selection algorithms are designed to extract the most relevant subset of features that can facilitate clustering and interpretation of the obtained results. However, these techniques are not applicable in many real-world scenarios where one has an access to datasets consisting of multiple views/representations e.g. various omics profiles of the patients, medical te...

Database management systems (DBMSs) require an administrator whose principal tasks are data management, both at the logical and physical levels, as well as performance optimization. With the wide development of databases and data warehouses, minimizing the administration function is crucial. This function includes the selection of suitable physical structures to improve system performance. View...