Explosive growth in geospatial data and the emergence of new spatial technologies emphasize the need for automated discovery of spatial knowledge. Spatial data mining is the process of discovering interesting and previously unknown, but potentially useful patterns from large spatial databases. The complexity of spatial data and implicit spatial relationships limits the usefulness of conventiona...

Explosive growth in geospatial data and the emergence of new spatial technologies emphasize the need for automated discovery of spatial knowledge. Spatial data mining is the process of discovering interesting and previously unknown, but potentially useful patterns from large spatial databases. The complexity of spatial data and intrinsic spatial relationships limits the usefulness of convention...

Explosive growth in geospatial data and the emergence of new spatial technologies emphasize the need for automated discovery of spatial knowledge. Spatial data mining is the process of discovering interesting and previously unknown, but potentially useful patterns from large spatial databases. The complexity of spatial data and intrinsic spatial relationships limits the usefulness of convention...

Data mining is a process of discovering and extracting various models, patterns, summaries, and derived values from a given collection of data. Furthermore, it involves the use of sophisticated data analysis tools to discover previously unknown, valid patterns and relationships in large data sets. It is ordinarily practiced in a wide range of profiling practices, such as marketing, surveillance...

The one-bead one-peptide combinatorial library method represents a powerful approach to the discovery of binding peptides for various macromolecular targets. It involves the synthesis of millions of peptides on beads such that each bead displays only one peptide entity. The peptide-beads that interact with a specific macromolecular target are then isolated for structure determination. We have a...

Submit Manuscript | http://medcraveonline.com a basic science, is increasing, following advanced technology to be used. Since Linneaus (1758) named 4,162 species of living organisms, 1.9 million species have been identified and named. It is less than 20-35% of 5-10 million species estimated commonly on our planet. By the present prevailing tendency to discover unknown species, it would take ano...

Current intrusion detection techniques mainly focus on discovering abnormal system events in computer networks and distributed communication systems. Clustering techniques are normally utilized to determine a possible attack. Due to the uncertainty nature of intrusions, fuzzy sets play an important role in recognizing dangerous events and reducing false alarms level. This paper proposes a dynam...

Data mining involves extracting information from large data sets, discovering the hidden relationships and unknown dependencies, and supporting strategic decision-making tasks. The alignment of data mining and business would bring benefits to the organization’s management. The study investigated the adoption of data mining technologies in managerial accounting system, concentrating on the chall...

A formidable challenge in uncertainty modeling in general, and when learning Bayesian networks in particular, is the discovery of unknown hidden variables. Few works that tackle this task are typically limited to discrete or Gaussian domains, or to tree structures. We propose a novel approach for discovering hidden variables in flexible nonGaussian domains using the powerful class of Gaussian c...