Contemporary organizations live in an environment of networks: internally, they manage the networks of employees, information resources, and knowledge assets to enhance productivity and improve efficiency; externally, they form alliances with strategic partners, suppliers, buyers, and other stakeholders to conserve resources, share risks, and gain market power. Many managerial and strategic dec...

Citation: Pape E, Bezerra TN, Hauquier F and Vanreusel A (2017) Limited Spatial and Temporal Variability in Meiofauna and Nematode Communities at Distant but Environmentally Similar Sites in an Area of Interest for Deep-Sea Mining. Front. Mar. Sci. 4:205. doi: 10.3389/fmars.2017.00205 Limited Spatial and Temporal Variability in Meiofauna and Nematode Communities at Distant but Environmentally S...

An approach to study the mechanism of mining-induced subsidence, using a combination of phase-stacking and sub-pixel offset-tracking methods, is reported. In this method, land subsidence with a small deformation gradient was calculated using time-series differential interferometric synthetic aperture radar (D-InSAR) data, whereas areas with greater subsidence were calculated by a sub-pixel offs...

Data Mining can be delineated as an action that analyze the data and draws out some new nontrivial information from the large amount of databases. Traditional data mining methods have focused on finding the statistical correlations between the items that are frequently appearing in the database. High utility itemset mining is an area of research where utility based mining is a descriptive type ...

Recurrent pattern mining is an important problem in the context of data mining. In this paper data mining algorithms have been discussed and compared. Recurrent pattern mining has been an important area in data mining research and it is the first step in the analysis of data rising in a broad range of applications. The algorithms are compared with respect to the items like methodology and its b...

Currently statistical and artificial neural network methods dominate in financial data mining. Alternative relational (symbolic) data mining methods have shown their effectiveness in robotics, drug design and other applications. Traditionally symbolic methods prevail in the areas with significant nonnumeric (symbolic) knowledge, such as relative location in robot navigation. At first glance, st...