Image processing algorithms related to remote sensing have been tested and utilized on the Hadoop MapReduce parallel platform by using an experimental 112-core high-performance cloud computing system that is situated in the Environmental Studies Center at the University of Qatar. Although there has been considerable research utilizing the Hadoop platform for image processing rather than for its...

Since many years ago, the scientific community is concerned about how to increase the accuracy of different classification methods, and major achievements have been made so far. Besides this issue, the increasing amount of data that is being generated every day by remote sensors raises more challenges to be overcome. In this work, a tool within the scope of InterIMAGE Cloud Platform (ICP), whic...

Coordinate structures are linguistic structures consisting of two or more conjuncts, which usually compose into larger constituent as a whole unit. However, the boundary of each conjunct is difficult to identify, which makes it difficult to parse the whole coordinate and larger structures. In labeled data, such as the Penn Chinese Tree Bank (CTB), coordinate structures are not labeled explicitl...

The moment map is a mathematical expression of the concept of the conservation associated with the symmetries of a Hamiltonian system. The abstract moment map is defined from G-manifold M to dual Lie algebra of G. We will interested study maps from G-manifold M to spaces that are more general than dual Lie algebra of G. These maps help us to reduce the dimension of a manifold much more.

We propose a novel resource allocation scheme, which can reduce MAP overhead and maximize the throughput in the MIMO-OFDM systems. In the message based broadband access system, we need to minimize the MAP overhead since the excessive MAP overhead causes degradation of system throughput. Increasing the size of resource allocation unit can reduce MAP overhead. However, multiuser diversity gain be...

Maximum a posteriori (MAP) inference is a particularly complex type of probabilistic inference in Bayesian networks. It consists of finding the most probable configuration of a set of variables of interest given observations on a collection of other variables. In this paper we study scalable solutions to the MAP problem in hybrid Bayesian networks parameterized using conditional linear Gaussian...

The increasing accessibility of mobile technologies and devices, such as smartphones and tablet PCs, has made mobile learning (m-learning) a critical feature of modern didactics. Mobile learning is among the many computerized activities that can be performed using mobile devices. As the volume of accessible important information on university websites continues to increase, students may face di...

There are many efficient tools significantly uses Map Reduce applications that assigns data with their corresponding tasks in parallel and distributed data processing. LIBRA symbolizes the lightweight problems of data skew with input data applications that can overlap map and reduce strategies. This is one of the innovative and accurate distribution methods for intermediate data sampling with n...