As a novel computational approach, ubiquitous computing was emerging at the beginning of the 1980s and has reached a rather mature level by now.
In this paper, novel computing approach using three different models of feed-forward artificial neural networks (ANNs) are presented for the solution of initial value problem (IVP) based on first Painlevé equation.
To overcome these drawbacks, this paper successfully investigates a novel soft computing approach referred to as a two-stage feature selection procedure using the orthogonal greedy algorithm (TSOGA) to select the important features as inputs of ANNs.
In the current study, a novel computed tomography (CT -guided free-hand ISBT approaCT -guidedlastic flexible needle applicators was developed.
In this paper, based on a cost-optimal parallel two-list algorithm, we propose a novel heterogeneous cooperative computing approach to solve the subset-sum problem on a hybrid CPU GPU cluster, which can make full use of all available computational resources of a cluster.
In this paper a novel unsupervised social computing approach is proposed that effectively performs both on open social media (twitter, blogs, microblogs etc) and on rule-stringent media (e.g. Facebook, LinkedIn etc).
We develop a novel approach for computing the circle Hough transform entirely on graphics hardware (GPU).
In this study, we propose a novel approach to computing the signature of a system consisting of subsystems with shared components.
In this paper, we propose a novel approach for computing real-valued discrete transforms such as the discrete cosine transform (DCT) and the discrete Hartley transform (DHT).
Using this framework, and building on the TVLA system for static analysis of programs, we develop a novel approach for computing generalizations of classical plans by identifying sequences of actions that will make measurable progress when placed in a loop.
A novel approach for computing the inversion of large sparse matrix is proposed to save memory space during model order reduction by partitioning the matrix into many smaller blocks.
