Personalized web service recommendation through mishmash technique and deep learning model

Multimedia Tools and Applications - Discovering the relevant web services for specific applications in the dynamically changing business world becomes very critical. Researchers have used many...     

Cooperative Communication Enabled Cognitive Radio in a Home-Care Application

Wireless Personal Communications - In this paper, cooperative communication (CC) assisted cognitive wireless sensor network (CWSN) is presented for monitoring health and activity of an end-user in...     

A novel binary gaining–sharing knowledge-based optimization algorithm for feature selection

Neural Computing and Applications - To obtain the optimal set of features in feature selection problems is the most challenging and prominent problem in machine learning. Very few human-related...     

Prediction of thermal expansion coefficients of plain weave fabric composites

Three plain weave fabric composite analysis models are presented for the prediction of the on-axes thermal expansion coefficients. These are two-dimensional models in the sense that the actual strand cross-sectional geometry, strand undulation and the presence of a gap between the adjacent strands are taken into account. In the first two models, termed refined models, the representative unit cell is discretised into slices and elements and analysed. In the third method, a closed-form solution is presented. In this case, the representative unit cell is idealised as a crossply laminate and analysed. The relative merits and demerits of the models are also discussed. The predicted results are compared with the experimental values. A good correlation is observed.