J-LDFR: joint low-level and deep neural network feature representations for pedestrian gender classification

Neural Computing and Applications - Appearance-based gender classification is one of the key areas in pedestrian analysis, and it has many useful applications such as visual surveillance, predict...     

Ab-initio study of the structural,optoelectronic, magnetic,hydrogen storage properties and mechanical behavior of novel combinations of hydride perovskites LiXH3 (X = Cr,Fe, Co, & Zn) for hydrogen storage applications

Journal of Computational Electronics - LiXH3 (X?=?Cr, Fe, Co, & Zn) hydride type perovskites have been studied by applying density functional theory (DFT), and their structural,...     

Antimicrobial drug residues in poultry products and implications on public health: A review

Poultry meat and eggs are important foods for fulfilling the dietary needs of the ever-growing human population. Efficient poultry production, however, necessitates use of pharmaceutical products, such as antibiotics, as prophylactic and curatives to ensure rapid growth and health. Nevertheless, inappropriate and non-judicious use of these drugs results in an accumulation of toxic and harmful residues in meat and eggs of treated birds which affect consumer health by triggering allergic reactions and transmitting antibiotic-resistant microbial infections. Therefore, regulatory authorities must take rigorous steps to curtail inappropriate use of numerous drugs for animal use in order to provide safe animal origin food to humans.     

A shrinkage method for causal network detection of brain regions

We present a computationally as well as statistically efficient method of inferring causal networks for the brain regions. It is based on James‐Stein‐type shrinkage estimation of covariance matrix, suggested by (Opgen‐Rhein and Strimmer, BMC Syst Biol 1 ( 2007 ), 37‐40), among different brain regions of interest of the functional magnetic resonance imaging (fMRI) experiment, that enhance the accuracy of vector autoregressive (VAR) model coefficient estimates. We have shown that this approach is well suited for the small number of samples in time and large number of brain regions encountered in real fMRI experiments of seventeen healthy individuals. © 2013 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 23, 140–146, 2013