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This paper investigates the unsteady free convective flow of heat generating/absorbing fluid through a porous vertical channel with velocity slip and temperature jump. Exact solution of the oscillatory flow problem is obtained in the slip flow regime through a microchannel. The effects of various flow parameters on the temperature and velocity profiles together with the influence of the velocity slip and temperature jump on the rate of heat transfer and the skin friction are presented and discussed. Ó 2015 Faculty of Engineering, Ain Shams University. Production and hosting by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

MSC Classification: 76A05; 35Q79; 80A20The present work examines the combined influence of variable thermal conductivity and viscosity on the irreversibility rate in couple stress fluid flow in between asymmetrically heated parallel plates. The dimensionless fluid equations are solved by using homotopy analysis method (HAM) and validated with Runge-Kutta shooting method (RKSM). The convergent series solution is then used for the irreversibility analysis in the flow domain. The effects of thermal conductivity and viscosity variation parameters, couple stress parameter, Reynolds number, Grashof number, Hartmann number on the velocity profile, temperature distribution, entropy production, and heat irreversibility ratio are presented through graphs, and salient features of the solutions are discussed. The computations show that the entropy production rate decreases with increased magnetic field and thermal conductivity parameters, whereas it rises with increasing values of couple stress parameter, Brinkman number, viscosity variation parameter, and Grashof number. The study is relevant to lubrication theory.

This paper investigates the effect of radiative heat transfer to oscillatory hydromagnetic nonNewtonian couple stress fluid flow through a porous channel with non-uniform wall temperature due to periodic heat input at the heated wall. Based on some simplifying assumptions, the dimensionless partial differential equations are transformed into a set of ordinary differential equations and then solved using the Adomian decomposition method. The effects of the flow parameters on temperature and velocity profiles are shown graphically and discussed

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In this paper, the effect of feature selection in malware detection using machine learning techniques is studied. We employ supervised and unsupervised machine learning algorithms with and without feature selection. These include both classification and clustering algorithms. The algorithms are compared for effectiveness and efficiency using their predictive accuracy, among others, as performance metric. From the studies, we observe that the best detection rate was attained for supervised learning with feature selection. The supervised learning algorithm used was Multilayer Perceptron (MLP) algorithm. The analysis also reveals that our system can detect viruses from varying sources. CCS Concepts• Computing methodologies➝Machine learning; Feature selection • Security and privacy➝Malware and its mitigation.