Attack containment in mobile ad-hoc networks through fair distribution of processing resources

Due to frequent joining and leaving of nodes and better performance, use of flooding algorithms is always proffered in Mobile Ad-hoc Networks (MANETs). A single query transmitted by a node can be received by hundreds of nodes at 3rd or 4th hop. But it is also fact that flooding algorithms provide an opportunity to attackers for launching query flooding attacks. On one side these query flooding attacks results in wastage of valuable processing resources and on the other side they cause in starvation and delay at legitimate user’s end. To solve this problem we proposed attack containment techniques by providing a fair share of processing resources to every node. Fair distribution is achieved by designing different query distribution techniques based on mathematical models. Results obtained through network simulator 2 prove that the proposed solution is resilient against various types of flooding attacks.     

Standalone PV-fed LED Street Lighting Using Resonant Converter

This paper proposes a single-stage, single-switch, non-isolated step-up converter with resonant inverter for a standalone photovoltaic battery-powered light-emitting diode (LED) street light. The LED driver presented in this paper integrates a high step-up DC–DC converter with coupled inductors and LCC resonant converter into a single-stage conversion circuit topology. The proposed converter is a compact cost-effective driver for powering a 60 W LED Street light with a battery backup charged from PV array of 12 V. The modes of operation and analysis of the proposed converter are explained. The design of the circuit elements is done based on the theoretical analysis. The proposed circuit has been simulated, and prototype has been developed to demonstrate its feasibility.     

Role of gamma radiation and EGDMA on the physico–mechanical properties of jute fabrics/polypropylene composites

Jute fabrics reinforced polypropylene (PP) composites (45 wt % fiber) were prepared by compression molding and their mechanical properties were investigated. Both jute fabrics and PP sheets were treated with gamma radiation (250–1,000 krad dose) at a rate of 350 krad/h. Irradiated jute fabrics were soaked into ethylene glycol dimethacrylate (EGDMA) solutions (5–40% by weight) and cured in an oven at different temperatures (40–100°C) for 60 min. The percentage of polymer loading (PL) was evaluated and found that 20% EGDMA‐treated jute fabrics contains the highest PL. Composites made of 20% EGDMA‐treated jute fabrics were studied further. It was found that the treatment using the EGDMA improved the mechanical properties of the composites significantly. Scanning electron microscopy and aging properties of untreated and treated composites were performed. POLYM. COMPOS., 2011. © 2011 Society of Plastics Engineers     

Velocity and Temperature Gradient Boundary Layer Formation During a Continuum Drawing in a Polymer Melt Chamber

This paper presents a boundary layer model for the velocity and temperature gradient on the introduction of a continuum (wire, strip, tube, etc.) in a melt bath of polymer positioned before the plasto-hydrodynamic pressure unit prior to drawing or coating. Results are presented for the boundary layer thicknesses of velocity and temperature at different wire velocities. Also, the friction factor and Nusselt number have been given for polymer melt at different continuum velocities. The velocity and temperature gradient boundary layer thickness are also discussed in relation to the quality of hydrodynamic coating of wire.     

A Transformed Coordinates Shallow Water Model for the Head of the Bay of Bengal Using Boundary-Fitted Curvilinear Grids

The Bay of Bengal is surrounded by coastline except to the south, where there is open sea. The coastline bends most sharply along the coast of Bangladesh, and there are many small and large islands in the offshore region there. In order to incorporate the island boundaries and the curved coastline properly, in any numerical scheme it is often necessary to consider a very fine grid resolution along the coastal belts whereas this is unnecessary away from the coasts. However, a very fine resolution involves more memory and more CPU time in the numerical solution process, and invites numerical instability. On the other hand, boundary-fitted curvilinear grids in hydrodynamic models for coastal seas, bays and estuaries not only fit to the coastline but also render the finite difference schemes simpler and more accurate. In this article, the boundary-fitted curvilinear grids for the model represent the complete boundary of the area considered by four curves defined by four functions, and the four boundaries of two of the larger islands are then represented approximately by two general functions. An appropriate independent coordinate transformation maps the curvilinear physical area to a square domain, and each island boundary is transformed to a rectangle within this square domain. The vertically integrated shallow water equations are transformed to the new space domain, and solved by a regular explicit finite difference scheme. The model is applied to compute the water levels due to astronomical tides, and also the water levels due to surges associated with tropical storms that hit the coast of Bangladesh.     

Modified nano supported catalyst for selective catalytic hydrogenation of edible oils

We report an interesting finding that the catalytic performance of supported Ni/γ-Al₂O₃ catalyst towards selective catalytic hydrogenation of edible oils can be greatly enhanced by pretreatment of the γ-Al₂O₃ support before catalyst preparation. Calcination of Al₂O₃ at appropriate temperatures results in the highly dispersive nano Ni/γ-Al₂O₃ catalyst and thus improves the catalytic performance. Catalyst sample of improved physical properties prepared by modified procedure using γ-Al₂O₃ as support was characterized using powder XRD, SEM, BET, FTIR, Particle size analyzer, CO-chemisorption, and TPR studies. These studies indicate that support pretreatment results in enhancing catalyst dispersion with increase in Ni loadings. Clearly the effect of surface area and particle size of the catalyst coupled with surface properties and method of catalyst preparation on the saturated fats content of the foods like margarines prevails.     

Deep Learning-Based FOPID Controller for Cascaded DC-DC Converters

Smart grids and their technologies transform the traditional electric grids to assure safe, secure, cost-effective, and reliable power transmission. Non-linear phenomena in power systems, such as voltage collapse and oscillatory phenomena, can be investigated by chaos theory. Recently, renewable energy resources, such as wind turbines, and solar photovoltaic (PV) arrays, have been widely used for electric power generation. The design of the controller for the direct Current (DC) converter in a PV system is performed based on the linearized model at an appropriate operating point. However, these operating points are ever-changing in a PV system, and the design of the controller is usually accomplished based on a low irradiance level. This study designs a fractional-order proportional-integrated-derivative (FOPID) controller using deep learning (DL) with quasi-oppositional Archimedes Optimization algorithm (FOPID-QOAOA) for cascaded DC-DC converters in micro-grid applications. The presented FOPID-QOAOA model is designed to enhance the overall efficiency of the cascaded DC-DC boost converter. In addition, the proposed model develops a FOPID controller using a stacked sparse autoencoder (SSAE) model to regulate the converter output voltage. To tune the hyper-parameters related to the SSAE model, the QOAOA is derived by the including of the quasi-oppositional based learning (QOBL) with traditional AOA. Moreover, an objective function with the including of the integral of time multiplied by squared error (ITSE) is considered in this study. For validating the efficiency of the FOPID-QOAOA method, a sequence of simulations was performed under distinct aspects. A comparative study on cascaded buck and boost converters is carried out to authenticate the effectiveness and performance of the designed techniques.     

Correction to: A review of machine learning-based human activity recognition for diverse applications

Neural Computing and Applications -