Novel numerical solutions of nonlinear heat transfer problems using the linear barycentric rational interpolation

In this investigation, a numerical technique to obtain the approximate solutions of four well‐known nonlinear differential equations in the area of heat transfer is presented. This method is based on the operational matrix of derivative of linear barycentric rational interpolation. The main advantages of this approach are that it uses the Floater‐Hormann weights, which are very efficient in practice, and reduces the governing differential equation to a system of algebraic equations. The results are compared with the obtained numerical results of the fourth‐order Runge‐Kutta method along with the shooting method and some of the previously existing methods. The acquired results reveal that the derivative operational matrix method with barycentric rational basis functions is very efficient and can be implemented easily and fast.     

Timeout Period Analysis to Detect Black Hole Attack in Multihop Wireless Ad Hoc Networks

A novel approach is proposed to estimate the timeout period used in wireless ad hoc networks in order to detect misbehaving nodes that make black hole attacks. Timeout period is an acceptable time frame for a node to forward a packet and is used to judge if the node is behaving properly. To avoid misjudgment and false alarms, the accuracy of the estimate of the timeout period is very important. Our method is based on the IEEE 802.11 MAC protocol and Dynamic Source Routing protocol. The main contribution of this paper is proposing a queuing analysis to calculate the mean and maximum delay per hop implementing the 95-percentile of medium access waiting time. In addition, a new technique is introduced that can be applied to determine the mean number of hops in flooding-based ad hoc networks, taking into account edge effects. For each proposed model, analytical results are compared with results obtained from simulations and the validity of the models is confirmed by observing the close relationship between the results.     

Application of shifted Jacobi pseudospectral method for solving (in)finite-horizon min–max optimal control problems with uncertainty

The difficulty of solving the min–max optimal control problems (M-MOCPs) with uncertainty using generalised Euler–Lagrange equations is caused by the combination of split boundary conditions, nonlinear differential equations and the manner in which the final time is treated. In this investigation, the shifted Jacobi pseudospectral method (SJPM) as a numerical technique for solving two-point boundary value problems (TPBVPs) in M-MOCPs for several boundary states is proposed. At first, a novel framework of approximate solutions which satisfied the split boundary conditions automatically for various boundary states is presented. Then, by applying the generalised Euler–Lagrange equations and expanding the required approximate solutions as elements of shifted Jacobi polynomials, finding a solution of TPBVPs in nonlinear M-MOCPs with uncertainty is reduced to the solution of a system of algebraic equations. Moreover, the Jacobi polynomials are particularly useful for boundary value problems in unbounded domain, which allow us to solve infinite- as well as finite and free final time problems by domain truncation method. Some numerical examples are given to demonstrate the accuracy and efficiency of the proposed method. A comparative study between the proposed method and other existing methods shows that the SJPM is simple and accurate.     

Nanoethosomal formulation of gammaoryzanol for skin-aging protection and wrinkle improvement: a histopathological study

Background: Free radical scavengers and antioxidants, with the main focus on enhanced targeting to the skin layers, can provide protection against skin ageing.

Objective: The aim of the present study was to prepare nanoethosomal formulation of gammaoryzanol (GO), a water insoluble antioxidant, for its dermal delivery to prevent skin aging.

Methods: Nanoethosomal formulation was prepared by a modified ethanol injection method and characterized by using laser light scattering, scanning electronic microscope (SEM) and X-ray diffraction (XRD) techniques. The effects of formulation parameters on nanoparticle size, encapsulation efficiency percent (EE%) and loading capacity percent (LC%) were investigated. Antioxidant activity of GO-loaded formulation was investigated in vitro using normal African green monkey kidney fibroblast cells (Vero). The effect of control and GO-loaded nanoethosomal formulation on superoxide dismutase (SOD) and malondialdehyde (MDA) content of rat skin was also probed. Furthermore, the effect of GO-loaded nanoethosomes on skin wrinkle improvement was studied by dermoscopic and histological examination on healthy humans and UV-irradiated rats, respectively.

Results: The optimized nanoethosomal formulation showed promising characteristics including narrow size distribution 0.17?±?0.02, mean diameter of 98.9?±?0.05?nm, EE% of 97.12?±?3.62%, LC% of 13.87?±?1.36% and zeta potential value of –15.1?±?0.9?mV. The XRD results confirmed uniform drug dispersion in the nanoethosomes structure. In vitro and in vivo antioxidant studies confirmed the superior antioxidant effect of GO-loaded nanoethosomal formulation compared with control groups (blank nanoethosomes and GO suspension).

Conclusions: Nanoethosomes was a promising carrier for dermal delivery of GO and consequently had superior anti-aging effect.     

NDNetGaming - development of a no-reference deep CNN for gaming video quality prediction

Multimedia Tools and Applications - Gaming video streaming services are growing rapidly due to new services such as passive video streaming of gaming content, e.g. Twitch.tv, as well as cloud...     

Coupled Quantity-Quality Simulation-Optimization Model for Conjunctive Surface-Groundwater Use

Many water resources optimization problems involve conflicting objectives which the main goal is to find a set of optimal solutions on, or near to, Pareto front. In this study a multi-objective water allocation model was developed for optimization of conjunctive use of surface water and groundwater resources to achieve sustainable supply of agricultural water. Here, the water resource allocation model is based on simulation-optimization (SO) modeling approach. Two surrogate models, namely an Artificial Neural Network model for groundwater level simulation and a Genetic Programming model for TDS concentration prediction were coupled with NSGA-II. The objective functions involved: 1) minimizing water shortage relative to the water demand, 2) minimizing the drawdown of groundwater level, and 3) minimizing the groundwater quality changes. According to the MSE and R² criteria, the results showed that the surrogate models for prediction of groundwater level and TDS concentration performed favorably in comparison to the measured values at the number of observation wells. In Najaf Abad plain case study, the average drawdown was limited to 0.18 m and the average TDS concentration also decreased from 1257 mg/lit to 1229 mg/lit under optimal conditions.     

SDN-based wireless user management system

The degradation of end-to-end quality of service (QoS) on mobile users is becoming a common issue for IEEE 802.11 infrastructure-based networks in crowded areas. This research tackles the issue by employing an SDN framework on an integrated wireless/wired environment. Thereby, we present the development and implementation of a system that performs user management by analyzing the network load from the OpenFlow statistics, as well as the wireless information collected from the associated users. In order to analyse the behaviour of the proposed user migration algorithm, we evaluate the system under scenarios with different traffic load and user session duration. From the experiments, we observed that in several cases wireless users get a considerable QoS improvement at the application layer (up to 30% improvement in throughput and up to 20% in delay in our simulations) once the system is activated. Based on the results, we present an analysis on how and when user migration in multi-access point IEEE 802.11 networks can be most effective.     

Synthesis and Characterization of Novel Sulfur-Functionalized Silica Gels as Mercury Adsorbents

This paper describes the synthesis, functionalization, and characterization of silica gels as mercury adsorbents. The synthesis was carried out according to the modified Stöber method using tetraethyl orthosilicate [TEOS], 3-mercaptopropyl trimethoxysilane [MPTMS] and bis(triethoxysilylpropyl) tetrasulfide [BTEPST] as precursors. The functionalization was carried out via co-condensation and impregnation methods using MPTMS, BTESPT, elemental sulfur [ES], and carbon disulfide [CS₂] as sulfur ligands. The choice of the sulfur ligands as precursors and functionalization agents was due to the existence of sulfur active groups in their molecular structures which were expected to have high affinity toward Hg(II) ions. The synthesized adsorbents were characterized by using scanning electron microscope, fourier transform infrared spectrophotometer, nitrogen adsorption/desorption, and energy dispersive X-ray diffractometer. The batch Hg(II) adsorption experiments were employed to evaluate the Hg(II) adsorption performances of the synthesized adsorbents under different pH values. The results revealed that the highest Hg(II) adsorption capacity was obtained for the SG-MPTMS(10) which was 47.83 mg/g at pH 8.5. In general, the existence of sulfur functional groups, especially MPTMS in the silica matrices, gave a significant enhancement of Hg(II) adsorption capacity and the sulfur functionalization via co-condensation method, which is potential as a superior approach in the mercury adsorbent synthesis.