Hall effect on unsteady Hartmann flow with heat transfer under exponential decaying pressure gradient

The unsteady Hartmann flow of an electrically conducting, viscous, incompressible fluid bounded by two parallel non-conducting porous plates is studied with heat transfer taking the Hall effect into consideration. An external uniform magnetic field and a uniform suction and injection are applied perpendicular to the plates while the fluid motion is subjected to an exponential decaying pressure gradient. The two plates are kept at different but constant temperatures while the Joule and viscous dissipations are included in the energy equation. The effect of the ion slip and the uniform suction and injection on both the velocity and temperature distributions is examined. On leave from: Department of Engineering Mathematics and physics, Fac. of Engineering, El-Fayoum University, El-Fayoum, Egypt.     

Software‐defined networking approach for enhanced evolved packet core network

The evolved packet core (EPC) network is the mobile network standardized by the 3rd Generation Partnership Project and represents the recent evolution of mobile networks providing high‐speed data rates and on‐demand connectivity services. Software‐defined networking (SDN) is recently gaining momentum in network research as a new generation networking technique. An SDN‐based EPC is expected to introduce gains to the EPC control plane architecture in terms of simplified, and perhaps even software‐based, vendor independent infrastructure nodes. In this paper, we propose a novel SDN‐based EPC architecture along with the protocol‐level detailed implementation and provide a mechanism for identifying information fields exchanged between SDN‐EPC entities that maintains correct functionality with minimal impact on the conventional design. Furthermore, we present the first comprehensive network performance evaluation for the SDN‐based EPC versus the conventional EPC and provide a comparative analysis of 2 networks performances identifying potential bottlenecks and performance issues. The evaluation focuses on 2 network control operations, namely, the S1‐handover and registration operations, taking into account several factors, and assessing performance metrics such as end‐to‐end delay (E2ED) for completion of the respective control operation, and EPC nodes utilization figures.     

Brainwave Classification for Character-Writing Application Using EMD-Based GMM and KELM Approaches

A brainwave classification, which does not involve any limb movement and stimulus for character-writing applications, benefits impaired people, in terms of practical communication, because it allows users to command a device/computer directly via electroencephalogram signals. In this paper, we propose a new framework based on Empirical Mode Decomposition (EMD) features along with the Gaussian Mixture Model (GMM) and Kernel Extreme Learning Machine (KELM)-based classifiers. For this purpose, firstly, we introduce EMD to decompose EEG signals into Intrinsic Mode Functions (IMFs), which actually are used as the input features of the brainwave classification for the character-writing application. We hypothesize that EMD along with the appropriate IMF is quite powerful for the brainwave classification, in terms of character applications, because of the wavelet-like decomposition without any down sampling process. Secondly, by getting motivated with shallow learning classifiers, we can provide promising performance for the classification of binary classes, GMM and KELM, which are applied for the learning of features along with the brainwave classification. Lastly, we propose a new method by combining GMM and KELM to fuse the merits of different classifiers. Moreover, the proposed methods are validated by using the volunteer-independent 5-fold cross-validation and accuracy as a standard measurement. The experimental results showed that EMD with the proper IMF achieved better results than the conventional discrete wavelet transform (DWT) feature. Moreover, we found that the EMD feature along with the GMM/KELM-based classifier provides the average accuracy of 77.40% and 80.10%, respectively, which could perform better than the conventional methods where we use DWT along with the artificial neural network classifier in order to get the average accuracy of 80.60%. Furthermore, we obtained the improved performance by combining GMM and KELM, i.e., average accuracy of 80.60%. These outcomes exhibit the usefulness of the EMD feature combining with GMM and KELM based classifiers for the brainwave classification in terms of the Character-Writing application, which do not require any limb movement and stimulus.     

Overlapping Shadow Rendering for Outdoor Augmented Reality

Realism rendering methods of outdoor augmented reality (AR) is an interesting topic. Realism items in outdoor AR need advanced impacts like shadows, sunshine, and relations between unreal items. A few realistic rendering approaches were built to overcome this issue. Several of these approaches are not dealt with real-time rendering. However, the issue remains an active research topic, especially in outdoor rendering. This paper introduces a new approach to accomplish reality real-time outdoor rendering by considering the relation between items in AR regarding shadows in any place during daylight. The proposed method includes three principal stages that cover various outdoor AR rendering challenges. First, real shadow recognition was generated considering the sun’s location and the intensity of the shadow. The second step involves real shadow protection. Finally, we introduced a shadow production algorithm technique and shades through its impacts on unreal items in the AR. The selected approach’s target is providing a fast shadow recognition technique without affecting the system’s accuracy. It achieved an average accuracy of 95.1% and an area under the curve (AUC) of 92.5%. The outputs demonstrated that the proposed approach had enhanced the reality of outside AR rendering. The results of the proposed method outperformed other state-of-the-art rendering shadow techniques’ outcomes.     

Local-Tetra-Patterns for Face Recognition Encoded on Spatial Pyramid Matching

Face recognition is a big challenge in the research field with a lot of problems like misalignment, illumination changes, pose variations, occlusion, and expressions. Providing a single solution to solve all these problems at a time is a challenging task. We have put some effort to provide a solution to solving all these issues by introducing a face recognition model based on local tetra patterns and spatial pyramid matching. The technique is based on a procedure where the input image is passed through an algorithm that extracts local features by using spatial pyramid matching and max-pooling. Finally, the input image is recognized using a robust kernel representation method using extracted features. The qualitative and quantitative analysis of the proposed method is carried on benchmark image datasets. Experimental results showed that the proposed method performs better in terms of standard performance evaluation parameters as compared to state-of-the-art methods on AR, ORL, LFW, and FERET face recognition datasets.     

Application of sliding mode control for maximum power point tracking of solar photovoltaic systems: A comprehensive review

A robust maximum power point tracking (MPPT) control is of paramount importance in the performance enhancement and the optimization of photovoltaic systems (PVSs). Solar panel exhibits nonlinear behavior under real climatic conditions and output power fluctuates with the variation in solar irradiance and temperature. Therefore, a control strategy is requisite to extract maximum power from solar panels under all operating conditions. Sliding mode control (SMC) is extensively used in non-linear control systems and has been implemented in PVSs to track maximum power point (MPP). The objective of this work is to classify, scrutinize and review the SMC techniques used to extract maximum power from PVSs in both off-grid and grid connected applications. The first order, perturb and observe, incremental conductance, linear expression based sliding mode control algorithms and their adaptive forms are discussed in detail. The advanced form of SMC, terminal sliding mode control (TSMC), super twisting theorem (STT) and artificial intelligent (AI) algorithm based are also presented with the focused application of MPPT of PVSs. A tabular comparison is provided at the end of each category to help the users to choose the most appropriate method for their PV application. It is anticipated that this work will serve as a reference and provides important insight into MPPT control of the PV systems.     

Kinematic analysis of the multi-link five-point suspension system in point coordinates

In this paper, a numerical algorithm for the kinematic analysis of a multi-link five-point suspension system is presented. The kinematic analysis is carried out in terms of the rectangular Cartesian coordinates of some defined points in the links and at the joints. Geometric constraints are introduced to fix the relative positions between the points belonging to the same rigid body. Position, velocity and acceleration analyses are carried out. The presented formulation in terms of this system of coordinates is simple and involves only elementary mathematics. The results of the kinematic analysis are presented and discussed.     

Prediction of subharmonic oscillation in switching regulators: from a slope to a ripple standpoint

New exact critical conditions for predicting subharmonic instability in switching regulators are approximated by simple design-oriented expressions valid under practical conditions. These simplified expressions contain the ripple and slope information of the feedback control signal. Depending on the converter topology, the controller used and values of parasitic parameters, either the slope or the ripple can be dominant in predicting instability. A discussion on the validity of this interpretation is illustrated through six different examples of switching regulators using the concept of the spectral radius and the relative degree of the system loop. Using this approach, the boundary between the desired stable region and the subharmonic instability can be easily obtained. The theoretical results are validated by means of numerical simulations.     

A new higher order effective P–C methods for stiff systems

In this paper a special class of k-step methods of order k+1 with two free parameters up to order 9 are established. The stability analysis of the P–C scheme is investigated. The coefficients of our class and the values of the parameters for getting A₀-stable schemes are tabulated. The relation between the parameters for obtaining L(α)-stable formula is determined. A comparison between the stability region and the error estimation for the fourth-order of our scheme and Cash's scheme is carried on.     

A new approach to the design of robust load-frequency controller for large scale power systems

A new method is presented for derivation of a robust controller for the load frequency controller of interconnected power systems with uncertain parameters. A combination of ‘Matching conditions’ and Lyapunov stability theory is adopted to implement a robust stabilizing controller. The stability analysis of the closed-loop interconnected systems for all admissible uncertainties is considered. The application of the proposed robust control scheme is considered through simulation studies of two-area power system model. Performance robustness of the proposed scheme is compared with the recent work of Wang et al. (1993, IEE Proc. C Vol. 140, pp. 11–16), and found to be very good.