Hybrid spatial‐spectral MoM analysis of microstrip structures

In this paper, a new hybrid method formulation to resolve the mixed potential integral equation in an efficient and a fast approach, which is based on a simultaneous formulation in both spatial and spectral domains, is proposed. The entries of the method of moments matrix are then given by the sum of two integrals. The first one is expressed in the spatial domain. This part is analytically evaluated after a development in Taylor series of the exponential terms in the function to integrate. The integrals expressed in the spectral domain have a finite range, and they are calculated using numerical integration. Then the convergence problem is avoided in this approach. A good agreement between the simulated and measured results has been achieved. Copyright © 2015 John Wiley & Sons, Ltd.     

Dipper Throated Algorithm for Feature Selection and Classification in Electrocardiogram

Arrhythmia has been classified using a variety of methods. Because of the dynamic nature of electrocardiogram (ECG) data, traditional handcrafted approaches are difficult to execute, making the machine learning (ML) solutions more appealing. Patients with cardiac arrhythmias can benefit from competent monitoring to save their lives. Cardiac arrhythmia classification and prediction have greatly improved in recent years. Arrhythmias are a category of conditions in which the heart's electrical activity is abnormally rapid or sluggish. Every year, it is one of the main reasons of mortality for both men and women, worldwide. For the classification of arrhythmias, this work proposes a novel technique based on optimized feature selection and optimized K-nearest neighbors (KNN) classifier. The proposed method makes advantage of the UCI repository, which has a 279-attribute high-dimensional cardiac arrhythmia dataset. The proposed approach is based on dividing cardiac arrhythmia patients into 16 groups based on the electrocardiography dataset’s features. The purpose is to design an efficient intelligent system employing the dipper throated optimization method to categorize cardiac arrhythmia patients. This method of comprehensive arrhythmia classification outperforms earlier methods presented in the literature. The achieved classification accuracy using the proposed approach is 99.8%.     

Erosion Regimes Characterization of Soda-Lime Glass

Silicon - In this work, a semi-empirical relationship between sandblasting times and the surface roughness is presented. The derived relation is valid for the case where the erosion process does...     

Robust stabilization for affine control systems in Banach spaces

This paper is devoted to the investigation of feedback stabilization of affine control systems on real Banach spaces. Under an appropriate decomposition of the state space, we provide sufficient conditions for exponential stabilization of the system at hand. Furthermore, we show that the proposed feedback law remains a stabilizing control under some types of perturbations on the dynamic and the control operator. Finally, two illustrative examples are provided.     

Intelligent Aquila Optimization Algorithm-Based Node Localization Scheme for Wireless Sensor Networks

In recent times, wireless sensor network (WSN) finds their suitability in several application areas, ranging from military to commercial ones. Since nodes in WSN are placed arbitrarily in the target field, node localization (NL) becomes essential where the positioning of the nodes can be determined by the aid of anchor nodes. The goal of any NL scheme is to improve the localization accuracy and reduce the localization error rate. With this motivation, this study focuses on the design of Intelligent Aquila Optimization Algorithm Based Node Localization Scheme (IAOAB-NLS) for WSN. The presented IAOAB-NLS model makes use of anchor nodes to determine proper positioning of the nodes. In addition, the IAOAB-NLS model is stimulated by the behaviour of Aquila. The IAOAB-NLS model has the ability to accomplish proper coordinate points of the nodes in the network. For guaranteeing the proficient NL process of the IAOAB-NLS model, widespread experimentation takes place to assure the betterment of the IAOAB-NLS model. The resultant values reported the effectual outcome of the IAOAB-NLS model irrespective of changing parameters in the network.