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This paper presents a recognition system for handwritten Pashto letters. However, handwritten character recognition is a challenging task. These letters not only differ in shape and style but also vary among individuals. The recognition becomes further daunting due to the lack of standard datasets for inscribed Pashto letters. In this work, we have designed a database of moderate size, which encompasses a total of 4488 images, stemming from 102 distinguishing samples for each of the 44 letters in Pashto. The recognition framework uses zoning feature extractor followed by K-Nearest Neighbour (KNN) and Neural Network (NN) classifiers for classifying individual letter. Based on the evaluation of the proposed system, an overall classification accuracy of approximately 70.05% is achieved by using KNN while 72% is achieved by using NN.

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In recent years, the use of Autonomous Underwater Vehicle (AUV) along a constrained path can improve the data delivery ratio and maximize the energy efficiency in Underwater Wireless Sensor Networks (UWSNs). However, constant speed of AUV leads to limited communication to collect data packet from nodes deployed randomly in large scalable network. Moreover, the excessive number of associated nodes with Gateway Node (GN) causes to quick depletion of its energy, thus lead to hot spot problem. This poses prominent challenges in jointly improving the throughput with minimum energy consumption. To address these issues, we presented a novel scalable data gathering scheme called Scalable and Efficient Data Gathering SEDG routing protocol, that increases the packet delivery ratio as well as conserves limited energy by optimal assignment of member nodes with GN. Moreover, the variable sojourn interval of AUV decreases the packet drop ratio and hence, maximize the throughput of network.

In recent few years Wireless Sensor Networks (WSNs) have seen an increased interest in various applications like border field security, disaster management and medical applications. So large number of sensor nodes are deployed for such applications, which can work autonomously. Due to small power batteries in WSNs, efficient utilization of battery power is an important factor. Clustering is an efficient technique to extend life time of sensor networks by reducing the energy consumption. In this paper, we propose a new protocol; Energy Consumption Rate based Stable Election Protocol (ECRSEP). Our CH selection scheme is based on the weighted election probabilities of each node according to the Energy Consumption Rate (ECR) of each node. We compare results of our proposed protocol with Low Energy Adaptive Clustering Hierarchy (LEACH), Distributed Energy Efficient Clustering (DEEC), Stable Election Protocol (SEP), and Enhanced SEP(ESEP). Our simulation results show that our proposed protocol, ECRSEP outperforms all these protocols in terms of network stability and network lifetime.

In this study, an investigation of magnetohydrodynamics flow of Oldroyd-B fluid by a rotating disk with the influence of thermophoresis on the deposition of particles is discussed. Additionally, the Soret–Dufour effects are taken into consideration. The von Karman transformation is used and the numerical results are obtained through BVP Midrich technique in Maple. The results are given through graphical structure and tabular form. The solutions of the governing equations are obtained and presented graphically in the form of velocity fields, temperature and concentration distributions. The results of local Stanton number (or inward axial thermophoretic deposition velocity) are presented through table. Results reveal that axial thermophoretic velocity enhances with the enlargement of relative temperature difference parameter and thermophoretic coefficient.

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