Handwritten character recognition is one of the practically important issues in pattern recognition applications. The applications of digit recognition include in postal mail sorting, bank check processing, form data entry, etc. The main problem lies within the ability on developing an efficient algorithm that can recognize hand written digits, which is submitted by users by the way of a scanner, tablet, and other digital devices. This paper presents an approach to off-line handwritten digit recognition based on different machine learning techniques. The main objective of this paper is to ensure the effectiveness and reliability of the approached recognition of handwritten digits. Several machines learning algorithms (i.e. Multilayer Perceptron, Support Vector Machine, Naïve Bayes, Bayes Net, Random Forest, J48, and Random Tree) have been used for the recognition of digits using WEKA. The experimental results showed that the highest accuracy was obtained by Multilayer Perceptron with the value of 90.37%.

Abstract-Innanotechnologies, quantum-dot cellular automata (QCA) offer promising and attractive features for nano-scale computing. QCA effectively overcomes the scaling shortfalls of CMOS technology. One of the variants of QCA is 4 Dot 2 Electron QCA which is well explored and researched. The main concentration of this study is on 2 Dot 1 Electron QCA, an emerging variant of QCA. A novel and efficient XOR gate based on 2 Dot 1 Electron QCA is designed. Moreover a comparator using the proposed novel XOR gate is presented in this present scope. The proposed architecture is justified using a wellaccepted standard mathematical function based on Coulomb's law. Energy and power dissipation of the architecture are analyzed using different energy parameters. AS the compactness of proposed design is 76.4% the design met high degree of compactness and better efficiency.

A comparative investigation in the cell performance of Copper Indium Gallium Selenide (CIGS) thin-film solar cell has been reported. The main objective behind our work is to present the effect of the doping concentration on each layer i.e. window layer (ZnO), buffer layer (CdS) and absorption layer (CIGS) in the CIGS solar cell to find out the optimum doping concentration using ADEPT 2.0, a 1D simulation software. The device parameters are optimized separately for each layer. Energy conversion efficiency is calculated from light J-V characteristics curve. A total-area efficiency of 19•75% for ZnO:Al/i-ZnO/CdS/CIGS based thin-film solar cells has been reported.

Mobile cloud computing (MCC) is the availability of cloud computing services in a mobile environment. By providing optimal services for mobile users MCC incorporates the elements of mobile networks and cloud computing. In mobile cloud computing, all the data and complicated computing modules can be processed in clouds and mobile devices do not need a powerful configuration like CPU speed, memory capacity etc. However, the mobile devices are facing up with many struggles in their resources (e.g., battery life, storage, and bandwidth) and communications (e.g., privacy, mobility and security). These challenges have great affect in the improvement of service qualities. In this paper, we discuss the overview of mobile cloud computing technology together with the architecture, applications, major characteristics, security issues, advantage and limitation and possibly solution.

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