This paper introduces a chess-playing robotic system that is designed to autonomously play board games against human opponents. The control of the robotic arm manipulator is addressed in terms of speed and position control. A complete control system is proposed to control the Lab-Volt 5150 robotic manipulator which is a five degree of freedom (DOF) robotic manipulator arm. A smart chessboard is built for tracking opponent’s movement. Board representation and search techniques are provided by using the free and open source chess application the "SharpChess". It was modified under VC# environment to fulfill the project requirement. The implemented control is a networked control system (NCS) scheme, the network exchanges the necessary information between the system parts. The proposed systems with all of their parts are tested in a real time with a real chess tournament and the system gave satisfactory results.
Keywords - Smart Chessboard, Robotic Manipulator, Lab-Volt 5150

In this paper, we present a new method to interact with the robotic hand by using a human hand gesture mirroring technique. This method uses a camera to get the input from the user and the robotic hand uses a microcontroller and servo motors. Such interface not only enables users to manipulate a remote robot by demonstration, but also ensures user-friendly interaction and software reusability in developing a networked robot system. The gesture-based remote human-robot interaction is uses any conventional monocular 2D camera. Experiments show an accuracy that outperforms a conventional light fall-off baseline, and is comparable to high-quality consumer cameras, but with a dramatically reduced cost, power consumption, and form-factor.
Keywords: Augmented reality, Gesture Control, Mechanized Division, Human Robot Interaction.

Colleges need to deal with huge amount of information in order to manage their issues like student registration, examination …etc., and usually all of these issues are handled manually. Obviously, this conventional method is not the efficient way due to the time and effort it consumes. In this paper a solution to this problem is presented, designed, implemented and analyzed. The proposed system makes a big difference in the way the college deals with its issues by utilizing new technologies and modern efficient system. It is a web-based application with different privileges, consists of three main subsystems: Registration Office Subsystem, Examination Committee Subsystem, and Students Subsystem.

Keywords- EC-IEB, MIS, SMIS, Registration Office Subsystem, Examination Committee.

Cloud storage is a model of networked online storage where data is stored in virtualized pools of storage which are generally hosted by third parties. Hosting companies operate large data centers, and people who require their data to be hosted buy or lease storage capacity from them. The data center operators, in the background, virtualizes the resources according to the requirements of the customer and expose them as storage pools, which the customers can themselves use to store files or data objects. Physically, the resource may span across multiple servers. The safety of the files depends upon the hosting websites.

A database can contain several dimensions or attributes. Many Clustering methods are designed for clustering low–dimensional data. In high dimensional space finding clusters of data objects is challenging due to the
curse of dimensionality. When the dimensionality increases, data in the irrelevant dimensions may produce much noise and mask the real clusters to be discovered. To deal with these problems, an efficient feature subset selection technique for high dimensional data has been proposed.
The FAST algorithm works in two steps. In the first step, features are divided into clusters by using graph-theoretic clustering methods. In the second step, the most representative feature that is strongly related to target classes is selected from each cluster to form a subset of features. Features in different clusters are relatively independent; the clustering-based strategy of FAST has a high probability of producing a subset of useful and independent features. The Minimum-Spanning Tree (MST) using Prim’s algorithm can concentrate on one tree at a time. To ensure the efficiency of FAST, adopt the efficient MST using the Kruskal’s Algorithm clustering method.

Keywords:  Feature subset selection, filter method,feature clustering, graph-based clustering, Kruskal’s algorithm

In this paper, we discuss the text search application of finite automata. First Nondeterministic Finite Automata designed, based on the given keywords. Then Nondeterministic Finite Automata converted into Deterministic Finite Automata. Then given keywords are searched using given paragraph. The transition function used to explain the text search of finite automata.
Keywords -- Finite Automata, Text search, Keywords.

A biometric system provides automatic identification of an individual based on a unique feature or characteristic possessed by the individual. This work deals with the development of a highly robust and efficient biometric person identification system based on fingerprint features. Human fingerprints are rich in details called minutiae, which can be used as identification marks for fingerprint verification. The goal of this project is to develop a complete system for fingerprint verification through extracting and matching minutiae. To achieve good minutiae extraction in fingerprints with varying quality, pre-processing in form of image enhancement and binarization is first applied on fingerprints before they are evaluated. Many methods have been combined to build a minutia extractor and a minutia matcher. Minutia-marking with false minutiae removal methods are used in the work. An alignment-based elastic matching algorithm has been developed for minutia matching. This algorithm is capable of finding the correspondences between input minutia pattern and the stored template minutia pattern without resorting to exhaustive search. The developed work utilizes finger print minutia as a feature for finger print identification. The software platform used for the implementation of the research work is MATLAB. Total 80 fingerprint images have been used to present the effectiveness of the developed work from fingerprint database of the FVC2000 (Fingerprint Verification Competition 2000). After the complete analysis it is found that the fingerprint recognition efficiency of the developed system is very high about 95 %, which is quit higher to the available fingerprint recognition techniques.

Keywords— Biometric system, fingerprint, minutia, feature extraction, feature matching.

In this scientific era, web is an important part of our lives because it provides anytime, anywhere access to information and services. These services provided by web are called web applications. Everyday millions of users connect to these web applications for various activities like for business transactions, financial transactions, social communication and much more. Despite of such advantages, security is one of the major issue of web applications. Web applications have been split into browser side and server side components. In this paper some browser side and server side attacks have been discussed and some techniques like web application scanners and firewalls have also been discussed to prevent these attacks.

Keywords— Web Application Security, Application Logic Vulnerability, Web Application Scanners, Firewalls.

Data mining is the process of extracting hidden patterns from large amounts of data and is  increasingly important tool for transforming  data into information. It is mostly used in a wide range of profiling practices, such as marketing, surveillance, and other practices. Association Rules mining is an important technique of data mining. Association rule mining, was proposed for market basket data, and it has many potential applications areas.  The most promising application area in the spatial data is remote sensed imagery (RSI) data that can extract interesting patterns and rules from spatial data sets and combination of other data such as ground and weather data, and images. It also  includes  precision agriculture, resource discovery and other application areas. In this paper we discover the P-trees algorithm, based on P-trees algorithm association rule mining algorithm PARM  evaluates calculation and significant  pruning techniques to modify  the efficiency of the rule mining process. With our algorithms, association rules mining technique is totally based on RSI spatial data.

Keywords— Association rule mining, data mining, remote sensed imagery (RSI), spatial data, PARM algorithm.