Management of legacy software and its code, generally written in procedural languages, is often costly and time-consuming. To help this management, a migration from procedural to object oriented paradigm could be a cost effective option. One approach for such migration can be based on the underlying dependency structure of the procedural source code. In this work, we propose a new heuristic algorithm that utilizes such structure for the design migration using agglomerative hierarchical clustering. The dependency structure that has been used involve functions, parameters and global data of the procedural code. Given a procedural code, the proposed approach produces candidate classes for an object oriented design. The proposed algorithm was tested against a database of procedural codes. The results obtained have been empirically validated using Jaccard similarity coefficient. It is observed that the proposed method yields 75.6% similarity with respect to the ground truth in the average case.

Malaria is a deadly disease that claims yearly lives of millions in Africa, and other endemic continents. The prevalence of malaria in these endemic regions is majorly attached to the lack of competent medical experts who are capable of providing medical care for the affected victims. This study considers developing a mobile based fuzzy expert system that could assist in diagnosing malaria. The fuzzification of crisp inputs by the system was carried out using an inter-valued and triangular membership functions while the deffuzification of the inference engine outputs was performed by weighted average method. Root sum square method of drawing inferences has been employed while the whole development has been achieved with the help of Java 2 Micro Edition of Java. This expert system executes on the readily available mobile devices of the patients. This fuzzy system was finally evaluated and confirmed effective in providing a human-expert like diagnosis.

Fingerprint matching is the most accurate method among the biometrics. They are used for recognizing the person identity. The matching of two fingerprint images based on the numbering of minutiae and bifurcation points. Minutiae based Algorithm only extract local features of fingerprint image. The new algorithm used pattern based method which covers the whole area of fingerprint image. It includes both local and global features of fingerprint image. This new algorithm divides in three phases. First phase include enhancing the image quality with the thresholding value and reducing the dimensional space of fingerprint image with principal component analysis. Principal Component analysis contains the Principal components in lower dimensionality space with high value information. In second phase, Gabor filter is used for extracting feature vectors from fingerprint image and number of feature vectors form feature map. In third phase, Euclidean distance is calculated between two feature maps to determine whether the two fingerprint images are same or not. The result evaluation is done on the basis of bifurcation and minutiae points and their comparisons with previous work.

This paper studies on image registration using Ant Colony Optimization technique of the medical imag-es. Ant Colony Optimization algorithm has ability of global optimization and facilitates quick search of opti-mal parameters for image registration. In this paper, a modified Ant Colony Optimization algorithm on prepro-cessed images is proposed to improve the accuracy in terms of PSNR (peak signal to noise ratio), Entropy and convergence speed. Preprocessing of images is adopted to remove noise so that extracted features provide more accurate and precise information about the image and results are more suitable for further analysis. The experi-mental results demonstrate the performance of proposed methodology as compared with traditional approaches as very promising.

The purpose of this article is to consider the notions of intuitionistic fuzzy soft matrices(IFSM) and to study some basic results associated with such matrices. This work deals particularly with the definition and some properties of transpose of intuitionistic fuzzy soft matrices. In the process, symmetric intuitionistic fuzzy matrix is also defined and some properties are discussed. Numerical examples are provided to make the concept clear.

A wireless sensor network (WSN) is an emerging field comprising of sensor nodes as basic units. These sensor nodes have limited resources like power, memory etc. WSNs can be used to monitor the remote areas where recharging or replacing the battery power of sensor nods is not possible. This limitation of WSNs makes energy consumption as a most challenging issue. Low-Energy Adaptive Clustering Hierarchy (LEACH) is an easiest and first significant protocol which consumes less amount of energy while routing the data to the base station. A lot of work has been done to improve energy efficiency of routing protocol by taking LEACH as a base protocol. In this review paper section I has introduction to Wireless Sensor Networks, section II has introduction of LEACH Protocol and all descendant protocols of LEACH with comparison table have been discussed in section III.

Computer applications and business administrations have gained significant importance in higher education. The type of education, students get in these areas depend on the geo-economical and the social demography. The choice of a institution in these area of higher education dependent on several factors like economic condition of students, geographical area of the institution, quality of educational organizations etc. To have a strategic approach for the development of importing knowledge in this area requires understanding the behavior aspect of these parameters. The scientific understanding of these can be had from obtaining patterns or recognizing the attribute behavior from previous academic years. Further, applying data mining tool to the previous data on the attributes identified will throw better light on the behavioral aspects of the identified patterns. In this paper, an attempt has been made to use of some techniques of education data mining on the dataset of MBA and MCA admission for the academic year 2014-15. The paper discusses the result obtained by applying RF and RT techniques. The results are analyzed for the knowledge discovery and are presented.

An SQL injection attack compromises the interactive web based applications, running database in the backend. The applications provide a form to accept user input and convert it into the SQL statement and fire the same to the database. The attackers change the structure of SQL statement by manipulating user inputs. The existing static and dynamic SQLIA detectors are being used for accurate detection of SQL injection, but it ignores the efficiency of the system. These detectors repeatedly verify the same queries inside the system, which causes unnecessary wastages of system resources. This paper contains the design approach of a parallel algorithm for the detection of SQL injection. The Algorithm uses the concept of Hot Query Bank (HQB) to cooperate with the existing SQLIA detectors (e.g. AMNESIA, SQLGuard, etc) and enhances the system performance. It simply keeps the information of previously verified queries in order to skip the verification process on the next appearance. The system performance has been observed by conducting a series of experiments on multi core processors. The experimental results have shown that parallel-SQLIA detector is 65% more efficient in term of time complexity. Further this design can be implemented in real web application environment; and the design interface can be standardized to cooperate with web application and the SQLIA detectors.