AES-Based Encoding and Decoding Images using MATLAB
A Novel Technique of Sign Language Recognition System using Machine Learning for Differently Abled Person
Implementation of Machine Learning Techniques for Depression in Text Messages: A Survey
A Study of Ransomware Attacks on Windows Platform
Techniques of Migration in Live Virtual Machine and its Challenges
Efficient Agent Based Priority Scheduling and LoadBalancing Using Fuzzy Logic in Grid Computing
A Survey of Various Task Scheduling Algorithms In Cloud Computing
A Viable Solution to Prevent SQL Injection Attack Using SQL Injection
A Computational Intelligence Technique for Effective Medical Diagnosis Using Decision Tree Algorithm
Integrated Atlas Based Localisation Features in Lungs Images
Data source represents the core part of any application. Web application can get the benefit of multiple data sources at the same time. This paper, focuses on delivering a platform independent application. Web applications are popular due to the ubiquity of web browsers, and the convenience of using a web browser as a client to update and maintain web applications without distributing and installing software on potentially thousands of client computers is a key reason for their popularity. This paper compares two different sources, Microsoft access database and MY-SQL data source. The comparison has been made according to the simplicity of the design of both the systems and performance. PHP has been used to build and produce both systems, and WAMP server has been used to test the systems provided in this paper along with a mid-range computers. This paper, shows in practice that the PHP-MYSQL “couple” still applicable and usable and has the both free and fast benefits.
Increased usage of web applications in recent years has emphasized the need to achieve confidentiality, integrity and availability of web applications. Web applications are used by the organizations to provide services like online banking, online shopping, social networking, etc. So people expect these applications to be secure and reliable when they are paying bills, shopping online, making transactions, etc. These web applications consist of underlying databases containing confidential user's information like financial information records, medical information records, personal information records which are highly sensitive and valuable, which in turn makes web applications as an ideal target for external attacks such as Structured Query Language (SQL) Injection. In fact, SQL Injection is categorized as the top-10 2010 web application vulnerabilities experienced by web applications according to OWASP (Open Web Application Security Project) . There is an emerging need to handle such attacks to secure the stored information.
Grid computing is the process of applying more computer resources to solve the complex problem. Load balancing and resource management are the major problems in grid computing. The goal of the load balancing algorithms is to allocate the load on grid resources to exploit their utilization while decreasing the total task execution time. To overcome these problems, the author has proposed an efficient agent based priority scheduling and fuzzy logic load balancing algorithm. The major role of priority scheduling is to assign priority to jobs and to assign jobs to available resources. After scheduling the jobs to resource, loads are balanced using the fuzzy rules. In this proposed scheme, the fuzzy rules are generated using the resource CPU (Central Processing Unit) speed, memory capacity and current load. The performance analysis shows that, the proposed priority scheduling and fuzzy load balancing can improve the overall performance of the grid computing resource.
In this paper, the authors have presented an efficient algorithm for improving the performance of speaker verification system by using polynomial kernel support vector machine along with dynamic time warping. The objective of speaker verification is to verify the identity of the speaker by characterizing the information of speaker. The idea is to improve the accuracy of Support Vector Machine (SVM) classifier with the combination of dynamic time warping and polynomial kernel. The resultant of SVM has higher degree of precision as well as accuracy. To characterize the classification accuracy and precision, we use a technique called as confusion matrix. The authors have performed the experiment over database of 30 speakers including male and female voices. The polynomial kernel SVM is used here to improve the accuracy.
This paper introduces a systematic approach for design of fuzzy inference system based on the class of neural network to predict the existence of Mycobacterium tuberculosis. Fuzzy systems have reached a recognized success in several applications to solve diverse class of problems. Currently, there is an existence trend to expand them in medical field and using them with adaptation capabilities through combination with other various techniques. This article focus on the development of data mining solution using Adaptive Neuro Fuzzy Inference System (ANFIS) that makes diagnosis of tuberculosis bacteria as precise as possible and helps in deciding whether it is reasonable to start treatment without waiting for the accurate medical tests. Dataset are collected from 200 different patient records which are obtained from health clinic (consent of physicians and patients). Patient record has 19 different input attributes which covers demographic and medical test data. The transparency, objectivity and easy implementation of the proposed method generates classes of tuberculosis that suits the need of pulmonary physicians and decrease the time consumed in generating diagnosis provide a useful way to start diagnosis in more reasonable and fairer manner.