Information Technology

This paper presents a novel method for early detection of forming a Tumor i.e. Micro-calcifications in Mammograms. The main objective of this paper is to segment and detect the Micro-calcification (MCCs) from Digital mammograms that helps to provide and support for clinical decision to perform biopsy of the breast. In this paper, there are two aspects. First is to enhance the image by using Mathematical Morphology and denoise by Wavelet Transform and segmentation and detection of Micro-calcifications using Spot detection. Second is to extract texture based features by using Gabor filters from the segmented image and finally classify it by using Probabilistic Neural Network (PNN) classifier. The Mammogram database consist of 154 images, in which 90 images are taken for training the Probabilistic neural network and 64 images are used for testing purpose.

Supporting different data structures and their variations in both static and dynamic aspects are one of the challenges in programming languages. One of the data structures is property list of which applications use it as a convenient way to store, organize, and access standard types of data. In this paper, the solution methods for implementation Property List as Link List, Hash and Tree are reviewed. Then an efficient way to implement the property list as Set is presented and compared with the existing methods.

Recent advances in radio and embedded systems have enabled the proliferation of wireless sensor networks. Wireless sensor networks are tremendously being used in different environments to perform various monitoring tasks such as search, rescue, disaster relief, target tracking and a number of tasks in smart environments. In many such tasks, node localization is inherently one of the system parameters. Node localization is required to report the origin of events, assist group querying of sensors, routing and to answer questions on the network coverage. So, one of the fundamental challenges in wireless sensor network is node localization.

Travelling salesman problem is an NP complete problem and can be solved using approximation algorithms. It is a minimization problem starting and finishing at a specified vertex after having visited every other vertex exactly once. Often, the model is a complete graph. An algorithm that returns near-optimal solutions is called approximation algorithms. Through analyzing the Metric TSP, the performance of the approximation algorithm can be improved significantly using parallelization that implements a program to find a path with approximately minimum travelling cost through parallel depth-first search and the result can be verified using graphical analysis of spanning trees.

Cloud computing provides the way to share distributed resource and services that belong to different organizations. Since cloud computing share distributed resources via network in the open environment thus it makes security problems. All types of users who require the secure transmission or storage of data in any kind of media or network. Since, the data transmissions on the internet or over any networks are vulnerable to the hackers attack. I’m in great need of encrypting the data. I propose a method to build a trusted computing environment for cloud computing system. In this method some important security service including authentication, encryption, decryption and compression are provided in the cloud computing system. Need of this software is divided in to three modules: Encryption, Decryption, and Compression.

Elliptic curves are algebraic curves that have been studied by many mathematicians since the seventeenth century. In 1985, Neal Koblitz and Victor Miller independently proposed public key cryptosystems using the group of points on an elliptic curve. The elliptic curve cryptosystem (ECC) was thus created. Since then, numerous researchers and developers have spent years researching the strength of ECC and improving techniques for its implementation. Secure applications in smart cards present implementation challenges particular to the platform’s memory, bandwidth, and computation constraints. ECC’s unique properties make it especially well suited to smart card applications. This paper describes the Elliptic Curve Cryptography algorithm and its security over RSA algorithm.

Static analysis means examining a program code and overcoming all possible errors that tend to occur at run-time. Static analysis tools are efficient in finding bugs and correction of defects that arise due to improper functioning of the code, before the actual execution of the code [10]. In recent times, technology has facilitated us with new tools that do deeper and more efficient code analysis and have a higher defect detection rate along with low fake warning ratio. This paper aims to deal with buffer overrun anomalies occurring in many areas of source code in Java.

Security has become the greatest problem within and outside the organizations. User ID, passwords and firewalls are the common steps that organizations take to secure their computers. However, these are not so effective mediums in current context of unsecure eon. Intruders and attackers are so advanced that they access the computer and manipulate it, so they cannot be traced easily. Through this contribution objective is to find out & present existing intrusion detection system (IDS) with their pros and cons that will be helpful to select the best one and provide the secure environment so that system will be protected from intrusion and attacks.

The advent of compression standards has led to the proliferation of innovative techniques in the compressed domain has become an active research topic. This paper presents an overview of the latest video compression standards related to the H.26xSeries and this paper is specifically covered including its latest standard, H.265 otherwise known as AVC (Advanced Video Coding). It also provides an overview of compression rules of thumb for different standards and the corresponding performance requirements for real-time implementations.

In recent years, we have witnessed a dramatic popularity of online social networking services, in which millions of people publicly communicate for a kind of mutual friendship relations. Social network research is one of the fastest growing academic areas as it is continuously expanding within our society. One key element of this field of research is social network visualization, which refers to the use of sociogram / illustrative diagrams of the joins that connect various actors in social networks. Visualization of social networks has a rich history, particularly within the social science since at least the 1930s. The use of graphical representations is one of the main defining properties of social networks. Researchers make use of pictorial images of social networks in order to communicate and understand the content and patterns within social networks. However, visual diagrams of social networks often suffer from a range of problems, the most common of which being the high density of edges and complex structures in large networks, providing sociograms that often appear as unclear set of nodes and edges. In this paper, we have made every possible effort to remove the fear from mind of people that understanding networks is a difficult process as it is difficult to visualize, navigate, and find patterns in networks. For this, we begin by defining what constitutes a social network site and then present our introduction of basic concepts of social networks, social network sites and then discussed about visualization needs and problems, benefits of using data visualization, implementations of visualization available over time.