Earticle

Fractals are among the most exciting and intriguing mathematical objects ever discovered. Because of the spectacular development of technology - and particularly computers and computer science - during the last decades, they have become very popular not only in scientific and technological domains but also in mass media related fields such as advertising, computer art, computer design, computer animation and many others. Nowadays there is a wealth of programs and tools to generate fractals by computer. However, none of them is able to yield high-quality graphical output to be readily embedded into standard LaTeX source code in a text-like form. This paper is aimed at filling this gap by introducing a new and freely available KETPic add-on for generating and rendering IFS fractal objects. This new software, developed in the popular scientific program Matlab, generates LaTeXreadable code so that image files are no longer invoked nor required. The resulting files are astonishingly small when compared with their image file counterparts, thus leading to higher compression ratios than other conventional formats such as JPEG, GIF, PNG, EPS and the like. In addition, since IFS fractals are auto-similar they still offer better quality. In fact, a great advantage of this method is that any final image encoded as a collection of IFS becomes resolution independent and hence it can be enlarged at will in a lossless fashion. This paper describes our program and gives some examples to illustrate the excellent performance of our approach.

In this paper, we discuss an insider security which has been one of the biggest issues in the network security. By surveying and analyzing an issue of previous studies, we suggest an effective approach for future research. Approximately 90% of the information leakage incidents are recently being performed by internal workers. It is coming as a more serious problem than outsider attacks. The information leakage incident makes an organization or a company not only loses information but also gives a hard blow to the image. To prevent economic loss and damage to the image in advance, we need various research and development for effective solution.

A wireless sensor network consists of tiny sensing devices, with limited energy and processing ability. Some time we have to distribute a database on sensor network, because of limited energy in sensors, load balanced distributing database can increase the lifetime of this networks. In this paper we propose Fuzzy based approach for Load balanced distributing database on sensor Network that prolonging the network lifetime. We use vertical partitioning algorithms for distributing database on sensors. First we clustering the network and then distribute partitions on clusters. A simulator was built and Results of various simulation runs are consistent with the hypothesis.

In this paper we focus on alleviating malicious traffic from DDoS attacks since many famous websites have been attacked by them and massive losses have been reported in recent years. We propose a Priority Queue-Based scheme to analyze the interval of the arrival times of incoming packets in order to distinguish malicious traffic from normal traffic and to take care of malicious attacks clogging the network. We use the network simulator, NS2, to assess the efficiency of the proposed scheme. Simulation results show that the proposed Priority Queue-based scheme not only effectively decreases the flows of malicious packets from DDoS attacks with various packet rates, but also provides smooth and constant flows for packets sent by normal users. Furthermore, our priority queue-based scheme performs much better than other schemes when the number of the DDoS nodes becomes large.