Learn More
New Advances in mobile computer technology, along with rapid growth of quality and quantity of wireless networks, introduce new capabilities, applications, and concerns to computer science and industry. Unique requirements and constraints of mobile systems bring new challenges to software development for such environments. It demands reconsidering the(More)
Applications in pervasive computing environment exploit information about the context of use, such as the location, tasks and preferences of the user, in order to adapt their behavior in response to changing operating environments and user requirements. Utilizing context with aid of ontology in data and model, decision support systems can provide better and(More)
The process of scanning the events occurring in a computer system or network and analyzing them for warning of intrusions is known as intrusion detection system (IDS). This paper presents a new intrusion detection system based on tabu search based fuzzy system. Here, we use tabu search algorithm to effectively explore and exploit the large state space(More)
One of the important problems in knowledge discovery from data is clustering. Clustering is the problem of partitioning a set of data using unsupervised techniques. An important characteristic of a clustering technique is the shape of the cluster it can find. Clustering methods which are capable to find simple cluster shapes are usually fast but inaccurate(More)
Real-time, fuzzy rule-based guidance systems for autonomous vehicles on limited-access highways are investigated. The goal of these systems is to plan trajectories that are safe, while satisfying the driver's requests based on stochastic information about the vehicle's state and the surrounding traffic. This paper presented a new method to implement an(More)
Clustering is the problem of partitioning a (large) set of data using unsupervised techniques.Today, there exist many clustering techniques. The most important characteristic of a clustering technique is the shape of the cluster it can find. In this paper, we propose a method that is capable to find arbitrary shaped clusters and uses simple geometric(More)
  • 1