The predictability of network traffic is a significant interest in many domains such as congestion control, admission control, and network management. An accurate traffic prediction model should have the ability to capture prominent traffic characteristics, such as long-range dependence (LRD) and self-similarity in the large time scale, multifractal in small time scale. In this paper we propose...

Introduction: One of the most common and recent highlighted psychological problems is anxiety. This study investigated the moderating role of defense mechanisms in the relationship between confrontation with existential issues (death, freedom, isolation, and meaninglessness) and anxiety. Methods: A total of 389 students (218 men and 171 women) of Ferdowsi University of Mashhad City, Iran, stud...

Precise destination prediction of taxi trajectories can benefit many intelligent location based services such as accurate ad for passengers. Traditional prediction approaches, which treat trajectories as one-dimensional sequences and process them in single scale, fail to capture the diverse two-dimensional patterns of trajectories in different spatial scales. In this paper, we propose TCONV whi...

The state prediction of resources in large scale distributed systems represents an important aspect for resources allocations, systems evaluation, and autonomic control. The paper presents advanced techniques for resources state prediction in Large Scale Distributed Systems, which include techniques based on bio-inspired algorithms like neural network improved with genetic algorithms. The appro...

Prediction markets have proven successful in large-scale applications such as elections and sporting events. Consequently, several large corporations have adopted prediction markets for smaller-scale internal applications where information may be complex and the number of traders small. Using laboratory experiments we test the performance of the standard prediction market in complex environment...