The main aim of this research is to propose a new Two-Level Adaptive Branch Prediction scheme, based on additional correlation information. Conventional two-level adaptive branch prediction exploits the correlation between the outcome of a branch and the path followed through a program to reach the branch. Typically the program path is identified by recording whether each branch on the path is ...

Path forecasts, defined as sequences of individual forecasts, generated by vector autoregressions are widely used in applied work. It has been recognized that a profound econometric analysis often requires, besides the path forecast, a joint prediction region that contains the whole future path with a prespecified coverage probability. The forecasting literature offers several different methods...

In the recent times the study of signal propagation models are under continuous reviewand currently a lot of work is being done on prediction of path losses associated with different kinds of environments, but the exactness of each model deployed is valid only for a small frame of fixed parameters which are the fundamentals of it. An exact radio propagation model is important for coping up with...

The Motion Compression framework for extended range telepresence applications consists of three functional modules: path prediction, path transformation, and user guidance. This paper presents a new path prediction module for known environments that exploits the property, that humans typically walk on straight paths toward discrete goal objects. In order to estimate the user’s goal object out o...

Adaptive routing algorithms are of great importance in the maintenance of packet-switched communication networks. A sufficiently flexible algorithm can yield increased quality of service (QoS), such as reduced packet loss ratio or delay, even in case of link failures or substantially changed traffic scenarios. These algorithms require constant monitoring of network state, and the measured infor...

In mobile radio systems, path loss models are necessary for proper planning, interference estimations, frequencies assignments and cell parameters which are basic for network planning process. Empirical models are the most adjustable models that can be suited to different types of environments. In this paper, data collected in Batna, Algeria is used to calculate the path loss for GSM (908-957 M...

Path prediction is useful in a wide range of applications. Most of the existing solutions, however, are based on eager learning methods where models and patterns are extracted from historical trajectories and then used for future prediction. Since such approaches are committed to a set of statistically significant models or patterns, problems can arise in dynamic environments where the underlyi...