Statistical-Learning-Theory
The goal of statistical learning theory is to study, in a statistical
FRAmework, the properties of learning algorithms. In particular,
most results take the form of so-called error bounds. This tutorial introduces
the techniques that are used to obtain such results.
THIS CHAPTER INTRODUCES and Java Server Pages (and then presents
a simple example to display how to use in creating and
provides excellent support for the Apache Struts FRAmework,
which I believe is the most popular Web FRAmework around. I will delve into how
you can easily create Struts-based and other files of relevance to Struts.
Some of the most useful enhancements to introduced in version 10g
are related to and Struts development.
Adaptive Coordinated Medium Access Control (AC-MAC), a contention-based Medium
Access Control protocol for wireless sensor networks. To handle the load variations in some real-time sensor applications, ACMAC
introduces the adaptive duty cycle scheme within the FRAmework of sensor-MAC (S-MAC).
The goal of this thesis is the development of traffic engineering rules for cellular packet
radio networks based on GPRS and EDGE. They are based on traffic models for typical
mobile applications. Load generators, representing these traffic models, are developed
and integrated into a simulation environment with the prototypical implementation of
the EGPRS protocols and models for the radio channel, which were also developed in
the FRAmework of this thesis. With this simulation tool a comprehensive performance
evaluation is carried out that leads to the traffic engineering rules.