With the growing number of clean-slate redesigns of the Internet, the need for a medium that enables all stakeholders to participate in the realization, evaluation, and selection of these designs is increasing. We believe that the missing catalyst is a meta network architecture that welcomes most, if not all, clean-state designs on a level playing field, lowers deployment barriers, and leaves the final evaluation to the broader community. This thesis presents the eXpressive Internet (Meta) Architecture (XIA), itself a clean-slate design, as well as Linux XIA, a native implementation of XIA in the Linux kernel, as a candidate. As a meta network architecture, XIA is highly flexible, leaving stakeholders to choose an expressive set of network principals to instantiate a given network architecture within the XIA framework. Central to XIA is its novel, non-linear network addressing format, from which derive key architectural features such as evolvability, intrinsically secure identifiers, and a low degree of principal isolation. XIP, the network layer protocol of XIA, forwards packets by navigating these structured addresses and delegating the decision-making and packet processing to appropriate principals, accordingly. Taken together, these mechanisms work in tandem to support a broad spectrum of interoperable principals. We demonstrate how to port four distinct and unrelated network architectures onto Linux XIA, none of which were designed for interoperability with this platform. We then show that, notwithstanding this flexibility, Linux XIA's forwarding performance remains comparable to that of the more mature legacy TCP/IP stack implementation. Moreover, the ported architectures, namely IP, Serval, NDN, and ANTS, empower us to present a deployment plan for XIA, to explore design variations of the ported architectures that were impossible in their original form due to the requirement of self-sufficiency that a standalone network architecture bears, and to substantiate the claim that XIA readily supports and enables network evolution. Our work highlights the benefits of specializing network designs that XIA affords, and comprises instructive examples for the network researcher interested in design and implementation for future interoperability.

The aim of this work was to develop the method for classification of ECG beats into two classes, namely ischemic and non-ischemic beats. Heart beats (P-QRS-T cycles) selected from animals orthogonal ECGs were preprocessed and used as the input signals. Spectral features vectors (values of cross spectral coherency), principal component and HRV parameters were derived from the beats. The beats were classified using feedforward multilayer neural network designed in Matlab. Classification performance reached the value approx. from 87,2 to 100%. Presented results can be suitable in future studies aimed at automatic classification of ECG.