Abstract
The changes in the communication paradigm envisioned for future networks, with peer-to-peer/symmetric attachments gaining momentum and two IP (Internet Protocol) versions coexisting, will pose new challenges to mobile communication networks. Traditional IP auto-configuration mechanisms will not work properly, since they were designed mostly having in mind a client-server/asymmetric attachment model, they assume a single IP version paradigm, and they target the auto-configuration of devices only. The IST Ambient Networks project has introduced a new concept - the Ambient Network - that enables handling every communication entity, either a single device or an entire network, as an Ambient Network (AN). This paper describes a new efficient mechanism, named Basic Connectivity (BC) mechanism, for auto-configuring IP connectivity between attaching ANs. A proof-of-concept prototype, experimental results, and theoretical analysis show that BC suites the future networking paradigm and represents a solution more efficient than the current trial-and-error mechanism for auto-configuring IP connectivity.

Abstract

Abstract
The growth of machine-generated relational databases, both in the sciences and in industry, is rapidly outpacing our ability to extract useful information from them by manual means. This has brought into focus machine learning techniques like Inductive Logic Programming (ILP) that are able to extract human-comprehensible models for complex relational data. The price to pay is that ILP techniques are not efficient: they can be seen as performing a form of discrete optimisation, which is known to be computationally hard; and the complexity is usually some super-linear function of the number of examples. While little can be done to alter the theoretical bounds on the worst-case complexity of ILP systems, some practical gains may follow from the use of multiple processors. In this paper we survey the state-of-the-art on parallel ILP. We implement several parallel algorithms and study their performance using some standard benchmarks. The principal findings of interest are these: (1) of the techniques investigated, one that simply constructs models in parallel on each processor using a subset of data and then combines the models into a single one, yields the best results; and (2) sequential (approximate) ILP algorithms based on randomized searches have lower execution times than (exact) parallel algorithms, without sacrificing the quality of the solutions found.

Abstract
In beyond 3G networks the user will not be aware of the access network technology used to provide a telecommunications service. Heterogeneous network technologies will be seamlessly integrated in one "common" access network, enabling users to move around and continuously receive their subscribed services. In a commercial environment, this network evolution requires that a telecommunications operator jointly manages its networks resources to improve the service offered to the users and, at the same time, to increase its revenue. Starting from the UMTS and WLAN interconnection architecture defined by 3GPP, this paper analyzes the performance of a new joint radio resource management strategy, comparing it with two well-known strategies used in scenarios where both networks, the UMTS and the WLAN, are interconnected. The new strategy presented in the paper bases its decisions on criteria related to user mobility characteristics and the application characteristics. The strategy also introduces the possibility of renegotiating new calls and reallocating running calls from one access network to another. The performance analysis considers two traffic scenarios. One where only real-time applications are running and other which also introduces TCP applications. The comparison studies show the proposed strategy outperforms the other strategies in what concerns call blocking probability and applications QoS support. Besides, the proposed strategy tends to reduce the handoffs between networks.

Abstract
Complete optical characterization of biological tissue is desirable to develop clinical methods using optical technologies. Particularly, to develop optical clearing methods in biological tissues, it is necessary to know the composition of the tissue, the percentage of each constituent and corresponding refractive indexes. To obtain such information for rat muscle, we used a simple method to characterize tissue constituents for both content percentage and refractive index. The study consisted on measuring mass with a precision weighting scale and the refractive index with an Abbe refractometer during tissue dehydration. With the collected data, we used a theoretical model to calculate the refractive index and percentage for both interstitial fluid and solid part of the rat muscle. The results obtained are in good agreement with data published by other authors, and were considered of vital information for the optical clearing studies that we planned to perform.

Abstract
When calculating correlation networks from multi-electrode array (MEA) data, one works with extensive computations. Unfortunately, as the MEAs grow bigger, the time needed for the computation grows even more: calculating pair-wise correlations for current 60 channel systems can take hours on normal commodity computers whereas for future 1000 channel systems it would take almost 280 times as long, given that the number of pairs increases with the square of the number of channels. Even taking into account the increase of speed in processors, soon it can be unfeasible to compute correlations in a single computer. Parallel computing is a way to sustain reasonable calculation times in the future. We provide a general tool for rapid computation of correlation networks which was tested for: (a) a single computer cluster with 16 cores, (b) the Newcastle Condor System utilizing idle processors of university computers and (c) the inter-cluster, with 192 cores. Our reusable tool provides a simple interface for neuroscientists, automating data partition and job submission, and also allowing coding in any programming language. It is also sufficiently flexible to be used in other high-performance computing environments.