Basic Pattern Matching Calculi: a Fresh View on Matching Failure

Abstract. We propose pattern matching calculi as a refinement of λ-calculus that integrates mechanisms appropriate for fine-grained mod-elling of non-strict pattern matching. Compared with the functional rewriting strategy usually employed to define the operational semantics of pattern matching in non-strict functional programming languages like Haskell or Clean, our pattern matching calculi achieve the same effects using simpler and more local rules. The main device is to embed into expressions the separate syntactic cate-gory of matchings; the resulting language naturally encompasses pattern guards and Boolean guards as special cases. By allowing a confluent reduction system and a normalising strategy, these pattern matching calculi provide a new basis for operational semantics of non-strict programming languages and also for implemen-tations.

On the Prediction of Solar Activity Using Different Neural Network Models

Accurate prediction of ionospheric parameters is crucial for telecommunication companies. These parameters strongly rely on solar activity. In this paper, we analyze the use of neural networks for sunspots time series prediction. Three types of models are tested and experimental results are reported for a particular sunspots time series: the IR5 index

Exploiting semantic clustering in the edonkey p2p network

Peer-to-peer file sharing now represents a significant portion of the Internet traffic and has generated a lot of interest from the research community. Some recent measurements studies of peer-to-peer workloads have demonstrated the presence of semantic proximity between peers. One way to improve performance of peer-to-peer file sharing systems is to exploit this locality of interest in order to connect semantically related peers so as to improve the search both in flooding- and server-based systems. Creating these additional connections raises interesting challenges and in particular (i) how to capture the semantic relationship between peers (ii) how to exploit these relationships and (iii) how to evaluate these improvements. In this paper, we evaluate several strategies to exploit the semantic proximity between peers against a real trace collected in November 2003 in the eDonkey 2000 peer-to-peer network. We present the results of this evaluation which confirm the presence of clustering in such networks and the interest to exploit it. 1 Introduction an

Optimisation of an asymmetric three phase-shift distributed feedback semiconductor laser

This paper shows that accurately optimised asymmetric three phase-shift (3PS)-distributed feedback (DFB) laser structures can strongly improve the stability of the single-longitudinal mode (SLM) operation, described by the mode selectivity and the flatness of the photon density profile, through an extended range of current injection, when compared to optimised symmetric 3PS-DFB structures reported elsewhere. This study reveals its importance in modern high bit-rate optical communication systems, by enhancing the possibility of attaining high performance DFB lasers, in easily fabricated structures. The procedure, based on matrix techniques, aims at the description of the optimal design of the laser structure and it is described step-by-step. Above-threshold calculations have been accomplished to evaluate the performance of the optimised asymmetric 3PS-DFB structure, namely: the mode selectivity ($G$), the flatness, the lasing wavelength, the optical power, and the side-mode suppression ratio (SMSR) evolutions with the current injection. For a current injection five times bigger than the threshold current, substantially improvements in $G$ (five times bigger) and in the SMSR (about 9 dB higher) are achieved when compared to similar, but symmetric, DFB structures

On the prediction of solar activity using different neural network models

Accurate prediction of ionospheric parameters is crucial for telecommunication companies. These parameters rely strongly on solar activity. In this paper, we analyze the use of neural networks for sunspot time series prediction. Three types of models are tested and experimental results are reported for a particular sunspot time series: the <i>IR</i>5 index

Peer-to-peer computing (Introduction to Topic 7)

Distributed systems have experienced a shift of scale in the past few years. This evolution has generated an interest in peer-to-peer systems and resulted in much interesting work. Peer-to-peer systems are characterized by their potential to scale due to their fully decentralized nature. They are self-organizing, adapting automatically to peer arrivals and departures, and are highly resilient to failures. They rely on a symmetric communication model where peers act both as servers and clients. As the peer-to-peer concepts and technologies become more mature, many distributed services and applications relying on this model are envisaged in the context of large-scale distributed and parallel systems. This topic examines peer-to-peer technologies, applications, and systems, and also identifies key research issues and challenges. Twenty-six papers were submitted to the track and we accepted six. We organized two sessions, the first devoted to the problem of query management in structured and unstructured overlay networks, the second containing a broader selection of topics