Abstract

Abstract
Large scale information systems, such as public information systems for light-train/metro networks, must be able to fulfill contractualized Service Level Agreements (SLAs) in terms of end-to-end latencies and jitter, even in the presence of faults. Failure to do so has potential legal and financial implications for the software developers. Current middleware solutions have a hard time coping with these demands due, fundamentally, to a lack of adequate, simultaneous, support for fault-tolerance (FT) and real-time (RT) tasks. In this paper we present Stheno, a general purpose peer-to-peer (P2P) middleware system that builds on previous work from TAO and MEAD to provide: (a) configurable, transparent, FT support by taking advantage of the P2P layer topology awareness to efficiently implement Common Of The Shelf (COTS) replication algorithms and replica management strategies, and; (b) kernel-level resource reservation integrated with well-known threading strategies based on priorities to provide more robust support for soft real-time tasks. An evaluation of the first (unoptimized) prototype for the middleware shows that Stheno is able to match and often greatly exceed the SLA agreements provided by our target system, the light-train/metro information system developed and maintained by EFACEC, and currently deployed at multiple cities in Europe and Brazil. Copyright 2012 ACM.

Abstract
Nowadays, a large number of people consume music from the web. Web sites and online services now typically contain millions of music tracks, which complicates search, retrieval, and discovery of music. Music recommender systems can address these issues by recommending relevant and novel music to a user based on personal musical tastes. In this paper, we propose a hybrid music recommender system, which combines usage and content data. We describe an online evaluation experiment performed in real-time on a commercial web site, specialized in content from the very Long Tail of music content. We compare it against two stand-alone recommender systems, the first system based on usage and the second one based on content data (namely, audio and textual tags). The results show that the proposed hybrid recommender shows advantages with respect to usage-based and content-based systems, namely, higher user absolute acceptance rate, higher user activity rate and higher user loyalty. © 2012, Springer-Verlag London.

Abstract
A repository of learning objects is a system that stores electronic resources in a technology-mediated learning process. The need for this kind of repository is growing as more educators become eager to use digital educational contents and more of it becomes available. The sharing and use of these resources relies on the use of content and communication standards as a means to describe and exchange educational resources, commonly known as learning objects. This paper presents the design and implementation of a service-oriented repository of learning objects called crimsonHex. This repository supports new definitions of learning objects for specialized domains and we illustrate this feature with the definition of programming exercises as learning objects and its validation by the repository. The repository is also fully compliant with existing communication standards and we propose extensions by adding new functions, formalizing message interchange and providing a REST interface. To validate the interoperability features of the repository, we developed a repository plug-in for Moodle that is expected to be included in the next release of this popular learning management system. Copyright (c) 2012 John Wiley & Sons, Ltd.

Abstract
Several standards have appeared in recent years to formalize the metadata of learning objects, but they are still insufficient to fully describe a specialized domain. In particular, the programming exercise domain requires interdependent resources (e. g. test cases, solution programs, exercise description) usually processed by different services in the programming exercise lifecycle. Moreover, the manual creation of these resources is time-consuming and error-prone, leading to an obstacle to the fast development of programming exercises of good quality. This chapter focuses on the definition of an XML dialect called PExIL (Programming Exercises Interoperability Language). The aim of PExIL is to consolidate all the data required in the programming exercise lifecycle from when it is created to when it is graded, covering also the resolution, the evaluation, and the feedback. The authors introduce the XML Schema used to formalize the relevant data of the programming exercise lifecycle. The validation of this approach is made through the evaluation of the usefulness and expressiveness of the PExIL definition. In the former, the authors present the tools that consume the PExIL definition to automatically generate the specialized resources. In the latter, they use the PExIL definition to capture all the constraints of a set of programming exercises stored in a learning objects repository. Copyright (C) 2013, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

Abstract
The central idea of the Web of Data is to interlink the information available in the Web, most of which is actually stored in databases rather than in static HTML pages. Tools to convert relational data into semantic web formats and publish then as linked data are essential to fulfill the vision of a web of data available for automatic processing, as web content is currently available to humans. This paper presents DaPress, a simple tool to publish linked data on the Web, that maps a relational database to an RDF triplestore and creates a SPARQL access point. The paper reports the use of DaPress to publish the database of Authenticus, a system that automatically assigns publication authors to known Portuguese researchers and institutions. © Teresa Costa and José Paulo Leal.