Abstract

Abstract

Abstract
This paper presents a comparative analysis of Free/Libre Open Source Software (FLOSS) Learning Management System (LMS). Following a selection process we analyze the functionalities and characteristics of 8 tools commonly used in formal and informal education. More specifically we focus on the availability of different tools concerning communication and assistance, such as, forum, email, calendar, portfolios, etc. Our analysis showed that despite their similarities, the appropriateness of different FLOSS LMSs can be greatly affected by the specific needs of students, instructors and institutions. © Springer-Verlag Berlin Heidelberg 2014.

Abstract
We present a compiler for CAO, an imperative DSL for the cryptographic domain. The tool takes high-level cryptographic algorithm specifications and translates them into C implementations through a series of security-aware transformations and optimizations. The compiler back-end is highly configurable, allowing the targeting of very disparate platforms in terms of memory requirements and computing power. © 2014 Springer-Verlag.

Abstract
In this paper we describe an approach to classifying heart sounds (classes Normal, Murmur and Extra-systole) that is based on the discretization of sound signals using the SAX (Symbolic Aggregate Approximation) representation. The ability of automatically classifying heart sounds or at least support human decision in this task is socially relevant to spread the reach of medical care using simple mobile devices or digital stethoscopes. In our approach, sounds are first pre-processed using signal processing techniques (decimate, low-pass filter, normalize, Shannon envelope). Then the pre-processed symbols are transformed into sequences of discrete SAX symbols. These sequences are subject to a process of motif discovery. Frequent sequences of symbols (motifs) are adopted as features. Each sound is then characterized by the frequent motifs that occur in it and their respective frequency. This is similar to the term frequency (TF) model used in text mining. In this paper we compare the TF model with the application of the TFIDF (Term frequency - Inverse Document Frequency) and the use of bi-grams (frequent size two sequences of motifs). Results show the ability of the motifs based TF approach to separate classes and the relative value of the TFIDF and the bi-grams variants. The separation of the Extra-systole class is overly difficult and much better results are obtained for separating the Murmur class. Empirical validation is conducted using real data collected in noisy environments. We have also assessed the cost-reduction potential of the proposed methods by considering a fixed cost model and using a cost sensitive meta algorithm.

Abstract
Bidirectional transformations have potential applications in a vast number of computer science domains. Spreadsheets, on the other hand, are widely used for developing business applications, but their formulas are unidirectional, in the sense that their result can not be edited and propagated back to their input cells. In this paper, we interpret such formulas as a well-known class of bidirectional transformations that go by the name of lenses. Being aimed at users that are not proficient with programming languages, we devote particular attention to the seamless embedding of the proposed bidirectional mechanism with the typical workflow of spreadsheet environments, allowing users to have a fine control and understanding of the behavior of the derived backward transformations.