The empirical study: encouraging students’ interest in software development using test-driven development

The supply is not matching the demand on the market for software developers. While the enrolment in undergraduate computer science courses is increasing, few students are interested in and committed to becoming software developers. It could be that students are overwhelmed by the software development methodology that they are taught. We are consequently looking for a constructivist approach to software engineering able to effectively engage learners. We empirically evaluated whether test-driven development (TDD) is able to improve the quality of both learning and of software development in the classroom. Although numerous studies have outlined the benefits and effects of TDD in the classroom, none of those studies have focused on measuring students\u27 interest in and attitudes toward using TDD in the classroom. We present a study evaluating the impact of TDD on the engagement and focus of learners of software development in the classroom. The results illustrate that the use of TDD in the classroom encourages learners to engage and focus

Towards a Privacy Diagnosis Centre : Measuring k-anonymity

Most of the recent efforts addressing the issue of privacy have focused on devising algorithms for the anonymization and diversification of data

Mining Term Association Rules for Global Query Expansion: A Case Study with Topic 202 from TREC4

The sudden growth of the World Wide Web and its unprecedented popularity as a de facto global digital library exemplified both the strengths and weaknesses of the Information Retrieval techniques used by popular search engines. Most queries are short and incomplete attempts to describe or characterize the possible documents relevant to the query. It seems then natural to try and expand the queries with additional terms, which are semantically and/or statistically associated with the original query terms. In this paper we are looking at the mining of associations between terms for the exploration of the terminology of a corpus as well as for the automatic expansion of queries. The technique we use for the discovery of the associations is association rules mining [Agrawal 96]. The technique we propose is more flexible than previous techniques based on term co-occurrence since it takes into account not only the co-occurrence frequency but also the confidence and direction of the association rules. Our preliminary experiment results show we can get benefit from this novel technique

Finding Quantum Critical Points with Neural-Network Quantum States

Finding the precise location of quantum critical points is of particular importance to characterise quantum many-body systems at zero temperature. However, quantum many-body systems are notoriously hard to study because the dimension of their Hilbert space increases exponentially with their size. Recently, machine learning tools known as neural-network quantum states have been shown to effectively and efficiently simulate quantum many-body systems. We present an approach to finding the quantum critical points of the quantum Ising model using neural-network quantum states, analytically constructed innate restricted Boltzmann machines, transfer learning and unsupervised learning. We validate the approach and evaluate its efficiency and effectiveness in comparison with other traditional approaches.Comment: 19 pages, 12 figures, extended version of an accepted paper at the 24th European Conference on Artificial Intelligence (ECAI 2020

GALEX UV Color Relations for Nearby Early-Type Galaxies

We use GALEX/optical photometry to construct color-color relationships for early-type galaxies sorted by morphological type. We have matched objects in the GALEX GR1 public release and the first IR1.1 internal release, with the RC3 early-type galaxies having a morphological type -5.5<T<-1.5 with mean error in T<1.5, and mean error on (B-V)T<0.05. After visual inspection of each match, we are left with 130 galaxies with a reliable GALEX pipeline photometry in the far-UV and near-UV bands. This sample is divided into Ellipticals (-5.5<T<-3.5) and Lenticulars (-3.5<T<-1.5). After correction for the Galactic extinction, the color-color diagrams FUV-NUV vs. (B-V)_{Tc} are plotted for the two subsamples. We find a tight anti-correlation between the FUV-NUV and (B-V)_{Tc} colors for Ellipticals, the UV color getting bluer when the (B-V)_{Tc} get redder. This relationship very likely is an extension of the color-metallicity relationship into the GALEX NUV band. We suspect that the main source of the correlation is metal line blanketing in the NUV band. The FUV-NUV vs B-V correlation has larger scatter for lenticular galaxies; we speculate this reflects the presence of low level star formation. If the latter objects (i.e. those that are blue both in FUV-NUV and B-V) are interpreted as harboring recent star formation activity, this would be the case for a few percent (~4%) of Ellipticals and ~15% of Lenticulars; this would make about 10% of early-type galaxies with residual star formation in our full sample of 130 early-type galaxies. We also plot FUV-NUV vs. the Mg_2 index and central velocity dispersion. We find a tight anti-correlation between FUV-NUV and the Mg_2 index(...).Comment: 25 pages, 5 figures, accepted for publication in ApJS (abstract abridged), typos corrected in section 2.

Collins and Sivers asymmetries in muonproduction of pions and kaons off transversely polarised protons

Measurements of the Collins and Sivers asymmetries for charged pions and charged and neutral kaons produced in semi-inclusive deep-inelastic scattering of high energy muons off transversely polarised protons are presented. The results were obtained using all the available COMPASS proton data, which were taken in the years 2007 and 2010. The Collins asymmetries exhibit in the valence region a non-zero signal for pions and there are hints of non-zero signal also for kaons. The Sivers asymmetries are found to be positive for positive pions and kaons and compatible with zero otherwise. © 2015