Friends don't lie: inferring personality traits from social network structure

In this work, we investigate the relationships between social network structure and personality; we assess the performances of different subsets of structural network features, and in particular those concerned with ego-networks, in predicting the Big-5 personality traits. In addition to traditional survey-based data, this work focuses on social networks derived from real-life data gathered through smartphones. Besides showing that the latter are superior to the former for the task at hand, our results provide a fine-grained analysis of the contribution the various feature sets are able to provide to personality classification, along with an assessment of the relative merits of the various networks exploited.European Commission (PERSI Project within the Marie Curie COFUND-FP7)Italy. Ministero dell'istruzione, dell'università e della ricerca (FIRB S-PATTERNS project

Quantifying the impact of OSS adoption risks with the help of i* Models

Adopting Open Source Software (OSS) components in organisational settings requires evaluating the possible impact of adoption decisions on business goals. Measures available in OSS, capturing indicators such as the quality of open source code and the activeness of the developing community, can be used as a driver to assess various risks in component adoption. In this paper we illustrate how risk and impact models are used to relate measures obtained from the component under analysis to business goals in i* -based OSS business strategy models.Postprint (author’s final draft

Symbolic search-based testing

We present an algorithm for constructing fitness functions that improve the efficiency of search-based testing when trying to generate branch adequate test data. The algorithm combines symbolic information with dynamic analysis and has two key advantages: It does not require any change in the underlying test data generation technique and it avoids many problems traditionally associated with symbolic execution, in particular the presence of loops. We have evaluated the algorithm on industrial closed source and open source systems using both local and global search-based testing techniques, demonstrating that both are statistically significantly more efficient using our approach. The test for significance was done using a one-sided, paired Wilcoxon signed rank test. On average, the local search requires 23.41% and the global search 7.78% fewer fitness evaluations when using a symbolic execution based fitness function generated by the algorithm

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In this article, we describe and interpret a set of acoustic and linguistic features that characterise emotional/emotion-related user states – confined to the one database processed: four classes in a German corpus of children interacting with a pet robot. To this end, we collected a very large feature vector consisting of more than 4000 features extracted at different sites. We performed extensive feature selection (Sequential Forward Floating Search) for seven acoustic and four linguistic types of features, ending up in a small number of ‘most important ’ features which we try to interpret by discussing the impact of different feature and extraction types. We establish different measures of impact and discuss the mutual influence of acoustics and linguistics

A 180-nm CMOS Time-of-Flight 3-D Image Sensor

Abstract-We report on the design and the experimental characterization of a new 3-D image sensor, based on a new 120-nm CMOS-compatible photo-detector, which features an internal demodulation mechanism effective up to high frequencies. The distance range covered by our proof-of-concept device spans from 1-m to a few meter, and the resolution is about 1-cm