Abstract
OVER A DECADE ago, Jeff Offutt noted, The field of mutation analysis has been growing, both in the number of published papers and the number of active researchers.(33) This trend has since continued, as confirmed by a survey of recent literature.(36) Mutation analysis is the use of well-defined rules defined on syntactic descriptions to make systematic changes to the syntax or to objects developed from the syntax.(33) It has been successfully used in research for assessing test efficacy and as a building block for testing and debugging approaches. It systematically generates syntactic variations, called mutants, of an original program based on a set of mutation operators, which are well-defined program transformation rules. The most common use case of mutation analysis is to assess test efficacy. In this use case, mutants represent faulty versions of the original program, and the ratio of detected mutants quantifies a test suite's efficacy. Empirical evidence supports the use of systematically

Abstract

Abstract
With the advent of self-driving cars, and big companies such as Waymo or Bosch pushing forward into fully driverless transportation services, the in-vehicle behaviour of passengers must be monitored to ensure safety and comfort. The use of audio-visual information is attractive by its spatio-temporal richness as well as non-invasive nature, but faces tile likely constraints posed by available hardware and energy consumption. Hence new strategies are required to improve the usage of these scarce resources. We propose the processing of audio and visual data in a cascade pipeline for in-vehicle action recognition. The data is processed by modality-specific sub-modules. with subsequent ones being used when a confident classification is not reached. Experiments show an interesting accuracy-acceleration trade-off when compared with a parallel pipeline with late fusion, presenting potential for industrial applications on embedded devices.

Abstract

Abstract
Increasingly social networks are used both in the personal and professional levels, being companies and employees also exposed to the risks posed by them. In this sense, it is relevant to analyze employees' perception of the risks and vulnerabilities posed by the use of social networks in corporate environments. For this purpose, a questionnaire was developed and distributed to 372 employees of small and medium-sized companies that allowed the characterization and analysis of those risks. The results indicate that the security risks are perceived moderately by employees, emphasizing the risk of defamation and cyberbullying as being the most pertinent. On the other hand, the findings indicate that older employees, the existence of lower academic qualifications, and those working in medium-sized companies are more aware of these risks.

Abstract
Motion control is an important task in several areas, such as robotics where the angular position and speed should be acquired, usually with encoders. For slow angular speeds, an error is introduced spoiling the measurement. In this paper there will be proposed two new methodologies, that when combined allow to increase the precision whereas reducing the error, even on transient velocities. The two methodologies Variable Acquisition Window and a Quadrature Phase Compensation are addressed and combined simultaneously. A real implementation of the proposed algorithms is performed on a real hardware, with a DC motor and a low resolution encoder based on hall effect. The results validate the proposed approach since the errors are reduced compared with the standard Quadrature Encoder Reading.