IEE (Luxembourg)

In the past years, several automated repair strategies have been proposed to fix bugs in individual software programs without any human intervention. There has been, however, little work on how automated repair techniques can resolve failures that arise at the system-level and are caused by undesired interactions among different system components or functions. Feature interaction failures are common in complex systems such as autonomous cars that are typically built as a composition of independent features (i.e., units of functionality). In this paper, we propose a repair technique to automatically resolve undesired feature interaction failures in automated driving systems (ADS) that lead to the violation of system safety requirements. Our repair strategy achieves its goal by (1) localizing faults spanning several lines of code, (2) simultaneously resolving multiple interaction failures caused by independent faults, (3) scaling repair strategies from the unit-level to the system-level, and (4) resolving failures based on their order of severity. We have evaluated our approach using two industrial ADS containing four features. Our results show that our repair strategy resolves the undesired interaction failures in these two systems in less than 16h and outperforms existing automated repair techniques.

The observation of the passenger compartment using an interior RADAR becomes challenging when a vehicle is in motion. The signal received by the RADAR sensor measures not only the target's motion that we would like to detect, e.g., vital signs, but also a second, unwanted motion induced by exterior effects, e.g., displacement caused by the road, strong wind gusts, or car engine vibrations. Consequently, traditional techniques used to remove white Gaussian noise cannot be applied in this scenario. We propose a theoretical framework to investigate the denoising of a signal received by an interior RADAR using accelerometer measurements and a mechanical model to generate the cancellation signal stemming from the (unwanted) vibrational motion. We explain the denoising technique and show that the fundamental idea behind the cleaning process works well. Our observations are corroborated by a robust mathematical model and verified by simulations. Furthermore, the aforementioned denoising techniques enable us to formulate and solve an optimization problem to find an estimation for the passenger's mass in certain cases.

Multiferroic oxide thin films continue to receive intensive research interest due to their excellent combination of properties that are related to the ferroic orders. In this paper, BiFeO₃thin films are fabricated on (001) Si substrates at varying ad-atom energy to establish the role of microstructure and stress evolution on their elastic properties. Stress evolution in the films is accomplished through incorporation of argon ions during in-situ film growth. The dynamics of the propagation of surface acoustic waves on BiFeO₃ thin films of varying microstructure and stress is investigated using surface Brillouin scattering (SBS). The film substrate configuration is of a slow on fast configuration that supports Rayleigh surface acoustic waves (RSAW) and Sezawa waves. Hence the phonon velocity dispersion curves were determined from the frequency shifts of both sets of the waves in the discrete region at constant incident angle of 71 deg. Using the inverse problem the elastic constant for isotropic film systems have been determined with the results showing that Ar⁺ incorporation decreases the bulk moduli and increases the shear moduli by 50%.

Optical damage limits the application range of congruent LiNbO3. This problem is commonly overcome by adding optical-damage-resistant cations. Here, the influence of doping with optical-damage-resistant Mg and Zn on the ionic and piezoelectric contributions to the dielectric permittivity is investigated in a broad frequency range (1 mHz–2 THz). It is shown that the two dopants have radically different influences on the variation of ionic permittivity with doping, in spite of their similarities with respect to the crystallographic structure. Raman spectroscopy reveals that the difference in permittivity can be traced to the effect of Mg and Zn doping on the susceptibility of the phonon modes. Both observations point to differences in the defect incorporation mechanisms.

This paper presents a real-time approach to address the motion artefact related to the Time-of-Flight (ToF) camera's working principle. ToF cameras based on demodulation lock-in pixels estimate depth from the phase-shift between emitted and received modulated near-infrared (NIR) signals, in which four sequential phase-shifted images are required, i.e., four-taps technique. The ToF working principle assumes the scene to be motionless during this time interval. However and in practise, unreliable depth measurements arise along object boundaries in dynamic scenes, mainly when fast movements are involved. Herein, we propose a robust method to identify those pixels in the resulting depth map that are prominent to be unreliable. Then, we replace their values by the closest reliable ones using the guided filter (GF) and an accurate guidance image, generated from the previously acquired sequential phase-shifted images. The GF has been selected as it presents a better behaviour near edges than alternative edge preserving filters with a major advantage of being a fast and non-approximate linear time algorithm. The experimental evaluation shows that the proposed method satisfactory addresses the motion artefact, even in extreme conditions.

International audience