Meaningful Learning for Deep Facial Emotional Features

Neural Processing Letters - Facial expression is an important aspect to recognize emotions between humans. However, this task remains difficult for machines. Several approaches have been developed...     

Flow and heat transfer of a Giesekus fluid in plane and 3D ducts

This study aims to investigate the Graetz problem of Newtonian and viscoelastic fluid obeying Giesekus model using ANSYS Polyflow solver. The non‐isothermal flow in straight ducts of circular and noncircular cross‐sections under the constant heat flux boundary conditions is considered. The effect of the mobility parameter (α), fluid elasticity defined by Weissenberg number (We) and Reynolds number (Re) on the flow field, secondary flows, and the fully developed and developing Nusselt number along the ducts length are investigated for all geometries. The obtained results are of great importance for practical application in the polymer industries such as polymer melt.     

Effect of Annealing on the Dark and Illuminated I(V ) Characterization of a ZnO:Ga|Cu2O Hetero-Junction Prepared by Ultrasonic Spray System

Semiconductors - This paper presents the Ultrasonic Spray Pyrolysis system fabrication of gallium-doped zinc oxide (ZnO:Ga)|cuprous oxide (Cu2O) thin film hetero-junction. The deposition parameters...     

Towards a verified compiler prototype for the synchronous language SIGNAL

SIGNAL belongs to the synchronous languages family which are widely used in the design of safety-critical real-time systems such as avionics, space systems, and nuclear power plants. This paper reports a compiler prototype for SIGNAL. Compared with the existing SIGNAL compiler, we propose a new intermediate representation (named S-CGA, a variant of clocked guarded actions), to integrate more synchronous programs into our compiler prototype in the future. The front-end of the compiler, i.e., the translation from SIGNAL to S-CGA, is presented. As well, the proof of semantics preservation is mechanized in the theorem prover Coq. Moreover, we present the back-end of the compiler, including sequential code generation and multithreaded code generation with time-predictable properties. With the rising importance of multi-core processors in safetycritical embedded systems or cyber-physical systems (CPS), there is a growing need for model-driven generation of multithreaded code and thus mapping on multi-core. We propose a time-predictable multi-core architecture model in architecture analysis and design language (AADL), and map the multi-threaded code to this model.     

Towards formalising AADL in Proof Assistants

This paper presents first steps towards a formalisation of the Architecture Analysis and Design Language, mainly concentrating on a representation of its data model. For this, we contrast two approaches: one set-based (using the B modelling framework) and one in a higher-order logic (using the Isabelle proof assistant). We illustrate a transformation on a simplified part of the AADL metamodel concerning flows.     

Reduction and Quantifier Elimination Techniques for Program Validation

We study the automatic verification of programs with infinite or parameterized state space. This paper presents methods allowing the transformation of some second-order formulas expressing Hoare triples into equivalent formulas expressed in a weaker but decidable logic. Two techniques are considered: quantifier elimination and reduction to a finite domain. We illustrate these techniques on the validation of memory coherency protocols expressed in Unity.     

Morphological and Mechanical Characterization of Extracellular Vesicles and Parent Human Synoviocytes under Physiological and Inflammatory Conditions

The morphology of fibroblast-like synoviocytes (FLS) issued from the synovial fluid (SF) of patients suffering from osteoarthritis (OA), rheumatoid arthritis (RA), or from healthy subjects (H), as well as the ultrastructure and mechanical properties of the FLS-secreted extracellular vesicles (EV), were analyzed by confocal microscopy, transmission electron microscopy, atomic force microscopy, and tribological tests. EV released under healthy conditions were constituted of several lipid bilayers surrounding a viscous inner core. This “gel-in” vesicular structure ensured high mechanical resistance of single vesicles and good tribological properties of the lubricant. RA, and to a lesser extent OA, synovial vesicles had altered morphology, corresponding to a “gel-out” situation with vesicles surrounded by a viscous gel, poor mechanical resistance, and poor lubricating qualities. When subjected to inflammatory conditions, healthy cells developed phenotypes similar to that of RA samples, which reinforces the importance of inflammatory processes in the loss of lubricating properties of SF.     

Design optimization of a solar tower power plant heliostat field by considering different heliostat shapes

The present study focuses on the optimization of solar tower power plant heliostat field by considering different heliostat shapes including rectangular, square, pentagon, hexagon, heptagon, octagon, and circular heliostat shapes. The optimization is carried out using an in-house developed code-based MATLAB program. The developed in-house code is validated first on a well-known PS10 Solar Thermal Power plant having rectangular heliostats shape and the resulting yearly unweighted heliostat field efficiency of about 64.43% could be obtained. The optimized PS10 heliostat field using different heliostat shapes showed that the circular and octagon heliostat shapes provide better efficiency with minimum land area. The yearly efficiency is increased from 69.65% for the rectangular heliostat shape to 70.96% and 71% for the octagon and circular shapes, respectively. In addition, the calculated field area (land area) is reduced for the case of circular and octagon heliostat shapes with a gain of about 11.10% and 10.93% (about 42.0436 × 10³ and 41.4036 × 10³ m²), respectively, in comparison with the PS10 field area.     

Using genetic algorithms to optimize the design parameters of generalized predictive controllers

Generalized predictive control algorithms are a powerful control design method widely applied to industrial processes. However, there is no easy way to tune the design parameters, mainly prediction and control horizons, in order to achieve optimal performance. In this work, a genetic algorithm is proposed whose aim is to find on line the optimal values for the tuning parameters.