The design of a collision avoidance system for use by Pilots operating on the airport ramp and in taxiway areas

Ground collisions have serious implications from both a safety and a commercial perspective. This paper reports on human computer interaction (HCI) research related to the advancement of a collision avoidance system, for use by Pilots operating on the airport ramp and in taxiway areas. Primarily, this paper focuses on the key findings of this research and the emerging HCI design solution.     

Blind spatial unmixing of multispectral images: New methods combining sparse component analysis,clustering and non-negativity constraints

Remote sensing has become an unavoidable tool for better managing our environment, generally by realizing maps of land cover using classification techniques. Traditional classification techniques assign only one class (e.g., water, soil, grass) to each pixel of remote sensing images. However, the area covered by one pixel contains more than one surface component and results in the mixture of these surface components. In such situations, classical classification is not acceptable for many major applications, such as environmental monitoring, agriculture, mineral exploration and mining, etc. Most methods proposed for treating this problem have been developed for hyperspectral images. On the contrary, there are very few automatic techniques suited to multispectral images. In this paper, we propose new unsupervised spatial methods (called 2D-Corr-NLS and 2D-Corr-NMF) in order to unmix each pixel of a multispectral image for better recognizing the surface components constituting the observed scene. These methods are related to the blind source separation (BSS) problem, and are based on sparse component analysis (SCA), clustering and non-negativity constraints. Our approach consists in first identifying the mixing matrix involved in this BSS problem, by using the first stage of a spatial correlation-based SCA method with very limited source sparsity constraints, combined with clustering. Non-negative least squares (NLS) or non-negative matrix factorization (NMF) methods are then used to extract spatial sources. An important advantage of our proposed methods is their applicability to the possibly globally underdetermined, but locally (over)determined BSS model in multispectral remote sensing images. Experiments based on realistic synthetic mixtures and real multispectral images collected by the Landsat ETM+ and the Formosat-2 sensors are performed to evaluate the performance of the proposed approach. We also show that our methods significantly outperform the sequential maximum angle convex cone (SMACC) method.     

Artificial intelligence implementation in the APS process diagnostic

Thermal spray process is a technique of coating manufacturing implementing a wide variety of materials and processes. This technique is characterized by up to 150 processing parameters influencing the coating properties. The control of the coating quality is needed through the consideration of a robust methodology that takes into account the parameter interdependencies, the process variability and offers the ability to quantify the processing parameter-process response relationships. The aim of this work is to introduce a new approach based on artificial intelligence responding to these requirements. A detailed procedure is presented considering an artificial neural network (ANN) structure which encodes implicitly the physical phenomena governing the process. The implementation of such a structure was coupled to experimental results of an optic sensor controlling the powder particle fusion state before the coating formation. The optimization steps were discussed and the predicted results were compared to the experimental ones allowing the identification of the control factors.     

Constrained model predictive control for time-varying delay systems: Application to an active car suspension

This study investigates the problem of robust model predictive control (RMPC) for active suspension systems with time-varying delays and input constraints. The uncertainty is of convex polytopic type. Based on the Lyapunov-Krasovskii functional method, sufficient stability conditions of the time-varying delays systems are derived by linear matrix inequalities (LMIs) terms. At each time set, a feasible state feedback is obtained by minimizing an upper bound of the ‘worst-case’ quadratic objective function over an infinite horizon subject to constraints on inputs. Finally, a quarter-vehicle model is exploited to demonstrate the effectiveness of the proposed method.     

A linear 60 GHz 65 nm-CMOS power amplifier realization and characterization for OFDM signal

A millimeter-wave Power Amplifier (PA) based on a 65nm CMOS technology from STMicroelectronics has been designed. The targeted feature is the unlicensed band around 60 GHz suitable for wireless personal area network application (WPAN). To optimize the linearity, the PA is designed under class A biasing to have an output compression point (OCP₁) close to its saturated Power (P _sat). S-parameters and large signal measurement results are demonstrated and compared with electromagnetic simulations. The PA offers a P _sat of 8.3 dBm, an OCP₁ of 6 dBm and a gain of 6.7 dB. The die area is 0.29 mm² with pads. Considering those results, one-tone simulations are not sufficient to characterize the linearity performances of the PA in its real conditions of use. Consequently, two-tone simulations are firstly performed. After, linearity figures of merit (FoM) are discussed applying an orthogonal frequency-division multiplexing (OFDM) modulated signal. The PA offers an adjacent channel power ratio (ACPR) of 15 dB and an error vector magnitude (EVM) of 20% at PA compression operating mode.     

Low speed lifting cable diagnosis using instantaneous angular speed

Journal of Mechanical Science and Technology - This paper describes an experimental study of lifting cable fault diagnostic based on instantaneous angular speed (IAS) technique. During the study...     

A two-step cloning-free PCR-based method for the deletion of genes in the opportunistic pathogenic yeast Candida lusitaniae

We describe a new cloning-free strategy to delete genes in the opportunistic pathogenic yeast Candida lusitaniae. We first constructed two ura3 Δ strains in C. lusitaniae for their use in transformation experiments. One was deleted for the entire URA3 coding sequence; the other possessed a partial deletion within the coding region, which was used to determine the minimum amount of homology required for efficient homologous recombination by double crossing-over of a linear DNA fragment restoring URA3 expression. This amount was estimated to 200 bp on each side of the DNA fragment. These data constituted the basis of the development of a strategy to construct DNA cassettes for gene deletion by a cloning-free overlapping PCR method. Two cassettes were necessary in two successive transformation steps for the complete removal of a gene of interest. As an example, we report here the deletion of the LEU2 gene. The first cassette was constituted by the URA3 gene flanked by two large fragments (500 bp) homologous to the 5' and 3' non-coding regions of LEU2. After transformation of an ura3 Δ recipient strain and integration of the cassette at the LEU2 locus, the URA3 gene was removed by a second transformation round with a DNA cassette made by the fusion between the 5' and 3' non-coding regions of the LEU2 gene. The overall procedure takes less than 2 weeks and allows the creation of a clean null mutant that retains no foreign DNA sequence integrated in its genome.     

Explaining the Difference Between Real Part and Virtual Design of 3D Printed Porous Polymer at the Microstructural Level

The combination of experimental and numerical approaches is attempted to shed more light on 3D microstructural imperfections and mechanical performance of 3D printed acrylonitrile butadiene styrene parts. The starting point is the virtual building of airy structures using a reverse engineering approach. This approach combines microstructure generator, finite element model, and optimization strategy to propose virtual airy structures satisfying structural and mechanical criteria up to a desired porosity content of 60%. Optimal structures are printed using fused deposition modeling and X‐ray microtomography is used to assess all microstructural defects. Compression testing is performed for load levels above 50% of reduction in sample height. The main outcome of this work is the demonstration of small amount of process induced porosity inducing high pore connectivity. The interdependence of process induced and desired porosity reveals genuine microstructural effects that are only characteristics of 3D printed materials.

     

Image-based truss recognition for density-based topology optimization approach

Structural and Multidisciplinary Optimization - Topology optimization is a tool that supports the creativity of structural-designers and is used in various industries, from automotive to...     

HVOF sprayed WC–Co coatings: Microstructure,mechanical properties and friction moment prediction

This study aims at gaining a better understanding of the microstructural features that control the mechanical and the tribological performances of WC–12 wt.% Co coatings under High Velocity Oxygen Fuel (HVOF) spraying conditions. This paper looks at the influences of the HVOF process parameters for WC–12Co material on the microstructural and the tribological behaviours of the coatings. The correlation between the coating microstructure and the wear behaviour is investigated by observing and analysing the microstructure and by studying the friction moment using enhanced statistical tool based on neural computations. According to the experimental and the numerical results, it has been shown that the spray parameters affect the phase composition, hardness and porosity of HVOF sprayed WC–12Co coatings and the correlations with HVOF process parameters are fully predictable in the steady-state regime.