Solid‐state lasers for projection

Abstract— The unique advantage of projection displays is the ability to produce large images from small devices. The use of lasers as the projection light source will mean a further step in terms of compactness as well as efficiency for projection systems. However, the advent of laser projection is currently still limited by the availability of low‐cost green lasers. Blue‐diode‐pumped solid‐state lasers are one promising way to realize green as well as red lasers that are specifically suited for projection applications. An efficient solid‐state laser that is based on Pr³⁺:YLF as the laser material, pumped by a blue‐laser diode and emitting at 523 nm, is presented here. The laser reaches power‐conversion efficiencies of more than 7% and output powers of up to 378 mW at green wavelengths. By making only minor modifications to the laser resonator, a red laser emitting at 640 nm can be realized within the same setup. An output power of 166 mW at a power‐conversion efficiency of 6.9% is demonstrated in the red. By combining a red‐ and a green‐emitting blue‐diode‐pumped solid‐state laser with another blue diode, an integrated RGB projection light source can be realized that is based on a single‐diode technology.     

Estimating the non-linear dynamics of free-flying objects

This paper develops a model-free method to estimate the dynamics of free-flying objects. We take a realistic perspective to the problem and investigate tracking accurately and very rapidly the trajectory and orientation of an object so as to catch it in flight. We consider the dynamics of complex objects where the grasping point is not located at the center of mass.To achieve this, a density estimate of the translational and rotational velocity is built based on the trajectories of various examples. We contrast the performance of six non-linear regression methods (Support Vector Regression (SVR) with Radial Basis Function (RBF) kernel, SVR with polynomial kernel, Gaussian Mixture Regression (GMR), Echo State Network (ESN), Genetic Programming (GP) and Locally Weighted Projection Regression (LWPR)) in terms of precision of recall, computational cost and sensitivity to choice of hyper-parameters. We validate the approach for real-time motion tracking of 5 daily life objects with complex dynamics (a ball, a fully-filled bottle, a half-filled bottle, a hammer and a pingpong racket). To enable real-time tracking, the estimated model of the object’s dynamics is coupled with an Extended Kalman Filter for robustness against noisy sensing.     

An incremental algorithm for Z-value computations

The Z-value (Comput. Chem. 23 (1999) 333) is an extension of the Z-score that is classically used to compare sets of biological sequences. The Z-value has been successfully used to handle complete genome studies as well as analyze large sets of proteins. The Z-value computation is based on a Monte Carlo approach to estimate the statistical significance of a Smith & Waterman alignment score. Comet et al. (Comput. Chem. 23 (1999) 333) have shown that, in contrast to the alignment score, the Z-value largely reduces the bias due to the lengths and compositions of the sequences. They also described an estimator of the deviation of Z-values, that we extend in this paper in order to optimize Z-values computation. The incremental algorithm described here provides two characteristics which are usually incompatible: (i) it improves the accuracy of Z-values calculation; (ii) it reduces the time complexity (this algorithm has been named incremental because it iteratively adds random sequences to the Monte-Carlo process when needed). Results are presented, originating from the all-by-all comparison of the proteins from Saccharomyces cerevisiae and Escherichia coli.     

LEARNING MOTOR SKILLS BY IMITATION: A BIOLOGICALLY INSPIRED ROBOTIC MODEL

This article presents a biologically inspired model for motor skills imitation. The model is composed of modules whose functinalities are inspired by corresponding brain regions responsible for the control of movement in primates. These modules are high-level abstractions of the spinal cord, the primary and premotor cortexes (M1 and PM), the cerebellum, and the temporal cortex. Each module is modeled at a connectionist level. Neurons in PM respond both to visual observation of movements and to corresponding motor commands produced by the cerebellum. As such, they give an abstract representation of mirror neurons. Learning of new combinations of movements is done in PM and in the cerebellum. Premotor cortexes and cerebellum are modeled by the DRAMA neural architecture which allows learning of times series and of spatio-temporal invariance in multimodal inputs. The model is implemented in a mechanical simulation of two humanoid avatars, the imitator and the imitatee. Three types of sequences learning are presented: (1) learning of repetitive patterns of arm and leg movements; (2) learning of oscillatory movements of shoulders and elbows, using video data of a human demonstration; 3) learning of precise movements of the extremities for grasp and reach.     

Iterative Estimation of Rigid-Body Transformations

Closed-form solutions are traditionally used in computer vision for estimating rigid body transformations. Here we suggest an iterative solution for estimating rigid body transformations and prove its global convergence. We show that for a number of applications involving repeated estimations of rigid body transformations, an iterative scheme is preferable to a closed-form solution. We illustrate this experimentally on two applications, 3D object tracking and image registration with Iterative Closest Point. Our results show that for those problems using an iterative and continuous estimation process is more robust than using many independent closed-form estimations.     

Microstructure, local and global mechanical properties of friction stir welds in aluminium alloy 6005A-T6

The effect of the welding speed on the microstructure, local and overall mechanical properties of friction stir welded joints has been investigated in the aluminium alloy 6005A-T6. The fine hardening precipitation within the heat-affected zone has been characterized by differential scanning calorimetry (DSC) and transmission electron microscopy (TEM). Post-welding heat treatments have been applied to obtain indications on the level of solid solution supersaturation in the as welded state. The local mechanical behaviour was determined using thin specimens extracted from various regions of the weld. The overall properties were measured on samples cut perpendicular to the weld. Specific attention was devoted to the relationship between the local microstructure and local hardening properties in the weakest region, which govern the overall strength and ductility of the welds.     

Submarine hull integrity under blast loading

The paper deals with numerical methodologies to model and study the structural resistance of submarine hull against explosions, where fluid and solid phenomena interact. Explosion Crack Starter Tests (ECST), which are a standard procedure to study submarine materials and weldments with respect to blast loading, are modelled using an explicit FE code that solves Fluid/Structure (F/S) interactions within the same computation. The proposed numerical methods aim at computing the structural response of a target subjected to sequential explosions. Numerical results are compared to the corresponding explosion tests (ECST) performed by DGA (French Ministry of Defence).     

Statistics of natural image categories

In this paper we study the statistical properties of natural images belonging to different categories and their relevance for scene and object categorization tasks. We discuss how second-order statistics are correlated with image categories, scene scale and objects. We propose how scene categorization could be computed in a feedforward manner in order to provide top-down and contextual information very early in the visual processing chain. Results show how visual categorization based directly on low-level features, without grouping or segmentation stages, can benefit object localization and identification. We show how simple image statistics can be used to predict the presence and absence of objects in the scene before exploring the image.     

Antimicrobial Effects of Nisin,Essential Oil,and γ‐Irradiation Treatments against High Load of Salmonella typhimurium on Mini‐carrots

This study aimed at using essential oil (EO) alone or combined EO with nisin and γ‐irradiation to control Salmonella Typhimurium during the refrigerated storage of mini‐carrots. Peeled mini‐carrots were inoculated with S. Typhimurium at a final concentration of approximately 7 log CFU/g. Inoculated samples were coated by 5 different coating solutions: (i) nisin solution at final concentration of 10³ IU/mL; (ii) mountain savory EO solution at 0.35%; (iii) carvacrol solution at 0.35%; (iv) mountain savory EO at 0.35% plus nisin solution of 10³ IU/mL; or (v) carvacrol at 0.35% plus nisin solution of 10³ IU/mL. Coated mini‐carrots were then irradiated at 0.5 or 1.0 kGy and compared to an unirradiated control sample. Samples were kept at 4 °C and microbial analyses were conducted at days 1, 3, 6, and 9. The results showed that mini‐carrots coated by carvacrol plus nisin solution or mountain savory EO plus nisin solution in combination with irradiation at 1.0 kGy completely eliminated S. Typhimurium to under the detection limit during the storage. Thus, the combined treatments using carvacrol plus nisin or mountain savory EO plus nisin coating solution and irradiation at 1.0 kGy could be used as an effective method for controlling S. Typhimurium in mini‐carrots.