Camera self-calibration with varying intrinsic parameters by an unknown three-dimensional scene

This work proposes a method of camera self-calibration having varying intrinsic parameters from a sequence of images of an unknown 3D object. The projection of two points of the 3D scene in the image planes is used with fundamental matrices to determine the projection matrices. The present approach is based on the formulation of a nonlinear cost function from the determination of a relationship between two points of the scene and their projections in the image planes. The resolution of this function enables us to estimate the intrinsic parameters of different cameras. The strong point of the present approach is clearly seen in the minimization of the three constraints of a self-calibration system (a pair of images, 3D scene, any camera): The use of a single pair of images provides fewer equations, which minimizes the execution time of the program, the use of a 3D scene reduces the planarity constraints, and the use of any camera eliminates the constraints of cameras having constant parameters. The experiment results on synthetic and real data are presented to demonstrate the performance of the present approach in terms of accuracy, simplicity, stability, and convergence.     

New results on discrete-time delay systems identification

A new approach for simultaneous online identification of unknown time delay and dynamic parameters of discrete-time delay systems is proposed in this paper.The proposed algorithm involves constructing a new generalized regression vector and defining the time delay and the rational dynamic parameters in the same vector.The gradient algorithm is used to deal with the identification problem.The effectiveness of this method is illustrated through simulation.     

Machine learning methods to forecast temperature in buildings

Efficient management of energy in buildings saves a very important amount of resources (both economic and technological). As a consequence, there is a very active research in this field. One of the keys of energy management is the prediction of the variables that directly affect building energy consumption and personal comfort. Among these variables, one can highlight the temperature in each room of a building. In this work we apply different machine learning techniques along with other classical ones for predicting the temperatures in different rooms. The obtained results demonstrate the validity of these techniques for predicting temperatures and, therefore, for the establishment of optimal policies of energy consumption.     

Bio‐nanocomposite films based on cellulose nanocrystals filled polyvinyl alcohol/chitosan polymer blend

Bio‐nanocomposite films based on polyvinyl alcohol/chitosan (PVA/CS) polymeric blend and cellulose nanocrystals (CNC) were prepared by casting a homogenous and stable aqueous mixture of the three components. CNC used as nanoreinforcing agents were extracted at the nanometric scale from sugarcane bagasse via sulfuric acid hydrolysis; then they were characterized and successfully dispersed into a PVA/CS (50/50, w/w) blend to produce PVA/CS–CNC bio‐nanocomposite films at different CNC contents (0.5, 2.5, 5 wt %). Viscosity measurement of the film‐forming solutions and structural and morphological characterizations of the solid films showed that the CNC are well dispersed into PVA/CS blend forming strong interfacial interactions that provide an enhanced load transfer between polymer chains and CNC, thus improving their properties. The obtained bio‐nanocomposite films are mechanically strong and exhibit improved thermal properties. The addition of 5 wt % CNC within a PVA/CS blend increased the Young's modulus by 105%, the tensile strength by 77%, and the toughness by 68%. Herein, the utilization of Moroccan sugarcane bagasse as raw material to produce high quality CNC has been explored. Additionally, the ability of the as‐isolated CNC to reinforce polymer blends was studied, resulting in the production of the aforementioned bio‐nanocomposite films with improved properties. © 2015 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2015 , 132, 42004.     

Effect of the Fiber Size on the Physicochemical and Mechanical Properties of Composites of Epoxy and Date Palm Tree Fibers

Lignocellulosic fibers from date palm trees were employed to reinforce an epoxy matrix. Two fiber sizes were used, with the length and diameter in the range of 20–30 and 1.5–3 mm, respectively, for the so‐called long fibers, and in the range of 5–15 and 0.25–0.75 mm, respectively, for the so‐called short fibers. The morphologies of the resulting composites, as well as their thermal, mechanical, and water sorption properties were evaluated. Strong interactions between both components and etherification reactions may occur between the hydroxyl groups of the fibers and the epoxy groups of the epoxy‐amine reactive mixture. These effects are emphasized when decreasing the size of the fibers.

     

Nonlocal PDEs on Graphs: From Tug-of-War Games to Unified Interpolation on Images and Point Clouds

In this paper, we introduce a new general class of partial difference operators on graphs, which interpolate between the nonlocal \(\infty \)-Laplacian, the Laplacian, and a family of discrete gradient operators. In this context, we investigate an associated Dirichlet problem for this general class of operators and prove the existence and uniqueness of respective solutions. We show that a certain partial difference equation based on this class of operators recovers many variants of a stochastic game known as ‘Tug-of-War’ and extends them to a nonlocal setting. Furthermore, we discuss a connection with certain nonlocal partial differential equations. Finally, we propose to use this class of operators as general framework to solve many interpolation problems in a unified manner as arising, e.g., in image and point cloud processing.     

Adaptive control design using stability analysis and tracking errors dynamics for nonlinear square MIMO systems

This paper investigates adaptive control design for nonlinear square MIMO systems. The control scheme is based on recurrent neural networks emulator and controller with decoupled adaptive rates. Networks' parameters are updated according to an autonomous algorithm inspired from the Real Time Recurrent Learning (RTRL). The contributions of this paper are the determination of Lyapunov sufficient stability conditions for decoupled adaptive rates of the emulator and controller and the development of new adaptation strategies based on the tracking error dynamics and Lyapunov stability analysis to improve the closed loop performances. Efficiency of the proposed controller is illustrated with nonlinear system simulations. An application of the developed approaches to a hot-air blower is presented in order to validate simulations results.     

Half-Metallic Magnetism of Quaternary Heusler Compounds Co2Fe x Mn1−x Si(x =0,0.5, and 1.0): First-Principles Calculations

Using first-principles calculations, the structural, electronic, and magnetic properties of ferromagnetic half-metallic full-Heusler Co₂FeSi, Co₂MnSi and Co₂ Fe _0.5Mn _0.5Si alloy via the full-potential linearized augmented plane-wave (FP-LAPW) method in the generalized gradient (GGA) and GGA + U approximations are compared with other experimental and theoretical results. The electronic band structures and density of states (DOS) of the compounds indicate they are half metallic because of the existence of the energy gap in the minority spin (DOS and band structure), which yields perfect spin polarization. The half metallicity of the obtained material may prove useful for applications in spin-polarizers and spin-injectors of magnetic nanodevices. The calculated total spin magnetic moments are almost exactly that expected from the Slater-Pauling rule.     

Large amplitude free vibration of a shear deformable laminated composite parabolic plate with parabolically orthotropic plies

The large amplitude free vibration of a laminated composite parabolic plate with parabolically orthotropic plies is investigated for the first time. The effects of out-of-plane shear deformations, rotary inertia, and geometrical nonlinearity are taken into account. The geometry of the plate is described, and the analysis performed in the parabolic coordinate system. The problem is solved numerically using a new parabolic hierarchical finite element. The nonlinear equations of free motion are mapped from the time domain into the frequency domain using the harmonic balance method. The resultant nonlinear equations are solved iteratively using the linearized updated mode method. Results for the fundamental linear and nonlinear frequencies are obtained for symmetric and antisymmetric laminates with clamped and simply supported edges. Comparisons are made with the finite element method for clamped and free isotropic parabolic plates and show excellent agreement. The aspect ratio, thickness ratio, moduli ratio, number of plies, layup sequence, and boundary conditions are shown to affect the hardening behavior.