Stereo matching cost computation based on nonsubsampled contourlet transform

A new matching cost computation method based on nonsubsampled contourlet transform (NSCT) for stereo image matching is proposed in this paper. Firstly, stereo image is decomposed into high frequency sub-band images at different scales and along different directions by NSCT. Secondly, by utilizing coefficients in high frequency domain and grayscales in RGB color space, the computation model of weighted matching cost between two pixels is designed based on the gestalt laws. Lastly, two types of experiments are carried out with standard stereopairs in the Middlebury benchmark. One of the experiments is to confirm optimum values of NSCT scale and direction parameters, and the other is to compare proposed matching cost with nine known matching costs. Experimental results show that the optimum values of scale and direction parameters are respectively 2 and 3, and the matching accuracy of the proposed matching cost is twice higher than that of traditional NCC cost.     

Three Ln(III)-2,3,5-trichlorobenzoate coordination polymers (Ln = Tb,Ho and Er): Syntheses,structures and magnetic properties

Three novel lanthanide polymers, [Ln(III)(L)₃EtOH]_n (Ln = Tb(1), Ho(2), Er(3), HL = 2,3,5-trichlorobenzoic acid), have been solvothermal synthesized and characterized by single-crystal X-ray diffraction, infrared spectroscopy and element analyses. The three polymers crystallize in triclinic space group P-1. The Ln(III) ions are in turn bridged by double and quadruple carboxylate of L⁻ ligands to form one-dimensional (1D) chains. Magnetic studies reveal that polymer 1 demonstrates dominant ferromagnetic behavior, polymer 2 shows antiferromagnetic behavior, and polymer 3 present spin-canting behavior.     

Preparation of biaxially textured Ce1-x(Y0.2Zr0.8)xOδ buffer layers on RABiTS NiW tapes by chemical solution deposition

Highly (100)-oriented Ce_1-x(Y_0.2Zr_0.8)_xO_δ (CYZO) films were prepared on biaxially textured NiW substrates by a chemical solution deposition approach using metal inorganic salts as starting materials. It has been found that both the preferential orientation and surface roughness of CYZO films decrease gradually with increasing of the doping percentage of Y³⁺ and Zr⁴⁺ ions. The epitaxial growth relationship of (220)_CYZO//(200)_NiW and [00?l]_CYZO//[001]_NiW was demonstrated by XRD texture measurement as well as atomic resolution STEM observation. XRD, Raman and XPS spectra results indicate that Y³⁺ and Zr⁴⁺ ions were indeed introduced into CeO₂ lattice to substitute Ce⁴⁺ ions and form cubic fluorite CYZO solid solution. Moreover, CeO₂ buffer layer can be endowed a strong enough capability to prevent element diffusion through co-doping of yttrium and zirconium, provided that an optimal doping ratio of them is adopted. This will provide a new approach to fabricating strong-barrier single buffer layer for coated conductor.     

Covariance matrix adaptation evolution strategy based design of fixed structure robust H∞ loop shaping controller

This paper proposes the application of Covariance Matrix Adaptation Evolution Strategy (CMA-ES) in fixed structure H_∞ loop shaping controller design. Integral Time Absolute Error (ITAE) performance requirement is incorporated as a constraint with an objective of maximization of stability margin in the fixed structure H_∞ loop shaping controller design problem. Pneumatic servo system, separating tower process and F18 fighter aircraft system are considered as test systems. The CMA-ES designed fixed structure H_∞ loop-shaping controller is compared with the traditional H_∞ loop shaping controller, non-smooth optimization and Heuristic Kalman Algorithm (HKA) based fixed structure H_∞ loop shaping controllers in terms of stability margin. 20% perturbation in the nominal plant is used to validate the robustness of the CMA-ES designed H_∞ loop shaping controller. The effect of Finite Word Length (FWL) is considered to show the implementation difficulties of controller in digital processors. Simulation results demonstrated that CMA-ES based fixed structure H_∞ loop shaping controller is suitable for real time implementation with good robust stability and performance.     

An ideal host-guest system to accomplish high-performance greenish yellow and hybrid white organic light-emitting diodes

Greenish yellow organic light-emitting diodes (GYOLEDs) have steadily attracted researcher's attention since they are important to our life. However, their performance significantly lags behind compared with the three primary colors based OLEDs. Herein, for the first time, an ideal host-guest system has been demonstrated to accomplish high-performance phosphorescent GYOLEDs, where the guest concentration is as low as 2%. The GYOLED exhibits a forward-viewing power efficiency of 57.0 lm/W at 1000 cd/m², which is the highest among GYOLEDs. Besides, extremely low efficiency roll-off and voltages are achieved. The origin of the high performance is unveiled and it is found that the combined mechanisms of host-guest energy transfer and direct exciton formation on the guest are effective to furnish the greenish yellow emission. Then, by dint of this ideal host-guest system, a simplified but high-performance hybrid white OLED (WOLED) has been developed. The WOLED can exhibit an ultrahigh color rendering index (CRI) of 92, a maximum total efficiency of 27.5 lm/W and a low turn-on voltage of 2.5 V (1 cd/m²), unlocking a novel avenue to simultaneously achieve simplified structure, ultrahigh CRI (>90), high efficiency and low voltage.     

Classification and regression models of audio and vibration signals for machine state monitoring in precision machining systems

We present a data-driven method for monitoring machine status in manufacturing processes. Audio and vibration data from precision machining are used for inference in two operating scenarios: (a) variable machine health states (anomaly detection); and (b) settings of machine operation (state estimation). Audio and vibration signals are first processed through Fast Fourier Transform and Principal Component Analysis to extract transformed and informative features. These features are then used in the training of classification and regression models for machine state monitoring. Specifically, three classifiers (K-nearest neighbors, convolutional neural networks and support vector machines) and two regressors (support vector regression and neural network regression) were explored, in terms of their accuracy in machine state prediction. It is shown that the audio and vibration signals are sufficiently rich in information about the machine that 100% state classification accuracy could be accomplished. Data fusion was also explored, showing overall superior accuracy of data-driven regression models.