Remarks on the tracking method of neural network weight change for a learning-type neural network feed-forward feed-back controller

Although many neural network controllers have been proposed, we still have to tune several parameters of neural networks in order to obtain a better learning performance in practical applications. Our tracking method provides a new aspect of this tuning of neural network parameters. It has been applied to adaptive and learning-type neural network direct controllers, and an adaptive-type neural network feed-forward feed-back controller. This work applied it to a learning-type neural network feed-forward feed-back controller. Simulation results confirmed its usefulness, and we discuss a transformation of the track on a 2D plane to one-dimensional values.     

Probabilistic calibration of discrete element simulations using the sequential quasi-Monte Carlo filter

The calibration of discrete element method (DEM) simulations is typically accomplished in a trial-and-error manner. It generally lacks objectivity and is filled with uncertainties. To deal with these issues, the sequential quasi-Monte Carlo (SQMC) filter is employed as a novel approach to calibrating the DEM models of granular materials. Within the sequential Bayesian framework, the posterior probability density functions (PDFs) of micromechanical parameters, conditioned to the experimentally obtained stress–strain behavior of granular soils, are approximated by independent model trajectories. In this work, two different contact laws are employed in DEM simulations and a granular soil specimen is modeled as polydisperse packing using various numbers of spherical grains. Knowing the evolution of physical states of the material, the proposed probabilistic calibration method can recursively update the posterior PDFs in a five-dimensional parameter space based on the Bayes’ rule. Both the identified parameters and posterior PDFs are analyzed to understand the effect of grain configuration and loading conditions. Numerical predictions using parameter sets with the highest posterior probabilities agree well with the experimental results. The advantage of the SQMC filter lies in the estimation of posterior PDFs, from which the robustness of the selected contact laws, the uncertainties of the micromechanical parameters and their interactions are all analyzed. The micro–macro correlations, which are byproducts of the probabilistic calibration, are extracted to provide insights into the multiscale mechanics of dense granular materials.     

Deformation and Fracture of Micron‐Sized Metal‐Coated Polymer Spheres: An In Situ Study

In situ imaging and analysis of the mechanical behavior of micron‐sized metal‐coated polymer particles under compression is reported. A nanoindentation set‐up mounted in a scanning electron microscope is used to observe the deformation and fracture of 10 μm polymer spheres with Ni, Ni/Au, Au, and Ag coatings. The spheres fracture in one of two metallization‐dependent modes, brittle, and ductile, depending only on the presence of a nickel layer. The metal coating always fractures parallel to the direction of compression. The mechanical properties up to the point of coating fracture are rate‐dependent due to the viscoelastic polymer core. Metal‐coated polymer spheres are an important composite material in electronics packaging, and this study demonstrates a novel method of evaluating the mechanical properties of particles to tailor them for electronic materials.

     

Single-crystal growth and characterization of Cu2O and CuO

We have prepared a large number of crystals of cuprous oxide (Cu2O) by various procedures. Photoluminescence spectra of these crystals were studied to examine the concentration of defects, especially copper vacancy VCu to seek favourable conditions for growing Cu2O crystal. High-quality single crystals of Cu2O were prepared by the floating-zone melting method in air. Several synthetic crystals (specimens FA, FZ and GZ) and also a natural crystal were studied by X-ray analysis, inductively coupled plasma spectroscopy analysis, optical absorption, photoluminescence, photoconductivity and cyclotron resonance absorption, photoluminescence, photoconductivity and cyclotron resonance absorption to characterize their optical and electrical qualities. The best values of mobility and scattering time of photocarriers at T = 4.2 K are estimated to be h1.8 × 105 cm2 V–1 s–1 and h60 ps for positive holes, and 1.3 × 105 cm2 V–1 s–1 and 70 ps for electrons in Cu2O. Further, we report preliminary experimental results on transport property of crystals also of cupric oxide (CuO) purified by the floating-zone melting method.     

Cu-NMR study on high-T c cuprate La1.89Ca1.11Cu2O6+δ (La2126)

Cu-NMR spectra and the nuclear spin-lattice relaxation rate T ₁ ^-1 have been studied intensively on the bilayer type high-T_c cuprate La_1.89Ca_1.11Cu₂O₆₊ (La2126). The resonance line shift showed a monotonic decrease with lowering temperature in the normal state, indicating that this compound belongs to the lightly-doped region. The Curie-Weiss temperature dependence of (T₁T)^–1 in the normal state shows that the pseudo spin-gap does not always exist in the light-doped bilayer systems.     

Adaptive locks: Combining transactions and locks for efficient concurrency

Transactional memory is being advanced as an alternative to traditional lock-based synchronization for concurrent programming. Transactional memory simplifies the programming model and maximizes concurrency. At the same time, transactions can suffer from interference that causes them to often abort, from heavy overheads for memory accesses, and from expressiveness limitations (e.g., for I/O operations). In this paper we propose an adaptive locking technique that dynamically observes whether a critical section would be best executed transactionally or while holding a mutex lock. The critical new elements of our approach include the adaptivity logic and cost–benefit analysis, a low-overhead implementation of statistics collection and adaptive locking in a full C compiler, and an exposition of the effects on the programming model. In experiments with both micro and macrobenchmarks we found adaptive locks to consistently match or outperform the better of the two component mechanisms (mutexes or transactions). Compared to either mechanism alone, adaptive locks often provide 3-to-10x speedups. Additionally, adaptive locks simplify the programming model by reducing the need for fine-grained locking: with adaptive locks, the programmer can specify coarse-grained locking annotations and often achieve fine-grained locking performance due to the transactional memory mechanisms.     

Compressive multi-spectral imaging using self-correlations of images based on hierarchical joint sparsity models

We propose a novel multi-spectral imaging method based on compressive sensing (CS). In CS theory, the enhancement of signal sparsity is important for accurate signal reconstruction. The main novelty of the proposed method is the employment of a self-correlation of an image, that is a local intensity similarity and multi-spectral correlation, to enhance the sparsity of the multi-spectral image to be recovered. Local intensity similarity, which is based on the concept that spatial changes in intensity are likely to be similar within local regions, contributes to sparsity enhancement. Furthermore, we exploit multi-spectral correlation to improve the sparsity of the multi-spectral components to be recovered. In order to simultaneously exploit different types of characteristics (i.e., local intensity similarity and multi-spectral correlation) for representing a signal as sufficiently sparse, we introduce a hierarchical joint sparsity model in the CS image recovery process. Our experiments show that the use of a self-correlation significantly improves the performance of multi-spectral image reconstruction.     

Molecular dynamics simulations of diffusion of submonolayer polar liquid lubricant films on solid surfaces

A fundamental understanding of the diffusion phenomena of submonolayer polar liquid films is important for achieving reliable lubrication between moving mechanical parts separated by a nanometer-sized gap. To acquire this understanding, we conducted molecular dynamics (MD) simulations of diffusion phenomena of submonolayer polar perfluoropolyether (PFPE) Zdol films on solid surfaces. To improve the accuracy of these simulations, we developed an all-atom model that includes hydrogen-bond potential and refined atomic charges for Zdol molecules and tested it through MD simulations of spreading of step-shaped submonolayer PFPE films. Our MD simulations reproduced the experimentally observed effects of polar end groups on the diffusion speed and molecular conformation of Zdol. We then conducted MD simulations of self-diffusion of submonolayer Zdol films; these simulations demonstrated that as the thickness of the submonolayer Zdol films decreases, molecular conformation becomes flatter and the self-diffusion coefficient decreases. These changes in molecular conformation partially explain our experimental finding that the spreading of step-shaped submonolayer polar PFPE films slows down with decreasing initial thickness.