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.     

Limitations on post-processing assisted quantum programming

A quantum multimeter is a programmable device that can implement measurements of different observables depending on the programming quantum state inserted into it. The advantage of this arrangement over a single-purpose device is in its versatility: one can realize various measurements simply by changing the programming state. The classical manipulation of measurement output data is known as post-processing. In this work we study the post-processing assisted quantum programming, which is a protocol where quantum programming and classical post-processing are combined. We provide examples showing that these two processes combined can be more efficient than either of them used separately. Furthermore, we derive an inequality relating the programming resources to their corresponding programmed observables, thereby enabling us to study the limitations on post-processing assisted quantum programming.     

Bottom-up pyramid cellular acceptors with three-dimensional layers

In 1997, C.R. Dyer and A. Rosenfeld introduced an acceptor on a two-dimensional pattern (or tape), called the pyramid cellular acceptor, and demonstrated that many useful recognition tasks are executed by pyramid cellular acceptors in time proportional to the logarithm of the diameter of the input. They also introduced a bottom-up pyramid cellular acceptor which is a restricted version of the pyramid cellular acceptor, and proposed some interesting open problems of the bottom-up pyramid cellular acceptors. On the other hand, we think that the study of threedimensional automata has been meaningful as the computational model of three-dimensional information processing such as computer vision, robotics, and so forth. In this paper, we investigate about bottom-up pyramid cellular acceptors with three-dimensional layers, and show their some accepting powers. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

Straight-through microchannel devices for generating monodisperse emulsion droplets several microns in size

The authors recently proposed a promising technique for producing monodisperse emulsions using a straight-through microchannel (MC) device composed of an array of microfabricated oblong holes. This research developed new straight-through MC devices with tens of thousands of oblong channels of several microns in size on a silicon-on-insulator plate, and investigated the emulsification characteristics using the microfabricated straight-through MC devices. Monodisperse oil-in-water (O/W) and W/O emulsions with average droplet diameters of 4.4–9.8 μm and coefficients of variation of less than 6% were stably produced using surface-treated straight-through MC devices that included uniformly sized oblong channels with equivalent diameters of 1.7–5.4 μm. The droplet size of the resultant emulsions depended greatly on the size of the preceding oblong channels. The emulsification process using the straight-through MC devices developed in this research had very high apparent energy efficiencies of 47–60%, defined as (actual energy input applied to droplet generation/theoretical minimum energy input necessary for making droplets) × 100. Straight-through MC devices with numerous oblong microfluidic channels also have great potential for increasing the productivity of monodisperse fine emulsions.     

Case learning for CBR-based collision avoidance systems

With the rapid development of case-based reasoning (CBR) techniques, CBR has been widely applied to real-world applications such as collision avoidance systems. A successful CBR-based system relies on a high-quality case base, and a case creation technique for generating such a case base is highly required. In this paper, we propose an automated case learning method for CBR-based collision avoidance systems. Building on techniques from CBR and natural language processing, we developed a methodology for learning cases from maritime affair records. After giving an overview on the developed systems, we present the methodology and the experiments conducted in case creation and case evaluation. The experimental results demonstrated the usefulness and applicability of the case learning approach for generating cases from the historic maritime affair records.     

Morphological and crystallographic features of γ-γ′ Ni-Al and Ni-Al-Ti two-phase bicrystals

Several- Ni-Al and Ni-Al-Ti two-phase bicrystals were made by the solid-state diffusion couple method. Each couple consisted of a-phase single crystal and a pure-Ni polycrystal, and was annealed at 1473 K in an Ar gas atmosphere. Single crystal layers of-phase with uniform thickness always grow into the parent-phase single crystals. The resultant/ interface has no voids or facets regardless of the orientation of interface and the chemical composition of the-phase. Porosity formation due to the Kirkendall effect is observed in the diffused region. Concentration profiles exhibit nearly constant gradients in-phase. The orientation relationship between both phases is found to be 001//001, that is, the-phase grows epitaxially along the crystal orientation of-phase.