Generalized measuring-worm algorithm: high-accuracy mapping and movement via cooperating swarm robots

Recently, many extensive studies have been conducted on robot control via self-positioning estimation techniques. In the simultaneous localization and mapping (SLAM) method, which is one approach to self-positioning estimation, robots generally use both autonomous position information from internal sensors and observed information on external landmarks. SLAM can yield higher accuracy positioning estimations depending on the number of landmarks; however, this technique involves a degree of uncertainty and has a high computational cost, because it utilizes image processing to detect and recognize landmarks. To overcome this problem, we propose a state-of-the-art method called a generalized measuring-worm (GMW) algorithm for map creation and position estimation, which uses multiple cooperating robots that serve as moving landmarks for each other. This approach allows problems of uncertainty and computational cost to be overcome, because a robot must find only a simple two-dimensional marker rather than feature-point landmarks. In the GMW method, the robots are given a two-dimensional marker of known shape and size and use a front-positioned camera to determine the marker distance and direction. The robots use this information to estimate each other’s positions and to calibrate their movement. To evaluate the proposed method experimentally, we fabricated two real robots and observed their behavior in an indoor environment. The experimental results revealed that the distance measurement and control error could be reduced to less than 3 %.     

Bright-field scanning confocal electron microscopy using a double aberration-corrected transmission electron microscope

Scanning confocal electron microscopy (SCEM) offers a mechanism for three-dimensional imaging of materials, which makes use of the reduced depth of field in an aberration-corrected transmission electron microscope. The simplest configuration of SCEM is the bright-field mode. In this paper we present experimental data and simulations showing the form of bright-field SCEM images. We show that the depth dependence of the three-dimensional image can be explained in terms of two-dimensional images formed in the detector plane. For a crystalline sample, this so-called probe image is shown to be similar to a conventional diffraction pattern. Experimental results and simulations show how the diffracted probes in this image are elongated in thicker crystals and the use of this elongation to estimate sample thickness is explored.     

Microscopic image restoration based on tensor factorization of rotated patches

In microscopic image processing for analyzing biological objects, structural characters of objects such as symmetry and orientation can be used as a prior knowledge to improve the results. In this study, we incorporated filamentous local structures of neurons into a statistical model of image patches and then devised an image processing method based on tensor factorization with image patch rotation. Tensor factorization enabled us to incorporate correlation structure between neighboring pixels, and patch rotation helped us obtain image bases that well reproduce filamentous structures of neurons. We applied the proposed model to a microscopic image and found significant improvement in image restoration performance over existing methods, even with smaller number of bases.     

Voronoi-based coverage control with anisotropic sensors and experimental case study

In this paper, we investigate coverage control problem for mobile sensor networks. The novelty is to consider an anisotropic sensor model whose performance depends not only on the distance but also on the orientation to a target point. By adapting Lloyd algorithm, a distributed control law is derived. Aside from coverage, we also show that the control law guarantees collision avoidance between the agents. The performance of the control laws is demonstrated through not only numerical simulation but also experiments on a mobile robot test bed.     

Thermal conductivity and phonon scattering mechanisms in La#x2212;x#x2212;x#x2212;xMxCuO4

The thermal conductivity of high density La_2–xM_xCuO₄ (M=Ba, Sr) sintered materials was measured between 15K and 150K for the various concentrations of Ba and the phonon thermal conductivity was analyzed comparing with that of Nd_2–xCe_xCuO₄. The pretty large value for pure La₂CuO₄ was drastically diminished by substituting La by a small amount of Ba atoms especially at low temperatures. It was found that a new type of the phonon scattering center such as a two-level tunneling must be taken account of in order to explain the observed reduction.     

A performance evaluation of disassembly systems with reverse blocking

For sustainable manufacturing, manufacturers should construct and design inverse manufacturing systems consisting of assembly and disassembly systems. The sorting process in the disassembly system is the first process of the whole inverse manufacturing system. Therefore, it can become a bottleneck and decrease the productivity of the whole inverse manufacturing systems.This study focuses on a disassembly system with reverse blocking in a sorting process [Yamada, T., & Matsui, M. (2003). Disassembly production systems and its design issues. Reprints of Japan Industrial Management Association, Spring meeting, Chofu, Japan, May, 144–145 (in Japanese)]. It generalizes the queuing model and discusses the performance of the disassembly system by mathematical and numerical analysis. First, the sorting process with reverse blocking is generally modeled as a queuing system. Next, the stationary state equations of the system are formulated, and the objective function is set as the throughput. Finally, the system performance is discussed by mathematical and numerical analysis in cases of a different number of stations and buffers, and also an example of the system design is shown and discussed in view of the busy rate, blocking probability and throughput.     

Efficient Leave-<Emphasis Type="Italic">m</Emphasis>-out Cross-Validation of Support Vector Regression by Generalizing Decremental Algorithm

We propose a computationally efficient method for cross-validation of the Support Vector Regression (SVR) by generalizing the decremental algorithm of SVR. Incremental and decremental algorithm of Support Vector Machines (SVM) ^{2, 8, 9)} efficiently update the trained SVM model when a single data point is added to or removed from the training set. The computational cost of leave-one-out cross-validation can be reduced using the decremental algorithm. However, when we perform leave-m-out cross-validation (m > 1), we have to repeatedly apply the decremental algorithm for each data point. In this paper, we extend the decremental algorithm of SVR^{8, 9)} in such a way that several data points can be removed more efficiently. Experimental results indicate that the proposed approach can reduce the computational cost. In particular, we observed that the number of breakpoints, which is the main computational cost of the involved path-following, were reduced from \({\mathcal O}(m)\) to \({\mathcal O}(\sqrt{m})\).     

Accurate finite element method for atomic calculations based on density functional theory and Hartree–Fock method

An accurate finite element method is developed for atomic calculations based on density functional theory (DFT) within local density approximation (LDA) and Hartree–Fock (HF) method. The radial wave functions are expanded by cubic Hermite spline functions on a uniform mesh for , and all the associated integrals are analytically evaluated in conjunction with fitting procedures of the Hartree and the exchange–correlation potentials to the same cubic Hermite spline functions using a set of recurrence formulas. The total energy of atoms systematically converges from above, and the error algebraically decays as the mesh spacing decreases. When the mesh spacing d is taken to be , the total energy for an atom of atomic number Z can be calculated within error of ¹⁰−7 hartree for both the LDA and HF methods. The equal applicability of the method to DFT and the HF method with a similar degree of high accuracy enables the method to be a reliable platform for development of new functionals in DFT such as hybrid functionals.     

Accumulation of triosephosphate isomerase, with sequence homology to Beta amyloid peptides, in vessel walls of the newborn piglet hippocampus

We investigated whether beta-amyloid (Abeta)-like immunoreactivity was seen in the brains of newborn piglets. The immunoreactivity for Abeta(1-42) and Abeta(1-40) proteins, but not Abeta precursor protein, was present in CD68-positive perivascular cells of the hippocampus and in parts of the meninges. It was colocalized with immunoreactivity for receptor for advanced glycation end product and tumor necrosis factor-alpha. The protein with a molecular mass of 27 kDa, which was recognized by the Abeta antibodies, was identified as triosephosphate isomerase (TPI) with sequence homology to Abeta peptides by N-terminal amino acid sequencing, mass fingerprint analysis using matrix-associated laser desorption/ionization mass spectrometry, and Western blotting. Western blotting assay also revealed that detectable expression of Abeta proteins were not seen in the piglet brains. These findings indicate that TPI with sequence homology to Abeta peptides accumulates in perivascular cells of the microglia/macrophage lineage located around arterial vessels of the newborn piglet hippocampus.