Technique for anisotropic extension of organic crystals: application to temperature dependence of electrical resistance

We have developed a technique for the anisotropic extension of fragile molecular crystals. The pressure medium and the instrument, which extends the pressure medium, are both made from epoxy resin. Since the thermal contraction of our instrument is identical to that of the pressure medium, the strain applied to the pressure medium has no temperature dependence down to 2 K. Therefore, the degree of extension applied to the single crystal at low temperatures is uniquely determined from the degree of extension in the pressure medium and thermal contractions of the epoxy resin and the single crystal at ambient pressure. Using this novel instrument, we have measured the temperature dependence of the electrical resistance of metallic, superconducting, and insulating materials. The experimental results are discussed from the viewpoint of the extension (compression) of the lattice constants along the parallel (perpendicular) direction.     

Magnetic probe array with high sensitivity for fluctuating field

A magnetic probe array is constructed to measure precisely the spatial structure of a small fluctuating field included in a strong confinement field that varies with time. To exclude the effect of the confinement field, the magnetic probes consisting of figure-eight-wound coils are prepared. The spatial structure of the fluctuating field is obtained from a Fourier analysis of the probe signal. It is found that the probe array is more sensitive to the fluctuating field with a high mode number than that with a low mode number. An experimental demonstration of the present method is attempted using a field-reversed configuration plasma, where the fluctuating field with 0.1% of the confinement field is successfully detected.     

Minimum cost source location problem with vertex-connectivity requirements in digraphs

Given a digraph (or an undirected graph) G=(V,E) with a set V of vertices v with nonnegative real costs w(v), and a set E of edges and a positive integer k, we deal with the problem of finding a minimum cost subset SV such that, for each vertex vV−S, there are k vertex-disjoint paths from S to v. In this paper, we show that the problem can be solved by a greedy algorithm in time in a digraph (or in time in an undirected graph), where n=|V| and m=|E|. Based on this, given a digraph and two integers k and ℓ, we also give a polynomial time algorithm for finding a minimum cost subset SV such that for each vertex vV−S, there are k vertex-disjoint paths from S to v as well as ℓ vertex-disjoint paths from v to S.     

ORBIT: A parallel computing model of Prolog

This paper proposes a parallel processing model of the Prolog language. The model modifies Or-parallelism by introducing the “process bundle” as a candidate for simultaneous execution. The Process bundle is a subset of backtrack points stacked in depth-first execution. The process bundle includes one or more backtrack points, so it provides a longer process life cycle than the Or-parallel process. A process bundle is dispatched when an idle processor requests a job from an executing processor. The executing processor dispatches a message containing the full environment by which the idle processor can execute the process without any communication with other processors.     

Theory of quasi-two-dimensional quantum solids. II. An anisotropic reaction-matrix approach

A self-consistent theory is proposed for anisotropic quantum solids such as dense helium monolayers adsorbed onto graphite, based upon the reactionmatrix formalism. The effect of the excitations normal to the adsorption plane is fully included in the ground-state as well as in the vibrational properties. Dispersion relations are derived both for the in-plane and out-of-plane vibrational modes, and the coupling of the two modes is studied as well.     

Superconductivity in dilute Cu-Nb-Sn alloys containing Nb3Sn precipitates

The dilute Cu-Nb-Sn alloys containing small amounts of Nb and Sn less than 1 at % exhibited superconductivity after quenching from the liquid state and ageing. The best superconducting properties ( andJ _c=130 A cm^–2) in a Cu-0.30 at % Nb 0.15 at % Sn alloy were obtained when the sample was aged at 550° C for 384 h. This sample exhibited a structure of fine Nb₃Sn precipitates of 200 to 500Å diameter distributed homogeneously in the Cu matrix, and therefore it was concluded that superconductivity in these alloys resulted from the proximity effect of Nb₃Sn particles. In spite of the similar structure obtained by ageing at 800° C, the Cu-Nb-Sn alloys showed inferior superconducting properties compared to the Cu-0.4 at % Nb alloy and this would be explained qualitatively by the difference in the mean free path in the two alloys.     

Efficient blind dereverberation and echo cancellation based on independent component analysis for actual acoustic signals

This letter presents a new algorithm for blind dereverberation and echo cancellation based on independent component analysis (ICA) for actual acoustic signals. We focus on frequency domain ICA (FD-ICA) because its computational cost and speed of learning convergence are sufficiently reasonable for practical applications such as hands-free speech recognition. In applying conventional FD-ICA as a preprocessing of automatic speech recognition in noisy environments, one of the most critical problems is how to cope with reverberations. To extract a clean signal from the reverberant observation, we model the separation process in the short-time Fourier transform domain and apply the multiple input/output inverse-filtering theorem (MINT) to the FD-ICA separation model. A naive implementation of this method is computationally expensive, because its time complexity is the second order of reverberation time. Therefore, the main issue in dereverberation is to reduce the high computational cost of ICA. In this letter, we reduce the computational complexity to the linear order of the reverberation time by using two techniques: (1) a separation model based on the independence of delayed observed signals with MINT and (2) spatial sphering for preprocessing. Experiments show that the computational cost grows in proportion to the linear order of the reverberation time and that our method improves the word correctness of automatic speech recognition by 10 to 20 points in a RT??= 670 ms reverberant environment.     

Efficient semi-supervised learning on locally informative multiple graphs

We address an issue of semi-supervised learning on multiple graphs, over which informative subgraphs are distributed. One application under this setting can be found in molecular biology, where different types of gene networks are generated depending upon experiments. Here an important problem is to annotate unknown genes by using functionally known genes, which connect to unknown genes in gene networks, in which informative parts vary over networks. We present a powerful, time-efficient approach for this problem by combining soft spectral clustering with label propagation for multiple graphs. We demonstrate the effectiveness and efficiency of our approach using both synthetic and real biological datasets.     

A high‐performance sorting algorithm for multicore single‐instruction multiple‐data processors

Many sorting algorithms have been studied in the past, but there are only a few algorithms that can effectively exploit both single‐instruction multiple‐data (SIMD) instructions and thread‐level parallelism. In this paper, we propose a new high‐performance sorting algorithm, called aligned‐access sort (AA‐sort), that exploits both the SIMD instructions and thread‐level parallelism available on today's multicore processors. Our algorithm consists of two phases, an in‐core sorting phase and an out‐of‐core merging phase. The in‐core sorting phase uses our new sorting algorithm that extends combsort to exploit SIMD instructions. The out‐of‐core algorithm is based on mergesort with our novel vectorized merging algorithm. Both phases can take advantage of SIMD instructions. The key to high performance is eliminating unaligned memory accesses that would reduce the effectiveness of SIMD instructions in both phases. We implemented and evaluated the AA‐sort on PowerPC 970MP and Cell Broadband Engine platforms. In summary, a sequential version of the AA‐sort using SIMD instructions outperformed IBM's optimized sequential sorting library by 1.8 times and bitonic mergesort using SIMD instructions by 3.3 times on PowerPC 970MP when sorting 32 million random 32‐bit integers. Also, a parallel version of AA‐sort demonstrated better scalability with increasing numbers of cores than a parallel version of bitonic mergesort on both platforms. Copyright © 2011 John Wiley & Sons, Ltd.     

A Linear-Time Algorithm for Star-Shaped Drawings of Planar Graphs with the Minimum Number of Concave Corners

A star-shaped drawing of a graph is a straight-line drawing such that each inner facial cycle is drawn as a star-shaped polygon, and the outer facial cycle is drawn as a convex polygon. In this paper, we consider the problem of finding a star-shaped drawing of a biconnected planar graph with the minimum number of concave corners. We first show new structural properties of planar graphs to derive a lower bound on the number of concave corners. Based on the lower bound, we prove that the problem can be solved in linear time by presenting a linear-time algorithm for finding a best plane embedding of a biconnected planar graph with the minimum number of concave corners. This is in spite of the fact that a biconnected planar graph may have an exponential number of different plane embeddings.