Binary sparse nonnegative matrix factorization

This paper presents a fast part-based subspace selection algorithm, termed the binary sparse nonnegative matrix factorization (B-SNMF). Both the training process and the testing process of B-SNMF are much faster than those of binary principal component analysis (B-PCA). Besides, B-SNMF is more robust to occlusions in images. Experimental results on face images demonstrate the effectiveness and the efficiency of the proposed B-SNMF.

Optical techniques for real-time binary multiplication

An optical system which performs the multiplication of binary numbers is described and proof-of-principle experiments are performed. The simultaneous generation of all partial products, optical regrouping of bit products, and optical carry look-ahead addition are novel features of the proposed scheme which takes advantage of the parallel operations capability of optical computers. The proposed processor uses liquid crystal light valves (LCLVs). By space-sharing the LCLVs one such system could function as an array of multipliers. Together with the optical carry look-ahead adders described, this would constitute an optical matrix-vector multiplier.

Binary image steganographic techniques classification based on multi-class steganalysis

In this paper, we propose a new multi-class steganalysis for binary image. The proposed method can identify the type of steganographic technique used by examining on the given binary image. In addition, our proposed method is also capable of differentiating an image with hidden message from the one without hidden message. In order to do that, we will extract some features from the binary image. The feature extraction method used is a combination of the method extended from our previous work and some new methods proposed in this paper. Based on the extracted feature sets, we construct our multi-class steganalysis from the SVM classifier. We also present the empirical works to demonstrate that the proposed method can effectively identify five different types of steganography.

Blind steganalysis : a countermeasure for binary image steganography

In this paper, we propose a new blind steganalytic method to detect the presence of secret messages embedded in black and white images using the steganographic techniques. We start by extracting several sets of matrix, such as run length matrix, gap length matrix and pixel difference. We also apply characteristic function on these matrices to enhance their discriminative capabilities. Then we calculate the statistics which include mean, variance, kurtosis and skewness to form our feature sets. The presented empirical works demonstrate our proposed method can effectively detect three different types of steganography. This proves the universality of our proposed method as a blind steganalysis. In addition, the experimental results show our proposed method is capable of detecting small amount of the embedded message.

Massive black-hole binary inspirals: results from the LISA parameter estimation taskforce

The LISA Parameter Estimation Taskforce was formed in September 2007 to provide the LISA Project with vetted codes, source distribution models and results related to parameter estimation. The Taskforce's goal is to be able to quickly calculate the impact of any mission design changes on LISA's science capabilities, based on reasonable estimates of the distribution of astrophysical sources in the universe. This paper describes our Taskforce's work on massive black-hole binaries (MBHBs). Given present uncertainties in the formation history of MBHBs, we adopt four different population models, based on (i) whether the initial black-hole seeds are small or large and (ii) whether accretion is efficient or inefficient at spinning up the holes. We compare four largely independent codes for calculating LISA's parameter-estimation capabilities. All codes are based on the Fisher-matrix approximation, but in the past they used somewhat different signal models, source parametrizations and noise curves. We show that once these differences are removed, the four codes give results in extremely close agreement with each other. Using a code that includes both spin precession and higher harmonics in the gravitational-wave signal, we carry out Monte Carlo simulations and determine the number of events that can be detected and accurately localized in our four population models.

Extraordinary synergy in the mechanical properties of polymer matrix composites reinforced with 2 nanocarbons

One of the applications of nanomaterials is as reinforcements in composites, wherein small additions of nanomaterials lead to large enhancements in mechanical properties. There have been extensive studies in the literature on composites where a polymer matrix is reinforced by a single nanomaterial such as carbon nanotubes. In this article, we examine the significant synergistic effects observed when 2 different types of nanocarbons are incorporated in a polymer matrix. Thus, binary combinations of nanodiamond, few-layer graphene, and single-walled nanotubes have been used to reinforce polyvinyl alcohol. The mechanical properties of the resulting composites, evaluated by the nanoindentation technique, show extraordinary synergy, improving the stiffness and hardness by as much as 400% compared to those obtained with single nanocarbon reinforcements. These results suggest a way of designing advanced materials with extraordinary mechanical properties by incorporating small amounts of 2 nanomaterials such as graphene plus nanodiamond or nanodiamond plus carbon nanotube.

Matrix Decomposition Methods for Data Mining : Computational Complexity and Algorithms

Matrix decompositions, where a given matrix is represented as a product of two other matrices, are regularly used in data mining. Most matrix decompositions have their roots in linear algebra, but the needs of data mining are not always those of linear algebra. In data mining one needs to have results that are interpretable -- and what is considered interpretable in data mining can be very different to what is considered interpretable in linear algebra. --- The purpose of this thesis is to study matrix decompositions that directly address the issue of interpretability. An example is a decomposition of binary matrices where the factor matrices are assumed to be binary and the matrix multiplication is Boolean. The restriction to binary factor matrices increases interpretability -- factor matrices are of the same type as the original matrix -- and allows the use of Boolean matrix multiplication, which is often more intuitive than normal matrix multiplication with binary matrices. Also several other decomposition methods are described, and the computational complexity of computing them is studied together with the hardness of approximating the related optimization problems. Based on these studies, algorithms for constructing the decompositions are proposed. Constructing the decompositions turns out to be computationally hard, and the proposed algorithms are mostly based on various heuristics. Nevertheless, the algorithms are shown to be capable of finding good results in empirical experiments conducted with both synthetic and real-world data.

Carbon-Nanohorn-Reinforced Polymer Matrix Composites: Synergetic Benefits in Mechanical Properties

Mechanical properties of single-walled carbon nanohoms (SWNH) and SWNH plus few-layer graphene (EG)-reinforced poly(vinyl alcohol) (PVA) matrix composites have been measured using the nanoindentation technique. The elastic modulus (E) and hardness (H) of PVA were found to improve by similar to 315% and similar to 135%, respectively, upon the addition of just 0.4 wt % SWNH. These properties were found to be comparable to those obtained upon the addition of 0.2 wt % single-walled nanotubes (SWNT) to PVA. Furthermore, upon binary addition of 0.2 wt % EG and 0.4 wt % SWNH to PVA, benefits in the form of similar to 400% and similar to 330% synergy in E and H, respectively, were observed, along with an increased resistance to viscoelastic deformation. The reasons for these improvements are discussed in terms of the dimensionality of nanocarbon, the effectiveness of nanocarbon and polymer matrix interaction, and the influence of nanocarbon on the degree of crystallinity of the polymer. The results from SWNH reinforcement in this study demonstrate the scope for a novel and, in contrast to SWNT composites, a commercially feasible opportunity for strengthening polymer matrices.

Impact of heterogeneous link qualities and network connectivity on binary consensus

In this paper we consider a network that is trying to reach consensus over the occurrence of an event while communicating over Additive White Gaussian Noise (AWGN) channels. We characterize the impact of different link qualities and network connectivity on consensus performance by analyzing both the asymptotic and transient behaviors. More specifically, we derive a tight approximation for the second largest eigenvalue of the probability transition matrix. We furthermore characterize the dynamics of each individual node. © 2009 AACC.

The formation of ordered nanoholes in binary, chemically similar, symmetric diblock copolymer blend films

Binary symmetric diblock copolymer blends, that is, low-molecular-weight poly(styrene-block-methyl methacrylate) (PS-b-PMMA) and high-molecular-weight poly(styrene-block-methacrylate) (PS-b-PMA), self-assemble on silicon substrates to form structures with highly ordered nanoholes in thin films. As a result of the chemically similar structure of the PMA and the PMMA block, the PMMA chain penetrates through the large PMA block that absorbs preferentially on the polar silicon substrate. This results in the formation of nanoholes in the PS continuous matrix.

Luminescence properties of rare earth (Eu3+ and Tb3+) complexes with conjugated carboxylic acids and 1,10-phenanthroline incorporated in silica matrix

Binary and ternary complexes of europium and terbium with conjugated carboxylic acid (nicotinic acid and 3,4-furandicarboxylic acid) and 1,10-phenanthroline were introduced into silica gel by the sol-gel method. The luminescence behavior of the complexes in silica gels was studied compared with the corresponding solid state complexes by means of emission, excitation spectra and lifetimes. The result indicated that the rare earth ions (EU3+ and Tb3+) showed fewer emission lines and slightly lower emission intensities in the silica gel than those in pure rare earth complexes. The lifetimes of rare earth ions (EU3+ and Tb3+) in silica gel doped with rare earth complexes became longer than those in pure rare earth complexes. (C) 1998 Elsevier Science S.A.

Constraint release in entangled binary blends of linear polymers: a molecular dynamics study

We present extensive molecular dynamics simulations of the dynamics of diluted long probe chains entangled with a matrix of shorter chains. The chain lengths of both components are above the entanglement strand length, and the ratio of their lengths is varied over a wide range to cover the crossover from the chain reptation regime to tube Rouse motion regime of the long probe chains. Reducing the matrix chain length results in a faster decay of the dynamic structure factor of the probe chains, in good agreement with recent neutron spin echo experiments. The diffusion of the long chains, measured by the mean square displacements of the monomers and the centers of mass of the chains, demonstrates a systematic speed-up relative to the pure reptation behavior expected for monodisperse melts of sufficiently long polymers. On the other hand, the diffusion of the matrix chains is only weakly perturbed by the diluted long probe chains. The simulation results are qualitatively consistent with the theoretical predictions based on constraint release Rouse model, but a detailed comparison reveals the existence of a broad distribution of the disentanglement rates, which is partly confirmed by an analysis of the packing and diffusion of the matrix chains in the tube region of the probe chains. A coarse-grained simulation model based on the tube Rouse motion model with incorporation of the probability distribution of the tube segment jump rates is developed and shows results qualitatively consistent with the fine scale molecular dynamics simulations. However, we observe a breakdown in the tube Rouse model when the short chain length is decreased to around N-S = 80, which is roughly 3.5 times the entanglement spacing N-e(P) = 23. The location of this transition may be sensitive to the chain bending potential used in our simulations.

Structural study of thin films prepared from tungstate glass matrix by Raman and X-ray absorption spectroscopy

Thin films were prepared using glass precursors obtained in the ternary system NaPO(3)-BaF(2)-WO(3) and the binary system NaPO(3)-WO(3) with high concentrations of WO(3) (above 40% molar). Vitreous samples have been used as a target to prepare thin films. Such films were deposited using the electron beam evaporation method onto soda-lime glass substrates. Several structural characterizations were performed by Raman spectroscopy and X-ray Absorption Near Edge Spectroscopy (XANES) at the tungsten L(I) and L(III) absorption edges. XANES investigations showed that tungsten atoms are only sixfold coordinated (octahedral WO(6)) and that these films are free of tungstate tetrahedral units (WO(4)). In addition, Raman spectroscopy allowed identifying a break in the linear phosphate chains as the amount of WO(3) increases and the formation of P-O-W bonds in the films network indicating the intermediary behavior of WO(6) octahedra in the film network. Based on XANES data, we suggested a new attribution of several Raman absorption bands which allowed identifying the presence of W-O and W=O terminal bonds and a progressive apparition of W-O-W bridging bonds for the most WO(3) concentrated samples (above 40% molar) attributed to the formation of WO(6) clusters. (C) 2008 Elsevier B.V. All rights reserved.

Novel fast random search clustering approach for mixing matrix identification in MIMO linear blind inverse problems with sparse inputs

In this paper we propose a novel fast random search clustering (RSC) algorithm for mixing matrix identification in multiple input multiple output (MIMO) linear blind inverse problems with sparse inputs. The proposed approach is based on the clustering of the observations around the directions given by the columns of the mixing matrix that occurs typically for sparse inputs. Exploiting this fact, the RSC algorithm proceeds by parameterizing the mixing matrix using hyperspherical coordinates, randomly selecting candidate basis vectors (i.e. clustering directions) from the observations, and accepting or rejecting them according to a binary hypothesis test based on the Neyman–Pearson criterion. The RSC algorithm is not tailored to any specific distribution for the sources, can deal with an arbitrary number of inputs and outputs (thus solving the difficult under-determined problem), and is applicable to both instantaneous and convolutive mixtures. Extensive simulations for synthetic and real data with different number of inputs and outputs, data size, sparsity factors of the inputs and signal to noise ratios confirm the good performance of the proposed approach under moderate/high signal to noise ratios. RESUMEN. Método de separación ciega de fuentes para señales dispersas basado en la identificación de la matriz de mezcla mediante técnicas de "clustering" aleatorio.

Mapping Binary Liquid-Vapor or Liquid-Liquid-Vapor Equilibria Regions, including the Different Azeotropic Behaviours, as a Function of the NRTL Binary Parameters

13th Mediterranean Congress of Chemical Engineering (Sociedad Española de Química Industrial e Ingeniería Química, Fira Barcelona, Expoquimia), Barcelona, September 30-October 3, 2014