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• Slope-assisted distributed fiber strain or temperature sensor is investigated. • Brillouin frequency shift estimated by different models is compared. • Slope-assisted method based on pseudo-Voigt model has highest accuracy. • A closed-form analytical solution for BFS is presented. • Proposed method can ensure high accuracy and enhance the dynamic range. To improve accuracy in temperature and strain measured by the slope-assisted distributed optical fiber sensor based on Brillouin scattering, the Lorentzian, Gaussian, pseudo-Voigt and Voigt models are used to approximate the measured Brillouin spectra. The results reveal that the pseudo-Voigt and Voigt profiles can give the better approximation than the other two profiles. In view of computational burden, a slope-assisted Brillouin frequency shift (BFS) estimation method based on the pseudo-Voigt model is proposed. To simplify BFS estimation in the slope-assisted method, by fitting the quartic function to the pseudo-Voigt profiles, a slope-assisted method based on the quartic function is proposed and a closed-form analytical solution for BFS is obtained in the method. The computer programs for the slope-assisted methods based on the line, Lorentzian, Gaussian, pseudo-Voigt models and quartic function are written and are used to estimate BFS for the measured Brillouin spectra with different pulse widths and average times along an optical fiber. The results reveal that the line model-based slope-assisted method has a narrow dynamic range. The Lorentzian, Gaussian models-based methods cannot always ensure its accuracy for Brillouin spectra measured in different situations. The method based on the pseudo-Voigt model possesses higher accuracy and wider dynamic range than the line, Lorentzian, Gaussian models-based ones. The quartic function-based slope-assisted method has almost the same accuracy as the pseudo-Voigt model-based one. [ABSTRACT FROM AUTHOR]

In this paper, a novel regularization method for image restoration and reconstruction is introduced which is accomplished by adopting a nonconvex nonsmooth penalty that depends on the eigenvalues of structure tensor of the underlying image. At first, an alternating minimization scheme is developed in which the problem can be decomposed into three subproblems, two of them are convex and the remaining one is smooth. Then, the convergence of the sequence which generate by the alternating minimization algorithm is proved. Finally, the efficient performance of the proposed method is demonstrated through experimental results for both grayscale and vector-value images. [ABSTRACT FROM AUTHOR]

The exponential random graph model (ERGM) has become a valuable tool for modeling social networks. In particular, ERGM provides great flexibility to account for both covariates effects on tie formations and endogenous network formation processes. However, there are both conceptual and computational issues for fitting ERGMs on big networks. This paper describes a framework and a series of methods (based on existent algorithms) to address these issues. It also outlines the advantages and disadvantages of the methods and the conditions to which they are most applicable. Selected methods are illustrated through examples. [ABSTRACT FROM AUTHOR]

Nonlinear dynamical system optimization problems exist in many scientific fields, ranging from computer vision to quantitative finance. In these problems, the underlying optimized parameters exhibit a certain degree of continuity, which can be formulated as a discrete sequence of nonlinear functions. Traditionally, such problems are either solved by ad-hoc algorithms or via independent optimization of the underlying functions. The former solutions are difficult to define and develop, requiring expertise in the field, while the latter approach does not take advantage of the inherent sequential properties of the functions. This paper presents a parallel spline-based algorithm for nonlinear optimization of function sequences, with emphasis on dataset sequences that represent dynamically evolving systems. The presented algorithm provides results that are more coherent with fewer evaluations than independent optimization of the sequence functions. We elaborate on the heuristic approach, the motivation behind using splines to model dynamical systems, and the various tiers of concurrency built into the algorithm. Furthermore, we present two distributed variants of the algorithm and compare their convergence with the serial version. The performance of the algorithm is demonstrated on benchmarks and real-world problems in audio signal decomposition, small angle X-ray scattering analysis, and video tracking of arbitrary objects. [ABSTRACT FROM AUTHOR]

Abstract: We prove a complexity dichotomy theorem for the most general form of Boolean #CSP where every constraint function takes values in the field of complex numbers . We first give a non-trivial tractable class of Boolean #CSP which was inspired by holographic reductions. The tractability crucially depends on algebraic cancelations which are absent for non-negative numbers. We then completely characterize all the tractable Boolean #CSP with complex-valued constraints and show that we have found all the tractable ones, and every remaining problem is #P-hard. We also improve our result by proving the same dichotomy theorem holds for Boolean #CSP with maximum degree 3 (every variable appears at most three times). The concept of Congruity and Semi-congruity provides a key insight and plays a decisive role in both the tractability and hardness proofs. We also introduce local holographic reductions as a technique in hardness proofs. [Copyright &y& Elsevier]

Abstract: We show that polynomial-time randomness (p-randomness) is preserved under a variety of familiar operations, including addition and multiplication by a nonzero polynomial-time computable real number. These results follow from a general theorem: If is an open interval, is a function, and is p-random, then is p-random provided [1.] f is p-computable on the dyadic rational points in I, and [2.] f varies sufficiently at r, i.e., there exists a real constant such that either or Our theorem implies in particular that any analytic function about a p-computable point whose power series has uniformly p-computable coefficients preserves p-randomness in its open interval of absolute convergence. Such functions include all the familiar functions from first-year calculus. [Copyright &y& Elsevier]

Abstract: The present article studies off-diagonal decay properties of Moore–Penrose pseudoinverses of (bi-infinite) matrices satisfying an analogous condition. Off-diagonal decay in our paper is considered with respect to specific index distance functions which incorporates those usually used for the study of localization properties for wavelet frames but also more general systems such as curvelets or shearlets. Our main result is that if a matrix satisfies an off-diagonal decay condition, then its Moore–Penrose pseudoinverse satisfies a similar condition. Applied to the study of frames this means that, if a wavelet, curvelet or shearlet frame is intrinsically localized, then its canonical dual is, too. [Copyright &y& Elsevier]

Abstract: This paper obtains explicit decomposition of threshold functions into bounded fan-in threshold functions. A small fan-in is important to satisfy technology constraints for large scale integration. By employing the concept of error in the threshold function, we are able to decompose functions in into a network of size and depth where n is the number of inputs of the function and M is the fan-in bound. The proposed construction enables one to trade-off the size and depth of the decomposition with the fan-in bound. Combined with the work on small weight threshold functions, this implies polynomial size, depth bounded fan-in decompositions for arbitrary threshold functions in . These results compare favorably with the classical decomposition which has a size and depth . We also show that the decomposition size and depth can be significantly reduced by exploiting the relationships between the input weights. As examples of this strategy, we demonstrate an size decomposition of the majority function and, size decompositions of an error tolerant pattern matching function and the comparison function. In all these examples, except for the first level, all other levels use only majority functions. [Copyright &y& Elsevier]

Abstract: Abstract interpretation techniques are used to derive a control-flow analysis for a simple higher-order functional language. The analysis approximates the interprocedural control-flow of both function calls and returns in the presence of first-class functions and tail-call optimization. In addition to an abstract environment, the analysis computes for each expression an abstract call-stack, effectively approximating where function calls return. The analysis is systematically derived by abstract interpretation of the stack-based abstract machine of Flanagan et al. using a series of Galois connections. We prove that the analysis is equivalent to an analysis obtained by first transforming the program into continuation-passing style and then performing control flow analysis of the transformed program. We then show how the analysis induces an equivalent constraint-based formulation, thereby providing a rational reconstruction of a constraint-based CFA from abstract interpretation principles. [Copyright &y& Elsevier]

Abstract: Contracts expressed by logic formulas allow one to formally specify expected behavior of programs. But writing such specifications manually takes a significant amount of work, in particular for uninteresting contracts which only aim at avoiding run-time errors during the execution. Thus, for programs of large size, it is desirable to at least partially infer such contracts. We propose a method to infer contracts expressed as boolean combinations of linear equalities and inequalities by combining different kinds of static analyses: abstract interpretation, weakest precondition computation and quantifier elimination. An important originality of our approach is to proceed modularly, considering subprograms independently. The practical applicability of our approach is demonstrated on experiments performed on a library and two benchmarks of vulnerabilities of C code. [Copyright &y& Elsevier]

Abstract: In this paper, we propose the notion of reducibility of symbols in term rewriting systems (TRSs). For a given algebraic specification, operation symbols can be classified on the basis of their denotations: the operation symbols for functions and those for constructors. In a model, each term constructed by using only constructors should denote an element, and functions are defined on sets formed by these elements. A term rewriting system provides operational semantics to an algebraic specification. Given a TRS, a term is called reducible if some rewrite rule can be applied to it. An irreducible term can be regarded as an answer in a sense. In this paper, we define the reducibility of operation symbols as follows: an operation symbol is reducible if any term containing the operation symbol is reducible. Non-trivial properties of context-sensitive rewriting, which is a simple restriction of rewriting, can be obtained by restricting the terms on the basis of variable occurrences, its sort, etc. We confirm the usefulness of the reducibility of operation symbols by applying them to behavioral specifications for proving the behavioral coherence property. [Copyright &y& Elsevier]

Cupric reducing antioxidant capacity (CUPRAC) method is one of the most widely used antioxidant methods. However, its need for a spectrophotometer, as in many other methods, is an important disadvantage. Cupric reducing antioxidant capacity was determined based on color analysis with Image J program in computer with the new method developed in this study and thus, use of spectrophotometer was eliminated. The new colorimetric CUPRAC assay was applied to various standard antioxidants and plant extracts. The reaction mixtures were dropped on TLC plate. The colors formed on TLC were transferred to the computer by using scanner images, and CTEAC value in μmol/L of each sample was determined with the image J program. The CTEAC values were compared with the TEAC values measured with the spectrometric method. A linear relationship was found between both (C)TEAC values of antioxidant standards (R2 = 0.991) and plant extracts (R2 = 0.994). Thus, the new method developed for the CUPRAC antioxidant assay can be easily performed in any environment without spectrophotometer device, and it is a low-cost method. • A new colorimetric CUPRAC antioxidant method was developed with using a scanner. • Low cost, simple and no spectrophotometer requirements are the advantages of the method. • The method is applicable to both single compounds and natural mixtures, e.g. plant extracts. • There is a strong correlation between the spectrophotometric and the new colorimetric CUPRAC methods. [ABSTRACT FROM AUTHOR]