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Recent rank-based attacks have reduced the security of Rainbow, which is one of the multi-layer UOV signatures, below the NIST security requirements by speeding up iterative kernel-finding operations using classical mathematics techniques. If quantum algorithms are applied to perform these iterative operations, the rank-based attacks may be more threatening to multi-layer UOV, including Rainbow. In this paper, we propose a quantum rectangular MinRank attack called the Q-rMinRank attack, the first quantum approach to key recovery attacks on multi-layer UOV signatures. Our attack is a general model applicable to multi-layer UOV signature schemes, and in this paper, we provide examples of its application to Rainbow and the Korean TTA standard, HiMQ. We design two quantum oracle circuits to find the kernel in consideration of the depth-width trade-off of quantum circuits. One is to reduce the width of the quantum circuits using qubits as a minimum, and the other is to reduce the depth using parallelization instead of using a lot of qubits. By designing quantum circuits to find kernels with fewer quantum resources and complexity by adding mathematical techniques, we achieve quadratic speedup for the MinRank attack to recover the private keys of multi-layer UOV signatures. We also estimate quantum resources for the designed quantum circuits and analyze quantum complexity based on them. The width-optimized circuit recovers the private keys of Rainbow parameter set V with only 1089 logical qubits. The depth-optimized circuit recovers the private keys of Rainbow parameter set V with a quantum complexity of 2 174 , which is lower than the complexity of 2 221 recovering the secret key of AES-192, which provides the same security level as parameter set III. [ABSTRACT FROM AUTHOR]

Traditional blood flow mapping algorithms are not effective enough when the region of interest contains the sources of artifacts. This paper examines the signatures of blood flow signals, as well as noise and artifact signals. Mathematical rules are proposed on the basis of these features to discriminate the blood flow signal from other signals, including the Doppler twinkling artifact. The diagnostic efficiency of the proposed decision rules is assessed using the previously collected database of raw ultrasound Doppler signals. The study results showed that taking account of the spatial stability of blood flow velocity can increase diagnostic efficiency to 91.6%. [ABSTRACT FROM AUTHOR]

Problems are often too complex to solve them in an optimal way. The complexity arises from connections between their elements, such that a change in one element influences the performance of other elements. Kauffman’s NK model offers a way to depict such interdependencies and has therefore often been used in economic investigations of the influence of problem or search decomposition on the attainable results. However, papers on the effect of different decompositions on solution quality come to contradictory conclusions. Some observe an initial advantage of over-modularization where others do not. As they also differ in the employed search procedures, but do not base them on empirical findings, the present paper examines the results of more empirically based search strategies. Using algorithms based on innovation strategies derived from patent data, the paper establishes a clear advantage of correct problem decompositions. [ABSTRACT FROM AUTHOR]

This paper provides results in the area of the analytical derivation of the efficient set of a mean-variance portfolio selection problem that has more than three criteria. By "analytical" we mean derived by formula as opposed to being computed by algorithm. By "more than three criteria", we mean that beyond the mean and variance of regular portfolio selection, the problems addressed have two or more additional linear objectives. The additional objectives might include sustainability, dividend yield, liquidity, and R&D as extra objectives like these are being seen with greater frequency. While not all multiple criteria portfolio selection problems lend themselves to an analytical derivation, a certain class does and the problems in this class are covered by the mathematics of this paper. [ABSTRACT FROM AUTHOR]

Origami, the ancient Japanese art of paper folding, is mathematically deeper than it looks. Delving into its complexities allows the construction of elaborate and useful structures from simple, flat templates. [ABSTRACT FROM AUTHOR]

Abstract The aim of this paper is to propose an algorithm based on the philosophy of the Variable Neighborhood Search (VNS) to solve Multi Depot Vehicle Routing Problems with Time Windows. The paper has two main contributions. First, from a technical point of view, it presents the first application of a VNS for this problem and several design issues of VNS algorithms are discussed. Second, from a problem oriented point of view the computational results show that the approach is competitive with an existing Tabu Search algorithm with respect to both solution quality and computation times. [ABSTRACT FROM AUTHOR]

This paper proposes an innovative statistical method to measure the impact of the class/school on student achievements in multiple subjects. We propose a semiparametric model for a bivariate response variable with random coefficients, that are assumed to follow a discrete distribution with an unknown number of support points, together with an Expectation-Maximization algorithm—called BSPEM algorithm—to estimate its parameters. In the case study, we apply the BSPEM algorithm to data about Italian middle schools, considering students nested within classes, and we identify subpopulations of classes, standing on their effects on student achievements in reading and mathematics. The proposed model is extremely informative in exploring the correlation between multiple class effects, which are typical of the educational production function. The estimated class effects on reading and mathematics student achievements are then explained in terms of various class and school level characteristics selected by means of a LASSO regression. [ABSTRACT FROM AUTHOR]

Tukey depth function is one of the most famous multivariate tools serving robust purposes. It is also very well known for its computability problems in dimensions $$p \ge 3$$ . In this paper, we address this computing issue by presenting two combinatorial algorithms. The first is naive and calculates the Tukey depth of a single point with complexity $$O\left( n^{p-1}\log (n)\right) $$ , while the second further utilizes the quasiconcave of the Tukey depth function and hence is more efficient than the first. Both require very minimal memory and run much faster than the existing ones. All experiments indicate that they compute the exact Tukey depth. [ABSTRACT FROM AUTHOR]

This paper presents a review of the current literature on the branch of multi-criteria decision modelling known as Goal Programming (GP). The result of our indepth investigations of the two main GP methods, lexicographic and weighted GP together with their distinct application areas is reported. Some guidelines to the scope of GP as an application tool are given and methods of determining which problem areas are best suited to the different GP approaches are proposed. The correlation between the method of assigning weights and priorities and the standard of the results is also ascertained. [ABSTRACT FROM AUTHOR]

Simulation and verification of numerically controlled (NC) manufacturing processes require efficient visualization and analysis of the swept volume generated by the motion of freeform NC tools along complex 3D paths. State-of-the-art methods are either based on approximation techniques (thus lacking the level of accuracy required in NC manufacturing) or are based on analytical solutions with high computational complexity, which are not suitable for real-time applications. In addition, until recently, modeling the self-intersection of a generated volume was thought to be obstructed by seemingly complex mathematics. This paper proposes solving the sweeping problem by using the sweep-envelope differential equation (SEDE). This method has advantages over other methods in terms of low computational complexity and high accuracy. Moreover, this method includes efficient tools for self-intersection detection and modeling. In this paper, we present an enhanced self-intersection algorithm and apply the SEDE algorithm on a ball-end cutter that is swept along non-intersecting and self-intersecting cutter paths. [ABSTRACT FROM AUTHOR]

Symbolic model checkers use BDDs to represent arithmetic constraints over bounded integer variables. The size of such BDDs can in the worst case be exponential in the number and size (in bits) of the integer variables. In this paper we show how to construct linear-sized BDDs for linear integer arithmetic constraints. We present basic constructions for atomic equality and inequality constraints and generalize our complexity results for arbitrary linear arithmetic formulas. We also present three alternative ways of handling out-of-bounds transitions and discuss heterogeneous bounds on integer variables. We experimentally compare our approach to other BDD-based symbolic model checkers and demonstrate that the algorithms presented in this paper can be used to improve their performance significantly. [ABSTRACT FROM AUTHOR]

In many applications of circuit design and synthesis, it is natural and in some instances essential to manipulate logic functions and model circuits using word-level representations and arithmetic operations in contrast to bit-level representations and logic operations. This paper reviews linear word-level structures and formulates their properties for combinational circuit modeling. The paper addresses the following problem: given a library of gates with their corresponding word-level representations such as linear arithmetic expressions or respective graph structures, find a word-level model of an arbitrary combinational circuit/netlist using that library of gates and minimizing memory allocation and time delay requirements. We present a comprehensive study on linearization assuming various circuit processing strategies. In particular, we develop a new approach to manipulate linear word-level representations by means of cascades. The practical applicability of linear structures and developed algorithms is strengthen by considering the problem of timing analysis. All this is supported by the experimental study on benchmark circuits. [ABSTRACT FROM AUTHOR]

The problem in this paper is motivated by physical problems concerned with the case when a class of continuous and equimeasurable densities of a string is given then how to find minimal frequencies among these given densities, that is, what kind of densities minimize the frequencies. By taking Dirichlet eigenvalues into account, given a certain weight function ω, we will show the minimizer of the mth eigenvalue is the m-degree continuous symmetrical decreasing rearrangement of ω. The main result of this paper can be viewed as complementary to Schwarz’s work (Schwarz in J. Math. Mech. 10:401-422, 1961). [ABSTRACT FROM AUTHOR]

In this paper, we consider the problem of fast and efficient indexing techniques for sequences evolving in non-Euclidean spaces. This problem has several applications in the areas of human activity analysis, where there is a need to perform fast search, and recognition in very high dimensional spaces. The problem is made more challenging when representations such as landmarks, contours, and human skeletons etc. are naturally studied in a non-Euclidean setting where even simple operations are much more computationally intensive than their Euclidean counterparts. We propose a geometry and data adaptive symbolic framework that is shown to enable the deployment of fast and accurate algorithms for activity recognition, dynamic texture recognition, motif discovery. Toward this end, we present generalizations of key concepts of piece-wise aggregation and symbolic approximation for the case of non-Euclidean manifolds. We show that one can replace expensive geodesic computations with much faster symbolic computations with little loss of accuracy in activity recognition and discovery applications. The framework is general enough to work across both Euclidean and non-Euclidean spaces, depending on appropriate feature representations without compromising on the ultra-low bandwidth, high speed and high accuracy. The proposed methods are ideally suited for real-time systems and low complexity scenarios. [ABSTRACT FROM AUTHOR]

The objective of this paper is analyzing to which extent the multiverse hypothesis provides a real explanation of the peculiarities of the laws and constants in our universe. First we argue in favor of the thesis that all multiverses except Tegmark's 'mathematical multiverse' are too small to explain the fine tuning, so that they merely shift the problem up one level. But the 'mathematical multiverse" is surely too large. To prove this assessment, we have performed a number of experiments with cellular automata of complex behavior, which can be considered as universes in the mathematical multiverse. The analogy between what happens in some automata (in particular Conway's 'Game of Life") and the real world is very strong. But if the results of our experiments can be extrapolated to our universe, we should expect to inhabit-in the context of the multiverse-a world in which at least some of the laws and constants of nature should show a certain time dependence. Actually, the probability of our existence in a world such as ours would be mathematically equal to zero. In consequence, the results presented in this paper can be considered as an inkling that the hypothesis of the multiverse, whatever its type, does not offer an adequate explanation for the peculiarities of the physical laws in our world. [ABSTRACT FROM AUTHOR]

Quaternary 1-generator quasi-cyclic codes are considered in the paper. Under the conditions that n is odd and gcd(|2|, m) = 1, where |2| denotes the order of 2 modulo n, we give the enumeration of quaternary 1-generator quasi-cyclic codes of length mn, and describe an algorithm which will obtain one, and only one, generator for each quaternary 1-generator quasi-cyclic code. [ABSTRACT FROM AUTHOR]

In this paper all cocyclic Hadamard matrices of order less than 40 are classified. That is, all such Hadamard matrices are explicitly constructed, up to Hadamard equivalence. This represents a significant extension and completion of work by de Launey and Ito. The theory of cocyclic development is discussed, and an algorithm for determining whether a given Hadamard matrix is cocyclic is described. Since all Hadamard matrices of order at most 28 have been classified, this algorithm suffices to classify cocyclic Hadamard matrices of order at most 28. Not even the total numbers of Hadamard matrices of orders 32 and 36 are known. Thus we use a different method to construct all cocyclic Hadamard matrices at these orders. A result of de Launey, Flannery and Horadam on the relationship between cocyclic Hadamard matrices and relative difference sets is used in the classification of cocyclic Hadamard matrices of orders 32 and 36. This is achieved through a complete enumeration and construction of (4 t, 2, 4 t, 2 t)-relative difference sets in the groups of orders 64 and 72. [ABSTRACT FROM AUTHOR]

This paper deals with downgrading the 1-median, i.e., changing values of parameters within certain bounds such that the optimal objective value of the location problem with respect to the new values is maximized. We suggest a game-theoretic view at this problem which leads to a characterization of an optimal solution. This approach is demonstrated by means of the Downgrading 1-median problem in the plane with Manhattan metric and implies an $\mathcal {O}(n\log^{2}n)$ time algorithm for this problem. [ABSTRACT FROM AUTHOR]

In this paper, we deepen the theoretical study of the geometric structure of a balanced complex polytope (b.c.p.), which is the generalization of a real centrally symmetric polytope to the complex space. We also propose a constructive algorithm for the representation of its facets in terms of their associated linear functionals. The b.c.p.s are used, for example, as a tool for the computation of the joint spectral radius of families of matrices. For the representation of real polytopes, there exist well-known algorithms such as, for example, the Beneath–Beyond method. Our purpose is to modify and adapt this method to the complex case by exploiting the geometric features of the b.c.p. However, due to the significant increase in the difficulty of the problem when passing from the real to the complex case, in this paper, we confine ourselves to examine the two-dimensional case. We also propose an algorithm for the computation of the norm the unit ball of which is a b.c.p. [ABSTRACT FROM AUTHOR]

In this paper, we introduce a supernode amalgamation algorithm which takes into account the characteristics of a hypermatrix data structure. The resulting frontal tree is then used to create a variable-sized partitioning of the hypermatrix. The sparse hypermatrix Cholesky factorization obtained runs slightly faster than the one which uses a fixed-sized partitioning. The algorithm also reduces data dependencies which limit exploitation of parallelism. [ABSTRACT FROM AUTHOR]

Given one instance of an $\mathcal{NP}$ -hard optimization problem, can we tell in advance whether it is exactly solvable or not? If it is not, can we predict which approximate algorithm is the best to solve it? Since the behavior of most approximate, randomized, and heuristic search algorithms for $\mathcal{NP}$ -hard problems is usually very difficult to characterize analytically, researchers have turned to experimental methods in order to answer these questions. In this paper we present a machine learning-based approach to address the above questions. Models induced from algorithmic performance data can represent the knowledge of how algorithmic performance depends on some easy-to-compute problem instance characteristics. Using these models, we can estimate approximately whether an input instance is exactly solvable or not. Furthermore, when it is classified as exactly unsolvable, we can select the best approximate algorithm for it among a list of candidates. In this paper we use the MPE (most probable explanation) problem in probabilistic inference as a case study to validate the proposed methodology. Our experimental results show that the machine learning-based algorithm selection system can integrate both exact and inexact algorithms and provide the best overall performance comparing to any single candidate algorithm. [ABSTRACT FROM AUTHOR]

In this paper, we present an algorithm which, for a given compact orientable irreducible boundary irreducible 3-manifold M, verifies whether M contains an essential orientable surface (possibly, with boundary), whose genus is at most N. The algorithm is based on Haken’s theory of normal surfaces, and on a trick suggested by Jaco and consisting in estimating the mean length of boundary curves in an unknown essential surface of a given genus in the given manifold. [ABSTRACT FROM AUTHOR]

In this paper, we consider algorithms for constructing n-terms approximations with nonnegative coefficients. The convergence theorem is proved for a “positive” analog of the Pure Greedy Algorithm. We establish a condition on the sequence of weakness coefficients which is sufficient for the convergence of the Positive Weak Greedy Algorithm. This condition is also necessary for the class of monotone sequences. [ABSTRACT FROM AUTHOR]

Consideration was given to control of a complex object whose motion obeys a multivariable nonlinear nonstationary mathematical model. Rigid constraints were imposed on the object’s dynamic precision. The paper considered computer-aided generation of the current equations of object motion with regard for the actuators which differ from subsystem to subsystem. The object is controlled adaptively with regard for the computer-based realization. The algorithms of control system operation that maintain the guaranteed precision of object motion were constructed. Conditions for problem solvability were formulated. The freeflying space robot was discussed by way of example. [ABSTRACT FROM AUTHOR]

Abstract  In this paper, we introduce and study a new system of generalized mixed quasi-variational inclusions with (H,η)-monotone operators which contains variational inequalities, variational inclusions, systems of variational inequalities and systems of variational inclusions in the literature as special cases. By using the resolvent technique for the (H,η)-monotone operators, we prove the existence of solutions and the convergence of some new p-step iterative algorithms for this system of generalized mixed quasi-variational inclusions and its special cases. The results in this paper unifies, extends and improves some known results in the literature. [ABSTRACT FROM AUTHOR]

Abstract In this paper, we present a new approach to model coupling that probably forms the methodological basis of a new generation of Integrated Assessment models. This approach respects the knowledge and expertise that is embodied in existing models and encourages their gradual evolution. Modularity is the guiding principle. Our approach is distinguished by the way modules are coupled which is based on an interplay of a job control module, a numerical coupling module, and a couple of stand-alone functional modules. The numerical coupling module - the core component - serves to treat the feedbacks between the functional modules. A first implemented example that couples an economic and a climate module by means of a two-phase meta-optimization is presented here. The algorithm and mathematical structure behind are discussed as well as important features such as convergence behavior and reliability. [ABSTRACT FROM AUTHOR]

3D elastoplastic frictional contact problems with orthotropic friction law belong to the unspecified boundary problems with nonlinearities in both material and geometric forms. One of the difficulties in solving the problem lies in the determination of the tangential slip states at the contact points. A great amount of computational efforts is needed so as to obtain high accuracy numerical results. Based on a combination of the well known mathematical programming method and iterative method, a finite element model is put forward in this paper. The problems are finally reduced to linear complementarity problems. A specially designed smoothing algorithm based on NCP-function is then applied for solving the problems. Numerical results are given to demonstrate the validity of the model and the algorithm proposed. [ABSTRACT FROM AUTHOR]

The research of medical image in the field of anti-counterfeiting and authentication plays a crucial role in the development of hospital digitization. In this paper, a new fragile medical watermarking scheme is proposed using the prime number distribution theorem, chaotic mapping, and Hash. Firstly, an approximate pixel set is constructed according to the distribution of prime numbers, and then the parity of the pixel value is re-granted with chaotic mapping, and Hash. The embedding and extraction of the watermark are done by using logical operations to adjust the pixel value according to the parity of the pixel value and the number of prime numbers contained in the pixel value. The experimental results demonstrate that the proposed scheme is imperceptible, efficient, and safe. Compared with the existing methods, the proposed scheme achieves the binding of medical image and patient information, as well as exhibits excellent detection and positioning capability, and will have good application prospects in medical image content authentication and tampering detection. [ABSTRACT FROM AUTHOR]

Due to recent advances in the development of linear programming solvers, some of the formerly considered difficult multicommodity problems can today be solved in few minutes, even faster than with specialized methods. However, for other kind of multicommodity instances, general linear solvers can still be quite inefficient. In this paper we will give an overview of the current state-of-the-art in solving large-scale multicommodity problems, comparing an specialized interior-point algorithm with CPLEX 6.5 in the solution of difficult multicommodity problems of up lo I million of variables and 300,000 constraints. [ABSTRACT FROM AUTHOR]

In this paper we consider the weighted minimax (1-center) location problem in the plane when the weights are not given but rather drawn from independent uniform distributions. The problem is formulated and analyzed. For certain parameters of the uniform distributions the objective function is proven to be convex and thus can be easily solved by standard software such as the Solver in Excel. Computational experience is reported. [ABSTRACT FROM AUTHOR]

Using the techniques of approximation and factorization of convolution operators we study the problem of irregular sampling of band-limited functions on a locally compact Abelian group G. The results of this paper relate to earlier work by Feichtinger and Gröchenig in a similar way as Kluvánek's work published in 1969 relates to the classical Shannon Sampling Theorem. Generally speaking we claim that reconstruction is possible as long as there is sufficient high sampling density. Moreover, the iterative reconstruction algorithms apply simultaneously to families of Banach spaces. [ABSTRACT FROM AUTHOR]

Effective design of parallel matrix multiplication algorithms relies on the consideration of many interdependent issues based on the underlying parallel machine or network upon which such algorithms will be implemented, as well as, the type of methodology utilized by an algorithm. In this paper, we determine the parallel complexity of multiplying two (not necessarily square) matrices on parallel distributed-memory machines and/or networks. In other words, we provided an achievable parallel run-time that can not be beaten by any algorithm (known or unknown) for solving this problem. In addition, any algorithm that claims to be optimal must attain this run-time. In order to obtain results that are general and useful throughout a span of machines, we base our results on the well-known LogP model. Furthermore, three important criteria must be considered in order to determine the running time of a parallel algorithm; namely, (i) local computational tasks, (ii) the initial data layout, and (iii) the communication schedule. We provide optimality results by first proving general lower bounds on parallel run-time. These lower bounds lead to significant insights on (i)–(iii) above. In particular, we present what types of data layouts and communication schedules are needed in order to obtain optimal run-times. We prove that no one data layout can achieve optimal running times for all cases. Instead, optimal layouts depend on the dimensions of each matrix, and on the number of processors. Lastly, optimal algorithms are provided. [ABSTRACT FROM AUTHOR]

Most writers on frequency assignment algorithms have described the details of a single algorithm, and evaluated the algorithm on selected data sets. There has been relatively little emphasis on describing the common features that are important if an algorithm is to have good performance. This paper describes the key features, with particular emphasis on algorithms for weighted fixed spectrum problems. The use of algorithms handling weighted constraints has become increasingly common in recent years. The advantages and disadvantages of weighting constraints are demonstrated. [ABSTRACT FROM AUTHOR]

The aim of this paper is to present an algorithm for finding a saddle point to the constrained minimax problem. The initial problem is transformed into an equivalent equality constrained problem, and then the interior point approach is used. To satisfy the original inequality constraints a logarithmic barrier function is used and special care is given to step size parameter to keep the variables within permitted boundaries. Numerical results illustrating the method are given. [ABSTRACT FROM AUTHOR]

This paper presents a new proof method about the paper (Yuan et al. in Appl. Math. Model. 47:811–825, 2017). In the proof, the global convergence of the Polak–Ribière–Polak algorithm is established without these two assumptions d k T g k < 0 and g k + 1 d k ≤ − σ 1 g k T d k which are needed in the above paper. This means that this paper has the same results under weaker conditions. More dimension functions for practical problems are tested to show the performance of the modified algorithm and the normal algorithm. An application of the fact engineering model is done to show the effectiveness of the given conjugate gradient algorithm. [ABSTRACT FROM AUTHOR]

In this paper, the uncapacitated facility location problem is considered, A tabu search algorithm for solving this problem is proposed. The algorithm is tested on some standard test problems taken from literature and its performance is compared with the known optimal solutions. Computational results show that the proposed algorithm produces optimal solutions for all test problems, and that it is very efficient in terms of time compared to existing algorithms in the literature. [ABSTRACT FROM AUTHOR]

This paper considers the problem of finding minimal length tree networks on the unit sphere Φ of a given point set (V) where distance is measured along great circular arcs. The related problems of finding a Steiner Minimal Tree SMT (V) and of finding a Minimum Spanning Tree MST(V) are treated through a simplicial decomposition technique based on computing the Delaunay Triangulation DT (V) and the Voronoi Diagram VD(V) of the given point set. O (N log N) algorithms for computing DT(V), VD(V), and WST(V) as well as an O(N log N) heuristic for finding a sub-optimal SMT(V) solution are presented, together with experimental results for randomly distributed points on Φ. [ABSTRACT FROM AUTHOR]

Economists have found a need to model agents who behave in ways that are not consistent with the traditional notions of rational behavior under uncertainty but that are oriented in some looser manner toward achieving ‘good’ outcomes. Adaptation over time in a myopic manner, rather that forward-looking optimization, has been proposed as one such model of behavior that displays bounded rationality. This paper investigates the relationship between adaptation as a model of behavior and as an algorithmic approach that has been used in computing solutions to optimization problems. It describes a specific adaptive model of behavior in discrete choice problems, one that is closely related to adaptive algorithms for optimization, and shows that this model can be fruitfully applied in studying several economic issues. [ABSTRACT FROM AUTHOR]

In this paper we study the point-objective problem of locating in R2 a facility serving a finite number of customers to minimize the travel time, or the distance, to each customer. Travel times, or distances, are measured by going in the directions of some given vectors which means that, under some conditions, are evaluated by a norm function. An algorithm is proposed to find all the quasi-efficient points and all the efficient points (alternately or strictly), for any given set of travelling directions. Consequently, the problem of efficiency is addressed in a general framework. [ABSTRACT FROM AUTHOR]

Mesh matching is an effective way to convert the non-conforming interfaces between two hexahedral meshes into conforming ones, which is very important for achieving high-quality finite element analysis. However, the existing mesh matching algorithm is neither efficient nor effective enough to handle complex interfaces and self-intersecting sheets. In this paper, the algorithm is improved in three aspects: (1) by introducing a more precise criteria for chord matching and the concept of partition chord set, complex interfaces with internal loops can be handled more effectively; (2) by proposing a new solution, self-intersecting sheet can be inflated and extracted locally; and (3) by putting forward a mesh quality evaluation method, the sheet extraction operation during mesh matching can be done more efficiently. Our improved mesh matching algorithm is fully automatic, and its effectiveness is demonstrated by several examples in different matching situations. [ABSTRACT FROM AUTHOR]

This paper presents a generalized version of the classic projective reconstruction theorem which helps to choose or assess depth constraints for projective depth estimation algorithms. The theorem shows that projective reconstruction is possible under a much weaker constraint than requiring all estimated projective depths to be nonzero. This result enables us to present classes of depth constraints under which any reconstruction of cameras and points projecting into given image points is projectively equivalent to the true camera-point configuration. It also completely specifies the possible wrong configurations allowed by other constraints. We demonstrate the application of the theorem by analysing several constraints used in the literature, as well as presenting new constraints with desirable properties. We mention some of the implications of our results on iterative depth estimation algorithms and projective reconstruction via rank minimization. Our theory is verified by running experiments on both synthetic and real data. [ABSTRACT FROM AUTHOR]

The coloring of disk graphs is motivated by the frequency assignment problem. In 1998, Malesińska et al. introduced double disk graphs as their generalization. They showed that the chromatic number of a double disk graph $$G$$ is at most $$33\,\omega (G) - 35$$ , where $$\omega (G)$$ denotes the size of a maximum clique in $$G$$ . Du et al. improved the upper bound to $$31\,\omega (G) - 1$$ . In this paper we decrease the bound substantially; namely we show that the chromatic number of $$G$$ is at most $$15\,\omega (G) - 14$$ . [ABSTRACT FROM AUTHOR]

In this paper we introduce an iterative algorithm for finding a common element of the fixed point set of an asymptotically strict pseudocontractive mapping S in the intermediate sense and the solution set of the minimization problem (MP) for a convex and continuously Frechet differentiable functional in Hilbert space. The iterative algorithm is based on several well-known methods including the extragradient method, CQ method, Mann-type iterative method and hybrid gradient projection algorithm with regularization. We obtain a strong convergence theorem for three sequences generated by our iterative algorithm. In addition, we also prove a new weak convergence theorem by a modified extragradient method with regularization for the MP and the mapping S. [ABSTRACT FROM AUTHOR]

In the paper,we study algebras having n bilinearmultiplication operations [InlineMediaObject not available: see fulltext.]: A× A → A, s = 1, ..., n, such that ( a[InlineMediaObject not available: see fulltext.] b) [InlineMediaObject not available: see fulltext.] c = a[InlineMediaObject not available: see fulltext.] ( b[InlineMediaObject not available: see fulltext.] c), s, r = 1,..., n, a, b, c ∈ A. The radical of such an algebra is defined as the intersection of the annihilators of irreducible A-modules, and it is proved that the radical coincides with the intersection of the maximal right ideals each of which is s-regular for some operation [InlineMediaObject not available: see fulltext.]. This implies that the quotient algebra by the radical is semisimple. If an n-tuple algebra is Artinian, then the radical is nilpotent, and the semisimple Artinian n-tuple algebra is the direct sum of two-sided ideals each of which is a simple algebra. Moreover, in terms of sandwich algebras, we describe a finite-dimensional n-tuple algebra A, over an algebraically closed field, which is a simple A-module. [ABSTRACT FROM AUTHOR]

The problem of enumerating and denumerating words generated by Dyck grammars arises in the work of compilers for high-level programming languages and a number of other applications. The present paper proposes an algorithm for the fast enumeration and denumeration of words of Dyck languages; the complexity of this algorithm per one symbol of enumerated words is O(log n log log n) bit operations, provided that the Schönhage-Strassen multiplication and division algorithmis used. The well-knownmethods applied earlier possess complexity O( n) per one symbol of enumerated words. The construction of the proposed algorithm is based on the Ryabko method. [ABSTRACT FROM AUTHOR]

In this paper we propose a novel message-passing algorithm, the so-called Action-GDL, as an extension to the generalized distributive law (GDL) to efficiently solve DCOPs. Action-GDL provides a unifying perspective of several dynamic programming DCOP algorithms that are based on GDL, such as DPOP and DCPOP algorithms. We empirically show how Action-GDL using a novel distributed post-processing heuristic can outperform DCPOP, and by extension DPOP, even when the latter uses the best arrangement provided by multiple state-of-the-art heuristics. [ABSTRACT FROM AUTHOR]

The matrix rank minimization problem has applications in many fields, such as system identification, optimal control, low-dimensional embedding, etc. As this problem is NP-hard in general, its convex relaxation, the nuclear norm minimization problem, is often solved instead. Recently, Ma, Goldfarb and Chen proposed a fixed-point continuation algorithm for solving the nuclear norm minimization problem ( Math. Program., doi:, ). By incorporating an approximate singular value decomposition technique in this algorithm, the solution to the matrix rank minimization problem is usually obtained. In this paper, we study the convergence/recoverability properties of the fixed-point continuation algorithm and its variants for matrix rank minimization. Heuristics for determining the rank of the matrix when its true rank is not known are also proposed. Some of these algorithms are closely related to greedy algorithms in compressed sensing. Numerical results for these algorithms for solving affinely constrained matrix rank minimization problems are reported. [ABSTRACT FROM AUTHOR]

In this paper, we present a novel method for constructing a super-optimal pairing with great efficiency, which we call the omega pairing. The computation of the omega pairing requires the simple final exponentiation and short loop length in Miller's algorithm which leads to a significant improvement over the previously known techniques on certain pairing-friendly curves. Experimental results show that the omega pairing is about 22% faster and 19% faster than the super-optimal pairing proposed by Scott at security level of AES 80 bits on certain pairing-friendly curves in affine coordinate systems and projective coordinate systems, respectively. [ABSTRACT FROM AUTHOR]

With the advent use of sophisticated and high-cost machines coupled with higher labor costs, concurrent optimization of machining process parameters and tolerance allocation plays a vital role in producing the parts economically. In this paper, an effort is made to concurrently optimize the manufacturing cost of piston and cylinder components by optimizing the operating parameters of the machining processes. Design of experiments (DoE) is adopted to investigate systematically the machining process parameters that influence product quality. In addition, tolerance plays a vital role in assembly of parts in manufacturing industries. For the selected piston and cylinder component, improvements efforts are made to reduce the total manufacturing cost of the components. By making use of central composite rotatable design method, a module of DoE, a mathematical model is developed for predicting the standard deviation of the tolerance achieved by grinding process. This mathematical model, which gives 93.3% accuracy, is used to calculate the quality loss cost. The intent of concurrent optimization problem is to minimize total manufacturing cost and quality loss function. Genetic algorithm is followed for optimizing the parameters. The results prove that there is a considerable reduction in manufacturing cost without violating the required tolerance, cutting force, and power. [ABSTRACT FROM AUTHOR]