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The simulation of rubber-like materials is usually based on hyperelasticity. If strain-rate dependency has to be considered viscous dampers also have to be taken into account in the rheological model. A disadvantage of such a description is time-consuming parameter identification associated with the damping constants. In this paper, a tabulated formulation is presented which allows the fast generation of input data based on uniaxial static and dynamic tensile tests at different strain rates. Unloading, i.e. forming a hysteresis loop, can also be modeled easily based on a damage formulation. We show the theoretical background and algorithmic setup of our model that has been implemented in the explicit finite element program LS-DYNA [1-3]. Apart from purely numerical examples, the validation of a soft and a hard rubber under loading and subsequent unloading at different strain rates is shown. [ABSTRACT FROM AUTHOR]

This contribution discusses the influence of different barrier update strategies on the performance and robustness of an interior point algorithm for single-crystal plasticity at small strains. To this end, single-crystal plasticity is first briefly presented in the framework of a primal-dual interior point algorithm to outline the general algorithmic structure. The manner in which the barrier parameter is modified within the interior point method, steering the penalization of constraints, plays a crucial role for the robustness and efficiency of the overall algorithm. In this paper, we compare and analyze different strategies in the framework of crystal plasticity. In a thorough analysis of a numerical example covering a broad range of settings in monocrystals, we investigate robust hyperparameter ranges and identify the most efficient and robust barrier parameter update strategies. [ABSTRACT FROM AUTHOR]

Selecting financial products is one of the most fundamental investment activities to both individuals and companies, and therefore it is very important to establish an efficient and practical method for financial products selection. To address the challenge of the complicated decision-making environment and decision makers' expression habits for the selection of financial products, this paper develops the incomplete additive probabilistic linguistic preference relation to depict decision makers' preferences. Considering that, when decision makers express their opinions using probabilistic linguistic preference relation, it is possible that the sum of the value of the probability information is more than 1, this paper also extends the concepts of probabilistic linguistic term set, additive probabilistic linguistic preference relation and incomplete additive probabilistic linguistic preference relation to improve and ensure their practicability. Moreover, an "inverse prospect theory-based" algorithm is proposed to choose proper financial products. The algorithm processes the original incomplete additive probabilistic linguistic preference relation by using the inverse functions of the prospect theory at first. Then, a priority weights deriving model is established based on the extended concepts. Finally, the numerical case and analysis is presented as the evidences to the conclusion that the proposed algorithm is practical and robust. [ABSTRACT FROM AUTHOR]

This paper which depended on the foundation of back strip method has established mathematic model to simulate stratum burial history, which considered the computation of stratum skeleton depth based on max depth and the equation-depth point on the procedure to recover stratum by stripping each layer, and put forward the enhanced restoration method taking layers group as studying object. Finally, the method has been applied to build the computer model and program automatic back strip algorithm successfully. Experiments have proved that the method is accurate, applicable, and extensible under the conditions of various complex strata. [ABSTRACT FROM AUTHOR]

In this paper, a novel zig-zag scan-based feedback convolution algorithm for image encryption against differential attacks is proposed. The two measures Number of Pixel Change Rate (NPCR) and Unified Average Changed Intensity (UACI) are commonly utilized for analyzing the differential attacks. From the study of the existing papers, even though high Number of Pixel Change Rate and Unified Average Changed Intensity values are obtained, a few values lie in the critical range of α-level significance which in turn increase the possibility of differential attacks. To overcome differential attacks, two aspects of scanning with different test cases are analyzed and from these analyses, it is concluded that zig-zag scan based feedback convolution in forward and reverse direction achieves good Number of Pixel Change Rate and Unified Average Changed Intensity without critical values. Zig-zag scan based feedback convolution in forward and reverse direction is enforced for key sequence generation and applied in diffusion process to achieve high level of security. Moreover, plain image related initial seed is also generated to overcome the chosen/known plain text attacks. Both numerical and theoretical analyses are performed to prove that the proposed encryption method is resistant to differential attacks. General security measures are carried out for the proposed method to validate its security level. From the simulations, it is shown that the proposed methodology has good keyspace, high key sensitivity, good randomness, and uniform distribution of cipher image pixels. [ABSTRACT FROM AUTHOR]

This paper proposes and evaluates a near admissible heuristic search strategy and its application to a kind of flexible manufacturing system (FMS) scheduling in a Petri net framework. Petri nets can concisely model the strict precedence constraint, multiple kinds of resources, and concurrent activities. To cope with the complexities for scheduling of FMS with alternative routings, this paper proposes an admissible heuristic function based on the execution of P-timed Petri nets and presents an improved dynamic weighting A* strategy using the proposed heuristic function. The search scheme does not need to predict the depth of solution in advance and the quality of the search result is also controllable. Some numerical experiments are carried out to demonstrate usefulness of the algorithm. [ABSTRACT FROM AUTHOR]

This paper discusses characteristics unique in the two-phase high-frequency-testing (HFT) environment in semiconductor manufacturing. We believe this paper is the first to define, formalize, and analyze the decision making problem associated with the two-phase HFT. Specifically, this paper defines the problem of minimizing the total HFT capacity usage by systematically finding the optimal number of preliminary HFT bin-1 chips subject to the main HFT, with the existence of the target service rate. We also propose a heuristic algorithm that exploits the special structure of the problem for efficiently obtaining a near-optimal solution. Finally, a numerical analysis and a case study have been conducted to gain more insights on the problem structure and the proposed algorithm. [ABSTRACT FROM AUTHOR]

This paper is concerned with mathematical and numerical analysis of the system of radiative integral transfer equations. The existence and uniqueness of solution to the integral system is proved by establishing the boundedness of the radiative integral operators and proving the invertibility of the operator matrix associated with the system. A collocation-boundary element method is developed to discretize the differential-integral system. For the non-convex geometries, an element-subdivision algorithm is developed to handle the computation of the integrals containing the visibility factor. An efficient iterative algorithm is proposed to solve the nonlinear discrete system and its convergence is also established. Numerical experiment results are also presented to verify the effectiveness and accuracy of the proposed method and algorithm. [ABSTRACT FROM AUTHOR]

In this paper, we attempt to introduce an algorithm which considers not only time factor but also cost, risk, and quality criteria to determine the critical path under fuzzy environment. In this algorithm first, decision makers allocate time, cost, risk, and quality to each activity. We are lacking in data and information, so in the proposed algorithm, the ratings of each activity and the weight of each criterion are described by fuzzy numbers and linguistic variables, which can be expressed in triangular fuzzy number. Linguistic variables are applied to represent the intensity of preferences of one criterion over another. Then, we add up triangular fuzzy numbers to determine the final evaluation value of each criterion for paths. Next, we use fuzzy TOPSIS, a technique for order preferences by similarity to an ideal solution, a method proposed by the authors in another paper, to choose the best alternative. Finally, numerical example is solved to illustrate the procedure of proposed method at the end of this paper. [ABSTRACT FROM AUTHOR]

The classical method for program analysis by abstract interpretation consists in computing first an increasing sequence using an extrapolation operation, called widening, to correctly approximate the limit of the sequence. Then, this approximation is improved by computing a decreasing sequence without widening, the terms of which are all correct, more and more precise approximations. It is generally admitted that, when the decreasing sequence reaches a fixpoint, it cannot be improved further. As a consequence, most efforts for improving the precision of an analysis have been devoted to improving the limit of the increasing sequence. In a previous paper, we proposed a method to improve a fixpoint after its computation. This method consists in computing from the obtained solution a new starting value from which increasing and decreasing sequences are computed again. The new starting value is obtained by projecting the solution onto well-chosen components. The present paper extends and improves the previous paper: the method is discussed in view of some example programs for which it fails. A new method is proposed to choose the restarting value: the restarting value is no longer a simple projection, but is built by gathering and combining information backward the widening nodes in the basic solution. Experiments show that the new method properly solves all our examples, and improves significantly the results obtained on a classical benchmark. [ABSTRACT FROM AUTHOR]

A novel algorithm for the control synthesis for nonlinear switched systems is presented in this paper. Based on an existing procedure of state-space bisection and made available for nonlinear systems with the help of guaranteed integration, the algorithm has been improved to be able to consider longer patterns of modes with a better pruning approach. Moreover, the use of guaranteed integration also permits to take bounded perturbations and varying parameters into account. It is particularly interesting for safety critical applications, such as in aeronautical, military or medical fields. The whole approach is entirely guaranteed and the induced controllers are correct-by-design. Some experimentations are performed to show the important gain of the new algorithm. [ABSTRACT FROM AUTHOR]

In this paper, we mainly study one class of convex mixed-integer nonlinear programming problems (MINLPs) with non-differentiable data. By dropping the differentiability assumption, we substitute gradients with subgradients obtained from KKT conditions, and use the outer approximation method to reformulate convex MINLP as one equivalent MILP master program. By solving a finite sequence of subproblems and relaxed MILP problems, we establish an outer approximation algorithm to find the optimal solution of this convex MINLP. The convergence of this algorithm is also presented. The work of this paper generalizes and extends the outer approximation method in the sense of dealing with convex MINLPs from differentiable case to non-differentiable one. [ABSTRACT FROM AUTHOR]

It has been pointed out by Jones D. R. that the DIRECT global optimization algorithm can quickly get close to the basin of the optimum but takes longer to achieve a high degree of accuracy. In this paper, we introduce a bilevel strategy into a modifed DIRECT algorithm to overcome this shortcoming. The proposed algorithm is proved to be convergent globally. Numerical results show that the proposed algorithm is very promising. [ABSTRACT FROM AUTHOR]

The multiple-sets split equality problem (MSSEP) requires finding a point x ∈∩Ni=1 Ci, y ∈∩Mj=1 Qj, such that Ax = By, where N and M are positive integers, {C1, C2,..., CN} and {Q1,Q2,...,QM} are closed convex subsets of Hilbert spaces H1, H2, respectively, and A : H1→H3, B : H2→H3 are two bounded linear operators. When N = M = 1, the MSSEP is called the split equality problem (SEP). If let B = I, then the MSSEP and SEP reduce to the well-known multiple-sets split feasibility problem (MSSFP) and split feasibility problem (SFP), respectively. Recently, some authors proposed many algorithms to solve the SEP and MSSEP. However, to implement these algorithms, one has to find the projection on the closed convex sets, which is not possible except in simple cases. One of the purposes of this paper is to study the SEP and MSSEP for a family of quasi-nonexpansive multi-valued mappings in the framework of infinite-dimensional Hilbert spaces, and propose an algorithm to solve the SEP and MSSEP without the need to compute the projection on the closed convex sets. [ABSTRACT FROM AUTHOR]

We consider the problem of tensor (i.e., multidimensional array) inpainting in this paper. By using higher-order singular value decomposition, we propose an iterative algorithm that performs soft thresholding on entries of the core tensor and then reconstructs via the directional orthogonal matrices. An inpainted tensor is obtained at the end of the iteration. Simulations conducted over color images, video frames, and MR images validate that the proposed algorithm is competitive with state-of-the-art completion algorithms. The evaluation is made in terms of quality metrics and visual comparison. [ABSTRACT FROM AUTHOR]

The maximum or minimum spanning tree problem is a classical combinatorial optimization problem. In this paper, we consider the partial inverse maximum spanning tree problem in which the weight function can only be decreased. Given a graph, an acyclic edge set, and an edge weight function, the goal of this problem is to decrease weights as little as possible such that there exists with respect to function containing the given edge set. If the given edge set has at least two edges, we show that this problem is APX-Hard. If the given edge set contains only one edge, we present a polynomial time algorithm. [ABSTRACT FROM AUTHOR]

Most of the traditional top- k algorithms are based on a single-server setting. They may be highly inefficient and/or cause huge communication overhead when applied to a distributed system environment. Therefore, the problem of top- k monitoring in distributed environments has been intensively investigated recently. This paper studies how to monitor the top- k data objects with the largest aggregate numeric values from distributed data streams within a fixed-size monitoring window W, while minimizing communication cost across the network. We propose a novel algorithm, which adaptively reallocates numeric values of data objects among distributed nodes by assigning revision factors when local constraints are violated and keeps the local top- k result at distributed nodes in line with the global top- k result. We also develop a framework that combines a distributed data stream monitoring architecture with a sliding window model. Based on this framework, extensive experiments are conducted on top of Apache Storm to verify the efficiency and scalability of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Spatial outlier detection is an important research problem that has received much attentions in recent years. Most existing approaches are designed for numerical attributes, but are not applicable to categorical ones (e.g., binary, ordinal, and nominal) that are popular in many applications. The main challenges are the modeling of spatial categorical dependency as well as the computational efficiency. This paper presents the first outlier detection framework for spatial categorical data. Specifically, a new metric, named as Pair Correlation Ratio (PCR), is measured for each pair of category sets based on their co-occurrence frequencies at specific spatial distance ranges. The relevances among spatial objects are then calculated using PCR values with regard to their spatial distances. The outlierness for each object is defined as the inverse of the average relevance between an object and its spatial neighbors. Those objects with the highest outlier scores are returned as spatial categorical outliers. A set of algorithms are further designed for single-attribute and multi-attribute spatial categorical datasets. Extensive experimental evaluations on both simulated and real datasets demonstrated the effectiveness and efficiency of our proposed approaches. [ABSTRACT FROM AUTHOR]

In this paper, we discuss the performance of the DIRECT global optimization algorithm on problems with linear scaling. We show with computations that the performance of DIRECT can be affected by linear scaling of the objective function. We also provide a theoretical result which shows that DIRECT does not perform well when the absolute value of the objective function is large enough. Then we present DIRECT-a, a modification of DIRECT, to eliminate the sensitivity to linear scaling of the objective function. We prove theoretically that linear scaling of the objective function does not affect the performance of DIRECT-a. Similarly, we prove that some modifications of DIRECT are also unaffected by linear scaling of the objective function, while the original DIRECT algorithm is sensitive to linear scaling. Numerical results in this paper show that DIRECT-a is more robust than the original DIRECT algorithm, which support the theoretical results. Numerical results also show that careful choices of the parameter ε can help DIRECT perform well when the objective function is poorly linearly scaled. [ABSTRACT FROM AUTHOR]

This paper focuses on the facility location problem with two conflicting objectives. We observe that minimization of the total cost of a particular echelon may lead to the increase in the total cost of a supply chain as a whole. Thus, these conflicting objectives are required to be met together from a supply chain perspective. We have solved the problem formulated in mixed nonlinear programming by a multi-objective evolutionary algorithm (MOEA) known as non-dominated sorting algorithm, or NSGA II in short. Numerical example is provided to show the effect of the algorithm on the solution. [ABSTRACT FROM AUTHOR]

The nonlinear complementarity problem (denoted by NCP( F)) can be reformulated as the solution of a nonsmooth system of equations. In this paper, we propose a new smoothing and regularization Newton method for solving nonlinear complementarity problem with P-function ( P-NCP). Without requiring strict complementarity assumption at the P-NCP solution, the proposed algorithm is proved to be convergent globally and superlinearly under suitable assumptions. Furthermore, the algorithm has local quadratic convergence under mild conditions. Numerical experiments indicate that the proposed method is quite effective. In addition, in this paper, the regularization parameter ε in our algorithm is viewed as an independent variable, hence, our algorithm seems to be simpler and more easily implemented compared to many previous methods. [ABSTRACT FROM AUTHOR]

Abstract  This paper addresses the problem of approximating a surface-to-surface intersection curve. Accurate computation of an intersection curve is not practical due to the degree explosion problem, when function decomposition is used, and fundamentally is not possible because of some computational reasons. Therefore, in practical applications, an approximate intersection curve with a low degree is extensively used. However, the approximation of an intersection curve needs to consider the topological and numerical aspects together to produce the approximate curve to be as close to the exact one as possible, since approximation inevitably involves both numerical and topological errors. In this paper, algorithms to compute an approximate intersection curve, which are topologically consistent and numerically accurate with the exact intersection curve, are presented. A set of sufficient conditions for an approximate curve to be topologically consistent with the exact one are provided, and the use of a validated ordinary differential equation solver is discussed. The approximate curve is then refined to reduce the error against the exact curve through optimization. The proposed method is demonstrated with examples. [ABSTRACT FROM AUTHOR]

In any machining fixture, the workpiece elastic deformation caused during machining influences the dimensional and form errors of the workpiece. Placing each locator and clamp in an optimal place can minimize the elastic deformation of the workpiece, which in turn minimizes the dimensional and form errors of the workpiece. Design of fixture configuration (layout) is a procedure to establish the workpiece–fixture contact through optimal positioning of clamping and locating elements. In this paper, an ant colony algorithm (ACA) based discrete and continuous optimization methods are applied for optimizing the machining fixture layout so that the workpiece elastic deformation is minimized. The finite element method (FEM) is used for determining the dynamic response of the workpiece caused due to machining and clamping forces. The dynamic response of the workpiece is simulated for all ACA runs. This paper proves that the ACA-based continuous fixture layout optimization method exhibits the better results than that of ACA-based discrete fixture layout optimization method. [ABSTRACT FROM AUTHOR]

The feasible implementation of signal processing techniques on hearing aids is constrained by the finite precision required to represent numbers and by the limited number of instructions per second to implement the algorithms on the digital signal processor the hearing aid is based on. This adversely limits the design of a neural network-based classifier embedded in the hearing aid. Aiming at helping the processor achieve accurate enough results, and in the effort of reducing the number of instructions per second, this paper focuses on exploring (1) the most appropriate quantization scheme and (2) the most adequate approximations for the activation function. The experimental work proves that the quantized, approximated, neural network-based classifier achieves the same efficiency as that reached by "exact" networks (without these approximations), but, this is the crucial point, with the added advantage of extremely reducing the computational cost on the digital signal processor. [ABSTRACT FROM AUTHOR]

The use of syndrome coding in steganographic schemes tends to reduce distortion during embedding. The more complete model comes from the wet papers (J. Fridrich et al., 2005) and allow to lock positions which cannot be modified. Recently, binary BCH codes have been investigated and seem to be good candidates in this context (D. Schönfeld and A. Winkler, 2006). Here, we show that Reed-Solomon codes are twice better with respect to the number of locked positions; in fact, they are optimal. First, a simple and efficient scheme based on Lagrange interpolation is provided to achieve the optimal number of locked positions. We also consider a new and more general problem, mixing wet papers (locked positions) and simple syndrome coding (low number of changes) in order to face not only passive but also active wardens. Using list decoding techniques, we propose an efficient algorithm that enables an adaptive tradeoff between the number of locked positions and the number of changes. [ABSTRACT FROM AUTHOR]

Modern constitutive models have the potential to improve the quality of engineering calculations involving non-linear anisotropic materials. The adoption of complex models in practice, however, depends on the availability of reliable and accurate solution methods for the stress point integration problem. This paper presents a modular implementation of explicit Runge–Kutta methods with error control, that is suitable for use, without change, with any rate-type constitutive model. The paper also shows how the complications caused by the algebraic constraint of conventional plasticity are resolved through a simple subloading modification. With this modification any rate-independent model can be implemented without difficulty, using the integration module as an accurate and robust standard procedure. The effectiveness and efficiency of the method are demonstrated through a comparative evaluation of second and fifth-order formulas, applied to a complex constitutive model for natural clay, full details of which are given. [ABSTRACT FROM AUTHOR]

Abstract  The existence of holes in meshes makes it difficult for mesh operations, especially when comes to model rebuilding, rapid prototyping and finite element analysis. Existing hole-filling algorithms are capable of filling holes on small and smooth regions of a model. For large holes with complex boundaries or in curved region, they may not result in satisfactory results. This paper proposes an algorithm which first split the holes into flatter ones and then split the complex holes based the concept of edge expansion. It incrementally splits a complex hole into simple ones by respecting the 3D shape of its boundary and the neighboring meshes, and then fills each resulting simple hole with planar triangulation. The proposed algorithm works well for a variety of complex holes and can better preserve the detailed features of the original mesh. [ABSTRACT FROM AUTHOR]

A sub-cycling integration algorithm (or named multi-time-steps integration algorithm), which has been successfully applied to FEM dynamical analysis, was firstly presented by Belytschko et al. (Comput Methods Appl Mech Eng 17/18:259–275, 1979). However, the problem of how to apply this type of algorithm to flexible multi-body dynamics (FMD) problems still lacks investigation up to now. Similar to the region-partitioning method used in FEM, this paper presents a central-difference-based sub-cycling integral method by decomposing the variables of an FMD equation into several groups and adopting different integral step sizes to each group of the variables. Based on the condensed form of an FMD equation, a group of common update formulae and a sub-step update formula, which constitute the sub-cycling together, are established in the paper. Furthermore, an implementation flowchart of the sub-cycling is presented. Stability of the sub-cycling will be analyzed and numerical examples will be performed to verify availability and precision of the sub-cycling in part II of the paper. [ABSTRACT FROM AUTHOR]

Numerical stability is an important issue for any integral procedure. Since sub-cycling algorithm has been presented by Belytschko et al. (Comput Methods Appl Mech Eng 17/18: 259–275, 1979), various kinds of these integral procedures were developed in later 20 years and their stability were widely studied. However, on how to apply the sub-cycling to flexible multi-body dynamics (FMD) is still a lack of investigation up to now. A particular sub-cycling algorithm for the FMD based on the central difference method was introduced in detail in part I (Miao et al. in Comp Mech doi: 10.1007/s00466-007-0183-9) of this paper. Adopting an integral approximation operator method, stability of the presented algorithm is transformed to a generalized eigenvalue problem in the paper and is discussed by solving the problem later. Numerical examples are performed to verify the availability and efficiency of the algorithm further. [ABSTRACT FROM AUTHOR]

This paper explores various aspects of the image decomposition problem using modern variational techniques. We aim at splitting an original image f into two components u and ρ, where u holds the geometrical information and ρ holds the textural information. The focus of this paper is to study different energy terms and functional spaces that suit various types of textures. Our modeling uses the total-variation energy for extracting the structural part and one of four of the following norms for the textural part: L 2, G, L 1 and a new tunable norm, suggested here for the first time, based on Gabor functions. Apart from the broad perspective and our suggestions when each model should be used, the paper contains three specific novelties: first we show that the correlation graph between u and ρ may serve as an efficient tool to select the splitting parameter, second we propose a new fast algorithm to solve the TV − L 1 minimization problem, and third we introduce the theory and design tools for the TV-Gabor model. [ABSTRACT FROM AUTHOR]

For a maximal monotone operatorT, a well-known overrelaxed point algorithm is often used to find the zeros ofT. In this paper, we enhance the algorithm to find a point in, whereis a given closed convex set. In the inexact case of our modified relaxed proximal point algorithm, we give a new criterion. The convergence analysis is quite easy to follow. [ABSTRACT FROM AUTHOR]

In this paper, a modified feasible semi-smooth asymptotically Newton method for nonlinear complementarity problems is proposed. The global convergence of the method and superlinear convergence are proved under some suitable assumptions. Numerical experiments are included to highlight the efficacy of the modified algorithm. [ABSTRACT FROM AUTHOR]

This paper proposes a stream selection algorithm to deal with the interference and increase the sum capacity in the context of heterogeneous networks where cells of different types coexist. Due to the different transmit powers between the macro and small cells, interference levels are also different. Since the small cells are densely deployed, fully connected interference network between small cells is considered in this paper. The proposed algorithm performs the selection of a stream sequence among a predetermined set of sequences. Those selected sequences are the ones that mostly contribute to the sum rate when performing the exhaustive search. As a consequence, since the search space is reduced, the complexity is significantly decreased. These stream sequences form a regular structure where the first stream is associated to a pico user. Another distinguishing property of the proposed approach is that the stream sequences include at least one stream for each user. When selecting the streams, the channel matrices of the unselected streams are projected orthogonally to the virtual transmit and virtual receive channels of the selected stream in order to align the interference in the null space of these virtual channels. The performance evaluations are carried out by considering different scenarios with different numbers and locations of pico cells. It is shown that the proposed method can significantly reduce the computational complexity while achieving a very close performance to the exhaustive search. [ABSTRACT FROM AUTHOR]

We study hedonic editing principles that aim to find individuals' maximum utility when confronted with multiple outcomes Thaler (Mark Sci 4:199–214, 1985). These principles have been primarily defined and studied for only two outcomes. However, when dealing with more than two outcomes, the principles become more ambiguous, and some of them may not continue to be valid. To address this, we present an algorithm designed to find the best solution over a partition set of a given vector of n outcomes. We demonstrate that this algorithm identifies the best-majorized vector for up to four outcomes and establish the conditions under which this vector is optimal for n outcomes. Our algorithm is fast since it requires at most n - 1 steps. We provide a detailed analysis of the algorithm's performance, characterizing the conditions that guarantee the optimal solution and identifying cases where the algorithm may not converge to the optimal solution. Nevertheless, in these cases, we demonstrate through numerical analysis that it can find the optimal solution with a high accuracy rate in most 'practical' instances, making it a reliable tool for solving hedonic editing problems. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to investigate the effect of individual arcs and nodes on the description of feasibility in an uncapacitated network. This is done by developing an iterative algorithm for finding all (necessary) Gale--Hoffman inequalities for the network. [ABSTRACT FROM AUTHOR]

This paper presents a method to find all intersections between curved lines such as structural line elements and finite element meshes with intentions to generate smaller, non-compatible, line cells (e.g. bar elements) between crossings. The intersection finding algorithm works for two and three-dimensional meshes constituted by linear, quadratic or higher order elements. Using the proposed algorithm, meshes can then be automatically prepared for finite element analyses with techniques for embedding elements within others or analyses that require lines within solids. The application of the method is demonstrated by a number of numerical examples illustrating its capabilities in handling complex geometries, relative speed and convenience. [ABSTRACT FROM AUTHOR]

An automated approach to quadrilateral mesh generation with complex internal geometric feature constraints is presented in this paper. It can deal with all kinds of feature constraints such as internal holes, constraint lines, constraint points, density lines and density points, etc., and satisfy special requirements of mesh generation for numerical analysis. The quadrilateral mesh is generated based on the looping algorithm. As the core of the algorithm, the new splitting criteria are put forward to improve the quality and efficiency of mesh generation. The method of dealing with feature constraints is proposed by considering constraint lines and points, density lines and density points as internal holes with zero area. The method for generating boundary elements is also introduced to improve the element quality around the boundary and feature constraints. For the situation in which feature constraints subdivide the domain into sub-domains, an automatic determination method of sub-domain boundaries is presented. An improved looping algorithm is presented for 3D surface meshing with feature constraints. The determination of proper splitting plane and the handling of feature constraints are put forward. The program of quadrilateral mesh generation has been developed based on the method presented in this paper and successfully applied to mesh generation in several engineering fields. [ABSTRACT FROM AUTHOR]

This paper defines the self-covariance property for the solutions of transferable utility cooperative games (TU-games) as a weakening of their covariance. Self-covariant solutions are positively homogenous and satisfy a "restricted" translation covariance so that feasible shifts are only the solution vectors themselves and their multipliers. A description of all non-empty, single-valued, efficient, anonymous, weakly and self-covariant solutions in the class of twoplayer TU-games is given. As demonstrated below, among them there exist just three solutions admitting consistent extensions in the Davis-Maschler sense. They are the equal share solution, the standard solution, and the constrained egalitarian solution for superadditive two-player TUgames. For the third solution mentioned, characterizations of some consistent extensions to the class of all TU-games are given. [ABSTRACT FROM AUTHOR]

In this paper, we introduce and analyze a general iterative algorithm for finding a common solution of a finite family of mixed equilibrium problems, a general system of generalized equilibria and a fixed point problem of nonexpansive mappings in a real Hilbert space. Under some appropriate conditions, we derive the strong convergence of the sequence generated by the proposed algorithm to a common solution, which also solves some optimization problem. The result presented in this paper improves and extends some corresponding ones in the earlier and recent literature. [ABSTRACT FROM AUTHOR]

Compressed sensing ensures the accurate reconstruction of sparse signals from far fewer samples than required in the classical Shannon-Nyquist theorem. In this paper, a generalized hard thresholding pursuit (GHTP) algorithm is presented that can recover unknown vectors without the sparsity level information. We also analyze the convergence of the proposed algorithm. Numerical experiments are given for synthetic and real-world data to illustrate the validity and the good performance of the proposed algorithm. [ABSTRACT FROM AUTHOR]

In this paper, we propose a new correction strategy for some first-order primal-dual algorithms arising from solving, e.g., total variation image restoration. With this strategy, we can prove the convergence of the algorithm under more flexible conditions than those proposed most recently. Some preliminary numerical results of image deblurring support that the new correction strategy can improve the numerical efficiency. [ABSTRACT FROM AUTHOR]

Geometric branch-and-bound methods are popular solution algorithms in deterministic global optimization to solve problems in small dimensions. The aim of this paper is to formulate a geometric branch-and-bound method for constrained global optimization problems which allows the use of arbitrary bounding operations. In particular, our main goal is to prove the convergence of the suggested method using the concept of the rate of convergence in geometric branch-and-bound methods as introduced in some recent publications. Furthermore, some efficient further discarding tests using necessary conditions for optimality are derived and illustrated numerically on an obnoxious facility location problem. [ABSTRACT FROM AUTHOR]

A typical interpolation strategy for line segments consists of a transition scheme, a Look-ahead ACC/DEC scheduling, and an interpolation algorithm. In these three parts, the main computation occurs in the first and second part. Some research work has been carried out to decrease the computation in the previous literatures, but these methods occupy a lot of computing resources for the optimization process during the calculation of transition curve parameters and feed rates. Consequently, the computational efficiency of interpolation strategy is greatly reduced. To deal with the issue, a real-time interpolation strategy is proposed in this paper. In the transition scheme, a Bézier curve is utilized to smooth the line segments. Based on the relationship among the approximation error, the approximation radius, and the transition curve, the curve can be directly generated when the approximation error is given. In the ACC/DEC scheduling, a 3-segment feed rate profile with jerk continuity is constructed. Meanwhile, a Look-ahead planning based on Backward Scanning and Forward Revision (BSFR) algorithm is utilized to eliminate redundant computation. Compared with Zhao’s and Shi’s strategy, the proposed strategy has the merits of C2 and G2 continuity for the tool path, jerk continuity for the tool movement, and distinguished real-time performance for interpolation. The experiments of 3D pentagram and 2D butterfly are carried out with different strategies and their results demonstrate that the interpolation efficiency can be greatly improved with the proposed strategy. [ABSTRACT FROM AUTHOR]

On the provable security of a block cipher against impossible differential cryptanalysis, the maximal length of impossible differentials is an essential aspect. Most previous work on finding impossible differentials for AES, omits the non-linear component (S-box), which is important for the security. In EUROCRYPT 2016, Sun et al. showed how to bound the length of impossible differentials of a SPN “structure” using the primitive index of its linear layer. They proved that there do not exist impossible differentials longer than four rounds for the AES “structure”, instead of the AES cipher. Since they do not consider the details of the S-box, their bound is not feasible for a concrete cipher. With their result, the upper bound of the length of impossible differentials for AES, is still unknown. We fill this gap in our paper. By revealing some important properties of the AES S-box, we further prove that even though the details of the S-box are considered, there do not exist truncated impossible differentials covering more than four rounds for AES, under the assumption that round keys are independent and uniformly random. Specially, even though the details of the S-box and key schedule are both considered, there do not exist truncated impossible differentials covering more than four rounds for AES-256. [ABSTRACT FROM AUTHOR]

Optical orthogonal signature pattern codes (OOSPCs) play an important role in a novel type of optical code division multiple access (OCDMA) network for 2-dimensional image transmission. There is a one-to-one correspondence between an (m,n,w,λ)-OOSPC and a (λ+1)-(mn, w, 1) packing design admitting a point-regular automorphism group isomorphic to Zm×Zn. In 2010, Sawa gave the first infinite class of (m, n, 4, 2)-OOSPCs by using S-cyclic Steiner quadruple systems. In this paper, we use various combinatorial designs such as strictly Zm×Zn-invariant s-fan designs, strictly Zm×Zn-invariant G-designs and rotational Steiner quadruple systems to present some constructions for (m, n, 4, 2)-OOSPCs. As a consequence, our new constructions yield more infinite families of optimal (m, n, 4, 2)-OOSPCs. Especially, we see that in some cases an optimal (m, n, 4, 2)-OOSPC can not achieve the Johnson bound. We also use Witt’s inversive planes to obtain optimal (p,p,p+1,2)-OOSPCs for all primes p≥3. [ABSTRACT FROM AUTHOR]

Let q be a power of a prime p, and let r=nk+1 be a prime such that r∤q, where n and k are positive integers. Under a simple condition on q, r and k, a Gauss period of type (n, k) is a normal element of Fqn over Fq; the complexity of the resulting normal basis of Fqn over Fq is denoted by C(n, k; p). Recent works determined C(n, k; p) for k≤7 and all qualified n and q. In this paper, we show that for any given k>0, C(n, k; p) is given by an explicit formula except for finitely many primes r=nk+1 and the exceptional primes are easily determined. Moreover, we describe an algorithm that allows one to compute C(n, k; p) for the exceptional primes r=nk+1. Our numerical results cover C(n, k; p) for k≤20 and all qualified n and q. [ABSTRACT FROM AUTHOR]

In this paper, we present a dynamic refinement algorithm for the smoothed particle Hydrodynamics (SPH) method. An SPH particle is refined by replacing it with smaller daughter particles, which positions are calculated by using a square pattern centered at the position of the refined particle. We determine both the optimal separation and the smoothing distance of the new particles such that the error produced by the refinement in the gradient of the kernel is small and possible numerical instabilities are reduced. We implemented the dynamic refinement procedure into two different models: one for free surface flows, and one for post-failure flow of non-cohesive soil. The results obtained for the test problems indicate that using the dynamic refinement procedure provides a good trade-off between the accuracy and the cost of the simulations. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to show that the iterative scheme recently studied by Xu (J Glob Optim 36(1):115-125, ) is the same as the one studied by Kamimura and Takahashi (J Approx Theory 106(2):226-240, ) and to give a supplement to these results. With the new technique proposed by Maingé (Comput Math Appl 59(1):74-79, ), we show that the convergence of the iterative scheme is established under another assumption. It is noted that if the computation error is zero or the approximate computation is exact, our new result is a genuine generalization of Xu's result and Kamimura-Takahashi's result. [ABSTRACT FROM AUTHOR]

In this paper we introduce a new smoothing function and show that it is coercive under suitable assumptions. Based on this new function, we propose a smoothing Newton method for solving the second-order cone complementarity problem (SOCCP). The proposed algorithm solves only one linear system of equations and performs only one line search at each iteration. It is shown that any accumulation point of the iteration sequence generated by the proposed algorithm is a solution to the SOCCP. Furthermore, we prove that the generated sequence is bounded if the solution set of the SOCCP is nonempty and bounded. Under the assumption of nonsingularity, we establish the local quadratic convergence of the algorithm without the strict complementarity condition. Numerical results indicate that the proposed algorithm is promising. [ABSTRACT FROM AUTHOR]

In this paper, we introduce and analyze a new hybrid extragradient-like iterative algorithm for finding a common solution of a generalized mixed equilibrium problem, a system of generalized equilibrium problems and a fixed point problem of infinitely many non expansive mappings. Under some mild conditions, we prove the strong convergence of the sequence generated by the proposed algorithm to a common solution of these three problems. Such solution also solves an optimization problem. Several special cases are also discussed. The results presented in this paper are the supplement, extension, improvement and generalization of the previously known results in this area. [ABSTRACT FROM AUTHOR]