On derivative-based global sensitivity criteria

A mathematical model f(x) given in the unit n-dimensional cube, where x = (x ₁, ..., x _n ), is considered. How can one estimate the global sensitivity of f(x) with respect to x _i ? If f(x) ∈ L ₂, global sensitivity indices help answer this question. Being less reliable, derivative-based sensitivity criteria are sometimes easier-to-compute. In this work, a new derivative-based global sensitivity criterion is compared to the respective global sensitivity index. These estimates are proven to coincide in the particular case when f(x) linearly depends on x _i . However, Monte Carlo approximations to the derivative-based criterion converge faster. Thus, the global derivative-based sensitivity criterion can prove useful when f(x) depends on x _i almost linearly. It can be also used to find nonessential variables x _i .     

An optimal adaptive stabilizing algorithm for two edge-disjoint paths problem

The problem of two edge-disjoint paths is to identify two paths \(Q_1\) and \(Q_2\) from source \(s \in V\) to target \(t \in V\) without any common arc in a directed connected graph \(G=(V, E)\). In this paper, we present an adaptive stabilizing algorithm for finding a pair of edge-disjoint paths from s to t in G in O(D) rounds with state-space complexity of \(O(log\; n)\) bits per process, where n is the number of nodes and D is the diameter of the graph. The proposed algorithm is optimal with respect to its time complexity, and the total length of the shortest paths. In addition, it can also be used to solve the problem for undirected graphs. Since the proposed algorithm is stabilizing, it does not require initialization and is capable of withstanding transient faults. We view a fault that perturbs the state of the system but not its program as a transient fault. In addition, the proposed algorithm is adaptive since it is capable of dealing with topology changes in the form of addition/removal of arcs and/or nodes as well as changes in the directions of arcs provided that two edge-disjoint paths between s and t exist after the topology change.     

A competitive study of the pseudoflow algorithm for the minimum <Emphasis Type="Italic">s</Emphasis>–<Emphasis Type="Italic">t</Emphasis> cut problem in vision applications

Rapid advances in image acquisition and storage technology underline the need for real-time algorithms that are capable of solving large-scale image processing and computer-vision problems. The minimum s–t cut problem, which is a classical combinatorial optimization problem, is a prominent building block in many vision and imaging algorithms such as video segmentation, co-segmentation, stereo vision, multi-view reconstruction, and surface fitting to name a few. That is why finding a real-time algorithm which optimally solves this problem is of great importance. In this paper, we introduce to computer vision the Hochbaum’s pseudoflow (HPF) algorithm, which optimally solves the minimum s–t cut problem. We compare the performance of HPF, in terms of execution times and memory utilization, with three leading published algorithms: (1) Goldberg’s and Tarjan’s Push-Relabel; (2) Boykov’s and Kolmogorov’s augmenting paths; and (3) Goldberg’s partial augment-relabel. While the common practice in computer-vision is to use either BK or PRF algorithms for solving the problem, our results demonstrate that, in general, HPF algorithm is more efficient and utilizes less memory than these three algorithms. This strongly suggests that HPF is a great option for many real-time computer-vision problems that require solving the minimum s–t cut problem.     

A measure of non-Gaussianity for quantum states

We propose a measure of non-Gaussianity for quantum states of a system of n oscillator modes. Our measure is based on the quasi-probability \({Q(\alpha),\alpha\in\mathcal{C}^n}\) . Since any measure of non-Gaussianity is necessarily an attempt at making a quantitative statement on the departure of the shape of the Q function from Gaussian, any good measure of non-Gaussianity should be invariant under transformations which do not alter the shape of the Q functions, namely displacements, passage through passive linear systems, and uniform scaling of all the phase space variables: Q(α) → λ²ⁿ Q(λα). Our measure which meets this ‘shape criterion’ is computed for a few families of states, and the results are contrasted with existing measures of non-Gaussianity. The shape criterion implies, in particular, that the non-Gaussianity of the photon-added thermal states should be independent of temperature.     

On resol vability of Steine r systems S( v = 2m, 4, 3) of rank r ≤ v − m + 1 o ve r $$\mathbb{F}_2 $$

Two new constructions of Steiner quadruple systems S(v, 4, 3) are given. Both preserve resolvability of the original Steiner system and make it possible to control the rank of the resulting system. It is proved that any Steiner system S(v = 2 ^m , 4, 3) of rank r ≤ v ? m + 1 over F₂ is resolvable and that all systems of this rank can be constructed in this way. Thus, we find the number of all different Steiner systems of rank r = v ? m + 1.     

Two-agent flowshop scheduling to maximize the weighted number of just-in-time jobs

We consider the scheduling problem in which two agents (agents A and B), each having its own job set (containing the A-jobs and B-jobs, respectively), compete to process their own jobs in a two-machine flowshop. Each agent wants to maximize a certain criterion depending on the completion times of its jobs only. Specifically, agent A desires to maximize either the weighted number of just-in-time (JIT) A-jobs that are completed exactly on their due dates or the maximum weight of the JIT A-jobs, while agent B wishes to maximize the weighted number of JIT B-jobs. Evidently four optimization problems can be formulated by treating the two agents’ criteria as objectives and constraints of the corresponding optimization problems. We focus on the problem of finding the Pareto-optimal schedules and present a bicriterion analysis of the problem. Solving this problem also solves the other three problems of bicriterion scheduling as a by-product. We show that the problems under consideration are either polynomially or pseudo-polynomially solvable. In addition, for each pseudo-polynomial-time solution algorithm, we show how to convert it into a two-dimensional fully polynomial-time approximation scheme for determining an approximate Pareto-optimal schedule. Finally, we conduct extensive numerical studies to evaluate the performance of the proposed algorithms.     

A parallel pattern for iterative stencil + reduce

We advocate the Loop-of-stencil-reduce pattern as a means of simplifying the implementation of data-parallel programs on heterogeneous multi-core platforms. Loop-of-stencil-reduce is general enough to subsume map, reduce, map-reduce, stencil, stencil-reduce, and, crucially, their usage in a loop in both data-parallel and streaming applications, or a combination of both. The pattern makes it possible to deploy a single stencil computation kernel on different GPUs. We discuss the implementation of Loop-of-stencil-reduce in FastFlow, a framework for the implementation of applications based on the parallel patterns. Experiments are presented to illustrate the use of Loop-of-stencil-reduce in developing data-parallel kernels running on heterogeneous systems.     

Average cost criterion induced by the regular utility function for continuous-time Markov decision processes

In this paper we study the average cost criterion induced by the regular utility function (U-average cost criterion) for continuous-time Markov decision processes. This criterion is a generalization of the risk-sensitive average cost and expected average cost criteria. We first introduce an auxiliary risk-sensitive first passage optimization problem and obtain the properties of the corresponding optimal value function under the slight conditions. Then we show that the pair of the optimal value functions of the risk-sensitive average cost criterion and the risk-sensitive first passage criterion is a solution to the optimality equation of the risk-sensitive average cost criterion allowing the risk-sensitivity parameter to take any nonzero value. Moreover, we have that the optimal value function of the risk-sensitive average cost criterion is continuous with respect to the risk-sensitivity parameter. Finally, we give the connections between the U-average cost criterion and the average cost criteria induced by the identity function and the exponential utility function, and prove the existence of a U-average optimal deterministic stationary policy in the class of all randomized Markov policies.     

Answering subgraph queries over massive disk resident graphs

Due to its wide applications, subgraph query has attracted lots of attentions in database community. In this paper, we focus on subgraph query over a single large graph G, i.e., finding all embeddings of query Q in G. Different from existing feature-based approaches, we map all edges into a two-dimensional space R ² and propose a bitmap structure to index R ². At run time, we find a set of adjacent edge pairs (AEP) or star-style patterns (SSP) to cover Q. We develop edge join (EJ) algorithms to address both AEP and SSP subqueries. Based on the bitmap index, our method can optimize I/O and CPU cost. More importantly, our index has the linear space complexity instead of exponential complexity in feature-based approaches, which indicates that our index can scale well with respect to large data size. Furthermore, our index has light maintenance overhead, which has not been considered in most of existing work. Extensive experiments show that our method significantly outperforms existing ones in both online and offline processing with respect to query response time, index building time, index size and index maintenance overhead.     

Nonparametric estimation of signal amplitude in white Gaussian noise

We assume that a transmitted signal is of the form S(t)f(t), where f(t) is a known function vanishing at some points of the observation interval and S(t) is a function of a known smoothness class. The signal is transmitted over a communication channel with additive white Gaussian noise of small intensity ?. For this model, we construct an estimator for S(t) which is optimal with respect to the rate of convergence of the risk to zero as ? → 0.     

On <Emphasis Type="Italic">L</Emphasis>-soft merotopies

The goal of this paper is to focus on the notions of merotopy and also merotopology in the soft universe. First of all, we propose L-soft merotopic (nearness) spaces and L-soft guild. Then, we study binary, contigual, regular merotopic spaces and also relations between them. We show that the category of binary L-soft nearness spaces is bireflective in the category of L-soft nearness spaces. Later, we define L-approach soft merotopological (nearness) spaces by giving several examples. Finally, we define a simpler characterization of L-approach soft grill merotopological space called grill-determined L-approach soft merotopological space. We investigate the categorical structures of these notions such as we prove that the category of grill-determined L-approach soft merotopological spaces is a topological category over the category of L-soft topological spaces. At the end, we define a partial order on the family of all L-approach soft grill merotopologies and show that this family is a completely distributive complete lattice with respect to the defined partial order.     

Generalized Preparata codes and 2-resolvable Steiner quadruple systems

We consider generalized Preparata codes with a noncommutative group operation. These codes are shown to induce new partitions of Hamming codes into cosets of these Preparata codes. The constructed partitions induce 2-resolvable Steiner quadruple systems S(n, 4, 3) (i.e., systems S(n, 4, 3) that can be partitioned into disjoint Steiner systems S(n, 4, 2)). The obtained partitions of systems S(n, 4, 3) into systems S(n, 4, 2) are not equivalent to such partitions previously known.     

A closed asynchronous dynamic model of cellular learning automata and its application to peer-to-peer networks

Cellular Learning Automata (CLAs) are hybrid models obtained from combination of Cellular Automata (CAs) and Learning Automata (LAs). These models can be either open or closed. In closed CLAs, the states of neighboring cells of each cell called local environment affect on the action selection process of the LA of that cell whereas in open CLAs, each cell, in addition to its local environment has an exclusive environment which is observed by the cell only and the global environment which can be observed by all the cells in CLA. In dynamic models of CLAs, one of their aspects such as structure, local rule or neighborhood radius may change during the evolution of the CLA. CLAs can also be classified as synchronous CLAs or asynchronous CLAs. In a synchronous CLA, all LAs in different cells are activated synchronously whereas in an asynchronous CLA, the LAs in different cells are activated asynchronously. In this paper, a new closed asynchronous dynamic model of CLA whose structure and the number of LAs in each cell may vary with time has been introduced. To show the potential of the proposed model, a landmark clustering algorithm for solving topology mismatch problem in unstructured peer-to-peer networks has been proposed. To evaluate the proposed algorithm, computer simulations have been conducted and then the results are compared with the results obtained for two existing algorithms for solving topology mismatch problem. It has been shown that the proposed algorithm is superior to the existing algorithms with respect to communication delay and average round-trip time between peers within clusters.     

One-Nonterminal Conjunctive Grammars over a Unary Alphabet

Systems of equations of the form X _i =φ _i (X ₁,…,X _n ) (1≤ i ≤ n) are considered, in which the unknowns are sets of natural numbers. Expressions φ _i may contain the operations of union, intersection and elementwise addition \(S+T=\{m+n\mid m\in S\), n∈T}. A system with an EXPTIME-complete least solution is constructed in the paper through a complete arithmetization of EXPTIME-completeness. At the same time, it is established that least solutions of all such systems are in EXPTIME. The general membership problem for these equations is proved to be EXPTIME-complete. Among the consequences of the result is EXPTIME-completeness of the compressed membership problem for conjunctive grammars.     

<Emphasis Type="Italic">k</Emphasis>-most suitable locations selection

Choosing the best location for starting a business or expanding an existing enterprize is an important issue. A number of location selection problems have been discussed in the literature. They often apply the Reverse Nearest Neighbor as the criterion for finding suitable locations. In this paper, we apply the Average Distance as the criterion and propose the so-called k-most suitable locations (k-MSL) selection problem. Given a positive integer k and three datasets: a set of customers, a set of existing facilities, and a set of potential locations. The k-MSL selection problem outputs k locations from the potential location set, such that the average distance between a customer and his nearest facility is minimized. In this paper, we formally define the k-MSL selection problem and show that it is NP-hard. We first propose a greedy algorithm which can quickly find an approximate result for users. Two exact algorithms are then proposed to find the optimal result. Several pruning rules are applied to increase computational efficiency. We evaluate the algorithms’ performance using both synthetic and real datasets. The results show that our algorithms are able to deal with the k-MSL selection problem efficiently.     

On polynomial solutions of the linear stationary control system

It is known that the controllable system x′ = Bx + Du, where the x is the n-dimensional vector, can be transferred from an arbitrary initial state x(0) = x ⁰ to an arbitrary finite state x(T) = x ^T by the control function u(t) in the form of the polynomial in degrees t. In this work, the minimum degree of the polynomial is revised: it is equal to 2p + 1, where the number (p ? 1) is a minimum number of matrices in the controllability matrix (Kalman criterion), whose rank is equal to n. A simpler and a more natural algorithm is obtained, which first brings to the discovery of coefficients of a certain polynomial from the system of algebraic equations with the Wronskian and then, with the aid of differentiation, to the construction of functions of state and control.     

<Emphasis Type="Italic">D</Emphasis>-decomposition technique state-of-the-art

It is a survey of recent extensions and new applications for the classical D-decomposition technique. We investigate the structure of the parameter space decomposition into root invariant regions for single-input single-output systems linear depending on the parameters. The D-decomposition for uncertain polynomials is considered as well as the problem of describing all stabilizing controllers of the certain structure (for instance, PID-controllers) that satisfy given H _∞-criterion. It is shown that the D-decomposition technique can be naturally linked with M-Δ framework (a general scheme for analysis of uncertain systems) and it is applicable for describing feasible sets for linear matrix inequalities. The problem of robust synthesis for linear systems can be also treated via D-decomposition technique.     

Exponential <Emphasis Type="Italic">H</Emphasis><Subscript>∞</Subscript> control for singular systems with time-varying delay

This paper studies the exponential admissibility and H _∞ control problems for a class of singular systems with time-varying delay in state. Firstly, an exponential admissibility criterion is obtained based on linear matrix inequalities (LMIs). It is worth mentioning that the derivative of the time-varying delay does not need to be smaller than one. Based on the proposed condition, a new delay-dependent H _∞ controller is also given, which guarantees the admissibility and the H _∞ performance γ. Numerical examples are given to illustrate the effectiveness of the proposed method.     

Partial and complete local diagnosis in computer systems with circulant structure

System diagnosis at multiple faults of multiplicity not greater than t is considered. The conditions when the state of each system module is only determined by the testing rusults of the physically connected modules (self-determination conditions) are analysed. The diagnosability conditions are established for the case when the self-determination conditions are not satisfied for any module. A new class of locally (t _r /t)-diagnosable systems is introduced, where t is the fault multiplicity and t _r is the multiplicity of faults at which the states of all system modules can be determined correctly and completely. The values of t _r are estimated. It is shown that the local t-diagnosability can be achieved by the system test redundancy.