Strongly Hamiltonian laceability of the even k-ary n-cube

The interconnection network considered in this paper is the k-ary n-cube that is an attractive variance of the well-known hypercube. Many interconnection networks can be viewed as the subclasses of the k-ary n-cubes include the cycle, the torus and the hypercube. A bipartite graph is Hamiltonian laceable if there exists a Hamiltonian path joining every two vertices which are in distinct partite sets. A bipartite graph G is strongly Hamiltonian laceable if it is Hamiltonian laceable and there exists a path of length N − 2 joining each pair of vertices in the same partite set, where N = |V(G)|. We prove that the k-ary n-cube is strongly Hamiltonian laceable for k is even and n  2.     

A sufficient condition for pancyclic graphs

In 2005, Rahman and Kaykobad proved that if G is a connected graph of order n such that d(x)+d(y)+d(x,y)n+1 for each pair x, y of distinct nonadjacent vertices in G, where d(x,y) is the length of a shortest path between x and y in G, then G has a Hamiltonian path [Inform. Process. Lett. 94 (2005) 37–41]. In 2006 Li proved that if G is a 2-connected graph of order n3 such that d(x)+d(y)+d(x,y)n+2 for each pair x,y of nonadjacent vertices in G, then G is pancyclic or G=K_n/2,n/2 where n4 is an even integer [Inform. Process. Lett. 98 (2006) 159–161]. In this work we prove that if G is a 2-connected graph of order n such that d(x)+d(y)+d(x,y)n+1 for all pairs x, y of distinct nonadjacent vertices in G, then G is pancyclic or G belongs to one of four specified families of graphs.     

Graph searching with advice

Fraigniaud et al. [L. Blin, P. Fraigniaud, N. Nisse, S. Vial, Distributing chasing of network intruders, in: 13th Colloquium on Structural Information and Communication Complexity, SIROCCO, in: LNCS, vol. 4056, Springer-Verlag, 2006, pp. 70–84] introduced a new measure of difficulty for a distributed task in a network. The smallest number of bits of advice   of a distributed problem is the smallest number of bits of information that has to be available to nodes in order to accomplish the task efficiently. Our paper deals with the number of bits of advice required to perform efficiently the graph searching problem in a distributed setting. In this variant of the problem, all searchers are initially placed at a particular node of the network. The aim of the team of searchers is to clear a contaminated graph in a monotone connected way, i.e., the cleared part of the graph is permanently connected, and never decreases while the search strategy is executed. Moreover, the clearing of the graph must be performed using the optimal number of searchers, i.e. the minimum number of searchers sufficient to clear the graph in a monotone connected way in a centralized setting. We show that the minimum number of bits of advice permitting the monotone connected and optimal clearing of a network in a distributed setting is Θ(nlogn)$\Theta (nlogn)$, where n$n$ is the number of nodes of the network. More precisely, we first provide a labelling of the vertices of any graph G$G$, using a total of O(nlogn)$O(nlogn)$ bits, and a protocol using this labelling that enables the optimal number of searchers to clear G$G$ in a monotone connected distributed way. Then, we show that this number of bits of advice is optimal: any distributed protocol requires Ω(nlogn)$\Omega (nlogn)$ bits of advice to clear a network in a monotone connected way, using an optimal number of searchers.     

The cost of monotonicity in distributed graph searching

Blin et al. (Theor Comput Sci 399(1–2):12–37, 2008) proposed a distributed protocol enabling the smallest possible number of searchers to clear any unknown graph in a decentralized manner. However, the strategy that is actually performed lacks of an important property, namely the monotonicity. This paper deals with the smallest number of searchers that are necessary and sufficient to monotonously clear any unknown graph in a decentralized manner. The clearing of the graph is required to be connected, i.e., the clear part of the graph must remain permanently connected, and monotone, i.e., the clear part of the graph only grows. We prove that a distributed protocol clearing any unknown n-node graph in a monotone connected way, in a decentralized setting, can achieve but cannot beat competitive ratio of Q(\fracnlogn){\Theta(\frac{n}{\log n})} , compared with the centralized minimum number of searchers. Moreover, our lower bound holds even in a synchronous setting, while our constructive upper bound holds even in an asynchronous setting.     

Effect of numerical integration on meshless methods

In this paper, we present the effect of numerical integration on meshless methods with shape functions that reproduce polynomials of degree k1. The meshless method was used on a second order Neumann problem and we derived an estimate for the energy norm of the error between the exact solution and the approximate solution from the meshless method under the presence of numerical integration. This estimate was obtained under the assumption that the numerical integration scheme satisfied a form of Green’s formula. We also indicated how to obtain numerical integration schemes satisfying this property.     

Kernel nonnegative matrix factorization for spectral EEG feature extraction

Nonnegative matrix factorization (NMF) seeks a decomposition of a nonnegative matrix X0 into a product of two nonnegative factor matrices U0 and V0, such that a discrepancy between X and UV is minimized. Assuming U=XW in the decomposition (for W0), kernel NMF (KNMF) is easily derived in the framework of least squares optimization. In this paper we make use of KNMF to extract discriminative spectral features from the time–frequency representation of electroencephalogram (EEG) data, which is an important task in EEG classification. Especially when KNMF with linear kernel is used, spectral features are easily computed by a matrix multiplication, while in the standard NMF multiplicative update should be performed repeatedly with the other factor matrix fixed, or the pseudo-inverse of a matrix is required. Moreover in KNMF with linear kernel, one can easily perform feature selection or data selection, because of its sparsity nature. Experiments on two EEG datasets in brain computer interface (BCI) competition indicate the useful behavior of our proposed methods.     

An optimal parallel algorithm for planar cycle separators

We present an optimal parallel algorithm for computing a cycle separator of ann-vertex embedded planar undirected graph inO(logn) time onn/logn processors. As a consequence, we also obtain an improved parallel algorithm for constructing a depth-first search tree rooted at any given vertex in a connected planar undirected graph in O(log² n) time on n/logn processors. The best previous algorithms for computing depth-first search trees and cycle separators achieved the same time complexities, but withn processors. Our algorithms run on a parallel random access machine that permits concurrent reads and concurrent writes in its shared memory and allows an arbitrary processor to succeed in case of a write conflict.A preliminary version of this paper appeared as Improved Parallel Depth-First Search in Undirected Planar Graphs in theProceedings of the Third Workshop on Algorithms and Data Structures, 1993, pp. 407–420.Supported in part by NSF Grant CCR-9101385.     

Searching among intervals and compact routing tables

Shortest paths in weighted directed graphs are considered within the context of compact routing tables. Strategies are given for organizing compact routing tables so that extracting a requested shortest path will takeo(k logn) time, wherek is the number of edges in the path andn is the number of vertices in the graph. The first strategy takesO (k+logn) time to extract a requested shortest path. A second strategy takes (k) time on average, assuming alln(n–1) shortest paths are equally likely to be requested. Both strategies introduce techniques for storing collections of disjoint intervals over the integers from 1 ton, so that identifying the interval within which a given integer falls can be performed quickly.This research was supported in part by the National Science Foundation under Grants CCR-9001241 and CCR-9322501 and by the Office of Naval Research under Contract N00014-86-K-0689.     

Bandwidth and pebbling

The main results of this paper establish relationships between the bandwidth of a graphG — which is the minimum over all layouts ofG in a line of the maximum distance between images of adjacent vertices ofG — and the ease of playing various pebble games onG. Three pebble games on graphs are considered: the well-known computational pebble game, the “progressive” (i.e., no recomputation allowed) version of the computational pebble game, both of which are played on directed acyclic graphs, and the quite different “breadth-first” pebble game, that is played on undirected graphs. We consider two costs of a play of a pebble game: the minimum number of pebbles needed to play the game on the graphG, and the maximumlifetime of any pebble in the game, i.e., the maximum number of moves that any pebble spends on the graph. The first set of results of the paper prove that the minimum lifetime cost of a play of either of the second two pebble games on a graphG is precisely the bandwidth ofG. The second set of results establish bounds on the pebble demand of all three pebble games in terms of the bandwidth of the graph being pebbled; for instance, the number of pebbles needed to pebble a graphG of bandwidthk is at most min (2k ²+k+1, 2k log₂|G|); and, in addition, there are bandwidth-k graphs that require 3k?1 pebbles. The third set of results relate the difficulty of deciding the cost of playing a pebble game on a given input graphG to the bandwidth ofG; for instance, the Pebble Demand problem forn-vertex graphs of bandwidthf(n) is in the class NSPACE (f(n) log² n); and the Optimal Lifetime Problem for either of the second two pebble games is NP-complete.     

Fast periodic graph exploration with constant memory

We consider the problem of periodic exploration of all nodes in undirected graphs by using a finite state automaton called later a robot. The robot, using a constant number of states (memory bits), must be able to explore any unknown anonymous graph. The nodes in the graph are neither labelled nor coloured. However, while visiting a node v the robot can distinguish between edges incident to it. The edges are ordered and labelled by consecutive integers 1,…,d(v) called port numbers, where d(v) is the degree of v. Periodic graph exploration requires that the automaton has to visit every node infinitely many times in a periodic manner. In this paper, we are interested in minimisation of the length of the exploration period. In other words, we want to minimise the maximum number of edge traversals performed by the robot between two consecutive visits of a generic node, in the same state and entering the node by the same port. Note that the problem is unsolvable if the local port numbers are set arbitrarily, see [L. Budach, Automata and labyrinths, Math. Nachr. 86 (1978) 195–282]. In this context, we are looking for the minimum function π(n), such that, there exists an efficient deterministic algorithm for setting the local port numbers allowing the robot to explore all graphs of size n along a traversal route with the period π(n). Dobrev et al. proved in [S. Dobrev, J. Jansson, K. Sadakane, W.-K. Sung, Finding short right-hand-on-the-wall walks in graphs, in: Proc. 12th Colloquium on Structural Information and Communication Complexity, SIROCCO 2005, in: Lecture Notes in Comput. Sci., vol. 3499, Springer, Berlin, 2005, pp. 127–139] that for oblivious robots π(n)10n. Recently Ilcinkas proposed another port labelling algorithm for robots equipped with two extra memory bits, see [D. Ilcinkas, Setting port numbers for fast graph exploration, in: Proc. 13th Colloquium on Structural Information and Communication Complexity, SIROCCO 2006, in: Lecture Notes in Comput. Sci., vol. 4056, Springer, Berlin, 2006, pp. 59–69], where the exploration period π(n)4n−2. In the same paper, it is conjectured that the bound 4n−O(1) is tight even if the use of larger memory is allowed. In this paper, we disprove this conjecture presenting an efficient deterministic algorithm arranging the port numbers, such that, the robot equipped with a constant number of bits is able to complete the traversal period in π(n)<3.75n−2 steps hence decreasing the existing upper bound. This reduces the gap with the lower bound of π(n)2n−2 holding for any robot.     

Improved bounds on sorting by length-weighted reversals

We study the problem of sorting binary sequences and permutations by length-weighted reversals. We consider a wide class of cost functions, namely f(ℓ)=ℓ^α for all α0, where ℓ is the length of the reversed subsequence. We present tight or nearly tight upper and lower bounds on the worst-case cost of sorting by reversals. Then we develop algorithms to approximate the optimal cost to sort a given input. Furthermore, we give polynomial-time algorithms to determine the optimal reversal sequence for a restricted but interesting class of sequences and cost functions. Our results have direct application in computational biology to the field of comparative genomics.     

Optimal horizons for a one-parameter family of unbiased FIR filters

In this paper, we find the optimal horizons and sampling intervals, both in the sense of the minimum mean square error (MSE), for a one-parameter family of the discrete-time unbiased finite impulse response (FIR) filters. On a horizon of N_l points in the nearest past, the FIR and the model k-state are represented with the l-degree and m-degree polynomials, respectively. The noise-free state space model is observed in the presence of zero-mean noise of an arbitrary distribution and covariance. The approach is based on the following. The FIR filter produces an unbiased estimate if lm. In order to reduce the noise, N_l needs to be increased. The model fits the increased horizon with a higher degree polynomial, m>l. Minimization of the mean square error for m>l gives the optimal horizon and sampling interval. Justification is provided for the global positioning system (GPS)-based measurements of the first state of a local crystal clock provided in the presence of uniformly distributed sawtooth noise induced by the GPS timing receiver.     

Backtracking Problem in the Traversal of an Unknown Directed Graph by a Finite Robot

A covering path in a directed graph is a path passing through all vertices and arcs of the graph, with each arc being traversed only in the direction of its orientation. A covering path exists for any initial vertex only if the graph is strongly connected. The traversal of an unknown graph implies that the topology of the graph is not a priori known, and we learn it only in the course of traversing the graph. This is similar to the problem of traversing a maze by a robot in the case where the plan of the maze is not available. If the robot is a general-purpose computer without any limitations on the number of its states, then traversal algorithms with the estimate O(nm) are known, where n is the number of vertices and m is the number of arcs. If the number of states is finite, then this robot is a finite automaton. Such a robot is an analogue of the Turing machine, where the tape is replaced by a graph and the cells are assigned to the graph vertices and arcs. The selection of the arc that has not been traversed yet among those originating from the current vertex is determined by the order of the outgoing arcs, which is a priori specified for each vertex. The best known traversal algorithms for a finite robot are based on constructing the output directed spanning tree of the graph with the root at the initial vertex and traversing it with the aim to find all untraversed arcs. In doing so, we face the backtracking problem, which consists in searching for all vertices of the tree in the order inverse to their natural partial ordering, i.e., from the leaves to the root. Therefore, the upper estimate of the algorithms is different from the optimal estimate O(nm) by the number of steps required for the backtracking along the outgoing tree. The best known estimate O(nm + n ²loglogn) has been suggested by the author in the previous paper [1]. In this paper, a finite robot is suggested that performs a backtracking with the estimate O(n ²log*(n)). The function log* is defined as an integer solution of the inequality 1 log₂ ^log*(n) < 2, where log ^t = log º log º ... º log (the superposition º is applied t – 1 times) is the tth compositional degree of the logarithm. The estimate O(nm + n ²log*(n)) for the covering path length is valid for any strongly connected graph for a certain (unfortunately, not arbitrary) order of the outgoing arcs. Interestingly, such an order of the arcs can be marked by symbols of the finite robot traversing the graph. Hence, there exists a robot that traverses the graph twice: first traversal with the estimate O(nm + n ²loglogn) and the second traversal with the estimate O(nm + n ²log*(n)).     

Primality testing with fewer random bits

In the usual formulations of the Miller-Rabin and Solovay-Strassen primality testing algorithms for a numbern, the algorithm chooses candidatesx ₁,x ₂, ...,x _k uniformly and independently at random from _n , and tests if any is a witness to the compositeness ofn. For either algorithm, the probabilty that it errs is at most 2^–k .In this paper, we study the error probabilities of these algorithms when the candidates are instead chosen asx, x+1, ..., x+k–1, wherex is chosen uniformly at random from _n . We prove that fork=[1/2log₂ n], the error probability of the Miller-Rabin test is no more thann ^–1/2+o(1), which improves on the boundn ^–1/4+o(1) previously obtained by Bach. We prove similar bounds for the Solovay-Strassen test, but they are not quite as strong; in particular, we only obtain a bound ofn ^–1/2+o(1) if the number of distinct prime factors ofn iso(logn/loglogn).     

Shortest noncrossing paths in plane graphs

Let G be an undirected plane graph with nonnegative edge length, and letk terminal pairs lie on two specified face boundaries. This paper presents an algorithm for findingk noncrossing paths inG, each connecting a terminal pair, and whose total length is minimum. Noncrossing paths may share common vertices or edges but do not cross each other in the plane. The algorithm runs in timeO(n logn) wheren is the number of vertices inG andk is an arbitrary integer.     

Connected component and simple polygon intersection searching

Efficient data structures are given for the following two query problems: (i) preprocess a setP of simple polygons with a total ofn edges, so that all polygons ofP intersected by a query segment can be reported efficiently, and (ii) preprocess a setS ofn segments, so that the connected components of the arrangement ofS intersected by a query segment can be reported quickly. In these problems we do not want to return the polygons or connected components explicitly (i.e., we do not wish to report the segments defining the polygon, or the segments lying in the connected components). Instead, we assume that the polygons (or connected components) are labeled and we just want to report their labels. We present data structures of sizeO(n ¹⁺) that can answer a query in timeO(n ¹⁺+k), wherek is the output size. If the edges ofP (or the segments inS) are orthogonal, the query time can be improved toO(logn+k) usingO(n logn) space. We also present data structures that can maintain the connected components as we insert new segments. For arbitrary segments the amortized update and query time areO(n ^1/2+) andO(n ^1/2++k), respectively, and the space used by the data structure isO(n ¹⁺. If we allowO(n ^4/3+ space, the amortized update and query time can be improved toO(n ^1/3+ andO(n ^1/3++k, respectively. For orthogonal segments the amortized update and query time areO(log² n) andO(log² n+klogn), and the space used by the data structure isO (n logn). Some other related results are also mentioned.Part of this work was done while the second author was visiting the first author on a grant by the Dutch Organization for Scientific Research (N.W.O.). The research of the second author was also supported by the ESPRIT Basic Research Action No. 3075 (project ALCOM). The research of the first author was supported by National Science Foundation Grant CCR-91-06514.     

Algorithms for dense graphs and networks on the random access computer

We improve upon the running time of several graph and network algorithms when applied to dense graphs. In particular, we show how to compute on a machine with word size = (logn) a maximal matching in ann-vertex bipartite graph in timeO(n ²+n ^2.5/)=O(n ^2.5/logn), how to compute the transitive closure of a digraph withn vertices andm edges in timeO(n ²+nm/), how to solve the uncapacitated transportation problem with integer costs in the range [O.C] and integer demands in the range [–U.U] in timeO ((n ³ (log log/logn)^1/2+n² logU) lognC), and how to solve the assignment problem with integer costs in the range [O.C] in timeO(n ^2.5 lognC/(logn/loglogn)^1/4).Assuming a suitably compressed input, we also show how to do depth-first and breadth-first search and how to compute strongly connected components and biconnected components in timeO(n+n ²/), and how to solve the single source shortest-path problem with integer costs in the range [O.C] in time0 (n ²(logC)/logn). For the transitive closure algorithm we also report on the experiences with an implementation.Most of this research was carried out while both authors worked at the Fachbereich Informatik, Universität des Saarlandes, Saarbrücken, Germany. The research was supported in part by ESPRIT Project No. 3075 ALCOM. The first author acknowledges support also from NSERC Grant No. OGPIN007.     

Visibility problems for orthogonal objects in two-or three-dimensions

LetP be a set ofl points in 3-space, and letF be a set ofm opaque rectangular faces in 3-space with sides parallel tox- ory-axis. We present anO(n logn) time andO(n) space algorithm for determining all points inP which are visible from a viewpoint at (0,0,), wheren=l+m. We also present anO(n logn+k) time andO(n) space algorithm for the hidden-line elimination problem for the orthogonal polyhedra together with a viewpoint at (0,0,), wheren is the number of vertices of the polyhedra andk is the number of edge intersections in the projection plane.     

Quality-based supplier selection and evaluation using fuzzy data

Since fuzzy quality data are ubiquitous in the real world, under this fuzzy environment, the supplier selection and evaluation on the basis of the quality criterion is proposed in this paper. The C_pk index has been the most popular one used to evaluate the quality of supplier’s products. Using fuzzy data collected from q2 possible suppliers’ products, fuzzy estimates of q suppliers’ capability indices are obtained according to the form of resolution identity that is a well-known theorem in fuzzy sets theory. Certain optimization problems are formulated and solved to obtain α-level sets for the purpose of constructing the membership functions of fuzzy estimates of C_pki. These membership functions are sorted by using a fuzzy ranking method to choose the preferable suppliers. Finally, a numerical example is illustrated to present the possible application by incorporating fuzzy data into the quality-based supplier selection and evaluation.     

The linear programming approach to the Randić index

Let G(k, n) be the set of simple graphs (i.e. without multiple edges or loops) that have n vertices and the minimum degree of vertices is k. The Randi? index of a graph G is: , where δ_u is the degree of vertex u and the summation extends over all edges (uv) of G. Using linear programming, we find the extremal graphs or give good bounds for this index when the number n_k of vertices of degree kis n?k+t, for 0tk and kn/2. We also prove that for n_kn?k, (kn/2) the minimum value of the Randi? index is attained for the graph .