Search

Abstract: The objective of this paper is to present an efficient hardware architecture for generalized Hebbian algorithm (GHA). In the architecture, the principal component computation and weight vector updating of the GHA are operated in parallel, so that the throughput of the circuit can be significantly enhanced. In addition, the weight vector updating process is separated into a number of stages for lowering area costs and increasing computational speed. To show the effectiveness of the circuit, a texture classification system based on the proposed architecture is designed. It is embedded in a system-on-programmable-chip (SOPC) platform for physical performance measurement. Experimental results show that the proposed architecture is an efficient design for attaining both high speed performance and low area costs. [Copyright &y& Elsevier]

Abstract: Hybrid strategy, which generalizes a specific single-label algorithm while one or two data decomposition tricks are applied implicitly or explicitly, has become an effective and efficient tool to design and implement various multi-label classification algorithms. In this paper, we extend traditional binary support vector machine by introducing an approximate ranking loss as its empirical loss term to build a novel support vector machine for multi-label classification, resulting into a quadratic programming problem with different upper bounds of variables to characterize label correlation of individual instance. Further, our optimization problem can be solved via combining one-versus-rest data decomposition trick with modified binary support vector machine, which dramatically reduces computational cost. Experimental study on ten multi-label data sets illustrates that our method is a powerful candidate for multi-label classification, compared with four state-of-the-art multi-label classification approaches. [Copyright &y& Elsevier]

Abstract: Multi-scale gist (MS-gist) feature manifold for building recognition is presented in the paper. It is described as a two-stage model. In the first stage, we extract the multi-scale gist features that represent the structural information of the building images. Since the MS-gist features are extrinsically high dimensional and intrinsically low dimensional, in the second stage, an enhanced fuzzy local maximal marginal embedding (EFLMME) algorithm is proposed to project MS-gist feature manifold to low-dimensional subspace. EFLMME aims to preserve local intra-class geometry and maximize local interclass margin separability of MS-gist feature manifold of different classes at the same time. To evaluate the performance of our proposed model, experiments were carried out on the Sheffield buildings database, compared with the existing works: (a) the visual gist based building recognition model (VGBR) and (b) the hierarchical building recognition model (HBR). Moreover, EFLMME is evaluated on Sheffield buildings database compared with some linear dimensionality reduction methods. The results show that the proposed model is superior to other models in practice of building recognition and can handle the building recognition problem caused by rotations, variant lighting conditions and occlusions very well. [Copyright &y& Elsevier]

Abstract: To address two problems, namely nonlinear problem and singularity problem, of linear discriminant analysis (LDA) approach in face recognition, this paper proposes a novel kernel machine-based rank-lifting regularized discriminant analysis (KRLRDA) method. A rank-lifting theorem is first proven using linear algebraic theory. Combining the rank-lifting strategy with three-to-one regularization technique, the complete regularized methodology is developed on the within-class scatter matrix. The proposed regularized scheme not only adjusts the projection directions but tunes their corresponding weights as well. Moreover, it is shown that the final regularized within-class scatter matrix approaches to the original one as the regularized parameter tends to zero. Two public available databases, namely FERET and CMU PIE face databases, are selected for evaluations. Compared with some existing kernel-based LDA methods, the proposed KRLRDA approach gives superior performance. [Copyright &y& Elsevier]

Abstract: In this paper we investigate two online scheduling problems. The first one is online scheduling on parallel machines with one machine periodically unavailable. The second problem is online scheduling on two uniform parallel machines where one machine is periodically unavailable. The online paradigm is that jobs arrive over list, i.e., when a job presents, we have to irrevocably assign it before the next one is seen. Preemption is not allowed. The objective is to minimize makespan. We suppose that the length of each available period is normalized to 1 and the length of each unavailable period is . For the first problem, we give an optimal algorithm with competitive ratio 2. For the second problem, we assume that the speed of the periodically unavailable machine is normalized to 1, while the speed of the other one is . In the case where , we design an algorithm and show that it is optimal with competitive ratio . Then we further give some lower bounds on competitive ratio in the case . We also study a special case and prove that algorithm proposed in Xu et al. (2009) is optimal with competitive ratio . [Copyright &y& Elsevier]

Abstract: The present paper considers the problem of partitioning a dataset into a known number of clusters using the sum of squared errors criterion (SSE). A new clustering method, called DE-KM, which combines differential evolution algorithm (DE) with the well known K-means procedure is described. In the method, the K-means algorithm is used to fine-tune each candidate solution obtained by mutation and crossover operators of DE. Additionally, a reordering procedure which allows the evolutionary algorithm to tackle the redundant representation problem is proposed. The performance of the DE-KM clustering method is compared to the performance of differential evolution, global K-means method, genetic K-means algorithm and two variants of the K-means algorithm. The experimental results show that if the number of clusters K is sufficiently large, DE-KM obtains solutions with lower SSE values than the other five algorithms. [Copyright &y& Elsevier]

Abstract: One critical problem in the operations of chemical processes is the occurrence of abnormal events. Therefore, an effective process monitoring methodology that can help detect, diagnose and predict abnormal events becomes potentially very useful. For the purpose of knowledge representation of chemical abnormality, a specified type of timed fuzzy Petri net (tFPN) approach is explicitly introduced in this paper. The dominant feature of tFPN metrics can be recognized from the fact that a timing factor is assigned to each transition, as well as a degree of reliability is associated with each place, which allows accurately representing the dynamic nature of fuzzy knowledge pertaining to abnormal events. Following a procedure towards abnormal event monitoring, two efficient algorithms in terms of abnormality prognostication and diagnosis are exploited by means of reachability analysis of tFPN. The benefits of derived techniques and solutions are illustrated through a case study consisting in a polypropylene reactor. [Copyright &y& Elsevier]

Abstract: Large amounts of high-dimensional data are distributed with the application of networks. Distributed clustering has become an increasingly important task due to variety of real-life constrains, including bandwidth and security aspects. Many distributed clustering algorithm have been proposed, but most of them have high transmission cost and poor clustering quality. In this paper, we propose a scalable local density-based distributed clustering algorithm which can easily fit high-dimensional data sets by this method such as density attractor distance and noise factor. In order to keep a lower transmission cost, we determine suitably low factor noises to send to the server. Furthermore, Test data sets, CMC data sets and KDD-CUP-99 are used for experimental evaluation to validate the performance practically. The experimental results and theoretical analysis show that the efficiency and quality for clustering of the proposed algorithm are superior to the other distributed clustering algorithm. [Copyright &y& Elsevier]

Abstract: This paper presents a novel approach to handle large amounts of geometric data. A data stream clustering is used to reduce the amount of data and build a hierarchy of clusters. The data stream concept allows for the processing of very large data sets. The cluster hierarchy is then used in a dynamic triangulation to create a multiresolution model. It allows for the interactive selection of a different level of detail in various parts of the data. A method for removal multiple points from Delaunay triangulation is proposed. It is significantly faster than the traditional approach. The clustering and the triangulation are supplemented by an elliptical metric to handle data with anisotropic properties. Compared to the closest competitive method by Isenburg et al., the presented algorithm requires only a single pass over the data and offers a high flexibility. These advantages culminate in a long running time. The method was tested on several large digital elevation maps. The clustering phase can take up to a few hours. Once the cluster hierarchy is built, the terrains can be efficiently manipulated in real time. [Copyright &y& Elsevier]

Abstract: Research on fine tuning stabilization properties has received attention for more than a decade. This paper presents probabilistic algorithms for fault containment. We demonstrate two exercises in fault containment in a weakly stabilizing system, which expedite recovery from single failures, and confine the effect of any single fault to the constant-distance neighborhood of the faulty process. The most significant aspect of the algorithms is that the fault gap, defined as the smallest interval after which the system is ready to handle the next single fault with the same efficiency, is independent of the network size. We argue that a small fault gap increases the availability of the fault-free system. [Copyright &y& Elsevier]

Abstract: In the -set agreement problem, each process (in a set of processes) proposes a value and has to decide a proposed value in such a way that at most different values are decided. While this problem can easily be solved in asynchronous systems prone to process crashes when , it cannot be solved when . For several years, the failure-detector-based approach has been investigated to circumvent this impossibility. While the weakest failure detector class to solve the -set agreement problem in read/write shared memory systems has recently been discovered (PODC 2009), the situation is different in message-passing systems where the weakest failure detector classes are known only for the extreme cases (consensus) and (set agreement). This paper presents four contributions whose aim is to help pave the way to discover the weakest failure detector class for -set agreement in message-passing systems. These contributions are the following. (a) The first is a new failure detector class, denoted , that is such that (the weakest class for ), and (the weakest class for ). (b) The second is an investigation of the structure of that shows that is the combination of two failure detector classes (that is new) and (they generalize the previous “quorums” and “eventual leaders” failure detector classes, respectively). (c) The third contribution concerns that is shown to be a necessary requirement (as far as information on failure is concerned) to solve the -set agreement problem in message-passing systems. (d) Finally, the last contribution is a -based algorithm that solves the -set agreement problem. This algorithm provides us with a new algorithmic insight on the way the -set agreement problem can be solved in asynchronous message-passing systems. It is hoped that these contributions will help discover the weakest failure detector class for -set agreement in message-passing systems. [Copyright &y& Elsevier]

Abstract: In this paper, we present algorithms that compute large matchings in planar graphs with fixed minimum degree. The algorithms give a guarantee on the size of the computed matching and run in linear time. Thus they are faster than the best known algorithm for computing maximum matchings in general graphs and in planar graphs, which run in and time, respectively. For the class of planar graphs with minimum degree 3, the bounds we achieve are known to be the best possible. Further, we discuss how minimum degree 5 can be used to obtain stronger bounds on the matching size. [Copyright &y& Elsevier]

Abstract: Frequent-itemset mining only considers the frequency of occurrence of the items but does not reflect any other factors, such as price or profit. Utility mining is an extension of frequent-itemset mining, considering cost, profit or other measures from user preference. Traditionally, the utility of an itemset is the summation of the utilities of the itemset in all the transactions regardless of its length. The average utility measure is thus adopted in this paper to reveal a better utility effect of combining several items than the original utility measure. It is defined as the total utility of an itemset divided by its number of items within it. The average-utility itemsets, as well as the original utility itemsets, does not have the “downward-closure” property. A mining algorithm is then proposed to efficiently find the high average-utility itemsets. It uses the summation of the maximal utility among the items in each transaction with the target itemset as the upper bound to overestimate the actual average utilities of the itemset and processes it in two phases. As expected, the mined high average-utility itemsets in the proposed way will be fewer than the high utility itemsets under the same threshold. The proposed approach can thus be executed under a larger threshold than the original, thus with a more significant and relevant criterion. Experimental results also show the performance of the proposed algorithm. [Copyright &y& Elsevier]

Abstract: Last few years have witnessed the development of various multi-objective evolutionary algorithms since they allow the generation of the overall Pareto front for multi-objective optimizations. With the problems in the real-world becoming more and more complex, however, no reported work in the literature focuses on the high-dimensional objective optimizations (HOPs). In this paper, we propose an evolutionary algorithm named HOEA (high-dimensional objective evolutionary algorithm) for HOPs. By adopting the concept of nonlinear definition for optimizing object, HOPs can be solved by HOEA, while the well-known multi-objective evolutionary algorithms work poorly on HOPs. We further analyze the nonlinear dynamic properties of HOEA on the basis of martingale theoretical framework. The theoretical results indicate that this new algorithm is indeed capable of achieving convergence. We also conduct experiments on HOEA with two representative test instances. The experimental results either confirm our theoretical results or show that the proposed algorithm is efficient and effective for HOPs. [Copyright &y& Elsevier]

Abstract: The support vector clustering (SVC) algorithm consists of two main phases: SVC training and cluster assignment. The former requires calculating Lagrange multipliers and the latter requires calculating adjacency matrix, which may cause a high computational burden for cluster analysis. To overcome these difficulties, in this paper, we present an improved SVC algorithm. In SVC training phase, an entropy-based algorithm for the problem of calculating Lagrange multipliers is proposed by means of Lagrangian duality and the Jaynes’ maximum entropy principle, which evidently reduces the time of calculating Lagrange multipliers. In cluster assignment phase, the kernel matrix is used to preliminarily classify the data points before calculating adjacency matrix, which effectively reduces the computing scale of adjacency matrix. As a result, a lot of computational savings can be achieved in the improved algorithm by exploiting the special structure in SVC problem. Validity and performance of the proposed algorithm are demonstrated by numerical experiments. [Copyright &y& Elsevier]

Abstract: Numerous privacy-preserving data publishing algorithms were proposed to achieve privacy guarantees such as . Many of them, however, were recently found to be vulnerable to algorithm-based disclosure—i.e., privacy leakage incurred by an adversary who is aware of the privacy-preserving algorithm being used. This paper describes generic techniques for correcting the design of existing privacy-preserving data publishing algorithms to eliminate algorithm-based disclosure. We first show that algorithm-based disclosure is more prevalent and serious than previously studied. Then, we strictly define Algorithm-SAfe Publishing (ASAP) to capture and eliminate threats from algorithm-based disclosure. To correct the problems of existing data publishing algorithms, we propose two generic tools to be integrated in their design: global look-ahead and local look-ahead. To enhance data utility, we propose another generic tool called stratified pick-up. We demonstrate the effectiveness of our tools by applying them to several popular algorithms: Mondrian, Hilb, and MASK. We conduct extensive experiments to demonstrate the effectiveness of our tools in terms of data utility and efficiency. [Copyright &y& Elsevier]

Abstract: This paper presents selective regeneration particle swarm optimization (SRPSO), a novel algorithm developed based on particle swarm optimization (PSO). It contains two new features, unbalanced parameter setting and particle regeneration operation. The unbalanced parameter setting enables fast convergence of the algorithm and the particle regeneration operation allows the search to escape from local optima and explore for better solutions. This algorithm is applied to data clustering problems for performance evaluation and a hybrid algorithm (KSRPSO) of K-means clustering method and SRPSO is developed. In the conducted numerical experiments, SRPSO and KSRPSO are compared to the original PSO algorithm, K-means, as well as, other methods proposed by other studies. The results demonstrate that SRPSO and KSRPSO are efficient, accurate, and robust methods for data clustering problems. [Copyright &y& Elsevier]

Abstract: Mining useful information and helpful knowledge from large databases has evolved into an important research area in recent years. Among the classes of knowledge derived, finding sequential patterns in temporal transaction databases is very important since it can help model customer behavior. In the past, researchers usually assumed databases were static to simplify data-mining problems. In real-world applications, new transactions may be added into databases frequently. Designing an efficient and effective mining algorithm that can maintain sequential patterns as a database grows is thus important. In this paper, we propose a novel incremental mining algorithm for maintaining sequential patterns based on the concept of pre-large sequences to reduce the need for rescanning original databases. Pre-large sequences are defined by a lower support threshold and an upper support threshold that act as gaps to avoid the movements of sequences directly from large to small and vice versa. The proposed algorithm does not require rescanning original databases until the accumulative amount of newly added customer sequences exceeds a safety bound, which depends on database size. Thus, as databases grow larger, the numbers of new transactions allowed before database rescanning is required also grow. The proposed approach thus becomes increasingly efficient as databases grow. [Copyright &y& Elsevier]

Abstract: This paper presents an error detection methodology to enable fault detection inspired on recent immune theory. The fault detection problem is a challenging problem due to processes increasing complexity and agility necessary to avoid malfunction or accidents. The key challenge is determining the difference between normal and potential harmful activities. A promising solution is emerging in the form of Artificial Immune System (AIS). In this article, Natural Killer (NK) immune cells mechanisms inspired an AIS. The AIS proposed uses recent biological mechanism such as: NK activation and education machinery. DAMADICS benchmark was applied to compare the proposed AIS performance to others fault detection algorithms. The results show that the novel approach developed provides better detection rate and false alarms tradeoff when compared to other methods in literature. [Copyright &y& Elsevier]

Abstract: The differential evolution (DE) is a global optimization algorithm to solve numerical optimization problems. Recently the quantum-inquired differential evolution (QDE) has been proposed for binary optimization. This paper proposes DE/QDE to learn the Takagi–Sugeno (T–S) fuzzy model. DE/QDE can simultaneously optimize the structure and the parameters of the model. Moreover a new encoding scheme is given to allow DE/QDE to be easily performed. The two benchmark problems are used to validate the performance of DE/QDE. Compared to some existing methods, DE/QDE shows the competitive performance in terms of accuracy. [Copyright &y& Elsevier]

Abstract: Let be a connected graph with vertices. Let be an integer. Suppose that a fire breaks out at a vertex of . A firefighter starts to protect vertices. At each time interval, the firefighter protects -vertices not yet on fire. At the end of each time interval, the fire spreads to all the unprotected vertices that have a neighbour on fire. Let sn denote the maximum number of vertices in that the firefighter can save when a fire breaks out at vertex . The -surviving rate of is defined to be , which is the average proportion of saved vertices. In this paper, we investigate the surviving rate of outerplanar graphs with vertices. The main results are as follows: (1) ; and (2) if , and if , which improves the result in [L.Cai, W.Wang, The surviving rate of a graph for the firefighter problem, SIAM J. Discrete Math. 23 (2009) 1814–1826]. [ABSTRACT FROM AUTHOR]

Abstract: Text steam analysis is now of great importance and practical value today. It has several applications such as news group filtering, topic detection & tracking (TDT), user characterized recommendation etc. Clustering is one of the most important methods of analyzing text stream. However, most text stream clustering algorithms rarely consider the possible change of features during a long-time of clustering, which is usually the case, leading to unsatisfactory results of the clustering system. The paper mainly focuses on the problem of adaptive feature selection for clustering text stream. A validity index based method of adaptive feature selection is proposed, incorporating with which a new text stream clustering algorithm is developed. During the clustering process, threshold of cluster valid index is used to automatically trigger feature re-selection in order to ensure the validity of clustering. The experiment using Reuters-21578 text set as the text source shows that the clustering algorithm reaches reasonable results of high quality. [ABSTRACT FROM AUTHOR]

Abstract: Geometric routing by using virtual locations is an elegant way for solving network routing problems. In its simplest form, greedy routing, a message is simply forwarded to a neighbor that is closer to the destination. One main drawback of this approach is that the coordinates of the virtual locations require bits to represent, which makes this scheme infeasible in some applications. The essence of the geometric routing is the following: When an origin vertex wants to send a message to a destination vertex , it forwards the message to a neighbor , solely based on the location information of and all neighbors of . In the greedy routing scheme, the decision is based on decreasing distance. For this idea to work, however, the decision needs not be based on decreasing distance. As long as the decision is made locally, this scheme will work fine. In this paper, we introduce a version of greedy routing which we call generalized greedy routing algorithm. Instead of relying on decreasing distance, a generalized greedy routing algorithm uses other criteria to determine routing paths, solely based on local information. We present simple generalized greedy routing algorithms based on -coordinates (consisting of two integers between 0 and ), which are derived from an -orientation of a 2-connected plane graph. We also generalize this result to arbitrary trees. Both algorithms are natural and simple to be implemented. [Copyright &y& Elsevier]

Abstract: There is no known algorithm that solves the general case of the approximate edit distance problem, where the edit operations are insertion, deletion, mismatch, and swap, in time , where is the length of the text and is the length of the pattern. In the effort to study this problem, the edit operations have been analyzed independently. Karloff  showed an algorithm that approximates the edit distance problem with only the mismatch operation in time . Amir et al. showed that if the only edit operations allowed are swap and mismatch, then the exact edit distance problem can be solved in time . In this paper, we discuss the problem of approximate edit distance with swap and mismatch. We show a randomized time algorithm for the problem. The algorithm guarantees an approximation factor of with probability of at least . [ABSTRACT FROM AUTHOR]

Abstract: Given a universe containing elements and a collection of multisets or sets over , the multiset multicover (MSMC) problem or the set multicover (SMC) problem is to cover all elements at least a number of times as specified in their coverage requirements with the minimum number of multisets or sets. In this paper, we give various exact algorithms for these two problems with or without constraints on the number of times a multiset or set may be chosen. First, we show that the MSMC without multiplicity constraints problem can be solved in time and polynomial space, where is the maximum coverage requirement and denotes the total number of given multisets over . (The notation suppresses a factor polynomial in .) To our knowledge, this is the first known exact algorithm for the MSMC without multiplicity constraints problem. Second, by combining dynamic programming and the inclusion–exclusion principle, we can exactly solve the SMC without multiplicity constraints problem in time. Compared with two recent results, in [Q.-S. Hua, Y. Wang, D. Yu, F.C.M. Lau, Set multi-covering via inclusion–exclusion, Theoretical Computer Science, 410 (38–40) (2009) 3882–3892] and [J. Nederlof, Inclusion exclusion for hard problems, Master Thesis, Utrecht University, The Netherlands, 2008], respectively, ours is the fastest exact algorithm for the SMC without multiplicity constraints problem. Finally, by directly using dynamic programming, we give the first known exact algorithm for the MSMC or the SMC with multiplicity constraints problem in time and space. This algorithm can also be easily adapted as a constructive algorithm for the MSMC without multiplicity constraints problem. [Copyright &y& Elsevier]

Abstract: This paper discusses optimization of quality measures over first order Delaunay triangulations. Unlike most previous work, our measures relate to edge-adjacent or vertex-adjacent triangles instead of only to single triangles. We give efficient algorithms to optimize certain measures, including measures related to the area ratio of adjacent triangles, angle between outward normals of adjacent triangles (for polyhedral terrains), and number of convex vertices. Some other measures are shown to be NP-hard. These include maximum vertex degree, number of convex edges, and number of mixed vertices. For the latter two measures we provide, for any constant , factor approximation algorithms that run in and time (when the Delaunay triangulation is given). For minimizing the maximum vertex degree, the NP-hardness proof provides an inapproximability result. Our results are presented for the class of first order Delaunay triangulations, but also apply to triangulations where for every triangle at least two edges are fixed. The approximation result on maximizing the number of convex edges is also extended to k-th order Delaunay triangulations. [Copyright &y& Elsevier]

Abstract: In this paper, two static and three dynamic routing algorithms have been proposed and compared to some of the existing algorithms on the basis of blocking probability. The two proposed static routing and wavelength assignment (RWA) algorithms reduce the blocking probability to maximize the utilization of network. For dynamic algorithms, first a model with no weights assignments is presented and then three algorithms are proposed and analysed with weight assignment resulting in reduction of blocking probability. All these algorithms are analysed and compared with four wavelength assignment schemes which are first-fit, random, most used and least used. It is shown that our proposed static algorithms give the best performance for first-fit wavelength assignment and most used wavelength assignment strategies with reduced complexity. For least used wavelength assignment and random wavelength assignment, 1 fixed and 2 alternate routing algorithm gives the lowest blocking probability. For dynamic routing, it has been shown that our proposed algorithm “less weight to maximum empty and nearest” gives the least blocking probability as compared to the other dynamic routing algorithms for random, most used and least used wavelength assignment strategies. [Copyright &y& Elsevier]

Abstract: The - and -methods are the basis for conformance testing from a deterministic finite state machine (DFSM) when the conformance relation considered is equivalence. However, many DFSM applications use only input sequences of limited length. In such cases, the test data only need to establish that the implementation under test produces the specified responses for sequences of length less than or equal to the upper bound . This paper extends the - and -methods to the case in which only bounded sequences are allowed. The methods for bounded sequences are stronger than the originals since test suites for the unbounded case can be obtained as a particular case (in which the upper bound is sufficiently large) from the new formulae. Furthermore, the generalization is not straightforward as it is not sufficient to extract the sequences of length at most from the test suites produced in the unbounded case, or even all prefixes of length at most of the original test sequences. The practicality of the methods is also improved in comparison to the unbounded case: the size of the test suites may be considerably reduced while the complexity of the test generation algorithms remains basically unchanged. [Copyright &y& Elsevier]

Abstract: This paper presents an algorithm for convex polygon decomposition around a given set of locations. Given an -vertex convex polygon and a set of points positioned arbitrarily inside , the task is to divide into equal-area convex parts, each containing exactly one point of . The algorithm runs in time . [Copyright &y& Elsevier]

Abstract: This paper presents methods for efficient recovery of accurate binocular disparity estimates in the vicinity of 3D surface discontinuities. Of particular concern are methods that impact coarse-to-fine, local block-based matching as it forms the basis of the fastest and the most resource efficient stereo computation procedures. A novel coarse-to-fine refinement procedure that adapts match window support across scale to ameliorate corruption of disparity estimates near boundaries is presented. Extensions are included to account for half-occlusions and colour uniformity. Empirical results show that incorporation of these advances in the standard coarse-to-fine, block matching framework reduces disparity errors by more than a factor of two, while performing little extra computation, preserving low complexity and the parallel/pipeline nature of the framework. Moreover, the proposed advances prove to be beneficial for CTF global matchers as well. [Copyright &y& Elsevier]

Abstract: In this paper, we address the problem of outdoor, appearance-based topological localization, particularly over long periods of time where seasonal changes alter the appearance of the environment. We investigate a straightforward method that relies on local image features to compare single-image pairs. We first look into which of the dominating image feature algorithms, SIFT or the more recent SURF, that is most suitable for this task. We then fine-tune our localization algorithm in terms of accuracy, and also introduce the epipolar constraint to further improve the result. The final localization algorithm is applied on multiple data sets, each consisting of a large number of panoramic images, which have been acquired over a period of nine months with large seasonal changes. The final localization rate in the single-image matching, cross-seasonal case is between 80% to 95%. [Copyright &y& Elsevier]

Abstract: In this paper, we consider the problem of scheduling with release dates and rejection on a single parallel batching machine, where the jobs have non-identical sizes. Our objective is to minimize the makespan of the accepted jobs plus the total penalty of the rejected jobs. First, we give a polynomial time approximation scheme (PTAS) for the case where jobs can be split. Then, we propose a -approximation algorithm for the special case with identical release dates. Finally, we present an approximation algorithm for the general problem with worst-case ratio , where is an arbitrarily small constant. [Copyright &y& Elsevier]

Abstract: In supervised learning tasks, boosting can combine multiple weak learners into a stronger one. AdaBoost is one of the most popular boosting algorithms, which is widely used and stimulates extensive research efforts in the boosting research community. Different from supervised learning, semi-supervised learning aims to make full use of both labeled and unlabeled data to improve learning performance, and has drawn considerable interests in both research and applications. To harness the power of boosting, it is important and interesting to extend AdaBoost to semi-supervised scenarios. Moreover, in semi-supervised learning, it is believed that incorporating pairwise constraints such as side-information is promising to obtain more satisfiable results. However, how to extend AdaBoost with pairwise constraints remains an open problem. In this paper, we propose a novel framework to solve this problem based on the gradient descent view of boosting. The proposed framework is almost as simple and flexible as AdaBoost, and can be readily applied in the presence of pairwise constraints. We present theoretical results, show possible further extensions, and validate the effectiveness via experiments. [Copyright &y& Elsevier]

Abstract: Classifying materials from their appearance is challenging. Impressive results have been obtained under varying illumination and pose conditions. Still, the effect of scale variations and the possibility to generalise across different material samples are still largely unexplored. This paper (A preliminary version of this work was presented in Hayman et al. [E. Hayman, B. Caputo, M.J. Fritz, J.-O. Eklundh, On the significance of real world conditions for material classification, in: Proceedings of the ECCV, Lecture Notes in Computer Science, vol. 4, Springer, Prague, 2004, pp. 253–266].) addresses these issues, proposing a pure learning approach based on support vector machines. We study the effect of scale variations first on the artificially scaled CUReT database, showing how performance depends on the amount of scale information available during training. Since the CUReT database contains little scale variation and only one sample per material, we introduce a new database containing 10 CUReT materials at different distances, pose and illumination. This database provides scale variations, while allowing to evaluate generalisation capabilities: does training on the CUReT database enable recognition of another piece of sandpaper? Our results demonstrate that this is not yet possible, and that material classification is far from being solved in scenarios of practical interest. [Copyright &y& Elsevier]

Abstract: The well-known problem of the longest common subsequence (LCS), of two strings of lengths and respectively, is -time solvable and is a classical distance measure for strings. Another well-studied string comparison measure is that of parameterized matching, where two equal-length strings are a parameterized match if there exists a bijection on the alphabets such that one string matches the other under the bijection. All works associated with parameterized pattern matching present polynomial time algorithms. There have been several attempts to accommodate parameterized matching along with other distance measures, as these turn out to be natural problems, e.g., Hamming distance, and a bounded version of edit-distance. Several algorithms have been proposed for these problems. In this paper we consider the longest common parameterized subsequence problem which combines the LCS measure with parameterized matching. We prove that the problem is -hard, and then show a couple of approximation algorithms for the problem. [Copyright &y& Elsevier]

Abstract: The claw finding problem has been studied in terms of query complexity as one of the problems closely connected to cryptography. Given two functions, and , with domain sizes and , respectively, and the same range, the goal of the problem is to find and such that . This problem has been considered in both quantum and classical settings in terms of query complexity. This paper describes an optimal algorithm that uses quantum walk to solve this problem. Our algorithm can be slightly modified to solve the more general problem of finding a tuple consisting of elements in the two function domains that has a prespecified property. It can also be generalized to find a claw of functions for any constant integer , where the domain sizes of the functions may be different. [Copyright &y& Elsevier]

Abstract: This paper studies online scheduling of unit length jobs on a parallel batching machine with the help of lookahead. The objective is to maximize the number of early jobs. Denote by the size of each batch with in the unbounded batching and in the bounded batching. In the lookahead model, at a time instant , an online algorithm can foresee all jobs that will arrive in the time segment . When , we show that a simple greedy online algorithm (independent of the value of ) has a best possible competitive ratio of , where is the number of jobs. This means that lookahead is useless when . When , we establish the upper bounds (for ) and (for ) of competitive ratios, and provide an online algorithm of competitive ratios (for ) and (for ). [Copyright &y& Elsevier]

Abstract: The paper is devoted to demonstrating a randomized algorithm for determining a dominating set in a given graph having a maximum degree of five. The algorithm follows the Las Vegas technique. Furthermore, the concept of a 2-separated collection of subsets of vertices in graphs is used. The suggested algorithm is based on a condition of the upper bound of the cardinality of a local dominating set. If the condition is not satisfied, then the algorithm halts with an appropriate message. Otherwise, the algorithm determines the dominating set. The given algorithm is considered a polynomial-time approximation one. [Copyright &y& Elsevier]

Abstract: Let be a graph without isolated vertices. For a positive integer , a set is a -distance paired-dominating set if each vertex in is within distance of a vertex in and the subgraph induced by contains a perfect matching. In this paper, we present two linear time algorithms to find a minimum cardinality -distance paired-dominating set in interval graphs and block graphs, which are two subclasses of chordal graphs. In addition, we present a characterization of trees with unique minimum -distance paired-dominating set. [Copyright &y& Elsevier]

Abstract: Let be a simple graph without isolated vertices. A vertex set is a paired-dominating set if every vertex in has a neighbor in and the induced subgraph has a perfect matching. In this paper, we investigate the approximation hardness of paired-domination in graphs. For weighted paired-domination, an approximation algorithm in general graphs and an exact dynamic programming style algorithm in trees are also given. [Copyright &y& Elsevier]

Abstract: Optical interconnections attract many engineers and scientists’ attention due to their potential for gigahertz transfer rates and concurrent access to the bus in a pipelined fashion. These unique characteristics of optical interconnections give us the opportunity to reconsider traditional algorithms designed for ideal parallel computing models, such as PRAMs. Since the PRAM model is far from practice, not all algorithms designed on this model can be implemented on a realistic parallel computing system. From this point of view, we study Cole’s pipelined merge sort [Cole R. Parallel merge sort. SIAM J Comput 1988;14:770–85] on the CREW PRAM and extend it in an innovative way to an optical interconnection model, the LARPBS (Linear Array with Reconfigurable Pipelined Bus System) model [Pan Y, Li K. Linear array with a reconfigurable pipelined bus system—concepts and applications. J Inform Sci 1998;106;237–58]. Although Cole’s algorithm is optimal, communication details have not been provided due to the fact that it is designed for a PRAM. We close this gap in our sorting algorithm on the LARPBS model and obtain an O(log N)-time optimal sorting algorithm using O(N) processors. This is a substantial improvement over the previous best sorting algorithm on the LARPBS model that runs in O(log N loglog N) worst-case time using N processors [Datta A, Soundaralakshmi S, Owens R. Fast sorting algorithms on a linear array with a reconfigurable pipelined bus system. IEEE Trans Parallel Distribut Syst 2002;13(3):212–22]. Our solution allows efficiently assign and reuse processors. We also discover two new properties of Cole’s sorting algorithm that are presented as lemmas in this paper. [Copyright &y& Elsevier]

Abstract: This paper presents a novel hybrid GMDH-type algorithm which combines neural networks (NNs) with an approximation scheme (self-organizing polynomial neural network: SOPNN). This composite structure is developed to establish a new heuristic approximation method for identification of nonlinear static systems. NNs have been widely employed to process modeling and control because of their approximation capabilities. And SOPNN is an analysis technique for identifying nonlinear relationships between the inputs and outputs of such systems and builds hierarchical polynomial regressions of required complexity. Therefore, the combined model can harmonize NNs with SOPNN and find a workable synergistic environment. Simulation results of the nonlinear static system are provided to show that the proposed method is much more accurate than other modeling methods. Thus, it can be considered for efficient system identification methodology. [Copyright &y& Elsevier]

Abstract: In this paper we revisit the semantics of extended regular expressions (regex), defined succinctly in the 90s [A.V. Aho, Algorithms for finding patterns in strings, in: Jan van Leeuwen (Ed.), Handbook of Theoretical Computer Science, in: Algorithms and Complexity, vol. A, Elsevier and MIT Press, 1990, pp. 255–300] and rigorously in 2003 by Câmpeanu, Salomaa and Yu [C. Câmpeanu, K. Salomaa, S. Yu, A formal study of practical regular expressions, IJFCS 14 (6) (2003) 1007–1018], when the authors reported an open problem, namely whether regex languages are closed under the intersection with regular languages. We give a positive answer; and for doing so, we propose a new class of machines — regex automata systems (RAS) — which are equivalent to regex. Among others, these machines provide a consistent and convenient method of implementing regex in practice. We also prove, as a consequence of this closure property, that several languages, such as the mirror language, the language of palindromes, and the language of balanced words are not regex languages. [Copyright &y& Elsevier]

Abstract: Phylogenetic networks are a generalization of evolutionary or phylogenetic trees that allow the representation of conflicting signals or alternative evolutionary histories in a single diagram. Recently the Quartet-Net or “QNet” method was introduced, a method for computing a special kind of phylogenetic network called a split network from a collection of weighted quartet trees (i.e. phylogenetic trees with 4 leaves). This can be viewed as a quartet analogue of the distance-based Neighbor-Net (NNet) method for constructing outer-labeled planar split networks. In this paper, we prove that QNet is a consistent method, that is, we prove that if QNet is applied to a collection of weighted quartets arising from a circular split weight function, then it will return precisely this function. This key property of QNet not only ensures that it is guaranteed to produce a tree if the input corresponds to a tree, and an outer-labeled planar split network if the input corresponds to such a network, but also provides the main guiding principle for the design of the method. [Copyright &y& Elsevier]

Online mining of path traversal patterns from Web click-streams is one of the most important problems of Web usage mining. In this paper, we propose a sliding window-based Web data mining algorithm, called Top-SW (Top-k path traversal patterns of Stream sliding Window), to discover the set of top-k path traversal patterns from streaming maximal forward references, where k is the desired number of path traversal patterns to be mined. A new summary data structure, called Top-list (a list of Top-k path traversal patterns) is developed to maintain the essential information about the top-k path traversal patterns from the current maximal forward references stream. Experimental studies show that the proposed Top-SW algorithm is an efficient, single-pass algorithm for mining the set of top-k path traversal patterns from a continuous stream of maximal forward references. [Copyright &y& Elsevier]

Abstract: This paper studies two problems on compressed strings described in terms of straight line programs (SLPs). One is to compute the length of the longest common substring of two given SLP-compressed strings, and the other is to compute all palindromes of a given SLP-compressed string. In order to solve these problems efficiently (in polynomial time w.r.t. the compressed size) decompression is never feasible, since the decompressed size can be exponentially large. We develop combinatorial algorithms that solve these problems in time with space, and in time with space, respectively, where is the size of the input SLP-compressed strings. [Copyright &y& Elsevier]

Abstract: Given a set of elements, a family of subsets of , and a connected graph on vertex set ,a connected set cover (CSC) is a subfamily of such that every element in is covered by at least one set of , and the subgraph of induced by is connected. If furthermore is -connected and every element in is covered by at least sets in , then is a -CSC. In this paper, we present two approximation algorithms for the minimum CSC problem, and one approximation algorithm for the minimum -CSC problem. Performance ratios are analyzed. These are the first approximation algorithms for CSC problems in general graphs with guaranteed performance ratios. [Copyright &y& Elsevier]

Influence Maximization Problem (IMP) is selecting a seed set of nodes in the social network to spread the influence as widely as possible. It has many applications in multiple domains, e.g., viral marketing is frequently used for new products or activities advertisement. While it is a classic and well-studied problem in computer science, unfortunately, all those proposed techniques are compromising among time efficiency, memory consumption, and result quality. In this paper, we conduct comprehensive experimental studies on the state-of-the-art IMP approximate approaches to reveal the underlying trade-off strategies. Interestingly, we find that even the state-of-the-art approaches are impractical when the propagation probability of the network have been taken into consideration. With the findings of existing approaches, we propose a novel residual-based approach (i.e., RCELF) for IMP , which (i) overcomes the deficiencies of existing approximate approaches, and (ii) provides theoretical guaranteed results with high efficiency in both time- and space-perspectives. We demonstrate the superiority of our proposal by extensive experimental evaluation on real datasets. • We reveal the trade-off strategies among the approximate approaches for IMP. • An effective and efficient approximate algorithm called RCELF is proposed. • The performance of RCELF is extensively evaluated on 5 real-world datasets. [ABSTRACT FROM AUTHOR]

Abstract: The least significant digit first decomposition of integer vectors into words of digit vectors provides a natural way for representing sets of integer vectors by automata. In this paper, the minimal automata representing Presburger sets are proved structurally Presburger: automata obtained by moving the initial state and replacing the accepting condition represent Presburger sets. [Copyright &y& Elsevier]

Abstract: In [R.J. Corin, J.I. den Hartog, A probabilistic hoare-style logic for game-based cryptographic proofs, in: M. Bugliesi, B. Preneel, V. Sassone (Eds.), ICALP 2006 Track C, Venice, Italy, in: Lecture Notes in Computer Science, vol. 4052, Springer-Verlag, Berlin, 2006, pp. 252–263] we build a formal verification technique for game-based correctness proofs of cryptographic algorithms based on a probabilistic Hoare style logic [J.I. den Hartog, E.P. de Vink, Verifying probabilistic programs using a Hoare like logic, International Journal of Foundations of Computer Science 13 (3) (2002) 315–340]. An important step towards enabling mechanized verification within this technique is an axiomatization of implication between predicates which is purely semantically defined in the latter reference cited above. In this paper we provide an axiomatization and illustrate its place in the formal verification technique given in the former. [Copyright &y& Elsevier]