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One of the fundamental issues in sensor networks is the coverage problem, which reflect-show well a sensor network is monitored or tracked by sensors. In this paper, we formulate this problem as a decision problem, whose goal is to determine whether every point in the servicearea of the sensor network is covered by at least α sensors, where ff is a given parameter andthe sensing regions of sensors are modeled by balls (not necessarily of the same radius). This problem in a 2D space is solved in [10] with an efficient polynomial-time algorithm (in termsof the number of sensors). In this paper, we show that tackling this problem in a 3D space is still feasible within polynomial time. Further, the proposed solution can be easily translated intoan efficient polynomial-time distributed protocol. We demonstrate an application of the derived result by proposing an energy-conserving scheduling protocol. [ABSTRACT FROM AUTHOR]

This paper studies the two-dimensional range search problem, and constructs a simple and efficient algorithm based on the Voronoi diagram. In this problem, a set of points and a query range are given, and we want to enumerate all the points which are inside the query range as quickly as possible. In most of the previous researches on this problem, the shape of the query range is restricted to particular ones such as circles, rectangles and triangles, and the improvement on the worst-case performance has been pursued. On the other hand, the algorithm proposed in this paper is designed for a general shape of the query range in the two-dimensional space, and is intended to accomplish a good average-case performance. This performance is actually observed by numerical experiments. In these experiments, we compare the execution time of the proposed algorithm with those of other representative algorithms such as those based on the bucketing technique and the k-d tree. We can observe that our algorithm shows the better performance in almost all the cases. [ABSTRACT FROM AUTHOR]

This paper proposes a new solution to geo-register the nearly feature-less maritime video feeds. We detect the horizon using sizable or uniformly moving vessels, and estimate the vertical apex using water reflections of the street lamps. The computed horizon and apex provide a metric rectification that removes the affine distortions and reduces the searching space for geo-registration. Geo-registration is obtained by searching the best orientation where the estimated water masks on satellite images and camera views are matched. The proposed solution has the following contributions: first, water and coastlines are used as features for registration between horizontally looking maritime views and satellite images. Second, water reflections are proposed to estimate the vertical vanishing point. Third, we give algorithms for the detection of water areas in both satellite images and camera views. Experimental results and applications on cross camera tracking are demonstrated. We also discuss several observations, as well as limitations of the proposed approach. [ABSTRACT FROM AUTHOR]

In this paper, by constructing a more entangled quantum system, we shorten the adiabatic quantum search algorithm to constant time. On the other hand, we show that the speed-up of adiabatic quantum algorithms by selecting particular adiabatic evolution paths or injecting energy into the quantum system can be explained as a form of entanglement enlargement. These findings suggest that entanglement plays a fundamental role for the efficiency of algorithm performance. [ABSTRACT FROM AUTHOR]

This paper presents a parallel framework for the solution of multi-objective optimization problems. The framework implements some of the best known multi-objective evolutionary algorithms. The plugin-based architecture of the framework minimizes the end user effort required to incorporate their own problems and evolutionary algorithms, and facilitates tool maintenance. A wide variety of configuration options can be specified to adapt the software behavior to many different parallel models. An innovation of the framework is that it provides a self-adaptive parallel model that is based on the cooperation of a set of evolutionary algorithms. The aim of the new model is to raise the level of generality at which most current evolutionary algorithms operate. This way, a wider range of problems can be tackled since the strengths of one algorithm can compensate for the weaknesses of another. The model proposed is a hybrid algorithm that combines a parallel island-based scheme with a hyperheuristic approach. The model grants more computational resources to those algorithms that show a more promising behavior. The flexibility and efficiency of the framework were tested and demonstrated by configuring standard and self-adaptive models for test problems and real-world applications. [ABSTRACT FROM AUTHOR]

This paper studies the complexity of determining if a finite algebra generates a variety that satisfies various Maltsev conditions, such as congruence distributivity or modularity. For idempotent algebras we show that there are polynomial time algorithms to test for these conditions but that in general these problems are EXPTIME complete. In addition, we provide sharp bounds in terms of the size of two-generated free algebras on the number of terms needed to witness various Maltsev conditions, such as congruence distributivity. [ABSTRACT FROM AUTHOR]

In this paper, we numerically investigate the structural characteristics that affect the synchronizability of coupled identical oscillators on scale-free networks. By using the edge-exchange method, we can change the network structure with degree sequence fixed. An optimal algorithm, namely Tabu Search, is applied, respectively, to enhance and weaken the synchronizability. The numerical results indicate that the synchronizability is most sensitive to the maximal betweenness. By tracking the optimization process, most previous works suggest that the synchonizability can be enhanced by reducing assortative coefficient and clustering coefficient; however, interestingly, our numerical simulations show that the depression of synchronizability also corresponds to the reduction process of those two coefficients. [ABSTRACT FROM AUTHOR]

Because of the inherent computational complexity, mining the complete frequent item-set in dense datasets remains to be a challenging task. Mining Maximal Frequent Item-set (MFI) is an alternative to address the problem. Set-Enumeration Tree (SET) is a common data structure used in several MFI mining algorithms. For this kind of algorithm, the process of mining MFI's can also be viewed as the process of searching in set-enumeration tree. To reduce the search space, in this paper, a new algorithm, Index-MaxMiner, for mining MFI is proposed by employing a hybrid search strategy blending breadth-first and depth-first. Firstly, the index array is proposed, and based on bitmap, an algorithm for computing index array is presented. By adding subsume index to frequent items, Index-MaxMiner discovers the candidate MFI's using breadth-first search at one time, which avoids first-level nodes that would not participate in the answer set and reduces drastically the number of candidate itemsets. Then, for candidate MFI's, depth-first search strategy is used to generate all MFI's. Thus, the jumping search in SET is implemented, and the search space is reduced greatly. The experimental results show that the proposed algorithm is efficient especially for dense datasets. [ABSTRACT FROM AUTHOR]

An algorithm that can decide, prior to performing the circuit analysis, if a procedure for the fast computation of the periodic steady state is necessary, is presented in this paper. The analysis of a switching supply illustrates how this algorithm works. [ABSTRACT FROM AUTHOR]

In this paper, we give a complete characterization of the existence of a galled-tree network in the form of simple sufficient and necessary conditions for both root-known and root-unknown cases. As a by-product we obtain a simple algorithm for constructing galled-tree networks. We also introduce a new necessary condition for the existence of a galled-tree network similar to bi-convexity. [ABSTRACT FROM AUTHOR]

In order to improve the performance of mass segmentation on mammograms, an intelligent algorithm is proposed in this paper. It establishes two mass models to characterize the various masses, and the ones in the denser tissue are represented with Model I, while the ones in the fatty tissue are represented with Model II. Then, it uses iterative thresholding to extract the suspicious area, as well as the rough regions of those masses matching Model II, and applies a DWT-based technique to locate those masses matching Model I, which are hidden in the high gray-level intensity and contrast area. A region growing process restricted by Canny edge detection is subsequently used to segment the rough regions of those masses matching Model I, and finally snakes are carried out to find all the mass regions roughly extracted above. Thirty patient cases with 60 mammograms and 107 masses were used for evaluation, and the experimental result has demonstrated the algorithm's better performance over the conventional methods. [ABSTRACT FROM AUTHOR]

A finite p-group G is called metacyclic if it has a cyclic normal subgroup A such that G/A is cyclic. In 1973, King classified metacyclic p-groups; in 1987, Newman and the first author developed a new approach to metacyclic p-groups suggested by the p-group generation algorithm, they found new presentations for these groups. However, their results were only announced in the case of p odd, and no proof was given. The purpose of this paper is to give a new proof of their results in the case of p=2, which is independent of the p-group generation algorithm. [ABSTRACT FROM AUTHOR]

While tree contraction algorithms play an important role in efficient tree computation in parallel, it is difficult to develop such algorithms due to the strict conditions imposed on contracting operators. In this paper, we propose a systematic method of deriving efficient tree contraction algorithms from recursive functions on trees. We identify a general recursive form that can be parallelized into efficient tree contraction algorithms, and present a derivation strategy for transforming general recursive functions to the parallelizable form. We illustrate our approach by deriving a novel parallel algorithm for the maximum connected-set sum problem on arbitrary trees, the tree-version of the well-known maximum segment sum problem. [ABSTRACT FROM AUTHOR]

This paper describes an efficient and adaptive method of threshold estimation for removing impulse noise from images, based on Double Density Wavelet Transform (DDWT). The performance of image de-noising algorithms using wavelet transforms can be improved significantly by fixing an optimum threshold value, based on the analysis of the statistical parameters of subband coefficients. In this proposed method, the choice of the threshold estimation is carried out by analyzing the statistical parameters of the wavelet subband coefficients like standard deviation, arithmetic mean and geometrical mean. Here the noisy image is first decomposed into many levels to obtain different frequency bands using DDWT. Then soft thresholding method is used to remove the noisy coefficients, by fixing the optimum threshold value by the proposed method. Experimental results on several test images by using the proposed method show that, the proposed method yields significantly superior image quality and better Peak Signal-to-Noise Ratio (PSNR). Some comparisons with the best available results will be given in order to illustrate the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

This paper presents a new sequential algorithm to answer the question about the existence of a causal explanation for a set of independence statements (a dependency model), which is consistent with a given set of background knowledge. Emphasis is placed on generality, efficiency and ease of parallelization of the algorithm. From this sequential algorithm, an efficient, scalable, and easy to implement parallel algorithm with very little inter-processor communication is derived. [ABSTRACT FROM AUTHOR]

In this paper, we consider a set of mobile nodes, each of which moves with constant velocity. We present algorithms to determine which of these mobile nodes can be captured the soonest by a set of one or more pursuers. We use a time parameterized R-tree (TPR-tree) to index these moving points. We then develop algorithms that operate on the TPR-tree to answer three query variations: (1) a single pursuer that is faster than all of the mobile nodes, (2) a single pursuer that is slower than some of the mobile nodes and (3) multiple pursuers. Experimental results show that our algorithms are simpler and faster than other approaches to solve the problem. [ABSTRACT FROM AUTHOR]

In [1], we described an efficient inductive scheme which uses a total of four operators to generate all prime alternating knots of a given minimal crossing size. The process is carried out in two steps, where in the first step, two of the four operators are applied to the prime alternating knots of minimal crossing size n to produce approximately 98% of the prime alternating knots of minimal crossing size n+1, while in the second step, the remaining two operators are applied to these newly constructed knots, thereby producing the remaining prime alternating knots of crossing size n+1. The process begins with the prime alternating knot of four crossings, the figure eight knot. In this paper, we provide an actual implementation of our procedure, wherein we spend considerable effort to make the procedure efficient. One very important aspect of the implementation is a new way of encoding a knot. We are able to assign an integer array (which we call the master array) to a prime alternating knot in such a way that each regular diagram of the knot can be constructed from the data in the array. Moreover, two knots are equivalent if and only if their master arrays are identical. We have used this generation scheme to enumerate the prime alternating knots up to and including those of 19 crossings. The knots up to and including 17 crossings produced by our generation scheme concurred with those found by M. Thistlethwaite, J. Hoste and J. Weeks (see [3]). The current implementation of the algorithms involved in the generation scheme allowed us to produce the 1,769,979 prime alternating knots of 17 crossings on a five node beowulf cluster in approximately 2.3 hours, while the time to produce the prime alternating knots up to and including those of 16 crossings totalled approximately 45 minutes. The prime alternating knots at 18 and 19 crossings were enumerated using the 48 node Compaq ES-40 beowulf cluster at the University of Western Ontario (we also received generous support from Compaq at the SC 99 conference). The cluster was shared with other users and so an accurate estimate of the running time is not available, but the generation of the 8,400,285 knots at 18 crossings was completed in 17 hours, and the generation of the 40,619,385 prime alternating knots at 19 crossings took approximately 72 hours. With the improvements that are described in the sequel, we anticipate that the knots at 19 crossings will be generated in not more than 10 hours on a current Pentium III personal computer equipped with 256 megabytes of main memory. [ABSTRACT FROM AUTHOR]

An algorithm is proposed in this paper that finds exact exclusive-or sum-of-products of an arbitrary function, provided the number of product terms is less than eight. If the number of product terms in the minimal expression is more than seven, then the algorithm detects it and heuristically returns near-optimal expressions. The algorithm is time and space efficient even for functions with many input variables. [ABSTRACT FROM AUTHOR]