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It is well known that the circular flow number of a bridgeless cubic graph can be computed in terms of certain partitions of its vertex set with prescribed properties. In the present paper, we first study some of these properties that turn out to be useful in order to make an efficient and practical implementation of an algorithm for the computation of the circular flow number of a bridgeless cubic graph. Using this procedure, we determine the circular flow number of all snarks on up to 36 vertices as well as the circular flow number of various famous snarks. After that, as combination of the use of this algorithm with new theoretical results, we present an infinite family of snarks of order 8 k + 2 whose circular flow numbers meet a general lower bound presented by Lukot'ka and Škoviera in 2008. In particular this answers a question proposed in their paper. Moreover, we improve the best known upper bound for the circular flow number of Goldberg snarks and we conjecture that this new upper bound is optimal. [ABSTRACT FROM AUTHOR]

This is a paper about the need for algorithmic rights: the right to algorithmic transparency and algorithmic explainability; the right to be informed if we are interacting with an automated system; the right not to be subject to a decision based solely on automated processing; and the right not to depend on an algorithmic system for compliance with our fundamental rights, but to instead choose human interaction in ensuring such compliance. There are several angles from which these rights can be discussed, but I will be looking at them as tools of empowerment supporting the right to good administration in the EU, where they can help us meet the challenge of good governance in an algorithm-based and data-driven public sector, and can in this way help to strengthen the rule of law and the fundamental rights that are central to it. [ABSTRACT FROM AUTHOR]

Abstract: The ability to guide relief vehicles to safety and quickly pass through environments affected by fires is critical in fighting forest fires. In this paper, we focus on route determination in the case of forest fires, and propose a data model that supports finding paths among moving obstacles. This data model captures both static information, such as the type of the response team, the topology of the road network, and dynamic information, such as sensor information, changing availabilities of roads during disasters, and the position of the vehicle. We use a fire simulation model to calculate the fire evolution. The spread of the fire is represented as movements of obstacles that block the responders׳ path in the road network. To calculate safe and optimal routes avoiding obstacles, the A⁎ algorithm is extended to consider the predicted availabilities of roads. We prove the optimality of the path calculated by our algorithm and then evaluate it in simulated scenarios. The results show that our model and algorithm are effective in planning routes that avoid one or more fire-affected areas and that the outlook for further investigation is promising. [Copyright &y& Elsevier]

Abstract: In this paper we present a novel algorithm, that will never fail, for inverting a general nonsingular -tridiagonal matrix. The computational cost of the algorithm is given. Some illustrative examples are introduced. [Copyright &y& Elsevier]

Abstract: In this paper we introduce the V-transform (V-BWT), a variant of the classic Burrows–Wheeler Transform. The original BWT uses lexicographic order, whereas we apply a distinct total ordering of strings called V-order. V-order string comparison and Lyndon-like factorization of a string into V-words have recently been shown to be linear in their use of time and space (Daykin et al., 2011) [18]. Here we apply these subcomputations, along with suffix-sorting (Ko and Aluru, 2003) [26], to implement linear V-sorting of all the rotations of a string. When it is known that the input string x is a V-word, we compute the V-transform in time and space, and also outline an efficient algorithm for inverting the V-transform and recovering x . We further outline a bijective algorithm in the case that x is arbitrary. We propose future research into other variants of transforms using lex-extension orderings (Daykin et al., 2013) [19]. Motivation for this work arises in possible applications to data compression. [Copyright &y& Elsevier]

Abstract: We consider a frequency allocation problem, in which we are given a cellular telephone network whose geographical coverage area is divided into cells in which phone calls are serviced by frequencies assigned to them, so that none of the pairs of calls emanating from the same or neighboring cells is assigned the same frequency. The problem is to use the frequencies efficiently, i.e., to minimize the span of frequencies used. The frequency allocation problem can be regarded as a multicoloring problem on a weighted hexagonal graph. In this paper, we present a 1-local 4/3-competitive distributed algorithm for multicoloring a hexagonal graph without certain forbidden configuration (introduced in Šparl and Žerovnik (2010) [7]). [Copyright &y& Elsevier]

Abstract: In this paper we study two solution methods for finding the largest eigenvalue (singular value) of general square (rectangular) nonnegative tensors. For a positive tensor, one can find the largest eigenvalue (singular value) based on the properties of the positive tensor and the power-type method. While for a general nonnegative tensor, we use a series of decreasing positive perturbations of the original tensor and repeatedly recall power-type method for finding the largest eigenvalue (singular value) of a positive tensor with an inexact strategy. We prove the convergence of the method for the general nonnegative tensor. Under a certain assumption, the computing complexity of the method is established. Motivated by the interior-point method for the convex optimization, we put forward a one-step inner iteration power-type method, whose convergence is also established under certain assumption. Additionally, by using embedding technique, we show the relationship between the singular values of the rectangular tensor and the eigenvalues of related square tensor, which suggests another way for finding the largest singular value of nonnegative rectangular tensor besides direct power-type method for this problem. Finally, numerical examples of our algorithms are reported, which demonstrate the convergence behaviors of our methods and show that the algorithms presented are promising. [Copyright &y& Elsevier]

Abstract: Privacy-preserving data publishing (PPDP) deals with data publishing while preserving individual's privacy in the data. Recent researches show that knowledge of mechanism of anonymization provides a loophole for attacks [1,2], we call this kind of attack a mechanism-based attack. In this paper, we first give a comprehensive study of mechanism-based attack and point out that the range of mechanism-based disclosure is much broader than ever said. Then, we analyze the rationale of mechanism-based attack and give the definition of mechanism-based attack formally. To counteract mechanism-based attack, we introduce a model called e-secrecy and corresponding solution algorithm MAIA. We conduct a comprehensive set of experiments to show mechanism-based attacks are practical concern in the real-world data sets and that our method introduces better data utility and very minor computation than the existing algorithms. [Copyright &y& Elsevier]

• Voltage dependent demand or supply response can cause inadequate energy utilization. • The GSMA algorithm improves energy utilization without utilizing communication. • Simulation and experimental results validate the behaviour of the GSMA algorithm. • The GSMA algorithm could also be applied to ac systems. Due to the distributed nature of future electrical power systems, decentralized control is essential for these grids. This paper shows that converters that have identical voltage thresholds switch off simultaneously even if some could have remained operational. Therefore, inadequate system and energy utilization can occur when decentralized demand or supply response is utilized. The Grid Sense Multiple Acces (GSMA) algorithm proposed in this paper ensures that, after a change occurs in the system, a subset of the converters remains connected to the grid, without the need of utilizing any form of communication. This is achieved by introducing an exponential backoff time between failed connection attempts. Furthermore, several simulations and experiments are conducted to illustrate and validate the behavior of the GSMA algorithm, showing that it can be applied to dc grids in order to improve system and energy utilization. [ABSTRACT FROM AUTHOR]

Historically, change detection reviews have examined and categorized algorithms based on their techniques for the remote sensing community. Here, we synthesize urban land change algorithms by the types of information they provide to a diverse and growing set of user communities. Two goals of the paper are first to synthesize past and current change detection studies to examine urban land change to help users of remote sensing algorithms understand and navigate the vast variety of available methods, and second to identify gaps in knowledge for the urban remote sensing community. We analyzed 644 peer-reviewed research papers published in English-language journals and conducted a systematic review of urban land change algorithms. All papers included in our study focus on urban land change ; studies that concentrate on single-date urban classification or mapping for one point in time without an explicit urban land change component are not included in this analysis. The review showed five key results and knowledge gaps. First, most urban change detection algorithms are being developed and applied for only a few regions, with 75% of studies focused on high or upper-middle-income countries and the majority of these on China or the United States. This suggests a major gap in geographic coverage as well as the need for more studies on cities in low and lower-middle-income countries. Second, the results show that 41% of the algorithms have been developed or applied for cities of over 5 million inhabitants. This focus on large cities is problematic given that only 11% of the world's urban population lives in cities with populations greater than 5 million and that most future urban growth will occur in small- and medium-sized towns and cities with populations of fewer than 1 million people. Third, our analysis shows that 62% of the studies use three or fewer time points to measure urban land change with an average study length of 17 years. Since rapidly growing urban areas are highly dynamic, this suggests that existing algorithms using only a few time points are likely missing urban transitions that can only be captured with high temporal frequency analysis. Fourth, we find that urban expansion is the most commonly monitored type of urban land change. Comparatively fewer studies characterized intra-urban change or three-dimensional structural change. Fifth and finally, the results show that an overwhelming majority—87%—of all studies identify only one urban class, highlighting a need for more studies that distinguish intra-urban variation and differentiate multiple urban classes. Our analysis shows that it is very difficult—nearly impossible—to compare across algorithms. Thus, for users of urban land change information, it is difficult to navigate the literature and know which algorithms are most appropriate for a particular use. Taken together, this points to the need for improved reproducibility, replicability, and comparability of studies in order to help harmonize urban land change information across regions and countries. This is especially important given the growing user communities of urban land change products and analysis, especially from policy and practice. • We conduct a systematic review of the urban land change algorithm literature. • Most studies monitor urban change at low temporal frequencies. • The majority of urban land change is characterized using only one urban class. • Over 75% of studies focus on high or upper-middle level income countries. • Key knowledge gaps include in geographic coverage, city size, and land transitions. [ABSTRACT FROM AUTHOR]

In recent years, epidemics have been raging around the world, causing serious harm to human health, and controlling the spread of the epidemics has become a hot topic. The study of network partition is of great practical significance to control the spread of the epidemics. Network partition is an N P hard problem. Much work has focused on identifying important nodes in complex networks to achieve network partition. Similarly, understanding the importance of links in spreading dynamics in a network can provide ways to hinder or slow down ongoing dynamical phenomena like the spreading of epidemic or the diffusion of information. This paper studies the algorithms to identify influential links in complex networks. Deleting some influential links can divide the network into some components so as to prevent effectively the spreading processes in epidemics. Our algorithms can successfully identify influential links at low computational cost by utilizing the eigenvector centrality measures. The simulated results in some real-world social networks and synthetic networks show that our algorithms are effective. The number of infected individuals can be remarkable reduced by removing influential links. [ABSTRACT FROM AUTHOR]

[Display omitted] • Non-contact measurement method is proposed for hexagonal shaft bending deflection. • The valid data is extracted within the allowable incident angle of laser sensor. • The measurement accuracy can reach the same level as ZEISS Calypso scanner. • High precision, high efficiency, non-rotation speed limited are method advantages. The hexagonal shaft is often used as the important transmission component. Its bending deflection is a main factor affecting the working capability and fatigue life. In this paper, a contactless continuous measurement method based on contour reconstruction is proposed, which only uses a laser displacement sensor moving at a constant speed to collect the profile information. According to the allowable incident angle, the valid data with high precision is extracted. An algorithm seeking for section center is deduced according to the hexagon edge equations fitted by the least square method, then, the three-dimensions blending axis is obtained. The method precision is analyzed by theoretical error analysis. Finally, the feasibility and high accuracy of the novel method are demonstrated by comparing with ZEISS Calypso scanner results and the repeatability and reproducibility (R&R) analysis. [ABSTRACT FROM AUTHOR]

Abstract: Measurements of structure orientations are afflicted with uncertainties which arise from many sources. Commonly, such uncertainties involve instrument imprecision, external disturbances and human factors. The aggregated uncertainty depends on the uncertainty of each of the sources. The orientation of an object measured in a borehole (e.g. a fracture) is calculated using four parameters: the bearing and inclination of the borehole and two relative angles of the measured object to the borehole. Each parameter may be a result of one or several measurements. The aim of this paper is to develop a method to both calculate and visualize the aggregated uncertainty resulting from the uncertainty in each of the four geometrical constituents. Numerical methods were used to develop a VBA-application in Microsoft Excel to calculate the aggregated uncertainty. The code calculates two different representations of the aggregated uncertainty: a 1-parameter uncertainty, the ‘minimum dihedral angle’, denoted by Ω; and, a non-parametric visual representation of the uncertainty, denoted by χ. The simple 1-parameter uncertainty algorithm calculates the minimum dihedral angle accurately, but overestimates the probability space that plots as an ellipsoid on a lower hemisphere stereonet. The non-parametric representation plots the uncertainty probability space accurately, usually as a sector of an annulus for steeply inclined boreholes, but is difficult to express numerically. The 1-parameter uncertainty can be used for evaluating statistics of large datasets whilst the non-parametric representation is useful when scrutinizing single or a few objects. [Copyright &y& Elsevier]

Abstract: For a positive integer , a -dominating set of a graph is a subset such that every vertex not in is adjacent to at least vertices in . The -domination problem is to determine a minimum -dominating set of . This paper studies the -domination problem in graphs from an algorithmic point of view. In particular, we present a linear-time algorithm for the -domination problem for graphs in which each block is a clique, a cycle or a complete bipartite graph. This class of graphs includes trees, block graphs, cacti and block-cactus graphs. We also establish NP-completeness of the -domination problem in split graphs. [Copyright &y& Elsevier]

Abstract: Soft set theory was originally proposed by Molodtsov as a general mathematical tool for dealing with uncertainty in 1999. Recently, researches of decision making based on soft sets have got some progress, but few people consider multi-experts situation. As such, this paper discusses multi-experts group decision making problems. Firstly, we give a concept of intuitionistic fuzzy soft matrix (IFSM) and prove some relevant properties of IFSM. Then, an adjustable approach is presented by means of median level soft set and p-quantile level soft set for dealing with decision making problems based on IFSM. Thirdly, we study aggregation methods of IFSM, give two kinds of aggregation operators and methods that how to determine experts’ weights under different situation with programming models, four corresponding algorithms have been proposed, too. Finally, a practical example has been demonstrated the reasonability and efficiency of these new algorithms. [Copyright &y& Elsevier]

Abstract: Given a positive integer and an undirected edge-weighted connected simple graph with at least edges of positive weight, we wish to partition the graph into edge-disjoint connected components of approximately the same size. We focus on the max-min ratio of the partition, which is the weight of the maximum component divided by that of the minimum component. It has been shown that for some instances, the max-min ratio is at least two. In this paper, for any graph with no edge weight larger than one half of the average weight, we provide a linear-time algorithm for delivering a partition with max-min ratio at most two. Furthermore, by an extreme example, we show that the above restriction on edge weights is the loosest possible. [Copyright &y& Elsevier]

Abstract: Regression models are used in geosciences to extrapolate data and identify significant predictors of a response variable. Criterion approaches based on the residual sum of squares (RSS), such as the Akaike Information Criterion, Bayesian Information Criterion (BIC), Deviance Information Criterion, or Mallows'' Cp can be used to compare non-nested models to identify an optimal subset of covariates. Computational limitations arise when the number of observations or candidate covariates is large in comparing all possible combinations of the available covariates, and in characterizing the covariance of the residuals for each examined model when the residuals are autocorrelated, as is often the case in spatial and temporal regression analysis. This paper presents computationally efficient algorithms for identifying the optimal model as defined using any RSS-based model selection criterion. The proposed dual criterion optimal branch and bound (DCO B&B) algorithm is guaranteed to identify the optimal model, while a single criterion heuristic (SCH) B&B algorithm provides further computational savings and approximates the optimal solution. These algorithms are applicable both to multiple linear regression (MLR) and to response variables with correlated residuals. We also propose an approach for iterative model selection, where a single set of covariance parameters is used in each iteration rather than a different set of parameters being used for each examined model. Simulation experiments are performed to evaluate the performance of the algorithms for regression models, using MLR and geostatistical regression as prototypical regression tools and BIC as a prototypical model selection approach. Results show massive computational savings using the DCO B&B algorithm relative to performing an exhaustive search. The SCH B&B is shown to provide a good approximation of the optimal model in most cases, while the DCO B&B with iterative covariance parameter optimization yields the closest approximation to the DCO B&B algorithm while also providing additional computational savings. [Copyright &y& Elsevier]

Abstract: A mixed dominating set of a simple graph is a subset such that every vertex or edge not in is adjacent or incident to at least one vertex or edge in . The mixed domination problem is to determine a minimum mixed dominating set of . This paper studies mixed domination in graphs from an algorithmic point of view. In particular, a linear-time labeling algorithm for the mixed domination problem in cacti is presented. In addition, we fix an incomplete proof of the NP-completeness of the mixed domination problem in split graphs Zhao et al. (2011) [23]. Finally, we establish a primal–dual algorithm for the mixed domination problem in trees. [Copyright &y& Elsevier]

Abstract: Double patterning lithography is promising for 32nm technology and beyond. In this technique, one-layer layout is decomposed into two masks. Much work has been proposed to solve feature decomposition problem. However, post-routing layer assignment, which determines the layout features on each layer, thus having great impact on double patterning related parameters, has not been explored in the merit of double patterning. In this paper, we formulate post-routing layer assignment for double patterning problem for the first time. Both this problem and traditional single layer double patterning problem are proved to be NP-complete. An effective algorithm is further proposed to solve it. The algorithm consists of three major phases: multi-layer assignment to minimize double patterning risks, single layer double patterning, and via reduction. Since blind post-routing layer assignment may jeopardize timing critical paths obtained in the routing stage, our algorithm also considers total wire length and coupling capacitance on critical paths as timing metrics. Experimental results on Collaborative Benchmarking Laboratory benchmarks demonstrate the effectiveness of our algorithm. In comparison with single layer double patterning, our method achieves 62% and 11% average reduction on unresolvable conflicts and stitches, respectively, with only 0.30% increase of via number in layouts. Furthermore, the via height and parallel wire length on critical paths are decreased by 8% and 14% on average. [Copyright &y& Elsevier]

Abstract: Background and objectives: In their paper, “Understanding and using the Implicit Association Test: I. An improved scoring algorithm”, Greenwald, Nosek, and Banaji (2003) investigated different ways to calculate the IAT-effect. However, up to now, it remained unclear whether these findings – based on internet data – also generalize to laboratory settings. Therefore, the main goal of the present study was to cross-validate scoring algorithms for the IAT in a laboratory setting, specifically in the domain of psychopathology. Methods: Four known IAT algorithms and seven alternative IAT algorithms were evaluated on several performance criteria in the large-scale laboratory sample of the Netherlands Study of Depression and Anxiety (N = 2981) in which two IATs were included to obtain measurements of automatic self-anxious and automatic self-depressed associations. Results and conclusions: Results clearly demonstrated that the D2SD-measure and the D600-measure as well as an alternative algorithm based on the correct trials only (DnoEP-measure) are suitable to be used in a laboratory setting for IATs with a fixed order of category combinations. It remains important to further replicate these findings, especially in studies that include outcome measures of more spontaneous kinds of behaviors. [Copyright &y& Elsevier]

Abstract: In this paper, we analyze an algorithm to compute a low-rank approximation of the similarity matrix introduced by Blondel et al. in [1]. This problem can be reformulated as an optimization problem of a continuous function where S is constrained to have unit Frobenius norm, and is a non-negative linear map. We restrict the feasible set to the set of matrices of unit Frobenius norm with either k nonzero identical singular values or at most k nonzero (not necessarily identical) singular values. We first characterize the stationary points of the associated optimization problems and further consider iterative algorithms to find one of them. We analyze the convergence properties of our algorithm and prove that accumulation points are stationary points of . We finally compare our method in terms of speed and accuracy to the full rank algorithm proposed in [1]. [Copyright &y& Elsevier]

Abstract: Active detectors used as radiation monitors in space are not usually able to perform Particle Identification (PID). Common techniques need energy loss spectra with high statistics to estimate ion abundances. The ALTEA-space detector system is a set of silicon strip particle telescopes monitoring the radiation environment on board the International Space Station since July 2006 with real-time telemetry capabilities. Its large geometrical factor due to the concurrent use of six detectors permits the acquisition of good energy loss spectra even in a short period of observation. In this paper we present a novel Fast Probabilistic Particle Identification (FPPI) algorithm developed for the ALTEA data analysis in order to perform nuclear identification with low statistics and, with some limitations, also in real time. [Copyright &y& Elsevier]

Abstract: This paper presents a simple algorithm to generate all ordered trees with exactly vertices including exactly leaves. The best known algorithm generates such trees in time per tree, whereas our algorithm generates such trees in time per tree in the worst case. [Copyright &y& Elsevier]

Abstract: Comprehensive two-dimensional gas chromatography coupled to mass spectrometry is a powerful tool to analyze complex samples. For application of the technique in studies like biomarker discovery in which large sets of complex samples have to be analyzed, extensive preprocessing is needed to align the data obtained in several injections (analyses). We developed new alignment and clustering algorithms for this type of data. New in the current procedures is the consistent way in which the phenomenon referred to as wrap-around is treated. The data analysis problems associated with this phenomenon are solved by treating the 2D display as the surface of a three-dimensional cylinder. Based on this transformation we developed a new similarity metric for features as a function of both the cylindrical distance (reflecting similarity in chromatographic behavior) and of the mass spectral correlation (reflecting similarity in chemical structure). The concepts are used in warping and clustering, and include a protection against greedy warping. The methods were applied – for the purpose of an example – to the analysis of 11 replicates of a human urine sample concentrated by solid phase extraction. It is shown that the alignment is well protected against greedy warping which is important with respect to analytical qualities as robustness and repeatability. It is also demonstrated that chemically similar features are clustered together. The paper is organized as follows. First a brief introduction is provided addressing the background of the GC×GC–MS data structure followed by a theoretical section with a conceptual description of the procedures and details of the algorithms. Finally an example is given in the experimental section, illustrating the application of the procedures. [Copyright &y& Elsevier]

Abstract: In this paper, an algorithm based on boundary-line analysis is developed for the first time to directly recognize polygon shapes with or without concaved angles and without any pre-stored shape templates. The algorithm is also capable of quantitatively characterizing an irregular shape by calculating a similarity number between the subject shape and a comparison polygon shape that is automatically constructed based on the subject shape features. The algorithm first generates an r–L curve from the shape boundary line by plotting the distance (r) between a point on the shape boundary line and the shape center as a function of accumulated boundary length (L). The algorithm then performs first and second derivatives on the r-L curve to find all peak/valley positions, peak-to-peak and peak-to-valley distances. Thus, our algorithm can directly recognize a polygon shape, since the number of peaks equals the number of polygon sides and a peak-to-peak distance equals a polygon side length. In addition, the peak height defines the side''s relative orientation if there is no valley corresponding to a concaved angle on the shape. If some valleys are at concaved angles, the number of polygon sides equals the number of peaks plus the number of valleys at concaved angles, and the polygon side length equals the peak-to-valley distance for the valley at a concaved angle. Our algorithm identifies convex/concave angles based on the positive or negative value of the bend angle at the valley point. The algorithm is tested satisfactorily using idealized polygons and real particles of salt, sugar and pharmaceutical powders. [Copyright &y& Elsevier]

Abstract: This paper presents the design of a novel robot capable of climbing on vertical and rough surfaces, such as stucco walls. Termed CLIBO (claw inspired robot), the robot can remain in position for a long period of time. Such a capability offers important civilian and military advantages such as surveillance, observation, search and rescue and even for entertainment and games. The robot’s kinematics and motion, is a combination between mimicking a technique commonly used in rock climbing using four limbs to climb and a method used by cats to climb on trees with their claws. It uses four legs, each with four-degrees-of-freedom (4-DOF) and specially designed claws attached to each leg that enable it to maneuver itself up the wall and to move in any direction. At the tip of each leg is a gripping device made of 12 fishing hooks and aligned in such a way that each hook can move independently on the wall’s surface. This design has the advantage of not requiring a tail-like structure that would press against the surface to balance its weight. A locomotion algorithm was developed to provide the robot with an autonomous capability for climbing along the pre-designed route. The algorithm takes into account the kinematics of the robot and the contact forces applied on the foot pads. In addition, the design provides the robot with the ability to review its gripping strength in order to achieve and maintain a high degree of reliability in its attachment to the wall. An experimental robot was built to validate the model and its motion algorithm. Experiments demonstrate the high reliability of the special gripping device and the efficiency of the motion planning algorithm. [Copyright &y& Elsevier]

Abstract: This paper presents a non-homogeneous age-usage semi-Markov model with a measurable state space. Several probability functions useful to assess the system’s reliability are investigated. They satisfy the same family of equations we call indexed Markov renewal equations. Sufficient conditions to assure the existence and uniqueness of their solutions are provided. The numerical analysis of these equations is executed through the construction of a process discrete in time and space, which is shown to converge to the continuous one in the Skorohod topology. An algorithm useful for solving the discretized system of equations is presented by using a matrix representation. [Copyright &y& Elsevier]

Abstract: Since the empirical mode decomposition (EMD) lacks strict orthogonality, a new method for multicomponent signal decomposition, orthogonal empirical mode decomposition (OEMD), is proposed by this paper. The essential principle of this method is to obtain the intrinsic mode functions (IMFs) and the residue by self-adaptive band-pass filtering. Firstly, the feasibility of OEMD is theoretically analyzed, then its strict orthogonality and completeness is proved, and the orthogonal basis used in OEMD is generated. Secondly, the method of analytical band-pass filtering which preserves perfect band-pass feature in the frequency domain is presented, then two fast algorithms to implement OEMD are proposed, i.e. IMF sequential searching (ISS) algorithm and IMF binary searching (IBS) algorithm. The speed of IBS is faster than that of ISS, whereas IBS algorithm may obtain much more false IMFs than ISS when signals are of complex spectral constitutions. Finally, OEMD is applied to both synthetic signals and mechanical vibration signals, the results show that compared with EMD, OEMD better solves mode aliasing, avoids the occurrence of false mode, is free of end extension, and can be effectively applied to mechanical fault diagnosis. [Copyright &y& Elsevier]

Abstract: This paper presents a novel formulation for structural topology optimization in which both cost function and constraints are expressed in terms of an implicit design variable—the iso-line/surface threshold of a characteristic response function, such as a strain or mutual strain energy density function. A new material representation model is developed to implicitly describe material usage in a given design domain in terms of one implicit design variable. Based on the Karush–Kuhn–Tucker (KKT) necessary conditions, optimality criteria for finding solutions are established and then employed to develop a simple algorithm for one-material minimum mean compliance and compliant mechanism problems. The algorithm consists of sequentially moving iso-surface threshold (MIST) of chosen characteristic response function. Numerical examples are then presented to validate the proposed algorithm MIST for the minimum mean compliance, compliant mechanism, and fully stressed design problems. [Copyright &y& Elsevier]

Abstract: Advanced driver assistance systems represent considerable progress for improving the safety of vehicles on the road. One group of these systems is based on the detection of obstacles. If positive results are to be achieved these systems must be capable of taking a coherent decision as to which situations involve hazard, in order to avoid false alarms that lead to actions that are not only wrong but disturbing to other road users and cause the driver to lose faith in the system. This paper presents some algorithms to improve those already existing for detecting, identifying and characterising obstacles by means of a laserscanner. The major innovations are: (1) fusing the information from the laserscanner with a positioning system while taking account of the quality of the latter; (2) the criteria for locating obstacles (segmentation process), overcoming the limitations of other approaches that ignore the influence of the obstacle’s orientation; (3) the method of defining the characteristic axes of the obstacles, without resorting to tolerance values that are difficult to adjust or reducing the influence of distance measurement errors of the laserscanner. The algorithms were tested with on-track tests using a Sick LRS 1000 long-range laserscanner with satisfactory results being attained that were an improvement on those provided by other methods. [Copyright &y& Elsevier]

Abstract: In this paper, we propose a well targeted algorithm (GAS algorithm) for detecting communities in high clustered networks by presenting group action technology on community division. During the processing of this algorithm, the underlying community structure of a clustered network emerges simultaneously as the corresponding partition of orbits by the permutation groups acting on the node set are achieved. As the derivation of the orbit partition, an algebraic structure -cycle can be considered as the origin of the community. To be a priori estimation for the community structure of the algorithm, the community separability is introduced to indicate whether a network has distinct community structure. By executing the algorithm on several typical networks and the LFR benchmark, it shows that this GAS algorithm can detect communities accurately and effectively in high clustered networks. Furthermore, we compare the GAS algorithm and the clique percolation algorithm on the LFR benchmark. It is shown that the GAS algorithm is more accurate at detecting non-overlapping communities in clustered networks. It is suggested that algebraic techniques can uncover fresh light on detecting communities in complex networks. [ABSTRACT FROM AUTHOR]

Abstract: We developed backward and forward types of algorithms for estimating the vertical profiles of extinction coefficients at 532nm for three component aerosols (water-soluble, dust, and sea salt) using three-channel Mie-scattering lidar data of the backscatter (β) at 532 and 1064nm and the depolarization ratio (δ) at 532nm. While the water-soluble and sea-salt particles were reasonably assumed to be spherical, the dust particles were treated as randomly oriented spheroids to account for their nonsphericity. The introduction of spheroid models enabled us to more effectively use the three-channel data (i.e., 2β+1δ data) and to reduce the uncertainties caused by the assumption of spherical dust particles in our previously developed algorithms. We also performed an extensive sensitivity study to estimate retrieval errors, which showed that the errors in the extinction coefficient for each aerosol component were smaller than 30% (60%) for the backward (forward) algorithm when the measurement errors were ±5%. We demonstrated the ability of the algorithms to partition aerosol layers consisting of three aerosol components by applying them to shipborne lidar data. Comparisons with sky radiometer measurements revealed that the retrieved optical thickness and angstrom exponent of aerosols using the algorithms developed in this paper agreed well with the sky radiometer measurements (within 6%). [ABSTRACT FROM AUTHOR]

Abstract: Generalization is an important technique for protecting privacy in data dissemination. In the framework of generalization, ℓ-diversity is a strong notion of privacy. However, since existing ℓ-diversity measures are defined in terms of the most specific (rather than general) sensitive attribute (SA) values, algorithms based on these measures can have narrow eligible ranges for data that has a heavily skewed distribution of SA values and produce anonymous data that has a low utility. In this paper, we propose a new ℓ-diversity measure called the functional (τ, ℓ)-diversity, which extends ℓ-diversity by using a simple function to constrain frequencies of base SA values that are induced by general SA values. As a result, algorithms based on (τ, ℓ)-diversity may generalize SA values, thus are much less constrained by skew SA distributions. We show that (τ, ℓ)-diversity is more flexible and elaborate than existing ℓ-diversity measures. We present an efficient heuristic algorithm that uses a novel order of quasi-identifier (QI) values to achieve (τ, ℓ)-diversity. We compare our algorithm with two state-of-the-art algorithms that are based on existing ℓ-diversity measures. Our preliminary experimental results indicate that our algorithm not only provides a stronger privacy protection but also results in better utility of anonymous data. [ABSTRACT FROM AUTHOR]

Abstract: Introduction: Helicopter emergency medical services play a valuable role in the transfer of critically ill patients. This paper reviews the role of air ambulance services in the provision of regional burns care and suggests guidelines for their use. Methods: A retrospective review of patients treated at the Midlands Adult Burns Centre over a 3-year period. Results: 27 adult burns patients were transported by air ambulance during the study period. Patients were aged 19–89 years (average 41.3 years) with an estimated burn size of 5–70% TBSA. Distance travelled was 11–79miles (average 41.2miles). All patients were appropriately referred to the burns centre according to national referral guidelines but in 7 cases (26%) it was felt that transport by air ambulance was not clinically indicated and land transfer would have been safe and appropriate. Conclusion: Air ambulances offer a fast and effective means of transferring patients to a regional burns centre in selected cases. There is limited data for the beneficial effects of helicopters and survival benefit is seen only in the most severely injured patients. We suggest criteria for the use of air ambulances in burns patients in order to maximise the benefit and reduce unnecessary flights. [Copyright &y& Elsevier]

Abstract: The Ouroboros Model is a new conceptual proposal for an algorithmic structure for efficient data processing in living beings as well as for artificial agents. Its central feature is a general repetitive loop, where one iteration cycle sets the stage for the next. A monitoring process called “consumption analysis” yields valuable feedback for the optimum allocation of attention and resources, including the selective establishment of useful new memory entries. In this paper, it will be tried to show that the Ouroboros Model offers much promise to understand “whole brain” function, and that it fares well in the light of criteria for general artificial intelligence set forth over time. [ABSTRACT FROM AUTHOR]

This paper deals with the in-line optimization and control of the freeze-drying process of pharmaceuticals in vials. The proposed control system, named LyoDriver, uses a mathematical model of the process to calculate the values of the temperature of the heating fluid: the goal is to minimize the time required to get the desired amount of residual water in the dried product, and to maintain product temperature below the maximum allowed value, thus preserving product quality. The values of product temperature and residual ice content, as well as other parameters, are required to perform the calculations: these variables are estimated in-line by means of the Dynamic Parameters Estimation algorithm, an advanced tool based on the pressure rise test, but also other monitoring systems can be used. Two different control algorithms are presented and investigated by means of mathematical simulation and experiments carried out in a small industrial-type apparatus (LyoBeta 25 by Telstar). Results show the effectiveness of LyoDriver in a wide range of operating conditions, even when the process becomes mass-transfer controlled, or when the operating pressure is changed. © 2010 Wiley-Liss, Inc. and the American Pharmacists Association J Pharm Sci 99:4691-4709, 2010 [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]

A multi-period nonlinear programming (NLP) formulation is presented in this paper. This is intended to optimize energy and materials simultaneously for diesel hydrotreating units in order to minimize the total costs which include product income, material cost, energy cost, and other fixed operating costs. The heat exchanger network (HEN) is integrated into the model to address the energy consumption changes with the stream flow and temperature of different production modes. Some process models are regressed from production data or are supplied by refinery engineers, similar to the models for steam turbines and compressors, and distillation towers. An iterative algorithm is developed to solve the complex mathematical model based on HEN simulation. An industrial diesel hydrotreating unit is provided by the Chinese Refinery Complex and is used to demonstrate the performance of the formulated model and algorithm. It is found that the optimized results from the simultaneous consideration of the energy and materials are more profitable than those obtained from other methods that individually optimized the energy or materials. [ABSTRACT FROM AUTHOR]

Abstract: Belief revision, as one central problem in artificial intelligence, is of interest in decision-making and game theory. To deal with local belief change that is a desirable property for belief revision, a novel notion – the finest splitting was proposed by Parikh, Kourousias and Makinson, respectively. But it was not clear how to construct the finest splitting of a propositional theory (a closed set of propositional formulae). In this paper, we propose a constructive method, that is intractable generally, to compute the finest splitting of a propositional theory. We also propose a polynomial time algorithm to compute the finest splitting of a propositional theory consisting of clauses. As an application in the diagnosis theory, we show that, given a diagnosis system , it is quite easy to compute all of its diagnosis if the splitting of is pre-computed. Additionally, in terms of this approach, we can have more specific reason to interpret observation than the original 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: This paper presents an agglomerative hierarchical clustering algorithm for spatial data. It discovers clusters of arbitrary shapes which may be nested. The algorithm uses a sweeping approach consisting of three phases: sorting is done during the preprocessing phase, determination of clusters is performed during the sweeping phase, and clusters are adjusted during the post processing phase. The properties of the algorithm are demonstrated by examples. The algorithm is also adapted to the streaming algorithm for clustering large spatial datasets. [Copyright &y& Elsevier]

Abstract: In this paper, we study the properties of regular systems and improve the efficiency of the regular decomposition method RegSer implemented in Epsilon. We define a weaker concept which retains most properties of regular system. It can be shown that from a weak regular system one can also define a regular set and vice versa. We present an algorithm RecurWeakRegSer to decompose a given polynomial system into weak regular systems. When , the output of RecurWeakRegSer() often contains fewer components than that of RegSer(). This is one advantage of RecurWeakRegSer. Another one is that RecurWeakRegSer is more efficient than RegSer. This was shown by experiments that we carried out. Since it is an essential step in RegSer to compute subresultant polynomial remainder sequences (PRS), and there is some weakness in the implementation, we implement a new version of subresultant algorithm using the optimization strategy of Ducos so that the efficiency of RegSer can be improved. [Copyright &y& Elsevier]

Abstract: We consider a class of non-identical parallel-machine scheduling problems in which the goal is to minimize total (or mean) weighted (or unweighted) completion time. Models and relaxations are collected and classified in this paper. Heuristics and optimizing techniques are surveyed for the problems. And a few of interesting areas for future research are also provided. [Copyright &y& Elsevier]

Abstract: In this paper, we consider the behavioral pseudometrics for probabilistic systems, which are a quantitative analogue of probabilistic bisimilarity in the sense that the distance zero captures the probabilistic bisimilarity. The model we are interested in is probabilistic automata, which are based on state transition systems and make a clear distinction between probabilistic and nondeterministic choices. The pseudometrics are defined as the greatest fixpoint of a monotonic functional on the complete lattice of state metrics. A distinguished characteristic of this pseudometric lies in that it does not discount the future, which addresses some algorithmic challenges to compute the distance of two states in the model. We solve this problem by providing an approximation algorithm: up to any desired degree of accuracy , the distance can be approximated to within in time exponential in the size of the model and logarithmic in . One of the key ingredients of our algorithm is to express a pseudometric being a post-fixpoint as the elementary sentence over real closed fields, which allows us to exploit Tarski’s decision procedure, together with the binary search to approximate the behavioral distance. [Copyright &y& Elsevier]

Abstract: In this paper, we give an algorithm for solving linear systems of the Pascal matrices. The method is based on the explicit factorization of the Pascal matrices. The algorithm costs no multiplications and additions. The linear systems of the generalized Pascal matrices are also considered. Some examples are given. [Copyright &y& Elsevier]

Abstract: A new algorithm to find the phase equilibrium conditions in systems with specified values of internal energy, volume, and number of moles of each component present (isochoric–isoenergetic flash problem) is proposed. The core of the procedure consists of maximizing the system entropy by iterating on the values, in each phase, of internal energy, volume, and number of moles of each component. Analytical expressions for the physical properties and derivatives required by the calculations were generated by computer algebra. The algorithm tests for the possible need to add or remove phases during the course of iterations. The paper discusses possible numerical difficulties during application of the procedure and how to overcome them. The algorithm has shown to be robust and capable of solving multiphase equilibrium problems, avoiding trivial solutions. [Copyright &y& Elsevier]

Abstract: A set of vertices in a graph with no isolated vertices is a paired-dominating set of if every vertex of is adjacent to at least one vertex in and if the subgraph induced by contains a perfect matching. Let be a permutation graph and be its corresponding permutation. In this paper we present an time algorithm for finding a minimum cardinality paired-dominating set for a permutation graph with vertices and edges. [Copyright &y& Elsevier]

Abstract: Initial contact (IC) and toe off (TO) times are essential measurements in the analysis of temporal gait parameters, especially in cerebral palsy (CP) gait analysis. A new gait event detection algorithm, called the high pass algorithm (HPA) has been developed and is discussed in this paper. Kinematics of markers on the heel and metatarsal are used. Their forward components are high pass filtered, to amplify the contact discontinuities, thus the local extrema of the processed signal correspond to IC and TO. The accuracy and precision of HPA are compared with the gold standard of foot contact event detection, that is, force plate measurements. Furthermore HPA is compared with two other kinematics methods. This study has been conducted on 20 CP children and on eight normal adults. For normal subjects all the methods performed equally well. True errors in HPA (mean±standard deviation) were found to be 1±23ms for IC and 2±25ms for TO in CP children. These results were significantly (p <0.05) more accurate and precise than those obtained using the other algorithms. Moreover, in the case of pathological gaits, the other methods are not suitable for IC detection when IC is flatfoot or forefoot. In conclusion, the HPA is a simple and robust algorithm, which performs equally well for adults and actually performs better when applied to the gait of CP children. It is therefore recommended as the method of choice. [Copyright &y& Elsevier]

Abstract: In this paper, we introduce a new algorithm for a system for generalized nonlinear variational inequalities in Banach spaces by using convergence of the generalized projection methods. Our results extend and improve the results of Fan [J.H. Fan, A Mann type iterative scheme for variational inequalities in noncompact subsets of Banach spaces, J. Math. Anal. Appl. 337 (2007) 1041–1047], Li [J. Li, On the existence of solutions of variational inequalities in Banach spaces, J. Math. Anal. Appl. 295 (2004) 115–126], Verma [R.U. Verma, Projection methods, algorithms and a new system of nonlinear variational inequalities, Comput. Math. Appl. 41 (2001) 1025–1031] and many others. [Copyright &y& Elsevier]

Abstract: This paper proposes an algorithm for ultrasonic distance measurement applications. In order to estimate the time-of-flight (ToF), an analytic process is developed based on the mathematical model of the ultrasonic envelope signal improving some previous methods by extrapolation and characterization of this envelope function using analytical parameters. An architecture based on a digital signal processor has been implemented to excite the ultrasonic transducer with a burst of 40kHz. The ultrasonic analogical echo is acquired at 500kHz. The results indicate a significant improvement over other similar strategies, allowing a optimized implementation for applications such as mobile robots. [Copyright &y& Elsevier]