Search

The paper considers algorithms for solving inverse scattering problems based on the discretization of the Gelfand–Levitan–Marchenko integral equations, associated with the system of nonlinear Schrödinger equations of the Manakov model. The numerical algorithm of the first order approximation for solving the scattering problem is reduced to the inversion of a series of nested block Toeplitz matrices using the Levinson-type bordering method. Increasing the approximation accuracy violates the Toeplitz structure of block matrices. Two algorithms are described that solve this problem for second order accuracy. One algorithm uses a block version of the Levinson bordering algorithm, which recovers the Toeplitz structure of the matrix by moving some terms of the systems of equations to the right-hand side. Another algorithm is based on the Toeplitz decomposition of an almost block-Toeplitz matrix and the Tyrtyshnikov bordering algorithm. The speed and accuracy of calculations using the presented algorithms are compared on an exact solution (the Manakov vector soliton). [ABSTRACT FROM AUTHOR]

A good stacking method can increase the packaging utility rate and reduce production costs. Much research has focused on 2D arrangements for rectangular, circular, or irregular shapes and regularly shaped 3D objects such as rectangular boxes. Genetic algorithms, simulated annealing, and other heuristic algorithms have been proposed. Recent research on the stacking of irregular-shaped 3D stone pieces has focused on balancing one stone piece on top of others to form one or more vertical towers, given the geometry of the stone pieces and the number of stone pieces available for the task. Stacking irregular-shaped 3D objects in a package is common in industry. However, there has been relatively little emphasis on the development of algorithms for stacking irregular-shaped 3D objects in a fixed-size container without prior knowledge of the stone geometries and the number of pieces available, with the goal of packing as many stone pieces as possible while maintaining stability. In this paper, three heuristic algorithms are proposed to solve the problem of nesting irregularly shaped stone pieces in layers within a container. All three algorithms use the following approach: (1) approximate the alignment of irregular shapes to a cluster of straight lines; (2) arrange stones one by one at the approximated angles using a step-by-step process; (3) for stability, consider the weight of the stone pieces based on pixel calculations. An automated real-time stacking system—including sensors, pneumatic suction cups, webcams, conveyor, robot, and programmable logic controller—was developed to evaluate the proposed algorithms using space utilization, stability, and cycle time as measures of performance. The developed algorithms and an existing stacking algorithm (bottom left most, or BLM) were tested using 25 sequences of 30 randomly ordered stone pieces. Results suggest that the developed algorithms effectively solve the stone piece packing problem. All three were significantly better than the BLM algorithm in terms of space utilization and stability, and there was no difference in cycle time. Algorithm 3 was better than Algorithms 1 and 2. [ABSTRACT FROM AUTHOR]

Some efficient top-k algorithms, i.e., Fagin's Algorithm, threshold algorithm (TA), and best position algorithm (BPA), can be used to answer k nearest neighbor (kNN) queries. However, extending the existing algorithms without further changes to the algorithms themselves would not be efficient since there are the different characteristics between the kNN queries and top-k queries. For example, the kNN queries are more distance-sensitive rather than the position of data points. Second, it is necessary to add some novel parallel heuristics and pruning policies for the kNN queries. Third, there are still many redundant random accesses among FA, TA, and BPA. In this paper, we address aforementioned these problems and take these algorithms to answer parallel kNN (PkNN) queries in spatial databases. We integrate the advantages of the B + -tree and Open MP programming and propose three efficient parallel kNN query algorithms, namely distance priority-based PkNN, optimized PkNN, and partition-based PkNN. Our performance evaluation shows that our proposed algorithms achieve significant improvement in comparison with existing algorithms, i.e., BPA and BPA2. In addition, our approaches are also capable of returning kNN results incrementally which greatly shorten the query response time and enhance user experience. [ABSTRACT FROM AUTHOR]

A graph is said to be two connected if between every pair of nodes there are at least two node-disjoint paths. Given weights on the edges of the graph, the two connected subgraph problem is to find a two connected spanning subgraph of G whose weight is minimum. This problem has many applications in telecommunications. In this paper we consider a new variant of this problem with additional disjunctive constraints (called also conflict constraints) related to the survivability of telecommunication networks. This can be called the Disjunctive Two-Connected Subgraph Problem (DTCSP). First, we give an extended formulation for the problem whose variables are the cycles of the graph. Then, we use a column generation algorithm to solve its linear relaxation, and further show that the pricing reduces to finding a specific cycle in the graph which can be formulated as an integer programming problem. We also describe several valid inequalities for the polytope. Moreover, we study the related separation problems and devise separation routines for these inequalities. Using this, we devise a Branch-and-Cut-and-Price algorithm for the problem along with an extensive experimental study. [ABSTRACT FROM AUTHOR]

We propose a dead-end control algorithm for the exact solution of NP-hard combinatorial optimization problems. The efficiency of the algorithm is demonstrated by examples of solving the set-partition and 0-1 knapsack problems. The paper also shows that the use of the idea of dead-end controls when implementing the dynamic programming method can considerably reduce the number of problem state variables at each optimization step. A comparative analysis of the proposed method with known algorithms for solving these problems is carried out. [ABSTRACT FROM AUTHOR]

The decision making of a suitable heating, ventilating and air conditioning system's set-point temperature is an energy and environmental challenge in our society. In the present paper, a general framework to define such temperature based on a dynamic adaptive comfort algorithm is proposed. Due to the fact that the thermal comfort of the occupants of a building has different ranges of acceptability, this method is applied to learn such comfort temperature with respect to the running mean temperature and therefore to decide the suitable range of indoor temperature. It is demonstrated that this solution allows to dynamically build an adaptive comfort algorithm, an algorithm based on the human being's thermal adaptability, without applying the traditional theory. The proposed methodology based on the K-Nearest-Neighbour algorithm was tested and compared with data from an experimental thermal comfort field study carried out in a mixed mode building in the south-western area of Spain and with the Support Vector Machine method. The results show that K-Nearest-Neighbour algorithm represents the pattern of thermal comfort data better than the traditional solution and that it is a suitable method to learn the thermal comfort area of a building and to define the set-point temperature for a heating, ventilating and air-conditioning system. [ABSTRACT FROM AUTHOR]

In this paper, we consider the problem of constructing a correction algorithm with the aim of increasing the adaptive properties of the ΣΠ-neuron, relying solely on the structure of the ΣΠ-neuron itself. To build the corrector, the logical-algebraic method of data analysis is used. Comparison of the advantages of the neural network approach and the logical-algebraic method suggests that a combined approach to the organization of the neural network improves its efficiency and allows one to build a set of rules that reveal hidden patterns in a given subject area, thus improving the quality of the recognition system. [ABSTRACT FROM AUTHOR]

Purpose: Fractures of the femoral shaft in children are common. The rates of bone growth and remodeling in children vary according to their ages, which affect their respective management. Methods: This paper evaluates the incidence and patterns of pediatric femoral shaft fracture and the current concepts of treatments available. Results: The type of fracture—closed or open; stable or unstable—needs to be taken into account. Child abuse should be suspected in fractures sustained by infants. For younger children, non-surgical management is preferred, which include Pavlik harness (< 6 months old) and early spica casting (6 months to 6 years old). Older children (> 6 years old) usually benefit from surgical treatments as outcomes of non-surgical alternatives are worse and are associated with prolonged recovery times. These operative measures for older children that are 6–12 years old include elastic stable intramedullary nailing and submuscular plating. Factors to be considered when devising an appropriate intervention include body mass, location of injury, and nature of fracture. For adolescent and skeletally mature teenagers (> 12 years old), rigid antegrade entry intramedullary fixation is indicated. In the event of open fractures or polytrauma, external fixation should be considered as a temporary treatment method for initial fracture stabilization. Conclusion: An age-based and evidence-based algorithm has been proposed to guide surgeons in the process of evaluating an appropriate treatment. [ABSTRACT FROM AUTHOR]

Node similarity search on graphs has wide applications in recommendation, link prediction, to name just a few. However, existing studies are insufficient due to two reasons: (i) the scale of the real-world graph is growing rapidly, and (ii) vertices are always associated with complex attributes. In this paper, we propose an efficiently distributed framework to support node similarity search on massive graphs, which considers both graph structure correlation and node attribute similarity in metric spaces. The framework consists of preprocessing stage and query stage. In the preprocessing stage, a parallel KD-tree construction (KDC) algorithm is developed to form a newly defined graph so-called hybrid graph, in order to integrate node attribute similarity into the original graph. To equally divide graph vertices into subsets, KDC adopts the KD-tree partitioning after the pivot mapping. In addition, two metric pruning rules and an optimized allocation strategy are presented to reduce communication and computation costs. In the query stage, based on the formed hybrid graph, we develop similarity search methods using random walk with restart (RWR) to measure node similarity. To boost efficiency, we derive tight bounds to rapidly shrink the search region. Extensive experiments with three real massive graphs are conducted to verify the effectiveness, efficiency, and scalability of our proposed techniques. [ABSTRACT FROM AUTHOR]

Classification accuracy provided by a machine learning model depends a lot on the feature set used in the learning process. Feature selection (FS) is an important and challenging preprocessing technique which helps to identify only the relevant features from a dataset, thereby reducing the feature dimension as well as improving the classification accuracy at the same time. The binary version of whale optimization algorithm (WOA) is a popular FS technique which is inspired from the foraging behavior of humpback whales. In this paper, an embedded version of WOA called embedded chaotic whale survival algorithm (ECWSA) has been proposed which uses its wrapper process to achieve high classification accuracy and a filter approach to further refine the selected subset with low computation cost. Chaos has been introduced in the ECWSA to guide selection of the type of movement followed by the whales while searching for prey. A fitness-dependent death mechanism has also been introduced in the system of whales which is inspired from the real-life scenario in which whales die if they are unable to catch their prey. The proposed method has been evaluated on 18 well-known UCI datasets and compared with its predecessors as well as some other popular FS methods. The source code of ECWSA can be found in https://github.com/Ritam-Guha/ECWSA. [ABSTRACT FROM AUTHOR]

This paper deals with the problem of finding the generators of the solution space for a system of inequalities A ⊗ x ≥ x in max-plus algebra. It provides an improved algorithm which can be used to find a smaller set of generators for the solution space by skipping a large number of invalid generators. [ABSTRACT FROM AUTHOR]

This paper presents two algorithms. The first decides the existence of a pointed homotopy between given simplicial maps f , g : X → Y , and the second computes the group [ Σ X , Y ] ∗ of pointed homotopy classes of maps from a suspension; in both cases, the target Y is assumed simply connected. More generally, these algorithms work relative to A ⊆ X . [ABSTRACT FROM AUTHOR]

In recent years, the backward trajectory model has been widely used in the research of meteorological and atmospheric environmental quality. This paper presents a comprehensive study on a stepwise clustering analysis algorithm in the clustering process of backward trajectory model and an application of the clustering analysis of single-particle backward trajectory in 2016 in Changchun City. This study starts with an analysis of the original stepwise clustering algorithm and its application to a clustering process of 8784 backward trajectories during 48 h in Changchun City as a benchmark test case. Then, two improvements are made in the algorithm: First, in the process of finding the optimal classification, the algorithm complexity is improved from original O(n3) to O(log(n)*n2) through algorithm improvement. The algorithm performance is enhanced by log(n) times. Second, in the process of re-establishing the classification, the algorithm complexity is improved from the original O(m*n2) to O(m*log(n)*n), that is another algorithm performance improvement by a factor of log(n). Therefore, the accumulative execution efficiency improvement through the algorithm optimization is 2*log(n) times, which has been further verified in the practical application in Changchun City. [ABSTRACT FROM AUTHOR]

In this paper, we propose and analyse a new unbiased stochastic approach for solving a class of integral equations. We study and compare the proposed unbiased approach against the known biased Monte Carlo method based on evaluation of truncated Liouville-Neumann series. We also compare the proposed algorithm against the deterministic Nystrom method. Extensions of the unbiased method for the weak and global solutions are described. Extensive numerical experiments have been performed to support the theoretical studies regarding the convergence of the unbiased algorithms. The results are compared to the best known biased Monte Carlo algorithms for numerical integration done in our previous studies. Conclusions about the applicability and efficiency of the proposed algorithms have been drawn. [ABSTRACT FROM AUTHOR]

This paper substantiates the urgency of developing theoretical foundations, methods, and algorithms for cryptographic protection of color image pixels using problem-oriented multifunctional data structuring and representing codes of color image pixels in the Rademacher, Chrestenson, Rademacher–Chrestenson, Haar–Chrestenson, and Galois systems and investigates the possibility of increasing the operating speed of algorithms for transforming, processing, and recognizing digital images using the modular arithmetic of residue number systems based on the mathematics of arithmetic operations of a non-positional residue number system. [ABSTRACT FROM AUTHOR]

This paper presents a new algorithm estimating structural equation models by using the generalized structured component analysis (GSCA) formulation. In GSCA models, the latent variables are composites. The weights are estimated in conjunction with the other model parameters, optimizing a genuine least squares criterion. The new algorithm is designed for three subclasses often used in applications. Linear regressions are alternated for different sets of parameters according to the nonlinear manner in which the parameters are incorporated in the model. The new algorithm is compared with two existing ones by using different examples from the literature, as well as simulations. On the average the proposed algorithm produces better criterion values compared to the other two ones. [ABSTRACT FROM AUTHOR]

Purpose: Antipsychotics (APs) are commonly used to manage neuropsychiatric symptoms (NPS) in elderly patients with dementia, even though several large studies have demonstrated an association between AP treatment and increased morbidity and mortality in people with dementia. The aim of this study is to review the scientific literature of the use of AP in the elderly with dementia and to propose an algorithm to assist in decision-making regarding the withdrawal of APs. Methods: A computerized literature search (MEDLINE: 1966 to December 2016, EMBASE: 1982 to December 2016) was used to locate relevant literature. Keywords in the search included terms from Medical Subject Headings (MESH) and EMBASE thesaurus (EMTREE). The following terms were used in the MESH database and EMTREE thesaurus: Aged, Antipsychotic Agents, Behavioral Symptoms and Dementia. Results: Earlier studies of APs used in elderly patients with dementia suggest that, in most elderly demented patients, APs can be withdrawn with no effect on behaviour. These patients are likely to benefit from the algorithm we propose to assist clinicians in the withdrawal of APs. Conclusions: In this paper, we review the potential risks and benefits of discontinuing AP treatment in elderly demented patients with NPS and propose an algorithm to assist in decision-making regarding AP withdrawal. [ABSTRACT FROM AUTHOR]

Scheduling of jobs and resources on a shop floor is an ever green optimization problem. Job shop scheduling problem (JSSP) is an allocation of 'n' jobs on 'm' machines so as to complete processing of all jobs in a minimum possible time. The JSSP has been addressed by various direct, indirect methods, programs, and algorithms in the last 40 year of literature. This paper presents a new paradigm of invasive weed optimization which mimics the process of weed colonization and distribution to solve JSSPs. The algorithm had shown encouraging and promising outputs on standard benchmarking problems. [ABSTRACT FROM AUTHOR]

Cluster analysis as an important function of the data mining has made great progress in recent years a series of methods for analysis of accuracy provides a solid foundation. This paper proposes the novel pattern clustering algorithm based on particle swarm optimization joint adaptive wavelet neural network model. Nonlinear adaptive filter has the stronger ability of that signal processing. However, due to complicated calculation of the nonlinear adaptive filter, the actual use of linear adaptive filter is still. To deal with this challenge, we integrate the wavelet neural network for modification. Usually, the wavelet neural network learning process using the gradient descent method, even if the error function that along the negative gradient direction, and which requires the step length direction along the negative gradient direction. As well, we revise the PSO to enhance the wavelet NN in the process of search, the equilibrium relation between the global search ability and local search ability for the success of the algorithm plays an important role. With this modification, our method obtains the better performance. The experimental result shows the feasibility and the effectiveness of the method compared with the other latest and state-of-the-art methods. [ABSTRACT FROM AUTHOR]

In the paper, we introduce a class of delay differential variational inequalities consisting of a system of delay differential equations and variational inequalities. The existence conclusion of Carathéodory's weak solution for delay differential variational equalities is obtained. Furthermore, an algorithm for solving the delay differential variational inequality is shown, and the convergence analysis for the algorithm is given. Finally, a numerical example is given to verify the validity of the algorithm. [ABSTRACT FROM AUTHOR]

In this paper, we introduce a new method to analyze the convergence of the standard finite element method for the noncoercive impulse control quasi-variational inequality (QVI). L convergence of the approximation is derived as a result of the geometrical convergence of a Bensoussan-Lions algorithm type and uniform error estimate between the continuous algorithm and its finite element counterpart. This approach is completely different from the one inroduced in [2] as it enables us to derive the error estimate through a computational iterative scheme. [ABSTRACT FROM AUTHOR]

As an increase in gastroesophageal reflux disease (GERD) has been reported in Japan, and public interest in GERD has been increasing, the Japanese Society of Gastroenterology published the Evidence-based Clinical Practice Guidelines for GERD (1st edition) in 2009. Six years have passed since its publication, and there have been a large number of reports in Japan concerning the epidemiology, pathophysiology, treatment, and Barrett's esophagus during this period. By incorporating the contents of these reports, the guidelines were completely revised, and a new edition was published in October 2015. The revised edition consists of eight items: epidemiology, pathophysiology, diagnosis, internal treatment, surgical treatment, esophagitis after surgery of the upper gastrointestinal tract, extraesophageal symptoms, and Barrett's esophagus. This paper summarizes these guidelines, particularly the parts related to the treatment for GERD. In the present revision, aggressive proton pump inhibitor (PPI) maintenance therapy is recommended for severe erosive GERD, and on-demand therapy or continuous maintenance therapy is recommended for mild erosive GERD or PPI-responsive non-erosive GERD. Moreover, PPI-resistant GERD (insufficient symptomatic improvement and/or esophageal mucosal break persisting despite the administration of PPI at a standard dose for 8 weeks) is defined, and a standard-dose PPI twice a day, change in PPI, change in the PPI timing of dosing, addition of a prokinetic drug, addition of rikkunshito (traditional Japanese herbal medicine), and addition of histamine H2-receptor antagonist are recommended for its treatment. If no improvement is observed even after these treatments, pathophysiological evaluation with esophageal impedance-pH monitoring or esophageal manometry at an expert facility for diseases of the esophagus is recommended. [ABSTRACT FROM AUTHOR]

Persistent homology with coefficients in a field $$\mathbb {F}$$ coincides with the same for cohomology because of duality. We propose an implementation of a recently introduced algorithm for persistent cohomology that attaches annotation vectors with the simplices. We separate the representation of the simplicial complex from the representation of the cohomology groups, and introduce a new data structure for maintaining the annotation matrix, which is more compact and reduces substantially the amount of matrix operations. In addition, we propose a heuristic to simplify further the representation of the cohomology groups and improve both time and space complexities. The paper provides a theoretical analysis, as well as a detailed experimental study of our implementation and comparison with state-of-the-art software for persistent homology and cohomology. [ABSTRACT FROM AUTHOR]

In the arsenal of resources for computer memory system performance improvement, predictors have gained an increasing role in the past years. They can suppress latencies when accessing cache or main memory. In our previous work we considered using predictors to decrease Synchronized Dynamic Random Access Memory (SDRAM) latency. If one wants to apply several predictors at the same time, there has to exist proper synchronization of the predictors. This stems from the fact that SDRAM controller has to activate and update each of the predictors at proper times, while at the same time executing standard SDRAM commands, such as opening/closing rows, accessing columns, etc. In this paper we propose a universal synchronization algorithm for predictors for SDRAM memories, which can be used with practically any predictor, regardless of its specific method of predicting, and with very little or no modifications. [ABSTRACT FROM AUTHOR]

We introduce algorithms for the computation of homology, cohomology, and related operations on cubical cell complexes, using the technique based on a chain contraction from the original chain complex to a reduced one that represents its homology. This work is based on previous results for simplicial complexes, and uses Serre's diagonalization for cubical cells. An implementation in C++ of the introduced algorithms is available at together with some examples. The paper is self-contained as much as possible, and is written at a very elementary level, so that basic knowledge of algebraic topology should be sufficient to follow it. [ABSTRACT FROM AUTHOR]

Advanced forging simulation codes leads die designer toward more efficient methods in waste material reduction. In this paper, an approach has been presented to reduce waste material by controlling material flow with variable gutter. Initially, an algorithm is offered for decision making. A control criterion (δ) has been suggested in order to determine the new modified gutter thickness and width. A new formula has been offered to calculate the new dimensions of gutter width and thickness base on (δ) criterion in each step. To evaluate the effectiveness of the proposed criterion and formula a set of Finite volume and finite element simulations has been done on different forging parts. Then a 'T shape' part has been chosen as a case study to investigate the effect of variable gutter width method and variable gutter thickness method separately. The FVM and FEM simulation results for variable thickness and width show a waste material reduction of 12% and 14%, respectively. Finally an experimental test has been setup to verify the simulation result of variable gutter thickness method. The simulation and experimental results have a good agreement. [ABSTRACT FROM AUTHOR]

The k-distance domination problem is to find a minimum vertex set D of a graph such that every vertex of the graph is either in D or within distance k from some vertex of D, where k is a positive integer. In the present paper, by using labeling method, a linear-time algorithm for k-distance domination problem on block graphs is designed. [ABSTRACT FROM AUTHOR]

Bat algorithm (BA) is a new stochastic optimization technique for global optimization. In the paper, we introduce both simulated annealing and Gaussian perturbations into the standard bat algorithm so as to enhance its search performance. As a result, we propose a simulated annealing Gaussian bat algorithm (SAGBA) for global optimization. Our proposed algorithm not only inherits the simplicity and efficiency of the standard BA with a capability of searching for global optimality, but also speeds up the global convergence rate. We have used BA, simulated annealing particle swarm optimization and SAGBA to carry out numerical experiments for 20 test benchmarks. Our simulation results show that the proposed SAGBA can indeed improve the global convergence. In addition, SAGBA is superior to the other two algorithms in terms of convergence and accuracy. [ABSTRACT FROM AUTHOR]