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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]

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]

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]

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 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 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]

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]

Springback is the most common defect in sheet metal forming, especially for the advanced high-strength steel (AHSS) parts. The compensation method is an effective way to overcome this defect by modifying the die-face. A new geometrical springback compensation algorithm based on the advanced displacement adjustment (DA) method is proposed in this paper for automobile AHSS parts. The die-face is reconstructed by the non-uniform rational B-spline surface with the advantage of UV curves; furthermore, the continuity and topology of the die-face are also studied. The high-quality geometry compensation die-face obtained from this algorithm can be directly applied to actual machining. To reduce the time and cost of the die manufacturing, this algorithm is seamlessly integrated into the CATIA platform. A new compensation user-defined feature is created, which can meet the need for iterative compensation and parametric association. At the end of this paper, two engineering examples of AHSS parts verify the feasibility and validity of this algorithm and system. [ABSTRACT FROM AUTHOR]

This paper describes an algorithm to compute the law of the Lie algebra $\mathfrak{g}_{n}$ associated with the Lie group G, formed of all the n× n upper-unitriangular matrices. The goal of this paper is to show the algorithm that computes the law of $\mathfrak{g}_{n}$ and its implementation using the symbolic computation package MAPLE. In addition, the complexity of the algorithm is described. [ABSTRACT FROM AUTHOR]

Recently, a multiple-material stereolithography (MMSL) system was introduced, which included the novel feature of stacking different photocurable resins to produce a multiple-material part. This process is capable of fabricating intricately detailed parts with smooth surface finish and internal structures of various colors. However, the MMSL system requires a washing process when switching materials, and this additional step increases the fabrication time and also introduces deformations in the build structure as registration errors accumulate. Consequently, reducing the number of material changeovers in this process is a priority, and the minimum number of changeovers is imposed in part by the sweep interference between layers of different materials. Fortunately, the use of low-viscosity resins permits possible fabrication without sweeping. As a result, multiple layers of one material can be continuously built without changing resins, and subsequently, a different low-viscosity material can be added without resulting in sweep obstruction with the original layers. In this paper, a stacking simulation, which determines the maximum number of layers possible to be continuously built between material changeovers, is described. This paper presents a novel interference-detection algorithm, which identifies interference by inspecting the overlap between loop segments. In addition, the algorithm successfully manages the triangulation errors that occur at a curved surface when two materials are adjacent within a layer. Finally, several practical examples are shown to verify the algorithm and provide compelling evidence that the proposed algorithm is effective and applicable in MMSL. [ABSTRACT FROM AUTHOR]

The lack of effective and efficient schedule-based pathfinding algorithms for transit networks has limited the application of GIS in transit trip planning services. This paper introduces a schedule-based path finding algorithm for transit networks. Based on a pattern-centered spatiotemporal transit network model, the algorithm searches the network by following route patterns. A pattern is a spatial layout of a route in transit terminology. A route usually has many patterns to serve various locations at different times. This path search algorithm is significantly different from traditional shortest path algorithms that are based on adjacent node search. By establishing a set of lemmas and theorems the paper proves that paths generated by the PFS algorithm are schedule-coordinated fastest paths for trips with given constraints. After analyzing computation and database query complexities of the algorithm the paper indicates that the PFS is efficient in computation and database query. Finally, effectiveness and efficiency of the algorithm are demonstrated by implementations in GIS-based online transit trip planners in Wisconsin, US. [ABSTRACT FROM AUTHOR]

The hypercube, or n-cube, has been widely used as the interconnection network in parallel computers. However, the major drawback of the hypercube is the increase in the number of communication links for each node with the increase in the total number of nodes in the system. This paper introduces a new interconnection network, namely dual-cube, for large-scale parallel computers and describes the algorithms for efficient collective communications in dual-cube. The dual-cube network mitigates the problem of increasing number of links in the large-scale hypercube network while retains hypercube’s topological properties. Design of efficient routing algorithms for collective communications is the key issue for any interconnection network. In this paper, we show that the collective communications can be done in dual-cube with almost the same communication times as in hypercube. [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]

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]

This work focuses on the most commonly used binarization method: Sauvola's. It performs relatively well on classical documents, however, three main defects remain: the window parameter of Sauvola's formula does not fit automatically to the contents, it is not robust to low contrasts, and it is not invariant with respect to contrast inversion. Thus, on documents such as magazines, the contents may not be retrieved correctly, which is crucial for indexing purpose. In this paper, we describe how to implement an efficient multiscale implementation of Sauvola's algorithm in order to guarantee good binarization for both small and large objects inside a single document without adjusting manually the window size to the contents. We also describe how to implement it in an efficient way, step by step. This algorithm remains notably fast compared to the original one. For fixed parameters, text recognition rates and binarization quality are equal or better than other methods on text with low and medium x-height and are significantly improved on text with large x-height. Pixel-based accuracy and OCR evaluations are performed on more than 120 documents. Compared to awarded methods in the latest binarization contests, Sauvola's formula does not give the best results on historical documents. On the other hand, on clean magazines, it outperforms those methods. This implementation improves the robustness of Sauvola's algorithm by making the results almost insensible to the window size whatever the object sizes. Its properties make it usable in full document analysis toolchains. [ABSTRACT FROM AUTHOR]

Hierarchical hypercubes (HHC), also known as cube-connected cubes, have been introduced in the literature as an interconnection network for massively parallel systems. Effectively, they can connect a large number of nodes while retaining a small diameter and a low degree compared to a hypercube of the same size. Especially (2+ m)-dimensional hierarchical hypercubes ( $\mathit {HHC}_{2^{m}+m}$), called perfect HHCs, are popular as they are symmetrical, which is a critical property when designing routing algorithms. In this paper, we describe an algorithm finding, in an $\mathit{HHC}_{2^{m}+m}$, mutually node-disjoint paths connecting k=⌈( m+1)/2⌉ pairs of distinct nodes. This problem is known as the k-pairwise disjoint-path routing problem and is one of the important routing problems when dealing with interconnection networks. In an $\mathit{HHC}_{2^{m}+m}$, our algorithm finds paths of lengths at most 2+ m(2+1)+4 in O(2) time, where 2 is the diameter of an $\mathit{HHC}_{2^{m}+m}$. Also, we have shown through an experiment that, in practice, the lengths of the generated paths are significantly lower than the worst-case theoretical estimations. [ABSTRACT FROM AUTHOR]

The m-machine no-wait flowshop scheduling problem, with the objective of minimizing total completion time subject to the constraint that makespan has to be less than or equal to a certain value, is addressed in this paper. First, an algorithm is proposed to find an upper bound on the makespan in case the upper bound is not given or unknown. Given the upper bound on makespan, a proposed algorithm ( PAL) with five versions L (1, 5, 10, 15, and 20) and a genetic algorithm ( GA) are utilized for solving the problem. Furthermore, a dominance relation is established for the case of four machines. The five versions of PAL and GA are evaluated on randomly generated problems with different number of jobs and number of machines. Computational experiments show that the errors of PA10, PA15, and PA20 are much smaller than that of GA while the CPU times of PA10, PA15, and PA20 are significantly smaller than that of GA. Therefore, the algorithms PA10, PA15, and PA20 are superior to the GA algorithm. [ABSTRACT FROM AUTHOR]

Small Footprint LiDAR (Light Detection And Ranging) has been proposed as an effective tool for measuring detailed biophysical characteristics of forests over broad spatial scales. However, by itself LiDAR yields only a sample of the true 3D structure of a forest. In order to extract useful forestry relevant information, this data must be interpreted using mathematical models and computer algorithms that infer or estimate specific forest metrics. For these outputs to be useful, algorithms must be validated and/or calibrated using a sub-sample of 'known' metrics measured using more detailed, reliable methods such as field sampling. In this paper we describe a novel method for delineating and deriving metrics of individual trees from LiDAR data based on watershed segmentation. Because of the costs involved with collecting both LiDAR data and field samples for validation, we use synthetic LiDAR data to validate and assess the accuracy of our algorithm. This synthetic LiDAR data is generated using a simple geometric model of Loblolly pine ( Pinus taeda) trees and a simulation of LiDAR sampling. Our results suggest that point densities greater than 2 and preferably greater than 4 points per m2 are necessary to obtain accurate forest inventory data from Loblolly pine stands. However the results also demonstrate that the detection errors (i.e. the accuracy and biases of the algorithm) are intrinsically related to the structural characteristics of the forest being measured. We argue that experiments with synthetic data are directly useful to forest managers to guide the design of operational forest inventory studies. In addition, we argue that the development of LiDAR simulation models and experiments with the data they generate represents a fundamental and useful approach to designing, improving and exploring the accuracy and efficiency of LiDAR algorithms. [ABSTRACT FROM AUTHOR]

Multi-traveling salesman problem (MTSP) is an extension of traveling salesman problem, which is a famous NP hard problem, and can be used to solve many real world problems, such as railway transportation, routing and pipeline laying. In this paper, we analyze the general properties of MTSP, and find that the multiple depots and closed paths in the graph is a big issue for MTSP. Thus, a novel method is presented to solve it. We transform a complicated graph into a simplified one firstly, then an effective algorithm is proposed to solve the MTSP based on the simplified results. In addition, we also propose a method to optimize the general results by using 2-OPT. Simulation results show that our method can find the global solution for MTSP efficiently. [ABSTRACT FROM AUTHOR]

Background: Searching for substructures in molecules belongs to the most elementary tasks in cheminformatics and is nowadays part of virtually every cheminformatics software. The underlying algorithms, used over several decades, are designed for the application to general graphs. Applied on molecular graphs, little effort has been spend on characterizing their performance. Therefore, it is not clear how current substructure search algorithms behave on such special graphs. One of the main reasons why such an evaluation was not performed in the past was the absence of appropriate data sets. Results: In this paper, we present a systematic evaluation of Ullmann's and the VF2 subgraph isomorphism algorithms on molecular data. The benchmark set consists of a collection of 1235 SMARTS substructure expressions and selected molecules from the ZINC database. The benchmark evaluates substructures search times for complete database scans as well as individual substructure-molecule pairs. In detail, we focus on the influence of substructure formulation and size, the impact of molecule size, and the ability of both algorithms to be used on multiple cores. Conclusions: The results show a clear superiority of the VF2 algorithm in all test scenarios. In general, both algorithms solve most instances in less than one millisecond, which we consider to be acceptable. Still, in direct comparison, the VF2 is most often several folds faster than Ullmann's algorithm. Additionally, Ullmann's algorithm shows a surprising number of run time outliers. [ABSTRACT FROM AUTHOR]

In the next decade, the high-performance supercomputers will consist of several millions of CPUs. The interconnection networks in such supercomputers play an important role for achieving high performance. In this paper, we introduce the Metacube (MC), a versatile family of interconnection network that can connect an extremely large number of nodes with a small number of links per node and keep the diameter rather low. An MC network has a 2-level hypercube structure. An MC( k, m) network can connect $2^{2^{k}m+k}$ nodes with m+ k links per node, where k is the dimension of the high-level hypercubes (classes) and m is the dimension of the low-level hypercubes (clusters). An MC is a symmetric network with short diameter, easy and efficient routing and broadcasting similar to that of the hypercube. However, the MC network can connect millions of nodes with up to 6 links per node. An MC(2,3) with 5 links per node has 16,384 nodes and an MC(3,3) with 6 links per node has 134,217,728 nodes. We describe the MC network’s structure, topological properties, routing and broadcasting algorithms, and the Hamiltonian cycle embedding in the Metacube networks. [ABSTRACT FROM AUTHOR]

According to the features of manufacturing grid (MGrid) resources, some resources should be reserved jointly to schedulers before executing a complex MGrid task. We define it as a co-reservation. In order to support co-reservation, we design a framework, a workflow, and a series of application programming interfaces of co-reservation in the MGrid system. The processing of co-reservation requests may be expensive due to a number of cell reservations, the complex relationships, and the large number of eligible resources in the MGrid system. In this paper, the processing of co-reservation requests is transferred to the subgraph isomorphism problem and an improved algorithm is introduced to solve it efficiently. Finally, we implement a prototype of co-reservation in the magnetic bearing resource and service sharing platform under MGrid. The experiment results show that the improved algorithm is effective to co-reservation. [ABSTRACT FROM AUTHOR]

An important query for spatio-temporal databases is to find nearest trajectories of moving objects. Existing work on this topic focuses on the closest trajectories in the whole data space. In this paper, we introduce and solve constrained k-nearest neighbor (C kNN) queries and historical continuous C kNN (HCC kNN) queries on R-tree-like structures storing historical information about moving object trajectories. Given a trajectory set D, a query object (point or trajectory) q, a temporal extent T, and a constrained region CR, (i) a C kNN query over trajectories retrieves from D within T, the k (≥ 1) trajectories that lie closest to q and intersect (or are enclosed by) CR; and (ii) an HCC kNN query on trajectories retrieves the constrained k nearest neighbors (C kNNs) of q at any time instance of T. We propose a suite of algorithms for processing C kNN queries and HCC kNN queries respectively, with different properties and advantages. In particular, we thoroughly investigate two types of C kNN queries, i.e., C kNNP and C kNNT, which are defined with respect to stationary query points and moving query trajectories, respectively; and two types of HCC kNN queries, namely, HCC kNNP and HCC kNNT, which are continuous counterparts of C kNNP and C kNNT, respectively. Our methods utilize an existing data-partitioning index for trajectory data (i.e., TB-tree) to achieve low I/O and CPU cost. Extensive experiments with both real and synthetic datasets demonstrate the performance of the proposed algorithms in terms of efficiency and scalability. [ABSTRACT FROM AUTHOR]

An automated general purpose method is introduced for computing a rigorous estimate of a bounded region in ℝ n whose points satisfy a given property. The method is based on calculations conducted in interval arithmetic and the constructed approximation is built of rectangular boxes of variable sizes. An efficient strategy is proposed, which makes use of parallel computations on multiple machines and refines the estimate gradually. It is proved that under certain assumptions the result of computations converges to the exact result as the precision of calculations increases. The time complexity of the algorithm is analyzed, and the effectiveness of this approach is illustrated by constructing a lower bound on the set of parameters for which an overcompensatory nonlinear Leslie population model exhibits more than one attractor, which is of interest from the biological point of view. This paper is accompanied by efficient and flexible software written in C++ whose source code is freely available at . [ABSTRACT FROM AUTHOR]

This paper considers the problem of scheduling n jobs on a single machine to minimize the total weighted completion time in the presence of sequence-dependent setup times and release times. To the best of our knowledge, little research has been devoted to this scheduling problem. Therefore, we developed two exact algorithms, including a constraint programming model and a branch-and-bound method for small problems. The obtained optimal solutions can be used as a benchmark for evaluating the performance of heuristics. With the complexity in mind, two heuristics, including a best index dispatch (BID) and a modified weighted shortest processing time (MWSPT) based on non-delay concepts are also proposed for large problems. The time complexities of the two proposed heuristics are O( n4) and O( n3), respectively. The computational results showed that the branch-and-bound method could solve most instances with 40 jobs under the time limit of 7,200 s. The BID heuristic is superior to the MWSPT in solution quality, although both can efficiently and effectively obtain near-optimal solutions for large instances. [ABSTRACT FROM AUTHOR]

In this paper we describe a singly exponential algorithm for computing the first Betti number of a given semi-algebraic set. Singly exponential algorithms for computing the zeroth Betti number, and the Euler–Poincaré characteristic, were known before. No singly exponential algorithm was known for computing any of the individual Betti numbers other than the zeroth one. As a consequence we also obtain algorithms for computing semi-algebraic descriptions of the semi-algebraically connected components of any given real algebraic or semi-algebraic set in singly exponential time, which improves on the complexity of the previously published algorithms for this problem. [ABSTRACT FROM AUTHOR]

Manual monitoring and seam tracking through welding images in real-time, by naked eye or industrial TV are experience-dependant, subjective, labor-intensive, and sometimes biased. So it is necessary to realize computer-aided seam tracking. We have developed a plasma arc welding (PAW) seam-tracking system, which senses the molten and the seam in a frame using a vision sensor, and then detects the seam deviation to adjust the work piece motion adaptively to the seam position sensed by the vision sensor with our collaborator. In this paper, we propose a novel molten pool area image-processing algorithm based on machine vision. The algorithm processes each image at a speed of 20 frames/s in real-time to extract three feature variables to get the seam deviation. It is proved experimentally that the algorithm is very fast and effective. Issues related to the algorithm are also discussed. [ABSTRACT FROM AUTHOR]

The tool switching problem is used to determine a job sequence and the tools to be loaded on a machine with the objective of minimising the total number of tool switches. In this paper, in order to develop a practical and efficient approach to solving this problem, a beam-search-based algorithm is introduced to formulate the solution space of the problem. The performance of the heuristic algorithm is compared with the heuristic developed by Bard. The proposed algorithm is then tested on some random test problems. The results show that the beam-search-based algorithm performs well in terms of computational efficiency and solution quality. [ABSTRACT FROM AUTHOR]

A CAD application tool kit interfacing with a Unigraphics (UG) system was developed for disintegrating large and complex rapid prototyping objects into smaller and simpler components which can be fabricated by a rapid prototyping system. As the core of the tool kit, the algorithm of such disintegration is described in detail in this paper. The algorithm combines the flat planar parting method and feature-based volume decomposition. Due consideration is also given to the optimisation of the surface accuracy, the build time, and the strength and number of segments generated. Based on the algorithm and the CAD application tool kit, the disintegration of two RP objects was realised in a selective laser sintering system. [ABSTRACT FROM AUTHOR]

It is a difficult task to manually cluster a large software system into loosely coupled modules with a large number of highly cohesive classes. On the other hand clustering is a NP-Hard problem. In this paper the design and implementation of a flexible software environment, called DAGC, to assemble and experiment with genetic clustering algorithms, for software (re)modularization, is described. The main idea behind the design of the DAGC is to define a general genetic clustering algorithm which may invoke different implementations for the parts from an extendable list of components. The DAGC provides visualization facilities to compare and evaluate different genetic clustering algorithms, regarding the two parameters of running time and the quality of clusters generated by the algorithms. [ABSTRACT FROM AUTHOR]

In this paper we present an algorithm for determining satisfiability of general Boolean formulas which are not necessarily in conjunctive normal form. The algorithm extends the well-known Davis–Putnam algorithm to work on Boolean formulas represented using Boolean Expression Diagrams (BEDs). The BED data structure allows the algorithm to take advantage of the built-in reduction rules and the sharing of sub-formulas. Furthermore, it is possible to combine the algorithm with traditional BDD construction (using Bryant’s Apply-procedure). By adjusting a single parameter to the BedSat algorithm, it is possible to control to what extent the algorithm behaves like the Apply-algorithm or like a SAT-solver. Thus, the algorithm can be seen as bridging the gap between standard SAT-solvers and BDDs. We present promising experimental results for 566 non-clausal formulas obtained from the multi-level combinational circuits in the ISCAS’85 benchmark suite and from performing model checking of a shift-and-add multiplier. [ABSTRACT FROM AUTHOR]