Teaching of algorithms and data structures is present in the curriculum of the most computer courses, having great influence on the performance of students in some subsequent disciplines, as well as student training. ...
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(纸本)9781450365598
Teaching of algorithms and data structures is present in the curriculum of the most computer courses, having great influence on the performance of students in some subsequent disciplines, as well as student training. However, many students' present difficulties in learning of the subject due to the abstraction ability and logical reasoning often have not developed. This research aims at presenting an open educational resource to assist students in learning algorithms and data structures. After applying the case study, the main results showed that the tool proposed is a good alternative to be used in the classroom contributing to learning the theme(1).
The high-lift Japan Aerospace Exploration Agency (JAXA) standard model (HL-JSM) has been numerically analyzed in order to further validate the HEMLAB code for realistic aircraft configurations. The numerical algorithm...
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The high-lift Japan Aerospace Exploration Agency (JAXA) standard model (HL-JSM) has been numerically analyzed in order to further validate the HEMLAB code for realistic aircraft configurations. The numerical algorithm is based on highly efficient edge-based data structure for a vertex-based finite volume algorithm on hybrid meshes. The data pattern is arranged to meet the requirements of a vertex-based finite volume algorithm by considering data access patterns and cache efficiency. A fully implicit version of the numerical algorithm has also been implemented based on the Portable, Extensible Toolkit for Scientific Computation (PETSc) library in order to improve the robustness of the algorithm. The resulting algebraic equations, including the one-equation Spalart-Allmaras, are solved in a monolithic manner using the restricted additive Schwarz preconditioner combined with the flexible generalized minimal residual method [FGMRES(m)] Krylov subspace algorithm. The numerical method is also combined with the metric-based anisotropic mesh refinement library Python Adaptive Mesh Geometry Suite-INRIA (pyAMG) from National Institute for Research in Digital Science and Technology in order to improve the numerical accuracy. The numerical algorithm is initially applied to the two-dimensional L1T2 (National High Lift Programme) high-lift system, and then the calculations around the HL-JSM are carried out at relatively high angles of attack. The numerical results with the anisotropic mesh refinement library pyAMG indicate significant improvements in numerical accuracy.
Distributed multi-agent unmanned aerial systems (UAS) have the potential to be heavily utilized in environmental monitoring, especially in wetland monitoring. Deep active learning algorithms provide key tools to analy...
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Distributed multi-agent unmanned aerial systems (UAS) have the potential to be heavily utilized in environmental monitoring, especially in wetland monitoring. Deep active learning algorithms provide key tools to analyze the sensed images captured during monitoring and interpret them precisely. However, these algorithms demand significant computational resources that limit their use with distributed UAS. In this paper, we propose a novel algorithm for consensus-enabled active learning that drastically reduces the computational demand while increasing the overall model accuracy. Once each of the UAS obtains a labeled subset of images through active learning, we update the weights of the model for three epochs only on the new images to reduce the computational cost, allowing for an increased operational time. The group of UAS communicates the model weights instead of the raw data and then leverages consensus to agree on updated weights. The consensus step mitigates the impact on weights caused by the updates and generalizes the knowledge of each individual UAS to the whole system, which results in increased model accuracy. Our method achieved an average of 11.15% increase in accuracy over 25 acquisition iterations whilst utilizing only 16.8% of the processor time compared to the centralized method of active learning.
A polyhedral decomposition can be unambiguously described as the collection of four primitive elements (i.e., polyhedra, facets, edges, and vertices) plus their mutual adjacency relations. We consider here the problem...
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Autonomous systems like unmanned aircraft systems are touted as front-runners in terms of efficiency and agility in challenging operations like emergency response. The ability of autonomous agents in such systems to a...
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Autonomous systems like unmanned aircraft systems are touted as front-runners in terms of efficiency and agility in challenging operations like emergency response. The ability of autonomous agents in such systems to avoid collisions with dynamic obstacles while navigating through an obstacle-cluttered environment is critical for success in any mission. In addition to that, further challenges are posed by environments with uncertainties in obstacles' motion, sensing, and occluded regions. To this end, a higher-order velocity obstacle-based novel motion planner is presented in this paper in a probabilistic setup for smooth, collision-free navigation of the agent with acceleration constraints in uncertain, unstructured environments with an element of anticipation for the future environment. The effectiveness of the developed algorithm for safe, collision-free, and smooth navigation of the agent is investigated in simulation studies in two different kinds of environments, one with known trajectories of obstacles and the other with unknown maneuvering trajectories of obstacles. Extensive simulation studies are performed in the presence of dynamic obstacles to elucidate the performance of the proposed algorithm on four crucial parameters-mission time, computational time, minimum obstacle distance, and an overall control effort under varied obstacle densities. With satisfactory performance in all these aspects, the developed algorithm possesses strong potential for real-time implementation.
An algorithm and data structure are developed for finding the Taylor series solution of the Hamilton-Jacobi-Isaacs equation associated with the nonlinear H-infinity control problem. This algorithm yields a set of line...
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An algorithm and data structure are developed for finding the Taylor series solution of the Hamilton-Jacobi-Isaacs equation associated with the nonlinear H-infinity control problem. This algorithm yields a set of linear algebraic equations that not only lead to a transparent solvability condition of the Hamilton-Jacobi-Isaacs equation in the form of the Taylor series, but also furnish a systematic procedure to generate the coefficients of the Taylor series. This algorithm is illustrated through a missile pitch autopilot design example.
Given n points in a circular region C in the plane, we study the problems of moving the n points to the boundary of G to form a regular n-gon such that the maximum (min-max) or the sum (min-sum) of the Euclidean dista...
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Given n points in a circular region C in the plane, we study the problems of moving the n points to the boundary of G to form a regular n-gon such that the maximum (min-max) or the sum (min-sum) of the Euclidean distances traveled by the points is minimized. These problems have applications, e.g., in mobile sensor barrier coverage of wireless sensor networks. The min-max problem further has two versions: the decision version and the optimization version. For the min-max problem, we present an O(nlog(2) n) time algorithm for the decision version and an O(nlog(3) n) time algorithm for the optimization version. The previously best algorithms for the two problem versions take O(n (3.5)) time and O(n (3.5)logn) time, respectively. For the min-sum problem we show that a special case with all points initially lying on the boundary of the circular region can be solved in O(n (2)) time, improving a previous O(n (4)) time solution. For the general min-sum problem, we present a 3-approximation O(n (2)) time algorithm. In addition, a by-product of our techniques is an algorithm for dynamically maintaining the maximum matching of a circular convex bipartite graph;our algorithm can handle each vertex insertion or deletion on the graph in O(log(2) n) time. This result may be interesting in its own right.
Given the trapezoid diagram, the problem of finding the minimum cardinality connected dominating set in trapezoid graphs was solved in O(m + n) time [Y.D. Liang, Steiner set and connected domination in trapezoid graph...
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Given the trapezoid diagram, the problem of finding the minimum cardinality connected dominating set in trapezoid graphs was solved in O(m + n) time [Y.D. Liang, Steiner set and connected domination in trapezoid graphs, Inform. Process. Lett. 56 (2) (1995) 101-108]. Kbhler [E. Kohler, Connected domination and dominating clique in trapezoid graphs, Discr. Appl. Math. 99 (2000) 91-110] recently improved this result to O(n) time. For the (vertex) weighted case, the problem of finding the minimum weighted connected dominating set in trapezoid graphs can be solved in O(m + n log n) time [Anand Srinivasan, M.S. Chang, K. Madhukar, C. Pandu Rangan, Efficient algorithms for the weighted domination problems on trapezoid graphs, Manuscript, 1996]. Herein n (m) denotes the number of vertices (edges) of the trapezoid graph. In this paper, we show a different approach for the problem of finding the minimum cardinality connected dominating set in trapezoid graphs using O(n) time. For finding the minimum weighted connected dominating set, we show the problem can be solved in O(n log log n) time. (c) 2007 Elsevier Inc. All rights reserved.
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