ERIC Educational Resources Information Center
Shore, M. L.
1980-01-01
There are many uses for the shortest path algorithm presented which are limited only by our ability to recognize when a problem may be converted into the shortest path in a graph representation. (Author/TG)
An Implementation of Chen & Han's Shortest Paths Algorithm
O'Rourke, Joseph
An Implementation of Chen & Han's Shortest Paths Algorithm Biliana Kaneva Joseph O'Rourke \\Lambda Abstract In 1990 Chen and Han proposed a quadratic algorithm for finding the shortest paths from one source In 1990 Chen and Han proposed a quadratic algorithm for finding the shortest paths from one source point
Shortest path algorithm based on city emergency system
Gui-Qin Dou; Yan-Song Zhu; Yu-Min Han
2011-01-01
It requires that the savers get to the spot with the quickest speed when the accidents take place in the City Emergency System, therefore the Shortest Path problem is one of the pivotal technology to satisfy the system. This paper put forward a real-time and effective algorithm realization of Shortest Path, according to the characteristics of City Emergency System, taking
Analysis of Algorithms Problem Set no. 3 --Dynamic All-Pairs Shortest Paths
Zwick, Uri
Analysis of Algorithms Problem Set no. 3 -- Dynamic All-Pairs Shortest Paths Given: December 15, 2010 Exercise 3.1 Describe a simple dynamic all-pairs shortest path algorithm that can handle decreas a weighted n-vertex graph with unique shortest paths in which there are (n3) locally shortest paths. (b) Show
An improved Physarum polycephalum algorithm for the shortest path problem.
Zhang, Xiaoge; Wang, Qing; Adamatzky, Andrew; Chan, Felix T S; Mahadevan, Sankaran; Deng, Yong
2014-01-01
Shortest path is among classical problems of computer science. The problems are solved by hundreds of algorithms, silicon computing architectures and novel substrate, unconventional, computing devices. Acellular slime mould P. polycephalum is originally famous as a computing biological substrate due to its alleged ability to approximate shortest path from its inoculation site to a source of nutrients. Several algorithms were designed based on properties of the slime mould. Many of the Physarum-inspired algorithms suffer from a low converge speed. To accelerate the search of a solution and reduce a number of iterations we combined an original model of Physarum-inspired path solver with a new a parameter, called energy. We undertook a series of computational experiments on approximating shortest paths in networks with different topologies, and number of nodes varying from 15 to 2000. We found that the improved Physarum algorithm matches well with existing Physarum-inspired approaches yet outperforms them in number of iterations executed and a total running time. We also compare our algorithm with other existing algorithms, including the ant colony optimization algorithm and Dijkstra algorithm. PMID:24982960
A bidirectional/multi-queue algorithm for the bi-objective multimodal viable shortest path
Paris-Sud XI, Université de
A bidirectional/multi-queue algorithm for the bi-objective multimodal viable shortest path problem fgueye@mobigis.fr, artigues@laas.fr, huguet@laas.fr Abstract Taking into account the multimodality-objective viable shortest path, multi-modal transportation, multi-queue label setting algorithms, deterministic
Label-setting algorithms for a polynomial bi-objective multimodal shortest path problem
Paris-Sud XI, Université de
Label-setting algorithms for a polynomial bi-objective multimodal shortest path problem Fallou the multimodality of urban transportation networks for com- puting the itinerary of an individual passenger techniques are discussed. keywords: bi-objective viable shortest paths, multimodal transportation, finite
Aloul, Fadi
efficient implementa- tions of Dijkstra's algorithm exist and can handle large net- works in short runtimesAbstract--Today, most routing problems are solved using Dijkstra's shortest path algorithm. Many Dijkstra's algorithm. Such conditions can include forcing the path to go through a specific node, forcing
Lecture notes for "Analysis of Algorithms": Dynamic All-Pairs Shortest Paths
Zwick, Uri
Lecture notes for "Analysis of Algorithms": Dynamic All-Pairs Shortest Paths Lecturer: Uri Zwick December 2010 Function apsp(G = (V, E, c)) t 0 foreach u V do E[u] [u] path(u) d[u, u] 0 p[u, u] [u] foreach u = v V do P[u, v] heap() insert-edges(E) build-paths() Function insert-edges(Eins) foreach e
Should QoS routing algorithms prefer shortest paths? Karol Kowalik and Martin Collier
Collier, Martin
Should QoS routing algorithms prefer shortest paths? Karol Kowalik and Martin Collier Research is the task of Quality of Service (QoS) routing. This paper considers link-state routing, and the choice of cost metric used to implement QoS routing. There are two schools of thought regarding the choice
Genetic Algorithm for Solving Fuzzy Shortest Path Problem in a Network with mixed fuzzy arc lengths
NASA Astrophysics Data System (ADS)
Mahdavi, Iraj; Tajdin, Ali; Hassanzadeh, Reza; Mahdavi-Amiri, Nezam; Shafieian, Hosna
2011-06-01
We are concerned with the design of a model and an algorithm for computing a shortest path in a network having various types of fuzzy arc lengths. First, we develop a new technique for the addition of various fuzzy numbers in a path using ? -cuts by proposing a linear least squares model to obtain membership functions for the considered additions. Then, using a recently proposed distance function for comparison of fuzzy numbers. we propose a new approach to solve the fuzzy APSPP using of genetic algorithm. Examples are worked out to illustrate the applicability of the proposed model.
Yang, Shengxiang
Genetic Algorithms with Elitism-based Immigrants for Dynamic Shortest Path Problem in Mobile Ad Hoc) in MANETs. In this paper, we propose to use elitism-based immigrants GA (EIGA) to solve the dynamic SP
NASA Astrophysics Data System (ADS)
Schafer, Sebastian; Singh, Vikas; Hoffmann, Kenneth R.; Noël, Peter B.; Xu, Jinhui
2007-03-01
Endovascular interventional procedures are being used more frequently in cardiovascular surgery. Unfortunately, procedural failure, e.g., vessel dissection, may occur and is often related to improper guidewire and/or device selection. To support the surgeon's decision process and because of the importance of the guidewire in positioning devices, we propose a method to determine the guidewire path prior to insertion using a model of its elastic potential energy coupled with a representative graph construction. The 3D vessel centerline and sizes are determined for a specified vessel. Points in planes perpendicular to the vessel centerline are generated. For each pair of consecutive planes, a vector set is generated which joins all points in these planes. We construct a graph representing these vector sets as nodes. The nodes representing adjacent vector sets are joined by edges with weights calculated as a function of the angle between the corresponding vectors (nodes). The optimal path through this weighted directed graph is then determined using shortest path algorithms, such as topological sort based shortest path algorithm or Dijkstra's algorithm. Volumetric data of an internal carotid artery phantom (Ø 3.5mm) were acquired. Several independent guidewire (Ø 0.4mm) placements were performed, and the 3D paths were determined using rotational angiography. The average RMS distance between the actual and the average simulated guidewire path was 0.7mm; the computation time to determine the path was 3 seconds. The ability to predict the guidewire path inside vessels may facilitate calculation of vessel-branch access and force estimation on devices and the vessel wall.
Faster Shortest Path Algorithm for H-Minor Free Graphs with Negative Edge Weights
Wulff-Nilsen, Christian
2010-01-01
Let $H$ be a fixed graph and let $G$ be an $H$-minor free $n$-vertex graph with integer edge weights and no negative weight cycles reachable from a given vertex $s$. We present an algorithm that computes a shortest path tree in $G$ rooted at $s$ in $\\tilde{O}(n^{4/3}\\log L)$ time, where $L$ is the absolute value of the smallest edge weight. The previous best bound was $\\tilde{O}(n^{\\sqrt{11.5}-2}\\log L) = O(n^{1.392}\\log L)$. Our running time matches an earlier bound for planar graphs by Henzinger et al.
Physarum can compute shortest paths.
Bonifaci, Vincenzo; Mehlhorn, Kurt; Varma, Girish
2012-09-21
Physarum polycephalum is a slime mold that is apparently able to solve shortest path problems. A mathematical model has been proposed by Tero et al. (Journal of Theoretical Biology, 244, 2007, pp. 553-564) to describe the feedback mechanism used by the slime mold to adapt its tubular channels while foraging two food sources s(0) and s(1). We prove that, under this model, the mass of the mold will eventually converge to the shortest s(0)-s(1) path of the network that the mold lies on, independently of the structure of the network or of the initial mass distribution. This matches the experimental observations by Tero et al. and can be seen as an example of a "natural algorithm", that is, an algorithm developed by evolution over millions of years. PMID:22732274
NASA Astrophysics Data System (ADS)
Blezek, Daniel J.; Robb, Richard A.
1999-05-01
Successful applications of virtual endoscopy often require the generation of centerlines as flight paths for fly-through examinations of anatomic structures. Criteria for design of effective centerline algorithms should include the following: (1) tracking of the most medial path possible, (2) robustness to segmentation errors, (3) computational efficiency, and (4) minimum of user interaction. To satisfy these design goals, we have developed a centerline generation algorithm based on the chamfer distance transform and Dijkstra's single-source shortest path algorithm. The distance transformation is applied to a segmented volume to determine the distance from each object voxel to the nearest background voxel -- a 'medialness' measure for each voxel. From a user specified source voxel, the distance and path from each object voxel to the source voxel is determined using Dijkstra's single-source shortest path algorithm, with the 'medialness' measure used as the weighting or distance factor between voxels. After execution of the algorithm is complete, paths from all voxels in the object to the source can be easily computed, a feature that is useful for all implementations of virtual endoscopy, but particularly for virtual bronchoscopy, which involves branching. The algorithm runs in O[2n(1 + f)] time, where n is the number of voxels in the volume, and f is the ratio of object voxels to total voxels in the volume. The algorithm is efficient, requiring approximately 90 seconds for a 60 megabyte dataset containing a segmented colon, and is robust to noise, segmentation errors, and start/end voxel selection. The only user interaction required is choosing the starting and ending voxels for the path. We report on objective and subjective evaluations of the algorithm when applied to several mathematical phantoms, the Visible Human Male Dataset and patient exams.
Physarum Can Compute Shortest Paths
Bonifaci, Vincenzo; Varma, Girish
2011-01-01
A mathematical model has been proposed by biologists to describe the feedback mechanism used by the Physarum Polycephalum slime mold to adapt its tubular channels while foraging two food sources $s_0$ and $s_1$. We give a proof of the fact that, under this model, the mass of the mold will eventually converge to the shortest $s_0$-$s_1$ path of the network that the mold lies on, independently of the structure of the network or of the initial mass distribution. This matches the experimental observations by the biologists and can be seen as an example of a "natural algorithm", that is, an algorithm developed by evolution over millions of years.
A Simpler Algorithm for the All Pairs Shortest Path Problem with O(n 2logn) Expected Time
NASA Astrophysics Data System (ADS)
Takaoka, Tadao; Hashim, Mashitoh
The best known expected time for the all pairs shortest path problem on a directed graph with non-negative edge costs is O(n 2logn) by Moffat and Takaoka. Let the solution set be the set of vertices to which the given algorithm has established shortest paths. The Moffat-Takaoka algorithm maintains complexities before and after the critical point in balance, which is the moment when the size of the solution set is n - n/logn. In this paper, we remove the concept of critical point and the data structure, called a batch list, whereby we make the algorithm simpler and seamless, resulting in a simpler analysis and speed-up.
Optimal Distributed All Pairs Shortest Paths
Optimal Distributed All Pairs Shortest Paths ETH Zurich Distributed Computing Group Stephan = Number of hops of shortest path #12;Diameter of a network · Distance between two nodes = Number of hops of shortest path #12;Diameter of a network · Distance between two nodes = Number of hops of shortest path
The inverse shortest paths problem with upper bounds on shortest paths costs.
Toint, Philippe
The inverse shortest paths problem with upper bounds on shortest paths costs. by D. Burton 1 W of the inverse shortest paths problem with upper bounds on shortest path costs, and prove that obtaining, Belgium Keywords : computational complexity, shortest paths, inverse problems, traffic modelling. #12; 1
Finding the k Shortest Paths David Eppstein
Eppstein, David
constraints beyond having a small length, but those other constraints may be ill-defined or hard to optimize-known shortest path problem, in which not one but several short paths must be produced. The k shortest paths problem, for a given k and a given source-destination pair in a digraph, is to list the k paths
Shortest path and Schramm-Loewner Evolution
Posé, N.; Schrenk, K. J.; Araújo, N. A. M.; Herrmann, H. J.
2014-01-01
We numerically show that the statistical properties of the shortest path on critical percolation clusters are consistent with the ones predicted for Schramm-Loewner evolution (SLE) curves for ? = 1.04 ± 0.02. The shortest path results from a global optimization process. To identify it, one needs to explore an entire area. Establishing a relation with SLE permits to generate curves statistically equivalent to the shortest path from a Brownian motion. We numerically analyze the winding angle, the left passage probability, and the driving function of the shortest path and compare them to the distributions predicted for SLE curves with the same fractal dimension. The consistency with SLE opens the possibility of using a solid theoretical framework to describe the shortest path and it raises relevant questions regarding conformal invariance and domain Markov properties, which we also discuss. PMID:24975019
Shortest Paths, Network Design and Associated Polyhedra
Magnanti, Thomas L.
We study a specialized version of network design problems that arise in telecommunication, transportation and other industries. The problem, a generalization of the shortest path problem, is defined on an undirected network ...
Shortest Path Edit Distance for Enhancing UMLS Integration and Audit
Rudniy, Alex; Geller, James; Song, Min
2010-01-01
Expansion of the UMLS is an important long-term research project. This paper proposes Shortest Path Edit Distance (SPED) as an algorithm for improving existing source-integration and auditing techniques. We use SPED as a string similarity measure for UMLS terms that are known to be synonyms because they are assigned to the same concept. We compare SPED with several other well known string matching algorithms using two UMLS samples as test bed. One of those samples is SNOMED-based. SPED transforms the task of calculating edit distance among two strings into a problem of finding a shortest path from a source to a destination in a node and link graph. In the algorithm, the two strings are used to construct the graph. The Pulling algorithm is applied to find a shortest path, which determines the string similarity value. SPED was superior for one of the data sets, with a precision of 0.6. PMID:21347068
Using shortest path to discover criminal community
Magalingam, Pritheega; Rao, Asha
2015-01-01
Extracting communities using existing community detection algorithms yields dense sub-networks that are difficult to analyse. Extracting a smaller sample that embodies the relationships of a list of suspects is an important part of the beginning of an investigation. In this paper, we present the efficacy of our shortest paths network search algorithm (SPNSA) that begins with an "algorithm feed", a small subset of nodes of particular interest, and builds an investigative sub-network. The algorithm feed may consist of known criminals or suspects, or persons of influence. This sets our approach apart from existing community detection algorithms. We apply the SPNSA on the Enron Dataset of e-mail communications starting with those convicted of money laundering in relation to the collapse of Enron as the algorithm feed. The algorithm produces sparse and small sub-networks that could feasibly identify a list of persons and relationships to be further investigated. In contrast, we show that identifying sub-networks o...
Shortest node-disjoint paths on random graphs
NASA Astrophysics Data System (ADS)
De Bacco, C.; Franz, S.; Saad, D.; Yeung, C. H.
2014-07-01
A localized method to distribute paths on random graphs is devised, aimed at finding the shortest paths between given source/destination pairs while avoiding path overlaps at nodes. We propose a method based on message-passing techniques to process global information and distribute paths optimally. Statistical properties such as scaling with system size and number of paths, average path-length and the transition to the frustrated regime are analysed. The performance of the suggested algorithm is evaluated through a comparison against a greedy algorithm.
Detecting duplicate biological entities using Shortest Path Edit Distance.
Rudniy, Alex; Song, Min; Geller, James
2010-01-01
Duplicate entity detection in biological data is an important research task. In this paper, we propose a novel and context-sensitive Shortest Path Edit Distance (SPED) extending and supplementing our previous work on Markov Random Field-based Edit Distance (MRFED). SPED transforms the edit distance computational problem to the calculation of the shortest path among two selected vertices of a graph. We produce several modifications of SPED by applying Levenshtein, arithmetic mean, histogram difference and TFIDF techniques to solve subtasks. We compare SPED performance to other well-known distance algorithms for biological entity matching. The experimental results show that SPED produces competitive outcomes. PMID:20815139
Route Dynamics for Shortest Path First Routing in Mobile Ad Hoc Networks
Bhatti, Saleem N.
dynamics of Shortest-Path First (SPF) routing in mobile ad hoc networks (MANETs). In particular, we find Path First (SPF) algorithm as in Optimised Link State Routing Protocol (OLSR) [1]. Moreover, fast]. In this paper we investigate the route dynamics of Shortest- Path First (SPF) routing protocols in MANETs
Shortest Path Problems with Resource Constraints
Stefan Irnich; Guy Desaulniers
In most vehicle routing and crew scheduling applications solved by column generation, the subproblem corresponds to a shortest\\u000a path problem with resource constraints (SPPRC) or one of its variants.\\u000a \\u000a This chapter proposes a classification and a generic formulation for the SPPRCs, briefly discusses complex modeling issues\\u000a involving resources, and presents the most commonly used SPPRC solution methods. First and foremost,
Shortest route algorithm with movement prohibitions
Said M. Easa
1985-01-01
This paper presents an algorithm with movement prohibitions which eliminates some problems encountered in network representation used for traffic assignment models, and further allows the representation of the network to be simplified. The paper first presents an appraisal of some proposed methods and reviews the basic concept of existing shortest-route algorithms. The problem of obtaining shortest routes in networks with
Self-organization and solution of shortest-path optimization problems with memristive networks.
Pershin, Yuriy V; Di Ventra, Massimiliano
2013-07-01
We show that memristive networks, namely networks of resistors with memory, can efficiently solve shortest-path optimization problems. Indeed, the presence of memory (time nonlocality) promotes self organization of the network into the shortest possible path(s). We introduce a network entropy function to characterize the self-organized evolution, show the solution of the shortest-path problem and demonstrate the healing property of the solution path. Finally, we provide an algorithm to solve the traveling salesman problem. Similar considerations apply to networks of memcapacitors and meminductors, and networks with memory in various dimensions. PMID:23944581
Shortest-path problems Proofs Weight of path p = v0 v1 vk
California at Davis, University of
Shortest-path problems Â Proofs Weight of path p = v0 v1 Â· Â· Â· vk: w(p) = k i=1 w(vi-1, vi) Shortest-path weight u ; v (u, v) = min{w(p) : u p ; v} if there exists a path u ; v otherwise Shortest-path u ; v any path p such that w(p) = (u, v) #12;Shortest-paths properties Triangular inequality
Shortest paths synthesis for a car-like robot
P. Soueres; J.-P. Laumond
1996-01-01
This paper deals with the complete characterization of the shortest paths for a car-like robot. Previous works have shown that the search for a shortest path may be limited to a simple family of trajectories. Our work completes this study by providing a way to select inside this family an optimal path to link any two configurations. We combine the
The role of convexity for solving some shortest path problems in plane without triangulation
NASA Astrophysics Data System (ADS)
An, Phan Thanh; Hai, Nguyen Ngoc; Hoai, Tran Van
2013-09-01
Solving shortest path problems inside simple polygons is a very classical problem in motion planning. To date, it has usually relied on triangulation of the polygons. The question: "Can one devise a simple O(n) time algorithm for computing the shortest path between two points in a simple polygon (with n vertices), without resorting to a (complicated) linear-time triangulation algorithm?" raised by J. S. B. Mitchell in Handbook of Computational Geometry (J. Sack and J. Urrutia, eds., Elsevier Science B.V., 2000), is still open. The aim of this paper is to show that convexity contributes to the design of efficient algorithms for solving some versions of shortest path problems (namely, computing the convex hull of a finite set of points and convex rope on rays in 2D, computing approximate shortest path between two points inside a simple polygon) without triangulation on the entire polygons. New algorithms are implemented in C and numerical examples are presented.
Improved Hardness of Approximation for Stackelberg Shortest-Path Pricing
Khanna, Sanjeev
Improved Hardness of Approximation for Stackelberg Shortest-Path Pricing Patrick Briest1, , Parinya blaekh@cs.mcgill.ca 5 College of Computing, Georgia Tech, Atlanta, GA, USA danupon@cc.gatech.edu Abstract. We consider the Stackelberg shortest-path pricing problem, which is defined as follows. Given a graph
Minimizing Average Shortest Path Distances via Shortcut Edge Addition
Meyerson, Adam W.
Minimizing Average Shortest Path Distances via Shortcut Edge Addition Adam Meyerson and Brian typically use mesh networks since regular topologies are easier to manufacture. However, many pairs of nodes k shortcut edges (of length 0) whose addition minimizes the weighted average shortest path
ON THE ACCELERATION OF SHORTEST PATH CALCULATIONS IN TRANSPORTATION NETWORKS
BAKER, ZACHARY K.; GOKHALE, MAYA B.
2007-01-08
Shortest path algorithms are a key element of many graph problems. They are used in such applications as online direction finding and navigation, as well as modeling of traffic for large scale simulations of major metropolitan areas. As the shortest path algorithms are an execution bottleneck, it is beneficial to move their execution to parallel hardware such as Field-Programmable Gate Arrays (FPGAs). Hardware implementation is accomplished through the use of a small A core replicated on the order of 20 times on an FPGA device. The objective is to maximize the use of on-board random-access memory bandwidth through the use of multi-threaded latency tolerance. Each shortest path core is responsible for one shortest path calculation, and when it is finished it outputs its result and requests the next source from a queue. One of the innovations of this approach is the use of a small bubble sort core to produce the extract-min function. While bubble sort is not usually considered an appropriate algorithm for any non-trivial usage, it is appropriate in this case as it can produce a single minimum out of the list in O(n) cycles, whwere n is the number of elements in the vertext list. The cost of this min operation does not impact the running time of the architecture, because the queue depth for fetching the next set of edges from memory is roughly equivalent to the number of cores in the system. Additionally, this work provides a collection of simulation results that model the behavior of the node queue in hardware. The results show that a hardware queue, implementing a small bubble-type minimum function, need only be on the order of 16 elements to provide both correct and optimal paths. Because the graph database size is measured in the hundreds of megabytes, the Cray SRAM memory is insufficient. In addition to the A* cores, they have developed a memory management system allowing round-robin servicing of the nodes as well as virtual memory managed over the Hypertransport bus. With support for a DRAM graph store with SRAM-based caching on the FPGA, the system provides a speedup of roughly 8.9x over the CPU-based implementation.
Elsayed, Khaled Fouad
in MPLS Networks Khaled M. F. Elsayed, Senior Member, IEEE Department of Electronics and Communications for routing of MPLS bandwidth-guaranteed tunnels in general topology networks. The HCASP algorithm tries of bandwidth-guaranteed tunnels in MPLS networks are the minimum interference routing algorithm (MIRA
Two betweenness centrality measures based on Randomized Shortest Paths
Kivimäki, Ilkka; Saramäki, Jari; Saerens, Marco
2015-01-01
This paper introduces two new closely related betweenness centrality measures based on the Randomized Shortest Paths (RSP) framework, which fill a gap between traditional network centrality measures based on shortest paths and more recent methods considering random walks or current flows. The framework defines Boltzmann probability distributions over paths of the network which focus on the shortest paths, but also take into account longer paths depending on an inverse temperature parameter. RSP's have previously proven to be useful in defining distance measures on networks. In this work we study their utility in quantifying the importance of the nodes of a network. The proposed RSP betweenness centralities combine, in an optimal way, the ideas of using the shortest and purely random paths for analysing the roles of network nodes, avoiding issues involving these two paradigms. We present the derivations of these measures and how they can be computed in an efficient way. In addition, we show with real world exa...
Multiple-Source Shortest Paths in Embedded Graphs Sergio Cabello
Erickson, Jeff
Multiple-Source Shortest Paths in Embedded Graphs Sergio Cabello Erin W. Chambers Jeff Erickson of Mathematics, FMF, University of Ljubljana, Slovenia, sergio. cabello@fmf.uni-lj.si. Research partially
Shortest Path Games: Computational Complexity of Solution Concepts
Amsterdam, University of
Shortest Path Games: Computational Complexity of Solution Concepts MSc Thesis (Afstudeerscriptie 9 2.1 Coalitional Games . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 2 Concepts for Coalitional Games . . . . . . . . . . . . . . . . . . . . . . . 12 2.3.1 Power Indices
Watershed cuts: thinnings, shortest path forests, and topological watersheds.
Cousty, Jean; Bertrand, Gilles; Najman, Laurent; Couprie, Michel
2010-05-01
We recently introduced watershed cuts, a notion of watershed in edge-weighted graphs. In this paper, our main contribution is a thinning paradigm from which we derive three algorithmic watershed cut strategies: The first one is well suited to parallel implementations, the second one leads to a flexible linear-time sequential implementation, whereas the third one links the watershed cuts and the popular flooding algorithms. We state that watershed cuts preserve a notion of contrast, called connection value, on which several morphological region merging methods are (implicitly) based. We also establish the links and differences between watershed cuts, minimum spanning forests, shortest path forests, and topological watersheds. Finally, we present illustrations of the proposed framework to the segmentation of artwork surfaces and diffusion tensor images. PMID:20299715
Distributional properties of stochastic shortest paths for smuggled nuclear material
Cuellar, Leticia [Los Alamos National Laboratory; Pan, Feng [Los Alamos National Laboratory; Roach, Fred [Los Alamos National Laboratory; Saeger, Kevin J [Los Alamos National Laboratory
2011-01-05
The shortest path problem on a network with fixed weights is a well studied problem with applications to many diverse areas such as transportation and telecommunications. We are particularly interested in the scenario where a nuclear material smuggler tries to succesfully reach herlhis target by identifying the most likely path to the target. The identification of the path relies on reliabilities (weights) associated with each link and node in a multi-modal transportation network. In order to account for the adversary's uncertainty and to perform sensitivity analysis we introduce random reliabilities. We perform some controlled experiments on the grid and present the distributional properties of the resulting stochastic shortest paths.
Evans, Will
16th Canadian Conference on Computational Geometry, 2004 Optimistic Shortest Paths on Uncertain shortest path on an un- certain terrain is NP-hard using a reduction similar to Canny and Reif's reduction of 3SAT to 3D Euclidean shortest path. §©!#"%$&'§() Shortest path problems are a well-studied class
Efficient Algorithms for Shortest Partial Seeds in Words
Lonardi, Stefano
Efficient Algorithms for Shortest Partial Seeds in Words Tomasz Kociumaka1 , Solon P. Pissis2. Wale Efficient Algorithms for Shortest Partial Seeds in Words 2/16 #12;Periodicity and quasiperiodicity. Radoszewski, W. Rytter, T. Wale Efficient Algorithms for Shortest Partial Seeds in Words 2/16 #12;Periodicity
Shortest Path Planning for a Tethered Robot or an Anchored Cable
Xavier, P.G.
1999-02-22
We consider the problem of planning shortest paths for a tethered robot with a finite length tether in a 2D environment with polygonal obstacles. We present an algorithm that runs in time O((k{sub 1} + 1){sup 2}n{sup 4}) and finds the shortest path or correctly determines that none exists that obeys the constraints; here n is the number obstacle vertices, and k{sub 1} is the number loops in the initial configuration of the tether. The robot may cross its tether but nothing can cross obstacles, which cause the tether to bend. The algorithm applies as well for planning a shortest path for the free end of an anchored cable.
Shortest path optimization under limited information
Dahleh, Munther A.
The problem of finding an optimal path in an uncertain graph arises in numerous applications, including network routing, path-planning for vehicles, and the control of finite-state systems. While techniques in robust and ...
State-based accelerations and bidirectional search for bi-objective multimodal shortest paths
Paris-Sud XI, Université de
State-based accelerations and bidirectional search for bi-objective multimodal shortest paths artigues@laas.fr, huguet@laas.fr Abstract Taking into account the multimodality of urban transportation-dependent context, is not a challenge anymore for labeling algorithms [6, 7, 19]. The case of multimodal passenger
Routing and Protection in GMPLS Networks: From Shortest Paths to Optimized Designs*
Elwalid, Anwar
Abstract-- Shortest path algorithms such as SPF and CSPF are widely used in online traffic engineering indicate that DBR outperforms SPF and CSPF under a wide range of operating con- ditions, and is robust- tion, protection, SPF, CSPF, DBR. I. INTRODUCTION A. Background and Motivation Service Providers
Performance of Shortest Path Routing under Various Link Cost Metrics for non-GEO Satellite Systems
Papapetrou, Evaggelos
. Specially in new generation satellite systems which employ Inter-Satellite Links (ISLs) [1,2] is foundPerformance of Shortest Path Routing under Various Link Cost Metrics for non-GEO Satellite Systems for non- GEO satellite systems. The Modified Dijkstra algorithm is used for different link cost functions
Expected Shortest Paths for Landmark-Based Robot Navigation
Scharstein, Daniel
Expected Shortest Paths for Landmark-Based Robot Navigation Amy J. Briggs1 , Carrick Detweiler1 of planning reliable landmark- based robot navigation strategies in the presence of significant sensor uncertainty. The navigation environments are modeled with directed weighted graphs in which edges can
FINDING THE SHORTEST PATH FOR QUALITY ASSURANCE OF ELECTRIC COMPONENTS
Masaru Kageura; CANON IN; Kenji Shimada
This paper presents a computational method for calculating the shortest path along the surface of a product assembly between two components. The goal of this method is to check whether or not there is sufficient distance between two electrical components to prevent the occurrence of a spark between them. Our approach is an approximating method using a discrete weighted graph.
Efficient Shortest Paths on Massive Social Graphs (Invited Paper)
Almeroth, Kevin C.
extended to locate (near-) shortest paths between node pairs. After a one- time preprocessing cost, Rigel node distance queries on the original graph. Our initial system, Orion, was a centralized system in practice. First, Orion's initial graph embedding process is centralized and computationally expensive
Randomized shortest-path problems: two related models.
Saerens, Marco; Achbany, Youssef; Fouss, François; Yen, Luh
2009-08-01
This letter addresses the problem of designing the transition probabilities of a finite Markov chain (the policy) in order to minimize the expected cost for reaching a destination node from a source node while maintaining a fixed level of entropy spread throughout the network (the exploration). It is motivated by the following scenario. Suppose you have to route agents through a network in some optimal way, for instance, by minimizing the total travel cost-nothing particular up to now-you could use a standard shortest-path algorithm. Suppose, however, that you want to avoid pure deterministic routing policies in order, for instance, to allow some continual exploration of the network, avoid congestion, or avoid complete predictability of your routing strategy. In other words, you want to introduce some randomness or unpredictability in the routing policy (i.e., the routing policy is randomized). This problem, which will be called the randomized shortest-path problem (RSP), is investigated in this work. The global level of randomness of the routing policy is quantified by the expected Shannon entropy spread throughout the network and is provided a priori by the designer. Then, necessary conditions to compute the optimal randomized policy-minimizing the expected routing cost-are derived. Iterating these necessary conditions, reminiscent of Bellman's value iteration equations, allows computing an optimal policy, that is, a set of transition probabilities in each node. Interestingly and surprisingly enough, this first model, while formulated in a totally different framework, is equivalent to Akamatsu's model ( 1996 ), appearing in transportation science, for a special choice of the entropy constraint. We therefore revisit Akamatsu's model by recasting it into a sum-over-paths statistical physics formalism allowing easy derivation of all the quantities of interest in an elegant, unified way. For instance, it is shown that the unique optimal policy can be obtained by solving a simple linear system of equations. This second model is therefore more convincing because of its computational efficiency and soundness. Finally, simulation results obtained on simple, illustrative examples show that the models behave as expected. PMID:19323635
Shortest Paths in Distance-Regular Graphs Enrique Bendito, Angeles Carmona and Andres M. Encinas
Bendito, Enrique
Shortest Paths in Distance-Regular Graphs Enrique Bendito, Angeles Carmona and Andr´es M. Encinas and Shortest Paths Angeles Carmona: e-mail:carmona@etseccpb.upc.es 2 #12;Abstract We aim here at introducing
THE K SHORTEST PATHS PROBLEM Ernesto de Queir' os Vieira Martins
Pascoal, Marta Margarida Braz
THE K SHORTEST PATHS PROBLEM Ernesto de Queir' os Vieira Martins Marta Margarida Braz Pascoal Jos Coimbra PORTUGAL June 1998 Abstract: The shortest path problem is a classical network programming problem that has been extensively studied. The problem of determining not only the shortest path, but also listing
Approximate Euclidean Shortest Paths amid Convex Obstacles Pankaj K. Agarwal R. Sharathkumar Hai Yu
Agarwal, Pankaj K.
Approximate Euclidean Shortest Paths amid Convex Obstacles Pankaj K. Agarwal R. Sharathkumar Hai Yu and data structures for the approximate Euclidean shortest path problem amid a set P of k convex obstacles for computing the exact Euclidean shortest path between two points amid polygonal obstacles. In three dimensions
von Thienen, Wolfhard; Metzler, Dirk; Witte, Volker
2015-05-01
The emergence of self-organizing behavior in ants has been modeled in various theoretical approaches in the past decades. One model explains experimental observations in which Argentine ants (Linepithema humile) selected the shorter of two alternative paths from their nest to a food source (shortest path experiments). This model serves as an important example for the emergence of collective behavior and self-organization in biological systems. In addition, it inspired the development of computer algorithms for optimization problems called ant colony optimization (ACO). In the model, a choice function describing how ants react to different pheromone concentrations is fundamental. However, the parameters of the choice function were not deduced experimentally but freely adapted so that the model fitted the observations of the shortest path experiments. Thus, important knowledge was lacking about crucial model assumptions. A recent study on the Argentine ant provided this information by measuring the response of the ants to varying pheromone concentrations. In said study, the above mentioned choice function was fitted to the experimental data and its parameters were deduced. In addition, a psychometric function was fitted to the data and its parameters deduced. Based on these findings, it is possible to test the shortest path model by applying realistic parameter values. Here we present the results of such tests using Monte Carlo simulations of shortest path experiments with Argentine ants. We compare the choice function and the psychometric function, both with parameter values deduced from the above-mentioned experiments. Our results show that by applying the psychometric function, the shortest path experiments can be explained satisfactorily by the model. The study represents the first example of how psychophysical theory can be used to understand and model collective foraging behavior of ants based on trail pheromones. These findings may be important for other models of pheromone guided ant behavior and might inspire improved ACO algorithms. PMID:25769943
The d-edge shortest-path problem for a Monge graph
Bein, W.W. [New Mexico Univ., Albuquerque, NM (United States). Dept. of Computer Science; Larmore, L.L. [California Univ., Riverside, CA (United States). Dept. of Computer Science; Park, J.K. [Sandia National Labs.,Albuquerque, NM (United States)
1992-07-14
A complete edge-weighted directed graph on vertices 1,2,...,n that assigns cost c(i,j) to the edge (i,j) is called Monge if its edge costs form a Monge array, i.e., for all i < k and j < l, c[i, j]+c[k,l]{le} < c[i,l]+c[k,j]. One reason Monge graphs are interesting is that shortest paths can be computed quite quickly in such graphs. In particular, Wilber showed that the shortest path from vertex 1 to vertex n of a Monge graph can be computed in O(n) time, and Aggarwal, Klawe, Moran, Shor, and Wilber showed that the shortest d-edge 1-to-n path (i.e., the shortest path among all 1-to-n paths with exactly d edges) can be computed in O(dn) time. This paper`s contribution is a new algorithm for the latter problem. Assuming 0 {le} c[i,j] {le} U and c[i,j + 1] + c[i + 1,j] {minus} c[i,j] {minus} c[i + 1, j + 1] {ge} L > 0 for all i and j, our algorithm runs in O(n(1 + 1g(U/L))) time. Thus, when d {much_gt} 1 + 1g(U/L), our algorithm represents a significant improvement over Aggarwal et al.`s O(dn)-time algorithm. We also present several applications of our algorithm; they include length-limited Huffman coding, finding the maximum-perimeter d-gon inscribed in a given convex n-gon, and a digital-signal-compression problem.
A Bio-Inspired Method for the Constrained Shortest Path Problem
Wang, Hongping; Lu, Xi; Wang, Qing
2014-01-01
The constrained shortest path (CSP) problem has been widely used in transportation optimization, crew scheduling, network routing and so on. It is an open issue since it is a NP-hard problem. In this paper, we propose an innovative method which is based on the internal mechanism of the adaptive amoeba algorithm. The proposed method is divided into two parts. In the first part, we employ the original amoeba algorithm to solve the shortest path problem in directed networks. In the second part, we combine the Physarum algorithm with a bio-inspired rule to deal with the CSP. Finally, by comparing the results with other method using an examples in DCLC problem, we demonstrate the accuracy of the proposed method. PMID:24959603
A NEW IMPLEMENTATION OF YEN'S RANKING LOOPLESS PATHS ALGORITHM 1
Pascoal, Marta Margarida Braz
A NEW IMPLEMENTATION OF YEN'S RANKING LOOPLESS PATHS ALGORITHM 1 Ernesto de Queir' os Vieira algorithm for ranking the K shortest loopless paths between a pair of nodes in a network. In this paper to conclude. Keywords: network, path, loopless path, paths ranking. 1 Introduction The problem of determining
Do People Use the Shortest Path? An Empirical Test of Wardrop’s First Principle
Zhu, Shanjiang; Levinson, David
2015-01-01
Most recent route choice models, following either the random utility maximization or rule-based paradigm, require explicit enumeration of feasible routes. The quality of model estimation and prediction is sensitive to the appropriateness of the consideration set. However, few empirical studies of revealed route characteristics have been reported in the literature. This study evaluates the widely applied shortest path assumption by evaluating routes followed by residents of the Minneapolis—St. Paul metropolitan area. Accurate Global Positioning System (GPS) and Geographic Information System (GIS) data were employed to reveal routes people used over an eight to thirteen week period. Most people did not choose the shortest path. Using three weeks of that data, we find that current route choice set generation algorithms do not reveal the majority of paths that individuals took. Findings from this study may guide future efforts in building better route choice models. PMID:26267756
Cognitive Shortest Path Tree Restoration (CSPTR) for MANET Using Cost-Sensitivity Analysis
NASA Astrophysics Data System (ADS)
Chen, Huan; Cheng, Bo-Chao; Tseng, Po-Kai
With quick topology changes due to mobile node movement or signal fading in MANET environments, conventional routing restoration processes are costly to implement and may incur high flooding of network traffic overhead and long routing path latency. Adopting the traditional shortest path tree (SPT) recomputation and restoration schemes used in Internet routing protocols will not work effectively for MANET. An object of the next generation SPT restoration system is to provide a cost-effective solution using an adaptive learning control system, wherein the SPT restoration engine is able to skip over the heavy SPT computation. We proposed a novel SPT restoration scheme, called Cognitive Shortest Path Tree Restoration (CSPTR). CSPTR is designed based on the Network Simplex Method (NSM) and Sensitivity Analysis (SA) techniques to provide a comprehensive and low-cost link failure healing process. NSM is used to derive the shortest paths for each node, while the use of SA can greatly reduce the effort of unnecessary recomputation of the SPT when network topology changes. In practice, a SA range table is used to enable the learning capability of CSPTR. The performance of computing and communication overheads are compared with other two well-known schemes, such as Dijstra's algorithm and incremental OSPF. Results show that CSPTR can greatly eliminate unnecessary SPT recomputation and reduce large amounts of the flooding overheads.
THE K SHORTEST LOOPLESS PATHS PROBLEM Ernesto de Queir' os Vieira Martins
Pascoal, Marta Margarida Braz
THE K SHORTEST LOOPLESS PATHS PROBLEM Ernesto de Queir' os Vieira Martins Marta Margarida Braz loopless paths problem. It is shown that in general this problem does not satisfy the optimality principle and as a consequence only methods based on the computation of a super set of the set of the K shortest loopless paths
Damage detection via shortest-path network sampling
NASA Astrophysics Data System (ADS)
Ciulla, Fabio; Perra, Nicola; Baronchelli, Andrea; Vespignani, Alessandro
2014-05-01
Large networked systems are constantly exposed to local damages and failures that can alter their functionality. The knowledge of the structure of these systems is, however, often derived through sampling strategies whose effectiveness at damage detection has not been thoroughly investigated so far. Here, we study the performance of shortest-path sampling for damage detection in large-scale networks. We define appropriate metrics to characterize the sampling process before and after the damage, providing statistical estimates for the status of nodes (damaged, not damaged). The proposed methodology is flexible and allows tuning the trade-off between the accuracy of the damage detection and the number of probes used to sample the network. We test and measure the efficiency of our approach considering both synthetic and real networks data. Remarkably, in all of the systems studied, the number of correctly identified damaged nodes exceeds the number of false positives, allowing us to uncover the damage precisely.
Corridor location: the multi-gateway shortest path model
NASA Astrophysics Data System (ADS)
Scaparra, Maria P.; Church, Richard L.; Medrano, F. Antonio
2014-07-01
The problem of corridor location can be found in a number of fields including power transmission, highways, and pipelines. It involves the placement of a corridor or rights-of-way that traverses a landscape starting at an origin and ending at a destination. Since most systems are subject to environmental review, it is important to generate competitive, but different alternatives. This paper addresses the problem of generating efficient, spatially different alternatives to the corridor location problem. We discuss the weaknesses in current models and propose a new approach which is designed to overcome many of these problems. We present an application of this model to a real landscape and compare the results to past work. Overall, the new model called the multi-gateway shortest path problem can generate a wide variety of efficient alignments, which eclipse what could be generated by past work.
Curvature-Constrained Shortest Paths in a Convex Polygon (Extended Abstract)
Agarwal, Pankaj K.
and shed some light on curvature-constrained shortest paths amid obstacles. Center for Geometric Computing-planning problem, a central problem in robotics, involves planning a collision-free path for a robot moving amid
Accepted Manuscript Shortest path in a multiply-connected domain having curved
Ramanathan, M.
Accepted Manuscript Shortest path in a multiply-connected domain having curved boundaries S this article as: Bharath Ram S, Ramanathan M. Shortest path in a multiply-connected domain having curved manuscript that has been accepted for publication. As a service to our customers we are providing this early
Shortest Paths in Time-Dependent FIFO Networks Using Edge Load Forecasts
Dehene, Frank
Shortest Paths in Time-Dependent FIFO Networks Using Edge Load Forecasts Frank Dehne School shortest paths in time- dependent networks with edge load forecasts where the be- havior of each edge in a pre- dictable manner and are given as edge load forecasts. For example, in many road networks
On the Complexity of Shortest Path Problems on Discounted Cost Graphs
Alur, Rajeev
it contains. In a generalized version of the shortest- path problem, each edge is labeled with a cost as wellOn the Complexity of Shortest Path Problems on Discounted Cost Graphs Rajeev Alur, Sampath Kannan, Kevin Tian, and Yifei Yuan University of Pennsylvania, Philadelphia, PA, US Abstract. Discounted Cost
Tubule detection in testis images using boundary weighting and circular shortest path.
Zhang, Chao; Sun, Changming; Davey, Rhonda; Su, Ran; Bischof, Leanne; Vallotton, Pascal; Lovell, David; Hope, Shelly; Lehnert, Sigrid; Pham, Tuan D
2013-01-01
In studies of germ cell transplantation, measureing tubule diameters and counting cells from different populations using antibodies as markers are very important. Manual measurement of tubule sizes and cell counts is a tedious and sanity grinding work. In this paper, we propose a new boundary weighting based tubule detection method. We first enhance the linear features of the input image and detect the approximate centers of tubules. Next, a boundary weighting transform is applied to the polar transformed image of each tubule region and a circular shortest path is used for the boundary detection. Then, ellipse fitting is carried out for tubule selection and measurement. The algorithm has been tested on a dataset consisting of 20 images, each having about 20 tubules. Experiments show that the detection results of our algorithm are very close to the results obtained manually. PMID:24110438
Larsen, Kristian; Faulkner, Guy E.?J.; Stone, Michelle R.
2013-01-01
Objectives. School route measurement often involves estimating the shortest network path. We challenged the relatively uncritical adoption of this method in school travel research and tested the route discordance hypothesis that several types of difference exist between shortest network paths and reported school routes. Methods. We constructed the mapped and shortest path through network routes for a sample of 759 children aged 9 to 13 years in grades 5 and 6 (boys?=?45%, girls?=?54%, unreported gender?=?1%), in Toronto, Ontario, Canada. We used Wilcoxon signed-rank tests to compare reported with shortest-path route measures including distance, route directness, intersection crossings, and route overlap. Measurement difference was explored by mode and location. Results. We found statistical evidence of route discordance for walkers and children who were driven and detected it more often for inner suburban cases. Evidence of route discordance varied by mode and school location. Conclusions. We found statistically significant differences for route structure and built environment variables measured along reported and geographic information systems–based shortest-path school routes. Uncertainty produced by the shortest-path approach challenges its conceptual and empirical validity in school travel research. PMID:23865648
He, Yunyue; Liu, Zhong; Shi, Jianmai; Wang, Yishan; Zhang, Jiaming; Liu, Jinyuan
2015-01-01
Emergency evacuation aims to transport people from dangerous places to safe shelters as quickly as possible. Police play an important role in the evacuation process, as they can handle traffic accidents immediately and help people move smoothly on roads. This paper investigates an evacuation routing problem that involves police resource allocation. We propose a novel k-th-shortest-path-based technique that uses explicit congestion control to optimize evacuation routing and police resource allocation. A nonlinear mixed-integer programming model is presented to formulate the problem. The model’s objective is to minimize the overall evacuation clearance time. Two algorithms are given to solve the problem. The first one linearizes the original model and solves the linearized problem with CPLEX. The second one is a heuristic algorithm that uses a police resource utilization efficiency index to directly solve the original model. This police resource utilization efficiency index significantly aids in the evaluation of road links from an evacuation throughput perspective. The proposed algorithms are tested with a number of examples based on real data from cities of different sizes. The computational results show that the police resource utilization efficiency index is very helpful in finding near-optimal solutions. Additionally, comparing the performance of the heuristic algorithm and the linearization method by using randomly generated examples indicates that the efficiency of the heuristic algorithm is superior. PMID:26226109
He, Yunyue; Liu, Zhong; Shi, Jianmai; Wang, Yishan; Zhang, Jiaming; Liu, Jinyuan
2015-01-01
Emergency evacuation aims to transport people from dangerous places to safe shelters as quickly as possible. Police play an important role in the evacuation process, as they can handle traffic accidents immediately and help people move smoothly on roads. This paper investigates an evacuation routing problem that involves police resource allocation. We propose a novel k-th-shortest-path-based technique that uses explicit congestion control to optimize evacuation routing and police resource allocation. A nonlinear mixed-integer programming model is presented to formulate the problem. The model's objective is to minimize the overall evacuation clearance time. Two algorithms are given to solve the problem. The first one linearizes the original model and solves the linearized problem with CPLEX. The second one is a heuristic algorithm that uses a police resource utilization efficiency index to directly solve the original model. This police resource utilization efficiency index significantly aids in the evaluation of road links from an evacuation throughput perspective. The proposed algorithms are tested with a number of examples based on real data from cities of different sizes. The computational results show that the police resource utilization efficiency index is very helpful in finding near-optimal solutions. Additionally, comparing the performance of the heuristic algorithm and the linearization method by using randomly generated examples indicates that the efficiency of the heuristic algorithm is superior. PMID:26226109
Maximum Entropy Models of Shortest Path and Outbreak Distributions in Networks
Bauckhage, Christian; Hadiji, Fabian
2015-01-01
Properties of networks are often characterized in terms of features such as node degree distributions, average path lengths, diameters, or clustering coefficients. Here, we study shortest path length distributions. On the one hand, average as well as maximum distances can be determined therefrom; on the other hand, they are closely related to the dynamics of network spreading processes. Because of the combinatorial nature of networks, we apply maximum entropy arguments to derive a general, physically plausible model. In particular, we establish the generalized Gamma distribution as a continuous characterization of shortest path length histograms of networks or arbitrary topology. Experimental evaluations corroborate our theoretical results.
NASA Astrophysics Data System (ADS)
Huang, Guo-Jiao; Bai, Chao-Ying; Greenhalgh, Stewart
2013-09-01
The traditional grid/cell-based wavefront expansion algorithms, such as the shortest path algorithm, can only find the first arrivals or multiply reflected (or mode converted) waves transmitted from subsurface interfaces, but cannot calculate the other later reflections/conversions having a minimax time path. In order to overcome the above limitations, we introduce the concept of a stationary minimax time path of Fermat's Principle into the multistage irregular shortest path method. Here we extend it from Cartesian coordinates for a flat earth model to global ray tracing of multiple phases in a 3-D complex spherical earth model. The ray tracing results for 49 different kinds of crustal, mantle and core phases show that the maximum absolute traveltime error is less than 0.12 s and the average absolute traveltime error is within 0.09 s when compared with the AK135 theoretical traveltime tables for a 1-D reference model. Numerical tests in terms of computational accuracy and CPU time consumption indicate that the new scheme is an accurate, efficient and a practical way to perform 3-D multiphase arrival tracking in regional or global traveltime tomography.
A Genetic Algorithm for Searching Shortest Lattice Vector of SVP Challenge
International Association for Cryptologic Research (IACR)
A Genetic Algorithm for Searching Shortest Lattice Vector of SVP Challenge Dan Ding1 , Guizhen Zhu2, China P. R. Abstract. In this paper, we propose a genetic algorithm for solving the shortest vector pruning. The experimental results show that the genetic algorithm runs rather good on the SVP challenge
The approach for shortest paths in fire succor based on component GIS technology
NASA Astrophysics Data System (ADS)
Han, Jie; Zhao, Yong; Dai, K. W.
2007-06-01
Fire safety is an important issue for the national economy and people's living. Efficiency and exactness of fire department succor directly relate to safety of peoples' lives and property. Many disadvantages of the traditional fire system have been emerged in practical applications. The preparation of pumpers is guided by wireless communication or wire communication, so its real-time and accurate performances are much poorer. The information about the reported fire, such as the position, disaster and map, et al., for alarm and command was processed by persons, which slows the reaction speed and delays the combat opportunity. In order to solve these disadvantages, it has an important role to construct a modern fire command center based on high technology. The construction of modern fire command center can realize the modernization and automation of fire command and management. It will play a great role in protecting safety of peoples' lives and property. The center can enhance battle ability and can reduce the direct and indirect loss of fire damage at most. With the development of science technology, Geographic Information System (GIS) has becoming a new information industry for hardware production, software development, data collection, space analysis and counseling. With the popularization of computers and the development of GIS, GIS has gained increasing broad applications for its strong functionality. Network analysis is one of the most important functions of GIS, and the most elementary and pivotal issue of network analysis is the calculation of shortest paths. The shortest paths are mostly applied to some emergent systems such as 119 fire alarms. These systems mainly require that the computation time of the optimal path should be 1-3 seconds. And during traveling, the next running path of the vehicles should be calculated in time. So the implement of the shortest paths must have a high efficiency. In this paper, the component GIS technology was applied to collect and record the data information (such as, the situation of this disaster, map and road status et al) of the reported fire firstly. The ant colony optimization was used to calculate the shortest path of fire succor secondly. The optimization results were sent to the pumpers, which can let pumpers choose the shortest paths intelligently and come to fire position with least time. The programming method for shortest paths is proposed in section 3. There are three parts in this section. The elementary framework of the proposed programming method is presented in part one. The systematic framework of GIS component is described in part two. The ant colony optimization employed is presented in part three. In section 4, a simple application instance was presented to demonstrate the proposed programming method. There are three parts in this section. The distributed Web application based on component GIS was described in part one. The optimization results without traffic constraint were presented in part two. The optimization results with traffic constraint were presented in part three. The contributions of this paper can be summarized as follows. (1) It proposed an effective approach for shortest paths in fire succor based on component GIS technology. This proposed approach can achieve the real-time decisions of shortest paths for fire succor. (2) It applied the ant colony optimization to implement the shortest path decision. The traffic information was considered in the shortest path decision using ant colony optimization. The final application instance suggests that the proposed approach is feasible, correct and valid.
DT-MRI Fiber Tracking: A Shortest Paths Approach
Andrew Zalesky
2008-01-01
We derive a new fiber tracking algorithm for DT- MRI that parts with the locally 'greedy' paradigm intrinsic to conventional tracking algorithms. We demonstrate the ability to precisely reconstruct a diverse range of fiber trajectori es in authentic and computer-generated DT-MRI data, for which well- known conventional tracking algorithms are shown to fail. Our approach is to pose fiber tracking
A Shortest Path Dependency Kernel for Relation Extraction Razvan C. Bunescu and Raymond J. Mooney
Bunescu, Razvan C.
of automatically derived syn- tactic information can lead to significant improve- ments in extraction accuracyA Shortest Path Dependency Kernel for Relation Extraction Razvan C. Bunescu and Raymond J. Mooney razvan,mooney@cs.utexas.edu Abstract We present a novel approach to relation extraction, based
Algorithms for Three Versions of the Shortest Common Superstring
Lonardi, Stefano
| + . . . + |sk| = n. Output: the shortest word s containing each si as a factor. Example: s1 = abaab, s2 = baba. Output: the shortest word s containing each si as a factor. Example: s1 = abaab, s2 = baba, s3 = aabbb, s. Output: the shortest word s containing each si as a factor. Example: s1 = abaab, s2 = baba, s3 = aabbb, s
Dynamic Approximate AllPairs Shortest Paths in Undirected Graphs
Zwick, Uri
/#, such estimated distances are exact.) # School of Computer Science, Tel Aviv University, Tel Aviv 69978, Israel. E(mn) and it answers each distance query in O(1) worstÂcase time. The algorithm uses â? O(n 2 ) space. A running timeÂ weighted undirected graphs: 1. For any fixed # > 0, a decremental algorithm with an expected total running
Ultrafast Shortest-Path Queries with Linear-Time Preprocessing
Matijevic, Domagoj
]. The asymptotic running time of Dijkstra's algorithm is O(m + n log m), where n is the number of nodes, and m in exactly that problem. Note that 1 #12;Figure 1: Transit nodes (red/bold dots) for a part of a city (center, dark) when travelling far (outside the light-gray area). road networks are particular in at least two
Scaling of average receiving time and average weighted shortest path on weighted Koch networks
NASA Astrophysics Data System (ADS)
Dai, Meifeng; Chen, Dandan; Dong, Yujuan; Liu, Jie
2012-12-01
In this paper we present weighted Koch networks based on classic Koch networks. A new method is used to determine the average receiving time (ART), whose key step is to write the sum of mean first-passage times (MFPTs) for all nodes to absorption at the trap located at a hub node as a recursive relation. We show that the ART exhibits a sublinear or linear dependence on network order. Thus, the weighted Koch networks are more efficient than classic Koch networks in receiving information. Moreover, average weighted shortest path (AWSP) is calculated. In the infinite network order limit, the AWSP depends on the scaling factor. The weighted Koch network grows unbounded but with the logarithm of the network size, while the weighted shortest paths stay bounded.
Multiple Source Shortest Paths in a Genus g Graph Sergio Cabello
Erickson, Jeff
Multiple Source Shortest Paths in a Genus g Graph Sergio Cabello Erin W. Chambers Abstract We give of Mathematics, IMFM, and Department of Mathematics, FMF, University of Ljubljana, Slovenia, sergio.cabello- Peled [5], O(g3/2 n3/2 log n) by Cabello and Mohar [1], and O(gO(g) n log n) by Kutz [10]. Our approach
A Computational Study Identifies HIV Progression-Related Genes Using mRMR and Shortest Path Tracing
Liu, Lei
2013-01-01
Since statistical relationships between HIV load and CD4+ T cell loss have been demonstrated to be weak, searching for host factors contributing to the pathogenesis of HIV infection becomes a key point for both understanding the disease pathology and developing treatments. We applied Maximum Relevance Minimum Redundancy (mRMR) algorithm to a set of microarray data generated from the CD4+ T cells of viremic non-progressors (VNPs) and rapid progressors (RPs) to identify host factors associated with the different responses to HIV infection. Using mRMR algorithm, 147 gene had been identified. Furthermore, we constructed a weighted molecular interaction network with the existing protein-protein interaction data from STRING database and identified 1331 genes on the shortest-paths among the genes identified with mRMR. Functional analysis shows that the functions relating to apoptosis play important roles during the pathogenesis of HIV infection. These results bring new insights of understanding HIV progression. PMID:24244287
A computational study identifies HIV progression-related genes using mRMR and shortest path tracing.
Ma, Chengcheng; Dong, Xiao; Li, Rudong; Liu, Lei
2013-01-01
Since statistical relationships between HIV load and CD4+ T cell loss have been demonstrated to be weak, searching for host factors contributing to the pathogenesis of HIV infection becomes a key point for both understanding the disease pathology and developing treatments. We applied Maximum Relevance Minimum Redundancy (mRMR) algorithm to a set of microarray data generated from the CD4+ T cells of viremic non-progressors (VNPs) and rapid progressors (RPs) to identify host factors associated with the different responses to HIV infection. Using mRMR algorithm, 147 gene had been identified. Furthermore, we constructed a weighted molecular interaction network with the existing protein-protein interaction data from STRING database and identified 1331 genes on the shortest-paths among the genes identified with mRMR. Functional analysis shows that the functions relating to apoptosis play important roles during the pathogenesis of HIV infection. These results bring new insights of understanding HIV progression. PMID:24244287
Analytical results for the distribution of shortest path lengths in random networks
NASA Astrophysics Data System (ADS)
Katzav, Eytan; Nitzan, Mor; ben-Avraham, Daniel; Krapivsky, P. L.; Kühn, Reimer; Ross, Nathan; Biham, Ofer
2015-07-01
We present two complementary analytical approaches for calculating the distribution of shortest path lengths in Erd?s-Rényi networks, based on recursion equations for the shells around a reference node and for the paths originating from it. The results are in agreement with numerical simulations for a broad range of network sizes and connectivities. The average and standard deviation of the distribution are also obtained. In the case in which the mean degree scales as N? with the network size, the distribution becomes extremely narrow in the asymptotic limit, namely almost all pairs of nodes are equidistant, at distance d=\\lfloor1/?\\rfloor from each other. The distribution of shortest path lengths between nodes of degree m and the rest of the network is calculated. Its average is shown to be a monotonically decreasing function of m, providing an interesting relation between a local property and a global property of the network. The methodology presented here can be applied to more general classes of networks.
THE SHORTEST PATH AMID 3-D POLYHEDRAL OBSTACLES SHUI-NEE CHOW, JUN LU, HAO-MIN ZHOU
Ferguson, Thomas S.
, namely it consists of straight line segments connected by junctions on the edges of the polyhedral in the presence of obstacles is one of the fundamental problems in path planning and robotics. The problem can be described as follows: given a finite number of obstacles in R2 or R3, what is the shortest path connecting
A Continuous-State Version of Discrete Randomized Shortest-Paths, with Application to Path Planning
Del Moral , Pierre
a weighted directed graph G, the RSP considers the policy that minimizes the expected cost (exploitation] is a well-known problem in the robotics community, described by [26] as "checking the consequences entropy [23]. The introduced path randomization allows balancing the load (number of packages) per path
Challenging of path planning algorithms for autonomous robot in known environment
NASA Astrophysics Data System (ADS)
Farah, R. N.; Irwan, N.; Zuraida, Raja Lailatul; Shaharum, Umairah; Hanafi@Omar, Hafiz Mohd
2014-06-01
Most of the mobile robot path planning is estimated to reach its predetermined aim through the shortest path and avoiding the obstacles. This paper is a survey on path planning algorithms of various current research and existing system of Unmanned Ground Vehicles (UGV) where their challenging issues to be intelligent autonomous robot. The focuses are some short reviews on individual papers for UGV in the known environment. Methods and algorithms in path planning for the autonomous robot had been discussed. From the reviews, we obtained that the algorithms proposed are appropriate for some cases such as single or multiple obstacles, static or movement obstacle and optimal shortest path. This paper also describes some pros and cons for every reviewed paper toward algorithms improvement for further work.
Freight Network Modeling System. Volume IV. Shortest-Path Analysis and Display user's guide
Not Available
1985-04-01
The Freight Network Modeling System (FNEM) is a general and flexible modeling system designed to have wide applicability to a variety of freight transportation analyses. The system consists of compatible network data bases, data management software, models of freight transportation, report generators, and graphics output. In many studies, a model as comprehensive as FNEM is not required. The second model, Shortest-Path Analysis and Display (SPAD), is a simpler model that optimizes routings of single shipments. The routing criteria that can be used are numerous - including minimizing cost, minimizing delay, minimizing population exposure (useful when considering shipments of hazardous materials), and minimizing accident risk. In addition to the above criteria, the routes can also be restricted to those with clearance for oversized loads or with sufficient load capabilities. SPAD can be used interactively and the routes can be displayed graphically. This volume contains a user's guide for SPAD including preprocessor programs and SPAD execution. 7 figs., 19 tabs.
Effective usage of shortest paths promotes transportation efficiency on scale-free networks
NASA Astrophysics Data System (ADS)
Du, Wen-Bo; Wu, Zhi-Xi; Cai, Kai-Quan
2013-09-01
With rapid economic and social development, the problem of traffic congestion is getting more and more serious. Accordingly, network traffic models have attracted extensive attention. In this paper, we introduce a shortest-remaining-path-first queuing strategy into a network traffic model on Barabási-Albert scale-free networks under efficient routing protocol, where one packet’s delivery priority is related to its current distance to the destination. Compared with the traditional first-in-first-out queuing strategy, although the network capacity has no evident changes, some other indexes reflecting transportation efficiency are significantly improved in the congestion state. Extensive simulation results and discussions are carried out to explain the phenomena. Our work may be helpful for the designing of optimal networked-traffic systems.
J. Sussmann; Guoqing Tang
1991-01-01
We illustrate the use of the techniques of modern geometric optimal control theory by studying the shortest paths for a model of a car that can move forwards and backwards. This problem was discussed in recent work by Reeds and Shepp who showed, by special methods, (a) that shortest path motion could always be achieved by means of trajectories of
Almeroth, Kevin C.
Orion: Shortest Path Estimation for Large Social Graphs Xiaohan Zhao, Alessandra Sala, Christo allowing constant time node distance computation. We describe Orion, a pro- totype graph coordinate system, and explore critical de- cisions in its design. Finally, we evaluate the accuracy of Orion's node distance
Bi-Qing Li; Tao Huang; Lei Liu; Yu-Dong Cai; Kuo-Chen Chou
2012-01-01
One of the most important and challenging problems in biomedicine and genomics is how to identify the disease genes. In this study, we developed a computational method to identify colorectal cancer-related genes based on (i) the gene expression profiles, and (ii) the shortest path analysis of functional protein association networks. The former has been used to select differentially expressed genes
Parameter Shortest Path Algorithms with an Application to Cyclic Staffing
Karp, Richard M.
Let G = (V,E) be a digraph with n vertices including a special vertex s. Let E' C E be a designated subset of edges. For each e E E there is an associated real number fl(e). Furthermore, let 1 if e E E' f2(e): 0 if e E-E' ...
Modeling wildfire propagation with Delaunay triangulation and shortest path algorithms
Smith, J. MacGregor
) reported in excess of 459 thousand fires on 9.6 million hectares of land. The cost of fire extinction U.S. dollars were spent daily on fire extinction during 2000-2004; 108 firefighters lost their lives analytical models of fire behavior/propagation are required to assess potential risk to human lives, property
NASA Astrophysics Data System (ADS)
Megherbi, Dalila B.; Teirelbar, A.; Boulenouar, A. J.
2001-09-01
Autonomous agent path planning is a main problem in the fields of machine learning and artificial intelligence. Reactive execution is often used in order to provide best decision for the agent's reactions. Although this problem is important in the stationary environment, most interesting environments are time varying. This paper is based on our previous work focusing on combining the potential field model with reinforcement learning to solve the stationary path problem. In this work we deal with the case of dynamic environment. In the dynamic environment, the motion of the obstacles provides for different problems and challenges, which our proposed algorithm in this paper encounters and addresses.
Kéchichian, Razmig; Valette, Sébastien; Desvignes, Michel; Prost, Rémy
2013-11-01
We derive shortest-path constraints from graph models of structure adjacency relations and introduce them in a joint centroidal Voronoi image clustering and Graph Cut multiobject semiautomatic segmentation framework. The vicinity prior model thus defined is a piecewise-constant model incurring multiple levels of penalization capturing the spatial configuration of structures in multiobject segmentation. Qualitative and quantitative analyses and comparison with a Potts prior-based approach and our previous contribution on synthetic, simulated, and real medical images show that the vicinity prior allows for the correct segmentation of distinct structures having identical intensity profiles and improves the precision of segmentation boundary placement while being fairly robust to clustering resolution. The clustering approach we take to simplify images prior to segmentation strikes a good balance between boundary adaptivity and cluster compactness criteria furthermore allowing to control the trade-off. Compared with a direct application of segmentation on voxels, the clustering step improves the overall runtime and memory footprint of the segmentation process up to an order of magnitude without compromising the quality of the result. PMID:23807445
NASA Astrophysics Data System (ADS)
Wu, Zikai; Hou, Baoyu; Zhang, Hongjuan; Jin, Feng
2014-04-01
Deterministic network models have been attractive media for discussing dynamical processes' dependence on network structural features. On the other hand, the heterogeneity of weights affect dynamical processes taking place on networks. In this paper, we present a family of weighted expanded Koch networks based on Koch networks. They originate from a r-polygon, and each node of current generation produces m r-polygons including the node and whose weighted edges are scaled by factor w in subsequent evolutionary step. We derive closed-form expressions for average weighted shortest path length (AWSP). In large network, AWSP stays bounded with network order growing (0 < w < 1). Then, we focus on a special random walks and trapping issue on the networks. In more detail, we calculate exactly the average receiving time (ART). ART exhibits a sub-linear dependence on network order (0 < w < 1), which implies that nontrivial weighted expanded Koch networks are more efficient than un-weighted expanded Koch networks in receiving information. Besides, efficiency of receiving information at hub nodes is also dependent on parameters m and r. These findings may pave the way for controlling information transportation on general weighted networks.
Wu, Jie
. The work of J. Wu was supported in part by U.S. NSF Grant CCR 9900646 and Grant ANI 0073736. Responsible, Philadelphia, PA 19104 USA (e-mail: LSheng@mcs.drexel.edu). J. Wu is with the Department of Computer Science) is Not Optimal for a General N N Torus Li Sheng and Jie Wu, Senior Member, IEEE Abstract--A shortest-path routing
PARALLEL EVOLUTIONARY ALGORITHMS FOR UAV PATH PLANNING
PARALLEL EVOLUTIONARY ALGORITHMS FOR UAV PATH PLANNING Dong Jia Post-Doctoral Research Associate vehicles (UAVs). Premature convergence prevents evolutionary-based algorithms from reaching global optimal. To overcome this problem, this paper presents a framework of parallel evolutionary algorithms for UAV path
The Shortest Path to Happiness: Recommending Beautiful, Quiet, and Happy Routes in the City
Quercia, Daniele; Aiello, Luca Maria
2014-01-01
When providing directions to a place, web and mobile mapping services are all able to suggest the shortest route. The goal of this work is to automatically suggest routes that are not only short but also emotionally pleasant. To quantify the extent to which urban locations are pleasant, we use data from a crowd-sourcing platform that shows two street scenes in London (out of hundreds), and a user votes on which one looks more beautiful, quiet, and happy. We consider votes from more than 3.3K individuals and translate them into quantitative measures of location perceptions. We arrange those locations into a graph upon which we learn pleasant routes. Based on a quantitative validation, we find that, compared to the shortest routes, the recommended ones add just a few extra walking minutes and are indeed perceived to be more beautiful, quiet, and happy. To test the generality of our approach, we consider Flickr metadata of more than 3.7M pictures in London and 1.3M in Boston, compute proxies for the crowdsourced...
Patrikalakis, Nicholas M.
Journal of Mechanical Design, ASME Transactions, Vol. 118 No. 4, pages 499-508, 1996. Computation of Shortest Paths on Free-Form Parametric Surfaces Takashi Maekawa Massachusetts Institute of Technology, computation of medial axis transforms of trimmed surface patches, terrain navigation and NC machining
Spreading and shortest paths in systems with sparse long-range connections
Cristian F. Moukarzel
1999-01-01
Spreading according to simple rules (e.g. of fire or diseases), and\\u000ashortest-path distances are studied on d-dimensional systems with a small\\u000adensity p per site of long-range connections (``Small-World'' lattices). The\\u000avolume V(t) covered by the spreading quantity on an infinite system is exactly\\u000acalculated in all dimensions. We find that V(t) grows initially as t^d\\/d for\\u000at<< t^* =
A new efficient optimal path planner for mobile robot based on Invasive Weed Optimization algorithm
NASA Astrophysics Data System (ADS)
Mohanty, Prases K.; Parhi, Dayal R.
2014-12-01
Planning of the shortest/optimal route is essential for efficient operation of autonomous mobile robot or vehicle. In this paper Invasive Weed Optimization (IWO), a new meta-heuristic algorithm, has been implemented for solving the path planning problem of mobile robot in partially or totally unknown environments. This meta-heuristic optimization is based on the colonizing property of weeds. First we have framed an objective function that satisfied the conditions of obstacle avoidance and target seeking behavior of robot in partially or completely unknown environments. Depending upon the value of objective function of each weed in colony, the robot avoids obstacles and proceeds towards destination. The optimal trajectory is generated with this navigational algorithm when robot reaches its destination. The effectiveness, feasibility, and robustness of the proposed algorithm has been demonstrated through series of simulation and experimental results. Finally, it has been found that the developed path planning algorithm can be effectively applied to any kinds of complex situation.
Stochastic Evolutionary Algorithms for Planning Robot Paths
NASA Technical Reports Server (NTRS)
Fink, Wolfgang; Aghazarian, Hrand; Huntsberger, Terrance; Terrile, Richard
2006-01-01
A computer program implements stochastic evolutionary algorithms for planning and optimizing collision-free paths for robots and their jointed limbs. Stochastic evolutionary algorithms can be made to produce acceptably close approximations to exact, optimal solutions for path-planning problems while often demanding much less computation than do exhaustive-search and deterministic inverse-kinematics algorithms that have been used previously for this purpose. Hence, the present software is better suited for application aboard robots having limited computing capabilities (see figure). The stochastic aspect lies in the use of simulated annealing to (1) prevent trapping of an optimization algorithm in local minima of an energy-like error measure by which the fitness of a trial solution is evaluated while (2) ensuring that the entire multidimensional configuration and parameter space of the path-planning problem is sampled efficiently with respect to both robot joint angles and computation time. Simulated annealing is an established technique for avoiding local minima in multidimensional optimization problems, but has not, until now, been applied to planning collision-free robot paths by use of low-power computers.
Path planning for autonomous UAV via vibrational genetic algorithm
Y. Volkan Pehlivanoglu; Oktay Baysal; Abdurrahman Hacioglu
2007-01-01
Purpose – It is aimed to provide an efficient algorithm for path planning in guidance of autonomous unmanned aerial vehicle (UAV) through 3D terrain environments. Design\\/methodology\\/approach – As a stochastic search method, vibrational genetic algorithm (VGA) is improved and used to accelerate the algorithm for path planning. Findings – Using VGA, an efficient path planning algorithm for autonomous UAV was
A load-balance path selection algorithm in automatically swiched optical network (ASON)
NASA Astrophysics Data System (ADS)
Gao, Fei; Lu, Yueming; Ji, Yuefeng
2007-11-01
In this paper, a novel load-balance algorithm is proposed to provide an approach to optimized path selection in automatically swiched optical network (ASON). By using this algorithm, improved survivability and low congestion can be achieved. The static nature of current routing algorithms, such as OSPF or IS-IS, has made the situation worse since the traffic is concentrated on the "least-cost" paths which causes the congestion for some links while leaving other links lightly loaded. So, the key is to select suitable paths to balance the network load to optimize network resource utilization and traffic performance. We present a method to provide the capability to control traffic engineering so that the carriers can define their own strategies for optimizations and apply them to path selection for dynamic load balancing. With considering load distribution and topology information, capacity utilization factor is introduced into Dijkstra (shortest path selection) for path selection to achieve balancing traffic over network. Routing simulations have been done over mesh networks to compare the two different algorithms. With the simulation results, a conclusion can be made on the performance of different algorithms.
A Path Algorithm for Constrained Estimation
Zhou, Hua; Lange, Kenneth
2013-01-01
Many least-square problems involve affine equality and inequality constraints. Although there are a variety of methods for solving such problems, most statisticians find constrained estimation challenging. The current article proposes a new path-following algorithm for quadratic programming that replaces hard constraints by what are called exact penalties. Similar penalties arise in l1 regularization in model selection. In the regularization setting, penalties encapsulate prior knowledge, and penalized parameter estimates represent a trade-off between the observed data and the prior knowledge. Classical penalty methods of optimization, such as the quadratic penalty method, solve a sequence of unconstrained problems that put greater and greater stress on meeting the constraints. In the limit as the penalty constant tends to ?, one recovers the constrained solution. In the exact penalty method, squared penalties!are replaced by absolute value penalties, and the solution is recovered for a finite value of the penalty constant. The exact path-following method starts at the unconstrained solution and follows the solution path as the penalty constant increases. In the process, the solution path hits, slides along, and exits from the various constraints. Path following in Lasso penalized regression, in contrast, starts with a large value of the penalty constant and works its way downward. In both settings, inspection of the entire solution path is revealing. Just as with the Lasso and generalized Lasso, it is possible to plot the effective degrees of freedom along the solution path. For a strictly convex quadratic program, the exact penalty algorithm can be framed entirely in terms of the sweep operator of regression analysis. A few well-chosen examples illustrate the mechanics and potential of path following. This article has supplementary materials available online. PMID:24039382
Robot path planning using a genetic algorithm
NASA Technical Reports Server (NTRS)
Cleghorn, Timothy F.; Baffes, Paul T.; Wang, Liu
1988-01-01
Robot path planning can refer either to a mobile vehicle such as a Mars Rover, or to an end effector on an arm moving through a cluttered workspace. In both instances there may exist many solutions, some of which are better than others, either in terms of distance traversed, energy expended, or joint angle or reach capabilities. A path planning program has been developed based upon a genetic algorithm. This program assumes global knowledge of the terrain or workspace, and provides a family of good paths between the initial and final points. Initially, a set of valid random paths are constructed. Successive generations of valid paths are obtained using one of several possible reproduction strategies similar to those found in biological communities. A fitness function is defined to describe the goodness of the path, in this case including length, slope, and obstacle avoidance considerations. It was found that with some reproduction strategies, the average value of the fitness function improved for successive generations, and that by saving the best paths of each generation, one could quite rapidly obtain a collection of good candidate solutions.
An Adaptive Path Planning Algorithm for Cooperating Unmanned Air Vehicles
Cunningham, C.T.; Roberts, R.S.
2000-09-12
An adaptive path planning algorithm is presented for cooperating Unmanned Air Vehicles (UAVs) that are used to deploy and operate land-based sensor networks. The algorithm employs a global cost function to generate paths for the UAVs, and adapts the paths to exceptions that might occur. Examples are provided of the paths and adaptation.
Adaptive path planning algorithm for cooperating unmanned air vehicles
Cunningham, C T; Roberts, R S
2001-02-08
An adaptive path planning algorithm is presented for cooperating Unmanned Air Vehicles (UAVs) that are used to deploy and operate land-based sensor networks. The algorithm employs a global cost function to generate paths for the UAVs, and adapts the paths to exceptions that might occur. Examples are provided of the paths and adaptation.
Approximation Algorithms for Disjoint Paths Problems Jon Michael Kleinberg
Kleinberg, Jon
a number of related algorithms by this approach, including a routing algorithm for the mesh that is optimalApproximation Algorithms for Disjoint Paths Problems by Jon Michael Kleinberg S.M., Electrical Students #12; 2 #12; Approximation Algorithms for Disjoint Paths Problems by Jon Michael Kleinberg
The Stable Paths Problem and Interdomain Routing Timothy G. Griffin F. Bruce Shepherd Gordon Wilfong
Wilfong, Gordon
The Stable Paths Problem and Interdomain Routing Timothy G. Griffin F. Bruce Shepherd Gordon essentially im plement distributed algorithms for solving the Shortest Paths Problem. The Border Gateway is not solving a shortest paths problem since any interdomain protocol is required to allow policybased metrics
Exact Algorithms for the Canadian Traveller Problem on Paths and Trees
Karger, David
2008-01-28
The Canadian Traveller problem is a stochastic shortest paths problem in which one learns the cost of an edge only when arriving at one of its endpoints. The goal is to find an adaptive policy (adjusting as one learns more ...
Improved algorithms for reaction path following: Higher-order implicit algorithms
Schlegel, H. Bernhard
Improved algorithms for reaction path following: Higher-order implicit algorithms Carlos Gonzaleza (Received 13May 1991;accepted17June 1991) Eight new algorithms for reaction path following are presented or if accurate propertiessuch ascurvature and frequenciesare needed.3*4 Numerous algorithms exist for following
NASA Astrophysics Data System (ADS)
Peng, Jinmin; Yan, He; Li, Taifu
2005-12-01
The focus of this study is path selection for manufacturing processing, such as finding the shortest processing path, in an application of such a printed circuit board in the electronic industry. This paper models this kind of processing path optimization problem by application of a GA algorithm. First, the related problem of math modeling is discussed, such as coding methods, selection of fitness functions, and choice of genetic operators such as a selection operator, crossover operator, reverse operator, mutation operator and related parameters. All of these are used to build a solving model. Then related factor of genetic optimization algorithm such as initial generation, fitness evaluation, computing steps and so on was designed. The results of simulation and comparisons with practical application show that GA is feasible and valid.
Shepherd, Bruce
The Stable Paths Problem and Interdomain Routing Timothy G. Griffin and F. Bruce Shepherd distributed algorithms for solving the Shortest Paths Problem. The Border Gateway Protocol (BGP) is currently the only interdomain routing protoÂ col deployed in the Internet. BGP is not solving a shortest paths
ON GENERALIZED NEWTON ALGORITHMS : QUADRATIC CONVERGENCE, PATH-FOLLOWING
Malajovich, Gregorio
ON GENERALIZED NEWTON ALGORITHMS : QUADRATIC CONVERGENCE, PATH-FOLLOWING AND ERROR ANALYSIS GREGORIO MALAJOVICH Abstract. Newton iteration is known (under some precise conditions) to con- verge) to actually compute Newton iteration exactly. In this paper, approximate Newton iteration is investigated
PCB Drill Path Optimization by Combinatorial Cuckoo Search Algorithm
Lim, Wei Chen Esmonde; Kanagaraj, G.; Ponnambalam, S. G.
2014-01-01
Optimization of drill path can lead to significant reduction in machining time which directly improves productivity of manufacturing systems. In a batch production of a large number of items to be drilled such as printed circuit boards (PCB), the travel time of the drilling device is a significant portion of the overall manufacturing process. To increase PCB manufacturing productivity and to reduce production costs, a good option is to minimize the drill path route using an optimization algorithm. This paper reports a combinatorial cuckoo search algorithm for solving drill path optimization problem. The performance of the proposed algorithm is tested and verified with three case studies from the literature. The computational experience conducted in this research indicates that the proposed algorithm is capable of efficiently finding the optimal path for PCB holes drilling process. PMID:24707198
PCB drill path optimization by combinatorial cuckoo search algorithm.
Lim, Wei Chen Esmonde; Kanagaraj, G; Ponnambalam, S G
2014-01-01
Optimization of drill path can lead to significant reduction in machining time which directly improves productivity of manufacturing systems. In a batch production of a large number of items to be drilled such as printed circuit boards (PCB), the travel time of the drilling device is a significant portion of the overall manufacturing process. To increase PCB manufacturing productivity and to reduce production costs, a good option is to minimize the drill path route using an optimization algorithm. This paper reports a combinatorial cuckoo search algorithm for solving drill path optimization problem. The performance of the proposed algorithm is tested and verified with three case studies from the literature. The computational experience conducted in this research indicates that the proposed algorithm is capable of efficiently finding the optimal path for PCB holes drilling process. PMID:24707198
Extracting contours of oval-shaped objects by Hough transform and minimal path algorithms
NASA Astrophysics Data System (ADS)
Tleis, Mohamed; Verbeek, Fons J.
2014-04-01
Circular and oval-like objects are very common in cell and micro biology. These objects need to be analyzed, and to that end, digitized images from the microscope are used so as to come to an automated analysis pipeline. It is essential to detect all the objects in an image as well as to extract the exact contour of each individual object. In this manner it becomes possible to perform measurements on these objects, i.e. shape and texture features. Our measurement objective is achieved by probing contour detection through dynamic programming. In this paper we describe a method that uses Hough transform and two minimal path algorithms to detect contours of (ovoid-like) objects. These algorithms are based on an existing grey-weighted distance transform and a new algorithm to extract the circular shortest path in an image. The methods are tested on an artificial dataset of a 1000 images, with an F1-score of 0.972. In a case study with yeast cells, contours from our methods were compared with another solution using Pratt's figure of merit. Results indicate that our methods were more precise based on a comparison with a ground-truth dataset. As far as yeast cells are concerned, the segmentation and measurement results enable, in future work, to retrieve information from different developmental stages of the cell using complex features.
Jiang, Hai, 1979-
2004-01-01
This thesis aims at the development of faster Dynamic Traffic Assignment (DTA) models to meet the computational efficiency required by real world applications. A DTA model can be decomposed into several sub-models, of which ...
Scalability of Parallel Algorithms for the AllPairs Shortest Path Problem \\Lambda
Kumar, Vipin
version of this paper appeared in the proceedings of the 1990 International Conference on Parallel Computer Science Department University of Minnesota Minneapolis, MN 55455 Internet: kumar@cs.umn.edu Vineet. \\Lambda This work was partially supported by Army Research Office grant # 28408MASDI to the University
Autonomous routing algorithms for networks with wide-spread failures
Modiano, Eytan H.
We study end-to-end delay performance of different routing algorithms in networks with random failures. Specifically, we compare delay performances of differential backlog (DB) and shortest path (SP) routing algorithms and ...
All-Pairs Shortest Paths with Real Weights in O(n 3 = log n) Time Timothy M. Chan
Chan, Timothy M.
is attainable: he gave an algorithm with an impressive-looking time bound of O(n 3 (log log n= log n) 1 log log n= log n) and O(n 3 = p log n) respectively. Just last year, several interesting, independent developments have occurred: #12;rst Han [12] announced an improved O(n 3 (log log n= log n) 5=7 )-time
Self avoiding paths routing algorithm in scale-free networks.
Rachadi, Abdeljalil; Jedra, Mohamed; Zahid, Noureddine
2013-03-01
In this paper, we present a new routing algorithm called "the self avoiding paths routing algorithm." Its application to traffic flow in scale-free networks shows a great improvement over the so called "efficient routing" protocol while at the same time maintaining a relatively low average packet travel time. It has the advantage of minimizing path overlapping throughout the network in a self consistent manner with a relatively small number of iterations by maintaining an equilibrated path distribution especially among the hubs. This results in a significant shifting of the critical packet generation rate over which traffic congestion occurs, thus permitting the network to sustain more information packets in the free flow state. The performance of the algorithm is discussed both on a Bara?basi-Albert network and real autonomous system network data. PMID:23556951
Mobile transporter path planning using a genetic algorithm approach
NASA Technical Reports Server (NTRS)
Baffes, Paul; Wang, Lui
1988-01-01
The use of an optimization technique known as a genetic algorithm for solving the mobile transporter path planning problem is investigated. The mobile transporter is a traveling robotic vehicle proposed for the Space Station which must be able to reach any point of the structure autonomously. Specific elements of the genetic algorithm are explored in both a theoretical and experimental sense. Recent developments in genetic algorithm theory are shown to be particularly effective in a path planning problem domain, though problem areas can be cited which require more research. However, trajectory planning problems are common in space systems and the genetic algorithm provides an attractive alternative to the classical techniques used to solve these problems.
Fast quantum algorithms for traversing paths of eigenstates
S. Boixo; E. Knill; R. D. Somma
2010-05-17
Consider a path of non-degenerate eigenstates of unitary operators or Hamiltonians with minimum eigenvalue gap G. The eigenpath traversal problem is to transform one or more copies of the initial to the final eigenstate. Solutions to this problem have applications ranging from quantum physics simulation to optimization. For Hamiltonians, the conventional way of doing this is by applying the adiabatic theorem. We give ``digital'' methods for performing the transformation that require no assumption on path continuity or differentiability other than the absence of large jumps. Given sufficient information about eigenvalues and overlaps between states on the path, the transformation can be accomplished with complexity O(L/G log(L/e)), where L is the angular length of the path and e is a specified bound on the error of the output state. We show that the required information can be obtained in a first set of transformations, whose complexity per state transformed has an additional factor that depends logarithmically on a maximum angular velocity along the path. This velocity is averaged over constant angular distances and does not require continuity. Our methods have substantially better behavior than conventional adiabatic algorithms, with fewer conditions on the path. They also improve on the previously best digital methods and demonstrate that path length and the gap are the primary parameters that determine the complexity of state transformation along a path.
Finding Breach Paths Using the Watershed Segmentation Algorithm in Surveillance
Finding Breach Paths Using the Watershed Segmentation Algorithm in Surveillance Wireless Sensor, Turkey Abstract. Considering wireless sensor networks for border surveillance, one of the major concerns coverage of surveillance wireless sensor networks is studied by utilizing a well-known image processing
Algorithms for Computing QoS Paths with Restoration
Sprintson, Alexander
1 Algorithms for Computing QoS Paths with Restoration Yigal Bejerano, Yuri Breitbart, Member, IEEE-- There is a growing interest among service providers to offer new services with Quality of Service (QoS) guarantees that are also resilient to failures. Supporting QoS connections requires the existence of a routing mechanism
Path Planning Algorithms for Autonomous Border Patrol Vehicles
NASA Astrophysics Data System (ADS)
Lau, George Tin Lam
This thesis presents an online path planning algorithm developed for unmanned vehicles in charge of autonomous border patrol. In this Pursuit-Evasion game, the unmanned vehicle is required to capture multiple trespassers on its own before any of them reach a target safe house where they are safe from capture. The problem formulation is based on Isaacs' Target Guarding problem, but extended to the case of multiple evaders. The proposed path planning method is based on Rapidly-exploring random trees (RRT) and is capable of producing trajectories within several seconds to capture 2 or 3 evaders. Simulations are carried out to demonstrate that the resulting trajectories approach the optimal solution produced by a nonlinear programming-based numerical optimal control solver. Experiments are also conducted on unmanned ground vehicles to show the feasibility of implementing the proposed online path planning algorithm on physical applications.
A NEW IMPLEMENTATION OF YEN'S RANKING LOOPLESS PATHS ALGORITHM\\Lambda
Pascoal, Marta Margarida Braz
A NEW IMPLEMENTATION OF YEN'S RANKING LOOPLESS PATHS ALGORITHM\\Lambda Ernesto Martins Marta Pascoal.gz \\Lambda Issued from: ``A new implementation of Yen's ranking loopless paths algoÂ rithm'', E. Martins of Yen's ranking loopless paths algorithm Yen's algorithm is a classical algorithm for ranking the K
A Bat Algorithm with Mutation for UCAV Path Planning
Wang, Gaige; Guo, Lihong; Duan, Hong; Liu, Luo; Wang, Heqi
2012-01-01
Path planning for uninhabited combat air vehicle (UCAV) is a complicated high dimension optimization problem, which mainly centralizes on optimizing the flight route considering the different kinds of constrains under complicated battle field environments. Original bat algorithm (BA) is used to solve the UCAV path planning problem. Furthermore, a new bat algorithm with mutation (BAM) is proposed to solve the UCAV path planning problem, and a modification is applied to mutate between bats during the process of the new solutions updating. Then, the UCAV can find the safe path by connecting the chosen nodes of the coordinates while avoiding the threat areas and costing minimum fuel. This new approach can accelerate the global convergence speed while preserving the strong robustness of the basic BA. The realization procedure for original BA and this improved metaheuristic approach BAM is also presented. To prove the performance of this proposed metaheuristic method, BAM is compared with BA and other population-based optimization methods, such as ACO, BBO, DE, ES, GA, PBIL, PSO, and SGA. The experiment shows that the proposed approach is more effective and feasible in UCAV path planning than the other models. PMID:23365518
A bat algorithm with mutation for UCAV path planning.
Wang, Gaige; Guo, Lihong; Duan, Hong; Liu, Luo; Wang, Heqi
2012-01-01
Path planning for uninhabited combat air vehicle (UCAV) is a complicated high dimension optimization problem, which mainly centralizes on optimizing the flight route considering the different kinds of constrains under complicated battle field environments. Original bat algorithm (BA) is used to solve the UCAV path planning problem. Furthermore, a new bat algorithm with mutation (BAM) is proposed to solve the UCAV path planning problem, and a modification is applied to mutate between bats during the process of the new solutions updating. Then, the UCAV can find the safe path by connecting the chosen nodes of the coordinates while avoiding the threat areas and costing minimum fuel. This new approach can accelerate the global convergence speed while preserving the strong robustness of the basic BA. The realization procedure for original BA and this improved metaheuristic approach BAM is also presented. To prove the performance of this proposed metaheuristic method, BAM is compared with BA and other population-based optimization methods, such as ACO, BBO, DE, ES, GA, PBIL, PSO, and SGA. The experiment shows that the proposed approach is more effective and feasible in UCAV path planning than the other models. PMID:23365518
Path Planning Algorithms for the Adaptive Sensor Fleet
NASA Technical Reports Server (NTRS)
Stoneking, Eric; Hosler, Jeff
2005-01-01
The Adaptive Sensor Fleet (ASF) is a general purpose fleet management and planning system being developed by NASA in coordination with NOAA. The current mission of ASF is to provide the capability for autonomous cooperative survey and sampling of dynamic oceanographic phenomena such as current systems and algae blooms. Each ASF vessel is a software model that represents a real world platform that carries a variety of sensors. The OASIS platform will provide the first physical vessel, outfitted with the systems and payloads necessary to execute the oceanographic observations described in this paper. The ASF architecture is being designed for extensibility to accommodate heterogenous fleet elements, and is not limited to using the OASIS platform to acquire data. This paper describes the path planning algorithms developed for the acquisition phase of a typical ASF task. Given a polygonal target region to be surveyed, the region is subdivided according to the number of vessels in the fleet. The subdivision algorithm seeks a solution in which all subregions have equal area and minimum mean radius. Once the subregions are defined, a dynamic programming method is used to find a minimum-time path for each vessel from its initial position to its assigned region. This path plan includes the effects of water currents as well as avoidance of known obstacles. A fleet-level planning algorithm then shuffles the individual vessel assignments to find the overall solution which puts all vessels in their assigned regions in the minimum time. This shuffle algorithm may be described as a process of elimination on the sorted list of permutations of a cost matrix. All these path planning algorithms are facilitated by discretizing the region of interest onto a hexagonal tiling.
Analysis of the contact graph routing algorithm: Bounding interplanetary paths
NASA Astrophysics Data System (ADS)
Birrane, Edward; Burleigh, Scott; Kasch, Niels
2012-06-01
Interplanetary communication networks comprise orbiters, deep-space relays, and stations on planetary surfaces. These networks must overcome node mobility, constrained resources, and significant propagation delays. Opportunities for wireless contact rely on calculating transmit and receive opportunities, but the Euclidean-distance diameter of these networks (measured in light-seconds and light-minutes) precludes node discovery and contact negotiation. Propagation delay may be larger than the line-of-sight contact between nodes. For example, Mars and Earth orbiters may be separated by up to 20.8 min of signal propagation time. Such spacecraft may never share line-of-sight, but may uni-directionally communicate if one orbiter knows the other's future position. The Contact Graph Routing (CGR) approach is a family of algorithms presented to solve the messaging problem of interplanetary communications. These algorithms exploit networks where nodes exhibit deterministic mobility. For CGR, mobility and bandwidth information is pre-configured throughout the network allowing nodes to construct transmit opportunities. Once constructed, routing algorithms operate on this contact graph to build an efficient path through the network. The interpretation of the contact graph, and the construction of a bounded approximate path, is critically important for adoption in operational systems. Brute force approaches, while effective in small networks, are computationally expensive and will not scale. Methods of inferring cycles or other librations within the graph are difficult to detect and will guide the practical implementation of any routing algorithm. This paper presents a mathematical analysis of a multi-destination contact graph algorithm (MD-CGR), demonstrates that it is NP-complete, and proposes realistic constraints that make the problem solvable in polynomial time, as is the case with the originally proposed CGR algorithm. An analysis of path construction to complement hop-by-hop forwarding is presented as the CGR-EB algorithm. Future work is proposed to handle the presence of dynamic changes to the network, as produced by congestion, link disruption, and errors in the contact graph. We conclude that pre-computation, and thus CGR style algorithms, is the only efficient method of routing in a multi-node, multi-path interplanetary network and that algorithmic analysis is the key to its implementation in operational systems.
Path planning algorithms for assembly sequence planning. [in robot kinematics
NASA Technical Reports Server (NTRS)
Krishnan, S. S.; Sanderson, Arthur C.
1991-01-01
Planning for manipulation in complex environments often requires reasoning about the geometric and mechanical constraints which are posed by the task. In planning assembly operations, the automatic generation of operations sequences depends on the geometric feasibility of paths which permit parts to be joined into subassemblies. Feasible locations and collision-free paths must be present for part motions, robot and grasping motions, and fixtures. This paper describes an approach to reasoning about the feasibility of straight-line paths among three-dimensional polyhedral parts using an algebra of polyhedral cones. A second method recasts the feasibility conditions as constraints in a nonlinear optimization framework. Both algorithms have been implemented and results are presented.
Searching in an Unknown Environment: An Optimal Randomized Algorithm for the Cow-Path Problem
Tate, Steve
Searching in an Unknown Environment: An Optimal Randomized Algorithm for the Cow-Path Problem Ming in mind, the abstract problem known as the w-lane cow-path problem was designed. There are known optimal deterministic algorithms for the cow-path problem, and we give the first randomized algorithm in this paper. We
Node-capacitated packing of A-paths How to make a polynomial algorithm strongly polynomial?
Pap, Gyula
Node-capacitated packing of A-paths -- How to make a polynomial algorithm strongly polynomial, January, 2008 Gyula Pap Node-capacitated packing of A-paths #12;Polynomial Time Algorithm (P) INPUT: n Node-capacitated packing of A-paths #12;Some famous sp algorithms Assume our problem given as an LP
Density shrinking algorithm for community detection with path based similarity
NASA Astrophysics Data System (ADS)
Wu, Jianshe; Hou, Yunting; Jiao, Yang; Li, Yong; Li, Xiaoxiao; Jiao, Licheng
2015-09-01
Community structure is ubiquitous in real world complex networks. Finding the communities is the key to understand the functions of those networks. A lot of works have been done in designing algorithms for community detection, but it remains a challenge in the field. Traditional modularity optimization suffers from the resolution limit problem. Recent researches show that combining the density based technique with the modularity optimization can overcome the resolution limit and an efficient algorithm named DenShrink was provided. The main procedure of DenShrink is repeatedly finding and merging micro-communities (broad sense) into super nodes until they cannot merge. Analyses in this paper show that if the procedure is replaced by finding and merging only dense pairs, both of the detection accuracy and runtime can be obviously improved. Thus an improved density-based algorithm: ImDS is provided. Since the time complexity, path based similarity indexes are difficult to be applied in community detection for high performance. In this paper, the path based Katz index is simplified and used in the ImDS algorithm.
A surface hopping algorithm for nonadiabatic minimum energy path calculations.
Schapiro, Igor; Roca-Sanjuán, Daniel; Lindh, Roland; Olivucci, Massimo
2015-02-15
The article introduces a robust algorithm for the computation of minimum energy paths transiting along regions of near-to or degeneracy of adiabatic states. The method facilitates studies of excited state reactivity involving weakly avoided crossings and conical intersections. Based on the analysis of the change in the multiconfigurational wave function the algorithm takes the decision whether the optimization should continue following the same electronic state or switch to a different state. This algorithm helps to overcome convergence difficulties near degeneracies. The implementation in the MOLCAS quantum chemistry package is discussed. To demonstrate the utility of the proposed procedure four examples of application are provided: thymine, asulam, 1,2-dioxetane, and a three-double-bond model of the 11-cis-retinal protonated Schiff base. PMID:25564760
Differential Evolution with an Evolution Path: A DEEP Evolutionary Algorithm.
Li, Yuan-Long; Zhan, Zhi-Hui; Gong, Yue-Jiao; Chen, Wei-Neng; Zhang, Jun; Li, Yun
2015-09-01
Utilizing cumulative correlation information already existing in an evolutionary process, this paper proposes a predictive approach to the reproduction mechanism of new individuals for differential evolution (DE) algorithms. DE uses a distributed model (DM) to generate new individuals, which is relatively explorative, whilst evolution strategy (ES) uses a centralized model (CM) to generate offspring, which through adaptation retains a convergence momentum. This paper adopts a key feature in the CM of a covariance matrix adaptation ES, the cumulatively learned evolution path (EP), to formulate a new evolutionary algorithm (EA) framework, termed DEEP, standing for DE with an EP. Without mechanistically combining two CM and DM based algorithms together, the DEEP framework offers advantages of both a DM and a CM and hence substantially enhances performance. Under this architecture, a self-adaptation mechanism can be built inherently in a DEEP algorithm, easing the task of predetermining algorithm control parameters. Two DEEP variants are developed and illustrated in the paper. Experiments on the CEC'13 test suites and two practical problems demonstrate that the DEEP algorithms offer promising results, compared with the original DEs and other relevant state-of-the-art EAs. PMID:25314717
Algorithm Plans Collision-Free Path for Robotic Manipulator
NASA Technical Reports Server (NTRS)
Backes, Paul; Diaz-Calderon, Antonio
2007-01-01
An algorithm has been developed to enable a computer aboard a robot to autonomously plan the path of the manipulator arm of the robot to avoid collisions between the arm and any obstacle, which could be another part of the robot or an external object in the vicinity of the robot. In simplified terms, the algorithm generates trial path segments and tests each segment for potential collisions in an iterative process that ends when a sequence of collision-free segments reaches from the starting point to the destination. The main advantage of this algorithm, relative to prior such algorithms, is computational efficiency: the algorithm is designed to make minimal demands upon the limited computational resources available aboard a robot. This path-planning algorithm utilizes a modified version of the collision-detection method described in "Improved Collision-Detection Method for Robotic Manipulator" (NPO-30356), NASA Tech Briefs, Vol. 27, No. 3 (June 2003), page 72. The method involves utilization of mathematical models of the robot constructed prior to operation and similar models of external objects constructed automatically from sensory data acquired during operation. This method incorporates a previously developed method, known in the art as the method of oriented bounding boxes (OBBs), in which an object is represented approximately, for computational purposes, by a box that encloses its outer boundary. Because many parts of a robotic manipulator are cylindrical, the OBB method has been extended in this method to enable the approximate representation of cylindrical parts by use of octagonal or other multiple-OBB assemblies denoted oriented bounding prisms (OBPs). A multiresolution OBB/OBP representation of the robot and its manipulator arm and a multiresolution OBB representation of external objects (including terrain) are constructed and used in a process in which collisions at successively finer resolutions are detected through computational detection of overlaps between the corresponding OBB and OBP models. For computational efficiency, the process is started at the coarsest resolution and stopped as soon as possible, preferably before reaching the finest resolution. At the coarsest resolution, there is a single OBB enclosing all relevant external objects and a single OBB enclosing the entire robot. At the next finer level of resolution, the coarsest-resolution OBB is divided into two OBBs, and so forth. If no collision is detected at the coarsest resolution, then there is no need for further computation to detect collisions. If a collision is detected at the coarsest resolution, then tests for collisions are performed at the next finer level of resolution. This process is continued to successively finer resolutions until either no more collisions are detected or the finest resolution is reached.
Precise flight-path control using a predictive algorithm
NASA Technical Reports Server (NTRS)
Hess, R. A.; Jung, Y. C.
1991-01-01
Generalized predictive control describes an algorithm for the control of dynamic systems in which a control input is generated that minimizes a quadratic cost function consisting of a weighted sum of errors between desired and predicted future system output and future predicted control increments. The output predictions are obtained from an internal model of the plant dynamics. A design technique is discussed for applying the single-input/single-output generalized predictive control algorithm to a problem of longitudinal/vertical terrain-following flight of a rotorcraft. By using the generalized predictive control technique to provide inputs to a classically designed stability and control augmentation system, it is demonstrated that a robust flight-path control system can be created that exhibits excellent tracking performance.
A TRACKING ALGORITHM FOR CAR PATHS ON ROAD GABRIELLA BRETTI AND BENEDETTO PICCOLI
Bretti, Gabriella
A TRACKING ALGORITHM FOR CAR PATHS ON ROAD NETWORKS GABRIELLA BRETTI AND BENEDETTO PICCOLI Abstract. In this paper we introduce a computation algorithm to trace car paths on road networks, whose load evolution is modeled by conservation laws. This algorithm is composed by two parts: computation
Path Selection Algorithms for Multi-hop VANETs Chulhee Jang and Jae Hong Lee
Lee, Jae Hong
Path Selection Algorithms for Multi-hop VANETs Chulhee Jang and Jae Hong Lee School of Electrical--In this paper, we introduce a collision model for vehicular cluster and we propose path selection algorithms performance as SNRG-Opt. Through computer simulations, it is shown that the proposed algorithms reduce
Shortest Non-trivial Cycles in Directed Surface Graphs Jeff Erickson
Erickson, Jeff
the observation by Cabello and Mohar [12] that the shortest non-trivial cycle crosses any shortest path at most condition [44] and Cabello and Mo- har's crossing condition [12] are consequences of the following easy
An Algorithm for Measurement and Detection of Path Cheating in Virtual Environments
Ottawa, University of
An Algorithm for Measurement and Detection of Path Cheating in Virtual Environments Dewan Tanvir, shervin}@discover.uottawa.ca Abstract -- In this paper, we introduce a cheat-free path discovering process of the users, but cheating is detected through a controller. The controller recalculates a path segment when
A Method Based on Genetic Algorithm for Anti-ship Missile Path Planning
Xuechun Zhao; Xiaohong Fan
2009-01-01
This paper presented a novel approach to search and optimize path points for anti-ship missile path planning. We utilized the method of MAKLINK graph to construct free space, and then, a global state connected graph is built up for searching for all possible routes. genetic algorithm is used to search and optimize path points severally in these local routes. According
Path Design and Control Algorithms for Articulated Mobile Robots Ulf Andersson, Kent Mrozek
Lunds Universitet
Path Design and Control Algorithms for Articulated Mobile Robots Ulf Andersson, Kent Mrozek Q mobile robots. The X4Y4 curve and a control algorithm for an articulated mobile robot following an X4Y4 for real-world mobile robots. Ill-designed curves on a path can cause large guidance errors, and also
A fast and accurate algorithm for high-frequency trans-ionospheric path length determination
NASA Astrophysics Data System (ADS)
Wijaya, Dudy D.
2015-08-01
This paper presents a fast and accurate algorithm for high-frequency trans-ionospheric path length determination. The algorithm is merely based on the solution of the Eikonal equation that is solved using the conformal theory of refraction. The main advantages of the algorithm are summarized as follows. First, the algorithm can determine the optical path length without iteratively adjusting both elevation and azimuth angles and, hence, the computational time can be reduced. Second, for the same elevation and azimuth angles, the algorithm can simultaneously determine the phase and group of both ordinary and extra-ordinary optical path lengths for different frequencies. Results from numerical simulations show that the computational time required by the proposed algorithm to accurately determine 8 different optical path lengths is almost 17 times faster than that required by a 3D ionospheric ray-tracing algorithm. It is found that the computational time to determine multiple optical path lengths is the same with that for determining a single optical path length. It is also found that the proposed algorithm is capable of determining the optical path lengths with millimeter level of accuracies, if the magnitude of the squared ratio of the plasma frequency to the transmitted frequency is less than 1.33× 10^{-3} , and hence the proposed algorithm is applicable for geodetic applications.
Packing non-returning A-paths algorithmically EGRES --Egervary Research Group
Pap, Gyula
Packing non-returning A-paths algorithmically Gyula Pap EGRES -- EgervÂ´ary Research Group EÂ¨otvÂ¨os LorÂ´and University EUROCOMB'05, 6th September 2005 G.P. Packing A-paths #12;"Packing" = "Fully node-disjoint family" Background maximum non-bipartite matching (Berge '58; Tutte '47) packing A-paths, A-paths (Gallai
NASA Technical Reports Server (NTRS)
Izumi, K. H.; Thompson, J. L.; Groce, J. L.; Schwab, R. W.
1986-01-01
The design requirements for a 4D path definition algorithm are described. These requirements were developed for the NASA ATOPS as an extension of the Local Flow Management/Profile Descent algorithm. They specify the processing flow, functional and data architectures, and system input requirements, and recommended the addition of a broad path revision (reinitialization) function capability. The document also summarizes algorithm design enhancements and the implementation status of the algorithm on an in-house PDP-11/70 computer. Finally, the requirements for the pilot-computer interfaces, the lateral path processor, and guidance and steering function are described.
Multiple Manifold Clustering Using Curvature Constrained Path
Babaeian, Amir; Bayestehtashk, Alireza; Bandarabadi, Mojtaba
2015-01-01
The problem of multiple surface clustering is a challenging task, particularly when the surfaces intersect. Available methods such as Isomap fail to capture the true shape of the surface near by the intersection and result in incorrect clustering. The Isomap algorithm uses shortest path between points. The main draw back of the shortest path algorithm is due to the lack of curvature constrained where causes to have a path between points on different surfaces. In this paper we tackle this problem by imposing a curvature constraint to the shortest path algorithm used in Isomap. The algorithm chooses several landmark nodes at random and then checks whether there is a curvature constrained path between each landmark node and every other node in the neighborhood graph. We build a binary feature vector for each point where each entry represents the connectivity of that point to a particular landmark. Then the binary feature vectors could be used as a input of conventional clustering algorithm such as hierarchical clustering. We apply our method to simulated and some real datasets and show, it performs comparably to the best methods such as K-manifold and spectral multi-manifold clustering. PMID:26375819
Felner, Ariel
2004-01-01
tile puzzle and Rubik's Cube (Korf, 1999) are examples of the c fl2004 AI Access Foundation. All rights unknown territory. We introduce the PhysicalA* algorithm (PHA*) for solving this problem. PHA* expands. However, due to the physical nature of the problem, the complexity of the algorithm is measured
A 3D curvilinear skeletonization algorithm with application to path tracing
Paris-Sud XI, Université de
A 3D curvilinear skeletonization algorithm with application to path tracing John Chaussard1 a novel 3D curvilinear skeletonization algorithm which produces filtered skeletons without needing any user input, thanks to a new parallel algorithm based on the cubical complex framework. These skeletons
Identification of secondary path in ANC using diagonal recurrent neural networks with EKF algorithm
Riyanto T. Bambang; Redi R. Yacoub; K. Uchida
2004-01-01
This paper presents theoretical and experimental modeling of secondary path of an active noise control system in free space by using recurrent neural networks. A learning algorithm for diagonal recurrent neural networks is developed based on extended Kalman filter and is referred to as diagonal recurrent extended Kalman filter algorithm. The neural network structure and its algorithm are applied to
Y. Volkan Pehlivanoglu
A new optimization algorithm called multi-frequency vibrational genetic algorithm (mVGA) that can be used to solve the path planning problems of autonomous unmanned aerial vehicles (UAVs) is significantly improved. The algorithm emphasizes a new mutation application strategy and diversity variety such as the global random and the local random diversity. Clustering method and Voronoi diagram concepts are used within the
Genetic Algorithm based route planner for large urban street networks
Suranga Chandima Nanayakkara; Dipti Srinivasan; Lai Wei Lup; Xavier German; Elizabeth Taylor; S. H. Ong
2007-01-01
Finding the shortest path from a given source to a given destination is a well known and widely applicable problem. Most of the work done in the area have used static route planning algorithms such as A*, Dijkstra's, Bellman-Ford algorithm etc. Although these algorithms are said to be optimum, they are not capable of dealing with certain real life scenarios.
Optimizing Graph Algorithms for Improved Cache Performance*+ Joon-Sang Park
Park, Joon-Sang
and deeper memory hierarchies to hide the cost of cache misses. The performance of these deep memoryOptimizing Graph Algorithms for Improved Cache Performance*+ Joon-Sang Park University: Cache-Friendly Algorithms, Cache-Oblivious Algorithms, Graph Algorithms, Shortest Path, Minimum Spanning
Path planning for mobile robots based on visibility graphs and A* algorithm
NASA Astrophysics Data System (ADS)
Contreras, Juan D.; Martínez S., Fernando; Martínez S., Fredy H.
2015-07-01
One of most worked issues in the last years in robotics has been the study of strategies to path planning for mobile robots in static and observable conditions. This is an open problem without pre-defined rules (non-heuristic), which needs to measure the state of the environment, finds useful information, and uses an algorithm to select the best path. This paper proposes a simple and efficient geometric path planning strategy supported in digital image processing. The image of the environment is processed in order to identify obstacles, and thus the free space for navigation. Then, using visibility graphs, the possible navigation paths guided by the vertices of obstacles are produced. Finally the A* algorithm is used to find a best possible path. The alternative proposed is evaluated by simulation on a large set of test environments, showing in all cases its ability to find a free collision plausible path.
Kulling, Karl Christian
2009-01-01
This thesis presents new algorithms for path planning in a communications constrained environment for teams of unmanned vehicles. This problem involves a lead vehicle that must gather information from a set of locations ...
An Analysis of 3D Particle Path Integration Algorithms D.L. Darmofal
Peraire, Jaime
An Analysis of 3D Particle Path Integration Algorithms D.L. Darmofal Research Fellow Aerospace & Astronautics MIT Cambridge, MA 02139 Abstract Several techniques for the numerical integration of particle paths in steady and unsteady vector (velocity) fields are analyzed. Most of the analysis applies
A hybrid genetic algorithm for rescue path planning in uncertain adversarial environment
Jean Berger; Khaled Jabeur; Abdeslem Boukhtouta; Adel Guitouni; Ahmed Ghanmi
2010-01-01
Efficient vehicle path planning in hostile environment to carry out rescue or tactical logistic missions remains very challenging. Most approaches reported so far relies on key assumptions and heuristic procedures to reduce problem complexity. In this paper, a new model and a hybrid genetic algorithm are proposed to solve the rescue path planning problem for a single vehicle navigating in
Zhu, Xiaoyan
2007-04-25
is acyclic, only one resource constraint is involved, and all resource requirements and costs are positive (Dumitrescu and Boland (2003)). Hassin (1992) showed that SRCSP is polynomial solvable if arc costs or arc resource requirements are bounded. Dror... (1988a) presented a primal-dual reoptimization approach for SPPTW and Desrochers (1988) generalized it to solve SPPRW. Dumitrescu and Boland (2003) investigated variants of the label-setting algorithm of Desrochers and Soumis (1988b) for both SRCSP...
Some Applications of String Algorithms in Human-Computer Interaction
NASA Astrophysics Data System (ADS)
Räihä, Kari-Jouko
Two applications of string algorithms in human-computer interaction are reviewed: one for comparing error rates of text entry techniques, another for abstracting collections of scan paths (paths of eye movements). For both applications, the classic string edit distance algorithm proves useful. For the latter application shortest common supersequences provide one option for further development. Applying them as such could be misleading, but a suitable approximation could provide a useful representation of a set of scan paths.
NSDL National Science Digital Library
Richard Teviotdale, Tom Naps
Visualization of Floyd's all-pairs shortest paths algorithm. Includes dynamically highlighted pseudo code. Associated HTML page contains an algorithm description, pseudo code, and example trace, and discussion of efficiency analysis. The AV is set up as a series of 'slides' in one pane, and pseudocode in the adjacent pane. As the user steps through the 'slides', the associated pseudocode is highlighted. Occasional questions pop up for the user to answer. In addition to coloration for the graph as the algorithm progresses, there is a 2D array showing the algorithm's currently computed shortest distances. The explanation pages are a pretty good supplement to the AV (and vice versa). Students might still have a little bit of difficulty understanding the concept of the 'k paths', and there is no reference to dynamic programming, which would be helpful. Recommended as lecture aide, standalone, self-study suppliment to tutorial or lecture.
ERIC Educational Resources Information Center
Boker, Steven M.; McArdle, J. J.; Neale, Michael
2002-01-01
Presents an algorithm for the production of a graphical diagram from a matrix formula in such a way that its components are logically and hierarchically arranged. The algorithm, which relies on the matrix equations of J. McArdle and R. McDonald (1984), calculates the individual path components of expected covariance between variables and…
Recombinant Rule Selection in Evolutionary Algorithm for Fuzzy Path Planner of Robot Soccer
Jong-hwan Park; Daniel Stonier; Jong-hwan Kim; Byung-ha Ahn; Moon-gu Jeon
2006-01-01
A rule selection scheme of evolutionary algorithm is pro- posed to design fuzzy path planner for shooting ability in robot soccer. The fuzzy logic is good for the system that works with ambiguous in- formation. Evolutionary algorithm is employed to deal with difficulty and tediousness in deriving fuzzy control rules. Generic evolutionary al- gorithm, however, evaluate and select chromosomes which
Transport path optimization algorithm based on fuzzy integrated weights
NASA Astrophysics Data System (ADS)
Hou, Yuan-Da; Xu, Xiao-Hao
2014-11-01
Natural disasters cause significant damage to roads, making route selection a complicated logistical problem. To overcome this complexity, we present a method of using a trapezoidal fuzzy number to select the optimal transport path. Using the given trapezoidal fuzzy edge coefficients, we calculate a fuzzy integrated matrix, and incorporate the fuzzy multi-weights into fuzzy integrated weights. The optimal path is determined by taking two sets of vertices and transforming undiscovered vertices into discoverable ones. Our experimental results show that the model is highly accurate, and requires only a few measurement data to confirm the optimal path. The model provides an effective, feasible, and convenient method to obtain weights for different road sections, and can be applied to road planning in intelligent transportation systems.
Path planning using a hybrid evolutionary algorithm based on tree structure encoding.
Ju, Ming-Yi; Wang, Siao-En; Guo, Jian-Horn
2014-01-01
A hybrid evolutionary algorithm using scalable encoding method for path planning is proposed in this paper. The scalable representation is based on binary tree structure encoding. To solve the problem of hybrid genetic algorithm and particle swarm optimization, the "dummy node" is added into the binary trees to deal with the different lengths of representations. The experimental results show that the proposed hybrid method demonstrates using fewer turning points than traditional evolutionary algorithms to generate shorter collision-free paths for mobile robot navigation. PMID:24971389
On the Efficiency of a Prefix Path Holistic Algorithm
NASA Astrophysics Data System (ADS)
Ba?a, Radim; Krátký, Michal
In recent years, many approaches to XML twig pattern searching have been developed. Holistic approaches such as TwigStack are particularly significant in that they provide a powerful theoretical model for optimal processing of some query types. Holistic algorithms use various partitionings of an XML document called streaming schemes and they prove algorithm optimality depending on query characteristics.
L1 Regularization Path Algorithm for Generalized Linear Models
Hastie, Trevor
the entire path of the coefficient estimates as varies, i.e., to find { ^() : 0 in the coefficients, and correcting the error in the previous prediction. A traditional approach to variable selection, selects variables according to the amount of penalization on the L1 norm of the coefficients, in a manner
Sampling-based algorithms for optimal path planning problems
Karaman, Sertac
2012-01-01
Sampling-based motion planning received increasing attention during the last decade. In particular, some of the leading paradigms, such the Probabilistic RoadMap (PRM) and the Rapidly-exploring Random Tree (RRT) algorithms, ...
Three-dimension path planning for UCAV using hybrid meta-heuristic ACO-DE algorithm
Haibin Duan; Yaxiang Yu; Xiangyin Zhang; Shan Shao
2010-01-01
Three-dimension path planning of uninhabited combat air vehicle (UCAV) is a complicated optimal problem, which mainly focuses on optimizing the flight route considering the different types of constrains under complicated combating environments. A new hybrid meta-heuristic ant colony optimization (ACO) and differential evolution (DE) algorithm is proposed to solve the UCAV three-dimension path planning problem. DE is applied to optimize
XL: An Efficient Network Routing Algorithm Kirill Levchenko
Savage, Stefan
impacted by most link-state changes (particu- larly those whose shortest path trees include the changed present a new link-state routing algorithm called Approximate Link state (XL) aimed at increasing routing such algorithm. We show, via simulation, that XL significantly outper- forms standard link-state and distance
An Algorithm For Planning An Optimum Collision-Free Path In Structured Environment
NASA Astrophysics Data System (ADS)
Radicci, M. G.; Interesse, M.; Distante, A.
1989-03-01
An efficient algorithm for planning collision-free paths in a planar workspace, cluttered by known obstacles, is presented. The mobile entity is assumed to move with a fixed orientation. Our approach adopts the transformation of the obstacles from the Cartesian space into the configuration space (C-space). Moreover the feasible paths inside the workspace are represented through a set of straight line trajectories (spines), constituting the axes of natural freeways between C-space obstacles. The path planner finds out the optimum path for the mobile point, from the start to the target position, displacing it from spine to spine, at their intersection points. The proposed approach was applied to the three-dimensional gross motion planning of an industrial robot (a PUMA 560). In the experimental phase it always yielded satisfactory results, finding out optimum paths also in highly cluttered environments.
A Hybrid Metaheuristic DE/CS Algorithm for UCAV Three-Dimension Path Planning
Wang, Gaige; Guo, Lihong; Duan, Hong; Wang, Heqi; Liu, Luo; Shao, Mingzhen
2012-01-01
Three-dimension path planning for uninhabited combat air vehicle (UCAV) is a complicated high-dimension optimization problem, which primarily centralizes on optimizing the flight route considering the different kinds of constrains under complicated battle field environments. A new hybrid metaheuristic differential evolution (DE) and cuckoo search (CS) algorithm is proposed to solve the UCAV three-dimension path planning problem. DE is applied to optimize the process of selecting cuckoos of the improved CS model during the process of cuckoo updating in nest. The cuckoos can act as an agent in searching the optimal UCAV path. And then, the UCAV can find the safe path by connecting the chosen nodes of the coordinates while avoiding the threat areas and costing minimum fuel. This new approach can accelerate the global convergence speed while preserving the strong robustness of the basic CS. The realization procedure for this hybrid metaheuristic approach DE/CS is also presented. In order to make the optimized UCAV path more feasible, the B-Spline curve is adopted for smoothing the path. To prove the performance of this proposed hybrid metaheuristic method, it is compared with basic CS algorithm. The experiment shows that the proposed approach is more effective and feasible in UCAV three-dimension path planning than the basic CS model. PMID:23193383
A hybrid metaheuristic DE/CS algorithm for UCAV three-dimension path planning.
Wang, Gaige; Guo, Lihong; Duan, Hong; Wang, Heqi; Liu, Luo; Shao, Mingzhen
2012-01-01
Three-dimension path planning for uninhabited combat air vehicle (UCAV) is a complicated high-dimension optimization problem, which primarily centralizes on optimizing the flight route considering the different kinds of constrains under complicated battle field environments. A new hybrid metaheuristic differential evolution (DE) and cuckoo search (CS) algorithm is proposed to solve the UCAV three-dimension path planning problem. DE is applied to optimize the process of selecting cuckoos of the improved CS model during the process of cuckoo updating in nest. The cuckoos can act as an agent in searching the optimal UCAV path. And then, the UCAV can find the safe path by connecting the chosen nodes of the coordinates while avoiding the threat areas and costing minimum fuel. This new approach can accelerate the global convergence speed while preserving the strong robustness of the basic CS. The realization procedure for this hybrid metaheuristic approach DE/CS is also presented. In order to make the optimized UCAV path more feasible, the B-Spline curve is adopted for smoothing the path. To prove the performance of this proposed hybrid metaheuristic method, it is compared with basic CS algorithm. The experiment shows that the proposed approach is more effective and feasible in UCAV three-dimension path planning than the basic CS model. PMID:23193383
Formal language constrained path problems
Barrett, C.; Jacob, R.; Marathe, M.
1997-07-08
In many path finding problems arising in practice, certain patterns of edge/vertex labels in the labeled graph being traversed are allowed/preferred, while others are disallowed. Motivated by such applications as intermodal transportation planning, the authors investigate the complexity of finding feasible paths in a labeled network, where the mode choice for each traveler is specified by a formal language. The main contributions of this paper include the following: (1) the authors show that the problem of finding a shortest path between a source and destination for a traveler whose mode choice is specified as a context free language is solvable efficiently in polynomial time, when the mode choice is specified as a regular language they provide algorithms with improved space and time bounds; (2) in contrast, they show that the problem of finding simple paths between a source and a given destination is NP-hard, even when restricted to very simple regular expressions and/or very simple graphs; (3) for the class of treewidth bounded graphs, they show that (i) the problem of finding a regular language constrained simple path between source and a destination is solvable in polynomial time and (ii) the extension to finding context free language constrained simple paths is NP-complete. Several extensions of these results are presented in the context of finding shortest paths with additional constraints. These results significantly extend the results in [MW95]. As a corollary of the results, they obtain a polynomial time algorithm for the BEST k-SIMILAR PATH problem studied in [SJB97]. The previous best algorithm was given by [SJB97] and takes exponential time in the worst case.
NASA Astrophysics Data System (ADS)
Zhao, Jijun; Zhang, Shuguang; Tang, Zhiyuan; Wang, Lirong
2008-11-01
Though analyzing and summarizing the strategies of dynamic multicast traffic grooming, the strategies embody that which optimization criterion would be chose for the requirement of low-speed multicast service to select grooming routing in the grooming network, and the different strategic combination would obtain the different effect of multicast traffic grooming. On this basis, the Light Tree based Integrated Grooming (LTIG) and the Markov Finite Horizon Decision Algorithm of Shortest Path Tree are studied deeply, The research indicates that what the min-cost grooming routing calculation of LTIG adopts is MPH algorithm and Dijikstra algorithm which has higher complexity. But the Markov Finite Horizon Decision Algorithm of Shortest Path Tree has low complexity and it only seeks solutions in General network and isn't applicable to multicast traffic grooming. Subsequently, the Markov Finite Horizon Decision Algorithm of Shortest Path Tree is introduced to LTIG algorithm and a new MTGA-SPT algorithm is proposed. MTGA-SPT algorithm can resolve the route selection problem of resource node to multi-destination nodes, thus forming the light tree. Through the analysis of algorithm complexity, the complexity of MTGA-SPT algorithm mainly depends on the calculation of traffic grooming routing, and adopts the Markov Finite Horizon Decision Algorithm of Shortest Path Tree to compute min-cost grooming routing, making the complexity of MTGA-SPT algorithm descended, The complexity of Markov Finite Horizon Decision Algorithm of Shortest Path Tree is O((V-1)•W), and other step algorithm complexity is about O(V). To sum up, MTGA-SPT algorithm can reduce the time delay effectively.
Seedlings in the Theory of Shortest Paths
Steele, J. Michael
(x) is the density of the absolutely continuous part of the distribution of the Xi. This result has proved fruitful is the existence of measure preserving transformations from [0, 1] onto [0, 1]d that are Lipschitz of order 1/d
Seedlings in the Theory of Shortest Paths
Grimmett, Geoffrey
of the distribution of the X i . This result has proved fruitful in most of the ways that are open to a mathematical preserving transformations from [0, 1] onto [0, 1] d that are Lipschitz of order 1/d. A basic objective
Robbiano, Lorenzo
Assessing path-following performance for Unmanned Marine Vehicles with algorithms from Numerical. Zereik2 Abstract-- A current trend in marine robotics consists of performance evaluation of Unmanned on the definition of a new criterion for evaluating the capability of an Unmanned Surface Vehicle (USV) to follow
An Energy-Efficient Algorithm For Conflict-Free AGV Routing On A Linear Path Layout
Zeng, Jianyang "Michael"
1 An Energy-Efficient Algorithm For Conflict-Free AGV Routing On A Linear Path Layout ZENG Jian quantitatively for assuring conflict-freedom and the energy efficiency. 1. Introduction Current AGV systems the energy, aiming to minimize energy consumption of the vehicles during routing. As the energy resource
An EnergyEfficient Algorithm For ConflictFree AGV Routing On A Linear Path Layout
Zeng, Jianyang "Michael"
1 An EnergyEfficient Algorithm For ConflictFree AGV Routing On A Linear Path Layout ZENG Jian quantitatively for assuring conflictfreedom and the energy efficiency. 1. Introduction Current AGV systems the energy, aiming to minimize energy consumption of the vehicles during routing. As the energy resource
An OSPF Based Load Sensitive QoS Routing Algorithm using Alternate Paths
Sahoo, Anirudha
An OSPF Based Load Sensitive QoS Routing Algorithm using Alternate Paths Anirudha Sahoo IEEE Member and video streaming require Quality of Service (QoS). Such applications are being executed over the public Internet. Since today's Internet largely supports best effort traffic, QoS routing in the best effort
Evolutionary algorithm based offline/online path planner for UAV navigation.
Nikolos, I K; Valavanis, K P; Tsourveloudis, N C; Kostaras, A N
2003-01-01
An evolutionary algorithm based framework, a combination of modified breeder genetic algorithms incorporating characteristics of classic genetic algorithms, is utilized to design an offline/online path planner for unmanned aerial vehicles (UAVs) autonomous navigation. The path planner calculates a curved path line with desired characteristics in a three-dimensional (3-D) rough terrain environment, represented using B-spline curves, with the coordinates of its control points being the evolutionary algorithm artificial chromosome genes. Given a 3-D rough environment and assuming flight envelope restrictions, two problems are solved: i) UAV navigation using an offline planner in a known environment, and, ii) UAV navigation using an online planner in a completely unknown environment. The offline planner produces a single B-Spline curve that connects the starting and target points with a predefined initial direction. The online planner, based on the offline one, is given on-board radar readings which gradually produces a smooth 3-D trajectory aiming at reaching a predetermined target in an unknown environment; the produced trajectory consists of smaller B-spline curves smoothly connected with each other. Both planners have been tested under different scenarios, and they have been proven effective in guiding an UAV to its final destination, providing near-optimal curved paths quickly and efficiently. PMID:18238242
Evolutionary Algorithm for Multiple Knapsack Stefka Fidanova
Fidanova, Stefka
to that of a single individual component of the colony. An interesting behavior of ant colonies is their foraging behavior, and in particular, how ants can #12;nd the shortest paths between food sources and their nest of evolutionary computation some interesting developments similar to ant colony optimization (ACO) algorithms have
Generalized Hough transform: A useful algorithm for signal path detection
NASA Astrophysics Data System (ADS)
Monari, Jader; Montebugnoli, Stelio; Orlati, Andrea; Ferri, Massimo; Leone, Giorgio
2006-02-01
How is it possible to recognize ETI signals coming from exoplanets? This is one of the questions that SETI researchers must answer. In early 1998, the Italian SETI program [S. Montebugnoli, et al., SETItalia, A new era in bioastronomy, ASP Conference Series, vol. 213, 2000, pp. 501-504.] started in Medicina with the installation of the Serendip IV 24Million Channel digital spectrometer. This system daily acquires a huge quantity of data to be processed off line, in order to detect possible ETI signals. The programs devoted to this topic are collectively called SALVE 2. Here a natural evolution of a previous effort is presented, which was based on a simple Hough transform and was limited to the detection of short linear tracks in the join time frequency matrix (JTFM) stored by SIV. The new generalized Hough algorithm allows us to detect the sinusoidal tracks by the transformation of the JTF bidimensional Cartesian space (x,y), in the generalized Hough quadridimensional space, where the main vectors are the sine parameters amplitude, frequency, phase and offset. At the end of the paper some results, obtained with the computation of real and simulated JTFM, are shown.
A path planning algorithm for lane-following-based autonomous mobile robot navigation
NASA Astrophysics Data System (ADS)
Aljeroudi, Yazan; Paulik, Mark; Krishnan, Mohan; Luo, Chaomin
2010-01-01
In this paper we address the problem of autonomous robot navigation in a "roadway" type environment, where the robot has to drive forward on a defined path that could be impeded by the presence of obstacles. The specific context is the Autonomous Challenge of the Intelligent Ground Vehicle Competition (www.igvc.org). The task of the path planner is to ensure that the robot follows the path without turning back, as can happen in switchbacks, and/or leaving the course, as can happen in dashed or single lane line situations. A multi-behavior path planning algorithm is proposed. The first behavior determines a goal using a center of gravity (CoG) computation from the results of image processing techniques designed to extract lane lines. The second behavior is based on developing a sense of the current "general direction" of the contours of the course. This is gauged based on the immediate path history of the robot. An adaptive-weight-based fusion of the two behaviors is used to generate the best overall direction. This multi-behavior path planning strategy has been evaluated successfully in a Player/Stage simulation environment and subsequently implemented in the 2009 IGVC. The details of our experience will be presented at the conference.
NASA Astrophysics Data System (ADS)
Zhang, Shi; Yu, TinJin; Zhang, Bing
2005-02-01
The current routing and wavelength assignment (RWA) algorithms in optical switching (OBS) networks usually adopt the shortest path between the source-destination pairs as the routes and assign wavelengths hop-by-hop. There are two main problems exist in theses algorithms: (1) If there are common links among the shortest paths of different source-destination pairs, the one-way reservation protocol may cause congestion on these links while other links are underutilized, which may deteriorate the network performance, especially in an unsymmetrical network. (2) Few RWA algorithms take the fault recovery into consideration, which is important for the network to operate smoothly. An ant system based RWA algorithm is proposed in this paper to resolve these two problems. The destination nodes send ACKs back for each successfully received burst control packet (BCP). The ACKs are feed back along the same path as the one through which BCPs are forwarded. ACKs leave some "pheromone" along the path. The coming bursts will choose the output links with the probability proportioned to their pheromone intensity. Numerical results obtained from simulation show that our RWA algorithm can find the optimal routes adaptively and get a better burst drop probability performance compared with current RWA algorithms in an unsymmetrical network. Furthermore, our RWA algorithm is robust for fault recovery. When there are failures on some fibers, the bursts can be dynamically deflected to a suitable route without any extra information exchange among the switching nodes.
Ferguson, Thomas S.
A Practical Path-planning Algorithm for a Vehicle with a Constrained Turning Radius: a Hamilton of optimal path planning of a forward moving simple car with a minimum turning radius (a Dubins' car position x0 and a tangent direction 0 to a target position xf (and possibly also a tangent direction f
Data-Oblivious Graph Algorithms for Secure Computation and Outsourcing
Blanton, Marina
,asteele2,maliasga}@nd.edu ABSTRACT This work treats the problem of designing data-oblivious al- gorithms motivation for this work. We provide data-oblivious algorithms for breadth-first search, single-source single-destination shortest path, minimum span- ning tree, and maximum flow, the asymptotic complexities of which are optimal
Path planning strategies for autonomous ground vehicles
NASA Astrophysics Data System (ADS)
Gifford, Kevin Kent
Several key issues involved with the planning and executing of optimally generated paths for autonomous vehicles are addressed. Two new path planning algorithms are developed, and examined, which effectively minimize replanning as unmapped hazards are encountered. The individual algorithms are compared via extensive simulation. The search strategy results are implemented and tested using the University of Colorado's autonomous vehicle test-bed, RoboCar, and results show the advantages of solving the single-destination all-paths problem for autonomous vehicle path planning. Both path planners implement a graph search methodology incorporating dynamic programming that solves the single-destination shortest-paths problem. Algorithm 1, termed DP for dynamic programming, searches a state space where each state represents a potential vehicle location in a breadth-first fashion expanding from the goal to all potential start locations in the state space. Algorithm 2, termed DP*, couples the heuristic search power of the well-known A* search procedure (Nilsson-80) with the dynamic programming principle applied to graph searching to efficiently make use of overlapping subproblems. DP* is the primary research contribution of the work contained within this thesis. The advantage of solving the single-destination shortest-paths problem is that the entire terrain map is solved in terms of reaching a specified goal. Therefore, if the robot is diverted from the pre-planned path, an alternative path is already computed. The search algorithms are extended to include a probabilistic approach using empirical loss functions to incorporate terrain map uncertainties into the path considering terrain planning process. The results show the importance of considering terrain uncertainty. If the map representation ignores uncertainty by marking any area with less than perfect confidence as unpassable or assigns it the worst case rating, then the paths are longer than intuitively necessary. A hierarchical software control architecture is introduced that uses as the main guidance function an arbitration-based scheme which is able to efficiently and robustly integrate disparate sensor data. The flexibility provided by such an architecture allows for very easy integration of any type of environmental sensing device into the path planning algorithm.
An improved algorithm for the solution of the regularization path of support vector machine.
Ong, Chong-Jin; Shao, Shiyun; Yang, Jianbo
2010-03-01
This paper describes an improved algorithm for the numerical solution to the support vector machine (SVM) classification problem for all values of the regularization parameter C . The algorithm is motivated by the work of Hastie and follows the main idea of tracking the optimality conditions of the SVM solution for ascending value of C . It differs from Hastie's approach in that the tracked path is not assumed to be 1-D. Instead, a multidimensional feasible space for the optimality condition is used to solve the tracking problem. Such a treatment allows the algorithm to properly handle data sets which Hastie's approach fails. These data sets are characterized by the presence of linearly dependent points (in the kernel space), duplicate points, or nearly duplicate points. Such data sets are quite common among many real-world data, especially those with nominal features. Other contributions of this paper include a unifying formulation of the tracking process in the form of a linear programming problem, update formula for the linear programs, considerations that guard against accumulation of errors resulting from the use of incremental updates, and routines to speed up the algorithm. The algorithm is implemented under the Matlab environment and is available for download. Experiments with several data sets including data set having up to several thousand data points are reported. PMID:20123570
NASA Astrophysics Data System (ADS)
Zamirian, M.; Kamyad, A. V.; Farahi, M. H.
2009-09-01
In this Letter a new approach for solving optimal path planning problems for a single rigid and free moving object in a two and three dimensional space in the presence of stationary or moving obstacles is presented. In this approach the path planning problems have some incompatible objectives such as the length of path that must be minimized, the distance between the path and obstacles that must be maximized and etc., then a multi-objective dynamic optimization problem (MODOP) is achieved. Considering the imprecise nature of decision maker's (DM) judgment, these multiple objectives are viewed as fuzzy variables. By determining intervals for the values of these fuzzy variables, flexible monotonic decreasing or increasing membership functions are determined as the degrees of satisfaction of these fuzzy variables on their intervals. Then, the optimal path planning policy is searched by maximizing the aggregated fuzzy decision values, resulting in a fuzzy multi-objective dynamic optimization problem (FMODOP). Using a suitable t-norm, the FMODOP is converted into a non-linear dynamic optimization problem (NLDOP). By using parametrization method and some calculations, the NLDOP is converted into the sequence of conventional non-linear programming problems (NLPP). It is proved that the solution of this sequence of the NLPPs tends to a Pareto optimal solution which, among other Pareto optimal solutions, has the best satisfaction of DM for the MODOP. Finally, the above procedure as a novel algorithm integrating parametrization method and fuzzy aggregation to solve the MODOP is proposed. Efficiency of our approach is confirmed by some numerical examples.
Path planning algorithm for VTOL type UAVs based on the methods of ray tracing and limit cycle
Byung Cheol Min; Hee Yeul Kwon; Donghan Kim
2009-01-01
In this paper, the new path planning algorithm for vertical take-off and landing (VTOL) type unmanned aerial vehicles (UAVs), which is widely used in various practical applications, is introduced. The essence of the algorithm comes from the existing limit cycle navigation method for works in 2D and 3D, respectively. In addition, the ray tracing method is applied in order to
Replacement Paths via Fast Matrix Multiplication Oren Weimann
Yuster, Raphael
Replacement Paths via Fast Matrix Multiplication Oren Weimann Department of Computer Science be a directed edge-weighted graph and let P be a shortest path from s to t in G. The replacement paths problem asks to compute, for every edge e on P, the shortest s-to-t path that avoids e. Apart from
Shortest billiard trajectories Daniel Bezdek Karoly Bezdek
de Leon, Alex R.
Shortest billiard trajectories DÂ´aniel Bezdek KÂ´aroly Bezdek October 23, 2008 Abstract shortest generalized billiard trajectory moreover, any of its shortest generalized billiard trajectories of its generating disks are at most r. We prove that any of the shortest generalized billiard
Xie, XianMing; Li, YingHui
2014-06-20
This paper presents an enhanced phase unwrapping algorithm by combining an unscented Kalman filter, an enhanced local phase gradient estimator based on an amended matrix pencil model, and a path-following strategy. This technology is able to accurately unwrap seriously noisy wrapped phase images by applying the unscented Kalman filter to simultaneously perform noise suppression and phase unwrapping along the path from the high-quality region to the low-quality region of the wrapped phase images. Results obtained with synthetic data and real data validate the effectiveness of the proposed method and show improved performance of this new algorithm with respect to some of the most used algorithms. PMID:24979440
NASA Astrophysics Data System (ADS)
Liu, Bing-Yi; Wang, Jun-Yang; Liu, Zhi-Shen
2014-11-01
Spaceborne integrated path differential absorption (IPDA) lidar is an active-detection system which is able to perform global CO2 measurement with high accuracy of 1ppmv at day and night over ground and clouds. To evaluate the detection performance of the system, simulation of the ground return signal and retrieval algorithm for CO2 concentration are presented in this paper. Ground return signals of spaceborne IPDA lidar under various ground surface reflectivity and atmospheric aerosol optical depths are simulated using given system parameters, standard atmosphere profiles and HITRAN database, which can be used as reference for determining system parameters. The simulated signals are further applied to the research on retrieval algorithm for CO2 concentration. The column-weighted dry air mixing ratio of CO2 denoted by XCO2 is obtained. As the deviations of XCO2 between the initial values for simulation and the results from retrieval algorithm are within the expected error ranges, it is proved that the simulation and retrieval algorithm are reliable.
Gao, Ming-Ke; Chen, Yi-Min; Liu, Quan; Huang, Chen; Li, Ze-Yu; Zhang, Dian-Hua
2015-11-01
Preoperative path planning plays a critical role in vascular access surgery. Vascular access surgery has superior difficulties and requires long training periods as well as precise operation. Yet doctors are on different leves, thus bulky size of blood vessels is usually chosen to undergo surgery and other possible optimal path is not considered. Moreover, patients and surgeons will suffer from X-ray radiation during the surgical procedure. The study proposed an improved ant colony algorithm to plan a vascular optimal three-dimensional path with overall consideration of factors such as catheter diameter, vascular length, diameter as well as the curvature and torsion. To protect the doctor and patient from exposing to X-ray long-term, the paper adopted augmented reality technology to register the reconstructed vascular model and physical model meanwhile, locate catheter by the electromagnetic tracking system and used Head Mounted Display to show the planning path in real time and monitor catheter push procedure. The experiment manifests reasonableness of preoperative path planning and proves the reliability of the algorithm. The augmented reality experiment real time and accurately displays the vascular phantom model, planning path and the catheter trajectory and proves the feasibility of this method. The paper presented a useful and feasible surgical scheme which was based on the improved ant colony algorithm to plan vascular three-dimensional path in augmented reality. The study possessed practical guiding significance in preoperative path planning, intraoperative catheter guiding and surgical training, which provided a theoretical method of path planning for vascular access surgery. It was a safe and reliable path planning approach and possessed practical reference value. PMID:26319273
Spreading paths in partially observed social networks
NASA Astrophysics Data System (ADS)
Onnela, Jukka-Pekka; Christakis, Nicholas A.
2012-03-01
Understanding how and how far information, behaviors, or pathogens spread in social networks is an important problem, having implications for both predicting the size of epidemics, as well as for planning effective interventions. There are, however, two main challenges for inferring spreading paths in real-world networks. One is the practical difficulty of observing a dynamic process on a network, and the other is the typical constraint of only partially observing a network. Using static, structurally realistic social networks as platforms for simulations, we juxtapose three distinct paths: (1) the stochastic path taken by a simulated spreading process from source to target; (2) the topologically shortest path in the fully observed network, and hence the single most likely stochastic path, between the two nodes; and (3) the topologically shortest path in a partially observed network. In a sampled network, how closely does the partially observed shortest path (3) emulate the unobserved spreading path (1)? Although partial observation inflates the length of the shortest path, the stochastic nature of the spreading process also frequently derails the dynamic path from the shortest path. We find that the partially observed shortest path does not necessarily give an inflated estimate of the length of the process path; in fact, partial observation may, counterintuitively, make the path seem shorter than it actually is.
Gong, Li-gang; Yang, Wen-lun
2014-01-01
Unmanned combat aerial vehicles (UCAVs) have been of great interest to military organizations throughout the world due to their outstanding capabilities to operate in dangerous or hazardous environments. UCAV path planning aims to obtain an optimal flight route with the threats and constraints in the combat field well considered. In this work, a novel artificial bee colony (ABC) algorithm improved by a balance-evolution strategy (BES) is applied in this optimization scheme. In this new algorithm, convergence information during the iteration is fully utilized to manipulate the exploration/exploitation accuracy and to pursue a balance between local exploitation and global exploration capabilities. Simulation results confirm that BE-ABC algorithm is more competent for the UCAV path planning scheme than the conventional ABC algorithm and two other state-of-the-art modified ABC algorithms. PMID:24790555
Herráez, Miguel Arevallilo; Burton, David R; Lalor, Michael J; Gdeisat, Munther A
2002-12-10
We describe what is to our knowledge a novel technique for phase unwrapping. Several algorithms based on unwrapping the most-reliable pixels first have been proposed. These were restricted to continuous paths and were subject to difficulties in defining a starting pixel. The technique described here uses a different type of reliability function and does not follow a continuous path to perform the unwrapping operation. The technique is explained in detail and illustrated with a number of examples. PMID:12502301
A novel routing algorithm of multi-priority label switch path in MPLS over WDM mesh networks
NASA Astrophysics Data System (ADS)
Su, Yang; Xu, Zhanqi; Liu, Zengji
2005-11-01
An extended layered graph of MPLS over WDM mesh networks is proposed in this paper, in which the label switch path (LSP) with various wavelengths and the limitation of optical transceivers at a routing node are both involved. Label switch paths are classified into different priorities according to each quality of service. The corresponding routing algorithm, differentiating integrated routing algorithm (DIRA), is proposed and studied. The quality of service (QoS) of a label switch path and the optimization of network resources utilization are taken into account comprehensively in DIRA. A comparison of DIRA with the representative optical routing algorithms via simulation shows that it can reduce the blocking probability of delay-constraint LSP and improve the network throughput.
A conflict-free, path-level parallelization approach for sequential simulation algorithms
NASA Astrophysics Data System (ADS)
Rasera, Luiz Gustavo; Machado, Péricles Lopes; Costa, João Felipe C. L.
2015-07-01
Pixel-based simulation algorithms are the most widely used geostatistical technique for characterizing the spatial distribution of natural resources. However, sequential simulation does not scale well for stochastic simulation on very large grids, which are now commonly found in many petroleum, mining, and environmental studies. With the availability of multiple-processor computers, there is an opportunity to develop parallelization schemes for these algorithms to increase their performance and efficiency. Here we present a conflict-free, path-level parallelization strategy for sequential simulation. The method consists of partitioning the simulation grid into a set of groups of nodes and delegating all available processors for simulation of multiple groups of nodes concurrently. An automated classification procedure determines which groups are simulated in parallel according to their spatial arrangement in the simulation grid. The major advantage of this approach is that it does not require conflict resolution operations, and thus allows exact reproduction of results. Besides offering a large performance gain when compared to the traditional serial implementation, the method provides efficient use of computational resources and is generic enough to be adapted to several sequential algorithms.
Discrete Optimization An exact algorithm for a single-vehicle routing problem
Potvin, Jean-Yves
Discrete Optimization An exact algorithm for a single-vehicle routing problem with time windows from benchmark instances of the classical vehicle routing problem with time windows. Ó 2006 Elsevier B; Elementary shortest paths 1. Introduction In this work, we consider a variant of the vehicle routing problem
A Tabu Search Based Routing Optimization Algorithm for Packet Switching Networks
DANIELE CASALI; GIOVANNI COSTANTINI; MASSIMO CAROTA
2007-01-01
In this paper, we present a tabu-search based algorithm that optimizes routing for packet switching networks. The problem of routing optimization can be seen as the search of the shortest path in a graph, where the bandwidths of connections, together with their traffic, can be considered as weights. This kind of optimization is usually carried out by means of the
An Efficient Graph Cut Algorithm for Computer Vision Problems
Chetan Arora; Subhashis Banerjee; Prem Kalra; S. N. Maheshwari
2010-01-01
\\u000a Graph cuts has emerged as a preferred method to solve a class of energy minimization problems in computer vision. It has been\\u000a shown that graph cut algorithms designed keeping the structure of vision based flow graphs in mind are more efficient than\\u000a known strongly polynomial time max-flow algorithms based on preflow push or shortest augmenting path paradigms [1]. We present
WORM ALGORITHM PATH INTEGRAL MONTE CARLO APPLIED TO THE 3He-4He II SANDWICH SYSTEM
NASA Astrophysics Data System (ADS)
Al-Oqali, Amer; Sakhel, Asaad R.; Ghassib, Humam B.; Sakhel, Roger R.
2012-12-01
We present a numerical investigation of the thermal and structural properties of the 3He-4He sandwich system adsorbed on a graphite substrate using the worm algorithm path integral Monte Carlo (WAPIMC) method [M. Boninsegni, N. Prokof'ev and B. Svistunov, Phys. Rev. E74, 036701 (2006)]. For this purpose, we have modified a previously written WAPIMC code originally adapted for 4He on graphite, by including the second 3He-component. To describe the fermions, a temperature-dependent statistical potential has been used. This has proven very effective. The WAPIMC calculations have been conducted in the millikelvin temperature regime. However, because of the heavy computations involved, only 30, 40 and 50 mK have been considered for the time being. The pair correlations, Matsubara Green's function, structure factor, and density profiles have been explored at these temperatures.
An Algorithm to Compute Statistics of Stochastic Paths on Complex Landscapes
NASA Astrophysics Data System (ADS)
Manhart, Michael; Morozov, Alexandre V.
2013-03-01
Many systems in physics, chemistry, and biology can be modeled as a random walk on a network subject to a potential landscape. There is great interest in understanding the statistical properties of pathways on these landscapes, especially their times, lengths, and distributions in space. The complexity of the networks and landscapes arising in many models makes them difficult to solve by traditional analytical and computational tools. Moreover, standard methods do not always provide the most relevant information for characterizing these pathways. We develop an explicitly path-based formalism for studying these problems, which we implement using a numerical dynamic programming algorithm. It is especially well-suited to studying first-passage problems and rare transitions between metastable states. This method is valid for arbitrary networks and landscapes, as well as semi-Markovian processes with non-exponential waiting-time distributions. We explore this method on a variety of simple models including regular lattices, fractals, and protein sequence evolution.
Research on optimal path planning algorithm of task-oriented optical remote sensing satellites
NASA Astrophysics Data System (ADS)
Liu, Yunhe; Xu, Shengli; Liu, Fengjing; Yuan, Jingpeng
2015-08-01
GEO task-oriented optical remote sensing satellite, is very suitable for long-term continuous monitoring and quick access to imaging. With the development of high resolution optical payload technology and satellite attitude control technology, GEO optical remote sensing satellites will become an important developing trend for aerospace remote sensing satellite in the near future. In the paper, we focused on GEO optical remote sensing satellite plane array stare imaging characteristics and real-time leading mission of earth observation mode, targeted on satisfying needs of the user with the minimum cost of maneuver, and put forward the optimal path planning algorithm centered on transformation from geographic coordinate space to Field of plane, and finally reduced the burden of the control system. In this algorithm, bounded irregular closed area on the ground would be transformed based on coordinate transformation relations in to the reference plane for field of the satellite payload, and then using the branch and bound method to search for feasible solutions, cutting off the non-feasible solution in the solution space based on pruning strategy; and finally trimming some suboptimal feasible solutions based on the optimization index until a feasible solution for the global optimum. Simulation and visualization presentation software testing results verified the feasibility and effectiveness of the strategy.
Ingram, Mary Ann
the subject a train of short duration and low power pulses, which are reflected back from the human torso-averaged Harmonic Path (SHAPA) algorithm for estimation of heart rate (HR) and respiration rate (RR) with Impulse Radio Ultrawideband (IR- UWB) radar. Periodic movement of human torso caused by respiration and heart
Reliability assessment of power distribution systems using disjoint path-set algorithm
NASA Astrophysics Data System (ADS)
Bourezg, Abdrabbi; Meglouli, H.
2015-10-01
Finding the reliability expression of different substation configurations can help design a distribution system with the best overall reliability. This paper presents a computerized a nd implemented algorithm, based on Disjoint Sum of Product (DSOP) algorithm. The algorithm was synthesized and applied for the first time to the determination of reliability expression of a substation to determine reliability indices and costs of different substation arrangements. It deals with the implementation and synthesis of a new designed algorithm for DSOP implemented using C/C++, incorporating parallel problem solving capability and overcoming the disadvantage of Monte Carlo simulation which is the lengthy computational time to achieve satisfactory statistical convergence of reliability index values. The major highlight of this research being that the time consuming procedures of the DSOP solution generated for different substation arrangements using the proposed method is found to be significantly lower in comparison with the time consuming procedures of Monte Carlo-simulation solution or any other method used for the reliability evaluation of substations in the existing literature such as meta-heuristic and soft computing algorithms. This implementation gives the possibility of RBD simulation for different substation configurations in C/C++ using their path-set Boolean expressions mapped to probabilistic domain and result in simplest Sum of Disjoint Product which is on a one-to-one correspondence with reliability expression. This software tool is capable of handling and modeling a large, repairable system. Additionally, through its intuitive interface it can be easily used for industrial and commercial power systems. With simple Boolean expression for a configuration's RBD inputted, users can define a power system utilizing a RBD and, through a fast and efficient built-in simulation engine, the required reliability expressions and indices can be obtained. Two case studies will be analyzed in this paper. The effects of different substation configurations on the reliability are analyzed and compared. Then, the reliability of a radial distribution system will be evaluated using DSOP solution. The failure results will be combined with a load flow scenario, and indices such as SAIDI, SAIFI will be determined.
Shortest recurrence periods of novae
Kato, Mariko [Department of Astronomy, Keio University, Hiyoshi, Yokohama 223-8521 (Japan); Saio, Hideyuki [Astronomical Institute, Graduate School of Science, Tohoku University, Sendai 980-8578 (Japan); Hachisu, Izumi [Department of Earth Science and Astronomy, College of Arts and Sciences, The University of Tokyo, 3-8-1 Komaba, Meguro-ku, Tokyo 153-8902 (Japan); Nomoto, Ken'ichi, E-mail: mariko@educ.cc.keio.ac.jp [Kavli Institute for the Physics and Mathematics of the Universe (WPI), The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8583 (Japan)
2014-10-01
Stimulated by the recent discovery of the 1 yr recurrence period nova M31N 2008-12a, we examined the shortest recurrence periods of hydrogen shell flashes on mass-accreting white dwarfs (WDs). We discuss the mechanism that yields a finite minimum recurrence period for a given WD mass. Calculating the unstable flashes for various WD masses and mass accretion rates, we identified a shortest recurrence period of about two months for a non-rotating 1.38 M {sub ?} WD with a mass accretion rate of 3.6 × 10{sup –7} M {sub ?} yr{sup –1}. A 1 yr recurrence period is realized for very massive (? 1.3 M {sub ?}) WDs with very high accretion rates (? 1.5 × 10{sup –7} M {sub ?} yr{sup –1}). We revised our stability limit of hydrogen shell burning, which will be useful for binary evolution calculations toward Type Ia supernovae.
NASA Astrophysics Data System (ADS)
Phanthong, Thanapong; Maki, Toshihiro; Ura, Tamaki; Sakamaki, Takashi; Aiyarak, Pattara
2014-03-01
This paper describes path re-planning techniques and underwater obstacle avoidance for unmanned surface vehicle (USV) based on multi-beam forward looking sonar (FLS). Near-optimal paths in static and dynamic environments with underwater obstacles are computed using a numerical solution procedure based on an A* algorithm. The USV is modeled with a circular shape in 2 degrees of freedom (surge and yaw). In this paper, two-dimensional (2-D) underwater obstacle avoidance and the robust real-time path re-planning technique for actual USV using multi-beam FLS are developed. Our real-time path re-planning algorithm has been tested to regenerate the optimal path for several updated frames in the field of view of the sonar with a proper update frequency of the FLS. The performance of the proposed method was verified through simulations, and sea experiments. For simulations, the USV model can avoid both a single stationary obstacle, multiple stationary obstacles and moving obstacles with the near-optimal trajectory that are performed both in the vehicle and the world reference frame. For sea experiments, the proposed method for an underwater obstacle avoidance system is implemented with a USV test platform. The actual USV is automatically controlled and succeeded in its real-time avoidance against the stationary undersea obstacle in the field of view of the FLS together with the Global Positioning System (GPS) of the USV.
Autonomous Local Path-Planning for a Mobile Robot Using a Genetic Algorithm
Wainwright, Roger L.
as follows [2]: "Given a robot and a description of an environment, plan a path between two specific line. The robot will proceed along this path until an obstacle is detected. At this point, our path continues to navigate toward the end- point along a straight line (in our system the robot moves
FORMAL-LANGUAGE-CONSTRAINED PATH PROBLEMS CHRIS BARRETT, RIKO JACOB, AND MADHAV MARATHE
FORMAL-LANGUAGE-CONSTRAINED PATH PROBLEMS CHRIS BARRETT, RIKO JACOB, AND MADHAV MARATHE SIAM J , the formal-language-constrained shortest/simple path problem con- sists of finding a shortest (simple) path p by concatenating the -labels of the edges along the path p. The main contributions of this paper include
Research on Taxiway Path Optimization Based on Conflict Detection
Zhou, Hang; Jiang, Xinxin
2015-01-01
Taxiway path planning is one of the effective measures to make full use of the airport resources, and the optimized paths can ensure the safety of the aircraft during the sliding process. In this paper, the taxiway path planning based on conflict detection is considered. Specific steps are shown as follows: firstly, make an improvement on A * algorithm, the conflict detection strategy is added to search for the shortest and safe path in the static taxiway network. Then, according to the sliding speed of aircraft, a time table for each node is determined and the safety interval is treated as the constraint to judge whether there is a conflict or not. The intelligent initial path planning model is established based on the results. Finally, make an example in an airport simulation environment, detect and relieve the conflict to ensure the safety. The results indicate that the model established in this paper is effective and feasible. Meanwhile, make comparison with the improved A*algorithm and other intelligent algorithms, conclude that the improved A*algorithm has great advantages. It could not only optimize taxiway path, but also ensure the safety of the sliding process and improve the operational efficiency. PMID:26226485
Research on Taxiway Path Optimization Based on Conflict Detection.
Zhou, Hang; Jiang, Xinxin
2015-01-01
Taxiway path planning is one of the effective measures to make full use of the airport resources, and the optimized paths can ensure the safety of the aircraft during the sliding process. In this paper, the taxiway path planning based on conflict detection is considered. Specific steps are shown as follows: firstly, make an improvement on A * algorithm, the conflict detection strategy is added to search for the shortest and safe path in the static taxiway network. Then, according to the sliding speed of aircraft, a time table for each node is determined and the safety interval is treated as the constraint to judge whether there is a conflict or not. The intelligent initial path planning model is established based on the results. Finally, make an example in an airport simulation environment, detect and relieve the conflict to ensure the safety. The results indicate that the model established in this paper is effective and feasible. Meanwhile, make comparison with the improved A*algorithm and other intelligent algorithms, conclude that the improved A*algorithm has great advantages. It could not only optimize taxiway path, but also ensure the safety of the sliding process and improve the operational efficiency. PMID:26226485
NASA Astrophysics Data System (ADS)
Zhao, Minghui; Zhao, Xuesen; Li, Zengqiang; Sun, Tao
2014-08-01
In the non-rotational symmetrical microstrcture surfaces generation using turning method with Fast Tool Servo(FTS), non-uniform distribution of the interpolation data points will lead to long processing cycle and poor surface quality. To improve this situation, nearly arc-length tool path generation algorithm is proposed, which generates tool tip trajectory points in nearly arc-length instead of the traditional interpolation rule of equal angle and adds tool radius compensation. All the interpolation points are equidistant in radial distribution because of the constant feeding speed in X slider, the high frequency tool radius compensation components are in both X direction and Z direction, which makes X slider difficult to follow the input orders due to its large mass. Newton iterative method is used to calculate the neighboring contour tangent point coordinate value with the interpolation point X position as initial value, in this way, the new Z coordinate value is gotten, and the high frequency motion components in X direction is decomposed into Z direction. Taking a typical microstructure with 4?m PV value for test, which is mixed with two 70?m wave length sine-waves, the max profile error at the angle of fifteen is less than 0.01?m turning by a diamond tool with big radius of 80?m. The sinusoidal grid is machined on a ultra-precision lathe succesfully, the wavelength is 70.2278?m the Ra value is 22.81nm evaluated by data points generated by filtering out the first five harmonics.
Kim, Do-Yeon; Chung, Sung-Mo; Park, Jong-Won
2006-05-01
In this paper, we propose a fast and automated navigation path generation algorithm to visualize inside of carotid artery using MR angiography images. The carotid artery is one of the body regions not accessible by real optical probe but can be visualized with virtual endoscopy. By applying two-phase adaptive region-growing algorithm, the carotid artery segmentation is started at the initial seed, which is located on the initially thresholded binary image. This segmentation algorithm automatically detects the branch position with stack feature. Combining with a priori knowledge of anatomic structure of carotid artery, the detected branch position is used to separate the carotid artery into internal carotid artery and external carotid artery. A fly-through path is determined to automatically move the virtual camera based on the intersecting coordinates of two bisectors on the circumscribed quadrangle of segmented carotid artery. In consideration of the interactive rendering speed and the usability of standard graphic hardware, endoscopic view of carotid artery is generated by using surface rendering algorithm with perspective projection method. In addition, the endoscopic view is provided with ray casting algorithm for off-line navigation of carotid artery. Experiments have been conducted on both mathematical phantom and clinical data sets. This algorithm is more effective than key-framing and topological thinning method in terms of automated features and computing time. This algorithm is also applicable to generate the centerline of renal artery, coronary artery, and airway tree which has tree-like cylinder shape of organ structures in the medical imagery. PMID:16112889
M*: A Complete Multirobot Path Planning Algorithm with Performance Glenn Wagner, Howie Choset
Choset, Howie
is constrained to its individually optimal path, represented by a single line, but when robots 1 and 2 collide (b robots collide while following their individually optimal paths (c), the local dimensionality of the system grows exponentially with the number of robots. Planning in the joint configuration space of a set
A Panoply of Quantum Algorithms
Bartholomew Furrow
2006-06-15
We create a variety of new quantum algorithms that use Grover's algorithm and similar techniques to give polynomial speedups over their classical counterparts. We begin by introducing a set of tools that carefully minimize the impact of errors on running time; those tools provide us with speedups to already-published quantum algorithms, such as improving Durr, Heiligman, Hoyer and Mhalla's algorithm for single-source shortest paths [quant-ph/0401091] by a factor of lg N. The algorithms we construct from scratch have a range of speedups, from O(E)->O(sqrt(VE lg V)) speedups in graph theory to an O(N^3)->O(N^2) speedup in dynamic programming.
Application of Improved Particle Swarm Optimization Algorithm in UCAV Path Planning
NASA Astrophysics Data System (ADS)
Ma, Qianzhi; Lei, Xiujuan
For the calculation complexity and the convergence in Unmanned Combat Aerial Vehicle (UCAV) path planning, the path planning method based on Second-order Oscillating Particle Swarm Optimization (SOPSO) was proposed to improve the properties of solutions, in which the searching ability of particles was enhanced by controlling the process of oscillating convergence and asymptotic convergence. A novel method of perceiving threats was applied for advancing the feasibility of the path. A comparison of the results was made by WPSO, CFPSO and SOPSO, which showed that the method we proposed in this paper was effective. SOPSO was much more suitable for solving this kind of problem.
NASA Astrophysics Data System (ADS)
Chen, Jun; Luo, Chaomin; Krishnan, Mohan; Paulik, Mark; Tang, Yipeng
2010-01-01
An enhanced dynamic Delaunay Triangulation-based (DT) path planning approach is proposed for mobile robots to plan and navigate a path successfully in the context of the Autonomous Challenge of the Intelligent Ground Vehicle Competition (www.igvc.org). The Autonomous Challenge course requires the application of vision techniques since it involves path-based navigation in the presence of a tightly clustered obstacle field. Course artifacts such as switchbacks, ramps, dashed lane lines, trap etc. are present which could turn the robot around or cause it to exit the lane. The main contribution of this work is a navigation scheme based on dynamic Delaunay Triangulation (DDT) that is heuristically enhanced on the basis of a sense of general lane direction. The latter is computed through a "GPS (Global Positioning System) tail" vector obtained from the immediate path history of the robot. Using processed data from a LADAR, camera, compass and GPS unit, a composite local map containing both obstacles and lane line segments is built up and Delaunay Triangulation is continuously run to plan a path. This path is heuristically corrected, when necessary, by taking into account the "GPS tail" . With the enhancement of the Delaunay Triangulation by using the "GPS tail", goal selection is successfully achieved in a majority of situations. The robot appears to follow a very stable path while navigating through switchbacks and dashed lane line situations. The proposed enhanced path planning and GPS tail technique has been successfully demonstrated in a Player/Stage simulation environment. In addition, tests on an actual course are very promising and reveal the potential for stable forward navigation.
Hammock-on-Ears Decomposition: A Technique for the E cient Parallel Solution of Shortest
Waldmann, Uwe
Hammock-on-Ears Decomposition: A Technique for the E cient Parallel Solution of Shortest Paths the sequential hammock decomposition technique intro- duced by G. Frederickson and the parallel ear decomposition technique, thus we call it the hammock-on-ears decomposition. We mention that hammock-on-ears decomposi
Information Spread of Emergency Events: Path Searching on Social Networks
Hu, Hongzhi; Wu, Tunan
2014-01-01
Emergency has attracted global attentions of government and the public, and it will easily trigger a series of serious social problems if it is not supervised effectively in the dissemination process. In the Internet world, people communicate with each other and form various virtual communities based on social networks, which lead to a complex and fast information spread pattern of emergency events. This paper collects Internet data based on data acquisition and topic detection technology, analyzes the process of information spread on social networks, describes the diffusions and impacts of that information from the perspective of random graph, and finally seeks the key paths through an improved IBF algorithm. Application cases have shown that this algorithm can search the shortest spread paths efficiently, which may help us to guide and control the information dissemination of emergency events on early warning. PMID:24600323
An algorithm to find minimum free-energy paths using umbrella integration
NASA Astrophysics Data System (ADS)
Bohner, Matthias U.; Kästner, Johannes
2012-07-01
The calculation of free-energy barriers by umbrella sampling and many other methods is hampered by the necessity for an a priori choice of the reaction coordinate along which to sample. We avoid this problem by providing a method to search for saddle points on the free-energy surface in many coordinates. The necessary gradients and Hessians of the free energy are obtained by multidimensional umbrella integration. We construct the minimum free-energy path by following the gradient down to minima on the free-energy surface. The change of free energy along the path is obtained by integrating out all coordinates orthogonal to the path. While we expect the method to be applicable to large systems, we test it on the alanine dipeptide in vacuum. The minima, transition states, and free-energy barriers agree well with those obtained previously with other methods.
Sun, Quanping; Chen, Xiaogang; Chen, Qianliang; Dai, Ning; Liao, Wenhe; He, Ning
2009-10-01
Molar crown is very small and has not only thin-wall, but also complex profile, especially, the occlusal surface of each molar crown has many cusps, ridges and fossae being differently distributed. When conventional processing method is used, it is impossible to machine molar prosthesis rapidly and exactly. To enhance machining velocity and improve the surface precision of molar crown, an algorithm of entity rapid offset-based STL format is put forward. By the application of Zigzag toolpath planning and micro-machining cutter, the finishing toolpaths for high speed milling molar prosthesis are generated. In terms of Mikron UCP800 high-speed machine center, the molar all-crown made of alloy aluminum material is successfully machined. The test results show that the algorithm of tool-path generation works fast, the number of toolpaths is small, and the cutter feeds smoothly. PMID:19947500
Methodology for Augmenting Existing Paths with Additional Parallel Transects
Wilson, John E.
2013-09-30
Visual Sample Plan (VSP) is sample planning software that is used, among other purposes, to plan transect sampling paths to detect areas that were potentially used for munition training. This module was developed for application on a large site where existing roads and trails were to be used as primary sampling paths. Gap areas between these primary paths needed to found and covered with parallel transect paths. These gap areas represent areas on the site that are more than a specified distance from a primary path. These added parallel paths needed to optionally be connected together into a single path—the shortest path possible. The paths also needed to optionally be attached to existing primary paths, again with the shortest possible path. Finally, the process must be repeatable and predictable so that the same inputs (primary paths, specified distance, and path options) will result in the same set of new paths every time. This methodology was developed to meet those specifications.
Approximation Algorithms and Heuristics for a 2-depot, Heterogeneous Hamiltonian Path Problem
Doshi, Riddhi Rajeev
2011-10-21
Various civil and military applications of UAVs, or ground robots, require a set of vehicles to monitor a group of targets. Routing problems naturally arise in this setting where the operators of the vehicles have to plan the paths suitably in order...
Ching-Chih Tsai; Hsu-Chih Huang; Cheng-Kai Chan
2011-01-01
This paper presents a parallel elite genetic algo- rithm (PEGA) and its application to global path planning for autonomous mobile robots navigating in structured environments. This PEGA, consisting of two parallel EGAs along with a mi- gration operator, takes advantages of maintaining better popu- lation diversity, inhibiting premature convergence, and keeping parallelism in comparison with conventional GAs. This initial feasible
Emilio J. González-Galván; Ambrocio Loredo-Flores; J. Jesús Cervantes-Sánchez; L. Antonio Aguilera-Cortés; Steven B. Skaar
2008-01-01
Multiple industrial manufacturing tasks require a complex path to be followed precisely over an arbitrary surface which has a geometry that is not known with precision. Examples of such tasks include welding, glue-application, cutting, plasma-spraying, etc., over commercial plates whose geometry cannot be known in advance. Such processes are in general referred to as surface manufacturing. In this work, a
Distortion-oriented welding path optimization based on elastic net method and genetic algorithm
H. Yang; H. Shao
2009-01-01
The optimization of welding path is one of the most combinatorial problems in robotic welding. This paper is focused on the optimization for both productivity and quality in robotic welding. The productivity related scheduling problem is similar to the well-known traveling salesman problem (TSP). An optimization strategy for TSP based on the “elastic net method” (ENM) and artificial neural network
Shortest Path Computation with No Information Leakage Kyriakos Mouratidis
Yiu, Man Lung
reveal personal information, such as social habits, health condition, shop- ping preferences, lifestyle systems and the diffusion of smart-phones has led to an expanding market of location-based services (LBSs nature of the queries may disclose per- sonal information (such as health status, shopping habits
Densities of shortest path lengths in spatial stochastic networks
Schmidt, Volker
for the probability density of this distribution which is based on functionals of the so-called typical serving zone processes, we derive a representation formula for the density of C # which is based on some functional for the typical serving zone which are used in a numerical study in order to estimate the density and moments
Scalable Shortest Paths Browsing on Land Surface Songhua Xing
Shahabi, Cyrus
popularity of online Earth visualization tools and geo-realistic games and the availability of high, where N is the size of the terrain. With this method, the time and space requirements for an exhaustive leading to the growing popularity of online Earth visualization platforms (e.g., Google EarthTM) and geo
Improved Approximation Results on the Shortest Common Supersequence Problem
NASA Astrophysics Data System (ADS)
Gotthilf, Zvi; Lewenstein, Moshe
The problem of finding the Shortest Common Supersequence (SCS) of an arbitrary number of input strings is a well-studied problem. Given a set L of k strings, s 1, s 2, ..., s k , over an alphabet ?, we say that their SCS is the shortest string that contains each of the input strings as a subsequence. The problem is known to be NP-hard [8] even over binary alphabet [12]. In this paper we focus on approximating two NP-hard variants of the SCS problem. For the first variant, where all input strings are of length 2, we present a 2 - frac {2}{1 + log{n}log{log{n}}} approximation algorithm, where |?| = n. This result immediately improves the 2 - frac {4}{n+1} approximation algorithm presented in [17]. Moreover, we present a 7/6 (? 1.166bar{6}) approximation algorithm for the restricted variant (but still NP-hard) where all input strings are of length 2 and every character in ? has at most 3 occurrences in L.
From Path Graphs to Directed Path Graphs Steven Chaplick1
Felsner, Stefan
From Path Graphs to Directed Path Graphs Steven Chaplick1 , Marisa Gutierrez2 , Benjamin LÂ´ev^eque3 time algorithm to greedily orient the edges of a path graph model to obtain a directed path graph model. This algorithm has several interesting conse- quences concerning the relationship between path graphs
Efficient algorithms for semiclassical instanton calculations based on discretized path integrals
Kawatsu, Tsutomu, E-mail: kawatsu@fukui.kyoto-u.ac.jp, E-mail: smiura@mail.kanazawa-u.ac.jp [Institute for Molecular Science, National Institute of Natural Science, 38 Nishigonaka, Myodaiji, Okazaki 222-8585 (Japan); School of Mathematics and Physics, Kanazawa University, Kanazawa 920-1192 (Japan); Miura, Shinichi, E-mail: kawatsu@fukui.kyoto-u.ac.jp, E-mail: smiura@mail.kanazawa-u.ac.jp [School of Mathematics and Physics, Kanazawa University, Kanazawa 920-1192 (Japan)
2014-07-14
Path integral instanton method is a promising way to calculate the tunneling splitting of energies for degenerated two state systems. In order to calculate the tunneling splitting, we need to take the zero temperature limit, or the limit of infinite imaginary time duration. In the method developed by Richardson and Althorpe [J. Chem. Phys. 134, 054109 (2011)], the limit is simply replaced by the sufficiently long imaginary time. In the present study, we have developed a new formula of the tunneling splitting based on the discretized path integrals to take the limit analytically. We have applied our new formula to model systems, and found that this approach can significantly reduce the computational cost and gain the numerical accuracy. We then developed the method combined with the electronic structure calculations to obtain the accurate interatomic potential on the fly. We present an application of our ab initio instanton method to the ammonia umbrella flip motion.
Guoren Wang; Ge Yu
2002-01-01
With the emerging of new applications, especially in Web, such as E-Commerce, Digital Library and DNA Bank, object database\\u000a systems show their stronger functions than other kinds of database systems due to their powerful representation ability on\\u000a complex semantics and relationship. One distinguished feature of object database systems is path expression, and most queries\\u000a on an object database are based
Min-cuts and Shortest Cycles in Planar Graphs in O(n log log n) Time
\\L\\kacki, Jakub
2011-01-01
We present a deterministic O(n log log n) time algorithm for finding shortest cycles and minimum cuts in planar graphs. The algorithm improves the previously known fastest algorithm by Italiano et al. in STOC'11 by a factor of log n. This speedup is obtained through the use of dense distance graphs combined with a divide-and-conquer approach.
A surgeon specific automatic path planning algorithm for deep brain stimulation
NASA Astrophysics Data System (ADS)
Liu, Yuan; Dawant, Benoit M.; Pallavaram, Srivatsan; Neimat, Joseph S.; Konrad, Peter E.; D'Haese, Pierre-Francois; Datteri, Ryan D.; Landman, Bennett A.; Noble, Jack H.
2012-02-01
In deep brain stimulation surgeries, stimulating electrodes are placed at specific targets in the deep brain to treat neurological disorders. Reaching these targets safely requires avoiding critical structures in the brain. Meticulous planning is required to find a safe path from the cortical surface to the intended target. Choosing a trajectory automatically is difficult because there is little consensus among neurosurgeons on what is optimal. Our goals are to design a path planning system that is able to learn the preferences of individual surgeons and, eventually, to standardize the surgical approach using this learned information. In this work, we take the first step towards these goals, which is to develop a trajectory planning approach that is able to effectively mimic individual surgeons and is designed such that parameters, which potentially can be automatically learned, are used to describe an individual surgeon's preferences. To validate the approach, two neurosurgeons were asked to choose between their manual and a computed trajectory, blinded to their identity. The results of this experiment showed that the neurosurgeons preferred the computed trajectory over their own in 10 out of 40 cases. The computed trajectory was judged to be equivalent to the manual one or otherwise acceptable in 27 of the remaining cases. These results demonstrate the potential clinical utility of computer-assisted path planning.
Heikalabad, Saeed Rasouli; Nematy, Farhad; Rahmani, Naeim
2011-01-01
Enabling real time applications in wireless sensor networks requires certain delay and bandwidth which pose more challenges in the design of routing protocols. The algorithm that is used for packet routing in such applications should be able to establish a tradeoff between end to end delay parameter and energy consumption. In this paper, we propose a new multi path routing algorithm for real time applications in wireless sensor networks namely QEMPAR which is QoS aware and can increase the network lifetime. Simulation results show that the proposed algorithm is more efficient than previous algorithms in providing quality of service requirements of real-time applications.
A Simple Path Non-Existence Algorithm using C-obstacle Query
North Carolina at Chapel Hill, University of
space or C-space. We use two basic queries: free cell query, which checks whether a cell in C-space lies entirely inside the free space, and C-obstacle cell query, which checks whether a cell lies entirely inside algorithms to perform free cell and C-obstacle cell queries using separation distance and generalized
Ivan Stojmenovic; Xu Lin
2001-01-01
In a localized routing algorithm, each node makes forwarding decisions solely based on the position of itself, its neighbors, and its destination. In distance, progress, and direction-based approaches (reported in the literature), when node A wants to send or forward message m to destination node D, it forwards m to its neighbor C which is closest to D (has best
Benefit of adaptive FEC in shared backup path protected elastic optical network.
Guo, Hong; Dai, Hua; Wang, Chao; Li, Yongcheng; Bose, Sanjay K; Shen, Gangxiang
2015-07-27
We apply an adaptive forward error correction (FEC) allocation strategy to an Elastic Optical Network (EON) operated with shared backup path protection (SBPP). To maximize the protected network capacity that can be carried, an Integer Linear Programing (ILP) model and a spectrum window plane (SWP)-based heuristic algorithm are developed. Simulation results show that the FEC coding overhead required by the adaptive FEC scheme is significantly lower than that needed by a fixed FEC allocation strategy resulting in higher network capacity for the adaptive strategy. The adaptive FEC allocation strategy can also significantly outperform the fixed FEC allocation strategy both in terms of the spare capacity redundancy and the average FEC coding overhead needed per optical channel. The proposed heuristic algorithm is efficient and not only performs closer to the ILP model but also does much better than the shortest-path algorithm. PMID:26367673
Multi-Path Relay Selection Algorithm Based on the Broadcast TV
NASA Astrophysics Data System (ADS)
Zhang, Chaoyi; Luan, Linlin; Wu, Muqing
This paper presents a relay selection method for Broadcast TV services. This method get through the node's time-delay and power information, obtain the value of the system interrupt as to be a decision threshold, then chose the relay node. At the same time this paper proposes an optimal relay selection strategy which can minimize the system interrupt probability combination with power distribution--Multi-Path Relay Routing Protocol. This protocol can dynamically change the appropriate route according to the shifty network. Simulation results show that the protocol can extend the coverage area, reducing time-delay and increase system throughput, improve system spectral efficiency, and enhance the Qos of the Broadcast TV service.
A labeling algorithm for the navigation of automated guided vehicles
Huang, J.; Palekar, U.S.; Kapoor, S.G. . Dept. of Mechanical and Industrial Engineering)
1993-08-01
Material handling is an important component of most automated manufacturing systems. AGVs are commonly employed for this function. Efficient use of the AGV system requires proper routing and scheduling of vehicular traffic. This problem is modeled as a shortest path problem with multiple time windows on arcs and at nodes of a network. A polynomial-time labeling algorithm has been developed. The algorithm has complexity O (D[sup 2]log[sub d]D), where D is the total number of time windows in the problem. The data required for the model is easy to maintain.
Multipath Routing Algorithm Applied to Cloud Data Center Services
NASA Astrophysics Data System (ADS)
Matsuura, Hiroshi
Cloud data center services, such as video on demand (VoD) and sensor data monitoring, have become popular. The quality of service (QoS) between a client and a cloud data center should be assured by satisfying each service's required bandwidth and delay. Multipath traffic engineering is effective for dispersing traffic flows on a network; therefore, an improved k-shortest paths first (k-SPF) algorithm is applied to these cloud data center services to satisfy their required QoS. k-SPF can create a set of multipaths between a cloud data center and all edge routers, to which client nodes are connected, within one algorithm process. Thus, k-SPF can produce k shortest simple paths between a cloud data center and every access router faster than with conventional Yen's algorithm. By using a parameter in the algorithm, k-SPF can also impartially use links on a network and shorten the average hop-count and number of necessary MPLS labels for multiple paths that comprise a multipath.
Energy-Aware Two Link-Disjoint Paths Routing Gongqi Lin, Sieteng Soh, Mihai Lazarescu
Chin, Kwan-Wu
. To address this problem, we present a fast heuristic, called TLDP by Shortest Path First (TLDP-SPF simulation results show that TLDP-SPF can reduce network energy usage, on average, by more than 20%, even for MLU below 50%. As compared to using Shortest Path routing, while reducing energy by about 20%, TLDP-SPF
Szymanski, Boleslaw K.
. Directed Diffusion (DD) is an example of an energy ef- ficient routing paradigm which is centralAlgorithm for Optimizing Energy Use and Path Resilience in Sensor Networks Lawrence A. Bush-centric communication paradigm to efficiently and effectively share data. Directed Diffusion is a data
NRMRL-RTP-P- 568 Childers, J.W., Phillips, W.J., Thompson*, E.L., Harris*, D.B., Kirchgessner*, D.A., Natschke, D.F., and Clayton, M.J. Comparison of an Innovative Nonlinear Algorithm to Classical Least Squares for Analyzing Open-Path Fourier Transform Infrared Spectra Collecte...
Li, Da-wei; Yang, Haijun; Han, Li; Huo, Shuanghong
2008-01-01
To predict a protein-folding pathway, we present an alternative to the time-consuming dynamic simulation of atomistic models. We replace the actual dynamic simulation with variational optimization of a reaction path connecting known initial and final protein conformations in such a way as to maximize an estimate of the reactive flux or minimize the mean first passage time at a given temperature, referred to as MaxFlux. We solve the MaxFlux global optimization problem with an efficient graph-theoretic approach, the probabilistic roadmap method (PRM). We employed CHARMM19 and the EEF1 implicit solvation model to describe the protein solution. The effectiveness of our MaxFlux-PRM is demonstrated in our promising simulation results on the folding pathway of the engrailed homeodomain. Our MaxFlux-PRM approach provides the direct evidence to support that the previously reported intermediate state is a genuine on-pathway intermediate, and the demand of CPU power is moderate. PMID:18024496
NASA Astrophysics Data System (ADS)
Ciesielski, Krzysztof Chris; Udupa, Jayaram K.; Falcão, A. X.; Miranda, P. A. V.
2012-02-01
We present a general graph-cut segmentation framework GGC, in which the delineated objects returned by the algorithms optimize the energy functions associated with the lp norm, 1 <= p <= ?. Two classes of well known algorithms belong to GGC: the standard graph cut GC (such as the min-cut/max-flow algorithm) and the relative fuzzy connectedness algorithms RFC (including iterative RFC, IRFC). The norm-based description of GGC provides more elegant and mathematically better recognized framework of our earlier results from [18, 19]. Moreover, it allows precise theoretical comparison of GGC representable algorithms with the algorithms discussed in a recent paper [22] (min-cut/max-flow graph cut, random walker, shortest path/geodesic, Voronoi diagram, power watershed/shortest path forest), which optimize, via lp norms, the intermediate segmentation step, the labeling of scene voxels, but for which the final object need not optimize the used lp energy function. Actually, the comparison of the GGC representable algorithms with that encompassed in the framework described in [22] constitutes the main contribution of this work.
Dynamic routing algorithm for large file transport in optical network
NASA Astrophysics Data System (ADS)
Zhang, Pengshan; Guo, Wei; Jin, Yaohui; Sun, Weiqiang; Hu, Weisheng
2007-11-01
Many distributed computing applications need transfer large files between distributed locations as fast as possible. A dynamic routing algorithm for optical network is designed to modify existing transfers and spare network resources for new request to satisfy both old and new transfers' requirements. In data intensive application on circuit-switch optical network, light-path resources are scarce and there should be concurrent file transfers competing for the same fibers. In static routing optical network, if new coming file transfer cannot acquire light-path with enough bandwidth, it could only wait for the releasing of current used resources. Due to the waiting, the delay time will be large. So we use our dynamic routing algorithm to schedule and modify existing light-paths, to spare a light-path with enough bandwidth for new coming file. Our optimized target is to make every file finish transferring in less time, so we propose two objectives defined in the paper: one is to make maximal delay time of all tasks less and the other is to make average delay time less. The algorithm proposed has two mainly steps: 1) Routing process; 2) Dynamic routing process. In routing step, when task of file arrives we firstly get k random paths, then use Least Congestion Algorithm (LCA) (or Shortest Path Algorithm (SPA)) to get the primary path P1 of maximal residual bandwidth (RB) from k paths and the alternate path P2 of the second maximal RB. If the bandwidth of P1 is enough for this task, transfer the file in P1 path. If not, we go to the dynamic routing process. In the second process, get all the links of P1 then we change the existing light paths of tasks in the P1 path one by one to their alternative paths until we can get enough bandwidth of P1. In the dynamic routing process, we design two different queuing strategies. The first strategy is First Arrive First Modified (FAFM) strategy, namely we schedule the first arrival task firstly. The other is Larger Bandwidth First Modified (LBFM) and the file with larger bandwidth is scheduled firstly. By comparison of simulation results, we can prove that our two kinds of dynamic routing algorithms can get better results for both decreasing maximal delay time and average delay time than LCA and SPA routing algorithms. In the two queuing strategies, LBFM can get better results than FAFM strategy. The receivers in the destinations can get better results by using our dynamic routing algorithm.
Mahajan, Meena
Longest Paths in Planar DAGs in Unambiguous Log-Space Nutan Limaye, Meena Mahajan, Prajakta,meena,prajakta}@imsc.res.in November 13, 2009 Abstract We present a transformation from longest paths to shortest paths in sub in the same class of graphs. As a corollary, we obtain our main result: Longest Paths in planar DAGs is in UL
NASA Astrophysics Data System (ADS)
Gilliam, Kyle L.
As part of former and current sea-surface altimetry missions, brightness temperatures measured by nadir-viewing 18-34 GHz microwave radiometers are used to determine apparent path delay due to variations in index of refraction caused by changes in the humidity of the troposphere. This tropospheric wet-path delay can be retrieved from these measurements with sufficient accuracy over open oceans. However, in coastal zones and over inland water the highly variable radiometric emission from land surfaces at microwave frequencies has prevented accurate retrieval of wet-path delay using conventional algorithms. To extend wet path delay corrections into the coastal zone (within 25 km of land) and to inland water bodies, a new method is proposed to correct for tropospheric wet-path delay by using higher-frequency radiometer channels from approximately 50-170 GHz to provide sufficiently small fields of view on the surface. A new approach is introduced based on the variability of observations in several millimeter-wave radiometer channels on small spatial scales due to surface emissivity in contrast to the larger-scale variability in atmospheric absorption. The new technique is based on the measurement of deflection ratios among several radiometric bands to estimate the transmissivity of the atmosphere due to water vapor. To this end, the Brightness Temperature Deflection Ratio (BTDR) method is developed starting from a radiative transfer model for a downward-looking microwave radiometer, and is extended to pairs of frequency channels to retrieve the wet path delay. Then a mapping between the wet transmissivity and wet-path delay is performed using atmospheric absorption models. A frequency selection study is presented to determine the suitability of frequency sets for accurate retrieval of tropospheric wet-path delay, and comparisons are made to frequency sets based on currently-available microwave radiometers. Statistical noise analysis results are presented for a number of frequency sets. Additionally, this thesis demonstrates a method of identifying contrasting surface pixels using edge detection algorithms to identify contrasting scenes in brightness temperature images for retrieval with the BTDR method. Finally, retrievals are demonstrated from brightness temperatures measured by Special Sensor Microwave Imager/Sounder (SSMIS) instruments on three satellites for coastal and inland water scenes. For validation, these retrievals are qualitatively compared to independently-derived total precipitable water products from SSMIS, the Tropical Rainfall Measurement Mission (TRMM) Microwave Imager (TMI) and the Advanced Microwave Sounding Radiometer for Earth Observing System (EOS) (AMSR-E). Finally, a quantitative method for analyzing the data consistency of the retrieval is presented as an estimate of the error in the retrieved wet path delay. From these comparisons, one can see that the BTDR method shows promise for retrieving wet path delays over inland water and coastal regions. Finally, several additional future uses for the algorithm are described.
Development and performance-testing of Multi-Path I/O algorithms on V-Series systems
TerBush, Ryan (Ryan T.)
2013-01-01
As data growth continues to accelerate, so must performance and efficiency of large scale storage systems. This project will present the implementation and performance analysis of Multi-Path I/O within Data ONTAP. The goal ...
Metropolis Algorithm for solving Shortest Lattice Vector Problem(SVP)
Biswas, Somenath
spanning from robotics to computational number theory, viz., polynomial factorization. At the same time problem for a long time. A breakthrough result by Ajtai[4] in 1998 finally showed that SVP is NP-hard under randomized reductions. Another breakthrough by Micciancio [5]in 2001 showed that SVP is hard
Delay-Constrained Multicast Routing Algorithm Based on Average Distance Heuristic
Ling, Zhou; Yu-xi, Zhu; 10.5121/ijcnc.2010.2212
2010-01-01
Multicast is the ability of a communication network to accept a single message from an application and to deliver copies of the message to multiple recipients at different location. With the development of Internet, Multicast is widely applied in all kinds of multimedia real-time application: distributed multimedia systems, collaborative computing, video-conferencing, distance education, etc. In order to construct a delay-constrained multicast routing tree, average distance heuristic (ADH) algorithm is analyzed firstly. Then a delay-constrained algorithm called DCADH (delay-constrained average distance heuristic) is presented. By using ADH a least cost multicast routing tree can be constructed; if the path delay can't meet the delay upper bound, a shortest delay path which is computed by Dijkstra algorithm will be merged into the existing multicast routing tree to meet the delay upper bound. Simulation experiments show that DCADH has a good performance in achieving a low-cost multicast routing tree.
Breast Contour Detection with Stable Paths
NASA Astrophysics Data System (ADS)
Cardoso, Jaime S.; Sousa, Ricardo; Teixeira, Luís F.; Cardoso, M. J.
Breast cancer conservative treatment (BCCT), due to its proven oncological safety, is considered, when feasible, the gold standard of breast cancer treatment. However, aesthetic results are heterogeneous and difficult to evaluate in a standardized way, due to the lack of reproducibility of the subjective methods usually applied. The objective assessment methods, considered in the past as being less capable of evaluating all aspects of BCCT, are nowadays being preferred to overcome the drawbacks of the subjective evaluation. A computer-aided medical system was recently developed to objectively and automatically evaluate the aesthetic result of BCCT. In this system, the detection of the breast contour on the patient's digital photograph is a necessary step to extract the features subsequently used in the evaluation process. In this paper an algorithm based on the shortest path on a graph is proposed to detect automatically the breast contour. The proposed method extends an existing semi-automatic algorithm for the same purpose. A comprehensive comparison with manually-drawn contours reveals the strength of the proposed method.
GRECS: Graph Encryption for Approximate Shortest Distance Queries
International Association for Cryptologic Research (IACR)
GRECS: Graph Encryption for Approximate Shortest Distance Queries Xianrui Meng1 , Seny Kamara2 Research 3 Department of Computer Science, Ben-Gurion University Abstract We propose graph encryption schemes that efficiently support approximate shortest distance queries on large-scale encrypted graphs
Finding the Minimum-Cost Path Without Cutting Corners
van Vliet, Lucas J.
, and Lucas J. van Vliet Quantitative Imaging Group, Delft University of Technology, The Netherlands L tracks are examples of string-like (network) structures, whose minimum-cost path is cutting through suggests that the path with the shortest arrival time will in general be longer than the Euclidean distance
Optimal paths for a car that goes both forwards and backwards
J. A. Reeds; L. A. Shepp
1990-01-01
The path taken by a car with a given minimum turning radius has a lower bound on its radius of curvature at each point, but the path has cusps if the car shifts into or out of reverse gear. What is the shortest such path a car can travel between two points if its starting and ending directions are specified?
IP-oriented control of unidirectional-path-switched-ring-based transport networks
NASA Astrophysics Data System (ADS)
Sharma, Vishal; Das, Abhimanyu; Chen, Charles
2003-03-01
An important requirement in the IP-based control of time-division multiplexing (TDM) optical transport networks is to utilize the in-built protection capabilities of synchronous optical network (SONET) unidirectional path-switched rings (UPSRs) and to automate the UPSR-protected path setup in mixed mesh-ring networks. This requires modifications to existing IP signaling and routing protocols and new processing rules at the network nodes. Here we leverage IP routing and signaling and multiprotocol label switching (MPLS) fast-reroute techniques for accurately advertising UPSR ring topologies to remote nodes and dynamically establishing UPSR-protected paths across a transport network. Our proposal also makes a NUT1-like (nonpreemptible unprotected traffic) feature possible in UPSRs, which allows for efficient utilization of UPSR protection bandwidth. We achieve this by encoding UPSR-specific information in the open shortest-path-first (OSPF) link state advertisements and in signaling messages of the Resource Reservation Protocol (RSVP) with TE extensions. In addition, we modify the signaling and routing state machines at the nodes to interpret and process this information to perform UPSR topology discovery and path computation. The uniqueness of our proposals is that the algorithms and the rules specified here allow for existing IP-based protocols [such as those within the generalized MPLS (GMPLS) framework, which currently applies to mesh networks] to be efficiently adapted for this context while still achieving our objective of exploiting UPSR-protection capabilities.
Parallel Shortest Lattice Vector Enumeration on Graphics Cards
International Association for Cryptologic Research (IACR)
Parallel Shortest Lattice Vector Enumeration on Graphics Cards Jens Hermans 1 , Michael Schneider2/SCD-COSIC and IBBT {Jens.Hermans,Frederik.Vercauteren,Bart.Preneel}@esat.kuleuven.be 2 Technische Universit
A Decision Processing Algorithm for CDC Location Under Minimum Cost SCM Network
NASA Astrophysics Data System (ADS)
Park, N. K.; Kim, J. Y.; Choi, W. Y.; Tian, Z. M.; Kim, D. J.
Location of CDC in the matter of network on Supply Chain is becoming on the high concern these days. Present status of methods on CDC has been mainly based on the calculation manually by the spread sheet to achieve the goal of minimum logistics cost. This study is focused on the development of new processing algorithm to overcome the limit of present methods, and examination of the propriety of this algorithm by case study. The algorithm suggested by this study is based on the principle of optimization on the directive GRAPH of SCM model and suggest the algorithm utilizing the traditionally introduced MST, shortest paths finding methods, etc. By the aftermath of this study, it helps to assess suitability of the present on-going SCM network and could be the criterion on the decision-making process for the optimal SCM network building-up for the demand prospect in the future.
Path finding by tube morphogenesis in an amoeboid organism.
Nakagaki, T; Yamada, H; Tóth, A
2001-08-30
We have studied how the plasmodium of Physarum polycephalum, a large amoeboid cell, is able to track the shortest path between two selected points in a labyrinth. When nutrients are supplied at these points to a sheet-like plasmodium extended fully in a maze, the organism forms a single tube which connects the two sites via the shortest route. During the path finding, plasmodial parts in dead ends of the maze shrink and finally the tube with the minimum-length is selected from the existing possibilities. A simple cellular mechanism based on interacting cellular rhythms may describe the experimental observations. PMID:11527578
Mobile transporter path planning
NASA Technical Reports Server (NTRS)
Baffes, Paul; Wang, Lui
1990-01-01
The use of a genetic algorithm (GA) for solving the mobile transporter path planning problem is investigated. The mobile transporter is a traveling robotic vehicle proposed for the space station which must be able to reach any point of the structure autonomously. Elements of the genetic algorithm are explored in both a theoretical and experimental sense. Specifically, double crossover, greedy crossover, and tournament selection techniques are examined. Additionally, the use of local optimization techniques working in concert with the GA are also explored. Recent developments in genetic algorithm theory are shown to be particularly effective in a path planning problem domain, though problem areas can be cited which require more research.
NASA Astrophysics Data System (ADS)
Bhanu Ghosh, Dipta; Cococcioni, Matteo; Elliott, Ryan S.
2011-12-01
This work formulates a new computational scheme to efficiently explore the configuration space of materials and to identify a material's stable equilibrium structures. This computational tool is obtained by coupling quantum-based density functional theory (DFT) calculations (employing periodic boundary conditions) with branch-following and bifurcation (BFB) techniques. BFB is used to map equilibrium paths (stable and unstable) on the DFT energy landscape as a function of the applied load and ultimately creates 'bifurcation maps' that identify the material's stable structures and connections between them, including: soft deformation directions, transition states, transformation mechanisms, etc. This new approach has been used to study structural transitions in Si and Fe under pressure loading. The results obtained so far indicate that the new DFT-BFB methodology has the potential to provide a significant new insight into the mechanisms that drive structural phase transitions in a wide range of technologically important materials.
NASA Astrophysics Data System (ADS)
Ghosh, Dipta Bhanu; Cococcioni, Matteo; Elliott, Ryan S.
2010-04-01
Understanding structural phase transformations in solid-state materials is of great scientific and technological interest. These phenomena are governed by electronic degrees of freedom and thus, in principle, can be described with quantum mechanics alone. However, any realistic material has multiple length and time scales and access to these scales is a formidable task to deal with using quantum mechanics. On the contrary, for the continuum regime, empirical constitutive models have severe difficulties capturing material properties that ultimately arise from (sub-)atomic effects, and further, must be fit to experimental data. Thus, in order to obtain a predictive, complete understanding of a material subjected to different external loading parameters, the two regimes- atomistic and continuum-must be coupled. The present work formulates a coupled quantum-continuum model for scanning phase-space in order to determine the material's stable structure at any given pressure. This is accomplished by coupling quantumbased Density Functional Theory (DFT) calculations (employing periodic boundary conditions) with Branch- Following and Bifurcation (BFB) techniques. BFB is capable of mapping out equilibrium paths (stable and unstable) as a function of the applied pressure and ultimately creates "bifurcation maps" that identify the material's stable structures and connections between them, including: soft deformation directions, transition states, transformation mechanisms, etc.. This study shows that the coupled DFT-BFB methodology is capable of efficiently mapping out equilibrium paths. This includes the identification of stable and unstable pressure ranges and the identification of the deformation modes that first become soft-resulting in the structure's loss of stability. Example computations are provided for iron and silicon. The results obtained so far indicate that the new DFT-BFB methodology has the potential to provide a significant new insight on the mechanisms that drive structural phase transitions in a wide range of technologically important materials.
Smith, E.A.; Farrar, M.R.; Xiang, X. [Florida State Univ., Tallahassee, FL (United States)] [Florida State Univ., Tallahassee, FL (United States); Turk, F.J. [Naval Research Lab., Monterey, CA (United States)] [Naval Research Lab., Monterey, CA (United States); Mugnai, A. [Instituto di Fisica dell`Atmosfera-CNR, Frascati (Italy)] [Instituto di Fisica dell`Atmosfera-CNR, Frascati (Italy)
1997-04-01
This study presents research in support of the design and implementation of a combined radar-radiometer algorithm to be used for precipitation retrieval during the Tropical Rainfall Measuring Mission (TRMM). The combined algorithm approach is expected to overcome various difficulties that arise with a radar-only approach, particularly related to estimates of path-integrated attenuation (PIA)along the TRMM radar beam. A technique is described for estimating PIA at the 13.8-GHz frequency of the TRMM precipitation radar (PR) from 10.7-GHz brightness temperature T{sub B} measurements obtained from the TRMM microwave imager. Through the use of variational or probabilistic techniques, the independent PIA calculations provide a means to adjust for errors that accumulate in estimates of range-dependent rain rates at progressively increasing range positions from radar reflectivity vectors. The accepted radar approach for obtaining PIA from ocean-viewing radar reflectivity measurements is called the surface reference technique, a scheme based on the difference in ocean surface cross sections between cloud-free and raining radar pixels. This technique has encountered problems, which are discussed and analyzed with the aid of coordinated aircraft radar (Airborne Rain Mapping Radar) and radiometer (Advanced Microwave Precipitation Radiometer) measurements obtained during the west Pacific Tropical Ocean Global Atmosphere Coupled Ocean-Atmosphere Response Experiment in 1993. 97 refs., 12 figs., 5 tabs.
Orthogonal Scan Paths for Data Path Logic Robert B. Norwood* and Edward J. McCluskey
Stanford University
Orthogonal Scan Paths for Data Path Logic Robert B. Norwood* and Edward J. McCluskey Center Abstract We have implemented a synthesis-for-test algorithm to implement orthogonal scan paths in data path logic. Orthogonal scan paths [Avra 92] facilitate the sharing of the functional and the test logic
Algorithmic Strategies in Combinatorial Chemistry
GOLDMAN,DEBORAH; ISTRAIL,SORIN; LANCIA,GIUSEPPE; PICCOLBONI,ANTONIO; WALENZ,BRIAN
2000-08-01
Combinatorial Chemistry is a powerful new technology in drug design and molecular recognition. It is a wet-laboratory methodology aimed at ``massively parallel'' screening of chemical compounds for the discovery of compounds that have a certain biological activity. The power of the method comes from the interaction between experimental design and computational modeling. Principles of ``rational'' drug design are used in the construction of combinatorial libraries to speed up the discovery of lead compounds with the desired biological activity. This paper presents algorithms, software development and computational complexity analysis for problems arising in the design of combinatorial libraries for drug discovery. The authors provide exact polynomial time algorithms and intractability results for several Inverse Problems-formulated as (chemical) graph reconstruction problems-related to the design of combinatorial libraries. These are the first rigorous algorithmic results in the literature. The authors also present results provided by the combinatorial chemistry software package OCOTILLO for combinatorial peptide design using real data libraries. The package provides exact solutions for general inverse problems based on shortest-path topological indices. The results are superior both in accuracy and computing time to the best software reports published in the literature. For 5-peptoid design, the computation is rigorously reduced to an exhaustive search of about 2% of the search space; the exact solutions are found in a few minutes.
A Flexible Reservation Algorithm for Advance Network Provisioning
Balman, Mehmet; Chaniotakis, Evangelos; Shoshani, Arie; Sim, Alex
2010-04-12
Many scientific applications need support from a communication infrastructure that provides predictable performance, which requires effective algorithms for bandwidth reservations. Network reservation systems such as ESnet's OSCARS, establish guaranteed bandwidth of secure virtual circuits for a certain bandwidth and length of time. However, users currently cannot inquire about bandwidth availability, nor have alternative suggestions when reservation requests fail. In general, the number of reservation options is exponential with the number of nodes n, and current reservation commitments. We present a novel approach for path finding in time-dependent networks taking advantage of user-provided parameters of total volume and time constraints, which produces options for earliest completion and shortest duration. The theoretical complexity is only O(n2r2) in the worst-case, where r is the number of reservations in the desired time interval. We have implemented our algorithm and developed efficient methodologies for incorporation into network reservation frameworks. Performance measurements confirm the theoretical predictions.
a Strategy of Designing Routing Algorithms Based on Ideal Routings
NASA Astrophysics Data System (ADS)
Shinjo, K.; Shimogawa, S.; Yamada, J.; Oida, K.
This paper proposes a strategy of designing routing algorithms for connectionless packet-switched networks. This strategy consists of three design elements as follows: [A] the notion of ideal routings is introduced to provide the upper performance limits attained by improving routing algorithm and it serves as a standard to measure the performance of other algorithms; [B] a method of constructing simple algorithms is presented under implementation conditions from ideal routings; [C] a method is described to enhance the performance limits of [A]. By using these elements, simple algorithms with a maximum degree of performance attainment are realized. By "degree of performance attainment", we mean that we can see how much room is left for the improvement of algorithms. We develop [A] and [B] with the performance measures of throughput and average packet delay and the M/M/1 queuing network. We decide ideal static routings and their performance limits from [A]. We obtain a new simple algorithm from [B] based on the notion of the ideal routings in implementation conditions. The designed algorithm improves the throughput and the average delay, which are comparable to those from ideal static routings. This improvement is contrasted to the adaptive and distributed OSPF (Open Shortest Path First), a standard Internet routing protocol.
Integrated Flight Path Planning System and Flight Control System for Unmanned Helicopters
Jan, Shau Shiun; Lin, Yu Hsiang
2011-01-01
This paper focuses on the design of an integrated navigation and guidance system for unmanned helicopters. The integrated navigation system comprises two systems: the Flight Path Planning System (FPPS) and the Flight Control System (FCS). The FPPS finds the shortest flight path by the A-Star (A*) algorithm in an adaptive manner for different flight conditions, and the FPPS can add a forbidden zone to stop the unmanned helicopter from crossing over into dangerous areas. In this paper, the FPPS computation time is reduced by the multi-resolution scheme, and the flight path quality is improved by the path smoothing methods. Meanwhile, the FCS includes the fuzzy inference systems (FISs) based on the fuzzy logic. By using expert knowledge and experience to train the FIS, the controller can operate the unmanned helicopter without dynamic models. The integrated system of the FPPS and the FCS is aimed at providing navigation and guidance to the mission destination and it is implemented by coupling the flight simulation software, X-Plane, and the computing software, MATLAB. Simulations are performed and shown in real time three-dimensional animations. Finally, the integrated system is demonstrated to work successfully in controlling the unmanned helicopter to operate in various terrains of a digital elevation model (DEM). PMID:22164029
Computing the Length of the Shortest Telomere in the Nucleus
NASA Astrophysics Data System (ADS)
Dao Duc, K.; Holcman, D.
2013-11-01
The telomere length can either be shortened or elongated by an enzyme called telomerase after each cell division. Interestingly, the shortest telomere is involved in controlling the ability of a cell to divide. Yet, its dynamics remains elusive. We present here a stochastic approach where we model this dynamics using a Markov jump process. We solve the forward Fokker-Planck equation to obtain the steady state distribution and the statistical moments of telomere lengths. We focus specifically on the shortest one and we estimate its length difference with the second shortest telomere. After extracting key parameters such as elongation and shortening dynamics from experimental data, we compute the length of telomeres in yeast and obtain as a possible prediction the minimum concentration of telomerase required to ensure a proper cell division.
An efficient QoS-aware routing algorithm for LEO polar constellations
NASA Astrophysics Data System (ADS)
Tian, Xin; Pham, Khanh; Blasch, Erik; Tian, Zhi; Shen, Dan; Chen, Genshe
2013-05-01
In this work, a Quality of Service (QoS)-aware routing (QAR) algorithm is developed for Low-Earth Orbit (LEO) polar constellations. LEO polar orbits are the only type of satellite constellations where inter-plane inter-satellite links (ISLs) are implemented in real world. The QAR algorithm exploits features of the topology of the LEO satellite constellation, which makes it more efficient than general shortest path routing algorithms such as Dijkstra's or extended Bellman-Ford algorithms. Traffic density, priority, and error QoS requirements on communication delays can be easily incorporated into the QAR algorithm through satellite distances. The QAR algorithm also supports efficient load balancing in the satellite network by utilizing the multiple paths from the source satellite to the destination satellite, and effectively lowers the rate of network congestion. The QAR algorithm supports a novel robust routing scheme in LEO polar constellation, which is able to significantly reduce the impact of inter-satellite link (ISL) congestions on QoS in terms of communication delay and jitter.
Advisory Algorithm for Scheduling Open Sectors, Operating Positions, and Workstations
NASA Technical Reports Server (NTRS)
Bloem, Michael; Drew, Michael; Lai, Chok Fung; Bilimoria, Karl D.
2012-01-01
Air traffic controller supervisors configure available sector, operating position, and work-station resources to safely and efficiently control air traffic in a region of airspace. In this paper, an algorithm for assisting supervisors with this task is described and demonstrated on two sample problem instances. The algorithm produces configuration schedule advisories that minimize a cost. The cost is a weighted sum of two competing costs: one penalizing mismatches between configurations and predicted air traffic demand and another penalizing the effort associated with changing configurations. The problem considered by the algorithm is a shortest path problem that is solved with a dynamic programming value iteration algorithm. The cost function contains numerous parameters. Default values for most of these are suggested based on descriptions of air traffic control procedures and subject-matter expert feedback. The parameter determining the relative importance of the two competing costs is tuned by comparing historical configurations with corresponding algorithm advisories. Two sample problem instances for which appropriate configuration advisories are obvious were designed to illustrate characteristics of the algorithm. Results demonstrate how the algorithm suggests advisories that appropriately utilize changes in airspace configurations and changes in the number of operating positions allocated to each open sector. The results also demonstrate how the advisories suggest appropriate times for configuration changes.
Visualization of Ant Pheromone Based Path Following
Sutherland, Benjamin T.
2010-07-14
This thesis develops a simulation and visualization of a path finding algorithm based on ant pheromone paths created in 3D space. The simulation is useful as a demonstration of a heuristic approach to NP-complete problems ...
A star recognition method based on the Adaptive Ant Colony algorithm for star sensors.
Quan, Wei; Fang, Jiancheng
2010-01-01
A new star recognition method based on the Adaptive Ant Colony (AAC) algorithm has been developed to increase the star recognition speed and success rate for star sensors. This method draws circles, with the center of each one being a bright star point and the radius being a special angular distance, and uses the parallel processing ability of the AAC algorithm to calculate the angular distance of any pair of star points in the circle. The angular distance of two star points in the circle is solved as the path of the AAC algorithm, and the path optimization feature of the AAC is employed to search for the optimal (shortest) path in the circle. This optimal path is used to recognize the stellar map and enhance the recognition success rate and speed. The experimental results show that when the position error is about 50?, the identification success rate of this method is 98% while the Delaunay identification method is only 94%. The identification time of this method is up to 50 ms. PMID:22294908
Ant Algorithms for Discrete Optimization
Libre de Bruxelles, UniversitÃ©
optimization that took inspiration from the observation of ant colonies' foraging behavior, and introduces and interesting behavior of ant colonies is their foraging behavior, and, in particular, how ants can find behavior can give rise, once employed by a colony of ants, to the emergence of shortest paths. That is
Ant Algorithms for Discrete Optimization
Conati, Cristina
optimization that took inspiration from the observation of ant colonies' foraging behavior, and introduces to the relative simplicity of the colony's individuals. An important and interesting behavior of ant colonies is their foraging behavior, and, in particular, how ants can nd the shortest paths between food sources
Ant Algorithms for Discrete Optimization
Gambardella, Luca Maria
for discrete optimization which took inspiration from the observation of ant colonies foraging behavior to the relative sim- plicity of the colony's individuals. An important and interesting behavior of ant colonies is their foraging behavior, and, in particular, how ants can find shortest paths between food sources and their nest
Computational Geometry Column 35 Joseph O'Rourke \\Lambda
O'Rourke, Joseph
a geodesic shortest path, in contrast to a Euclidean shortest path, which may leave the 2manifold and fly through 3space. Whereas finding a Euclidean shortest path is NPhard [CR87], the geodesic shortest path that does not track the wavefront [CH96]. This latter algorithm is simple enough to invite implementations
NASA Technical Reports Server (NTRS)
Ng, Hok K.; Grabbe, Shon; Mukherjee, Avijit
2010-01-01
The optimization of traffic flows in congested airspace with varying convective weather is a challenging problem. One approach is to generate shortest routes between origins and destinations while meeting airspace capacity constraint in the presence of uncertainties, such as weather and airspace demand. This study focuses on development of an optimal flight path search algorithm that optimizes national airspace system throughput and efficiency in the presence of uncertainties. The algorithm is based on dynamic programming and utilizes the predicted probability that an aircraft will deviate around convective weather. It is shown that the running time of the algorithm increases linearly with the total number of links between all stages. The optimal routes minimize a combination of fuel cost and expected cost of route deviation due to convective weather. They are considered as alternatives to the set of coded departure routes which are predefined by FAA to reroute pre-departure flights around weather or air traffic constraints. A formula, which calculates predicted probability of deviation from a given flight path, is also derived. The predicted probability of deviation is calculated for all path candidates. Routes with the best probability are selected as optimal. The predicted probability of deviation serves as a computable measure of reliability in pre-departure rerouting. The algorithm can also be extended to automatically adjust its design parameters to satisfy the desired level of reliability.
Scaling up multiphoton neural scanning: the SSA algorithm.
Schuck, Renaud; Annecchino, Luca A; Schultz, Simon R
2014-01-01
In order to reverse-engineer the information processing capabilities of the cortical circuit, we need to densely sample neural circuit; it may be necessary to sample the activity of thousands of neurons simultaneously. Frame scanning techniques do not scale well in this regard, due to the time "wasted" scanning extracellular space. For scanners in which inertia can be neglected, path length minimization strategies enable large populations to be imaged at relatively high sampling rates. However, in a standard multiphoton microscope, the scanners responsible for beam deflection are inertial, indicating that an optimal solution should take rotor and mirror momentum into account. We therefore characterized the galvanometric scanners of a commercial multiphoton microscope, in order to develop and validate a MATLAB model of microscope scanning dynamics. We tested the model by simulating scan paths across pseudo-randomly positioned neuronal populations of differing neuronal density and field of view. This model motivated the development of a novel scanning algorithm, Adaptive Spiral Scanning (SSA), in which the radius of a circular trajectory is constantly updated such that it follows a spiral trajectory scanning all the cells. Due to the kinematic efficiency of near-circular trajectories, this algorithm achieves higher sampling rates than shortest path approaches, while retaining a relatively efficient coverage fraction in comparison to raster or resonance based frame-scanning approaches. PMID:25570582
NASA Astrophysics Data System (ADS)
Luangpaiboon, P.
2009-10-01
Many entrepreneurs face to extreme conditions for instances; costs, quality, sales and services. Moreover, technology has always been intertwined with our demands. Then almost manufacturers or assembling lines adopt it and come out with more complicated process inevitably. At this stage, products and service improvement need to be shifted from competitors with sustainability. So, a simulated process optimisation is an alternative way for solving huge and complex problems. Metaheuristics are sequential processes that perform exploration and exploitation in the solution space aiming to efficiently find near optimal solutions with natural intelligence as a source of inspiration. One of the most well-known metaheuristics is called Ant Colony Optimisation, ACO. This paper is conducted to give an aid in complicatedness of using ACO in terms of its parameters: number of iterations, ants and moves. Proper levels of these parameters are analysed on eight noisy continuous non-linear continuous response surfaces. Considering the solution space in a specified region, some surfaces contain global optimum and multiple local optimums and some are with a curved ridge. ACO parameters are determined through hybridisations of Modified Simplex and Simulated Annealing methods on the path of Steepest Ascent, SAM. SAM was introduced to recommend preferable levels of ACO parameters via statistically significant regression analysis and Taguchi's signal to noise ratio. Other performance achievements include minimax and mean squared error measures. A series of computational experiments using each algorithm were conducted. Experimental results were analysed in terms of mean, design points and best so far solutions. It was found that results obtained from a hybridisation with stochastic procedures of Simulated Annealing method were better than that using Modified Simplex algorithm. However, the average execution time of experimental runs and number of design points using hybridisations were longer than those using a single method when compared. Finally they stated a recommendation of proper level settings of ACO parameters for all eight functions that can be used as a guideline for future applications of ACO. This is to promote ease of use of ACO in real life problems.
NASA Technical Reports Server (NTRS)
Janich, Karl W.
2005-01-01
The At-Least version of the Generalized Minimum Spanning Tree Problem (L-GMST) is a problem in which the optimal solution connects all defined clusters of nodes in a given network at a minimum cost. The L-GMST is NPHard; therefore, metaheuristic algorithms have been used to find reasonable solutions to the problem as opposed to computationally feasible exact algorithms, which many believe do not exist for such a problem. One such metaheuristic uses a swarm-intelligent Ant Colony System (ACS) algorithm, in which agents converge on a solution through the weighing of local heuristics, such as the shortest available path and the number of agents that recently used a given path. However, in a network using a solution derived from the ACS algorithm, some nodes may move around to different clusters and cause small changes in the network makeup. Rerunning the algorithm from the start would be somewhat inefficient due to the significance of the changes, so a genetic algorithm based on the top few solutions found in the ACS algorithm is proposed to quickly and efficiently adapt the network to these small changes.
Pair correlations in classical crystals: The shortest-graph method
NASA Astrophysics Data System (ADS)
Yurchenko, Stanislav O.; Kryuchkov, Nikita P.; Ivlev, Alexei V.
2015-07-01
The shortest-graph method is applied to calculate the pair correlation functions of crystals. The method is based on the representation of individual correlation peaks by the Gaussian functions, summed along the shortest graph connecting the two given points. The analytical expressions for the Gaussian parameters are derived for two- and three-dimensional crystals. The obtained results are compared with the pair correlation functions deduced from the molecular dynamics simulations of Yukawa, inverse-power law, Weeks-Chandler-Andersen, and Lennard-Jones crystals. By calculating the Helmholtz free energy, it is shown that the method is particularly accurate for soft interparticle interactions and for low temperatures, i.e., when the anharmonicity effects are insignificant. The accuracy of the method is further demonstrated by deriving the solid-solid transition line for Yukawa crystals, and the compressibility for inverse-power law crystals.
Pair correlations in classical crystals: The shortest-graph method.
Yurchenko, Stanislav O; Kryuchkov, Nikita P; Ivlev, Alexei V
2015-07-21
The shortest-graph method is applied to calculate the pair correlation functions of crystals. The method is based on the representation of individual correlation peaks by the Gaussian functions, summed along the shortest graph connecting the two given points. The analytical expressions for the Gaussian parameters are derived for two- and three-dimensional crystals. The obtained results are compared with the pair correlation functions deduced from the molecular dynamics simulations of Yukawa, inverse-power law, Weeks-Chandler-Andersen, and Lennard-Jones crystals. By calculating the Helmholtz free energy, it is shown that the method is particularly accurate for soft interparticle interactions and for low temperatures, i.e., when the anharmonicity effects are insignificant. The accuracy of the method is further demonstrated by deriving the solid-solid transition line for Yukawa crystals, and the compressibility for inverse-power law crystals. PMID:26203035
Parsimonious path openings and closings.
Morard, Vincent; Dokladal, Petr; Decenciere, Etienne
2014-04-01
Path openings and closings are morphological tools used to preserve long, thin, and tortuous structures in gray level images. They explore all paths from a defined class, and filter them with a length criterion. However, most paths are redundant, making the process generally slow. Parsimonious path openings and closings are introduced in this paper to solve this problem. These operators only consider a subset of the paths considered by classical path openings, thus achieving a substantial speed-up, while obtaining similar results. In addition, a recently introduced 1D opening algorithm is applied along each selected path. Its complexity is linear with respect to the number of pixels, independent of the size of the opening. Furthermore, it is fast for any input data accuracy (integer or floating point) and works in stream. Parsimonious path openings are also extended to incomplete paths, i.e., paths containing gaps. Noise-corrupted paths can thus be processed with the same approach and complexity. These parsimonious operators achieve a several orders of magnitude speed-up. Examples are shown for incomplete path openings, where computing times are brought from minutes to tens of milliseconds, while obtaining similar results. PMID:24569442
Inter-Domain Redundancy Path Computation Methods Based on PCE
NASA Astrophysics Data System (ADS)
Hayashi, Rie; Oki, Eiji; Shiomoto, Kohei
This paper evaluates three inter-domain redundancy path computation methods based on PCE (Path Computation Element). Some inter-domain paths carry traffic that must be assured of high quality and high reliability transfer such as telephony over IP and premium virtual private networks (VPNs). It is, therefore, important to set inter-domain redundancy paths, i. e. primary and secondary paths. The first scheme utilizes an existing protocol and the basic PCE implementation. It does not need any extension or modification. In the second scheme, PCEs make a virtual shortest path tree (VSPT) considering the candidates of primary paths that have corresponding secondary paths. The goal is to reduce blocking probability; corresponding secondary paths may be found more often after a primary path is decided; no protocol extension is necessary. In the third scheme, PCEs make a VSPT considering all candidates of primary and secondary paths. Blocking probability is further decreased since all possible candidates are located, and the sum of primary and secondary path cost is reduced by choosing the pair with minimum cost among all path pairs. Numerical evaluations show that the second and third schemes offer only a few percent reduction in blocking probability and path pair total cost, while the overheads imposed by protocol revision and increase of the amount of calculation and information to be exchanged are large. This suggests that the first scheme, the most basic and simple one, is the best choice.
Finding Shortest Paths on Surfaces by Fast Global Approximation and Precise Local Refinement
Kimmel, Ron
. The 3D curve shortening flow is transformed into an equivalent 2D one that is implemented using an arbi trary initial curve ending at two given surface points via geodesic curvature shortening flow numerical solutions of differential equations by numerical integration [2], and are com putationally
Computing Single Source Shortest Paths using Single-Objective Fitness Functions
Doerr, Benjamin
such as vehicle routing [8] and routing problems in networks [6, 10] have been tackled. Therefore, it seems- est in recent years. One approach to analyze evolutionary Work supported by the Collaborative Research
A Parametric Copula Approach for Modelling Shortest-Path Trees in Telecommunication Networks
Schmidt, Volker
estimation in telecommunication networks, it is desir- able to gain knowledge about distributional properties derive a joint bivariate distribution for the lengths of these branches by means of copula functions, i copula, parametric marginal distribution, stochastic ge- ometry, network planning, Palm calculus
The Multiple Choice Elementary Constrained Shortest Path Problem Karen Smilowitz Guangming Zhang
Smilowitz, Karen
-and-price approaches for variations of the vehicle routing problem in which the nodes to be visited are chosen among incorporate these methods into a branch-and-price approach to solve a variation of the vehicle routing problem-and-price method for a variation of the vehicle routing problem, known as the Multi-Resource Routing Problem (MRRP
A Dynamic Programming Approach to Identifying the Shortest Path in Virtual Learning Environments
ERIC Educational Resources Information Center
Fazlollahtabar, Hamed
2008-01-01
E-learning has been widely adopted as a promising solution by many organizations to offer learning-on-demand opportunities to individual employees (learners) in order to reduce training time and cost. While successful information systems models have received much attention among researchers, little research has been conducted to assess the success…
All-Pairs Almost Shortest Paths Ausarbeitung des Vortrags von Martin Holzer
Brandes, Ulrik
Grafen. Wird nun die Bedingung der Exaktheit dieser Distanzen etwas aufgeweicht und ein einseiti- ger und das APASP-Problem fÂ¨ur einen Grafen mit einem ein- seitigen additiven Fehler von maximal k l-Emulator zu einem ungewichteten Grafen einen gewichteten Grafen mit derselben Knotenmenge so, dass die Distanz
Stochastic Shortest Path MDPs with Dead Ends Andrey Kolobov Mausam Daniel S. Weld
Mausam
.g., sending a rover on Mars). Even though MDP algo- rithms are used for solving problems with dead with in many real-world planning problems, be it sending a rover on Mars or navigating a robot in a building for them. The first class we present, SSPADE, is a small extension of SSP that has well-defined easily
Fekete, SÃ¡ndor P.
Networks SÂ´andor Fekete Tom Kamphans Michael Stelzer Abstract A problem studied in Systems Biology is how do not properly reflect biochemical facts. An approach to overcome this issue is to use edge labels@freenet.de Helmholtz Centre for Infection Research (HZI), Systems Biology, 38124 Braunschweig, Germany Figure 1
Shortest Path versus Multi-Hub Routing in Networks with Uncertain Demand
Shepherd, Bruce
-to- point peak demands. Second, design the network to support all hose matrices (all matrices not exceeding patterns is available. We introduce a capped hose model to explore a range of traffic scenarios, which includes the above two as special cases. It is known that optimal network designs for the hose model
All-Pairs Shortest Paths for Unweighted Undirected Graphs in o(mn) Time
Chan, Timothy M.
n) if m > n log n log log log n O(mn log log n= log n) if m > n log log n O(n 2 log 2 log n= log n) if m #20; n log log n: These represent the best time bounds known for the problem for all m #28; n 1 in the general case with real-valued weights (the #12;rst subcubic time bound was O(n 3 (log log n= log n) 1
Watanabe, Shin; Tero, Atsushi; Takamatsu, Atsuko; Nakagaki, Toshiyuki
2011-09-01
Traffic optimization of railroad networks was considered using an algorithm that was biologically inspired by an amoeba-like organism, plasmodium of the true slime mold, Physarum polycephalum. The organism developed a transportation network consisting of a tubular structure to transport protoplasm. It was reported that plasmodium can find the shortest path interconnecting multiple food sites during an adaptation process (Nakagaki et al., 2001. Biophys. Chem. 92, 47-52). By mimicking the adaptation process a path finding algorithm was developed by Tero et al. (2007). In this paper, the algorithm is newly modified for applications of traffic distribution optimization in transportation networks of infrastructure such as railroads under the constraint that the network topology is given. Application of the algorithm to a railroad in metropolitan Tokyo, Japan is demonstrated. The results are evaluated using three performance functions related to cost, traveling efficiency, and network weakness. The traffic distribution suggests that the modified Physarum algorithm balances the performances under a certain parameter range, indicating a biological process. PMID:21620930
NSDL National Science Digital Library
Perry Samson
This website catalogs all the tornado paths in the United States since 1950. The tornado path data is overlaid onto a Google Maps base for easy browsing and manipulation of the map view. Clicking on individual tornados provides the user with information such as its Fujita rating, the amount of damage caused by the tornado, the size of the path that the tornado made, and the length of time the tornado was on the ground.
Pedestrian traffic: on the quickest path
NASA Astrophysics Data System (ADS)
Kretz, Tobias
2009-03-01
When a large group of pedestrians moves around a corner, most pedestrians do not follow the shortest path, which is to stay as close as possible to the inner wall, but try to minimize the travel time. For this they accept to move on a longer path with some distance to the corner, to avoid large densities and by this succeed in maintaining a comparatively high speed. In many models of pedestrian dynamics the basic rule of motion is often either 'move as far as possible toward the destination' or—reformulated—'of all coordinates accessible in this time step move to the one with the smallest distance to the destination'. On top of this rule modifications are placed to make the motion more realistic. These modifications usually focus on local behavior and neglect long-ranged effects. Compared to real pedestrians this leads to agents in a simulation valuing the shortest path a lot better than the quickest. So, in a situation such as the movement of a large crowd around a corner, one needs an additional element in a model of pedestrian dynamics that makes the agents deviate from the rule of the shortest path. In this work it is shown how this can be achieved by using a flood fill dynamic potential field method, where during the filling process the value of a field cell is not increased by 1, but by a larger value, if it is occupied by an agent. This idea may be an obvious one: however, the tricky part—and therefore in a strict sense the contribution of this work—is (a) to minimize unrealistic artifacts, as naive flood fill metrics deviate considerably from the Euclidean metric and in this respect yield large errors, (b) do this with limited computational effort and (c) keep agents' movement at very low densities unaltered.
Powers of Hamiltonian Paths in Interval Graphs
Isaak, Garth
Powers of Hamiltonian Paths in Interval Graphs Garth Isaak* DEPARTMENT OF MATHEMATICS LEHIGH of a Hamiltonian path are sufficient for the class of interval graphs. The proof is based on showing that a greedy algorithm tests for the existence of Hamiltonian path powers in interval graphs. We will also discuss covers
Theraulaz, Guy
2006-01-01
the foraging behavior of ants moving in an artificial network of tunnels in which several interconnected paths and those of the experiments, showing that simple behavioral rules can lead ants to find the shortest paths; Trail; Collective behavior 1. Introduction In a lot of ant species foragers do not exploit food sources
Dispersion of nonlinear group velocity determines shortest envelope solitons
Amiranashvili, Sh.; Bandelow, U.; Akhmediev, N. [Weierstrass Institute for Applied Analysis and Stochastics, Mohrenstrasse 39, D-10117 Berlin (Germany); Optical Sciences Group, Research School of Physics and Engineering, Institute of Advanced Studies, Australian National University, Canberra ACT 0200 (Australia)
2011-10-15
We demonstrate that a generalized nonlinear Schroedinger equation (NSE), which includes dispersion of the intensity-dependent group velocity, allows for exact solitary solutions. In the limit of a long pulse duration, these solutions naturally converge to a fundamental soliton of the standard NSE. In particular, the peak pulse intensity times squared pulse duration is constant. For short durations, this scaling gets violated and a cusp of the envelope may be formed. The limiting singular solution determines then the shortest possible pulse duration and the largest possible peak power. We obtain these parameters explicitly in terms of the parameters of the generalized NSE.
NASA Astrophysics Data System (ADS)
Ghassib, Humam B.; Sakhel, Asaad R.; Obeidat, Omar; Al-Oqali, Amer; Sakhel, Roger R.
2012-01-01
We demonstrate the effectiveness of a statistical potential (SP) in the description of fermions in a worm-algorithm path-integral Monte Carlo simulation of a few 3He atoms floating on a 4He layer adsorbed on graphite. The SP in this work yields successful results, as manifested by the clusterization of 3He, and by the observation that the 3He atoms float on the surface of 4He. We display the positions of the particles in 3D coordinate space, which reveal clusterization of the 3He component. The correlation functions are also presented, which give further evidence for the clusterization.
Open-path Fourier transform infrared (OP/FTIR) spectrometry was used to measure the concentrations of ammonia, methane, and other atmospheric gases at an integrated swine production facility. The concentration-pathlength products of the target gases at this site often exceeded th...
CMPSCI 611: "Advanced Algorithms" Lecture 10: Seidel's Algorithm
McGregor, Andrew
and PG quickly? 4/9 #12;Depth of Recursion The diameter of a graph G is the "longest shortest path", diam(G) = max i,j G (i, j) Note that if diam(G) 3: diam(G2) diam(G) 2 + 1 2 2diam(G) 3 After recursing t steps, the diameter is at most (2/3)t diam(G) and so after log(n/2)/ log(3/2) steps, the diameter
Escaping path approach for speckle noise reduction
NASA Astrophysics Data System (ADS)
Szczepanski, Marek; Radlak, Krystian
2015-02-01
A novel fast filtering technique for multiplicative noise removal in ultrasound images was presented in this paper. The proposed algorithm utilizes concept of digital paths created on the image grid presented in [1] adapted to the needs of multiplicative noise reduction. The new approach uses special type of digital paths so called Escaping Path Model and modified path length calculation based on topological as well as gray-scale distances. The experiments confirmed that the proposed algorithm achieves a comparable results with the existing state-of-the-art denoising schemes in suppressing multiplicative noise in ultrasound images.
Pokemon Cards and the Shortest Common Superstring Mark Stamp Austin E Stamp
Stamp, Mark
Pok´emon Cards and the Shortest Common Superstring Mark Stamp Austin E Stamp June 12, 2003 Abstract Evidence is presented that certain sequences of Pok´emon cards are determined by selecting consecutive (SCS), i.e., the shortest string that contains each of the Pok´emon card sequences as a consecutive
Path planning using a tangent graph for mobile robots among polygonal and curved obstacles
Liu, Yun-Hui; Arimoto, Suguru (Univ. of Tokyo (Japan))
1992-08-01
This article proposes a tangent graph for path planning of mobile robots among obstacles with a general boundary. The tangent graph is defined on the basis of the locally shortest path. It has the same data structure as the visibility graph, but its nodes represent common tangent points on obstacle boundaries, and its edges correspond to collision-free common tangents between the boundaries and convex boundary segments between the tangent points. The tangent graph requires O(K[sup 2]) memory, where K denotes the total number of convex segments of the obstacle boundaries. The tangent graph includes all locally shortest paths and is capable of coping with path planning not only among polygonal obstacles but also among curved obstacles.
Applications of Path Compression on Balanced Trees
Robert Endre Tarjan
1979-01-01
Several fast algorithms are presented for computing functions defined on paths in trees under various assumpuons. The algorithms are based on tree mampulatton methods first used to efficiently represent equivalence relations. The algorithms have O((m + n)a(m + n, n)) running tunes, where m and n are measures of the problem size and a Is a functional reverse of Ackermann's
Minimum Wheel-Rotation Paths for Differential-Drive Mobile Hamidreza Chitsaz
LaValle, Steven M.
Minimum Wheel-Rotation Paths for Differential-Drive Mobile Robots Hamidreza Chitsaz , Steven M. La. To obtain a well-defined notion of shortest, the total amount of wheel rotation is optimized. Using-Shepp car is equal to minimum wheel-rotation for the differential drive, and minimum time curves
An Explicit Characterization of Minimum Wheel-Rotation Paths for Differential-Drives
LaValle, Steven M.
An Explicit Characterization of Minimum Wheel-Rotation Paths for Differential-Drives Hamidreza. A well-defined notion of shortest is obtained by optimizing the total amount of wheel rotation. This paper extends our previous characterization of the minimum wheel-rotation trajectories that are maximal
Leaf-sequencing for intensity-modulated arc therapy using graph algorithms.
Luan, Shuang; Wang, Chao; Cao, Daliang; Chen, Danny Z; Shepard, David M; Yu, Cedric X
2008-01-01
Intensity-modulated arc therapy (IMAT) is a rotational IMRT technique. It uses a set of overlapping or nonoverlapping arcs to create a prescribed dose distribution. Despite its numerous advantages, IMAT has not gained widespread clinical applications. This is mainly due to the lack of an effective IMAT leaf-sequencing algorithm that can convert the optimized intensity patterns for all beam directions into IMAT treatment arcs. To address this problem, we have developed an IMAT leaf-sequencing algorithm and software using graph algorithms in computer science. The input to our leaf-sequencing software includes (1) a set of (continuous) intensity patterns optimized by a treatment planning system at a sequence of equally spaced beam angles (typically 10 degrees apart), (2) a maximum leaf motion constraint, and (3) the number of desired arcs, k. The output is a set of treatment arcs that best approximates the set of optimized intensity patterns at all beam angles with guaranteed smooth delivery without violating the maximum leaf motion constraint. The new algorithm consists of the following key steps. First, the optimized intensity patterns are segmented into intensity profiles that are aligned with individual MLC leaf pairs. Then each intensity profile is segmented into k MLC leaf openings using a k-link shortest path algorithm. The leaf openings for all beam angles are subsequently connected together to form 1D IMAT arcs under the maximum leaf motion constraint using a shortest path algorithm. Finally, the 1D IMAT arcs are combined to form IMAT treatment arcs of MLC apertures. The performance of the implemented leaf-sequencing software has been tested for four treatment sites (prostate, breast, head and neck, and lung). In all cases, our leaf-sequencing algorithm produces efficient and highly conformal IMAT plans that rival their counterpart, the tomotherapy plans, and significantly improve the IMRT plans. Algorithm execution times ranging from a few seconds to 2 min are observed on a laptop computer equipped with a 2.0 GHz Pentium M processor. PMID:18293562
Leaf-sequencing for intensity-modulated arc therapy using graph algorithms
Luan Shuang; Wang Chao; Cao Daliang; Chen, Danny Z.; Shepard, David M.; Yu, Cedric X.
2008-01-15
Intensity-modulated arc therapy (IMAT) is a rotational IMRT technique. It uses a set of overlapping or nonoverlapping arcs to create a prescribed dose distribution. Despite its numerous advantages, IMAT has not gained widespread clinical applications. This is mainly due to the lack of an effective IMAT leaf-sequencing algorithm that can convert the optimized intensity patterns for all beam directions into IMAT treatment arcs. To address this problem, we have developed an IMAT leaf-sequencing algorithm and software using graph algorithms in computer science. The input to our leaf-sequencing software includes (1) a set of (continuous) intensity patterns optimized by a treatment planning system at a sequence of equally spaced beam angles (typically 10 deg. apart), (2) a maximum leaf motion constraint, and (3) the number of desired arcs, k. The output is a set of treatment arcs that best approximates the set of optimized intensity patterns at all beam angles with guaranteed smooth delivery without violating the maximum leaf motion constraint. The new algorithm consists of the following key steps. First, the optimized intensity patterns are segmented into intensity profiles that are aligned with individual MLC leaf pairs. Then each intensity profile is segmented into k MLC leaf openings using a k-link shortest path algorithm. The leaf openings for all beam angles are subsequently connected together to form 1D IMAT arcs under the maximum leaf motion constraint using a shortest path algorithm. Finally, the 1D IMAT arcs are combined to form IMAT treatment arcs of MLC apertures. The performance of the implemented leaf-sequencing software has been tested for four treatment sites (prostate, breast, head and neck, and lung). In all cases, our leaf-sequencing algorithm produces efficient and highly conformal IMAT plans that rival their counterpart, the tomotherapy plans, and significantly improve the IMRT plans. Algorithm execution times ranging from a few seconds to 2 min are observed on a laptop computer equipped with a 2.0 GHz Pentium M processor.
Katherine E. Coons; Xia Chen; Sundeep K. Kushwaha; Doug Burger; Kathryn S. McKinley
Growing on-chip wire delays are motivating architectural features that expose on-chip communication to the compiler. EDGE archi- tectures are one example of communication-exposed microarchi- tectures in which the compiler forms dataflow graphs that spe cify how the microarchitecture maps instructions onto a distributed ex- ecution substrate. This paper describes a compiler scheduling al- gorithm called spatial path scheduling that factors
Generating informative paths for persistent sensing in unknown environments
Soltero, Daniel E.
We present an online algorithm for a robot to shape its path to a locally optimal configuration for collecting information in an unknown dynamic environment. As the robot travels along its path, it identifies both where ...
Path planning in a two-dimensional environment
NASA Astrophysics Data System (ADS)
Fox, Richard K.; Garcia, Antonio, Jr.; Nelson, Michael L.
1999-07-01
This paper presents a path planning algorithm that is part of the STESCA control architecture for autonomous vehicles. The path planning algorithm models an autonomous vehicle's path as a series of line segments in Cartesian space and compares each line segment to a list of known obstacles and hazardous areas to determine if any collisions or hindrances exist. In the event of a detected collision, the algorithm selects a point outside the obstacle or hazardous area, generates two new path segments that avoid the obstruction and recursively checks the new paths for other collisions. Once underway, if the autonomous vehicle encounters previously unknown obstacles or hazardous areas, the path planner operates in a run-time mode that decides how to re-route the path around the obstacle or abort. This paper describes the path planner along with examples of path planning in a two-dimensional environment with a wheeled land-based robotic vehicle.
A methodology for predicting minimum travel paths using real-time traffic network data
Liu, Chang
1991-01-01
the shortest path between any two nodes. This is the path with minimum total link length. The links can be either directional or nondirectional. Mathematically, this problem can be defined as follows: if node V, and V, are the source and 11 destination... directional links. The TRANSYT computer program developed by Robertson in 19& can determine optimum cycle length, phase splits, and offsets that minimize a performance index which is a linear combination of stops and delays. The TRANSYT program can predict...
Minimum-Risk Path Finding by an Adaptive Amoebal Network
NASA Astrophysics Data System (ADS)
Nakagaki, Toshiyuki; Iima, Makoto; Ueda, Tetsuo; Nishiura, Yasumasa; Saigusa, Tetsu; Tero, Atsushi; Kobayashi, Ryo; Showalter, Kenneth
2007-08-01
When two food sources are presented to the slime mold Physarum in the dark, a thick tube for absorbing nutrients is formed that connects the food sources through the shortest route. When the light-avoiding organism is partially illuminated, however, the tube connecting the food sources follows a different route. Defining risk as the experimentally measurable rate of light-avoiding movement, the minimum-risk path is exhibited by the organism, determined by integrating along the path. A model for an adaptive-tube network is presented that is in good agreement with the experimental observations.
A novel algorithm for OSPF link flap damping
NASA Astrophysics Data System (ADS)
Yang, Yang; Liu, Guangyi; Lin, Xiaokang
2005-02-01
Open shortest path first (OSPF) is the most widely used routing protocol in today"s IP networks, and its excellent performance has been proved in wired environments. However, when it is executed under bad channel conditions such as in wireless networks or areas with severe signal interference, links may flap frequently and some terrible problems will appear. This paper proposes a novel algorithm called OSPF link flap damping algorithm (OLFDA). The objective of OLFDA is to reduce the events of link state advertisement (LSA) update and damp the link flap with the precondition that the overall network performance is satisfying. To accomplish this, we can define criteria to identify and dynamically suppress the poorly behaved links. Information of the suppressed links won"t be advertised in OSPF domain and used in calculation of the routing tables. In addition, we can control the maximal number of links suppressed simultaneously by a router to ensure the network connectivity. OLFDA are simulated in many scenarios, and the results indicate that the algorithm has an excellent performance.
Preferential Path Profiling: Compactly Numbering Interesting Paths
Chilimbi, Trishul
Preferential Path Profiling: Compactly Numbering Interesting Paths Kapil Vaswani Indian Institute@microsoft.com Trishul M. Chilimbi Microsoft Research trishulc@microsoft.com Abstract Path profiles provide a more preferential path profiling (PPP), that reduces the overhead of path profiling. PPP leverages the observation
NASA Astrophysics Data System (ADS)
Nakamura, T.; Sekimoto, Y.; Usui, T.; Shibasaki, R.
2012-07-01
Nowadays, for the estimation of traffic demand or people flow, modelling route choice activity in road networks is an important task and many algorithms have been developed to generate route choice sets. However, developing an algorithm based on a small amount of data that can be applied generally within a metropolitan area is difficult. This is because the characteristics of road networks vary widely. On the other hand, recently, the collection of people movement data has lately become much easier, especially through mobile phones. Lately, most mobile phones include GPS functionality. Given this background, we propose a data-oriented algorithm to generate route choice sets using mobile phone GPS data. GPS data contain a number of measurement errors; hence, they must be adjusted to account for these errors before use in advanced people movement analysis. However, this is time-consuming and expensive, because an enormous amount of daily data can be obtained. Hence, the objective of this study is to develop an algorithm that can easily manage GPS data. Specifically, at first movement data from all GPS data are selected by calculating the speed. Next, the nearest roads in the road network are selected from the GPS location and count such data for each road. Then An algorithm based on the GSP (Gateway Shortest Path) algorithm is proposed, which searches the shortest path through a given gateway. In the proposed algorithm, the road for which the utilization volume calculated by GPS data is large is selected as the gateway. Thus, route choice sets that are based on trends in real GPS data are generated. To evaluate the proposed method, GPS data from 0.7 million people a year in Japan and DRM (Digital Road Map) as the road network are used. DRM is one of the most detailed road networks in Japan. Route choice sets using the proposed algorithm are generated and the cover rate of the utilization volume of each road under evaluation is calculated. As a result, the proposed route generation algorithm and GPS data cleaning process work well and a huge variety of routes that have high potential to be used in the real world can be generated.
NSDL National Science Digital Library
Cynthia Ann Radle (McCullough High School REV)
1995-06-30
Students follow several pathways using anatomical directions on a simulated "body" produced from a copy of a school building's fire evacuation plan. The main hallways are designated as major blood vessels and the various areas of the school, the head, chest, abdomen, etc. Students complete several pathways using anatomical terms as directions. For example, one of my paths begins, "Ex- ot-, ad- superior, ecto- derm-, peri-frontal, circum- rhino-, " which loosely means, exit the ear, go to the superior region, outside the skin, around the frontal region, around the nose. At the end of each path I leave a clue that lets me know the students actually made it. The combined clues form a sentence.
Towards Safest Path Adversarial Coverage (Extended Abstract)
Kaminka, Gal A.
to perform coverage missions in hazardous environments, such as opera- tions in nuclear power plants- plistic heuristic algorithm that generates a coverage path which tries to minimize a cost function, which
A hybrid genetic algorithm for the weight setting problem in OSPF\\/ISIS routing
Luciana S. Buriol; Mauricio G. C. Resende; Celso C. Ribeiro; Mikkel Thorup
2005-01-01
Intradomain traffic engineering aims to make more effi- cient use of network resources within an autonomous system. Interior Gateway Protocols such as OSPF (Open Shortest Path First) and IS-IS (Intermediate System- Intermediate System) are commonly used to select the paths along which traffic is routed within an autonomous system. These routing protocols direct traffic based on link weights assigned by
A Random Sampling Scheme for Path Planning
Latombe, Jean-Claude
precludes any useful application. This negative result has led some researchers to seek heuristic algorithms path planners have been proposed during the last few years. Their at tractiveness stems from for future research. 1 Introduction Robot path planning has been proven a hard problem [40]. There is strong
The shortest modulation period Blazhko RR Lyrae star: SS Cnc
J. Jurcsik; B. Szeidl; Á. Sódor; I. Dékány; Zs. Hurta; K. Posztobányi; K. Vida; M. Váradi; A. Szing
2006-03-20
Extended BV(RI)c CCD observations of SS Cnc, a short period RRab star are presented. Nearly 1400 data points in each band have been obtained spanning over 79 days during the spring of 2005. The star exhibits light curve modulation, the so called Blazhko effect with small amplitude (B maximum brightness varies 0.1 mag) and with the shortest modulation period (5.309 d) ever observed. In the Fourier spectrum of the V light curve the pulsation frequency components are detected up to the 24th harmonic order, and modulation side lobe frequencies with significantly asymmetric amplitudes are seen up to the 15th and 9th orders for the lower and higher frequency components, respectively. Detailed comparison of the modulation behavior of SS Cnc and RR Gem, the two recently discovered small amplitude, short modulation period Blazhko stars is presented. The modulation frequency (f_m) appears in the Fourier spectrum of both stars with similar amplitude. We also demonstrate that the modulation frequencies have basically different properties as the pulsation and modulation side lobe frequencies have, indicating that the physics behind these frequency components are not the same. The discovery of small amplitude modulations of RRab stars cautions that the large photometric surveys (MACHO, OGLE) may seriously underestimate the number of modulated RR Lyrae stars.
Identification of Biochemical Network Modules Based on Shortest Retroactive Distances
Sridharan, Gautham Vivek; Hassoun, Soha; Lee, Kyongbum
2011-01-01
Modularity analysis offers a route to better understand the organization of cellular biochemical networks as well as to derive practically useful, simplified models of these complex systems. While there is general agreement regarding the qualitative properties of a biochemical module, there is no clear consensus on the quantitative criteria that may be used to systematically derive these modules. In this work, we investigate cyclical interactions as the defining characteristic of a biochemical module. We utilize a round trip distance metric, termed Shortest Retroactive Distance (ShReD), to characterize the retroactive connectivity between any two reactions in a biochemical network and to group together network components that mutually influence each other. We evaluate the metric on two types of networks that feature feedback interactions: (i) epidermal growth factor receptor (EGFR) signaling and (ii) liver metabolism supporting drug transformation. For both networks, the ShReD partitions found hierarchically arranged modules that confirm biological intuition. In addition, the partitions also revealed modules that are less intuitive. In particular, ShReD-based partition of the metabolic network identified a ‘redox’ module that couples reactions of glucose, pyruvate, lipid and drug metabolism through shared production and consumption of NADPH. Our results suggest that retroactive interactions arising from feedback loops and metabolic cycles significantly contribute to the modularity of biochemical networks. For metabolic networks, cofactors play an important role as allosteric effectors that mediate the retroactive interactions. PMID:22102800
Fritz, Sean
2015-01-01
In this study, an interplanetary space flight mission design is established to obtain the minimum \\(\\Delta V\\) required for a rendezvous and sample return mission from an asteroid. Given the initial (observed) conditions of an asteroid, a (robust) genetic algorithm is implemented to determine the optimal choice of \\(\\Delta V\\) required for the rendezvous. Robustness of the optimum solution is demonstrated through incorporated bounded-uncertainties in the outbound \\(\\Delta V\\) maneuver via genetic fitness function. The improved algorithm results in a solution with improved robustness and reduced sensitivity to propulsive errors in the outbound maneuver. This is achieved over a solution optimized solely on \\(\\Delta V\\), while keeping the increase in \\(\\Delta V\\) to a minimum, as desired. Outcomes of the analysis provide significant results in terms of improved robustness in asteroid rendezvous missions.
NASA Astrophysics Data System (ADS)
Harrison, F. W.; Lin, B.; Ismail, S.; Nehrir, A. R.; Dobler, J. T.; Browell, E. V.; Kooi, S. A.; Campbell, J. F.; Obland, M. D.; Yang, M. M.; Meadows, B.
2014-12-01
This paper presents an overview of the methods for the retrieval of carbon dioxide (CO2) and oxygen (O2) column amounts and their associated path lengths measured by the Multi-Functional Fiber Laser Lidar (MFLL) and the ASCENDS CarbonHawk Experiment Simulator (ACES). MFLL and ACES are multi-frequency, Intensity-Modulated, Continuous-Wave (IM-CW) Lidar systems developed as proof-of-concept demonstrators for NASA's Active Sensing of CO2 Emissions over Nights, Days, and Seasons (ASCENDS) mission. The National Research Council identified ASCENDS in 2007 as an important mid-term decadal survey mission to provide measurements critical to improved projections of the Earth's future climate. The ASCENDS measurement requirements have evolved significantly since first proposed by the NRC as has our understanding of the IM-CW measurement technique we propose for use by ASCENDS. To meet these requirements, both MFLL and ACES transmit wavelengths near 1.57 and 1.26 ?m modulated with range-encoded signals to minimize bias from thin clouds in the CO2 and O2 column measurements while simultaneously measuring the path length to the surface and to intervening cloud layers. In preparation for the ASCENDS mission, the MFLL has been deployed on 13 airborne field campaigns since 2005, including the latest series of flights in August 2014. NASA also flew the ACES instrument as a technology demonstrator in 2014. In this paper we describe the current ASCENDS retrieval technique and present the accuracy and precision of the measurements obtained using this technique. We also present a reanalysis of the 2011 MFLL measurements and compare the results previously reported to the reanalysis. Reanalysis yields range precisions of less that one meter from an altitude of 12 kilometers from the CO2 offline channel with 1.6 watts of transmitted power.
A Comparison of Two Path Planners for Planetary Rovers
NASA Technical Reports Server (NTRS)
Tarokh, M.; Shiller, Z.; Hayati, S.
1999-01-01
The paper presents two path planners suitable for planetary rovers. The first is based on fuzzy description of the terrain, and genetic algorithm to find a traversable path in a rugged terrain. The second planner uses a global optimization method with a cost function that is the path distance divided by the velocity limit obtained from the consideration of the rover static and dynamic stability. A description of both methods is provided, and the results of paths produced are given which show the effectiveness of the path planners in finding near optimal paths. The features of the methods and their suitability and application for rover path planning are compared
Constrained motion control on a hemispherical surface: path planning.
Berman, Sigal; Liebermann, Dario G; McIntyre, Joseph
2014-03-01
Surface-constrained motion, i.e., motion constraint by a rigid surface, is commonly found in daily activities. The current work investigates the choice of hand paths constrained to a concave hemispherical surface. To gain insight regarding paths and their relationship with task dynamics, we simulated various control policies. The simulations demonstrated that following a geodesic path (the shortest path between 2 points on a sphere) is advantageous not only in terms of path length but also in terms of motor planning and sensitivity to motor command errors. These stem from the fact that the applied forces lie in a single plane (that of the geodesic path). To test whether human subjects indeed follow the geodesic, and to see how such motion compares to other paths, we recorded movements in a virtual haptic-visual environment from 11 healthy subjects. The task comprised point-to-point motion between targets at two elevations (30° and 60°). Three typical choices of paths were observed from a frontal plane projection of the paths: circular arcs, straight lines, and arcs close to the geodesic path for each elevation. Based on the measured hand paths, we applied k-means blind separation to divide the subjects into three groups and compared performance indicators. The analysis confirmed that subjects who followed paths closest to the geodesic produced faster and smoother movements compared with the others. The "better" performance reflects the dynamical advantages of following the geodesic path and may also reflect invariant features of control policies used to produce such a surface-constrained motion. PMID:24259548
Fast surface-based travel depth estimation algorithm for macromolecule surface shape description.
Giard, Joachim; Alface, Patrice Rondao; Gala, Jean-Luc; Macq, Benoît
2011-01-01
Travel Depth, introduced by Coleman and Sharp in 2006, is a physical interpretation of molecular depth, a term frequently used to describe the shape of a molecular active site or binding site. Travel Depth can be seen as the physical distance a solvent molecule would have to travel from a point of the surface, i.e., the Solvent-Excluded Surface (SES), to its convex hull. Existing algorithms providing an estimation of the Travel Depth are based on a regular sampling of the molecule volume and the use of the Dijkstra's shortest path algorithm. Since Travel Depth is only defined on the molecular surface, this volume-based approach is characterized by a large computational complexity due to the processing of unnecessary samples lying inside or outside the molecule. In this paper, we propose a surface-based approach that restricts the processing to data defined on the SES. This algorithm significantly reduces the complexity of Travel Depth estimation and makes possible the analysis of large macromolecule surface shape description with high resolution. Experimental results show that compared to existing methods, the proposed algorithm achieves accurate estimations with considerably reduced processing times. PMID:21071797
ACO Algorithm for MKP Using Various Heuristic Information
Fidanova, Stefka
to the relative simplicity of the colony's individuals. An important and interesting behavior of ant colonies is their foraging behavior, and in particular, how ants can #12;nd the shortest paths between food sources Libre de Bruxelles, Av. Roosevelt 50 - Bruxelles, Belgium fidanova@ulb.ac.be Abstract. The ant colony
Planning Flight Paths of Autonomous Aerobots
NASA Technical Reports Server (NTRS)
Kulczycki, Eric; Elfes, Alberto; Sharma, Shivanjli
2009-01-01
Algorithms for planning flight paths of autonomous aerobots (robotic blimps) to be deployed in scientific exploration of remote planets are undergoing development. These algorithms are also adaptable to terrestrial applications involving robotic submarines as well as aerobots and other autonomous aircraft used to acquire scientific data or to perform surveying or monitoring functions.
Adaptive path planning for VTOL-UAVs
Oliver Meister; Natalie Frietsch; Christian Ascher; Gert F. Trommer
2009-01-01
This describes the development of path planning algorithms of a small unmanned four-rotor helicopter. A powerful simulation environment of the whole UAV system - including the characteristics of the important ranging sensors for collision avoidance was developed. This is essential for developing, testing, and verifying of the algorithms. Different collision avoidance strategies for VTOL-UAVs are presented. Enhancements and miniaturization will
Mining Preferred Traversal Paths with HITS
NASA Astrophysics Data System (ADS)
Yeh, Jieh-Shan; Lin, Ying-Lin; Chen, Yu-Cheng
Web usage mining can discover useful information hidden in web logs data. However, many previous algorithms do not consider the structure of web pages, but regard all web pages with the same importance. This paper utilizes HITS values and PNT preferences as measures to mine users' preferred traversal paths. Wë structure mining uses HITS (hypertext induced topic selection) to rank web pages. PNT (preferred navigation tree) is an algorithm that finds users' preferred navigation paths. This paper introduces the Preferred Navigation Tree with HITS (PNTH) algorithm, which is an extension of PNT. This algorithm uses the concept of PNT and takes into account the relationships among web pages using HITS algorithm. This algorithm is suitable for E-commerce applications such as improving web site design and web server performance.
Efficient algorithms for wildland fire simulation
NASA Astrophysics Data System (ADS)
Kondratenko, Volodymyr Y.
In this dissertation, we develop the multiple-source shortest path algorithms and examine their application importance in real world problems, such as wildfire modeling. The theoretical basis and its implementation in the Weather Research Forecasting (WRF) model coupled with the fire spread code SFIRE (WRF-SFIRE model) are described. We present a data assimilation method that gives the fire spread model the ability to start the fire simulation from an observed fire perimeter instead of an ignition point. While the model is running, the fire state in the model changes in accordance with the new arriving data by data assimilation. As the fire state changes, the atmospheric state (which is strongly effected by heat flux) does not stay consistent with the fire state. The main difficulty of this methodology occurs in coupled fire-atmosphere models, because once the fire state is modified to match a given starting perimeter, the atmospheric circulation is no longer in sync with it. One of the possible solutions to this problem is a formation of the artificial time of ignition history from an earlier fire state, which is later used to replay the fire progression to the new perimeter with the proper heat fluxes fed into the atmosphere, so that the fire induced circulation is established. In this work, we develop efficient algorithms that start from the fire arrival times given at the set of points (called a perimeter) and create the artificial fire time of ignition and fire spread rate history. Different algorithms were developed in order to suit possible demands of the user, such as implementation in parallel programming, minimization of the required amount of iterations and memory use, and use of the rate of spread as a time dependent variable. For the algorithms that deal with the homogeneous rate of spread, it was proven that the values of fire arrival times they produce are optimal. It was also shown that starting from arbitrary initial state the algorithms have finite convergence and the amount of iterations was estimated. Application of the method on real tests, based on the data taken from the observed fires, has shown the high accuracy of the algorithm and its usefulness. Besides wildfire modeling, this technique has a high application value in different fields, such as epidemiology, demographics control, flood modeling, etc.
Route choices of transport bicyclists: a comparison of actually used and shortest routes
2014-01-01
Background Despite evidence that environmental features are related to physical activity, the association between the built environment and bicycling for transportation remains a poorly investigated subject. The aim of the study was to improve our understanding of the environmental determinants of bicycling as a means of transportation in urban European settings by comparing the spatial differences between the routes actually used by bicyclists and the shortest possible routes. Methods In the present study we examined differences in the currently used and the shortest possible bicycling routes, with respect to distance, type of street, and environmental characteristics, in the city of Graz, Austria. The objective measurement methods of a Global Positioning System (GPS) and a Geographic Information System (GIS) were used. Results Bicycling routes actually used were significantly longer than the shortest possible routes. Furthermore, the following attributes were also significantly different between the used route compared to the shortest possible route: Bicyclists often used bicycle lanes and pathways, flat and green areas, and they rarely used main roads and crossings. Conclusion The results of the study support our hypothesis that bicyclists prefer bicycle pathways and lanes instead of the shortest possible routes. This underlines the importance of a well-developed bicycling infrastructure in urban communities. PMID:24597725
NASA Technical Reports Server (NTRS)
Prabhakaran, Nagarajan; Rishe, Naphtali; Athauda, Rukshan
1997-01-01
The South East coastal region experiences hurricane threat for almost six months in every year. To improve the accuracy of hurricane forecasts, meteorologists would need the storm paths of both the present and the past. A hurricane path can be established if we could identify the correct position of the storm at different times right from its birth to the end. We propose a method based on both spatial and temporal image correlations to locate the position of a storm from satellite images. During the hurricane season, the satellite images of the Atlantic ocean near the equator are examined for the hurricane presence. This is accomplished in two steps. In the first step, only segments with more than a particular value of cloud cover are selected for analysis. Next, we apply image processing algorithms to test the presence of a hurricane eye in the segment. If the eye is found, the coordinate of the eye is recorded along with the time stamp of the segment. If the eye is not found, we examine adjacent segments for the existence of hurricane eye. It is probable that more than one hurricane eye could be found from different segments of the same period. Hence, the above process is repeated till the entire potential area for hurricane birth is exhausted. The subsequent/previous position of each hurricane eye will be searched in the appropriate adjacent segments of the next/previous period to mark the hurricane path. The temporal coherence and spatial coherence of the images are taken into account by our scheme in determining the segments and the associated periods required for analysis.
Zhu, Ping
2013-01-01
The unreliability and dynamics of mobile wireless sensor networks make it hard to perform end-to-end communications. This paper presents a novel source-initiated on-demand routing mechanism for efficient data transmission in mobile wireless sensor networks. It explores the Thorup-Zwick theory to achieve source-initiated on-demand routing with time efficiency. It is able to find out shortest routing path between source and target in a network and transfer data in linear time. The algorithm is easy to be implemented and performed in resource-constrained mobile wireless sensor networks. We also evaluate the approach by analyzing its cost in detail. It can be seen that the approach is efficient to support data transmission in mobile wireless sensor networks. PMID:24453826
Robot navigation in unknown terrains: Introductory survey of non-heuristic algorithms
Rao, N.S.V.; Kareti, S.; Shi, Weimin; Iyengar, S.S.
1993-07-01
A formal framework for navigating a robot in a geometric terrain by an unknown set of obstacles is considered. Here the terrain model is not a priori known, but the robot is equipped with a sensor system (vision or touch) employed for the purpose of navigation. The focus is restricted to the non-heuristic algorithms which can be theoretically shown to be correct within a given framework of models for the robot, terrain and sensor system. These formulations, although abstract and simplified compared to real-life scenarios, provide foundations for practical systems by highlighting the underlying critical issues. First, the authors consider the algorithms that are shown to navigate correctly without much consideration given to the performance parameters such as distance traversed, etc. Second, they consider non-heuristic algorithms that guarantee bounds on the distance traversed or the ratio of the distance traversed to the shortest path length (computed if the terrain model is known). Then they consider the navigation of robots with very limited computational capabilities such as finite automata, etc.
Buldyrev, Sergey
away. For example, in oil recovery the rst passage time from the injection well to a production well:1300:005 2 and dmin 1:13070:0004 3 . There has been an extensive theoretical and computer work done
Almeroth, Kevin C.
between node pairs. After a one- time preprocessing cost, Rigel answers node-distance queries in 10's, Orion, was a centralized system that approximated node distances by mapping nodes to the Euclidean coordinate system [4]. It has several limitations in practice. First, Orion's initial graph embedding process
Kuperstein, Inna; Grieco, Luca; Cohen, David P A; Thieffry, Denis; Zinovyev, Andrei; Barillot, Emmanuel
2015-03-01
Several decades of molecular biology research have delivered a wealth of detailed descriptions of molecular interactions in normal and tumour cells. This knowledge has been functionally organised and assembled into dedicated biological pathway resources that serve as an invaluable tool, not only for structuring the information about molecular interactions but also for making it available for biological, clinical and computational studies. With the advent of high-throughput molecular profiling of tumours, close to complete molecular catalogues of mutations, gene expression and epigenetic modifications are available and require adequate interpretation. Taking into account the information about biological signalling machinery in cells may help to better interpret molecular profiles of tumours. Making sense out of these descriptions requires biological pathway resources for functional interpretation of the data. In this review, we describe the available biological pathway resources, their characteristics in terms of construction mode, focus, aims and paradigms of biological knowledge representation. We present a new resource that is focused on cancer-related signalling, the Atlas of Cancer Signalling Networks. We briefly discuss current approaches for data integration, visualisation and analysis, using biological networks, such as pathway scoring, guilt-by-association and network propagation. Finally, we illustrate with several examples the added value of data interpretation in the context of biological networks and demonstrate that it may help in analysis of high-throughput data like mutation, gene expression or small interfering RNA screening and can guide in patients stratification. Finally, we discuss perspectives for improving precision medicine using biological network resources and tools. Taking into account the information about biological signalling machinery in cells may help to better interpret molecular patterns of tumours and enable to put precision oncology into general clinical practice. PMID:25688112
Zhang, Hongwei
" with intermediate speed, and "super-containment wave" with the highest speed. The containment wave contains a different propagation speed, i.e., "stabilization wave" with the lowest speed, "containment wave the mistakenly initiated stabilization wave, the super-containment wave contains the mistakenly initiated
Roughan, Matthew
in providing realistic network scenarios for other researchers. The Rocketfuel project attempted this process to assess the quality of the weight inference. We used this to test Rocketfuel's algo- rithm, and our tests in properties of large networks (or graphs). The Rocketfuel project [1, 2] suggested techniques for "reverse
Computational path planner for product assembly in complex environments
NASA Astrophysics Data System (ADS)
Shang, Wei; Liu, Jianhua; Ning, Ruxin; Liu, Mi
2013-03-01
Assembly path planning is a crucial problem in assembly related design and manufacturing processes. Sampling based motion planning algorithms are used for computational assembly path planning. However, the performance of such algorithms may degrade much in environments with complex product structure, narrow passages or other challenging scenarios. A computational path planner for automatic assembly path planning in complex 3D environments is presented. The global planning process is divided into three phases based on the environment and specific algorithms are proposed and utilized in each phase to solve the challenging issues. A novel ray test based stochastic collision detection method is proposed to evaluate the intersection between two polyhedral objects. This method avoids fake collisions in conventional methods and degrades the geometric constraint when a part has to be removed with surface contact with other parts. A refined history based rapidly-exploring random tree (RRT) algorithm which bias the growth of the tree based on its planning history is proposed and employed in the planning phase where the path is simple but the space is highly constrained. A novel adaptive RRT algorithm is developed for the path planning problem with challenging scenarios and uncertain environment. With extending values assigned on each tree node and extending schemes applied, the tree can adapts its growth to explore complex environments more efficiently. Experiments on the key algorithms are carried out and comparisons are made between the conventional path planning algorithms and the presented ones. The comparing results show that based on the proposed algorithms, the path planner can compute assembly path in challenging complex environments more efficiently and with higher success. This research provides the references to the study of computational assembly path planning under complex environments.
Definition of average path and relativity parameter computation in CASA
NASA Astrophysics Data System (ADS)
Wu, Dawei; Huang, Yan; Chen, Xiaohua; Yu, Chang
2001-09-01
System CASA (computer-assisted semen analysis) is a medical applicable system which gets the sperm motility and its parameters using image processing method. But there is no any authoritative administration or academic organization gives a set of criterion for CASA now result in lowering the effective compare of work between the labs or researchers. The average path and parameters relative to it as average path velocity, amplitude of lateral head displacement and beat cross frequency are often unable to compare between systems because of different algorithm. The paper presents a new algorithm that could define the average path uniquely and compute those 3 parameters above quickly and handy from any real path.
Path connectivity based spectral defragmentation in flexible bandwidth networks.
Wang, Ying; Zhang, Jie; Zhao, Yongli; Zhang, Jiawei; Zhao, Jie; Wang, Xinbo; Gu, Wanyi
2013-01-28
Optical networks with flexible bandwidth provisioning have become a very promising networking architecture. It enables efficient resource utilization and supports heterogeneous bandwidth demands. In this paper, two novel spectrum defragmentation approaches, i.e. Maximum Path Connectivity (MPC) algorithm and Path Connectivity Triggering (PCT) algorithm, are proposed based on the notion of Path Connectivity, which is defined to represent the maximum variation of node switching ability along the path in flexible bandwidth networks. A cost-performance-ratio based profitability model is given to denote the prons and cons of spectrum defragmentation. We compare these two proposed algorithms with non-defragmentation algorithm in terms of blocking probability. Then we analyze the differences of defragmentation profitability between MPC and PCT algorithms. PMID:23389118
THE LENGTH OF THE SHORTEST CLOSED GEODESIC ON A 2 -DIMENSIONAL SPHERE
Nabutovsky, Alexander
by C. Croke [2] and Maeda [4]. 1. Introduction The connection between the length of a shortest closed connected manifold are the results of Croke [2] and Maeda [4]. Croke proved that if a Riemannian manifold M; 9d . The last in- equality was later improved by Maeda who demonstrated that l(M) #20; 5d if M is di
On the Evaluation of Shortest Journeys in Dynamic Networks Afonso Ferreira
Bermond, Jean-Claude
On the Evaluation of Shortest Journeys in Dynamic Networks Afonso Ferreira CNRS - MASCOTTE Project Department of Computer Science, University of Sao Paulo, Brazil {gold,jm}@ime.usp.br Abstract The assessment industry and are widely available in our every day life. A promising type of these networks is the Mobile
Finding Shortest Non-Trivial Cycles in Directed Graphs on Surfaces
Colin de Verdière, Éric
Finding Shortest Non-Trivial Cycles in Directed Graphs on Surfaces Sergio Cabello Department of Mathematics, IMFM Department of Mathematics, FMF University of Ljubljana, Slovenia sergio.cabello or hard copies of all or part of this work for personal or classroom use is granted without fee provided
Show me the (shortest) way to go home Foams, soap films and minimization
Cox, Simon
Simon Cox Show me the (shortest) way to go home Foams, soap films and minimization #12;The force two possible (non-trivial) soap film combinations that touch all edges: Wire Frames foams not be straight. Wire Frames foams@aber.ac.uk #12;Soap films solve the Steiner problem: Given n cities on a plain
Finding shortest and closest vectors in a lattice of Voronoi's first kind
Finding shortest and closest vectors in a lattice of Voronoi's first kind Robby McKilliam Alex;Lattices Lattices of Voronoi's first kind Graphs, cuts, and minimum cuts A series of relevant vectors What will show that the problem is relatively easy to solve for lattices of Voronoi's first kind. 8 / 46 #12;The
Path Planning Algorithms for Multiple Heterogeneous Vehicles
Oberlin, Paul V.
2010-01-16
as the \\Precedence Constrained Asymmetric Travelling Salesman Problem" (PCATSP). v ACKNOWLEDGMENTS Special thanks to the Air Force Research Laboratory (AFRL) Air Vehicles Direc- torate for providing funding and motivation for portions of this thesis, Waqar Malik...
Gathering Algorithms on Paths under Interference Constraints
Paris-Sud XI, Université de
joseph.yu@ucfv.ca Abstract. We study the problem of gathering information from the nodes of a multi supported by the Conselho Nacional de Desenvolvimento Cient´ifico e Tec- nol´ogico, CNPq, Brazil. Partially of information into a special node t, called the gathering node. In this paper, we propose solutions
Path optimization for oil probe
NASA Astrophysics Data System (ADS)
Smith, O'Neil; Rahmes, Mark; Blue, Mark; Peter, Adrian
2014-05-01
We discuss a robust method for optimal oil probe path planning inspired by medical imaging. Horizontal wells require three-dimensional steering made possible by the rotary steerable capabilities of the system, which allows the hole to intersect multiple target shale gas zones. Horizontal "legs" can be over a mile long; the longer the exposure length, the more oil and natural gas is drained and the faster it can flow. More oil and natural gas can be produced with fewer wells and less surface disturbance. Horizontal drilling can help producers tap oil and natural gas deposits under surface areas where a vertical well cannot be drilled, such as under developed or environmentally sensitive areas. Drilling creates well paths which have multiple twists and turns to try to hit multiple accumulations from a single well location. Our algorithm can be used to augment current state of the art methods. Our goal is to obtain a 3D path with nodes describing the optimal route to the destination. This algorithm works with BIG data and saves cost in planning for probe insertion. Our solution may be able to help increase the energy extracted vs. input energy.
Evaluation of concurrent priority queue algorithms. Technical report
Huang, Q.
1991-02-01
The priority queue is a fundamental data structure that is used in a large variety of parallel algorithms, such as multiprocessor scheduling and parallel best-first search of state-space graphs. This thesis addresses the design and experimental evaluation of two novel concurrent priority queues: a parallel Fibonacci heap and a concurrent priority pool, and compares them with the concurrent binary heap. The parallel Fibonacci heap is based on the sequential Fibonacci heap, which is theoretically the most efficient data structure for sequential priority queues. This scheme not only preserves the efficient operation time bounds of its sequential counterpart, but also has very low contention by distributing locks over the entire data structure. The experimental results show its linearly scalable throughput and speedup up to as many processors as tested (currently 18). A concurrent access scheme for a doubly linked list is described as part of the implementation of the parallel Fibonacci heap. The concurrent priority pool is based on the concurrent B-tree and the concurrent pool. The concurrent priority pool has the highest throughput among the priority queues studied. Like the parallel Fibonacci heap, the concurrent priority pool scales linearly up to as many processors as tested. The priority queues are evaluated in terms of throughput and speedup. Some applications of concurrent priority queues such as the vertex cover problem and the single source shortest path problem are tested.
Adaptive path planning for flexible manufacturing
Chen, Pang C.
1994-08-01
Path planning needs to be fast to facilitate real-time robot programming. Unfortunately, current planning techniques are still too slow to be effective, as they often require several minutes, if not hours of computation. To overcome this difficulty, we present an adaptive algorithm that uses past experience to speed up future performance. It is a learning algorithm suitable for automating flexible manufacturing in incrementally-changing environments. The algorithm allows the robot to adapt to its environment by having two experience manipulation schemes: For minor environmental change, we use an object-attached experience abstraction scheme to increase the flexibility of the learned experience; for major environmental change, we use an on-demand experience repair scheme to retain those experiences that remain valid and useful. Using this algorithm, we can effectively reduce the overall robot planning time by re-using the computation result for one task to plan a path for another.
Metabolic Flux-Based Modularity using Shortest Retroactive distances
2012-01-01
Background Graph-based modularity analysis has emerged as an important tool to study the functional organization of biological networks. However, few methods are available to study state-dependent changes in network modularity using biological activity data. We develop a weighting scheme, based on metabolic flux data, to adjust the interaction distances in a reaction-centric graph model of a metabolic network. The weighting scheme was combined with a hierarchical module assignment algorithm featuring the preservation of metabolic cycles to examine the effects of cellular differentiation and enzyme inhibitions on the functional organization of adipocyte metabolism. Results Our analysis found that the differences between various metabolic states primarily involved the assignment of two specific reactions in fatty acid synthesis and glycerogenesis. Our analysis also identified cyclical interactions between reactions that are robust with respect to metabolic state, suggesting possible co-regulation. Comparisons based on cyclical interaction distances between reaction pairs suggest that the modular organization of adipocyte metabolism is stable with respect to the inhibition of an enzyme, whereas a major physiological change such as cellular differentiation leads to a more substantial reorganization. Conclusion Taken together, our results support the notion that network modularity is influenced by both the connectivity of the network’s components as well as the relative engagements of the connections. PMID:23270532
Efficient fair algorithms for message communication Sergey Gorinsky a,*, Eric J. Friedman b
Gorinsky, Sergey
Strasse 1, 85622 Munich, Germany a r t i c l e i n f o Article history: Available online 9 September 2008 algorithms called Pessimistic Fair Sojourn Protocol (PFSP), Optimistic Fair Sojourn Protocol (OFSP), and Shortest Fair Sojourn (SFS). Then, we prove that a fair online algorithm does not assure minimal average
Hop-by-Hop Routing Algorithms For Premium Traffic Department of Computer Science
Nahrstedt, Klara
Hop-by-Hop Routing Algorithms For Premium Traffic Jun Wang Department of Computer Science@cs.uiuc.edu ABSTRACT In Differentiated Service (DiffServ) networks, the routing algorithms used by the premium class on the premium class traffic itself, but on all other classes of traffic as well. The shortest hop-count routing
Asymptotically optimal path planning and surface reconstruction for inspection
Papadopoulos, Georgios
2014-01-01
Motivated by inspection applications for marine structures, this thesis develops algorithms to enable their autonomous inspection. Two essential parts of the inspection problem are (1) path planning and (2) surface ...
Path dependent receding horizon control policies for hybrid electric vehicles
Kolmanovsky, Ilya V.
Future hybrid electric vehicles (HEVs) may use path-dependent operating policies to improve fuel economy. In our previous work, we developed a dynamic programming (DP) algorithm for prescribing the battery state of charge ...
Efficient Data Mining for Path Traversal Patterns
Ming-syan Chen; Jong Soo Park; Philip S. Yu
1998-01-01
In this paper, we explore a new data mining capability that involves mining path traversal patterns in a distributed information-providing environment where documents or objects are linked together to facilitate interactive access. Our solution procedure consists of two steps. First, we derive an algorithm to convert the original sequence of log data into a set of maximal forward references. By
Staff detection with stable paths.
Dos Santos Cardoso, Jaime; Capela, Artur; Rebelo, Ana; Guedes, Carlos; Pinto da Costa, Joaquim
2009-06-01
The preservation of musical works produced in the past requires their digitalization and transformation into a machine-readable format. The processing of handwritten musical scores by computers remains far from ideal. One of the fundamental stages to carry out this task is the staff line detection. We investigate a general-purpose, knowledge-free method for the automatic detection of music staff lines based on a stable path approach. Lines affected by curvature, discontinuities, and inclination are robustly detected. Experimental results show that the proposed technique consistently outperforms well-established algorithms. PMID:19372615
Reconfigurable data path processor
NASA Technical Reports Server (NTRS)
Donohoe, Gregory (Inventor)
2005-01-01
A reconfigurable data path processor comprises a plurality of independent processing elements. Each of the processing elements advantageously comprising an identical architecture. Each processing element comprises a plurality of data processing means for generating a potential output. Each processor is also capable of through-putting an input as a potential output with little or no processing. Each processing element comprises a conditional multiplexer having a first conditional multiplexer input, a second conditional multiplexer input and a conditional multiplexer output. A first potential output value is transmitted to the first conditional multiplexer input, and a second potential output value is transmitted to the second conditional multiplexer output. The conditional multiplexer couples either the first conditional multiplexer input or the second conditional multiplexer input to the conditional multiplexer output, according to an output control command. The output control command is generated by processing a set of arithmetic status-bits through a logical mask. The conditional multiplexer output is coupled to a first processing element output. A first set of arithmetic bits are generated according to the processing of the first processable value. A second set of arithmetic bits may be generated from a second processing operation. The selection of the arithmetic status-bits is performed by an arithmetic-status bit multiplexer selects the desired set of arithmetic status bits from among the first and second set of arithmetic status bits. The conditional multiplexer evaluates the select arithmetic status bits according to logical mask defining an algorithm for evaluating the arithmetic status bits.
Model Checking Restricted Sets of Timed Paths Nicolas Markey a
Doyen, Laurent
. When the verification of a safety or a linear- time property fails, those symbolic algorithms identifyModel Checking Restricted Sets of Timed Paths Nicolas Markey a Jean-FranÃ§ois Raskin b aLab is the symbolic representation of an infinite set of timed paths that are counter-examples to the property
Path Profile Guided Partial Dead Code Elimination Using Predication \\Lambda
Gupta, Rajiv
Path Profile Guided Partial Dead Code Elimination Using Predication \\Lambda Rajiv Gupta y David A Corporation Pittsburgh, PA 15260 Santa Clara, CA 95052 Abstract We present a path profile guided partial dead code elimination algorithm that uses predication to enable sinking for the removal of deadness along
Path planning by querying persistent stores of trajectory segments
Grossman, Robert
September, 1992 Laboratory for Advanced Computing Technical Report Number LAC 93-R3, University of IllinoisPath planning by querying persistent stores of trajectory segments R. L. Grossman S. Mehta X. Qin at Chicago, September, 1992. Introduction. In this paper, we introduce an algorithm for path planning (long
MinimumCost Spanning Tree PathFinding Problem
Maggs, Bruce M.
MinimumCost Spanning Tree as a PathFinding Problem Bruce M. Maggs Serge A. Plotkin Laboratorycost spanning tree is a special case of the closed semiring pathfinding problem. This observation gives us a nonrecursive algorithm for finding minimum cost spanning trees on meshconnected computers that has
A Decentralized Model for Virtual Path Capacity Allocation
Konstantopoulos, Takis
in an ATM network. function, and investigated the equilibrium point and converging algorithms. In [41 A Decentralized Model for Virtual Path Capacity Allocation SEUNG H. RHEE and TAKIS,takis¡ @alea.ece.utexas.edu Abstract--We investigate the problem of Virtual Path (VP) capacity al- location
Walden's Paths - Ensemble Edition
NSDL National Science Digital Library
2011-01-04
Walden?s Paths enables users of digital document collections (e.g. the Web) to exploit these documents by reusing them for previously unintended audiences in an academic setting. Authors of paths (usually educators) overlay a linear, directed meta-structure over the Web documents and recontextualize these by adding explanatory text to achieve their curricular goals. Paths do not modifythe structure or content of the Web resources that they include. The creation of a path over pre-organized content (e.g. books, Web pages) to reorganize and associate related information serves to facilitate easy retrieval and communication. Walden?s Paths displays the information that the path points to in conjunction with the textual annotations added by the author of the path.
Vulnerability of complex networks under path-based attacks
NASA Astrophysics Data System (ADS)
Pu, Cun-Lai; Cui, Wei
2015-02-01
We investigate vulnerability of complex networks including model networks and real-world networks subject to path-based attacks. Specifically, we remove approximately the longest simple path from a network iteratively until there are no paths left in the network. We propose two algorithms, the random augmenting approach (RPA) and the Hamilton-path based approach (HPA), for finding the approximately longest simple path in a network. Results demonstrate that steps of longest-path attacks increase with network density linearly for random networks, while exponentially increasing for scale-free networks. The more homogeneous the degree distribution is, the more fragile the network, which is different from the previous results of node or edge attacks. HPA is generally more efficient than RPA in the longest-path attacks of complex networks. These findings further help us understand the vulnerability of complex systems, better protect complex systems, and design more tolerant complex systems.
Christian Fleischhack
2015-03-21
The symmetries of paths in a manifold $M$ are classified with respect to a given pointwise proper action of a Lie group $G$ on $M$. Here, paths are embeddings of a compact interval into $M$. There are at least two types of symmetries: Firstly, paths that are parts of an integral curve of a fundamental vector field on $M$ (continuous symmetry). Secondly, paths that can be decomposed into finitely many pieces, each of which is the translate of some free segment, where possibly the translate is cut at the two ends of the paths (discrete symmetry). Here, a free segment is a path $e$ whose $G$-translates either equal $e$ or intersect it in at most finitely many points. Note that all the statements above are understood up to the parametrization of the paths. We will show, for the category of analytic manifolds, that each path is of exactly one of either types. For the proof, we use that the overlap of a path $\\gamma$ with one of its translates is encoded uniquely in a mapping between subsets of $\\dom\\gamma$. Running over all translates, these mappings form the so-called reparametrization set to $\\gamma$. It will turn out that, up to conjugation with a diffeomorphism, any such set is given by the action of a Lie subgroup of $O(2)$ on $S^1$, restricted in domain and range to some compact interval on $S^1$. Now, the infinite subgroups correspond to the continuous symmetry above, finite ones to the discrete symmetry.
Path Integrals and Hamiltonians
NASA Astrophysics Data System (ADS)
Baaquie, Belal E.
2014-03-01
1. Synopsis; Part I. Fundamental Principles: 2. The mathematical structure of quantum mechanics; 3. Operators; 4. The Feynman path integral; 5. Hamiltonian mechanics; 6. Path integral quantization; Part II. Stochastic Processes: 7. Stochastic systems; Part III. Discrete Degrees of Freedom: 8. Ising model; 9. Ising model: magnetic field; 10. Fermions; Part IV. Quadratic Path Integrals: 11. Simple harmonic oscillators; 12. Gaussian path integrals; Part V. Action with Acceleration: 13. Acceleration Lagrangian; 14. Pseudo-Hermitian Euclidean Hamiltonian; 15. Non-Hermitian Hamiltonian: Jordan blocks; 16. The quartic potential: instantons; 17. Compact degrees of freedom; Index.
Path Factorization Approach to Stochastic Simulations
NASA Astrophysics Data System (ADS)
Athènes, Manuel; Bulatov, Vasily V.
2014-12-01
The computational efficiency of stochastic simulation algorithms is notoriously limited by the kinetic trapping of the simulated trajectories within low energy basins. Here we present a new method that overcomes kinetic trapping while still preserving exact statistics of escape paths from the trapping basins. The method is based on path factorization of the evolution operator and requires no prior knowledge of the underlying energy landscape. The efficiency of the new method is demonstrated in simulations of anomalous diffusion and phase separation in a binary alloy, two stochastic models presenting severe kinetic trapping.
PathFinder: a negotiation-based performance-driven router for FPGAs
Larry McMurchie; Carl Ebeling
1995-01-01
Routing FPGAs is a challenging problem because of the relative scarcity of routing resources, both wires and connection points. This can lead either to slow implementations caused by long wiring paths that avoid congestion or a failure to route all signals. This paper presents PathFinder, a router that balances the goals of performance and routability. PathFinder uses an iterative algorithm
A Hybrid Fault-Tolerant Algorithm for MPLS Networks
Pitsillides, Andreas
A Hybrid Fault-Tolerant Algorithm for MPLS Networks Maria Hadjiona, Chryssis Georgiou, Maria Papa, path maintaining, algorithm for use in MPLS based networks. The novelty of the algorithm lies upon the fact that it is the first to employ both path restoration mechanisms typically used in MPLS networks
Shape Analysis as a Generalized Path Problem Thomas Reps
Reps, Thomas W.
, Madison, WI 53706. Telephone: (608) 262-1204. Electronic mail: reps@cs.wisc.edu. tions of selection to connect two vertices only if the con- catenation of the labels on the edges of the path is a word on the run- ning time of an algorithm for shape analysis. It also per- mits us to obtain a demand algorithm
Path Planning, Replanning, and Execution for Autonomous Driving in Urban and Offroad Environments
Roland Philippsen; Sascha Kolski; Kristijan Macek; Roland Siegwart
2007-01-01
We present an autonomous driving system that is capable of planning, replanning, and executing paths for driving in urban and offroad environments. For planning, we rely on the E algorithm which computes a smooth navigation function that takes into account traversibility information extracted from laser scans. The path execution algorithm is centered around a kinodynamic controller which follows the gradient
Hierarchical Fuzzy Cooperative Control and Path Following for a Team of Mobile Robots
Hasan Mehrjerdi; Maarouf Saad; Jawhar Ghommam
2011-01-01
In this paper, an intelligent cooperative control and path-following algorithm is proposed and tested for a group of mo- bile robots. The core of this algorithm uses a fuzzy model, which mimics human thought to control the robot's velocity, movement, and group behavior. The designed fuzzy model employs two be- haviors: path following and group cooperation. Hierarchical con- trollers have
Longest jobs first algorithm in solving job shop scheduling using adaptive genetic algorithm (GA)
NASA Astrophysics Data System (ADS)
Alizadeh Sahzabi, Vahid; Karimi, Iman; Alizadeh Sahzabi, Navid; Mamaani Barnaghi, Peiman
2012-01-01
In this paper, genetic algorithm was used to solve job shop scheduling problems. One example discussed in JSSP (Job Shop Scheduling Problem) and I described how we can solve such these problems by genetic algorithm. The goal in JSSP is to gain the shortest process time. Furthermore I proposed a method to obtain best performance on performing all jobs in shortest time. The method mainly, is according to Genetic algorithm (GA) and crossing over between parents always follows the rule which the longest process is at the first in the job queue. In the other word chromosomes is suggested to sorts based on the longest processes to shortest i.e. "longest job first" says firstly look which machine contains most processing time during its performing all its jobs and that is the bottleneck. Secondly, start sort those jobs which are belonging to that specific machine descending. Based on the achieved results," longest jobs first" is the optimized status in job shop scheduling problems. In our results the accuracy would grow up to 94.7% for total processing time and the method improved 4% the accuracy of performing all jobs in the presented example.
Longest jobs first algorithm in solving job shop scheduling using adaptive genetic algorithm (GA)
NASA Astrophysics Data System (ADS)
Alizadeh Sahzabi, Vahid; Karimi, Iman; Alizadeh Sahzabi, Navid; Mamaani Barnaghi, Peiman
2011-12-01
In this paper, genetic algorithm was used to solve job shop scheduling problems. One example discussed in JSSP (Job Shop Scheduling Problem) and I described how we can solve such these problems by genetic algorithm. The goal in JSSP is to gain the shortest process time. Furthermore I proposed a method to obtain best performance on performing all jobs in shortest time. The method mainly, is according to Genetic algorithm (GA) and crossing over between parents always follows the rule which the longest process is at the first in the job queue. In the other word chromosomes is suggested to sorts based on the longest processes to shortest i.e. "longest job first" says firstly look which machine contains most processing time during its performing all its jobs and that is the bottleneck. Secondly, start sort those jobs which are belonging to that specific machine descending. Based on the achieved results," longest jobs first" is the optimized status in job shop scheduling problems. In our results the accuracy would grow up to 94.7% for total processing time and the method improved 4% the accuracy of performing all jobs in the presented example.
Enzymatic reaction paths as determined by transition path sampling
NASA Astrophysics Data System (ADS)
Masterson, Jean Emily
Enzymes are biological catalysts capable of enhancing the rates of chemical reactions by many orders of magnitude as compared to solution chemistry. Since the catalytic power of enzymes routinely exceeds that of the best artificial catalysts available, there is much interest in understanding the complete nature of chemical barrier crossing in enzymatic reactions. Two specific questions pertaining to the source of enzymatic rate enhancements are investigated in this work. The first is the issue of how fast protein motions of an enzyme contribute to chemical barrier crossing. Our group has previously identified sub-picosecond protein motions, termed promoting vibrations (PVs), that dynamically modulate chemical transformation in several enzymes. In the case of human heart lactate dehydrogenase (hhLDH), prior studies have shown that a specific axis of residues undergoes a compressional fluctuation towards the active site, decreasing a hydride and a proton donor--acceptor distance on a sub-picosecond timescale to promote particle transfer. To more thoroughly understand the contribution of this dynamic motion to the enzymatic reaction coordinate of hhLDH, we conducted transition path sampling (TPS) using four versions of the enzymatic system: a wild type enzyme with natural isotopic abundance; a heavy enzyme where all the carbons, nitrogens, and non-exchangeable hydrogens were replaced with heavy isotopes; and two versions of the enzyme with mutations in the axis of PV residues. We generated four separate ensembles of reaction paths and analyzed each in terms of the reaction mechanism, time of barrier crossing, dynamics of the PV, and residues involved in the enzymatic reaction coordinate. We found that heavy isotopic substitution of hhLDH altered the sub-picosecond dynamics of the PV, changed the favored reaction mechanism, dramatically increased the time of barrier crossing, but did not have an effect on the specific residues involved in the PV. In the mutant systems, we observed changes in the reaction mechanism and altered contributions of the mutated residues to the enzymatic reaction coordinate, but we did not detect a substantial change in the time of barrier crossing. These results confirm the importance of maintaining the dynamics and structural scaffolding of the hhLDH PV in order to facilitate facile barrier passage. We also utilized TPS to investigate the possible role of fast protein dynamics in the enzymatic reaction coordinate of human dihydrofolate reductase (hsDHFR). We found that sub-picosecond dynamics of hsDHFR do contribute to the reaction coordinate, whereas this is not the case in the E. coli version of the enzyme. This result indicates a shift in the DHFR family to a more dynamic version of catalysis. The second inquiry we addressed in this thesis regarding enzymatic barrier passage concerns the variability of paths through reactive phase space for a given enzymatic reaction. We further investigated the hhLDH-catalyzed reaction using a high-perturbation TPS algorithm. Though we saw that alternate reaction paths were possible, the dominant reaction path we observed corresponded to that previously elucidated in prior hhLDH TPS studies. Since the additional reaction paths we observed were likely high-energy, these results indicate that only the dominant reaction path contributes significantly to the overall reaction rate. In conclusion, we show that the enzymes hhLDH and hsDHFR exhibit paths through reactive phase space where fast protein motions are involved in the enzymatic reaction coordinate and exhibit a non-negligible contribution to chemical barrier crossing.
NSDL National Science Digital Library
Australian National University
This site features an interactive applet that models the Sun's path from a geocentric view. It calculates and visualizes the position of the Sun based on latitude and time, and allows students to simulate the Sun's position and path for an hour, a day, a month or a year.
Calix[4]pyrroles with Shortest Possible Strap: Exclusively Selective toward Fluoride Ion.
Samanta, Ritwik; Kumar, B Sathish; Panda, Pradeepta K
2015-09-01
Four new calix[4]pyrroles with the shortest possible strap so far through ortho-linking of the aromatic unit have been synthesized, including a naphthalene-derived fluorescent receptor. They show exclusive selectivity toward the fluoride ion as confirmed by (1)H NMR, isothermal titration calorimetry, and fluorescence spectroscopic study. Anion affinity could also be modulated further via functionalization at the strap. Computational analysis displays calix[4]pyrroles binding to fluoride ion in a very unusual 1,3-alternate conformation where the anion resides on the opposite side of the strap. PMID:26313641
Spin up in RX J0806+15 - the shortest period binary
Hakala, P; Wu, K; Hjalmarsdotter, L; Järvinen, S; Järvinen, A; Cropper, M; Hakala, Pasi; Ramsay, Gavin; Wu, Kinwah; Hjalmarsdotter, Linnea; Jarvinen, Silva; Jarvinen, Arto; Cropper, Mark
2003-01-01
RX J0806+15 has recently been identified as the binary system with the shortest known orbital period. We present a series of observations of RX J0806+15 including new optical observations taken one month apart. Using these observations and archival data we find that the period of this system is decreasing over time. Our measurements imply f_dot = 6.11x10^-16 Hz/s, which is in agreement with a rate expected from the gravitational radiation for two white dwarfs orbiting at a given period. However, a smaller value of f_dot = 3.14x10^-16 Hz/s cannot be ruled out. Our result supports the idea that the 321.5 s period is the orbital period and that the system is the shortest period binary known so far and that it is one of the strongest sources of constant gravitational radiation in the sky. Furthermore, the decrease of the period strongly favours the unipolar inductor (or electric star) model rather than the accretion models.
Spin up in RX J0806+15 - the shortest period binary
Pasi Hakala; Gavin Ramsay; Kinwah Wu; Linnea Hjalmarsdotter; Silva Jarvinen; Arto Jarvinen; Mark Cropper
2003-05-15
RX J0806+15 has recently been identified as the binary system with the shortest known orbital period. We present a series of observations of RX J0806+15 including new optical observations taken one month apart. Using these observations and archival data we find that the period of this system is decreasing over time. Our measurements imply f_dot = 6.11x10^-16 Hz/s, which is in agreement with a rate expected from the gravitational radiation for two white dwarfs orbiting at a given period. However, a smaller value of f_dot = 3.14x10^-16 Hz/s cannot be ruled out. Our result supports the idea that the 321.5 s period is the orbital period and that the system is the shortest period binary known so far and that it is one of the strongest sources of constant gravitational radiation in the sky. Furthermore, the decrease of the period strongly favours the unipolar inductor (or electric star) model rather than the accretion models.
Adaptive path planning for VTOL-UAVs
O. Meister; N. Frietsch; Ch. Ascher; G. F. Trommer
2010-01-01
This paper addresses the development of an adaptive path planning algorithm for a small vertical take-off and landing (VTOL)\\u000a unmanned aerial vehicle (UAV) with a take off weight below 1 kg. The UAV was developed for versatile surveillance and reconnaissance\\u000a applications in close-up range up to 10 km. The UAV platform with the onboard navigation system is described. Improvements\\u000a of
Some Materials for Discrete Mathematics
NSDL National Science Digital Library
Lady, E. Lee
Files in PDF, DVI, and Postscript format. Contents include: an algorithm for solving linear Diophantine equations, the Chinese remainder theorem, mathematical induction and recursive algorithms, Change of base to Cantor representation, Dijkstra's algorithm for shortest path, and amortization.
Image-based path planning for automated virtual colonoscopy navigation
NASA Astrophysics Data System (ADS)
Hong, Wei
2008-03-01
Virtual colonoscopy (VC) is a noninvasive method for colonic polyp screening, by reconstructing three-dimensional models of the colon using computerized tomography (CT). In virtual colonoscopy fly-through navigation, it is crucial to generate an optimal camera path for efficient clinical examination. In conventional methods, the centerline of the colon lumen is usually used as the camera path. In order to extract colon centerline, some time consuming pre-processing algorithms must be performed before the fly-through navigation, such as colon segmentation, distance transformation, or topological thinning. In this paper, we present an efficient image-based path planning algorithm for automated virtual colonoscopy fly-through navigation without the requirement of any pre-processing. Our algorithm only needs the physician to provide a seed point as the starting camera position using 2D axial CT images. A wide angle fisheye camera model is used to generate a depth image from the current camera position. Two types of navigational landmarks, safe regions and target regions are extracted from the depth images. Camera position and its corresponding view direction are then determined using these landmarks. The experimental results show that the generated paths are accurate and increase the user comfort during the fly-through navigation. Moreover, because of the efficiency of our path planning algorithm and rendering algorithm, our VC fly-through navigation system can still guarantee 30 FPS.
ERIC Educational Resources Information Center
Stegemoller, William; Stegemoller, Rebecca
2004-01-01
The path taken and the turns made as a turtle traces a polygon are examined to discover an important theorem in geometry. A unique tool, the Angle Adder, is implemented in the investigation. (Contains 9 figures.)
Tortuous path chemical preconcentrator
Manginell, Ronald P. (Albuquerque, NM); Lewis, Patrick R. (Albuquerque, NM); Adkins, Douglas R. (Albuquerque, NM); Wheeler, David R. (Albuquerque, NM); Simonson, Robert J. (Cedar Crest, NM)
2010-09-21
A non-planar, tortuous path chemical preconcentrator has a high internal surface area having a heatable sorptive coating that can be used to selectively collect and concentrate one or more chemical species of interest from a fluid stream that can be rapidly released as a concentrated plug into an analytical or microanalytical chain for separation and detection. The non-planar chemical preconcentrator comprises a sorptive support structure having a tortuous flow path. The tortuosity provides repeated twists, turns, and bends to the flow, thereby increasing the interfacial contact between sample fluid stream and the sorptive material. The tortuous path also provides more opportunities for desorption and readsorption of volatile species. Further, the thermal efficiency of the tortuous path chemical preconcentrator is comparable or superior to the prior non-planar chemical preconcentrator. Finally, the tortuosity can be varied in different directions to optimize flow rates during the adsorption and desorption phases of operation of the preconcentrator.
NSDL National Science Digital Library
In this lesson, younger students will be introduced to the various orbital paths that are used for satellites. Using a globe and a satellite model or a large picture of Earth, the teacher will introduce three types of orbital paths (polar, elliptical, and geosynchronous). The students should be able to define 'satellite', define the three types of orbits, describe how satellites orbit the Earth, and understand how they are slowed down by drag from the atmosphere.
A 2D analytical cylindrical gate tunnel FET (CG-TFET) model: impact of shortest tunneling distance
NASA Astrophysics Data System (ADS)
Dash, S.; Mishra, G. P.
2015-09-01
A 2D analytical tunnel field-effect transistor (FET) potential model with cylindrical gate (CG-TFET) based on the solution of Laplace’s equation is proposed. The band-to-band tunneling (BTBT) current is derived by the help of lateral electric field and the shortest tunneling distance. However, the analysis is extended to obtain the subthreshold swing (SS) and transfer characteristics of the device. The dependency of drain current, SS and transconductance on gate voltage and shortest tunneling distance is discussed. Also, the effect of scaling the gate oxide thickness and the cylindrical body diameter on the electrical parameters of the device is analyzed.
NASA Astrophysics Data System (ADS)
Matvienko, G. G.; Oshlakov, V. K.; Stepanov, A. N.; Sukhanov, A. Ya
2015-02-01
We consider the algorithms that implement a broadband ('multiwave') radiative transfer with allowance for multiple (aerosol) scattering and absorption by main atmospheric gases. In the spectral range of 0.6 – 1 ?m, a closed numerical simulation of modifications of the supercontinuum component of a probing femtosecond pulse is performed. In the framework of the algorithms for solving the inverse atmospheric-optics problems with the help of a genetic algorithm, we give an interpretation of the experimental backscattered spectrum of the supercontinuum. An adequate reconstruction of the distribution mode for the particles of artificial aerosol with the narrow-modal distributions in a size range of 0.5 – 2 mm and a step of 0.5 mm is obtained.
Monochromatic paths and path squares in infinite graphs
Mildenberger, Heike
Monochromatic paths and path squares in infinite graphs Lajos Soukup AlfrÃ©d RÃ©nyi Institute disjoint monochromatic paths with different colours which cover all vertices of K. #12;The beginning complete graph K is coloured with r colors. Then there are r disjoint monochromatic paths with different
Multipath Binomial Congestion Control Algorithms
NASA Astrophysics Data System (ADS)
Le, Tuan Anh; Hong, Choong Seon; Lee, Sungwon
Nowadays portable devices with multiple wireless interfaces and using multimedia services are becoming more popular on the Internet. This paper describes a family of multipath binomial congestion control algorithms for audio/video streaming, where a low variant of transmission rate is important. We extend the fluid model of binomial algorithms for single-path transmission to support the concurrent transmission of packets across multiple paths. We focus on the extension of two particular algorithms, SQRT and IIAD, for multiple paths, called MPSQRT and MPIIAD, respectively. Additionally, we apply the design technique (using the multipath fluid model) for multipath TCP (MPTCP) into the extension of SQRT and IIAD, called fbMPSQRT and fbMPIIAD, respectively. Both two approaches ensure that multipath binomial congestion control algorithms achieve load-balancing, throughput improvement, and fairness to single-path binomial algorithms at shared bottlenecks. Through the simulations and comparison with the uncoordinated protocols MPSQRT/MPIIAD, fbMPSQRT/fbMPIIAD and MPTCP, we find that our extended multipath transport protocols can preserve lower latency and transmission rate variance than MPTCP, fairly share with single-path SQRT/IIAD, MPTCP and TCP, and also can achieve throughput improvements and load-balancing equivalent to those of MPTCP under various scenarios and network conditions.
Non-Blocking, Localized Routing Algorithm for Balanced Energy Consumption in Mobile Ad Hoc Networks
Yu, Chansu
1 Non-Blocking, Localized Routing Algorithm for Balanced Energy Consumption in Mobile Ad Hoc relevant nodes but also to balance individual battery levels. Unbalanced energy usage will result achieves a trade-off between balanced energy consumption and shortest routing delay, and at the same time
Hop-by-Hop Routing Algorithms For Premium Traffic Department of Computer Science
Nahrstedt, Klara
Hop-by-Hop Routing Algorithms For Premium Traffic Jun Wang Department of Computer Science@cs.uiuc.edu ABSTRACT In Differentiated Service (DiffServ) networks, the routing algo- rithms used by the premium class on the premium class traffic itself, but on all other classes of traffic as well. The shortest hop-count routing
Zhao, Yan-Jiang; Joseph, Felix Orlando Maria; Yan, Kaiguo; Datla, Naresh V; Zhang, Yong-De; Podder, Tarun K; Hutapea, Parsaoran; Dicker, Adam; Yu, Yan
2014-01-01
In robot-assisted needle-based medical procedures, path planning for a flexible needle is challenging with regard to time consumption and searching robustness for the solution due to the nonholonomic motion of the needle tip and the presence of anatomic obstacles and sensitive organs in the intended needle path. We propose a novel and fast path planning algorithm for a robot-assisted active flexible needle. The algorithm is based on Rapidly-Exploring Random Trees combined with reachability-guided strategy and greedy heuristic strategy. Linear segments are taken into consideration to the paths, and insertion orientations are relaxed by the introduction of the linear segments. The proposed algorithm yields superior results as compared to the commonly used algorithm in terms of computational speed, form of path and robustness of searching ability, which potentially can make it suitable for the real-time intraoperative planning for clinical procedures. PMID:25569976
Path Planning for Autonomous Driving in Unknown Environments
Dmitri Dolgov; Sebastian Thrun; Michael Montemerlo; James Diebel
2008-01-01
We describe a practical path-planning algorithm that generates smooth paths for an autonomous vehicle operating in an unknown\\u000a environment, where obstacles are detected online by the robot’s sensors. This work was motivated by and experimentally validated\\u000a in the 2007 DARPA Urban Challenge, where robotic vehicles had to autonomously navigate parking lots. Our approach has two\\u000a main steps. The first step
Adaptive path planning for a VTOL-UAV
Oliver Meister; Natalie Frietsch; Christian Ascher; Gert F. Trommer
2008-01-01
Unmanned aerial vehicles (UAV) can be used for versatile surveillance and reconnaissance missions. If a UAV is capable of flying automatically on a predefined path, the range of possible applications is widened significantly. This paper addresses the development of adaptive path planning algorithms for a small vertical take-off and landing (VTOL) unmanned four-rotor helicopter with a take-off weight below 1
Paths in the minimally weighted path model are incompatible with Schramm-Loewner evolution
NASA Astrophysics Data System (ADS)
Norrenbrock, C.; Melchert, O.; Hartmann, A. K.
2013-03-01
We study numerically the geometrical properties of minimally weighted paths that appear in the minimally weighted path (MWP) model on two-dimensional lattices assuming a combination of periodic and free boundary conditions (BCs). Each realization of the disorder consists of a random fraction (1-?) of bonds with unit strength and a fraction ? of bond strengths drawn from a Gaussian distribution with zero mean and unit width. For each such sample, a path is forced to span the lattice along the direction with the free BCs. The path and a set of negatively weighted loops form a ground state. A ground state on such a lattice can be determined performing a nontrivial transformation of the original graph and applying sophisticated matching algorithms. Here we examine whether the geometrical properties of the paths are in accordance with the predictions of the Schramm-Loewner evolution (SLE). Measuring the fractal dimension, considering the winding angle statistics, and reviewing Schramm's left passage formula indicate that the paths cannot be described in terms of SLE.
Atmospheric Science Data Center
2014-12-08
... is natural to name each of these different trajectories or paths. For MISR, the path is the generic name (actually the numeric label) of ... that are close to each other in longitude will be covered by paths with similar numbers. The path number is also included in the file name ...
Adaptive robot path planning in changing environments
Chen, P.C.
1994-08-01
Path planning needs to be fast to facilitate real-time robot programming. Unfortunately, current planning techniques are still too slow to be effective, as they often require several minutes, if not hours of computation. To overcome this difficulty, we present an adaptive algorithm that uses past experience to speed up future performance. It is a learning algorithm suitable for incrementally-changing environments such as those encountered in manufacturing of evolving products and waste-site remediation. The algorithm allows the robot to adapt to its environment by having two experience manipulation schemes: For minor environmental change, we use an object-attached experience abstraction scheme to increase the flexibility of the learned experience; for major environmental change, we use an on-demand experience repair scheme to retain those experiences that remain valid and useful. Using this algorithm, we can effectively reduce the overall robot planning time by re-using the computation result for one task to plan a path for another.
X-ray counterpart of the shortest activity cycle found to date
NASA Astrophysics Data System (ADS)
Sanz-Forcada, Jorge
2011-10-01
Activity cycles are commonly found among late type stars through the chromospheric Ca II emission. Their coronal counterpart, remains elusive in most cases, despite of the clear cycle observed in the solar corona, spanning as much as 1.7 dex in Lx. The recent discovery of a Ca II cycle in HR 810 of just 1.6 yr, the shortest to date, offers a unique opportunity to test the existence of an X-ray counterpart of the cycle within two XMM-Newton observing periods. The star offers two more interesting properties: it represents a young (500 Myr) solar analog, and a 1.9 Mj planet orbits the star at 0.9 a.u. We started our search for the cycle of HR 810 in AO 10 and we intend to make 5 new snapshots during XMM-Newton AO 11, for a total of 25 ks, to complete the coverage of the cycle.
Path integral for the loop representation of lattice gauge theories
Aroca, J.M. [Departament de Matematiques, Universitat Politecnica de Catalunya, Gran Capita, s/n Mod C-3 Campus Nord, 08034 Barcelona (Spain)] [Departament de Matematiques, Universitat Politecnica de Catalunya, Gran Capita, s/n Mod C-3 Campus Nord, 08034 Barcelona (Spain); Fort, H.; Gambini, R. [Instituto de Fisica, Facultad de Ciencias, Tristan Narvaja 1674, 11200 Montevideo (Uruguay)] [Instituto de Fisica, Facultad de Ciencias, Tristan Narvaja 1674, 11200 Montevideo (Uruguay)
1996-12-01
We show how the Hamiltonian lattice {ital loop} {ital representation} can be cast straightforwardly in the path integral formalism. The procedure is general for any gauge theory. Here we present in detail the simplest case: pure compact QED. The lattice loop path integral approach allows us to knit together the power of statistical algorithms with the transparency of the gauge-invariant loop description. The results produced by numerical simulations with the loop classical action for different lattice models are discussed. We also analyze the lattice path integral in terms of loops for the non-Abelian theory. {copyright} {ital 1996 The American Physical Society.}
arXiv:1005.1035v1[math.PR]6May2010 DIFFUSION LIMITS FOR SHORTEST REMAINING
Puha, Amber
, that is, the job with the shortest remaining processing time. More Research supported in part by NSF Remaining Processing Time (SRPT) policy, preemptive priority is given to the job that can be completed first.i.d. service times, and let I(t) index those jobs that are in the queue at time t. For i I(t), let wi
Qian, Weixian; Zhou, Xiaojun; Lu, Yingcheng; Xu, Jiang
2015-09-15
Both the Jones and Mueller matrices encounter difficulties when physically modeling mixed materials or rough surfaces due to the complexity of light-matter interactions. To address these issues, we derived a matrix called the paths correlation matrix (PCM), which is a probabilistic mixture of Jones matrices of every light propagation path. Because PCM is related to actual light propagation paths, it is well suited for physical modeling. Experiments were performed, and the reflection PCM of a mixture of polypropylene and graphite was measured. The PCM of the mixed sample was accurately decomposed into pure polypropylene's single reflection, pure graphite's single reflection, and depolarization caused by multiple reflections, which is consistent with the theoretical derivation. Reflection parameters of rough surface can be calculated from PCM decomposition, and the results fit well with the theoretical calculations provided by the Fresnel equations. These theoretical and experimental analyses verify that PCM is an efficient way to physically model light-matter interactions. PMID:26371930
Sullivan, Blair D; Seymour, Dr. Paul Douglas
2010-01-01
Say a digraph is k-free if it has no directed cycles of length at most k, for k {element_of} Z{sup +}. Thomasse conjectured that the number of induced 3-vertex directed paths in a simple 2-free digraph on n vertices is at most (n-1)n(n+1)/15. We present an unpublished result of Bondy proving there are at most 2n{sup 3}/25 such paths, and prove that for the class of circular interval digraphs, an upper bound of n{sup 3}/16 holds. We also study the problem of bounding the number of (non-induced) 4-vertex paths in 3-free digraphs. We show an upper bound of 4n{sup 4}/75 using Bondy's result for Thomasse's conjecture.
Auto-Directed Video Stabilization with Robust L1 Optimal Camera Paths Matthias Grundmann1,2
Haro, Antonio
Auto-Directed Video Stabilization with Robust L1 Optimal Camera Paths Matthias Grundmann1,2 Vivek algorithm for automatically applying constrainable, L1-optimal camera paths to generate stabi- lized videos of the re- sulting camera path. Our method allows for video stabiliza- tion beyond the conventional
Zhanfang Chen; Guoyu Zhang; Xiaopeng Zhang
2009-01-01
After analyzing the characteristics of virtual endoscopy and volume data visualization, this paper proposes an improved volume rendering algorithm based on interactive dynamic volume rendering algorithm of perspective project volume rendering, which improves the volume rendering speed in the 3D data field of the virtual endoscopy. This algorithm adopts the dynamic data reduction technique. It automatically generates the navigation path
Automatic tool path generation for finish machining
Kwok, Kwan S.; Loucks, C.S.; Driessen, B.J.
1997-03-01
A system for automatic tool path generation was developed at Sandia National Laboratories for finish machining operations. The system consists of a commercially available 5-axis milling machine controlled by Sandia developed software. This system was used to remove overspray on cast turbine blades. A laser-based, structured-light sensor, mounted on a tool holder, is used to collect 3D data points around the surface of the turbine blade. Using the digitized model of the blade, a tool path is generated which will drive a 0.375 inch diameter CBN grinding pin around the tip of the blade. A fuzzified digital filter was developed to properly eliminate false sensor readings caused by burrs, holes and overspray. The digital filter was found to successfully generate the correct tool path for a blade with intentionally scanned holes and defects. The fuzzified filter improved the computation efficiency by a factor of 25. For application to general parts, an adaptive scanning algorithm was developed and presented with simulation results. A right pyramid and an ellipsoid were scanned successfully with the adaptive algorithm.
Efficiently finding the minimum free energy path from steepest descent path.
Chen, Changjun; Huang, Yanzhao; Ji, Xiaofeng; Xiao, Yi
2013-04-28
Minimum Free Energy Path (MFEP) is very important in computational biology and chemistry. The barrier in the path is related to the reaction rate, and the start-to-end difference gives the relative stability between reactant and product. All these information is significant to experiment and practical application. But finding MFEP is not an easy job. Lots of degrees of freedom make the computation very complicated and time consuming. In this paper, we use the Steepest Descent Path (SDP) to accelerate the sampling of MFEP. The SHAKE algorithm and the Lagrangian multipliers are used to control the optimization of both SDP and MFEP. These strategies are simple and effective. For the former, it is more interesting. Because as we known, SHAKE algorithm was designed to handle the constraints in molecular dynamics in the past, has never been used in geometry optimization. Final applications on ALA dipeptide and 10-ALA peptide show that this combined optimization method works well. Use the information in SDP, the initial path could reach the more optimal MFEP. So more accurate free energies could be obtained and the amount of computation time could be saved. PMID:23635126
Quad-rotor flight path energy optimization
NASA Astrophysics Data System (ADS)
Kemper, Edward
Quad-Rotor unmanned areal vehicles (UAVs) have been a popular area of research and development in the last decade, especially with the advent of affordable microcontrollers like the MSP 430 and the Raspberry Pi. Path-Energy Optimization is an area that is well developed for linear systems. In this thesis, this idea of path-energy optimization is extended to the nonlinear model of the Quad-rotor UAV. The classical optimization technique is adapted to the nonlinear model that is derived for the problem at hand, coming up with a set of partial differential equations and boundary value conditions to solve these equations. Then, different techniques to implement energy optimization algorithms are tested using simulations in Python. First, a purely nonlinear approach is used. This method is shown to be computationally intensive, with no practical solution available in a reasonable amount of time. Second, heuristic techniques to minimize the energy of the flight path are tested, using Ziegler-Nichols' proportional integral derivative (PID) controller tuning technique. Finally, a brute force look-up table based PID controller is used. Simulation results of the heuristic method show that both reliable control of the system and path-energy optimization are achieved in a reasonable amount of time.
ERIC Educational Resources Information Center
McGarvey, Lynn M.; Sterenberg, Gladys Y.; Long, Julie S.
2013-01-01
The authors elucidate what they saw as three important challenges to overcome along the path to becoming elementary school mathematics teacher leaders: marginal interest in math, low self-confidence, and teaching in isolation. To illustrate how these challenges were mitigated, they focus on the stories of two elementary school teachers--Laura and…
DNA Computing Hamiltonian path
Hagiya, Masami
2014 DNA DNA #12;DNA Computing · Feynman · Adleman · DNASIMD · ... · · · · · DNADNA #12;DNA · DNA · · · · DNA · · #12;2000 2005 2010 1995 Hamiltonian path DNA tweezers DNA tile DNA origami DNA box Sierpinski DNA tile self assembly DNA logic gates Whiplash PCR DNA automaton DNA spider MAYA
ERIC Educational Resources Information Center
Coleman, Toni
2012-01-01
A growing number of institutions are being more deliberate about bringing in fundraisers who fit the culture of the development department and about assessing skills and providing training that fill specific needs. Development shops are paying more attention to cultivating their staffs, staying attuned to employees' needs and creating career paths…
NSDL National Science Digital Library
CareerPath offers a searchable index of employment ads from six major newspapers: The Boston Globe, Chicago Tribune, Los Angeles Times, The New York Times, The San Jose Mercury News, and The Washington Post. The total ads available on October 21 was 21,442. The site is attractive and easy to use.
ERIC Educational Resources Information Center
Grimm, Karen
1999-01-01
Describes "Off the Beaten Path", a program that takes at-risk students out of the traditional classroom and puts them into a camping atmosphere in order to increase academic achievement, improve self-esteem, and promote better social skills. (WRM)
ERIC Educational Resources Information Center
Rodia, Becky
2004-01-01
This article profiles Diane Stanley, an author and illustrator of children's books. Although she was studying to be a medical illustrator in graduate school, Stanley's path changed when she got married and had children. As she was raising her children, she became increasingly enamored of the colorful children's books she would check out of the…
NASA Technical Reports Server (NTRS)
Bill, R. C.; Johnson, R. D. (inventors)
1979-01-01
A gas path seal suitable for use with a turbine engine or compressor is described. A shroud wearable or abradable by the abrasion of the rotor blades of the turbine or compressor shrouds the rotor bades. A compliant backing surrounds the shroud. The backing is a yieldingly deformable porous material covered with a thin ductile layer. A mounting fixture surrounds the backing.
2013-03-05
where j a differential 1-form on some vector space V and t/Xt is a path in V not necessarily of .... Let C be the algebra of bounded continuous functions from R to R and ... Let OC g be the subspace of elements XAOC such that. jjXjjg :¼ sup t;
NASA Astrophysics Data System (ADS)
Zheng, Feifei; Simpson, Angus R.; Zecchin, Aaron C.
2011-08-01
This paper proposes a novel optimization approach for the least cost design of looped water distribution systems (WDSs). Three distinct steps are involved in the proposed optimization approach. In the first step, the shortest-distance tree within the looped network is identified using the Dijkstra graph theory algorithm, for which an extension is proposed to find the shortest-distance tree for multisource WDSs. In the second step, a nonlinear programming (NLP) solver is employed to optimize the pipe diameters for the shortest-distance tree (chords of the shortest-distance tree are allocated the minimum allowable pipe sizes). Finally, in the third step, the original looped water network is optimized using a differential evolution (DE) algorithm seeded with diameters in the proximity of the continuous pipe sizes obtained in step two. As such, the proposed optimization approach combines the traditional deterministic optimization technique of NLP with the emerging evolutionary algorithm DE via the proposed network decomposition. The proposed methodology has been tested on four looped WDSs with the number of decision variables ranging from 21 to 454. Results obtained show the proposed approach is able to find optimal solutions with significantly less computational effort than other optimization techniques.
Robot path planning for space-truss assembly
NASA Technical Reports Server (NTRS)
Muenger, Rolf; Sanderson, Arthur C.
1992-01-01
Construction, repair, and maintenance of space-based structures will require extensive planning of operations in order to effectively carry out these tasks. The path planning algorithm described here is a general approach to generating paths that guarantee collision avoidance for a single chain nonredundant or redundant robot. The algorithm uses a graph search of feasible points in position space, followed by a local potential field method that guarantees collision avoidance among objects, structures, and the robot arm as well as conformance to joint limit constraints. This algorithm is novel in its computation of goal attractive potential fields in Cartesian space, and computation of obstacle repulsive fields in robot joint space. These effects are combined to generate robot motion. Computation is efficiently implemented through the computation of the robot arm Jacobian and not the full inverse arm kinematics. These planning algorithms have been implemented and evaluated using existing space-truss designs, and are being integrated into the RPI-CIRSSE Testbed environment.
Filtered backprojection proton CT reconstruction along most likely paths
Rit, Simon; Dedes, George; Freud, Nicolas; Sarrut, David; Letang, Jean Michel [Universite de Lyon, CREATIS, CNRS UMR5220, Inserm U1044, INSA-Lyon, Universite Lyon 1, Centre Leon Berard, 69008 Lyon (France)
2013-03-15
Purpose: Proton CT (pCT) has the potential to accurately measure the electron density map of tissues at low doses but the spatial resolution is prohibitive if the curved paths of protons in matter is not accounted for. The authors propose to account for an estimate of the most likely path of protons in a filtered backprojection (FBP) reconstruction algorithm. Methods: The energy loss of protons is first binned in several proton radiographs at different distances to the proton source to exploit the depth-dependency of the estimate of the most likely path. This process is named the distance-driven binning. A voxel-specific backprojection is then used to select the adequate radiograph in the distance-driven binning in order to propagate in the pCT image the best achievable spatial resolution in proton radiographs. The improvement in spatial resolution is demonstrated using Monte Carlo simulations of resolution phantoms. Results: The spatial resolution in the distance-driven binning depended on the distance of the objects from the source and was optimal in the binned radiograph corresponding to that distance. The spatial resolution in the reconstructed pCT images decreased with the depth in the scanned object but it was always better than previous FBP algorithms assuming straight line paths. In a water cylinder with 20 cm diameter, the observed range of spatial resolutions was 0.7 - 1.6 mm compared to 1.0 - 2.4 mm at best with a straight line path assumption. The improvement was strongly enhanced in shorter 200 Degree-Sign scans. Conclusions: Improved spatial resolution was obtained in pCT images with filtered backprojection reconstruction using most likely path estimates of protons. The improvement in spatial resolution combined with the practicality of FBP algorithms compared to iterative reconstruction algorithms makes this new algorithm a candidate of choice for clinical pCT.
Tunable path centrality: Quantifying the importance of paths in networks
NASA Astrophysics Data System (ADS)
Pu, Cun-Lai; Cui, Wei; Yang, Jian
2014-07-01
Centrality is a fundamental measure in network analysis. Specifically, centrality of a path describes the importance of the path with respect to the remaining part of the network. In this paper, we propose a tunable path centrality (TPC) measure, which quantifies the centrality of a path by integrating the path degree (PD) (number of neighbors of the path) and the path bridge (PB) (number of bridges in the path) with a control parameter ?. Considering the complexity of large-scale and dynamical topologies of many real-world networks, both PD and PB are computed with only the local topological structure of a path. We demonstrate the distribution of the three path centralities (TPC, PD and PB) in computer-generated networks and real-world networks. Furthermore, we apply the three path centralities to the network fragility problem, and exploit the distribution of the optimal control parameter ? through simulation and analysis. Finally, the simulation results show that generally TPC is more efficient than PD and PB in the network fragility problem. These path centralities are also applicable in many other network problems including spread, control, prediction and so on.
Practical and conceptual path sampling issues
NASA Astrophysics Data System (ADS)
Bolhuis, P. G.; Dellago, C.
2015-06-01
In the past 15 years transition path sampling (TPS) has evolved from its basic algorithm to an entire collection of methods and a framework for investigating rare events in complex systems. The methodology is applicable to a wide variety of systems and processes, ranging from transitions in small clusters or molecules to chemical reactions, phase transitions, and conformational changes in biomolecules. The basic idea of TPS is to harvest dynamical unbiased trajectories that connect a reactant with a product, by a Markov Chain Monte Carlo procedure called shooting. This simple importance sampling yields the rate constants, the free energy surface, insight in the mechanism of the rare event of interest, and by using the concept of the committor, also access to the reaction coordinate. In the last decade extensions to TPS have been developed, notably the transition interface sampling (TIS) methods, and its generalization multiple state TIS. Combination with advanced sampling methods such as replica exchange and the Wang-Landau algorithm, among others, improves sampling efficiency. Notwithstanding the success of TPS, there are issues left to discuss, and, despite the method's apparent simplicity, many pitfalls to avoid. This paper discusses several of these issues and pitfalls: the choice of stable states and interface order parameters, the problem of positioning the TPS windows and TIS interfaces, the matter of convergence of the path ensemble, the matter of kinetic traps, and the question whether TPS is able to investigate and sample Markov state models. We also review the reweighting technique used to join path ensembles. Finally we discuss the use of the sampled path ensemble to obtain reaction coordinates.
On the importance of path for phase unwrapping in synthetic aperture radar interferometry.
Osmanoglu, Batuhan; Dixon, Timothy H; Wdowinski, Shimon; Cabral-Cano, Enrique
2011-07-01
Phase unwrapping is a key procedure in interferometric synthetic aperture radar studies, translating ambiguous phase observations to topography, and surface deformation estimates. Some unwrapping algorithms are conducted along specific paths based on different selection criteria. In this study, we analyze six unwrapping paths: line scan, maximum coherence, phase derivative variance, phase derivative variance with branch-cut, second-derivative reliability, and the Fisher distance. The latter is a new path algorithm based on Fisher information theory, which combines the phase derivative with the expected variance to get a more robust path, potentially performing better than others in the case of low image quality. In order to compare only the performance of the paths, the same unwrapping function (phase derivative integral) is used. Results indicate that the Fisher distance algorithm gives better results in most cases. PMID:21743520
Aircraft path planning for optimal imaging using dynamic cost functions
NASA Astrophysics Data System (ADS)
Christie, Gordon; Chaudhry, Haseeb; Kochersberger, Kevin
2015-05-01
Unmanned aircraft development has accelerated with recent technological improvements in sensing and communications, which has resulted in an "applications lag" for how these aircraft can best be utilized. The aircraft are becoming smaller, more maneuverable and have longer endurance to perform sensing and sampling missions, but operating them aggressively to exploit these capabilities has not been a primary focus in unmanned systems development. This paper addresses a means of aerial vehicle path planning to provide a realistic optimal path in acquiring imagery for structure from motion (SfM) reconstructions and performing radiation surveys. This method will allow SfM reconstructions to occur accurately and with minimal flight time so that the reconstructions can be executed efficiently. An assumption is made that we have 3D point cloud data available prior to the flight. A discrete set of scan lines are proposed for the given area that are scored based on visibility of the scene. Our approach finds a time-efficient path and calculates trajectories between scan lines and over obstacles encountered along those scan lines. Aircraft dynamics are incorporated into the path planning algorithm as dynamic cost functions to create optimal imaging paths in minimum time. Simulations of the path planning algorithm are shown for an urban environment. We also present our approach for image-based terrain mapping, which is able to efficiently perform a 3D reconstruction of a large area without the use of GPS data.
Kinematic path planning for space-based robotics
NASA Astrophysics Data System (ADS)
Seereeram, Sanjeev; Wen, John T.
1998-01-01
Future space robotics tasks require manipulators of significant dexterity, achievable through kinematic redundancy and modular reconfigurability, but with a corresponding complexity of motion planning. Existing research aims for full autonomy and completeness, at the expense of efficiency, generality or even user friendliness. Commercial simulators require user-taught joint paths-a significant burden for assembly tasks subject to collision avoidance, kinematic and dynamic constraints. Our research has developed a Kinematic Path Planning (KPP) algorithm which bridges the gap between research and industry to produce a powerful and useful product. KPP consists of three key components: path-space iterative search, probabilistic refinement, and an operator guidance interface. The KPP algorithm has been successfully applied to the SSRMS for PMA relocation and dual-arm truss assembly tasks. Other KPP capabilities include Cartesian path following, hybrid Cartesian endpoint/intermediate via-point planning, redundancy resolution and path optimization. KPP incorporates supervisory (operator) input at any detail to influence the solution, yielding desirable/predictable paths for multi-jointed arms, avoiding obstacles and obeying manipulator limits. This software will eventually form a marketable robotic planner suitable for commercialization in conjunction with existing robotic CAD/CAM packages.
Hierarchical path planning and control of a small fixed-wing UAV: Theory and experimental validation
NASA Astrophysics Data System (ADS)
Jung, Dongwon
2007-12-01
Recently there has been a tremendous growth of research emphasizing control of unmanned aerial vehicles (UAVs) either in isolation or in teams. As a matter of fact, UAVs increasingly find their way into military and law enforcement applications (e.g., reconnaissance, remote delivery of urgent equipment/material, resource assessment, environmental monitoring, battlefield monitoring, ordnance delivery, etc.). This trend will continue in the future, as UAVs are poised to replace the human-in-the-loop during dangerous missions. Civilian applications of UAVs are also envisioned such as crop dusting, geological surveying, search and rescue operations, etc. In this thesis we propose a new online multiresolution path planning algorithm for a small UAV with limited on-board computational resources. The proposed approach assumes that the UAV has detailed information of the environment and the obstacles only in its vicinity. Information about far-away obstacles is also available, albeit less accurately. The proposed algorithm uses the fast lifting wavelet transform (FLWT) to get a multiresolution cell decomposition of the environment, whose dimension is commensurate to the on-board computational resources. A topological graph representation of the multiresolution cell decomposition is constructed efficiently, directly from the approximation and detail wavelet coefficients. Dynamic path planning is sequentially executed for an optimal path using the A* algorithm over the resulting graph. The proposed path planning algorithm is implemented on-line on a small autopilot. Comparisons with the standard D*-lite algorithm are also presented. We also investigate the problem of generating a smooth, planar reference path from a discrete optimal path. Upon the optimal path being represented as a sequence of cells in square geometry, we derive a smooth B-spline path that is constrained inside a channel that is induced by the geometry of the cells. To this end, a constrained optimization problem is formulated by setting up geometric linear constraints as well as boundary conditions. Subsequently, we construct B-spline path templates by solving a set of distinct optimization problems. For application in UAV motion planning, the path templates are incorporated to replace parts of the entire path by the smooth B-spline paths. Each path segment is stitched together while preserving continuity to obtain a final smooth reference path to be used for path following control. The path following control for a small fixed-wing UAV to track the prescribed smooth reference path is also addressed. Assuming the UAV is equipped with an autopilot for low level control, we adopt a kinematic error model with respect to the moving Serret-Frenet frame attached to a path for tracking controller design. A kinematic path following control law that commands heading rate is presented. Backstepping is applied to derive the roll angle command by taking into account the approximate closed-loop roll dynamics. A parameter adaptation technique is employed to account for the inaccurate time constant of the closed-loop roll dynamics during actual implementation. Finally, we implement the proposed hierarchical path control of a small UAV on the actual hardware platform, which is based on an 1/5 scale R/C model airframe (Decathlon) and the autopilot hardware and software. Based on the hardware-in-the-loop (HIL) simulation environment, the proposed hierarchical path control algorithm has been validated through on-line, real-time implementation on a small micro-controller. By a seamless integration of the control algorithms for path planning, path smoothing, and path following, it has been demonstrated that the UAV equipped with a small autopilot having limited computational resources manages to accomplish the path control objective to reach the goal while avoiding obstacles with minimal human intervention.
Geoffrey F. Chew
2008-02-21
Arrowed-time divergence-free rules or cosmological quantum dynamics are formulated through stepped Feynman paths across macroscopic slices of Milne spacetime. Slice boundaries house totally-relativistic rays representing elementary entities--preons. Total relativity and the associated preon Fock space, despite distinction from special relativity (which lacks time arrow), are based on the Lorentz group. Each path is a set of cubic vertices connected by straight, directed and stepped arcs that carry inertial, electromagnetic and gravitational action. The action of an arc step comprises increments each bounded by Planck's constant. Action from extremely-distant sources is determined by universe mean energy density. Identifying the arc-step energy that determines inertial action with that determining gravitational action establishes both arc-step length and universe density. Special relativity is accurate for physics at laboratory spacetime scales far below that of Hubble and far above that of Planck.
A randomized algorithm for finding a maximum clique in the visibility graph of a simple polygon
Cabello, Sergio
Sergio Cabello Maria Saumell October 17, 2013 Abstract We present a randomized algorithm to compute-self-intersecting, closed, polygonal path. The polygonal path itself is part of the polygon; it is usually called its
Energy aware path planning in complex four dimensional environments
NASA Astrophysics Data System (ADS)
Chakrabarty, Anjan
This dissertation addresses the problem of energy-aware path planning for small autonomous vehicles. While small autonomous vehicles can perform missions that are too risky (or infeasible) for larger vehicles, the missions are limited by the amount of energy that can be carried on board the vehicle. Path planning techniques that either minimize energy consumption or exploit energy available in the environment can thus increase range and endurance. Path planning is complicated by significant spatial (and potentially temporal) variations in the environment. While the main focus is on autonomous aircraft, this research also addresses autonomous ground vehicles. Range and endurance of small unmanned aerial vehicles (UAVs) can be greatly improved by utilizing energy from the atmosphere. Wind can be exploited to minimize energy consumption of a small UAV. But wind, like any other atmospheric component , is a space and time varying phenomenon. To effectively use wind for long range missions, both exploration and exploitation of wind is critical. This research presents a kinematics based tree algorithm which efficiently handles the four dimensional (three spatial and time) path planning problem. The Kinematic Tree algorithm provides a sequence of waypoints, airspeeds, heading and bank angle commands for each segment of the path. The planner is shown to be resolution complete and computationally efficient. Global optimality of the cost function cannot be claimed, as energy is gained from the atmosphere, making the cost function inadmissible. However the Kinematic Tree is shown to be optimal up to resolution if the cost function is admissible. Simulation results show the efficacy of this planning method for a glider in complex real wind data. Simulation results verify that the planner is able to extract energy from the atmosphere enabling long range missions. The Kinematic Tree planning framework, developed to minimize energy consumption of UAVs, is applied for path planning in ground robots. In traditional path planning problem the focus is on obstacle avoidance and navigation. The optimal Kinematic Tree algorithm named Kinematic Tree* is shown to find optimal paths to reach the destination while avoiding obstacles. A more challenging path planning scenario arises for planning in complex terrain. This research shows how the Kinematic Tree* algorithm can be extended to find minimum energy paths for a ground vehicle in difficult mountainous terrain.
Louis Fishman
2006-01-01
The multidimensional, scalar Helmholtz equation of mathematical physics is addressed. Rather than pursuing traditional approaches for the representation and computation of the fundamental solution, path integral representations, originating in quantum physics, are considered. Constructions focusing on the global, two-way nature of the Helmholtz equation, such as the Feynman\\/Fradkin, Feynman\\/Garrod, and Feynman\\/DeWitt-Morette representations, are reviewed, in addition to the complementary phase
Studness, C.M.
1995-05-01
The financial community`s focus on utility competition has been riveted on the proceedings now in progress at state regulatory commissions. The fear that something immediately damaging will come out of these proceedings seems to have diminished in recent months, and the stock market has reacted favorably. However, regulatory developments are only one of four paths leading to competition; the others are the marketplace, the legislatures, and the courts. Each could play a critical role in the emergence of competition.
MINIMUM WEIGHT PATHS TIMEDEPENDENT NETWORKS
Orda, Ariel
MINIMUM WEIGHT PATHS in TIMEDEPENDENT NETWORKS Ariel Orda Raphael Rom Department of Electrical) ABSTRACT We investigate the minimum weight path problem in networks whose link weights and link delays are both functions of time. We demonstrate that in general there exist cases in which no finite path
Synthesis of Shape Morphing Compliant Mechanisms Using a Load Path Representation Method
Lu, Kerr-Jia
algorithm, topology optimization 1. INTRODUCTION The performance of many mechanical systems is directly a load path representation method to efficiently exclude the invalid topologies (disconnected structures the GA are also discussed. Keywords: compliant mechanism, adaptive structure, shape morphing, genetic
Iterative Snapping of Odometry Trajectories for Path Identification
Veloso, Manuela M.
errors of dead reckoning but it captures the relative shape of the traversed path well. Our approach map. Our algorithm is inspired by prior vehicular GPS map matching techniques that snap global GPS mod- ifications are required to ensure these techniques are robust when given relative measurements
Time-Optimal Control of Robotic Manipulators Along Specified Paths
J. E. Bobrow; S. Dubowsky; J. S. Gibson
1985-01-01
The minimum-time manipulator control problem is solved for the case when the path is specified and the actuator torque limitations are known. The optimal open-loop torques are found, and a method is given for implementing these torques with a conventional linear feedback control system. The algorithm allows bounds on the torques that may be arbitrary functions of the joint angles
Start and Stop Rules for Exploratory Path Analysis.
ERIC Educational Resources Information Center
Shipley, Bill
2002-01-01
Describes a method for choosing rejection probabilities for the tests of independence that are used in constraint-based algorithms of exploratory path analysis. The method consists of generating a Markov or semi-Markov model from the equivalence class represented by a partial ancestral graph and then testing the d-separation implications. (SLD)
ANALYTICAL SYNTHESIS LEAST CURVATURE PATHS FOR UNDERWATER APPLICATIONS
Zimmer, Uwe
holonomic vehicles concerned with generation algorithms. problem smooth least curvature 3D planning is addressed a variational approach general 3D EulerPoisson equation derived. solution calculated as the projection general as proportional elastic ergy of curve. Due to sought plane path sometimes called least energy curve literature
PATHS groundwater hydrologic model
Nelson, R.W.; Schur, J.A.
1980-04-01
A preliminary evaluation capability for two-dimensional groundwater pollution problems was developed as part of the Transport Modeling Task for the Waste Isolation Safety Assessment Program (WISAP). Our approach was to use the data limitations as a guide in setting the level of modeling detail. PATHS Groundwater Hydrologic Model is the first level (simplest) idealized hybrid analytical/numerical model for two-dimensional, saturated groundwater flow and single component transport; homogeneous geology. This document consists of the description of the PATHS groundwater hydrologic model. The preliminary evaluation capability prepared for WISAP, including the enhancements that were made because of the authors' experience using the earlier capability is described. Appendixes A through D supplement the report as follows: complete derivations of the background equations are provided in Appendix A. Appendix B is a comprehensive set of instructions for users of PATHS. It is written for users who have little or no experience with computers. Appendix C is for the programmer. It contains information on how input parameters are passed between programs in the system. It also contains program listings and test case listing. Appendix D is a definition of terms.
Chakraborty, Swati
2015-04-27
the path generation with the SAT solvers. The techniques presented are circuit simplification, Dynamic SAT Solving (DSS), Circuit Observability Don’t Cares (Cir- ODC) and Approximate Observability Don’t Cares (AODC). In DSS, the structural information.... But generation of compatible ODCs is complex. An efficient algorithm to find approximate ODCs is presented in [26]. 1.5.1 MiniSat MiniSat is a minimalistic, open-source SAT solver [27]. It has been used in CodGen because of its modifiability, efficiency...
Algorithmic randomness and physical entropy
Zurek, W.H. )
1989-10-15
{ital Algorithmic} {ital randomness} provides a rigorous, entropylike measure of disorder of an individual, microscopic, definite state of a physical system. It is defined by the size (in binary digits) of the shortest message specifying the microstate uniquely up to the assumed resolution. Equivalently, algorithmic randomness can be expressed as the number of bits in the smallest program for a universal computer that can reproduce the state in question (for instance, by plotting it with the assumed accuracy). In contrast to the traditional definitions of entropy, algorithmic randomness can be used to measure disorder without any recourse to probabilities. Algorithmic randomness is typically very difficult to calculate exactly but relatively easy to estimate. In large systems, probabilistic ensemble definitions of entropy (e.g., coarse-grained entropy of Gibbs and Boltzmann's entropy {ital H}=ln{ital W}, as well as Shannon's information-theoretic entropy) provide accurate estimates of the algorithmic entropy of an individual system or its average value for an ensemble. One is thus able to rederive much of thermodynamics and statistical mechanics in a setting very different from the usual. {ital Physical} {ital entropy}, I suggest, is a sum of (i) the missing information measured by Shannon's formula and (ii) of the algorithmic information content---algorithmic randomness---present in the available data about the system. This definition of entropy is essential in describing the operation of thermodynamic engines from the viewpoint of information gathering and using systems. These Maxwell demon-type entities are capable of acquiring and processing information and therefore can decide'' on the basis of the results of their measurements and computations the best strategy for extracting energy from their surroundings. From their internal point of view the outcome of each measurement is definite.
(Nothing else) MATor(s): Monitoring the Anonymity of Tor's Path Selection
International Association for Cryptologic Research (IACR)
(Nothing else) MATor(s): Monitoring the Anonymity of Tor's Path Selection Michael Backes1,2 Aniket we present MATOR: a framework for rigorously assessing the degree of anonymity in the Tor network deployed Tor, such as its path selection algorithm, Tor consensus data, and the preferences
Optimal View Path Planning for Visual SLAM Sebastian Haner and Anders Heyden
Lunds Universitet
Optimal View Path Planning for Visual SLAM Sebastian Haner and Anders Heyden Centre efficient iterative algorithm targeted toward application within real-time SLAM systems is presented and tested on simulated data. Keywords: Next best view planning, path optimization, SLAM 1 Introduction
Tracking and classification of objects moving along a known path in an outdoor environment
Donohoe, G.W.; Hush, D.R.; Fogler, R.J.
1986-01-01
This paper describes a method for tracking and classifying objects which are moving along a known path in an outdoor environment (e.g., cars along a road). The input is a continuous sequence of video frames. Only the portion of the image which lies along the known path is processed, resulting in a significant reduction in the computational requirements of the algorithm.
Model Checking Restricted Sets of Timed Paths Nicolas Markey a JeanFranois Raskin b
Doyen, Laurent
. When the verification of a safety or a linearÂ time property fails, those symbolic algorithms identifyModel Checking Restricted Sets of Timed Paths Nicolas Markey a JeanÂFranÃ§ois Raskin b a Lab is the symbolic representation of an infinite set of timed paths that are counterÂexamples to the property
Crack paths in composite materials M. Patricio* R. M. M. Mattheij*
Eindhoven, Technische Universiteit
#12;Crack paths in composite materials M. PatrÂ´icio* R. M. M. Mattheij* *Adress: Department ----------------------------------------------------------------Â Abstract Composites are often exposed to harsh loading conditions. This may lead to crack formation and propagation. In this paper an algorithm is described to predict the path of pre-existing cracks in homogeneous
Flexible Path Planning Using Corridor Maps Mark Overmars, Ioannis Karamouzas, and Roland Geraerts
Geraerts, R.J.
to tackle it. (See [1, 2] for an overview.) These algorithms were mainly developed in the field of robotics such paths must be able to handle hundreds of characters in real-time and must be flexible. The Corridor Map such paths must be able to handle hundreds of characters in real-time and must be flexible to e.g. avoid
DYNAMITE: an efficient automatic test pattern generation system for path delay faults
Karl Fuchs; Franz Fink; Michael H. Schulz
1991-01-01
The authors present DYNAMITE, a versatile and efficient automatic test pattern generation system for path delay fault. Based upon a ten-valued and a three-valued logic, the deterministic test pattern generation algorithm incorporated in DYNAMITE is capable of generating both robust and nonrobust tests for path delay faults. Particular emphasis has been placed on coping with the main disadvantage of the
DATA-PATH AND MEMORY ERROR COMPENSATION TECHNIQUE FOR LOW POWER JPEG IMPLEMENTATION
Kambhampati, Subbarao
DATA-PATH AND MEMORY ERROR COMPENSATION TECHNIQUE FOR LOW POWER JPEG IMPLEMENTATION Yunus Emre effects of data- path and memory errors in JPEG implementations. These errors are mainly caused by voltage and derive a probability distribution of the total number of errors. We propose an algorithm
USING JET ROUTES TO MODEL PATH RE-ROUTING IN THE NATIONAL AIRSPACE SYSTEM
Malloy, Brian
USING JET ROUTES TO MODEL PATH RE-ROUTING IN THE NATIONAL AIRSPACE SYSTEM Brian A. Malloy #3; Dean Class Diagram, Object-oriented, Floyd's algorithm, Jet routes, Fix, Airport Fix, National Airspace that the majority of air traÆc must negotiate. These paths, or jet routes, intersect at navigation points or #12;xes
Bloom Filter-based XML Packets Filtering for Millions of Path Queries
Xueqing Gong; Ying Yan; Weining Qian; Aoying Zhou
2005-01-01
The filtering of XML data is the basis of many complex applications. Lots of algorithms have been proposed to solve this problem(2, 3, 5, 6, 7, 8, 9, 11, 12, 13, 18). One important challenge is that the number of path queries is huge. It is necessary to take an efficient data structure rep- resenting path queries. Another challenge is
A Specialized Particle Swarm Optimization for global path planning of mobile robots
Qing Li; Yong Tang; Lijun Wang; Chao Zhang; Yixin Yin
2010-01-01
A specialized global path planning algorithm for mobile robot based on Guaranteed Convergence Particle Swarm Optimization (GCPSO) is proposed. An environmental map was set up and a path connecting the start node and the goal node was coded as a particle. Then, a particular “active region” for particles was mapped out according to the location of obstacles. The initial particle
Path planning and control for multiple point surveillance by an unmanned aircraft in wind
Timothy G. McGee; J. Karl Hedrick
2006-01-01
In this paper, we explore the surveillance of multiple waypoints by a constant velocity aircraft in the presence of wind. It is assumed that the aircraft has a maximum turning rate and that the wind is equal to a known constant plus small possibly time varying components. The proposed strategy consists of separate path planning and control algorithms. The path
Region-based Approach for Determining the Optimal Path Using PSO
Nair, Dr T R Gopalakrishnan; Shetty, Ms Deepthi D; Hegde, Ms Prapthi; Hegde, Ms Anusha
2011-01-01
Many research works have been carried out recently to find the optimal path in network routing. Among them the evolutionary algorithms is an area where work is carried out extensively. We in this paper, have used PSO for finding the optimal path and the concept of region based network is introduced along with the use of indirect encoding. A comparative study of genetic algorithm (GA) and particle swarm optimization (PSO) is carried out, and it was found that PSO performed better than GA.
Rajeev Motwani; Prabhakax Raghavan
1995-01-01
The last decade has witnessed a tremendous growth in the area of randomized algorithms.During this period, randomized algorithms went from being a tool in computational number theory to finding widespread application in many types of algorithms. Two benefits of randomization have spearheaded this growth: simplicity and speed. For many applications, a randomized algorithm is the simplest algorithm available, or the
NASA Technical Reports Server (NTRS)
Mehhtz, Peter
2005-01-01
JPF is an explicit state software model checker for Java bytecode. Today, JPF is a swiss army knife for all sort of runtime based verification purposes. This basically means JPF is a Java virtual machine that executes your program not just once (like a normal VM), but theoretically in all possible ways, checking for property violations like deadlocks or unhandled exceptions along all potential execution paths. If it finds an error, JPF reports the whole execution that leads to it. Unlike a normal debugger, JPF keeps track of every step how it got to the defect.
Bleakley, Hoyt; Lin, Jeffrey
2012-05-01
We examine portage sites in the U.S. South, Mid-Atlantic, and Midwest, including those on the fall line, a geomorphological feature in the southeastern U.S. marking the final rapids on rivers before the ocean. Historically, waterborne transport of goods required portage around the falls at these points, while some falls provided water power during early industrialization. These factors attracted commerce and manufacturing. Although these original advantages have long since been made obsolete, we document the continuing importance of these portage sites over time. We interpret these results as path dependence and contrast explanations based on sunk costs interacting with decreasing versus increasing returns to scale. PMID:23935217
NSDL National Science Digital Library
The well known Berkeley Digital Library SunSite, discussed in the February 9, 1996 Scout Report, has recently added a new resource to its collection. The PATH database, maintained by the Harmer E. Davis Transportation Library at the University of California, is "the world's largest bibliographical database pertaining to Intelligent Transportation Systems (ITS)." It is searchable and browsable (Browse by ITS Thesaurus Term), and contains over 9,000 records and abstracts "including monographs, journal articles, conference papers, technical reports, theses and selected media coverage," dating back to the 1940s.
Bleakley, Hoyt; Lin, Jeffrey
2012-01-01
We examine portage sites in the U.S. South, Mid-Atlantic, and Midwest, including those on the fall line, a geomorphological feature in the southeastern U.S. marking the final rapids on rivers before the ocean. Historically, waterborne transport of goods required portage around the falls at these points, while some falls provided water power during early industrialization. These factors attracted commerce and manufacturing. Although these original advantages have long since been made obsolete, we document the continuing importance of these portage sites over time. We interpret these results as path dependence and contrast explanations based on sunk costs interacting with decreasing versus increasing returns to scale. PMID:23935217
AH Cam: A metal-rich RR Lyrae star with the shortest known Blazhko period
NASA Technical Reports Server (NTRS)
Smith, Horace A.; Matthews, Jaymie M.; Lee, Kevin M.; Williams, Jeffrey; Silbermann, N. A.; Bolte, Michael
1994-01-01
Analysis of 746 new V-band observations of the RR Lyrae star AH Cam obtained during 1989 - 1992 clearly show that its light curve cannot be described by a single period. In fact, at first glance, the Fourier spectrum of the photometry resembles that of a double-mode pulsator, with peaks at a fundamental period of 0.3686 d and an apparent secondary period of 0.2628 d. Nevertheless, the dual-mode solution is a poor fit to the data. Rather, we believe that AH Cam is a single-mode RR Lyrae star undergoing the Blazhko effect: periodic modulation of the amplitude and shape of its light curve. What was originally taken to be the period of the second mode is instead the 1-cycle/d alias of a modulation sidelobe in the Fourier spectrum. The data are well described by a modulation period of just under 11 d, which is the shortest Blazhko period reported to date in the literature and confirms the earlier suggestion by Goranskii. A low-resolution spectrum of AH Cam indicates that it is relatively metal rich, with delta-S less than or = 2. Its high metallicity and short modulation period may provide a critical test of at least one theory for the Blazhko effect. Moskalik's internal resonance model makes specific predictions of the growth rate of the fundamental model vs fundamental period. AH Cam falls outside the regime of other known Blazhko variables and resonance model predictions, but these are appropriate for metal-poor RR Lyrae stars. If the theory matches the behavior of AH Cam for a metal-rich stellar model, this would bolster the resonance hypothesis.
Shortest Loops are Pacemakers in Random Networks of Electrically Coupled Axons
Vladimirov, Nikita; Tu, Yuhai; Traub, Roger D.
2012-01-01
High-frequency oscillations (HFOs) are an important part of brain activity in health and disease. However, their origins remain obscure and controversial. One possible mechanism depends on the presence of sparsely distributed gap junctions that electrically couple the axons of principal cells. A plexus of electrically coupled axons is modeled as a random network with bi-directional connections between its nodes. Under certain conditions the network can demonstrate one of two types of oscillatory activity. Type I oscillations (100–200?Hz) are predicted to be caused by spontaneously spiking axons in a network with strong (high conductance) gap junctions. Type II oscillations (200–300?Hz) require no spontaneous spiking and relatively weak (low-conductance) gap junctions, across which spike propagation failures occur. The type II oscillations are reentrant and self-sustained. Here we examine what determines the frequency of type II oscillations. Using simulations we show that the distribution of loop lengths is the key factor for determining frequency in type II network oscillations. We first analyze spike failure between two electrically coupled cells using a model of anatomically reconstructed CA1 pyramidal neuron. Then network oscillations are studied by a cellular automaton model with random network connectivity, in which we control loop statistics. We show that oscillation periods can be predicted from the network’s loop statistics. The shortest loop, around which a spike can travel, is the most likely pacemaker candidate. The principle of one loop as a pacemaker is remarkable, because random networks contain a large number of loops juxtaposed and superimposed, and their number rapidly grows with network size. This principle allows us to predict the frequency of oscillations from network connectivity and visa versa. We finally propose that type I oscillations may correspond to ripples, while type II oscillations correspond to so-called fast ripples. PMID:22514532
Iwamoto, Takahiro; Slanina, Zdenek; Mizorogi, Naomi; Guo, Jingdong; Akasaka, Takeshi; Nagase, Shigeru; Takaya, Hikaru; Yasuda, Nobuhiro; Kato, Tatsuhisa; Yamago, Shigeru
2014-10-27
[11]Cycloparaphenylene ([11]CPP) selectively encapsulates La@C82 to form the shortest possible metallofullerene-carbon nanotube (CNT) peapod, La@C82 ?[11]CPP, in solution and in the solid state. Complexation in solution was affected by the polarity of the solvent and was 16?times stronger in the polar solvent nitrobenzene than in the nonpolar solvent 1,2-dichlorobenzene. Electrochemical analysis revealed that the redox potentials of La@C82 were negatively shifted upon complexation from free La@C82 . Furthermore, the shifts in the redox potentials increased with polarity of the solvent. These results are consistent with formation of a polar complex, (La@C82 )(?-) ?[11]CPP(?+) , by partial electron transfer from [11]CPP to La@C82 . This is the first observation of such an electronic interaction between a fullerene pea and CPP pod. Theoretical calculations also supported partial charge transfer (0.07) from [11]CPP to La@C82 . The structure of the complex was unambiguously determined by X-ray crystallographic analysis, which showed the La atom inside the C82 near the periphery of the [11]CPP. The dipole moment of La@C82 was projected toward the CPP pea, nearly perpendicular to the CPP axis. The position of the La atom and the direction of the dipole moment in La@C82 ?[11]CPP were significantly different from those observed in La@C82 ?CNT, thus indicating a difference in orientation of the fullerene peas between fullerene-CPP and fullerene-CNT peapods. These results highlight the importance of pea-pea interactions in determining the orientation of the metallofullerene in metallofullerene-CNT peapods. PMID:25224281
Counting Depth Zero Patterns in Ballot Paths
Niederhausen, Heinrich
Counting Depth Zero Patterns in Ballot Paths Heinrich Niederhausen and Shaun Sullivan Florida it to the enu- meration of certain lattice paths. The lattice paths we consider are ballot paths. A ballot path is a path that stays weakly above the diagonal y = x, starts at the origin, and takes steps from the set f
Minimum Cuts and Shortest Non-Separating Cycles via Homology Covers
Erickson, Jeff
the recent algorithm of Cabello et al. [SOCG 2010] for all g = o(log n). The second is a combinatorial studied, the first nontrivial results for directed graphs were only recently published by Cabello et al
K. J. Kyriakopoulos; G. N. Saridis
1988-01-01
A simple method of trajectory generation of robot manipulators is presented. It is based on an optimal control problem formulation. The jerk, the third derivative of position, of the desired trajectory, adversely affect the efficiency of the control algorithms and therefore should be minimized. assuming joint position, velocity and acceleration to be constrained, a cost criterion containing jerk is considered.
Light transport on path-space manifolds
NASA Astrophysics Data System (ADS)
Jakob, Wenzel Alban
The pervasive use of computer-generated graphics in our society has led to strict demands on their visual realism. Generally, users of rendering software want their images to look, in various ways, "real", which has been a key driving force towards methods that are based on the physics of light transport. Until recently, industrial practice has relied on a different set of methods that had comparatively little rigorous grounding in physics---but within the last decade, advances in rendering methods and computing power have come together to create a sudden and dramatic shift, in which physics-based methods that were formerly thought impractical have become the standard tool. As a consequence, considerable attention is now devoted towards making these methods as robust as possible. In this context, robustness refers to an algorithm's ability to process arbitrary input without large increases of the rendering time or degradation of the output image. One particularly challenging aspect of robustness entails simulating the precise interaction of light with all the materials that comprise the input scene. This dissertation focuses on one specific group of materials that has fundamentally been the most important source of difficulties in this process. Specular materials, such as glass windows, mirrors or smooth coatings (e.g. on finished wood), account for a significant percentage of the objects that surround us every day. It is perhaps surprising, then, that it is not well-understood how they can be accommodated within the theoretical framework that underlies some of the most sophisticated rendering methods available today. Many of these methods operate using a theoretical framework known as path space integration. But this framework makes no provisions for specular materials: to date, it is not clear how to write down a path space integral involving something as simple as a piece of glass. Although implementations can in practice still render these materials by side-stepping limitations of the theory, they often suffer from unusably slow convergence; improvements to this situation have been hampered by the lack of a thorough theoretical understanding. We address these problems by developing a new theory of path-space light transport which, for the first time, cleanly incorporates specular scattering into the standard framework. Most of the results obtained in the analysis of the ideally smooth case can also be generalized to rendering of glossy materials and volumetric scattering so that this dissertation also provides a powerful new set of tools for dealing with them. The basis of our approach is that each specular material interaction locally collapses the dimension of the space of light paths so that all relevant paths lie on a submanifold of path space. We analyze the high-dimensional differential geometry of this submanifold and use the resulting information to construct an algorithm that is able to "walk" around on it using a simple and efficient equation-solving iteration. This manifold walking algorithm then constitutes the key operation of a new type of Markov Chain Monte Carlo (MCMC) rendering method that computes lighting through very general families of paths that can involve arbitrary combinations of specular, near-specular, glossy, and diffuse surface interactions as well as isotropic or highly anisotropic volume scattering. We demonstrate our implementation on a range of challenging scenes and evaluate it against previous methods.
Hardwick, R D
1989-01-01
The design and implementation of an Intrusion Path Analysis (IPA) function came about as a result of the upgrades to the security systems at the Savannah River Site (SRS), near Aiken, South Carolina. The stated requirements for IPA were broad, leaving opportunity for creative freedom during design and development. The essential elements were that it: be based on alarm and sensor state data; consider insider as well as outsider threats; be flexible and easily enabled or disabled; not be processor intensive; and provide information to the operator in the event the analysis reveals possible path openings. The final design resulted from many and varied conceptual inputs, and will be implemented in selected test areas at SRS. It fulfils the requirements and: allows selective inclusion of sensors in the analysis; permits the formation of concentric rings of protection around assets; permits the defining of the number of rings which must be breached before issuing an alert; evaluates current sensor states as well as a recent, configurable history of sensor states; considers the sensors' physical location, with respect to the concentric rings; and enables changes for maintenance without software recompilation. 3 figs.
NASA Technical Reports Server (NTRS)
2008-01-01
[figure removed for brevity, see original site] Click on the image for movie of Phoenix's Path to Mars
This artist's animation shows the route NASA's Phoenix Mars Lander took to get from Earth to Mars. The spacecraft's path is shown in yellow, and the orbits of Mars and Earth are shown in red and blue, respectively.
Phoenix was launched from Cape Canaveral Air Force Station, Fla., on Aug. 4, 2007, when Earth and Mars were 195 million kilometers (121 million miles) apart. It will have traveled a total of 679 million kilometers (422 million miles) when it is scheduled to reach Mars on May 25, 2008. At that time, Earth and Mars will be farther apart, at 276 million kilometers (171 million miles).
The Phoenix Mission is led by the University of Arizona, Tucson, on behalf of NASA. Project management of the mission is by NASA's Jet Propulsion Laboratory, Pasadena, Calif. Spacecraft development is by Lockheed Martin Space Systems, Denver
Algorithms for Solving Rubik's Cubes
Demaine, Erik D; Eisenstat, Sarah; Lubiw, Anna; Winslow, Andrew
2011-01-01
The Rubik's Cube is perhaps the world's most famous and iconic puzzle, well-known to have a rich underlying mathematical structure (group theory). In this paper, we show that the Rubik's Cube also has a rich underlying algorithmic structure. Specifically, we show that the n x n x n Rubik's Cube, as well as the n x n x 1 variant, has a "God's Number" (diameter of the configuration space) of Theta(n^2/log n). The upper bound comes from effectively parallelizing standard Theta(n^2) solution algorithms, while the lower bound follows from a counting argument. The upper bound gives an asymptotically optimal algorithm for solving a general Rubik's Cube in the worst case. Given a specific starting state, we show how to find the shortest solution in an n x O(1) x O(1) Rubik's Cube. Finally, we show that finding this optimal solution becomes NP-hard in an n x n x 1 Rubik's Cube when the positions and colors of some of the cubies are ignored (not used in determining whether the cube is solved).
Critical Path-Based Thread Placement for NUMA Systems
Su, C Y; Li, D; Nikolopoulos, D S; Grove, M; Cameron, K; de Supinski, B R
2011-11-01
Multicore multiprocessors use a Non Uniform Memory Architecture (NUMA) to improve their scalability. However, NUMA introduces performance penalties due to remote memory accesses. Without efficiently managing data layout and thread mapping to cores, scientific applications, even if they are optimized for NUMA, may suffer performance loss. In this paper, we present algorithms and a runtime system that optimize the execution of OpenMP applications on NUMA architectures. By collecting information from hardware counters, the runtime system directs thread placement and reduces performance penalties by minimizing the critical path of OpenMP parallel regions. The runtime system uses a scalable algorithm that derives placement decisions with negligible overhead. We evaluate our algorithms and runtime system with four NPB applications implemented in OpenMP. On average the algorithms achieve between 8.13% and 25.68% performance improvement compared to the default Linux thread placement scheme. The algorithms miss the optimal thread placement in only 8.9% of the cases.
Computing Path Tables for Quickest Multipaths In Computer Networks
Grimmell, W.C.
2004-12-21
We consider the transmission of a message from a source node to a terminal node in a network with n nodes and m links where the message is divided into parts and each part is transmitted over a different path in a set of paths from the source node to the terminal node. Here each link is characterized by a bandwidth and delay. The set of paths together with their transmission rates used for the message is referred to as a multipath. We present two algorithms that produce a minimum-end-to-end message delay multipath path table that, for every message length, specifies a multipath that will achieve the minimum end-to-end delay. The algorithms also generate a function that maps the minimum end-to-end message delay to the message length. The time complexities of the algorithms are O(n{sup 2}((n{sup 2}/logn) + m)min(D{sub max}, C{sub max})) and O(nm(C{sub max} + nmin(D{sub max}, C{sub max}))) when the link delays and bandwidths are non-negative integers. Here D{sub max} and C{sub max} are respectively the maximum link delay and maximum link bandwidth and C{sub max} and D{sub max} are greater than zero.
Path integrals on curved manifolds
NASA Astrophysics Data System (ADS)
Grosche, C.; Steiner, F.
1987-12-01
A general framework for treating path integrals on curved manifolds is presented. We also show how to perform general coordinate and space-time transformations in path integrals. The main result is that one has to subtract a quantum correction ?V˜ h 2 from the classical Lagrangian ?, i.e. the correct effective Lagrangian to be used in the path integral is ?eff = ?- ?V. A general prescription for calculating the quantum correction ? V is given. It is based on a canonical approach using Weyl-ordering and the Hamiltonian path integral defined by the midpoint prescription. The general framework is illustrated by several examples: The d-dimensional rotator, i.e. the motion on the sphere S d-1, the path integral in d-dimensional polar coordinates, the exact treatment of the hydrogen atom in R 2 and R 3 by performing a Kustaanheimo-Stiefel transformation, the Langer transformation and the path integral for the Morse potential.
Iterative path attacks on networks
NASA Astrophysics Data System (ADS)
Pu, Cunlai; Li, Siyuan; Michaelson, Andrew; Yang, Jian
2015-08-01
We investigate a path-attack process on model networks and real-world networks. Based on the local topological structure of a path, we propose an attack centrality measure with a control parameter ? for quantifying the influence of a path. In the path-attack process, we iteratively remove the path with the largest attack centrality from a network. Results demonstrate that, for a specific network, there is an optimal ? which results in maximum attack efficiency. The denser and more homogeneous the networks, the more robust the networks are against iterative path attacks. Our work helps to explain the vulnerability of networks and provides some clues about the protection and design of real complex systems.
Interactive cutting path analysis programs
NASA Technical Reports Server (NTRS)
Weiner, J. M.; Williams, D. S.; Colley, S. R.
1975-01-01
The operation of numerically controlled machine tools is interactively simulated. Four programs were developed to graphically display the cutting paths for a Monarch lathe, Cintimatic mill, Strippit sheet metal punch, and the wiring path for a Standard wire wrap machine. These programs are run on a IMLAC PDS-ID graphic display system under the DOS-3 disk operating system. The cutting path analysis programs accept input via both paper tape and disk file.
Handbook of Feynman Path Integrals
NASA Astrophysics Data System (ADS)
Grosche, Christian, Steiner, Frank
The Handbook of Feynman Path Integrals appears just fifty years after Richard Feynman published his pioneering paper in 1948 entitled "Space-Time Approach to Non-Relativistic Quantum Mechanics", in which he introduced his new formulation of quantum mechanics in terms of path integrals. The book presents for the first time a comprehensive table of Feynman path integrals together with an extensive list of references; it will serve the reader as a thorough introduction to the theory of path integrals. As a reference book, it is unique in its scope and will be essential for many physicists, chemists and mathematicians working in different areas of research.
Path Integration in Conical Space
Akira Inomata; Georg Junker
2011-11-24
Quantum mechanics in conical space is studied by the path integral method. It is shown that the curvature effect gives rise to an effective potential in the radial path integral. It is further shown that the radial path integral in conical space can be reduced to a form identical with that in flat space when the discrete angular momentum of each partial wave is replaced by a specific non-integral angular momentum. The effective potential is found proportional to the squared mean curvature of the conical surface embedded in Euclidean space. The path integral calculation is compatible with the Schr\\"odinger equation modified with the Gaussian and the mean curvature.
A fast algorithm for finding dominators in a flowgraph
Thomas Lengauer; Robert Endre Tarjan
1979-01-01
A fast algorithm for finding dominators in a flowgraph is presented. The algorithm uses depth-first search and an efficient method of computing functions defined on paths in trees. A simple implementation of the algorithm runs in O(m log n) time, where m is the number of edges and n is the number of vertices in the problem graph. A more
A Hybrid Fault-Tolerant Algorithm for MPLS Networks
Georgiou, Chryssis
A Hybrid Fault-Tolerant Algorithm for MPLS Networks Maria Hadjiona, Chryssis Georgiou, Maria Papa maintaining, algorithm for use in MPLS based networks. The novelty of the algorithm lies upon the fact that it is the first to employ both path restoration mechanisms typically used in MPLS networks: protection switching