Shortest Path Algorithm What is the Shortest Path Problem?
Razak, Saquib
at vertex B: The resulting vertex-weighted graph is: #12;Data structures required · The implementation. · The method returns a vertex-weighted Digraph from which the shortest path from s to any vertex can be found;What is the shortest path problem? · In an edge-weighted graph, the weight of an edge measures the cost
A shortest path algorithm for mobile satellite communication network
Zhang Tao; Zhang Jun; Liu Zhong Kan
2005-01-01
Mobile satellite network is a special time-varying network. Some classical network theories used in the current terrestrial networks, such as the shortest path algorithm, cannot be applied to it availably. In this paper, based on the proposed model of mobile satellite network, the classical shortest path algorithm of fixed topological network, such as the Dijkstra algorithm, is proved to be
A near linear shortest path algorithm for weighted undirected graphs
Muhammad Aasim Qureshi; Mohd Fadzil Hassan; Sohail Safdar; Rehan Akbar
2011-01-01
This paper presents an algorithm for Shortest Path Tree (SPT) problem. The presented algorithm is an improvement over a previously published work of the authors. The effort is put in to improve the running\\/execution time of the SPT problem. Introduced improvement is simple and easy to incorporate in to the existing algorithm. This algorithm uses Depth First Search (DFS) like
Two Phase Shortest Path Algorithm for Nonnegative Weighted Undirected Graphs
Muhammad Aasim Qureshi; Mohd Fadzil Hassan; Sohail Safdar; Rehan Akbar
2010-01-01
Abstract-Breadth First Search (BFS) can calculate the shortest path for un-weighted graphs very efficiently but when it comes to non-negative weighted graphs it fails at a point when a successor updates a predecessor. Such nodes are being referred as Culprit nodes in this research. These Culprit nodes are the ones that cause error in shortest path in an algorithm that
Materialization Trade-Offs in Hierarchical Shortest Path Algorithms
Shashi Shekhar; Andrew Fetterer; Bjajesh Goyal
1997-01-01
Materialization and hierarchical routing algorithms are becoming important tools in querying databases for the shortest paths in time-critical applications like Intelligent Transportation Systems (ITS), due to the growing size of their spatial graph databases [16]. A hierarchical routing algorithm decomposes the original graph into a set of fragment graphs and a boundary graph which summarizes the fragment graphs. A fully
An Improved Physarum polycephalum Algorithm for the Shortest Path Problem
Wang, Qing; Adamatzky, Andrew; Chan, Felix T. S.; Mahadevan, Sankaran
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
Parallel Shortest Path Algorithms for Solving Large-Scale Instances
Kamesh Madduri; David A. Bader; Jonathan W. Berry; Bruce A. Hendrickson
We present an experimental study of parallel algorithms for solving the single source shortest path problem with non-negative edge weights (NSSP) on large-scale graphs. We implement Meyer and Sander's ?-stepping algorithm and report performance re- sults on the Cray MTA-2, a multithreaded parallel architecture. The MTA-2 is a high-end shared memory system offering two unique features that aid the efficient
Multiple Object Tracking Using the Shortest Path Faster Association Algorithm
Liu, Heping; Liu, Huaping; Yang, Bin
2014-01-01
To solve the persistently multiple object tracking in cluttered environments, this paper presents a novel tracking association approach based on the shortest path faster algorithm. First, the multiple object tracking is formulated as an integer programming problem of the flow network. Then we relax the integer programming to a standard linear programming problem. Therefore, the global optimum can be quickly obtained using the shortest path faster algorithm. The proposed method avoids the difficulties of integer programming, and it has a lower worst-case complexity than competing methods but better robustness and tracking accuracy in complex environments. Simulation results show that the proposed algorithm takes less time than other state-of-the-art methods and can operate in real time. PMID:25215322
Distributed Shortest Paths Algorithms (Extended Abstract)
Rao, Satish
is an orientation of G(V, E), i.e. (i + j) E i? implies that (i - j) E E. Those problems appear to be fairly basic communication net- work. For the problem of Breadth First Search, the best previously known algorithms required is the diameter.) This constitutes a major step towards achieving the lower bounds, which are 0(E) communication
An edge-wise linear shortest path algorithm for non negative weighted undirected graphs
Muhammad Aasim Qureshi; Mohd Fadzil Hassan; Sohail Safdar; Rehan Akbar; Rabia Sammi
2009-01-01
In most of the shortest path problems like vehicle routing problems and network routing problems, we only need an efficient path between two points---source and destination, and it is not necessary to calculate the shortest path from source to all other nodes. This paper concentrates on this very idea and presents an algorithm for calculating shortest path for nonnegative weighted
Quantum algorithms for shortest paths problems in structured instances
Aran Nayebi; Virginia Vassilevska Williams
2014-10-23
We consider the quantum time complexity of the all pairs shortest paths (APSP) problem and some of its variants. The trivial classical algorithm for APSP and most all pairs path problems runs in $O(n^3)$ time, while the trivial algorithm in the quantum setting runs in $\\tilde{O}(n^{2.5})$ time, using Grover search. A major open problem in classical algorithms is to obtain a truly subcubic time algorithm for APSP, i.e. an algorithm running in $O(n^{3-\\varepsilon})$ time for constant $\\varepsilon>0$. To approach this problem, many truly subcubic time classical algorithms have been devised for APSP and its variants for structured inputs. Some examples of such problems are APSP in geometrically weighted graphs, graphs with small integer edge weights or a small number of weights incident to each vertex, and the all pairs earliest arrivals problem. In this paper we revisit these problems in the quantum setting and obtain the first nontrivial (i.e. $O(n^{2.5-\\varepsilon})$ time) quantum algorithms for the problems.
An Optimal Algorithm for L1 Shortest Paths Among Obstacles in the Plane
Mitchell, Joseph S.B.
orientation" metric, yielding an O(n log n ) approximation algorithm for finding Euclidean shortest pathsAn Optimal Algorithm for L1 Shortest Paths Among Obstacles in the Plane (Draft) Joseph S. B 11794-3600 jsbm@ams.sunysb.edu Abstract We present an optimal (n log n) algorithm for determining
An Experimental Study of a Parallel Shortest Path Algorithm for Solving Large-Scale Graph Instances
Bader, David A.
shortest path problem with non-negative edge weights (NSSP) on large- scale graphs using the -stepping with competitive sequential algorithms, for low-diameter sparse graphs. For instance, -stepping on a directed scaleAn Experimental Study of a Parallel Shortest Path Algorithm for Solving Large-Scale Graph Instances
Inverse shortest path algorithms in protected UMTS access networks
István Gódor; János Harmatos; Alpár Jüttner
2005-01-01
In this paper, the application questions of OSPF (Open Shortest Path First) routing protocols in the all{IP based protected UMTS (Universal Mobile Telecommunications System) access networks is inves- tigated. The basic problem here is how the OSPF administrative weights should be adjusted in an ade- quate way, resulting near{optimal overall network per- formance both in nominal network operation and in
Computing almost shortest paths
Michael Elkin
2005-01-01
We study the s-sources almost shortest paths(abbreviated s-ASP) problem. Given an unweightedgraph G = (V,E),and a subset S ? Vof s nodes, the goal is to compute almostshortest paths between all the pairs of nodes S× V. We devise an algorithm withrunning timeO(∣E∣n?+ s ·n1 + ?)for this problem that computes the pathsPu,wfor all pairs (u,w) ?S × V such
Geometric Shortest Path Containers
Dorothea Wagner; Thomas Willhalm; Christos Zaroliagis
2004-01-01
In this paper, we consider Dijkstra's algorithm for the single source single target shortest path problem in large sparse graphs. The goal is to reduce the response time for on-line queries by using precomputed information. Due to the size of the graph, preprocessing space requirements can be only linear in the number of nodes. We assume that a layout of
The Bellman-Ford algorithm Most basic shortest-paths algorithm for the shortest-path problem
Bai, Zhaojun
the "lightest" or "closest" vertex in V - S to insert into S #12;The SSSP in DAG DAG: can have negative-weight negative-weight edges Compute d[v] and [v] for all v V d[v] = (s, v): the shortest-path weight from the source s to v. [v]: the parent (predecessor) of v. Return TRUE if no negative-weight cycles reachable
A Faster Algorithm for the Single Source Shortest Path Problem with Few Distinct Positive Lengths
Orlin, James B.
In this paper, we propose an efficient method for implementing Dijkstra's algorithm for the Single Source Shortest Path Problem (SSSPP) in a graph whose edges have positive length, and where there are few distinct edge ...
An Evaluation of Potentials of Genetic Algorithm in Shortest Path Problem
NASA Astrophysics Data System (ADS)
Hassany Pazooky, S.; Rahmatollahi Namin, Sh; Soleymani, A.; Samadzadegan, F.
2009-04-01
One of the most typical issues considered in combinatorial systems in transportation networks, is the shortest path problem. In such networks, routing has a significant impact on the network's performance. Due to natural complexity in transportation networks and strong impact of routing in different fields of decision making, such as traffic management and vehicle routing problem (VRP), appropriate solutions to solve this problem are crucial to be determined. During last years, in order to solve the shortest path problem, different solutions are proposed. These techniques are divided into two categories of classic and evolutionary approaches. Two well-known classic algorithms are Dijkstra and A*. Dijkstra is known as a robust, but time consuming algorithm in finding the shortest path problem. A* is also another algorithm very similar to Dijkstra, less robust but with a higher performance. On the other hand, Genetic algorithms are introduced as most applicable evolutionary algorithms. Genetic Algorithm uses a parallel search method in several parts of the domain and is not trapped in local optimums. In this paper, the potentiality of Genetic algorithm for finding the shortest path is evaluated by making a comparison between this algorithm and classic algorithms (Dijkstra and A*). Evaluation of the potential of these techniques on a transportation network in an urban area shows that due to the problem of classic methods in their small search space, GA had a better performance in finding the shortest path.
An Experimental Study of a Parallel Shortest Path Algorithm for Solving Large-Scale Graph Instances
Hutter, Frank
of the single source short- est path problem with non-negative edge weights (NSSP) on large-scale graphs using with competitive sequential algorithms, for low-diameter sparse graphs. For instance, -stepping on a directed scaleAn Experimental Study of a Parallel Shortest Path Algorithm for Solving Large-Scale Graph Instances
A O(E) Time Shortest Path Algorithm For Non Negative Weighted Undirected Graphs
Qureshi, Muhammad Aasim; Safdar, Sohail; Akbar, Rehan
2009-01-01
In most of the shortest path problems like vehicle routing problems and network routing problems, we only need an efficient path between two points source and destination, and it is not necessary to calculate the shortest path from source to all other nodes. This paper concentrates on this very idea and presents an algorithm for calculating shortest path for (i) nonnegative weighted undirected graphs (ii) unweighted undirected graphs. The algorithm completes its execution in O(E) for all graphs except few in which longer path (in terms of number of edges) from source to some node makes it best selection for that node. The main advantage of the algorithms is its simplicity and it does not need complex data structures for implementations.
Circular Shortest Path on Regular Grids
Changming Sun; Stefano Pallottino Csiro
2002-01-01
Shortest path algorithms have been used for a number of applications such as crack detection, road orlinear feature extraction on images. There are applications where the starting and ending positionsof the shortest path needs to be constrained. In this paper, we presents several new algorithms forthe extraction of a circular shortest path within an image such that the starting and
Shortest Paths in Euclidean Graphs
Robert Sedgewick; Jeffrey Scott Vitter
1986-01-01
We analyze a simple method for finding shortest paths inEuclidean graphs (where vertices are points in a Euclidean space and edge weights are Euclidean distances between points). For many graph\\u000a models, the average running time of the algorithm to find the shortest path between a specified pair of vertices in a graph\\u000a withV vertices andE edges is shown to beO(V)
Disambiguating Road Names in Text Route Descriptions using Exact-All-Hop Shortest Path Algorithm
Klippel, Alexander
Disambiguating Road Names in Text Route Descriptions using Exact-All-Hop Shortest Path Algorithm issues involved, road name disambiguation is the most important, because one road name can refer to more than one road. Compared with traditional toponym (place name) disambiguation, the challenges
Dynamic Shortest Paths Containers
Dorothea Wagner; Thomas Willhalm; Christos D. Zaroliagis
2004-01-01
Using a set of geometric containers to speed up shortest path queries in a weighted graph has been proven a useful tool for dealing with large sparse graphs. Given a layout of a graph G = (V; E), we store, for each edge (u; v) 2 E, the bounding box of all nodes t 2 V for which a shortest
Finding splitting lines for touching cell nuclei with a shortest path algorithm.
Bai, Xiangzhi; Wang, Peng; Sun, Changming; Zhang, Yu; Zhou, Fugen; Meng, Cai
2014-10-22
A shortest path-based algorithm is proposed in this paper to find splitting lines for touching cell nuclei. First, an initial splitting line is obtained through the distance transform of a marker image and the watershed algorithm. The initial splitting line is then separated into different line segments as necessary, and the endpoint positions of these line segments are adjusted to the concave points on the contour. Finally, a shortest path algorithm is used to find the accurate splitting line between the starting-point and the end-point, and the final split can be achieved by the contour of the touching cell nuclei and the splitting lines. Comparisons of experimental results show that the proposed algorithm is effective for segmentation of different types of touching cell nuclei. PMID:25458811
Muhammad Aasim Qureshi; Mohd Fadzil Hassan; Sohail Safdar; Rehan Akbar; Rabia Sammi
2010-01-01
Shortest path and related problems have been a very hot topic for researchers since Dijekstra devised his first shortest path algorithm. In transportation and communication routing, during the execution of system, failure of any link needs robust and most effective recovery. In such problems we need some recovery mechanism and\\/or plan for the continuation of the process with minimum or
An Efficient Shortest Triangle Paths Algorithm Applied to Multi-camera Self-calibration
Ferid Bajramovic; Marcel Brückner; Joachim Denzler
We propose a novel minimum uncertainty approach to relative pose selection for multi-camera self-calibration. We show how\\u000a this discrete global optimization problem can be expressed as a shortest triangle paths problem. For the latter, we present\\u000a an efficient algorithm and prove its correctness. It has several advantages compared to a similar approach of Vergés-Llahí,\\u000a Moldovan and Wada. In quantitative experiments
Parallel shortest augmenting path algorithm for the assignment problem. Technical report
Balas, E.; Miller, D.; Pekny, J.; Toth, P.
1989-04-01
We describe a parallel version of the shortest augmenting path algorithm for the assignment problem. While generating the initial dual solution and partial assignment in parallel does not require substantive changes in the sequential algorithm, using several augmenting paths in parallel does require a new dual variable recalculation method. The parallel algorithm was tested on a 14-processor Butterfly Plus computer, on problems with up to 900 million variables. The speedup obtained increases with problem size. The algorithm was also embedded into a parallel branch and bound procedure for the traveling salesman problem on a directed graph, which was tested on the Butterfly Plus on problems involving up to 7,500 cities. To our knowledge, these are the largest assignment problems and traveling salesman problems solved so far.
Shortest Path Problems on a Polyhedral Surface
Atlas F. Cook; Carola Wenk
2009-01-01
We develop algorithms to compute edge sequences, Voronoi diagrams, shortest path maps, the Fréchet distance, and the diameter for a polyhedral surface. Dis- tances on the surface are measured either by the length of a Euclidean shortest path or by link distance.
Zhang, Jian; Jiang, Min; Yuan, Fei; Feng, Kai-Yan; Cai, Yu-Dong; Xu, Xun; Chen, Lei
2013-01-01
This study attempted to find novel age-related macular degeneration (AMD) related genes based on 36 known AMD genes. The well-known shortest path algorithm, Dijkstra's algorithm, was applied to find the shortest path connecting each pair of known AMD related genes in protein-protein interaction (PPI) network. The genes occurring in any shortest path were considered as candidate AMD related genes. As a result, 125 novel AMD genes were predicted. The further analysis based on betweenness and permutation test indicates that there are 10 genes involved in the formation or development of AMD and may be the actual AMD related genes with high probability. We hope that this contribution would promote the study of age-related macular degeneration and discovery of novel effective treatments. PMID:24455700
Nair, T R Gopalakrishnan; Yashoda, M B
2011-01-01
In Internet Routing, the static shortest path (SP) problem has been addressed using well known intelligent optimization techniques like artificial neural networks, genetic algorithms (GAs) and particle swarm optimization. Advancement in wireless communication lead more and more mobile wireless networks, such as mobile networks [mobile ad hoc networks (MANETs)] and wireless sensor networks. Dynamic nature of the network is the main characteristic of MANET. Therefore, the SP routing problem in MANET turns into dynamic optimization problem (DOP). Here the nodes ae made aware of the environmental condition, thereby making it intelligent, which goes as the input for GA. The implementation then uses GAs with immigrants and memory schemes to solve the dynamic SP routing problem (DSPRP) in MANETS. In our paper, once the network topology changes, the optimal solutions in the new environment can be searched using the new immigrants or the useful information stored in the memory. Results shows GA with new immigrants sho...
Highway Hierarchies Hasten Exact Shortest Path Queries
Peter Sanders; Dominik Schultes
2005-01-01
\\u000a We present a new speedup technique for route planning that exploits the hierarchy inherent in real world road networks. Our\\u000a algorithm preprocesses the eight digit number of nodes needed for maps of the USA or Western Europe in a few hours using linear\\u000a space. Shortest (i.e. fastest) path queries then take around eight milliseconds to produce exact shortest paths. This
Goal Directed Shortest Path Queries Using Precomputed Cluster Distances
Matijevic, Domagoj
of starting and end point as well as the length of the shortest connection between each pair of clusters[v] algorithm removes the closest node u, settles Dijkstra's algorithm for shortest path queries can be accelerated by using precomputed shortest path
Dynamic Shortest Paths Containers Dorothea Wagnera,1
Zaroliagis, Christos D.
of nodes. In [17], angular sectors were introduced to speed up the processing of such shortest path queries of Patras, 26500 Patras, Greece Abstract Using a set of geometric containers to speed up shortest path is quite large (though sparse), and hence space requirements are only acceptable to be linear in the number
Shortest path and Schramm-Loewner Evolution
NASA Astrophysics Data System (ADS)
Posé, N.; Schrenk, K. J.; Araújo, N. A. M.; Herrmann, H. J.
2014-06-01
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.
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 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
Yang, Shengxiang
) problem has been well addressed using intelligent optimization techniques, e.g., artificial neural, they will be effective in fixed infrastructure wireless or wired networks. But, they exhibit unacceptably high Networks Hui Cheng, Shengxiang Yang Member, IEEE Abstract-- In recent years, the static shortest path (SP
Analysis of Algorithms Problem Set no. 3 --Dynamic All-Pairs Shortest Paths
Zwick, Uri
of the graph. Show that there can be at most O(zn2) locally historical paths passing through a given vertex v. Guidance: Showing that there are at most O(zn2) such paths that start or end at v is relatively straightforward. The harder part of the proof is showing that there only O(zn2) locally historical paths having v
Paris-Sud XI, Université de
example of a non-holonomic robot is that of a car : assuming 1As we will see below, the optimal path-holonomic robot motion plan- ning 2, 3, 13, 15, 16, 17, 18, 19, 20, 24, 25]. A robot is said to be non wheels of the car is always tangent to the car axis. Though the problem considered in this paper is one
Multi-population Genetic Algorithms with Immigrants Scheme for Dynamic Shortest Path
Yang, Shengxiang
.g., artificial neural networks, genetic algo- rithms (GAs), particle swarm optimization, etc. However intelligence techniques, e.g., artificial neural networks (ANNs) [2], genetic algorithms (GAs) [3, they will be effective in fixed infrastructure wireless or wired networks. But, they exhibit unacceptably high com
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...
Accumulative competition neural network for shortest path tree computation
Ji-Yang Dong; Wen-Jun Wang; Jun-Ying Zhang
2003-01-01
Shortest path tree (SPT) computation is an important combinatorial optimization problem with numerous applications. A novel neural network model called accumulative competition neural network (ACNN) is proposed in this paper to compute the SPT in a given weighted graph. Comparing with the other neural network based search algorithms, the algorithm presented here features in much less number of neurons needed,
Shortest Path Computation with No Information Leakage
Mouratidis, Kyriakos
2012-01-01
Shortest path computation is one of the most common queries in location-based services (LBSs). Although particularly useful, such queries raise serious privacy concerns. Exposing to a (potentially untrusted) LBS the client's position and her destination may reveal personal information, such as social habits, health condition, shopping preferences, lifestyle choices, etc. The only existing method for privacy-preserving shortest path computation follows the obfuscation paradigm; it prevents the LBS from inferring the source and destination of the query with a probability higher than a threshold. This implies, however, that the LBS still deduces some information (albeit not exact) about the client's location and her destination. In this paper we aim at strong privacy, where the adversary learns nothing about the shortest path query. We achieve this via established private information retrieval techniques, which we treat as black-box building blocks. Experiments on real, large-scale road networks assess the pract...
Finding Shortest Path for Developed Cognitive Map Using Medial Axis
Farhan, Hazim A; Al-Ghazi, Suhaib I
2011-01-01
this paper presents an enhancement of the medial axis algorithm to be used for finding the optimal shortest path for developed cognitive map. The cognitive map has been developed, based on the architectural blueprint maps. The idea for using the medial-axis is to find main path central pixels; each center pixel represents the center distance between two side boarder pixels. The need for these pixels in the algorithm comes from the need of building a network of nodes for the path, where each node represents a turning in the real world (left, right, critical left, critical right...). The algorithm also ignores from finding the center pixels paths that are too small for intelligent robot navigation. The Idea of this algorithm is to find the possible shortest path between start and end points. The goal of this research is to extract a simple, robust representation of the shape of the cognitive map together with the optimal shortest path between start and end points. The intelligent robot will use this algorithm i...
Shortest Paths in Microseconds Rachit Agarwal
, the goal is to minimize latency while maintaining feasible memory requirements. We present ASAP, a system that achieves this goal by exploiting the structure of social networks. ASAP preprocesses a given network edges, ASAP computes a shortest path for most node pairs in less than 49 microseconds per pair. ASAP
Optimal Distributed All Pairs Shortest Paths
Optimal Distributed All Pairs Shortest Paths ETH Zurich Distributed Computing Group Stephan Holzer ETH Zürich Roger Wattenhofer ETH Zürich #12;Distributed network Graph G of n nodes 2 4 5 1 3 #12;Distributed network Graph G of n nodes 2 4 5 1 3 Unique IDs #12;Distributed network Graph G of n nodes 2 4 5 1
Using Edge-Valued Decision Diagrams for Symbolic Generation of Shortest Paths
Gianfranco Ciardo; Radu Siminiceanu
2002-01-01
We present a new method for the symbolic construction of shortest paths in reachability graphs. Our algorithm relies on a variant of edge{valued decision diagrams that supports ecien t xed{p oint it- erations for the joint computation of both the reachable states and their distance from the initial states. Once the distance function is known, a shortest path from an
Approximating shortest paths on a convex polytope in three dimensions
Pankaj K. Agarwal; Sariel Har-Peled; Micha Sharir; Kasturi R. Varadarajan
1997-01-01
Given a convex polytope P withn faces in R3, points s,t?6P, and a parameter 0e?1, we present an algorithm that constructs a path on6P from s tot whose length is at most1+edPs,t, where dPs,t is the length of the shortest path betweens andt on 6P. The algorithm runs in Onlog1\\/e+1\\/e3 time, and is relatively simple. The running time isOn+1\\/e3 if
All Pairs Shortest Paths for Graphs with Small Integer Length Edges
Zvi Galil; Oded Margalit
1997-01-01
The authors have solved the all pairs shortest distances (APSD) problem for graphs with integer edge lengths. Our algorithm is subcubic for edge lengths of small (?M) absolute value. In this paper we show how to transform these algorithms to solve the all pairs shortest paths (APSP), in the same time complexity, up to a polylogarithmic factor. Forn=|V| the number
Self-organization and solution of shortest-path optimization problems with memristive networks
Pershin, Yuriy V
2013-01-01
We show that memristive networks-namely networks of resistors with memory-can efficiently solve shortest-path optimization problems. Indeed, the presence of memory (time non-locality) 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.
Implicit Routing And Shortest Path Information
Evangelos Kranakis; Danny Krizanc; Jorge Urrutia
1995-01-01
)Evangelos Kranakisy(kranakis@scs.carleton.ca)Danny Krizancy(krizanc@scs.carleton.ca)Jorge Urrutiazy(jorge@csi.uottawa.ca)AbstractWe study the problem of constructing graphs from shortest path information(complete or partial). Consider graphs with labeled verticesand edges. Given a collection V of vertices and for each u 2 V a positiveinteger d(u), and a family F u = fF u;i : i ! d(u)g of subsets of Vconstruct a graph such that for each u
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
Running Time Analysis of ACO Systems for Shortest Path Problems
NASA Astrophysics Data System (ADS)
Horoba, Christian; Sudholt, Dirk
Ant Colony Optimization (ACO) is inspired by the ability of ant colonies to find shortest paths between their nest and a food source. We analyze the running time of different ACO systems for shortest path problems. First, we improve running time bounds by Attiratanasunthron and Fakcharoenphol [Information Processing Letters, 105(3):88-92, 2008] for single-destination shortest paths and extend their results for acyclic graphs to arbitrary graphs. Our upper bound is asymptotically tight for large evaporation factors, holds with high probability, and transfers to the all-pairs shortest paths problem. There, a simple mechanism for exchanging information between ants with different destinations yields a significant improvement. Our results indicate that ACO is the best known metaheuristic for the all-pairs shortest paths problem.
ON THE ACCELERATION OF SHORTEST PATH CALCULATIONS IN TRANSPORTATION NETWORKS
BAKER, ZACHARY K. [Los Alamos National Laboratory; GOKHALE, MAYA B. [Los Alamos National Laboratory
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.
Traffic Grooming Based on Shortest Path in Optical WDM Mesh Networks
Lee, Tae-Jin
propose Shortest-path First Traffic grooming(SFT) algo- rithm. The comprehensive computer simulation shows-path First Traffic grooming (SFT) algorithm in objective to maximize the network throughput and to minimize together and carried. According to the computer simulation, the SFT algorithm achieves 14% improved
Fast Point-to-Point Shortest Path Computations with Arc-Flags
Moritz Hilger; Rolf H. Mohring; Heiko Schilling
2006-01-01
In this paper, we conduct a detailed study of the arc-flag approach introduced in (Lau97, Lau04). Arc-flags are a modification of Dijkstra's algorithm to accel erate point-to-point (p2p) shortest path computa- tions. The usage of arc-flags avoids exploring unnecessary p aths during shortest path query computations. We present two improvements of the original arc-flag method tha t reduce the pre-calculation
NASA Astrophysics Data System (ADS)
Yu, Feng; Li, Yanjun; Wu, Tie-Jun
2010-02-01
A large number of networks in the real world have a scale-free structure, and the parameters of the networks change stochastically with time. Searching for the shortest paths in a scale-free dynamic and stochastic network is not only necessary for the estimation of the statistical characteristics such as the average shortest path length of the network, but also challenges the traditional concepts related to the “shortest path” of a network and the design of path searching strategies. In this paper, the concept of shortest path is defined on the basis of a scale-free dynamic and stochastic network model, and a temporal ant colony optimization (TACO) algorithm is proposed for searching for the shortest paths in the network. The convergence and the setup for some important parameters of the TACO algorithm are discussed through theoretical analysis and computer simulations, validating the effectiveness of the proposed algorithm.
An Effective Evolutionary Approach for Bicriteria Shortest Path Routing Problems
NASA Astrophysics Data System (ADS)
Lin, Lin; Gen, Mitsuo
Routing problem is one of the important research issues in communication network fields. In this paper, we consider a bicriteria shortest path routing (bSPR) model dedicated to calculating nondominated paths for (1) the minimum total cost and (2) the minimum transmission delay. To solve this bSPR problem, we propose a new multiobjective genetic algorithm (moGA): (1) an efficient chromosome representation using the priority-based encoding method; (2) a new operator of GA parameters auto-tuning, which is adaptively regulation of exploration and exploitation based on the change of the average fitness of parents and offspring which is occurred at each generation; and (3) an interactive adaptive-weight fitness assignment mechanism is implemented that assigns weights to each objective and combines the weighted objectives into a single objective function. Numerical experiments with various scales of network design problems show the effectiveness and the efficiency of our approach by comparing with the recent researches.
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
OBSTACLE-AVOIDING SIMILARITY METRICS AND SHORTEST PATH PROBLEMS
Texas at San Antonio, University of
-AVOIDING SIMILARITY METRICS AND SHORTEST PATH PROBLEMS Atlas F. Cook IV, Ph.D. The University of Texas at San Antonio COMMITTEE: ________________________________________ Carola Wenk, Ph.D., Chair ________________________________________ Tom Bylander, Ph.D. ________________________________________ José Iovino, Ph.D
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.
Traffic-engineering-aware shortest-path routing and its application in IP-over-WDM networks [Invited
NASA Astrophysics Data System (ADS)
Lee, Youngseok; Mukherjee, Biswanath
2004-03-01
Single shortest-path routing is known to perform poorly for Internet traffic engineering (TE) where the typical optimization objective is to minimize the maximum link load. Splitting traffic uniformly over equal-cost multiple shortest paths in open shortest path first and intermediate system-intermediate system protocols does not always minimize the maximum link load when multiple paths are not carefully selected for the global traffic demand matrix. However, a TE-aware shortest path among all the equal-cost multiple shortest paths between each ingress-egress pair can be selected such that the maximum link load is significantly reduced. IP routers can use the globally optimal TE-aware shortest path without any change to existing routing protocols and without any serious configuration overhead. While calculating TE-aware shortest paths, the destination-based forwarding constraint at a node should be satisfied, because an IP router will forward a packet to the next hop toward the destination by looking up the destination prefix. We present a mathematical problem formulation for finding a set of TE-aware shortest paths for the given network as an integer linear program, and we propose a simple heuristic for solving large instances of the problem. Then we explore the usage of our proposed algorithm for the integrated TE method in IP-over-WDM networks. The proposed algorithm is evaluated through simulations in IP networks as well as in IP-over-WDM networks.
Fast Shortest-path Distance Queries on Road Networks by Pruned Highway Labeling
Imai, Hiroshi
Fast Shortest-path Distance Queries on Road Networks by Pruned Highway Labeling Takuya Akiba Yoichi- ferred to as highway-based labelings and a preprocessing algorithm for it named pruned highway labeling to as the highway-based labeling framework and a preprocessing algorithm for the framework named pruned highway
Efficient Algorithms for Shortest Partial Seeds in Words
Lonardi, Stefano
Efficient Algorithms for Shortest Partial Seeds in Words Tomasz Kociumaka1 , Solon P. Pissis2 Algorithms for Shortest Partial Seeds in Words 1/16 #12;Periodicity and quasiperiodicity Periodicity. Wale Efficient Algorithms for Shortest Partial Seeds in Words 2/16 #12;Periodicity and quasiperiodicity
Ramaswamy, Ramkumar
2004-12-10
This paper addresses sensitivity analysis questions concerning the shortest path problem and the maximum capacity path problem in an undirected network. For both problems, we determine the maximum and ...
122 IEEE COMMUNICATIONS LETTERS, VOL. 8, NO. 2, FEBRUARY 2004 Finding All Hops Shortest Paths
Ansari, Nirwan
122 IEEE COMMUNICATIONS LETTERS, VOL. 8, NO. 2, FEBRUARY 2004 Finding All Hops Shortest Paths Gang a new problem referred to as the All Hops Shortest Paths (AHSP) problem. The AHSP problem involves selecting, for all hop counts, the shortest paths from a given source to any other node in a network. We
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 approach to shortest paths on networks based on the quantum bosonic mechanism
NASA Astrophysics Data System (ADS)
Jiang, Xin; Wang, Hailong; Tang, Shaoting; Ma, Lili; Zhang, Zhanli; Zheng, Zhiming
2011-01-01
This paper presents quantum bosonic shortest path searching (QBSPS), a natural, practical and highly heuristic physical algorithm for reasoning about the recognition of network structure via quantum dynamics. QBSPS is based on an Anderson-like itinerant bosonic system in which a boson's Green function is used as a navigation pointer for one to accurately approach the terminals. QBSPS is demonstrated by rigorous mathematical and physical proofs and plenty of simulations, showing how it can be used as a greedy routing to seek the shortest path between different locations. In methodology, it is an interesting and new algorithm rooted in the quantum mechanism other than combinatorics. In practice, for the all-pairs shortest-path problem in a random scale-free network with N vertices, QBSPS runs in O(?(N) ln ln N) time. In application, we suggest that the corresponding experimental realizations are feasible by considering path searching in quantum optical communication networks; in this situation, the method performs a pure local search on networks without requiring the global structure that is necessary for current graph algorithms.
Algorithms for the Shortest and Closest Lattice Vector Problems
Hanrot, Guillaume
Algorithms for the Shortest and Closest Lattice Vector Problems Guillaume Hanrot and Xavier Pujol of the art solvers of the Shortest and Closest Lattice Vector Problems in the Euclidean norm. We recall the three main families of algorithms for these problems, namely the algo- rithm by Micciancio and Voulgaris
Finding Shortest Paths on Terrains by Killing Two Birds with One Stone
Wong, Raymond Chi-Wing
) of the terrain via shortest terrain paths. Other applications include robot path planning for unmanned vehicles. Such queries all rely on an important operation, that of finding shortest surface distances. However, shortest surface dis- tance computation is very time consuming. We propose techniques that enable efficient
Shortest Path Refinement for Motion Estimation from Tagged MR Images
Liu, Xiaofeng; Prince, Jerry L.
2013-01-01
Magnetic resonance tagging makes it possible to measure the motion of tissues such as muscles in the heart and tongue. The harmonic phase (HARP) method largely automates the process of tracking points within tagged MR images, permitting many motion properties to be computed. However, HARP tracking can yield erroneous motion estimates due to: (1) large deformations between image frames; (2) through-plane motion; and (3) tissue boundaries. Methods that incorporate the spatial continuity of motion—so-called refinement or floodfilling methods—have previously been reported to reduce tracking errors. This paper presents a new refinement method based on shortest path computations. The method uses a graph representation of the image and seeks an optimal tracking order from a specified seed to each point in the image by solving a single source shortest path problem. This minimizes the potential errors for those path dependent solutions that are found in other refinement methods. In addition to this, tracking in the presence of through-plane motion is improved by introducing synthetic tags at the reference time (when the tissue is not deformed). Experimental results on both tongue and cardiac images show that the proposed method can track the whole tissue more robustly and is also computationally efficient. PMID:20304720
Backbones and borders from shortest-path trees
NASA Astrophysics Data System (ADS)
Grady, Daniel; Thiemann, Christian; Brockmann, Dirk
2011-03-01
One of the most important tasks in complex network research is to distinguish between vertices and edges that are topologically essential and those that are not. To this end, a variety of vertex and edge centrality measures have been introduced, ranging from measuring local properties (degree, strength) to quantities that depend on the global structure of the graph (betweenness). Here we introduce a novel technique based on the family of shortest-path trees, which is applicable to strongly heterogeneous networks. This approach can identify significant edges in the network, distinct from conventional edge betweenness, and these edges make up a network backbone relevant to dynamical processes that evolve on such networks. We will show that important network structures can be extracted by investigating the similarity and differences of shortest-path trees and show that tree dissimilarity in combination with hierarchical clustering can identify communities in heterogeneous networks more successfully than ordinary reciprocal-weight distance measures. We demonstrate the success of this technique on complex multi-scale mobility networks.
Report SYCON91-10 SHORTEST PATHS FOR THE REEDS-SHEPP CAR
Sussmann, Hector
Report SYCON91-10 SHORTEST PATHS FOR THE REEDS-SHEPP CAR: A WORKED OUT EXAMPLE OF THE USE the shortest paths for a model of a car that can move forwards and backwards. This problem was discussed to derive some of the properties of the minimum paths of the Reeds-Shepp car, cf. [7]. 2 This author's work
Pomelo: accurate and decentralized shortest-path distance estimation in social graphs
Zhuo Chen; Yang Chen; Cong Ding; Beixing Deng; Xing Li
2011-01-01
Computing the shortest-path distances between nodes is a key problem in analyzing social graphs. Traditional methods like breadth-first search (BFS) do not scale well with graph size. Recently, a Graph Coordinate System, called Orion, has been proposed to estimate shortest-path distances in a scalable way. Orion uses a landmark-based approach, which does not take account of the shortest-path distances between
CS 105: Algorithms (Grad) Solving Shortest Superstring via Set Cover
Chakrabarti, Amit
CS 105: Algorithms (Grad) Solving Shortest Superstring via Set Cover Khanh Do Ba Feb 24, 2005 1 Recap: Minimum Set Cover Recall the (Weighted) Set Cover problem, defined as follows. Set Cover Problem. First, the algorithm is as follows. Algorithm 1: GreedySetCover(X, F) C - 1 U - X2 while U = do3 Find
Membrane Boundary Extraction Using a Circular Shortest Path Technique
NASA Astrophysics Data System (ADS)
Sun, Changming; Vallotton, Pascal; Wang, Dadong; Lopez, Jamie; Ng, Yvonne; James, David
2007-11-01
Membrane proteins represent over 50% of known drug targets. Accordingly, several widely used assays in the High Content Analysis area rely on quantitative measures of the translocation of proteins between intracellular organelles and the cell surface. In order to increase the sensitivity of these assays, one needs to measure the signal specifically along the membrane, requiring a precise segmentation of this compartment. Doing this manually is a very time-consuming practice, limited to an academic setting. Manual tracing of the membrane compartment also confronts us with issues of objectivity and reproducibility. In this paper, we present an approach based on a circular shortest path technique that enables us to segment the membrane compartment accurately and rapidly. This feature is illustrated using cells expressing epitope-tagged membrane proteins.
Pomelo: Accurate and Decentralized Shortest-path Distance Estimation in Social Graphs
Hong, Jason I.
Pomelo: Accurate and Decentralized Shortest-path Distance Estimation in Social Graphs Zhuo Chen1 the graph structure well. In this paper, we propose Pomelo, which calculates the graph coordinates in a decentralized manner. Every node in Pomelo computes its shortest-path distances to both nearby neighbors
PHA*: Finding the Shortest Path with A* in An Unknown Physical Environment
Ben-Yair, A; Kraus, S; Netanyahu, N; Stern, R; 10.1613/jair.1373
2011-01-01
We address the problem of finding the shortest path between two points in an unknown real physical environment, where a traveling agent must move around in the environment to explore unknown territory. We introduce the Physical-A* algorithm (PHA*) for solving this problem. PHA* expands all the mandatory nodes that A* would expand and returns the shortest path between the two points. However, due to the physical nature of the problem, the complexity of the algorithm is measured by the traveling effort of the moving agent and not by the number of generated nodes, as in standard A*. PHA* is presented as a two-level algorithm, such that its high level, A*, chooses the next node to be expanded and its low level directs the agent to that node in order to explore it. We present a number of variations for both the high-level and low-level procedures and evaluate their performance theoretically and experimentally. We show that the travel cost of our best variation is fairly close to the optimal travel cost, assuming t...
Color texture classification using shortest paths in graphs.
de Mesquita Sa Junior, Jarbas Joaci; Cortez, Paulo Cesar; Backes, Andre Ricardo
2014-09-01
Color textures are among the most important visual attributes in image analysis. This paper presents a novel method to analyze color textures by modeling a color image as a graph in two different and complementary manners (each color channel separately and the three color channels altogether) and by obtaining statistical moments from the shortest paths between specific vertices of this graph. Such an approach allows to create a set of feature vectors, which were extracted from VisTex, USPTex, and TC00013 color texture databases. The best classification results were 99.07%, 96.85%, and 91.54% (LDA with leave-one-out), 87.62%, 66.71%, and 88.06% (1NN with holdout), and 98.62%, 96.16%, and 91.34% (LDA with holdout) of success rate (percentage of samples correctly classified) for these three databases, respectively. These results prove that the proposed approach is a powerful tool for color texture analysis to be explored. PMID:24988594
A New GPU-based Approach to the Shortest Path Problem
Llanos, Diego R.
. Llanos, and Arturo Gonzalez-Escribano Dept. Inform´atica, Universidad de Valladolid, Spain. {hector|yuri.torresA New GPU-based Approach to the Shortest Path Problem Hector Ortega-Arranz, Yuri Torres, Diego R
Reliability Theory Model and Expected Life Shortest Path in Stochastic and Time-Dependent Networks
Guo-zhen Tan; Xiang-fu Xia; Wen Gao
2003-01-01
We consider the priori expected shortest path problem from a single origin to a single destination for each departure time\\u000a in stochastic and time-dependent networks. Such problem requires more than standard shortest path techniques. First, we transform\\u000a this problem into the problem of systemic reliability, and identify a weaker consistent reliability condition that insures\\u000a the validity of generalized dynamic-programming method
Shortest-path and hot-potato routing on unbuffered 2-D tori
Miltos D. Grammatikakis; Miro Kraetzl; Eric Fleury
1997-01-01
We probabilistically model dynamic routing on unbuffered 2-dimensional tori. We consider shortest-path routing with packet loss and retransmissions versus a newly proposed all-link busy (ALB) hot-potato routing strategy with packet deflections. Computations of the sustained packet generating rate, node throughput, and average packet latency indicate that the proposed ALB strategy is a much better alternative to a shortest-path routing on
Traffic-engineering-aware shortest-path routing and its application in IP-over-WDM networks [Invited
Youngseok Lee; Biswanath Mukherjee
2004-01-01
Single shortest-path routing is known to perform poorly for Internet traffic engineering (TE) where the typical optimization objective is to minimize the maximum link load. Splitting traffic uniformly over equal-cost multiple shortest paths in open shortest path first and intermediate system-intermediate system protocols does not always minimize the maximum link load when multiple paths are not carefully selected for the
Su, Ran; Sun, Changming; Zhang, Chao; Pham, Tuan D
2014-12-01
Dendritic spines are tiny membranous protrusions from neuron's dendrites. They play a very important role in the nervous system. A number of mental diseases such as Alzheimer's disease and mental retardation are revealed to have close relations with spine morphologies or spine number changes. Spines have various shapes, and spine images are often not of good quality; hence it is very challenging to detect spines in neuron images. This paper presents a novel pipeline to detect dendritic spines in 2D maximum intensity projection (MIP) images and a new dendrite backbone extraction method is developed in the pipeline. The strategy for the backbone extraction approach is that it iteratively refines the extraction result based on directional morphological filtering and improved Hessian filtering until a satisfactory extraction result is obtained. A shortest path method is applied along a backbone to extract the boundary of the dendrites. Spines are then segmented from the dendrites outside the extracted boundary. Touching spines will be split using a marker-controlled watershed algorithm. We present the results of our algorithm on real images and compare our algorithm with two other spine detection methods. The results show that the proposed approach can detect dendrites and spines more accurately. Measurements and classification of spines are also made in this paper. PMID:25155696
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.
Li, Longxiang; Gong, Jianhua; Zhou, Jieping
2014-01-01
Effective assessments of air-pollution exposure depend on the ability to accurately predict pollutant concentrations at unmonitored locations, which can be achieved through spatial interpolation. However, most interpolation approaches currently in use are based on the Euclidean distance, which cannot account for the complex nonlinear features displayed by air-pollution distributions in the wind-field. In this study, an interpolation method based on the shortest path distance is developed to characterize the impact of complex urban wind-field on the distribution of the particulate matter concentration. In this method, the wind-field is incorporated by first interpolating the observed wind-field from a meteorological-station network, then using this continuous wind-field to construct a cost surface based on Gaussian dispersion model and calculating the shortest wind-field path distances between locations, and finally replacing the Euclidean distances typically used in Inverse Distance Weighting (IDW) with the shortest wind-field path distances. This proposed methodology is used to generate daily and hourly estimation surfaces for the particulate matter concentration in the urban area of Beijing in May 2013. This study demonstrates that wind-fields can be incorporated into an interpolation framework using the shortest wind-field path distance, which leads to a remarkable improvement in both the prediction accuracy and the visual reproduction of the wind-flow effect, both of which are of great importance for the assessment of the effects of pollutants on human health. PMID:24798197
Edge Congestion of Shortest Path Systems for All-to-All Communication
Charles M. Fiduccia; Paul J. Hedrick
1997-01-01
The problem of choosing a static shortest-path system that minimizes maximum edge congestion in a network is studied. Bounds based on parameters, such as diameter, bisection width, and average distance, are derived and conditions for producing uniform congestion on all edges are explored. Trees are shown to have maximum congestion on edges that are incident to a centroid node. Cartesian
IE 170 Laboratory 8: Shortest Paths Drs. T.K. Ralphs and R.T. Berger
Ralphs, Ted
and generality of graph search in solving many important problems. 3. Understand the importance of object-oriented design and code re-use. 4. Understand the importance of and application of the shortest path problem. 1.4 Design and Analysis In this lab, you will recycle source code from two previous labs to implement
Li, Longxiang; Gong, Jianhua; Zhou, Jieping
2014-01-01
Effective assessments of air-pollution exposure depend on the ability to accurately predict pollutant concentrations at unmonitored locations, which can be achieved through spatial interpolation. However, most interpolation approaches currently in use are based on the Euclidean distance, which cannot account for the complex nonlinear features displayed by air-pollution distributions in the wind-field. In this study, an interpolation method based on the shortest path distance is developed to characterize the impact of complex urban wind-field on the distribution of the particulate matter concentration. In this method, the wind-field is incorporated by first interpolating the observed wind-field from a meteorological-station network, then using this continuous wind-field to construct a cost surface based on Gaussian dispersion model and calculating the shortest wind-field path distances between locations, and finally replacing the Euclidean distances typically used in Inverse Distance Weighting (IDW) with the shortest wind-field path distances. This proposed methodology is used to generate daily and hourly estimation surfaces for the particulate matter concentration in the urban area of Beijing in May 2013. This study demonstrates that wind-fields can be incorporated into an interpolation framework using the shortest wind-field path distance, which leads to a remarkable improvement in both the prediction accuracy and the visual reproduction of the wind-flow effect, both of which are of great importance for the assessment of the effects of pollutants on human health. PMID:24798197
Stochastic Shortest Path MDPs with Dead Ends Andrey Kolobov Mausam Daniel S. Weld
Mausam
, weld}@cs.washington.edu Dept of Computer Science and Engineering University of Washington Seattle, USAStochastic Shortest Path MDPs with Dead Ends Andrey Kolobov Mausam Daniel S. Weld {akolobov, mausam with in many real-world planning problems, be it sending a rover on Mars or navigating a robot in a building
Do People Use the Shortest Path? Empirical Test of Wardrop's First
Levinson, David M.
(10). Zhu, Shanjiang, David Levinson and Henry Liu, Measuring Winners and Losers from New I 35W Mississippi (67%) #12;#12;Diversity in Commute Route (Source: Zhu and Levinson 2010b) #12;Conclusions · MajorityDo People Use the Shortest Path? Empirical Test of Wardrop's First Principle Shanjiang Zhu, Ph
Shortest Traversal Path of n Circles in Layered Manufacturing Applications
Chang-chien Chou; Yu-kumg Chen; Shuo-yan Chou
2007-01-01
Layered manufacturing in rapid prototyping is to fabricate prototype by using a laser beam to trace the cross-sectional contours of a product layer by layer. Such cross-sections of geometrical objects differ by layers and generally have more than one continuous contour in each layer. In an attempt to facilitate an efficient approach for path planning, the problem is simplified by
Solution Methods for the Multi-trip Elementary Shortest Path ...
2011-03-15
algorithm-specific details of the computational experiments and presents computational results ... Figure 1 displays a visualization of a pricing problem and its solution. ...... European Journal of Operational Research, 100:180–191, 1997.
Watershed Cuts: Thinnings, Shortest Path Forests, and Topological Watersheds
Jean Cousty; Gilles Bertrand; Laurent Najman; Michel Couprie
2010-01-01
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
A Specific Genetic Algorithm for Optimum Path Planning in Intelligent Transportation System
Qing Li; Guangjun Liu; Wei Zhang; Cailu Zhao; Yixin Yin; Zhiliang Wang
2006-01-01
A specific genetic algorithm is proposed in this paper for optimum path planning. Operations such as encoding, crossover and mutation are tailored to fit optimum path planning. Simulation results show that the specific genetic algorithm has advantages such as rapid calculation speed and high probability of optimal solution. It is a new approach for solving shortest path problems in practical
Path Planning Algorithm for Vehicles Based on Time-dependent Optimization Criterion
Qing Li; Sijiang Xie; Xinhai Tong; Guangjun Liu
2007-01-01
A specialized genetic algorithm is proposed in this paper for path planning of vehicles based on time-dependent optimization criterion. A variable signal encoding scheme is adopted to represent the path and a particular fitness function is investigated for time-dependent shortest path planning. Domain heuristic knowledge based crossover, mutation and deletion operators are also specifically designed to fit the vehicle path
Transitive functional annotation by shortest-path analysis of gene expression data
Zhou, Xianghong; Kao, Ming-Chih J.; Wong, Wing Hung
2002-01-01
Current methods for the functional analysis of microarray gene expression data make the implicit assumption that genes with similar expression profiles have similar functions in cells. However, among genes involved in the same biological pathway, not all gene pairs show high expression similarity. Here, we propose that transitive expression similarity among genes can be used as an important attribute to link genes of the same biological pathway. Based on large-scale yeast microarray expression data, we use the shortest-path analysis to identify transitive genes between two given genes from the same biological process. We find that not only functionally related genes with correlated expression profiles are identified but also those without. In the latter case, we compare our method to hierarchical clustering, and show that our method can reveal functional relationships among genes in a more precise manner. Finally, we show that our method can be used to reliably predict the function of unknown genes from known genes lying on the same shortest path. We assigned functions for 146 yeast genes that are considered as unknown by the Saccharomyces Genome Database and by the Yeast Proteome Database. These genes constitute around 5% of the unknown yeast ORFome. PMID:12196633
NASA Astrophysics Data System (ADS)
Sun, Yu; Dai, Meifeng; Xi, Lifeng
Recent work on the networks has focused on the weighted hierarchical networks that are significantly different from the un-weighted hierarchical networks. In this paper we study a family of weighted hierarchical networks which are recursively defined from an initial uncompleted graph, in which the weights of edges have been assigned to different values with certain scale. Firstly, we study analytically the average weighted shortest path (AWSP) on the weighted hierarchical networks. Using a recursive method, we determine explicitly the AWSP. The obtained rigorous solution shows that the networks grow unbounded but with the logarithm of the network size, while the weighted shortest paths stay bounded. Then, depending on a biased random walk, we research the mean first-passage time (MFPT) between a hub node and any peripheral node. Finally, we deduce the analytical expression of the average of MFPTs for a random walker originating from any node to first visit to a hub node, which is named as the average receiving time (ART). The obtained result shows that ART is bounded or grows sublinearly with the network order relating to the number of initial nodes and the weighted factor or grows quadratically with the iteration.
The tomography of human mobility -- what do shortest-path trees reveal?
NASA Astrophysics Data System (ADS)
Grady, Daniel; Thiemann, Christian; Brockmann, Dirk
2010-03-01
Similar to illustrating the anatomy of organs using pictures of tissue slices taken at various depths, we construct shortest-path trees of different nodes to create a tomogram of large-scale mobility networks. This tomography allows us to measure global properties of the system conditioned on a reference location in the network to gain a fuller characterization of a node. Using this technqiue, we discovered a new symmetry that characterizes a large class of mobility networks. Furthermore, introducing the notion of tree similarity, we devised a new technique for clustering nodes with similar topological footprint, yielding a new, unique and efficient method for community identification in these networks and extracting their topological backbone. We applied these methods to a multi-scale human mobility network obtained from the dollar-bill-tracking site wheresgoerge.com and to the U.S. and world-wide air transportation network.
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
Chao-Ying Bai; Xiao-Ping Tang; Rui Zhao
2009-01-01
Grid-cell based schemes for tracing seismic arrivals, such as the finite difference eikonal equation solver or the shortest path method (SPM), are conventionally confined to locating first arrivals only. However, later arrivals are numerous and sometimes of greater amplitude than the first arrivals, making them valuable information, with the potential to be used for precise earthquake location, high-resolution seismic tomography,
Morita, Yusuke; Ogihara, Naomichi; Kanai, Takashi; Suzuki, Hiromasa
2013-08-01
Three-dimensional geometric morphometric techniques have been widely used in quantitative comparisons of craniofacial morphology in humans and nonhuman primates. However, few anatomical landmarks can actually be defined on the neurocranium. In this study, an alternative method is proposed for defining semi-landmarks on neurocranial surfaces for use in detailed analysis of cranial shape. Specifically, midsagittal, nuchal, and temporal lines were approximated using Bezier curves and equally spaced points along each of the curves were defined as semi-landmarks. The shortest paths connecting pairs of anatomical landmarks as well as semi-landmarks were then calculated in order to represent the surface morphology between landmarks using equally spaced points along the paths. To evaluate the efficacy of this method, the previously outlined technique was used in morphological analysis of sexual dimorphism in modern Japanese crania. The study sample comprised 22 specimens that were used to generate 110 anatomical semi-landmarks, which were used in geometric morphometric analysis. Although variations due to sexual dimorphism in human crania are very small, differences could be identified using the proposed landmark placement, which demonstrated the efficacy of the proposed method. PMID:23868177
CS 105: Algorithms (Grad) Set Cover and Application to Shortest Superstring
Chakrabarti, Amit
CS 105: Algorithms (Grad) Set Cover and Application to Shortest Superstring Valika K. Wan & Khanh Do Ba Feb 21-24, 2005 1 Approximating Set Cover 1.1 Definition An Instance (X, F) of the set-covering a minimum size subset C F whose members cover all of X. X = SC S (1) The cost of the set-covering
Shortest Path Discovery Problems: A Framework, Algorithms and Experimental Results
Szepesvari, Csaba
with execution like in real-time search, etc. Recently there has been a growing interest in incremental search assumptions made on the underlying search graph one gets fundamentally different problem types: the graph may of estimates of the cost- to-go function like in heuristic search, or the search might be interleaved
Path and Trajectory Diversity Theory and Algorithms
Branicky, Michael S.
Path and Trajectory Diversity Theory and Algorithms Ross A. Knepper International Conference. Kuffner #12;R.A. Knepper Path and Trajectory Diversity 2 Applications [Knepper and Mason, ISER, 2008][Lau and Trajectory Diversity 3 Not all path sets are created equal Introduction Conclusion
Curvature-Constrained Shortest Paths in a Convex Polygon (Extended Abstract)
Paris-Sud XI, Université de
naturally when the point robot models a real-world robot with a mini- mum turning radius; see for example Therese Biedl Sylvain Lazard Steve Robbins§ Subhash Suri¶ Sue Whitesides Abstract Let B be a point robot in robotics, involves planning a collision-free path for a robot moving amid obstacles, and has been widely
'Mini small worlds' of shortest link paths crossing domain boundaries in an academic Web space
Lennart Björneborn
2006-01-01
Summary Combining webometric and social network analytic approaches, this study developed a methodology to sample and identify Web\\u000a links, pages, and sites that function as small-world connectors affecting short link distances along link paths between different\\u000a topical domains in an academic Web space. The data set comprised 7669 subsites harvested from 109 UK universities. A novel\\u000a corona-shaped Web graph model revealed
All-Pairs Shortest Paths for Unweighted Undirected Graphs in o(mn) Time
Chan, Timothy M.
well-known examples of log-factor speedup was Arlazarov et al.'s (a.k.a. the \\four-Russians") algorithm with n vertices and m edges. We present new algorithms with the following running times: 8 log 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
Shortest paths for differential drive robots under visibility and sensor constraints
Jean-Bernard Hayet; Rafael Murrieta-Cid
Abstract—This article revisits the problem,of planning,short- est paths in terms of distance in the plane (i.e., not in time) for the differential drive robot (DDR) in the absence,of obstacles. We complete,the existing works,by explaining,and,deepening the remarks,made,recently in the literature [10] that exhibited more,cases that what,was,thought,until then. Motivated by that work, we show that there cannot be more than 4-word trajectories
Geometric SpeedUp Techniques for Finding Shortest Paths in Large Sparse Graphs
Dorothea Wagner; Thomas Willhalm
2003-01-01
In this paper, we consider Dijkstra's algorithm for the single source single target shortestpaths problem in large sparse graphs. The goal is to reduce the response time for onlinequeries by using precomputed information. For the result of the preprocessing, we admit atmost linear space. We assume that a layout of the graph is given. From this layout, in thepreprocessing, we
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.
NASA Astrophysics Data System (ADS)
Forkert, Nils Daniel; Schmidt-Richberg, Alexander; Säring, Dennis; Illies, Till; Fiehler, Jens; Handels, Heinz
2010-03-01
Exact segmentations of the cerebrovascular system are the basis for several medical applications, like preoperation planning, postoperative monitoring and medical research. Several automatic methods for the extraction of the vascular system have been proposed. These automatic approaches suffer from several problems. One of the major problems are interruptions in the vascular segmentation, especially in case of small vessels represented by low intensities. These breaks are problematic for the outcome of several applications e.g. FEM-simulations and quantitative vessel analysis. In this paper we propose an automatic post-processing method to connect broken vessel segmentations. The approach proposed consists of four steps. Based on an existing vessel segmentation the 3D-skeleton is computed first and used to detect the dead ends of the segmentation. In a following step possible connections between these dead ends are computed using a graph based approach based on the vesselness parameter image. After a consistency check is performed, the detected paths are used to obtain the final segmentation using a level set approach. The method proposed was validated using a synthetic dataset as well as two clinical datasets. The evaluation of the results yielded by the method proposed based on two Time-of-Flight MRA datasets showed that in mean 45 connections between dead ends per dataset were found. A quantitative comparison with semi-automatic segmentations by medical experts using the Dice coefficient revealed that a mean improvement of 0.0229 per dataset was achieved. In summary the approach presented can considerably improve the accuracy of vascular segmentations needed for following analysis steps.
Improved genetic algorithms based optimum path planning for mobile robot
Soh Chin Yun; Veleppa Ganapathy; Lim Ooi Chong
2010-01-01
Improved genetic algorithms incorporate other techniques, methods or algorithms to optimize the performance of genetic algorithm. In this paper, improved genetic algorithms of optimum path planning for mobile robot navigation are proposed. An Obstacle Avoidance Algorithm (OAA) and a Distinguish Algorithm (DA) are introduced to generate the initial population in order to improve the path planning efficiency to select only
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.
Incremental Multi-Scale Search Algorithm for Dynamic Path Planning With Low Worst-Case Complexity.
Lu, Yibiao; Huo, Xiaoming; Arslan, Oktay; Tsiotras, Panagiotis
2011-06-16
Path-planning (equivalently, path-finding) problems are fundamental in many applications, such as transportation, VLSI design, robot navigation, and many more. In this paper, we consider dynamic shortest path-planning problems on a graph with a single endpoint pair and with potentially changing edge weights over time. Several algorithms exist in the literature that solve this problem, notably among them the Lifelong Planning A(?) (LPA(?)) algorithm. The LPA(?) algorithm is an incremental search algorithm that replans the path when there are changes in the environment. In numerical experiments, however, it was observed that the performance of LPA(?) is sensitive in the number of vertex expansions required to update the graph when an edge weight value changes or when a vertex is added or deleted. Although, in most cases, the classical LPA(?) requires a relatively small number of updates, in some other cases the amount of work required by the LPA(?) to find the optimal path can be overwhelming. To address this issue, in this paper, we propose an extension of the baseline LPA(?) algorithm, by making efficient use of a multiscale representation of the environment. This multiscale representation allows one to quickly localize the changed edges, and subsequently update the priority queue efficiently. This incremental multiscale LPA(?) ( m-LPA(?) for short) algorithm leads to an improvement both in terms of robustness and computational complexity-in the worst case-when compared to the classical LPA(?). Numerical experiments validate the aforementioned claims. PMID:21690015
Symbolic Shortest Path Planning
Morik, Katharina
efficiency, the paper analyzes the locality for weighted problem graphs and show that it matches the duplicate detection scope in best-first search graphs. Cost-optimal plans for compiled competition benchmark breadth- first to best-first search graphs. We show how to combine a set of disjoint weighted symbolic
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 their ability to follow the reaction path and to reproducethe curvature along the path. I. INTRODUCTION
An Overview of Autonomous Mobile Robot Path Planning Algorithms
N. Sariff; N. Buniyamin
2006-01-01
Determination of a collision free path for a robot between start and goal positions through obstacles cluttered in a workspace is central to the design of an autonomous robot path planning. This paper presents an overview of autonomous mobile robot path planning focusing on algorithms that produce an optimal path for a robot to navigate in an environment. To complete
Multiple paths extraction in images using a constrained expanded trellis.
Sun, Changming; Appleton, Ben
2005-12-01
Single shortest path extraction algorithms have been used in a number of areas such as network flow and image analysis. In image analysis, shortest path techniques can be used for object boundary detection, crack detection, or stereo disparity estimation. Sometimes one needs to find multiple paths as opposed to a single path in a network or an image where the paths must satisfy certain constraints. In this paper, we propose a new algorithm to extract multiple paths simultaneously within an image using a constrained expanded trellis (CET) for feature extraction and object segmentation. We also give a number of application examples for our multiple paths extraction algorithm. PMID:16355660
Multi-objective stochastic path planning
Dasgupta, Sumantra
2009-05-15
of multiple objectives and stochastic edge parameters. 2. Identify candidate constraints where clustering based multi-level programming can be applied to eliminate infeasible edges. 3. Provide an exact O (V.E) algorithm for building redundant shortest paths. 4...
Path Planning Algorithm for Extinguishing Forest Fires
Kumar, M P Sivaram
2012-01-01
One of the major impacts of climatic changes is due to destroying of forest. Destroying of forest takes place in many ways but the majority of the forest is destroyed due to wild forest fires. In this paper we have presented a path planning algorithm for extinguishing fires which uses Wireless Sensor and Actor Networks (WSANs) for detecting fires. Since most of the works on forest fires are based on Wireless Sensor Networks (WSNs) and a collection of work has been done on coverage, message transmission, deployment of nodes, battery power depletion of sensor nodes in WSNs we focused our work in path planning approach of the Actor to move to the target area where the fire has occurred and extinguish it. An incremental approach is presented in order to determine the successive moves of the Actor to extinguish fire in an environment with and without obstacles. This is done by comparing the moves determined with target location readings obtained using sensors until the Actor reaches the target area to extinguish f...
Stability of multi-path dual congestion control algorithms
Thomas Voice
2006-01-01
ó This paper investigates fair, scalable, stable con- gestion controls which achieve high bandwidth utilisation over networks operating multi-path routing. The aim is to take ad- vantage of path diversity to achieve efcient bandwidth allocation without causing instability. Two multi-path extensions to the class of dual algorithms are considered. The rst is a natural extension previously proposed in the literature,
Dynamic Path Planning of Mobile Robots Based on ABC Algorithm
Qianzhi Ma; Xiujuan Lei
2010-01-01
\\u000a For the global path planning of mobile robot under the dynamic uncertain environment, a path planning method combined time\\u000a rolling window strategy and artificial bee colony (ABC) algorithm was proposed. To meet the real time requirement, the global\\u000a path was replaced by local paths within a series of rolling windows. Due to the ability of global optimization, and rapid\\u000a convergence
An Integer Programming Algorithm for Routing Optimization in IP Networks
Andreas Bley
2008-01-01
Most data networks nowadays use shortest path protocols to route the traffic. Given administrative routing lengths for the\\u000a links of the network, all data packets are sent along shortest paths with respect to these lengths from their source to their\\u000a destination.\\u000a \\u000a In this paper, we present an integer programming algorithm for the minimum congestion unsplittable shortest path routing problem,\\u000a which
An Integer Programming Algorithm for Routing Optimization in IP Networks
Andreas Bley
2011-01-01
Most data networks nowadays use shortest path protocols to route the traffic. Given administrative routing lengths for the\\u000a links of the network, all data packets are sent along shortest paths with respect to these lengths from their source to their\\u000a destination.\\u000a \\u000a \\u000a In this paper, we present an integer programming algorithm for the minimum congestion unsplittable shortest path routing problem,\\u000a which
Wireless sensor network path optimization based on particle swarm algorithm
Xia Zhu; Yulin Zhang
2011-01-01
This paper proposes a particle swarm optimization algorithm for Wireless Sensor Network (WSN) path optimization. It designs and increases the mutation operator. This algorithm can find effective optimization of WSN routing, not only the solution quality is superior to genetic algorithm, but also increases in the success rate. In experimental results verified that proposed PSO-WSN intelligent method can escape from
Algorithms and Sensors for Small Robot Path Following
NASA Technical Reports Server (NTRS)
Hogg, Robert W.; Rankin, Arturo L.; Roumeliotis, Stergios I.; McHenry, Michael C.; Helmick, Daniel M.; Bergh, Charles F.; Matthies, Larry
2002-01-01
Tracked mobile robots in the 20 kg size class are under development for applications in urban reconnaissance. For efficient deployment, it is desirable for teams of robots to be able to automatically execute path following behaviors, with one or more followers tracking the path taken by a leader. The key challenges to enabling such a capability are (l) to develop sensor packages for such small robots that can accurately determine the path of the leader and (2) to develop path following algorithms for the subsequent robots. To date, we have integrated gyros, accelerometers, compass/inclinometers, odometry, and differential GPS into an effective sensing package. This paper describes the sensor package, sensor processing algorithm, and path tracking algorithm we have developed for the leader/follower problem in small robots and shows the result of performance characterization of the system. We also document pragmatic lessons learned about design, construction, and electromagnetic interference issues particular to the performance of state sensors on small robots.
Optimal path planning in Rapid Prototyping based on genetic algorithm
Yang Weidong
2009-01-01
One of important researches in rapid prototyping (RP) is to optimize the path planning which affects the efficiency and building quality of RP system. But it is very difficult to solve its optimization by traditional methods. Genetic algorithms (GAs) are excellent approaches to solving these complex problems in optimization with difficult constraints. The classic path-planning optimization problem has been shown
Algorithms for Computing QoS Paths with Restoration
Sprintson, Alexander
1 Algorithms for Computing QoS Paths with Restoration Yigal Bejerano, Yuri Breitbart, Member, IEEE and the restoration topology should be a major consideration of the routing process. We undertake a comprehensive study of problems related to finding suitable restoration topologies for QoS paths. We consider both
Chen Xin; Xiucheng Guo; Dongtao Fan
2011-01-01
Aviation safety is the base for the operation of air transportation system. It plays a significant role in maneuvering accidents quickly and efficiently. In this paper, the network of airport on the airside was analyzed from the aspect of aviation safety; then a nodes-arcs relation database was built to describe the airside network topology and the Dijkstra algorithm was employed
Path planning using genetic algorithms for mini-robotic tasks
Víctor Ayala-ramírez; Arturo Pérez-garcía; F. J. Montecillo-puente; E. Martinez-labrada; Raúl Enrique Sánchez-yáñez
2004-01-01
We present a genetic algorithm-based method to optimize trajectory planning for mini-robotic tasks. Codifying a number of motion primitive parameters into computational chromosomes does this. Each trajectory is composed of a fixed number N of straight segments. We search with a genetic algorithm the length and direction parameters of the N path segments that let us to arrive a target
An efficient transition path sampling algorithm for nanoparticles under pressure
Geissler, Phillip
An efficient transition path sampling algorithm for nanoparticles under pressure Michael GrÃ¼nwald this algorithm by showing that it preserves the distribution of an ideal gas at constant temperature and pressure investigate the h-MgO to rocksalt transformation in faceted CdSe nanocrystals. Starting from an artificial
Huang, Tao; Cai, Yu-Dong
2014-01-01
The recently emerging Influenza A/H7N9 virus is reported to be able to infect humans and cause mortality. However, viral and host factors associated with the infection are poorly understood. It is suggested by the “guilt by association” rule that interacting proteins share the same or similar functions and hence may be involved in the same pathway. In this study, we developed a computational method to identify Influenza A/H7N9 virus infection-related human genes based on this rule from the shortest paths in a virus-human protein interaction network. Finally, we screened out the most significant 20 human genes, which could be the potential infection related genes, providing guidelines for further experimental validation. Analysis of the 20 genes showed that they were enriched in protein binding, saccharide or polysaccharide metabolism related pathways and oxidative phosphorylation pathways. We also compared the results with those from human rhinovirus (HRV) and respiratory syncytial virus (RSV) by the same method. It was indicated that saccharide or polysaccharide metabolism related pathways might be especially associated with the H7N9 infection. These results could shed some light on the understanding of the virus infection mechanism, providing basis for future experimental biology studies and for the development of effective strategies for H7N9 clinical therapies. PMID:24955349
Mobile Robot Path Planning Using Genetic Algorithms
Carlos E. Thomaz; Marco Aurélio Cavalcanti Pacheco; Marley B. R. Vellasco
1999-01-01
Genetic Algorithms (GAs) have demonstrated to be effective procedures for solving multi- criterion optimization problems. These algorithms mimic models of natural evolution and have the ability to adaptively search large spaces in near -optimal ways. One direct application of this intelligent technique is in the area of evolutionary robotics, where GAs are typically used for designing behavioral controllers for robots
Performance analysis of the AntNet algorithm
S. S. Dhillon; Piet Van Mieghem
2007-01-01
A number of routing algorithms based on the ant-colony metaphor have been proposed for communication networks. However, there has been little work on the performance analysis of ant-routing algorithms. In this paper, we compare the performance of AntNet, an ant-routing algorithm, with Dijkstra's shortest path algorithm. Our simulations show that the performance of AntNet is comparable to Dijkstra's shortest path
NASA Astrophysics Data System (ADS)
Pahlavani, Parham; Delavar, Mahmoud R.; Frank, Andrew U.
2012-08-01
The personalized urban multi-criteria quasi-optimum path problem (PUMQPP) is a branch of multi-criteria shortest path problems (MSPPs) and it is classified as a NP-hard problem. To solve the PUMQPP, by considering dependent criteria in route selection, there is a need for approaches that achieve the best compromise of possible solutions/routes. Recently, invasive weed optimization (IWO) algorithm is introduced and used as a novel algorithm to solve many continuous optimization problems. In this study, the modified algorithm of IWO was designed, implemented, evaluated, and compared with the genetic algorithm (GA) to solve the PUMQPP in a directed urban transportation network. In comparison with the GA, the results have shown the significant superiority of the proposed modified IWO algorithm in exploring a discrete search-space of the urban transportation network. In this regard, the proposed modified IWO algorithm has reached better results in fitness function, quality metric and running-time values in comparison with those of the GA.
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.
Trust Path-Searching Algorithm Based on PSO
Zhiwen Zeng; Ya Gao; Zhigang Chen; Xiaoheng Deng
2008-01-01
As there are many malicious nodes spreading false information in P2P networks, it is of great importance to build a sound mechanism of trust in the P2P environments. To avoid the shortage of the existing trust model, this paper provides a Trust Path-Searching Algorithm based on PSO. In this algorithm, after initializing the particle swarm, each particle can update its
A hybrid multi-path ant QoS routing algorithm for MANETs
Radwa Attia; R. Rizk; Mahmoud Mariee
2009-01-01
Supporting multimedia for Mobile ad hoc networks (MANETs) is an important issue. This paper presents two routing algorithms in MANETs inspired by the ant colony optimization routing algorithms. The first algorithm is a Hybrid Multi-Ant (HMAnt) routing algorithm. It is a hybrid since it combines reactive path establishment with proactive path maintenance. It supports multi-path while maintaining an acceptable level
Relativistic Path Integral as a Lattice-based Quantum Algorithm
Jeffrey Yepez
2005-01-01
We demonstrate the equivalence of two representations of many-body relativistic quantum mechanics: the quantum lattice-gas\\u000a method and the path integral method. The former serves as an efficient lattice-based quantum algorithm to simulate the space-time\\u000a dynamics of a system of Dirac particles.
Fast convergence of the simplified largest step path following algorithm
Gonzaga, C.C.; Bonnans, J.F.
1994-12-31
In this talk we describe a simplified Newton path following algorithm for the solution of monotone horizontal linear complementarity problems. Each master iteration of the algorithm starts from a feasible solution in an Euclidean norm neighborhood of the central path, computes a Jacobian matrix and performs p internal steps; each internal step uses this fixed Jacobian to compute a (simplified) Newton step for approaching a central point. Each step is constructed to obtain the largest possible reduction in complementarity measure with iterates in the neighborhood. We show that this algorithm with the addition of a computationally trivial safeguard procedure generates sequences of objective values (duality gaps) that converge to zero with Q-order p + 1 in the number of master iterations, and with a complexity of O({radical}nL) iterations.
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 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.
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.
Parikh, Kush Jay
2013-01-01
follow. The driver only sends information and never receivesclient receives information from the driver (not necessarydriver is omitted in this experiment) .23 4.2 (b) The neighbor topology (direction of arrow represents the path of information
Dynamic route guidance algorithm based on artificial immune system
Licai Yang; Jie Lin; Dewei Wang; Lei Jia
2007-01-01
To improve the performance of the K-shortest paths search in intelligent traffic guidance systems, this paper proposes an optimal search algorithm based on the\\u000a intelligent optimization search theory and the metaphor mechanism of vertebrate immune systems. This algorithm, applied to\\u000a the urban traffic network model established by the node-expanding method, can expediently realize K-shortest paths search in the urban traffic
Historical Traffic-Tolerant Paths in Road Networks Pui Hang Li Man Lung Yiu
Yiu, Man Lung
paths that mini- mize the aggregate (historical) travel time. Unlike the shortest path problem, the TTP problem has a combinatorial search space that renders the optimal solution expensive to compute. We demonstrate the effectiveness of TTP paths and the efficiency of our proposed algorithms. Categories
A Distributed Multi-commodity Flow Approximation Algorithm for Path Restoration
Venkatesan, S.
A Distributed Multi-commodity Flow Approximation Algorithm for Path Restoration S algorithm specif- ically tailored for path restoration, which is an important problem in building survivable telecommunication backbone networks. Path-based restoration schemes are known their for high restora- tion
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.
An O(ND) Difference Algorithm and Its Variations
Eugene W. Myers
1986-01-01
The problems of findinga longest common subsequence of two sequences A and B and a shortest edit script for transforming A into B have long been known to be dual problems. In this paper, they are shown to be equivalent to finding a shortest\\/longest path in an edit graph. Using this perspective, a simple O(ND) time and space algorithm is
Path Planning Based on Biphasic Ant Colony Algorithm and Fuzzy Control in Dynamic Environment
Cai Wenbin; Zhu Qingbao; Hu Jun
2010-01-01
This paper presents a simple yet efficient dynamic path planning algorithm based on biphasic ant colony algorithm with fuzzy control in the environment with some dynamic obstacles. A global optimal path is planned by using the Biphasic ACO (BACO) searching algorithm without consideration of any dynamic obstacles to solve the problem of local optimization. On that basis, the fuzzy control
Guang-Yu Zhu; Wei-Bo Zhang
2008-01-01
Drilling path optimization is one of the key problems in holes-machining. This paper presents a new approach to solve the drilling path optimization problem belonging to discrete space, based on the particle swarm optimization (PSO) algorithm. Since the standard PSO algorithm is not guaranteed to be global convergent or local convergent, based on the mathematical model, the algorithm is improved
A Proficient Path Selection for Wireless Ad Hoc Routing Protocol
A. N. Al-Khwildi; H. S. Al-Raweshidy
2006-01-01
Usually, routing protocols which are based on link-state information such as (OSPF, OLSR, and FSR) compute the shortest routes to each reachable destination using a path-selection algorithm like Dijkstra's algorithm or the Bellman-Ford algorithm. However, in an on-demand link-state routing protocol, there is no need to know the path to every other node. Accordingly, when a node chooses a next
Evolutionary algorithm based offline\\/online path planner for UAV navigation
Ioannis K. Nikolos; Kimon P. Valavanis; Nikos C. Tsourveloudis; Anargyros N. Kostaras
2003-01-01
Abstract—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
Minefield path planning: architecture and algorithms obeying kinematic constraints
Christopher B. McCubbin; Christine D. Piatko; Steven J. Marshall
2004-01-01
We have been developing path planning techniques to look for paths that balance the utility and risk associated with different routes through a minefield. Such methods will allow a battlegroup commander to evaluate alternative route options while searching for low risk paths. Extending on previous years' efforts, we have implemented a generalized path planning framework to allow rapid evaluation and
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
An algorithm for generating NC tool paths for arbitrarily shaped pockets with islands
Allan Hansen; Farhad Arbab
1992-01-01
In this paper we describe algorithms for generating NC tool paths for machining of arbitrarily shaped 2 l\\/2 dimensional pockets with arbitrary islands. These pocketing algorithms are based on a new offsetting algorithm presented in this paper. Our offsetting algorithm avoids costly two-dimensional Boolean set operations, relatively expensive distance calculations, and the overhead of extraneous geometry, such as the Voronoi
A Motion Constraint Dynamic Path Planning Algorithm for Multi-Agent Simulations
Tao Ruan Wan; H. Chen; Rae A. Earnshaw
2005-01-01
In this paper, we present a novel motion-orientated path planning algorithm fo r real-time navigation of mobile agents. The algorithm works well in dynamical and un-configured environments, and is able to produce a collision-free, time -optimal motion trajectory in order to find a navigation path. In additi on to the motion constraint path planning, our approach can deal with the
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.
Graph algorithms for clock schedule optimization
Narendra V. Shenoy; Robert K. Brayton; Alberto L. Sangiovanni-Vincentelli
1992-01-01
Performance driven synthesis of sequential circuits relies on techniquessuch as optimal clocking, retiming and resynthesis. In this paper we address the optimal clockingproblem and demonstrate that it is reducible to a parametric shortest path problem. We use constraints that take into account both the short and long paths. The main contributions are efjicient graph algorithms to solve the set of
Sensor-based path-planning algorithms for a nonholonomic mobile robot
Hiroshi Noborio; Iku Yamamoto; Toshihiro Komaki
2000-01-01
We propose sensor-based path-planning algorithms for a nonholonomic mobile robot. A car-like robot supervised by these algorithms always reaches its target point (position, and orientation) globally while sensing and avoiding uncertain neighbor obstacles locally in a 2-D environment. In general, all the classic sensor-based path-planning algorithms lead a robot to its destination (x,y) quickly in a 2-D unknown search space.
A Generic Path Algorithm for Regularized Statistical Estimation.
Zhou, Hua; Wu, Yichao
2014-01-01
Regularization is widely used in statistics and machine learning to prevent overfitting and gear solution towards prior information. In general, a regularized estimation problem minimizes the sum of a loss function and a penalty term. The penalty term is usually weighted by a tuning parameter and encourages certain constraints on the parameters to be estimated. Particular choices of constraints lead to the popular lasso, fused-lasso, and other generalized ?1 penalized regression methods. In this article we follow a recent idea by Wu (2011, 2012) and propose an exact path solver based on ordinary differential equations (EPSODE) that works for any convex loss function and can deal with generalized ?1 penalties as well as more complicated regularization such as inequality constraints encountered in shape-restricted regressions and nonparametric density estimation. Non-asymptotic error bounds for the equality regularized estimates are derived. In practice, the EPSODE can be coupled with AIC, BIC, Cp or cross-validation to select an optimal tuning parameter, or provides a convenient model space for performing model averaging or aggregation. Our applications to generalized ?1 regularized generalized linear models, shape-restricted regressions, Gaussian graphical models, and nonparametric density estimation showcase the potential of the EPSODE algorithm. PMID:25242834
A Generic Path Algorithm for Regularized Statistical Estimation
Zhou, Hua; Wu, Yichao
2014-01-01
Regularization is widely used in statistics and machine learning to prevent overfitting and gear solution towards prior information. In general, a regularized estimation problem minimizes the sum of a loss function and a penalty term. The penalty term is usually weighted by a tuning parameter and encourages certain constraints on the parameters to be estimated. Particular choices of constraints lead to the popular lasso, fused-lasso, and other generalized ?1 penalized regression methods. In this article we follow a recent idea by Wu (2011, 2012) and propose an exact path solver based on ordinary differential equations (EPSODE) that works for any convex loss function and can deal with generalized ?1 penalties as well as more complicated regularization such as inequality constraints encountered in shape-restricted regressions and nonparametric density estimation. Non-asymptotic error bounds for the equality regularized estimates are derived. In practice, the EPSODE can be coupled with AIC, BIC, Cp or cross-validation to select an optimal tuning parameter, or provides a convenient model space for performing model averaging or aggregation. Our applications to generalized ?1 regularized generalized linear models, shape-restricted regressions, Gaussian graphical models, and nonparametric density estimation showcase the potential of the EPSODE algorithm. PMID:25242834
Robust three-dimensional best-path phase-unwrapping algorithm that avoids singularity loops.
Abdul-Rahman, Hussein; Arevalillo-Herráez, Miguel; Gdeisat, Munther; Burton, David; Lalor, Michael; Lilley, Francis; Moore, Christopher; Sheltraw, Daniel; Qudeisat, Mohammed
2009-08-10
In this paper we propose a novel hybrid three-dimensional phase-unwrapping algorithm, which we refer to here as the three-dimensional best-path avoiding singularity loops (3DBPASL) algorithm. This algorithm combines the advantages and avoids the drawbacks of two well-known 3D phase-unwrapping algorithms, namely, the 3D phase-unwrapping noise-immune technique and the 3D phase-unwrapping best-path technique. The hybrid technique presented here is more robust than its predecessors since it not only follows a discrete unwrapping path depending on a 3D quality map, but it also avoids any singularity loops that may occur in the unwrapping path. Simulation and experimental results have shown that the proposed algorithm outperforms its parent techniques in terms of reliability and robustness. PMID:19668273
An obstacle-avoidance path-planning in robot soccer based on Refined Genetic Algorithms
Song Da-lei; Li Yan-li
2010-01-01
An intelligent obstacle-avoidance algorithms in robot soccer based on Refined Genetic Algorithms is introduced in the paper and this method is used to plan the path of the robot in robot soccer based on Microsoft Robotics Simulation Platform. The genetic algorithms display a better obstacle-avoidance effect from the data based on Microsoft Robotics Simulation Platform 11 VS 11. Because of
Felner, Ariel
2004-01-01
Journal of Artificial Intelligence Research 21 (2004) 631Â670 Submitted 9/03; published 6/04 PHA unknown territory. We introduce the PhysicalÂA* algorithm (PHA*) for solving this problem. PHA* expands by the traveling effort of the moving agent and not by the number of generated nodes, as in standard A*. PHA
An efficient dynamic system for real-time robot-path planning
Allan R. Willms; Simon X. Yang
2006-01-01
This paper presents a simple yet efficient dynamic-programming (DP) shortest path algorithm for real-time collision-free robot-path planning applicable to situations in which targets and barriers are permitted to move. The algorithm works in real time and requires no prior knowledge of target or barrier movements. In the case that the barriers are stationary, this paper proves that this algorithm always
A Large Family of Multi-path Dual Congestion Control Algorithms
Liu, Ying; Xu, Ke; Shen, Meng; Zhong, Yifeng
2011-01-01
The goal of traffic management is efficiently utilizing network resources via adapting of source sending rates and routes selection. Traditionally, this problem is formulated into a utilization maximization problem. The single-path routing scheme fails to react to instantaneous network congestion. Multi-path routing schemes thus have been proposed aiming at improving network efficiency. Unfortunately, the natural optimization problem to consider is concave but not strictly concave. It thus brings a huge challenge to design stable multi-path congestion control algorithms. In this paper, we propose a generalized multi-path utility maximization model to consider the problem of routes selection and flow control, and derive a family of multi-path dual congestion control algorithms. We show that the proposed algorithms are stable in the absence of delays. We also derive decentralized and scalable sufficient conditions for a particular scheme when propagation delays exist in networks. Simulations are implemented usi...
Shared-path protection algorithm for joint routing selection in survivable WDM mesh networks
NASA Astrophysics Data System (ADS)
Guo, Lei; Yu, Hongfang; Li, Lemin; Luo, Hongbin
2005-02-01
In this paper, we propose a new shared-path protection approach, called joint routing algorithm (JRA), under shared-risk link group (SRLG) constraints for survivable WDM mesh networks. JRA differs from previous algorithms that are socalled separated routing algorithm (SRA), and can find K path pairs and select an optimal path pair as the result, while SRA can only find a path pair that may be not an optimal routing pair. So, JRA can perform better than SRA. We also study the relationship between the protection switching time and the resource utilization, and suggest a new joint cost function to compute the least-cost path pairs. Under dynamic traffics with different load, the simulation results show that JRA not only has better performances than SRA but also can determine the appropriate tradeoffs between the resource utilization ratio (or blocking ratio) and the protection switching time.
An algorithm to find critical execution paths of software based on complex network
NASA Astrophysics Data System (ADS)
Huang, Guoyan; Zhang, Bing; Ren, Rong; Ren, Jiadong
2015-01-01
The critical execution paths play an important role in software system in terms of reducing the numbers of test date, detecting the vulnerabilities of software structure and analyzing software reliability. However, there are no efficient methods to discover them so far. Thus in this paper, a complex network-based software algorithm is put forward to find critical execution paths (FCEP) in software execution network. First, by analyzing the number of sources and sinks in FCEP, software execution network is divided into AOE subgraphs, and meanwhile, a Software Execution Network Serialization (SENS) approach is designed to generate execution path set in each AOE subgraph, which not only reduces ring structure's influence on path generation, but also guarantees the nodes' integrity in network. Second, according to a novel path similarity metric, similarity matrix is created to calculate the similarity among sets of path sequences. Third, an efficient method is taken to cluster paths through similarity matrices, and the maximum-length path in each cluster is extracted as the critical execution path. At last, a set of critical execution paths is derived. The experimental results show that the FCEP algorithm is efficient in mining critical execution path under software complex network.
Manipulator path planning by decomposition: algorithm and analysis
Arjang Hourtash; Mahmoud Tarokh
2001-01-01
Path planning is achieved by a special decomposition of the robot manipulator, an offline preprocessing stage, and a three phase online path planning scheme. The decomposition consists of separating the robot into several chains where a chain is a combination of several consecutive links and joints. Preprocessing is performed by defining a set of postures for each chain and setting
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 ...
Design and Protection Algorithms for Path Level Aggregation of Traffic in WDM Metro Optical Networks
Design and Protection Algorithms for Path Level Aggregation of Traffic in WDM Metro Optical . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xv CHAPTER 1. IP over Optical Networks - Introduction . . . . . . . . . . . . 1 1.1 Traditional Metro . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1.3 New Metro Solutions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 1
The Path-of-Probability Algorithm for Steering and Feedback Control of Flexible Needles
Park, Wooram; Wang, Yunfeng; Chirikjian, Gregory S.
2010-01-01
In this paper we develop a new framework for path planning of flexible needles with bevel tips. Based on a stochastic model of needle steering, the probability density function for the needle tip pose is approximated as a Gaussian. The means and covariances are estimated using an error propagation algorithm which has second order accuracy. Then we adapt the path-of-probability (POP) algorithm to path planning of flexible needles with bevel tips. We demonstrate how our planning algorithm can be used for feedback control of flexible needles. We also derive a closed-form solution for the port placement problem for finding good insertion locations for flexible needles in the case when there are no obstacles. Furthermore, we propose a new method using reference splines with the POP algorithm to solve the path planning problem for flexible needles in more general cases that include obstacles. PMID:21151708
A Smooth Path Tracking Algorithm for Wheeled Mobile Robots with Dynamic Constraints
Kyoung Chul Koh; Hyung Suck Cho
1999-01-01
In order to avoid wheel slippage or mechanical damage during the mobile robot navigation, it is necessary tosmoothly change driving velocity or direction of the mobile robot. This means that dynamic constraints of the mobile robotshould be considered in the design of path tracking algorithm. In the study, a path tracking problem is formulated asfollowing a virtual target vehicle which
Preview path based real-time fuzzy navigation algorithm for mobile robot
Guoyang Li; Yingying Wu; Wei Wei
2008-01-01
The problem of goal-oriented obstacle avoidance for mobile robot in unknown environment is studied. By imitating the preview navigation behavior of human, the paper proposed a novel real-time fuzzy navigation algorithm for mobile robot., Firstly, the preview path was estimated based on the current scenario. The objective orientation of robot was calculated by synthesizing preview path tracking and obstacle avoidance.
Approximating Disjoint-Path Problems Using Greedy Algorithms and Packing Integer Programs
Stavros G. Kolliopoulos; Clifford Stein
1998-01-01
The edge and vertex-disjoint path problems together with their unsplittable flow generalization are NP-hard problems with a multi- tude of applications in areas such as routing, scheduling and bin packing. Given the hardness of the problems, we study polynomial-time approxi- mation algorithms with bounded performance guarantees. We introduce techniques which yield new algorithms for a wide range of disjoint-path problems.
Approximation Algorithms and Heuristics for a 2-depot, Heterogeneous Hamiltonian Path Problem
Doshi, Riddhi Rajeev
2011-10-21
APPROXIMATION ALGORITHMS AND HEURISTICS FOR A 2-DEPOT, HETEROGENOUS HAMILTONIAN PATH PROBLEM A Thesis by RIDDHI RAJEEV DOSHI Submitted to the Office of Graduate Studies of Texas A&M University in partial fulfillment of the requirements... for the degree of MASTER OF SCIENCE August 2010 Major Subject: Mechanical Engineering APPROXIMATION ALGORITHMS AND HEURISTICS FOR A 2-DEPOT, HETEROGENOUS HAMILTONIAN PATH PROBLEM A Thesis by RIDDHI RAJEEV DOSHI Submitted to the Office of Graduate Studies...
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.
Algorithms for an Unmanned Vehicle Path Planning Problem
Qin, Jianglei
2013-06-25
Unmanned Vehicles (UVs) have been significantly utilized in military and civil applications over the last decade. Path-planning of UVs plays an important role in effectively using the available resources such as the UVs and sensors as efficiently...
Ohya, Akihisa
Transform [2][3] (Fig.1) Fig.1 Obstacle plot 2.2 Fig.2 ( ) (Fig.2) #12;Fig.2 Obstacle judgment 2.3 Distance Transform 0 (Fig.3) ( ) 4 1 (Fig.3) Fig.3 Distance Transform 4 +1 1 ( +5) (Fig.4) Fig.3 Path generation (the same weight) Fig.4 Path generation (different weights) 2.4 (Fig.5) Fig.5 #12;Fig.5 Shortest path
Memorial University of Newfoundland Department of Mathematics and Statistics Dijkstra's Algorithm
deYoung, Brad
Memorial University of Newfoundland Department of Mathematics and Statistics Dijkstra's Algorithm.k.a. the shortest path) from vertex v 0 to each other vertex in the graph. #15; The Algorithm: 1. Let t = 0; S = fv) until either V (G) n S = ; or d i = 1 8v i 2 V (G) n S. What the algorithm does is build a set, S
Robust Flight Path Determination for Mars Precision Landing Using Genetic Algorithms
NASA Technical Reports Server (NTRS)
Bayard, David S.; Kohen, Hamid
1997-01-01
This paper documents the application of genetic algorithms (GAs) to the problem of robust flight path determination for Mars precision landing. The robust flight path problem is defined here as the determination of the flight path which delivers a low-lift open-loop controlled vehicle to its desired final landing location while minimizing the effect of perturbations due to uncertainty in the atmospheric model and entry conditions. The genetic algorithm was capable of finding solutions which reduced the landing error from 111 km RMS radial (open-loop optimal) to 43 km RMS radial (optimized with respect to perturbations) using 200 hours of computation on an Ultra-SPARC workstation. Further reduction in the landing error is possible by going to closed-loop control which can utilize the GA optimized paths as nominal trajectories for linearization.
Quantum Adiabatic Algorithms, Small Gaps, and Different Paths
Farhi, Edward
We construct a set of instances of 3SAT which are not solved efficiently using the simplestquantum adiabatic algorithm. These instances are obtained by picking randomclauses all consistent with two disparate planted solutions ...
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, ...
NASA Astrophysics Data System (ADS)
Ringle, Christian M.; Sarstedt, Marko; Schlittgen, Rainer
When applying structural equation modeling methods, such as partial least squares (PLS) path modeling, in empirical studies, the assumption that the data have been collected from a single homogeneous population is often unrealistic. Unobserved heterogeneity in the PLS estimates on the aggregate data level may result in misleading interpretations. Finite mixture partial least squares (FIMIX-PLS) and PLS genetic algorithm segmentation (PLS-GAS) allow the classification of data in variance-based structural equation modeling. This research presents an initial application and comparison of these two methods in a computational experiment in respect of a path model which includes multiple endogenous latent variables. The results of this analysis reveal particular advantages and disadvantages of the approaches. This study further substantiates the effectiveness of FIMIX-PLS and PLS-GAS and provides researchers and practitioners with additional information they need to proficiently evaluate their PLS path modeling results by applying a systematic means of analysis. If significant heterogeneity were to be uncovered by the procedures, the analysis may result in group-specific path modeling outcomes, thus allowing further differentiated and more precise conclusions to be formed.
An Adaptive Multi-paths Algorithm for Wireless Sensor Networks
Zhendong Wu; Shanping Li
2007-01-01
Multi-path strategy is one of the favorable choices to transmit data efficiently and flexibly in sensor networks. Due to various\\u000a applications, it is hard to devise a generic WSN routing strategy to meet all requirements of various applications and environments\\u000a at the same time. Therefore, a novel routing strategy should provide flexible schemes which adjusts forwarding schemes dynamically\\u000a according to
Evaluation of Point-to-Point Network Routing Algorithms
P. Bell; K. Jabbour
1987-01-01
A sampling of routing algorithms is evaluated through simulation. The algorithms selected are random walk, fixed directory, split traffic, isolated shortest queue (hot potato) and backward learning. Backward learning exhibited the most desirable characteristics, approaching fixed directory routing in delay and path length, while adapting to link failures.
Artificial Immune Algorithm Based Obstacle Avoiding Path Planning of Mobile Robots
Yen-nien Wang; Hao-hsuan Hsu; Chun-cheng Lin
2005-01-01
\\u000a This investigation studies the applicability of using mobile robots with artificial immune algorithm (AIA) based obstacle-avoiding\\u000a path planning inside a specified environment in real time. Path planning is an important problem in robotics. AIA is applied\\u000a to determine the position and the angle between a mobile robot, an obstacle and the goal in a limited field. The method seeks\\u000a to
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.
Robust constrained shortest path problems under budgeted ...
2014-09-12
The proposed solution approaches have been coded in JAVA and our numerical experiments have been carried out on an Intel(R) Core(TM) i7 CPU M 620, 2.67 GHz, 4 ..... Robust discrete optimization and its applications, volume 14. Springer
An O ( ND ) difference algorithm and its variations
Eugene W. Myers
1986-01-01
The problems of finding a longest common subsequence of two sequencesA andB and a shortest edit script for transformingA intoB have long been known to be dual problems. In this paper, they are shown to be equivalent to finding a shortest\\/longest path\\u000a in an edit graph. Using this perspective, a simpleO(ND) time and space algorithm is developed whereN is the
Genetic Algorithm-Based Test Data Generation for Multiple Paths via Individual Sharing
Gong, Dunwei
2014-01-01
The application of genetic algorithms in automatically generating test data has aroused broad concerns and obtained delightful achievements in recent years. However, the efficiency of genetic algorithm-based test data generation for path testing needs to be further improved. In this paper, we establish a mathematical model of generating test data for multiple paths coverage. Then, a multipopulation genetic algorithm with individual sharing is presented to solve the established model. We not only analyzed the performance of the proposed method theoretically, but also applied it to various programs under test. The experimental results show that the proposed method can improve the efficiency of generating test data for many paths' coverage significantly. PMID:25691894
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 Multi-stage Probabilistic Algorithm for Dynamic Path-Planning
Barriga, Nicolas A
2009-01-01
Probabilistic sampling methods have become very popular to solve single-shot path planning problems. Rapidly-exploring Random Trees (RRTs) in particular have been shown to be efficient in solving high dimensional problems. Even though several RRT variants have been proposed for dynamic replanning, these methods only perform well in environments with infrequent changes. This paper addresses the dynamic path planning problem by combining simple techniques in a multi-stage probabilistic algorithm. This algorithm uses RRTs for initial planning and informed local search for navigation. We show that this combination of simple techniques provides better responses to highly dynamic environments than the RRT extensions.
A statistical-based scheduling algorithm in automated data path synthesis
NASA Technical Reports Server (NTRS)
Jeon, Byung Wook; Lursinsap, Chidchanok
1992-01-01
In this paper, we propose a new heuristic scheduling algorithm based on the statistical analysis of the cumulative frequency distribution of operations among control steps. It has a tendency of escaping from local minima and therefore reaching a globally optimal solution. The presented algorithm considers the real world constraints such as chained operations, multicycle operations, and pipelined data paths. The result of the experiment shows that it gives optimal solutions, even though it is greedy in nature.
Bandwidth Scheduling and Path Computation Algorithms for Connection-Oriented Networks
Sartaj Sahni; Nageshwara Rao; Sanjay Ranka; Yan Li; Eun-sung Jung; Nara Kamath
2007-01-01
There has been an increasing number of network deployments that provide dedicated connections through on-demand and in-advance scheduling in support of high- performance applications. We describe algorithms for scheduling and path computations needed for dedicated bandwidth connections for fixed-slot, highest available bandwidth in a given slot, first available slot, and all-available slots computations. These algorithms for bandwidth scheduling are based
RCMP: Reliable clustering based multi-path routing algorithm for wireless sensor networks
Tohid Bagheri; Ali Ghaffari; Saeed Rasouli Heikalabad
2011-01-01
Although data forwarding algorithms are among the first set of the most important issues explored in sensor networks, how to efficiently and reliably deliver sensing data through a large field of sensors remains a research challenge. Multi-path is favorite alternative for sensor networks, as it provides an easy mechanism to distribute traffic and balance network's load, as well as considerate
Robbiano, Lorenzo
on the definition of a new criterion for evaluating the capability of an Unmanned Surface Vehicle (USV) to followAssessing path-following performance for Unmanned Marine Vehicles with algorithms from Numerical is the definition of standards and rules to be applied to unmanned vehicles (like USVs) in civilian scenarios
A fast algorithm for determining the propagation path of multiple diffracted rays
Buffa, Annalisa
1 A fast algorithm for determining the propagation path of multiple diffracted rays Patrizia of multiple diffracted rays relevant to ray tracing techniques. The focus is on double diffracted rays edges. Index Terms-- Multiple diffraction, Ray tracing, Electromag- netic edge diffraction, HF wave
David Rathbun; Sean Kragelund; Anawat Pongpunwattana; Brian Capozzi
2002-01-01
Adaptive and intelligent on-board path planning is a required part of a fully autonomous UAV. In controlled airspace, such a UAV would have to interact with other vehicles moving though its environment. The locations of obstacles (other vehicles) that form obstructions in the environment may only be known with limited accuracy. Evolutionary algorithms (EA) have been successfully used to compute
Efficient algorithms for computing the longest viable path in a combinational network
Patrick C. McGeer; Robert K. Brayton
1989-01-01
We consider the elimination of false paths in combinational circuits. We give the single generic algorithm that is used to solve this problem, and demonstrate that it is parameterized by a Boolean function called the sensitization condition. We give two criteria which we argue that a valid sensitization condition must meet, and introduce four conditions that have appeared in the
Jim Burke; Song Xu
2000-01-01
. We present a predictor–corrector non–interior path following algorithm for the monotone linear complementarity problem based\\u000a on Chen–Harker–Kanzow–Smale smoothing techniques. Although the method is modeled on the interior point predictor–corrector\\u000a strategies, it is the first instance of a non–interior point predictor–corrector algorithm. The algorithm is shown to be both\\u000a globally linearly convergent and locally quadratically convergent under standard hypotheses. The
A Path Towards Operational Uncertainty of Cloud Phase Identification Algorithms
NASA Astrophysics Data System (ADS)
Riihimaki, L.; Comstock, J. M.; Luke, E. P.; Pulsipher, T.; Sivaraman, C.; Tardiff, M.; Thompson, S.
2014-12-01
Cloud phase state is a key piece of information in characterizing the impact of clouds on radiation and dynamics. Identifying cloud phase is also the first step towards deriving further information about hydrometeor mass, concentration, and size in remote sensing retrievals. While a variety of phase identification algorithms exist, they don't have quantitative estimates of their uncertainty when run operationally. The difficulty of assigning uncertainties to remote sensing retrievals stems both from a lack of objective "truth" of hydrometeor properties, and insufficient independent information available to fully constrain the properties of cloud particles.Two promising directions for improving and identifying uncertainties in cloud phase characterization are inclusion of additional information available in cloud radar Doppler spectra and using statistical techniques to quantify the value of the information available from multiple sensors at a given time. We will report on progress incorporating multiple remote sensing observations from the ARM Climate Research Facility into a Bayesian net framework to characterize the rigor of identifying cloud phase given different sets of information, including higher order moments of the doppler spectra than are often used. Comparisons to available in situ data will be used to evaluate the results, identify further in situ measurements needed to characterize the problem, and to discuss the implications of the uncertainty in phase state identification for microphysical retrievals.
Optimal Path Planning Program for Autonomous Speed Sprayer in Orchard Using Order-Picking Algorithm
NASA Astrophysics Data System (ADS)
Park, T. S.; Park, S. J.; Hwang, K. Y.; Cho, S. I.
This study was conducted to develop a software program which computes optimal path for autonomous navigation in orchard, especially for speed sprayer. Possibilities of autonomous navigation in orchard were shown by other researches which have minimized distance error between planned path and performed path. But, research of planning an optimal path for speed sprayer in orchard is hardly founded. In this study, a digital map and a database for orchard which contains GPS coordinate information (coordinates of trees and boundary of orchard) and entity information (heights and widths of trees, radius of main stem of trees, disease of trees) was designed. An orderpicking algorithm which has been used for management of warehouse was used to calculate optimum path based on the digital map. Database for digital map was created by using Microsoft Access and graphic interface for database was made by using Microsoft Visual C++ 6.0. It was possible to search and display information about boundary of an orchard, locations of trees, daily plan for scattering chemicals and plan optimal path on different orchard based on digital map, on each circumstance (starting speed sprayer in different location, scattering chemicals for only selected trees).
Su, S.D.; Baylor, K.J.; Engholm, B.A. (CEGA Corporation, San Diego, CA (United States))
1987-05-01
PATH is a highly flexible shielding code utilizing the common point-kernel integration technique primarily for treating gamma radiation from reactors, radioactive components and from complex piping systems. Major features of the code include complex geometry capability, various source options, extensive data library, simple but flexible input and well-organized output format.
Exact and heuristic algorithms for the uncapacitated multiple allocation p-hub median problem
Andreas T. Ernst; Mohan Krishnamoorthy
1998-01-01
In this paper new MILP formulations for the multiple allocation p-hub median problem are presented. These require fewer variables and constraints than those traditionally used in the literature. An efficient heuristic algorithm, based on shortest paths, is described. LP based solution methods as well as an explicit enumeration algorithm are developed to obtain exact solutions. Computational results are presented for
A Position Based Ant Colony Routing Algorithm for Mobile Ad-hoc Networks
Shahab Kamali; Jaroslav Opatrny
2008-01-01
Position based routing algorithms use the knowledge of the position of nodes for routing of packets in mobile ad-hoc networks. Previously proposed position based routing algorithms may fail to find a route from a source to a destination in some types of ad-hoc networks and if they find a route, it may be much longer than the shortest path. On
[Research of tool-path generation algorithm for NC machining dental crown restoration].
Sun, Quanping; Wang, Tongyue; Chen, Qianliang; Dai, Ning; Liao, Wenhe; He, Ning
2008-06-01
Seeing that the manual method to restore tooth has the disadvantages such as long "lead-time", assurance of quality highly depending on operator's technology, and real-time cure difficulty met by lots of dental patients coming up for tooth restoration, we put forward an algorithm of tool-path generation based on STL data model for roughing dental restoration. The algorithm can reconfigure the STL data of dental crown restoration quickly, can generates the multi-level offset wire-loop by the use of horizontal plane cutting triangle facets; and then on the basis of offset wire-loop, it can plan Zigzag and follow the contour machining tool path. The algorithm has been applied to Dental CAM software, through simulation machining, the result shows that it can not only generate interference-free tool path, but also save a lot of "lead-time" for dental restoration. Accordingly, the algorithm is of great value for reference in clinical application. PMID:18693428
Calibration of neural networks using genetic algorithms, with application to optimal path planning
NASA Technical Reports Server (NTRS)
Smith, Terence R.; Pitney, Gilbert A.; Greenwood, Daniel
1987-01-01
Genetic algorithms (GA) are used to search the synaptic weight space of artificial neural systems (ANS) for weight vectors that optimize some network performance function. GAs do not suffer from some of the architectural constraints involved with other techniques and it is straightforward to incorporate terms into the performance function concerning the metastructure of the ANS. Hence GAs offer a remarkably general approach to calibrating ANS. GAs are applied to the problem of calibrating an ANS that finds optimal paths over a given surface. This problem involves training an ANS on a relatively small set of paths and then examining whether the calibrated ANS is able to find good paths between arbitrary start and end points on the surface.
NSDL National Science Digital Library
Started in the 1970s as an agency to assist men and women in gaining access to a variety of birth control methods, PATH has since expanded its focus to provide "sustainable, culturally relevant [health] solutions, enabling communities worldwide to break longstanding cycles of poor health." The PATH website has more than a dozen videos and slideshows available to visitors at the "Our Multimedia" link near the bottom right hand corner of the homepage. A three-minute video entitled "Better Nutrition For Life" educates visitors about an innovative rice product that could bring greater nutrition to millions of malnourished people where rice is a staple food. The product is Ultra Rice, and is actually fortified pasta that looks, cooks, and tastes like rice, but is fortified with nutrients. The "rice" can be fortified with the needed nutrients the particular population being served is lacking. A slideshow about TB in the Ukraine, explains to visitors why there has been a resurgence of TB in Eastern Europe, and how PATH and its partners set out to help control it throughout the region.
Orbital Systolic Algorithms and Array Processors for Solution of the Algebraic Path Problem
NASA Astrophysics Data System (ADS)
Sedukhin, Stanislav G.; Miyazaki, Toshiaki; Kuroda, Kenichi
The algebraic path problem (APP) is a general framework which unifies several solution procedures for a number of well-known matrix and graph problems. In this paper, we present a new 3-dimensional (3-D) orbital algebraic path algorithm and corresponding 2-D toroidal array processors which solve the n × n APP in the theoretically minimal number of 3n time-steps. The coordinated time-space scheduling of the computing and data movement in this 3-D algorithm is based on the modular function which preserves the main technological advantages of systolic processing: simplicity, regularity, locality of communications, pipelining, etc. Our design of the 2-D systolic array processors is based on a classical 3-D?2-D space transformation. We have also shown how a data manipulation (copying and alignment) can be effectively implemented in these array processors in a massively-parallel fashion by using a matrix-matrix multiply-add operation.
A disjoint path selection scheme with shared risk link groups in GMPLS networks
Eiji Oki; Nobuaki Matsuura; Kohei Shiomoto; Naoaki Yamanaka
2002-01-01
This letter proposes a disjoint path selection scheme for generalized multi-protocol label switching (GMPLS) networks with shared risk link group (SRLG) constraints. It is called the weighted-SRLG (WSRLG) scheme. It treats the number of SRLG members related to a link as part of the link cost when the k-shortest path algorithm is executed. In WSRLG, a link that has many
A novel algorithm for detecting differentially regulated paths based on gene set enrichment analysis
Keller, Andreas; Backes, Christina; Gerasch, Andreas; Kaufmann, Michael; Kohlbacher, Oliver; Meese, Eckart; Lenhof, Hans-Peter
2009-01-01
Motivation: Deregulated signaling cascades are known to play a crucial role in many pathogenic processes, among them are tumor initiation and progression. In the recent past, modern experimental techniques that allow for measuring the amount of mRNA transcripts of almost all known human genes in a tissue or even in a single cell have opened new avenues for studying the activity of the signaling cascades and for understanding the information flow in the networks. Results: We present a novel dynamic programming algorithm for detecting deregulated signaling cascades. The so-called FiDePa (Finding Deregulated Paths) algorithm interprets differences in the expression profiles of tumor and normal tissues. It relies on the well-known gene set enrichment analysis (GSEA) and efficiently detects all paths in a given regulatory or signaling network that are significantly enriched with differentially expressed genes or proteins. Since our algorithm allows for comparing a single tumor expression profile with the control group, it facilitates the detection of specific regulatory features of a tumor that may help to optimize tumor therapy. To demonstrate the capabilities of our algorithm, we analyzed a glioma expression dataset with respect to a directed graph that combined the regulatory networks of the KEGG and TRANSPATH database. The resulting glioma consensus network that encompasses all detected deregulated paths contained many genes and pathways that are known to be key players in glioma or cancer-related pathogenic processes. Moreover, we were able to correlate clinically relevant features like necrosis or metastasis with the detected paths. Availability: C++ source code is freely available, BiNA can be downloaded from http://www.bnplusplus.org/. Contact: ack@bioinf.uni-sb.de Supplementary information: Supplementary data are available at Bioinformatics online. PMID:19713416
A new path planning algorithm for maximizing visibility in computed tomography colonography.
Kang, Dong-Goo; Ra, Jong Beom
2005-08-01
In virtual colonoscopy, minimizing the blind areas is important for accurate diagnosis of colonic polyps. Although useful for describing the shape of an object, the centerline is not always the optimal camera path for observing the object. Hence, conventional methods in which the centerline is directly used as a path produce considerable blind areas, especially in areas of high curvature. Our proposed algorithm first approximates the surface of the object by estimating the overall shape and cross-sectional thicknesses. View positions and their corresponding view directions are then jointly determined to enable us to maximally observe the approximated surface. Moreover, by adopting bidirectional navigations, we may reduce the blind area blocked by haustral folds. For comfortable navigation, we carefully smoothen the obtained path and minimize the amount of rotation between consecutive rendered images. For the evaluation, we quantified the overall observable area on the basis of the temporal visibility that reflects the minimum interpretation time of a human observer. The experimental results show that our algorithm improves visibility coverage and also significantly reduces the number of blind areas that have a clinically meaningful size. A sequence of rendered images shows that our algorithm can provide a sequence of centered and comfortable views of colonography. PMID:16092328
Calculating Least Risk Paths in 3d Indoor Space
NASA Astrophysics Data System (ADS)
Vanclooster, A.; De Maeyer, Ph.; Fack, V.; Van de Weghe, N.
2013-08-01
Over the last couple of years, research on indoor environments has gained a fresh impetus; more specifically applications that support navigation and wayfinding have become one of the booming industries. Indoor navigation research currently covers the technological aspect of indoor positioning and the modelling of indoor space. The algorithmic development to support navigation has so far been left mostly untouched, as most applications mainly rely on adapting Dijkstra's shortest path algorithm to an indoor network. However, alternative algorithms for outdoor navigation have been proposed adding a more cognitive notion to the calculated paths and as such adhering to the natural wayfinding behaviour (e.g. simplest paths, least risk paths). These algorithms are currently restricted to outdoor applications. The need for indoor cognitive algorithms is highlighted by a more challenged navigation and orientation due to the specific indoor structure (e.g. fragmentation, less visibility, confined areas…). As such, the clarity and easiness of route instructions is of paramount importance when distributing indoor routes. A shortest or fastest path indoors not necessarily aligns with the cognitive mapping of the building. Therefore, the aim of this research is to extend those richer cognitive algorithms to three-dimensional indoor environments. More specifically for this paper, we will focus on the application of the least risk path algorithm of Grum (2005) to an indoor space. The algorithm as proposed by Grum (2005) is duplicated and tested in a complex multi-storey building. The results of several least risk path calculations are compared to the shortest paths in indoor environments in terms of total length, improvement in route description complexity and number of turns. Several scenarios are tested in this comparison: paths covering a single floor, paths crossing several building wings and/or floors. Adjustments to the algorithm are proposed to be more aligned to the specific structure of indoor environments (e.g. no turn restrictions, restricted usage of rooms, vertical movement) and common wayfinding strategies indoors. In a later stage, other cognitive algorithms will be implemented and tested in both an indoor and combined indoor-outdoor setting, in an effort to improve the overall user experience during navigation in indoor environments.
Hedging Uncertainty: Approximation Algorithms for Stochastic Optimization Problems
R. Ravi; Amitabh Sinha
2004-01-01
We study the design of approximation algorithms for stoch- astic combinatorial optimization problems. We formulate the problems in the framework of two-stage stochastic optimization, and provide nearly tight approximations. Our problems range from the simple (shortest path, vertex cover, bin packing) to complex (facility location, set cover), and contain representatives with different approximation ratios. The approximation ratio of the stochastic
An Algorithm of Tool-Path Optimization for High-Speed Machining Deep-Cavity Precision Forging Die
Q. P. Sun; Q. L. Chen; Q. F. Wang; W. H. Liao
2009-01-01
Aiming at the difficulty of maintaining the contour precision of forging die with deep pocket, an optimization algorithm of tool-path generation for high speed machining (abbr. HSM) forging die with deep cavity is proposed in this paper. In terms of measuring errors of pocketing die, a mathematical model correlation to the length of a tool-path, the available length of a
Hsu-Chih Huang; Ching-Chih Tsai; Shui-Chun Lin
2009-01-01
This paper presents an efficient parallel elite genetic algorithm (PEGA) for global path planning of an omnidirectional mobile robot moving in a static environment expressed by a grid-based map. This efficient PEGA, consisting of two parallel EGAs along with a migration operator, is proposed for global path planning of the mobile robots. The PEGA takes advantages of maintaining better population
Trajectory Generation and Path Planning for Autonomous Aerobots
NASA Technical Reports Server (NTRS)
Sharma, Shivanjli; Kulczycki, Eric A.; Elfes, Alberto
2007-01-01
This paper presents global path planning algorithms for the Titan aerobot based on user defined waypoints in 2D and 3D space. The algorithms were implemented using information obtained through a planner user interface. The trajectory planning algorithms were designed to accurately represent the aerobot's characteristics, such as minimum turning radius. Additionally, trajectory planning techniques were implemented to allow for surveying of a planar area based solely on camera fields of view, airship altitude, and the location of the planar area's perimeter. The developed paths allow for planar navigation and three-dimensional path planning. These calculated trajectories are optimized to produce the shortest possible path while still remaining within realistic bounds of airship dynamics.
Restoration by Path Concatenation: Fast Recovery of MPLS Paths
Bremler-Barr, Anat
Restoration by Path Concatenation: Fast Recovery of MPLS Paths Yehuda Afek Anat Bremler,natali,haimkg@math.tau.ac.il, fedith,mischug@research.att.com Abstract A new general theory about restoration of network paths is first introduced. The theory pertains to restoration of shortest paths in a network following failure, e.g., we
Restoration by Path Concatenation: Fast Recovery of MPLS Paths
Kaplan, Haim
Restoration by Path Concatenation: Fast Recovery of MPLS Paths Yehuda Afek Anat Bremler-Barr Haim,natali,haimk}@math.tau.ac.il, {edith,mischu}@research.att.com Abstract A new general theory about restoration of network paths is first introduced. The theory pertains to restoration of shortest paths in a network following failure, e.g., we
NASA Astrophysics Data System (ADS)
Miura, Shinichi
2007-03-01
In this paper, we present a path integral hybrid Monte Carlo (PIHMC) method for rotating molecules in quantum fluids. This is an extension of our PIHMC for correlated Bose fluids [S. Miura and J. Tanaka, J. Chem. Phys. 120, 2160 (2004)] to handle the molecular rotation quantum mechanically. A novel technique referred to be an effective potential of quantum rotation is introduced to incorporate the rotational degree of freedom in the path integral molecular dynamics or hybrid Monte Carlo algorithm. For a permutation move to satisfy Bose statistics, we devise a multilevel Metropolis method combined with a configurational-bias technique for efficiently sampling the permutation and the associated atomic coordinates. Then, we have applied the PIHMC to a helium-4 cluster doped with a carbonyl sulfide molecule. The effects of the quantum rotation on the solvation structure and energetics were examined. Translational and rotational fluctuations of the dopant in the superfluid cluster were also analyzed.
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
In search of preferential flow paths in structured porous media using a simple genetic algorithm
NASA Astrophysics Data System (ADS)
Gwo, Jin-Ping
2001-06-01
Fracture network and preferential flow path images from exposed outcrops of geological formations, exposed soil pedon faces, and extracted soil columns and rock cores are often used to conceptualize and construct models to predict the fate and transport of subsurface contaminants. Both the scale resolutions inherent in these observations and the upscaling methods used to obtain macroscopic flow and transport parameters may result in uncertainties in the prediction. We present a mechanistic-based approach that utilizes a discrete fracture flow and transport model, a distributed and high performance computational architecture, and a genetic-based search algorithm to invert scale- representative, equivalent fracture networks or the preferential flow paths. Synthetic breakthrough curves (BTCs) and exposed structural information from known fracture networks in hypothetical soil columns are presented to the search algorithm. Using three genetic operators, a simple genetic algorithm (SGA) is able to invert the correct pictures of simple but not complex fracture networks. Solute transport experiments using soil columns often assume that the structure of soil columns is laterally uniform with respect to the macroscopic transport direction and the transport process is longitudinally one- dimensional. This assumption and the one BTC thus collected for each injection of solutes, even with flow interruptions, are not sufficient to guide the search algorithm toward the global optimum. Additional information (e.g., multiple solute BTCs along a cross section of the soil column) is necessary for the SGA to invert the correct fracture network. Three SGA population statistics, fracture network uncertainty, informatic entropy, and matrix-fracture contact area, are proposed to measure the uncertainty of SGA near optima. A positive correlation between the reduction of these statistics and the level of relevant information to better confine the SGA search space was found. The SGA search algorithm is then applied to a laboratory solute transport problem. Multiple scenarios of search constraints, derived from visually traced surface features, are examined. The hypothesis that variation in fracture aperture may reduce the uncertainty of SGA near optima is also tested. The results from these applications suggest that there is a certain degree of uncertainty regarding the flowing nature of the exposed fracture segments that are visually traced. The uncertainty of SGA near optima is not improved by incorporating fracture aperture information into the fracture networks. Breakthrough curves thus calculated have marginal improvement, relative to the uniform aperture SGA near optima, in fitting the observations. The lack of improvement may be caused by the relative uniform structure of the soil and the scale of the problem. It is further suggested that in applying the search algorithm to laboratory and field problems, one explores only the search scenarios that relevant information and search constraints may warrant.
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
Robot Path Integration in Manufacturing Processes: Genetic Algorithm Versus Ant Colony Optimization
Tewolde S. Tewolde; Weihua Sheng
2008-01-01
Tool path planning for automated manufacturing processes is a computationally complex task. This paper addresses the problem of tool path integration in the context of spray-forming processes. Tool paths for geometry-complicated parts are generated by partitioning them into individual freeform surfaces, generating the paths for each partition, and then, finally, interconnecting the paths from the different patches so as to
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.
Provably Efficient Algorithms for Numerical Tensor Edgar Solomonik
California at Berkeley, University of
://www.eecs.berkeley.edu/Pubs/TechRpts/2014/EECS-2014-170.html September 30, 2014 #12;Copyright © 2014, by the author(s). All rights reserved. Permission to make digital or hard copies of all or part of this work for personal or classroom use-Warshall all-pairs shortest-paths algorithm. 2.5D algorithms achieve lower interprocessor bandwidth cost
Provably Efficient Algorithms for Numerical Tensor Edgar Solomonik
California at Berkeley, University of
://www.eecs.berkeley.edu/Pubs/TechRpts/2014/EECS-2014-163.html August 29, 2014 #12;Copyright © 2014, by the author(s). All rights reserved. Permission to make digital or hard copies of all or part of this work for personal or classroom use-Warshall all-pairs shortest-paths algorithm. 2.5D algorithms achieve lower interprocessor bandwidth cost
NASA Technical Reports Server (NTRS)
Longendorfer, B. A.
1976-01-01
The construction of an autonomous roving vehicle requires the development of complex data-acquisition and processing systems, which determine the path along which the vehicle travels. Thus, a vehicle must possess algorithms which can (1) reliably detect obstacles by processing sensor data, (2) maintain a constantly updated model of its surroundings, and (3) direct its immediate actions to further a long range plan. The first function consisted of obstacle recognition. Obstacles may be identified by the use of edge detection techniques. Therefore, the Kalman Filter was implemented as part of a large scale computer simulation of the Mars Rover. The second function consisted of modeling the environment. The obstacle must be reconstructed from its edges, and the vast amount of data must be organized in a readily retrievable form. Therefore, a Terrain Modeller was developed which assembled and maintained a rectangular grid map of the planet. The third function consisted of directing the vehicle's actions.
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.
A computational study of routing algorithms for realistic transportation networks
Jacob, R.; Marathe, M.V.; Nagel, K.
1998-12-01
The authors carry out an experimental analysis of a number of shortest path (routing) algorithms investigated in the context of the TRANSIMS (Transportation Analysis and Simulation System) project. The main focus of the paper is to study how various heuristic and exact solutions, associated data structures affected the computational performance of the software developed especially for realistic transportation networks. For this purpose the authors have used Dallas Fort-Worth road network with very high degree of resolution. The following general results are obtained: (1) they discuss and experimentally analyze various one-one shortest path algorithms, which include classical exact algorithms studied in the literature as well as heuristic solutions that are designed to take into account the geometric structure of the input instances; (2) they describe a number of extensions to the basic shortest path algorithm. These extensions were primarily motivated by practical problems arising in TRANSIMS and ITS (Intelligent Transportation Systems) related technologies. Extensions discussed include--(i) time dependent networks, (ii) multi-modal networks, (iii) networks with public transportation and associated schedules. Computational results are provided to empirically compare the efficiency of various algorithms. The studies indicate that a modified Dijkstra`s algorithm is computationally fast and an excellent candidate for use in various transportation planning applications as well as ITS related technologies.
Mongi Marzoug; Paul Amayenc
1991-01-01
A range-profiling algorithm for rainfall rate retrieval from a single-frequency downward-looking spaceborne radar is presented. The algorithm is based on a linear reformulation of the radar equation. The path-integrated attenuation given by the surface echo measurement is used as a constraint for normalizing the range-gated rain echoes. The expected performances are studied analytically and compared with those of the approach
Optimal parallel algorithms for problems modeled by a family of intervals
NASA Technical Reports Server (NTRS)
Olariu, Stephan; Schwing, James L.; Zhang, Jingyuan
1992-01-01
A family of intervals on the real line provides a natural model for a vast number of scheduling and VLSI problems. Recently, a number of parallel algorithms to solve a variety of practical problems on such a family of intervals have been proposed in the literature. Computational tools are developed, and it is shown how they can be used for the purpose of devising cost-optimal parallel algorithms for a number of interval-related problems including finding a largest subset of pairwise nonoverlapping intervals, a minimum dominating subset of intervals, along with algorithms to compute the shortest path between a pair of intervals and, based on the shortest path, a parallel algorithm to find the center of the family of intervals. More precisely, with an arbitrary family of n intervals as input, all algorithms run in O(log n) time using O(n) processors in the EREW-PRAM model of computation.
Algorithms for Reliable Navigation and Wayfinding
Shazia Haque; Lars Kulik; Alexander Klippel
2006-01-01
\\u000a Wayfinding research has inspired several algorithms that compute the shortest, fastest, or even simplest paths between two\\u000a locations. Current navigation systems, however, do not take into account the navigational complexity of certain intersections.\\u000a A short route might involve a number of intersections that are difficult to navigate, because they offer more than one alternative\\u000a to turn left or right. The
Haddadi, Hamed
/CTS to avoid collisions from hidden terminals. But the packet delay and data congestion increase rapidly selected for study are carrier sense multiple access with collision avoidance (CSMA/CA) and dual busy tone1 Novel Clustering Algorithm Based on Minimal Path Loss Ratio for Medium Access Control in Vehicle
M. Marzoug; P. Amayenc
1990-01-01
A new range profiling algorithm for rainfall rate retrieval from a downward looking spaceborne one frequency radar is presented. It is based upon a linear reformulation of the radar equation.The path integrated attenuation given by the surface echo measurement is used as a constraint for normalizing the range gated rain echoes. The expected performances are studied analytically and compared with
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.
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.
Finding the dominant energy transmission paths in statistical energy analysis
NASA Astrophysics Data System (ADS)
Guasch, Oriol; Aragonès, Àngels
2011-05-01
A key issue for noise, vibration and harshness purposes, when modelling the vibroacoustic behaviour of a system, is that of determining how energy is transmitted from a given source, where external energy is being input, to a target where energy is to be reduced. In many situations of practical interest, a high percentage of the transmitted energy is driven by a limited set of dominant paths. For instance, this is at the core of the existence of transmission loss regulations between dwellings. In this work, it is shown that in the case of a system modelled with statistical energy analysis (SEA), the problem of ranking dominant paths can be posed as a variation of the so-called K shortest path problem in graph theory. An algorithm for the latter is then modified and adapted to obtain the sorted set of K dominant energy transmission paths in a SEA model. A numerical example to show its potential for practical applications is included.
A New Path Computation Algorithm and Its Implementation in NS2
Davide Adami; Christian Callegari; Stefano Giordano; Michele Pagano
2007-01-01
Originally conceived as a fast forwarding technique, MPLS provides support for traffic engineering and network survivability. Constrained-based path computation is a key building block for traffic engineering in MPLS networks, since it allows to select a path that satisfies assigned QoS requirements. In this paper, we introduce a novel path computation procedure which aims at improving the performance of the
Tool path integration for spray forming processes using a genetic algorithm
Weihua Sheng; Girma Tewolde; Heping Chen
2005-01-01
Spray forming is a new manufacturing process. The automated tool planning for this process is a nontrivial problem, especially for geometry-complicated parts consisting of multiple freeform surfaces. We have developed a tool path planning system which can automatically generate optimized tool plans. This paper focuses on the path integration problem, or how to connect the paths from different surface patches
Pokemon Cards and the Shortest Common Superstring
Mark Stamp; Austin E Stamp
2003-01-01
Evidence is presented that certain sequences of Pokemon cards are determined by selecting consecutive elements from a longer sequence. We then consider the problem of recovering the shortest common superstring (SCS), i.e., the shortest string that contains each of the Pokemon card sequences as a consecutive substring. The SCS problem arises in many applications, most notably in DNA sequencing.
An Evolutionary Artificial Potential Field Algorithm for Dynamic Path Planning of Mobile Robot
Qixin Cao; Yanwen Huang; Jingliang Zhou
2006-01-01
The artificial potential field (APF) method is widely used for autonomous mobile robot path-planning due to its simplicity and mathematical elegance. However, most researches are focused on solving the path-planning problem in a stationary environment, where both targets and obstacles are stationary. This paper proposes a new APF method for path-planning of mobile robots in a dynamic environment where the
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.
Dijkstra's Algorithm with Fibonacci Heaps: An Executable Description in CHR
Jon Sneyers; Tom Schrijvers; Bart Demoen
2006-01-01
We construct a readable, compact and ecien t implementation of Dijkstra's shortest path algorithm and Fibonacci heaps using Constraint Handling Rules (CHR), which is increasingly used as a high-level rule-based general-purpose programming language. We measure its performance in dieren t CHR systems, investigating both the theoretical asymp- totic complexity and the constant factors realized in practice. Constraint Handling Rules (CHR)
The capacitated multiple allocation hub location problem: Formulations and algorithms
Jamie Ebery; Mohan Krishnamoorthy; Andreas T. Ernst; Natashia Boland
2000-01-01
In this paper we consider and present formulations and solution approaches for the capacitated multiple allocation hub location problem. We present a new mixed integer linear programming formulation for the problem. We also construct an efficient heuristic algorithm, using shortest paths. We incorporate the upper bound obtained from this heuristic in a linear-programming-based branch-and-bound solution procedure. We present the results
A rounding algorithm for approximating minimum Manhattan networks1
Chepoi, Victor
A rounding algorithm for approximating minimum Manhattan networks1 Victor Chepoi, Karim Nouioua,nouioua,vaxes}@lif.univ-mrs.fr Abstract. For a set T of n points (terminals) in the plane, a Manhattan network on T is a network N(T) = (V T and for every pair of terminals, the network N(T) contains a shortest l1-path between them. A minimum Manhattan
Packing non-returning A-paths algorithmically EGRES --Egervary Research Group
Pap, Gyula
;definition G[U] is a called a "dragon" if all the nodes v U are "reachable inside U". U v I.e. for all v U dragons. U1 U2 U3 G/U1/U2/U3 A path in G/U1/U2/ · · · /Um is allowed if its pre-image can be extended by "inside reaching paths". G.P. Packing A-paths #12;DEF Contraction of a family of disjoint dragons. U1 U2 U
Information spread of emergency events: path searching on social networks.
Dai, Weihui; Hu, Hongzhi; Wu, Tunan; Dai, Yonghui
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
Zhou, Xuesong
Time Path Problem Lixing Yang State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong for continuous link travel times through variance and other statistics (e.g., Fu and Rilett 1998; Sun, Gu
Asymptotically-optimal path planning for manipulation using incremental sampling-based algorithms
Perez, Alejandro Tomas
A desirable property of path planning for robotic manipulation is the ability to identify solutions in a sufficiently short amount of time to be usable. This is particularly challenging for the manipulation problem due to ...
A stereophonic echo canceling algorithm for correct echo-path estimation
M. Kimoto; T. Furukawa; Shinsaku Morit
2001-01-01
The authors had proposed a stereophonic echo canceller for correct echo path estimation. We pay attention to the convergence value of the filter coefficient vector of the multichannel least mean squares (MC-LMS) and that of the compact multichannel echo canceller (CEC) and use those differences. Concretely, the coefficient vector of the MC-LMS is converged to a correct echo-path by properly
Visibility-Polygon Search and Euclidean Shortest Paths
Takao Asano; Tetsuo Asano; Leonidas J. Guibas; John Hershberger; Hiroshi Imai
1985-01-01
Consider a collection of disjoint polygons in the plane containing a total of n edges. We show how to build, in O(n2) time and space, a data structure from which in O(n) time we can compute the visibility polygon of a given point with respect to the polygon collection. As an application of this structure, the visibility graph of the
A Particle Swarm Optimization Algorithm with Path Relinking for the Location Routing Problem
Yannis Marinakis; Magdalene Marinaki
2008-01-01
This paper introduces a new hybrid algorithmic nature inspired approach based on particle swarm optimization, for solving\\u000a successfully one of the most popular logistics management problems, the location routing problem (LRP). The proposed algorithm\\u000a for the solution of the location routing problem, the hybrid particle swarm optimization (HybPSO-LRP), combines a particle\\u000a swarm optimization (PSO) algorithm, the multiple phase neighborhood search
Awi Federgruen; Michal Tzur
1991-01-01
This paper is concerned with the general dynamic lot size model, or (generalized) Wagner-Whitin model. Let n denote the number of periods into which the planning horizon is divided. We describe a simple forward algorithm which solves the general model in 0(n log n) time and 0(n) space, as opposed to the well-known shortest path algorithm advocated over the last
An Efficient Path Selection Algorithm for OnDemand LinkState HopbyHop Routing
California at Santa Cruz, University of
lished frequently in adhoc networks, proactive maintenance of paths does not scale well. To minimize and n: number of nodes). I. INTRODUCTION In the wired networks of the Internet, proactive routing pro tocols are used to compute routes to all destinations in the net work. However, proactive routing
Guo, Yi
are free forp navigation To recognize regions or locations in the environment To recognize specific objects visible 3 P t ti l Fi ldwhere features disappear or get visible 3. Potential Field Imposing a mathematical Decomposition Fixed-size cell decomposition such as grid- based representation.representation. #12;Road-Map Path
A modified artificial potential field algorithm for mobile robot path planning
Ningning Qi; Bojun Ma; Xian'en Liu; Zhenxin Zhang; Dongchun Ren
2008-01-01
A modified APF (artificial potential field) based method is proposed for mobile robot path planning. To address the local minima problem in the classical APF, a method composed of robot regression and potential field filling is proposed. Furthermore, by adjusting potential field in the environment dynamically, the collision problem is also well settled. Simulation experiments, in which eight sonar transmitters
An artificial immune system algorithm for CDMA multiuser detection over multi-path channels
Maoguo Gong; Ling Wang; Licheng Jiao; Haifeng Du
2005-01-01
Based on the Antibody Clonal Selection Theory of immunology, we put forward a novel clonal selection algorithm for multiuser detection in Code-division Multiple-access Systems. By using the clonal selection operator, the new algorithm can carry out the global search and the local search in many directions rather than one direction around the same individual simultaneously. After discussing the main characters
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
A path-following interior-point algorithm for linear and quadratic problems
Wright, S.J.
1993-12-01
We describe an algorithm for the monotone linear complementarity problem that converges for many positive, not necessarily feasible, starting point and exhibits polynomial complexity if some additional assumptions are made on the starting point. If the problem has a strictly complementary solution, the method converges subquadratically. We show that the algorithm and its convergence extend readily to the mixed monotone linear complementarity problem and, hence, to all the usual formulations of the linear programming and convex quadratic programming problems.
Algorithms for Rapid Computation of Some Distance Functions Between Objects for Path Planning
K. Sridharan; Harry E. Stephanou
1994-01-01
This paper presents efficient algorithms for computing new types of distance measures. One of the measures denoted by drho+ (A, B) characterizes proximity of non-intersecting objects A and B taking into account their shapes. The second measure denoted by ?(?; A, B) characterizes the penetration between two intersecting objects. The main contributions include: 1) O(m log n+n log m) algorithms
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.
NASA Astrophysics Data System (ADS)
Xu, Xianrui; Li, Xiaojie; Hu, Yujie; Peng, Zhongren
2012-12-01
In recent years, the increasing development of traffic information collection technology based on floating car data has been recognized, which gives rise to the establishment of real-time traffic information dissemination system in many cities. However, the recent massive construction of urban elevated roads hinders the processing of corresponding GPS data and further extraction of traffic information (e.g., identifying the real travel path), as a result of the frequent transfer of vehicles between ground and elevated road travel. Consequently, an algorithm for identifying the travel road type (i.e., elevated or ground road) of vehicles is designed based on the vehicle traveling features, geometric and topological characteristics of the elevated road network, and a trajectory model proposed in the present study. To be specific, the proposed algorithm can detect the places where a vehicle enters, leaves or crosses under elevated roads. An experiment of 10 sample taxis in Shanghai, China was conducted, and the comparison of our results and results that are obtained from visual interpretation validates the proposed algorithm.
A new graph model and algorithms for consistent superstring problems†
Na, Joong Chae; Cho, Sukhyeun; Choi, Siwon; Kim, Jin Wook; Park, Kunsoo; Sim, Jeong Seop
2014-01-01
Problems related to string inclusion and non-inclusion have been vigorously studied in diverse fields such as data compression, molecular biology and computer security. Given a finite set of positive strings and a finite set of negative strings , a string ? is a consistent superstring if every positive string is a substring of ? and no negative string is a substring of ?. The shortest (resp. longest) consistent superstring problem is to find a string ? that is the shortest (resp. longest) among all the consistent superstrings for the given sets of strings. In this paper, we first propose a new graph model for consistent superstrings for given and . In our graph model, the set of strings represented by paths satisfying some conditions is the same as the set of consistent superstrings for and . We also present algorithms for the shortest and the longest consistent superstring problems. Our algorithms solve the consistent superstring problems for all cases, including cases that are not considered in previous work. Moreover, our algorithms solve in polynomial time the consistent superstring problems for more cases than the previous algorithms. For the polynomially solvable cases, our algorithms are more efficient than the previous ones. PMID:24751868
Path optimization using sub-Riemannian manifolds with applications to astrodynamics
Whiting, James K. (James Kalani), 1980-
2011-01-01
Differential geometry provides mechanisms for finding shortest paths in metric spaces. This work describes a procedure for creating a metric space from a path optimization problem description so that the formalism of ...
An Implementation of Mobile Robots' Path Planning and Tracing Based on Fuzzy PID Algorithms
Wu Zhou; Yanjun Fang
2008-01-01
To participate in the Asia Broadcast Union Robocon Contest 2008, some intelligent mobile robots are designed in Wuhan University of China. The two-wheel robot is navigated by two separated photoelectric encoders fixed beside the wheels symmetrically. The encoders can give the feedback of the practical robot's displacement and speed. The advanced fuzzy PID algorithm is proposed to improve the conventional
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
The stencil buffer sweep plane algorithm for 5-axis CNC tool path verification
Erik L. J. Bohez; Nguyen Thi Hong Minh; Ben Kiatsrithanakorn; Peeraphan Natasukon; Huang Ruei-yun; Le Thanh Son
2003-01-01
A new algorithm based on the sweep plane approach to determine the machined part geometry in 5-axis machining with general APT tools is presented. Undercut and overcut can be determined. Collision detection between the toolholder, workpiece and workpiece fixture can also be detected. The subtraction of the removed material is obtained for each sweep plane by using a stencil buffer.
G. Yin; C. Ion; V. Krishnamurthy
2009-01-01
Stochastic optimization\\/approximation algorithms are widely used to recursively estimate the optimum of a suitable function\\u000a or its root under noisy observations when this optimum or root is a constant or evolves randomly according to slowly time-varying\\u000a continuous sample paths. In comparison, this paper analyzes the asymptotic properties of stochastic optimization\\/approximation\\u000a algorithms for recursively estimating the optimum or root when it
Corina Popescu; Jose L. Martinez Lastra
2010-01-01
This paper presents an algorithm that selects a group of independent events out of a given set of possibly conflicting actions. The procedure is matrix-based and was implemented in JAVA to guide backtracking scheduling search based on a Petri Net-derived model of flow. The manufacturing systems particularly addressed in the implementation are using Web Services to implement the Service-Oriented-Architecture pattern.
Time-Optimal Path Planning and Control Using Neural Networks and a Genetic Algorithm
Nachol Chaiyaratana; Ali M. S. Zalzala
2002-01-01
This paper presents the use of neural networks and a genetic algorithm in time-optimal control of a closed-loop 3-dof robotic system. Extended Kohonen networks which contain an additional lattice of output neurons are used in conjunction with PID controllers in position control to minimise command tracking errors. The extended Kohonen networks are trained using reinforcement learning where the overall learning
S. A. Bortoff; E. Hartford
2000-01-01
In this paper, a two step path-planning algorithm for UAVs is proposed. The algorithm generates a stealthy path through a set of enemy radar sites of known location, and provides an intuitive way to trade-off stealth versus path length. In the first step, a suboptimal rough-cut path is generated through the radar sites by constructing and searching a graph based
Campodonico, Miguel A; Andrews, Barbara A; Asenjo, Juan A; Palsson, Bernhard O; Feist, Adam M
2014-09-01
The production of 75% of the current drug molecules and 35% of all chemicals could be achieved through bioprocessing (Arundel and Sawaya, 2009). To accelerate the transition from a petroleum-based chemical industry to a sustainable bio-based industry, systems metabolic engineering has emerged to computationally design metabolic pathways for chemical production. Although algorithms able to provide specific metabolic interventions and heterologous production pathways are available, a systematic analysis for all possible production routes to commodity chemicals in Escherichia coli is lacking. Furthermore, a pathway prediction algorithm that combines direct integration of genome-scale models at each step of the search to reduce the search space does not exist. Previous work (Feist et al., 2010) performed a model-driven evaluation of the growth-coupled production potential for E. coli to produce multiple native compounds from different feedstocks. In this study, we extended this analysis for non-native compounds by using an integrated approach through heterologous pathway integration and growth-coupled metabolite production design. In addition to integration with genome-scale model integration, the GEM-Path algorithm developed in this work also contains a novel approach to address reaction promiscuity. In total, 245 unique synthetic pathways for 20 large volume compounds were predicted. Host metabolism with these synthetic pathways was then analyzed for feasible growth-coupled production and designs could be identified for 1271 of the 6615 conditions evaluated. This study characterizes the potential for E. coli to produce commodity chemicals, and outlines a generic strain design workflow to design production strains. PMID:25080239
3D Motion Planning Algorithms for Steerable Needles Using Inverse Kinematics
Duindam, Vincent; Xu, Jijie; Alterovitz, Ron; Sastry, Shankar; Goldberg, Ken
2010-01-01
Steerable needles can be used in medical applications to reach targets behind sensitive or impenetrable areas. The kinematics of a steerable needle are nonholonomic and, in 2D, equivalent to a Dubins car with constant radius of curvature. In 3D, the needle can be interpreted as an airplane with constant speed and pitch rate, zero yaw, and controllable roll angle. We present a constant-time motion planning algorithm for steerable needles based on explicit geometric inverse kinematics similar to the classic Paden-Kahan subproblems. Reachability and path competitivity are analyzed using analytic comparisons with shortest path solutions for the Dubins car (for 2D) and numerical simulations (for 3D). We also present an algorithm for local path adaptation using null-space results from redundant manipulator theory. Finally, we discuss several ways to use and extend the inverse kinematics solution to generate needle paths that avoid obstacles. PMID:21359051
NASA Astrophysics Data System (ADS)
Tzionas, Panagiotis G.; Tsalides, Phillippos G.; Thanailakis, Adonios
1993-11-01
A new algorithm for the estimation of the minimum cost path between a pair of points in the 3D space and its VLSI implementation by means of a new multistate conditional 3D cellular automata (CA) architecture are presented. The proposed algorithm establishes the minimum cost path between the source and target points along the maximum allowable change of direction on the 3D grid in the presence of obstacles. Lines at arbitrary angles on this grid are piecewise approximated with elementary line segments along the principle axes of the grid, as well as along the diagonals of the 3D elementary Cartesian cube and along the diagnosis of the faces of this cube. The proposed algorithm guarantees to find the minimum coat path in 3D space, if such as path exists. The VLSI implementation presented is realized by mapping the 3D CA architecture onto a 2D chip surface, resulting in a very high speed of operation, while the storage requirements are kept low.
The Trade-offs of Multicast Trees and Algorithms
Liming Wei; Deborah Estrin
1995-01-01
Multicast trees can be shared across sources (shared trees) or may be source-specific (shortest pathtrees). Inspired by recent interests in using shared trees for interdomain multicasting, we investigate thetrade-offs among shared tree types and source specific shortest path trees, by comparing performanceover both individual multicast group and the whole network. The performance is evaluated in termsof path length, link cost,
Shortest-route formulation of mixed-model assembly line balancing problem
Erdal Erel; Hadi Gökçen
1999-01-01
A shortest-route formulation of the mixed-model assembly line balancing problem is presented. Common tasks across models are assumed to exist and these tasks are performed in the same stations. The formulation is based on an algorithm which solves the single-model version of the problem. The mixed-model system is transformed into a single-model system with a combined precedence diagram. The model
Automatic tracking of neuro vascular tree paths
NASA Astrophysics Data System (ADS)
Suryanarayanan, S.; Gopinath, A.; Mallya, Y.; Shriram, K. S.; Joshi, M.
2006-03-01
3-D analysis of blood vessels from volumetric CT and MR datasets has many applications ranging from examination of pathologies such as aneurysm and calcification to measurement of cross-sections for therapy planning. Segmentation of the vascular structures followed by tracking is an important processing step towards automating the 3-D vessel analysis workflow. This paper demonstrates a fast and automated algorithm for tracking the major arterial structures that have been previously segmented. Our algorithm uses anatomical knowledge to identify the start and end points in the vessel structure that allows automation. Voxel coding scheme is used to code every voxel in the vessel based on its geodesic distance from the start point. A shortest path based iterative region growing is used to extract the vessel tracks that are subsequently smoothed using an active contour method. The algorithm also has the ability to automatically detect bifurcation points of major arteries. Results are shown for tracking the major arteries such as the common carotid, internal carotid, vertebrals, and arteries coming off the Circle of Willis across multiple cases with various data related and pathological challenges from 7 CTA cases and 2 MR Time of Flight (TOF) cases.
NASA Astrophysics Data System (ADS)
Wojcik, E. A.; Ni, D.; Lam, T. M.; Le Coz, Y. L.
2015-07-01
We have created the first stochastic SoP (Sum-over-Paths) algorithm to extract third-order impulse-response (IR) moment within RC IC interconnects. It employs a newly discovered Feynman SoP Postulate. Importantly, our algorithm maintains computational efficiency and full parallelism. Our approach begins with generation of s-domain nodal-voltage equations. We then perform a Taylor-series expansion of the circuit transfer function. These expansions yield transition diagrams involving mathematical coupling constants, or weight factors, in integral powers of complex frequency s. Our SoP Postulate enables stochastic evaluation of path sums within the circuit transition diagram to order s3-corresponding to the order of IR moment (m3) we seek here. We furnish, for the first time, an informal algebraic proof independently validating our SoP Postulate and algorithm. We list, as well, detailed procedural steps, suitable for coding, that define an efficient stochastic algorithm for m3 IR extraction. Origins of the algorithm's statistical "capacitor-number cubed" correction and "double-counting" weight factors are explained, for completeness. Our algorithm was coded and successfully tested against exact analytical solutions for 3-, 5-, and 10-stage RC lines. We achieved better than 0.65% 1-? error convergence, after only 10K statistical samples, in less than 1 s of 2-GHz Pentium® execution time. These results continue to suggest that stochastic SoP algorithms may find useful application in circuit analysis of massively coupled networks, such as those encountered in high-end digital IC-interconnect CAD.
Minimal Realizations of Linear Systems: The "Shortest Basis" Approach
Forney, G. David, Jr.
Given a discrete-time linear system C, a shortest basis for C is a set of linearly independent generators for C with the least possible lengths. A basis B is a shortest basis if and only if it has the predictable span ...
Encoding user motion preferences in harmonic function path planning
Giles D'silva; Manfred Huber
2009-01-01
Humans have unique motion preferences when pursuing a given task. These motion preferences could be expressed as moving in a straight line, following the wall, avoiding sharp turns, avoiding damp surfaces or choosing the shortest path. While it would be very useful for a range of applications to allow robot systems or artificial agents to generate paths with similar specific
Dev C. Chen; Jan M. Rabaey
1992-01-01
A field-programmable multiprocessor integrated circuit, PADDI (programmable arithmetic devices for high-speed digital signal processing), has been designed for the rapid prototyping of high-speed data paths typical to real-time digital signal processing applications. The processor architecture addresses the key requirements of these data paths: (a) fast, concurrently operating, multiple arithmetic units, (b) conflict-free data routing, (c) moderate hardware multiplexing (of the
A methodology for predicting minimum travel paths using real-time traffic network data
Liu, Chang
1991-01-01
, existing traffic simulation and optimization models have been reviewed, and appropriate models have been chosen to predict link travel time and fuel consumption. Link-node types of mathematical networks have been established, and minimum travel distance... Integration of ATMS with ADIS Traffic Data Fusion For Link Time Prediction . . NETWORK ANALYSIS Shortest Path Problem Shortest Path with Fixed-Charges Problem . . STUDY DESIGN REVIEW OF EXISTING TRAFFIC MODELS PASSER II-87 PASSER III-88 TRANSYT-7F...
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?
Finding a least hop(s) path subject to multiple additive constraints Gang Cheng, Nirwan Ansari*
Ansari, Nirwan
Finding a least hop(s) path subject to multiple additive constraints Gang Cheng, Nirwan Ansari referred to as the least hop(s) multiple additively constrained path (LHMACP) selection, which is NP of computing All Hops k-shortest Paths (AHKP) between a source and a destination. Through extensive analysis
Path Planning for Autonomous Underwater Vehicles
Clément Pêtrès; Yan Pailhas; Pedro Patrón; Yvan R. Petillot; Jonathan Evans
2007-01-01
Efficient path planning algorithms are a crucial issue for modern autonomous underwater vehicles. Classical path planning algorithms in artificial intelligence are not designed to deal with wide continuous environments prone to currents. We present a novel Fast Marching based approach to address the following issues. First, we develop an algorithm we call FM* to efficiently extract a continuous path from
Vladimir J. Lumelsky
1991-01-01
A number of existing maze-searching and robot motion planning algorithms are studied from the standpoint of a single performance criterion. The main motivation is to build a framework for selecting basic planning algorithms for autonomous vehicles and robot arm manipulators that operate in an environment filled with unknown obstacles of arbitrary shapes. In choosing an appropriate criterion, it is noted
On path selection for traffic with bandwidth guarantees
Qingming Ma; Peter Steenkiste
1997-01-01
Transmission of multimedia streams imposes a minimum-band width requirementon the path being used to ensure end-to-end Qual ity-of- Service (QoS) guarantees. While any shortest-path algorit hm can be used to select a feasible path, additional constraints th at limit resource consumption and balance the network load are neede d to achieve efficient resource utilization. We present a syst ematic evaluation
R. Kubota; E. Nishiyama; K. Murase; J. Kasahara
2005-01-01
Seismic tomography techniques have been rapidly developed to interpret crustal seismic refraction data. Forward modeling approaches, however, are also necessary to examine an initial model for inversion and\\/or later phases. Ray-paths and travel times of later phases, as well as fastest arrivals, such as reflection, later refraction and P-SV converted waves, provide indispensable information for seismic crustal structure analyses. Although
Peter Nalbach; Akihito Ishizaki; Graham R. Fleming; Michael Thorwart
2011-01-01
We determine the real-time quantum dynamics of a biomolecular donor-acceptor system in order to describe excitonic energy transfer in the presence of slow environmental Gaussian fluctuations. For this, we compare two different approaches. On the one hand, we use the numerically exact iterative quasi-adiabatic propagator path-integral scheme that incorporates all non-Markovian contributions. On the other, we apply the second-order cumulant
Rapid approximation for optimal paths in phase space
Chyon Hae Kim; Hiroshi Tsujino; Shigeki Sugano
2011-01-01
This paper addresses optimal motion for general machines. Approximation for optimal motion needs a global path planning algorithm that precisely calculates the whole dynamics of a machine in a brief calculation. We propose a path planning algorithm that is composed of a path searching algorithm and a pruning algorithm. The pruning algorithm is based on our analysis for the resemblances
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.
An Almost Linear Time Algorithm for Field Splitting in Radiation Therapy.
Wu, Xiaodong; Dou, Xin; Bayouth, John E; Buatti, John M
2013-08-01
In this paper, we study an interesting geometric partition problem, called optimal field splitting, which arises in Intensity-Modulated Radiation Therapy (IMRT). In current clinical practice, a multi-leaf collimator (MLC) with a maximum leaf spread constraint is used to deliver the prescribed intensity maps (IMs). However, the maximum leaf spread of an MLC may require to split a large intensity map into several overlapping sub-IMs with each being delivered separately. We develop a close-to-linear time algorithm for solving the field splitting problem while minimizing the total complexity of the resulting sub-IMs, thus improving the treatment delivery efficiency. Meanwhile, our algorithm strives to minimize the maximum beam-on time of those sub-IMs. Our basic idea is to formulate the field splitting problem as computing a shortest path in a directed acyclic graph, which expresses a special "layered" structure. The edge weights of the graph satisfy the Monge property, which enables us to solve this shortest path problem by examining only a small portion of the graph, yielding a close-to-linear time algorithm. To minimize the maximum beam-on time of the resulting sub-IMs, we consider an interesting min-max slope path problem in a monotone polygon which is solvable in linear time. The min-max slope path problem may be of interest in its own right. Experimental results based on real medical data and computer generated IMs showed that our new algorithm runs fast and produces high quality field splitting results. PMID:24999294
A GENETIC ALGORITHM FOR THE WEIGHT SETTING PROBLEM ...
2001-10-09
Oct 9, 2001 ... Interior Gateway Protocols (IGP) are used within the AS, while. Exterior ... router knows the complete topology, each router can compute all needed shortest paths [4]. .... Lin and Wang [20] present a completely different ap-.
Tianchi Ma; Rajkumar Buyya
2005-01-01
Parameter-sweep has been widely adopted in large numbers of scientific applications. Parameter-sweep features need to be incorporated into Grid workflows so as to increase the scale and scope of such applications. New scheduling mechanisms and algorithms are required to provide optimized policy for resource allocation and task arrangement in such a case. This paper addresses scheduling sequential parameter-sweep tasks in
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
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
Aguilar-Mogas, Antoni; Giménez, Xavier; Bofill, Josep Maria
2010-10-01
The intrinsic reaction coordinate (IRC) curve is used widely as a representation of the Reaction Path and can be parameterized taking the potential energy as a reaction coordinate (Aguilar-Mogas et al., J Chem Phys 2008, 128, 104102). Taking this parameterization and its variational nature, an algorithm is proposed that permits to locate this type of curve joining two points from an arbitrary curve that joints the same initial and final points. The initial and final points are minima of the potential energy surface associated with the geometry of reactants and products of the reaction whose mechanism is under study. The arbitrary curves are moved toward the IRC curve by a Runge-Kutta-Fehlberg technique. This technique integrates a set of differential equations resulting from the minimization until value zero of the line integral over the Weierstrass E-function. The Weierstrass E-function is related with the second variation in the theory of calculus of variations. The algorithm has been proved in real chemical systems. PMID:20652993
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.
The Trade-offs of Multicast Trees and Algorithms
Deborah Estrin; Liming Wei
1994-01-01
Multicast trees can be shared across sources (shared trees)or may be source-specific (shortest path trees). Inspired byrecent interests in using shared trees for interdomain multicasting,we investigate the trade-offs among shared treetypes and source specific shortest path trees, by comparingperformance over both individual multicast group and thewhole network. The performance is evaluated in terms ofpath length, link cost, and traffic concentration.We
Energy-efficient Paths in Radio Networks Rene Beier1
Matijevic, Domagoj
Introduction The shortest-path problem is one of the fundamental problems which has been studied for a long, Cp is a node-dependent offset cost and |pq| denotes the Euclidean distance between p and q. For every in wireless networking. In recent years wireless network technology has gained tremendous importance
Traffic engineering approach to path selection in optical burst switching networks
NASA Astrophysics Data System (ADS)
Teng, Jing; Rouskas, George N.
2005-11-01
It is usually assumed that optical burst switching (OBS) networks use the shortest path routing along with next-hop burst forwarding. The shortest path routing minimizes delay and optimizes utilization of resources, however, it often causes certain links to become congested while others remain underutilized. In a bufferless OBS network in which burst drop probability is the primary metric of interest, the existence of a few highly congested links could lead to unacceptable performance for the entire network. We take a traffic engineering approach to path selection in OBS networks with the objective of balancing the traffic across the network links to reduce congestion and to improve overall performance. We present an approximate integer linear optimization problem as well as a simple integer relaxation heuristic to solve the problem efficiently for large networks. Numerical results demonstrate that our approach is effective in reducing the network-wide burst drop probability, in many cases significantly, over the shortest path routing.
Minimum Wheel-Rotation Paths for Differential-Drive Mobile Hamidreza Chitsaz
LaValle, Steven M.
, with the goal of classifying solutions in the spirit of Dubins curves and Reeds-Shepp curves for car-like robotsMinimum Wheel-Rotation Paths for Differential-Drive Mobile Robots Hamidreza Chitsaz , Steven M. LaValle, Devin J. Balkcom, and Matthew T. Mason August 7, 2007 Abstract The shortest paths for a mobile robot
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.
PATH PLANNING BY MULTIHEURISTIC SEARCH VIA SUBGOALS
Pekka Isto
1996-01-01
An efficient path planning algorithm for general 6 degrees of freedom robots is presented in the paper. The path planner is based on multiheuristic A * search algorithm with dynamic subgoal generation for rapid escaping from deep local-minimum wells. The algorithm has been implemented as an extension to a robot off-line programming and simulation system for testing. The presented test
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
NASA Astrophysics Data System (ADS)
Moreno Oliva, Víctor Iván; Castañeda Mendoza, Álvaro; Campos García, Manuel; Díaz Uribe, Rufino
2011-09-01
The null screen is a geometric method that allows the testing of fast aspherical surfaces, this method measured the local slope at the surface and by numerical integration the shape of the surface is measured. The usual technique for the numerical evaluation of the surface is the trapezoidal rule, is well-known fact that the truncation error increases with the second power of the spacing between spots of the integration path. Those paths are constructed following spots reflected on the surface and starting in an initial select spot. To reduce the numerical errors in this work we propose the use of the Dijkstra algorithm.1 This algorithm can find the shortest path from one spot (or vertex) to another spot in a weighted connex graph. Using a modification of the algorithm it is possible to find the minimal path from one select spot to all others ones. This automates and simplifies the integration process in the test with null screens. In this work is shown the efficient proposed evaluating a previously surface with a traditional process.
Path planning for virtual bronchoscopy.
Negahdar, Mohamadreza; Ahmadian, Alireza; Navab, Nassir; Firouznia, Kavous
2006-01-01
We have developed an automated path planning method, which enables virtual bronchoscopic 3D multidetector computed tomography (MDCT) image analysis and follow on image-guided bronchoscopy. The method fundamentals are novel combination of distance transformation and snake-based models. The computation time of our algorithm is faster than similar works and there were no missing or false branches in the final path of airways. The planned path is suitable for quantitative airway analysis and smooth virtual navigation. PMID:17946384
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
Relative Improvement by Alternative Solutions for Classes of Simple Shortest Path Problems
with Uncertain Data -- Part I: Strings of Pearls Gn with Unbiased Perturbations l l l l l l l l s s s s s s s 3 3 of this section we introduce the considered model in detail: the graph model (string of pearls Gn) and an unbiased.1 The Model We consider the following graph model: Definition 1.1 (string of pearls Gn) Consider a weighted
Relative Improvement by Alternative Solutions for Classes of Simple Shortest Path Problems
with Uncertain Data -- Part II: Strings of Pearls Gn,r with Biased Perturbations l l l l l l l l the considered models in detail: the graph model (string of pearls Gn,r) and two different biased perturbation. We finish with conclusions in Section 5. 1.1 The Models Definition 1.1 (string of pearls Gn
On designing a shortest-path-based cache replacement in a transcoding proxy
Hao-ping Hung; Ming-syan Chen
2009-01-01
The technology advance in network has accelerated the development of multimedia applications over the wired and wireless communication.\\u000a To alleviate network congestion and to reduce latency and workload on multimedia servers, the concept of multimedia proxy\\u000a has been proposed to cache popular contents. Caching the data objects can relieve the bandwidth demand on the external network,\\u000a and reduce the average
The Multiple Choice Elementary Constrained Shortest Path Problem Karen Smilowitz Guangming Zhang
Hazen, Gordon
to solve the Vehicle Routing Problem (VRP) and variations of the VRP, including the Pickup and Delivery®ort required to solve the linear relaxation of the VRP at the nodes of the branch-and-price tree by considering
The Multiple Choice Elementary Constrained Shortest Path Problem Karen Smilowitz Guangming Zhang
Smilowitz, Karen
Problem (VRP) and variations of the VRP, including the Pickup and Delivery Problem; see, for example the linear relaxation of the VRP at the nodes of the branch-and-price tree by considering a reduced subset
NASA Astrophysics Data System (ADS)
Rajagopalan, Srinivasan; Robb, Richard
2006-03-01
The degree of match between the delineation result produced by a segmentation technique and the ground truth can be assessed using robust "presence-absence" resemblance measures. Previously, we had investigated and introduced an exhaustive list of similarity indices for assessing multiple segmentation techniques. However, these measures are highly sensitive to even minor boundary perturbations which imminently manifest in the segmentations of random biphasic spaces reminiscent of the stochastic pore-solid distributions in the tissue engineering scaffolds. This paper investigates the ideas adapted from ecology to emphasize global resemblances and ignore minor local dissimilarities. It uses concepts from graph theory to perform controlled local mutations in order to maximize the similarities. The effect of this adjustment is investigated on a comprehensive list (forty nine) of similarity indices sensitive to the over- and under- estimation errors associated with image delineation tasks.
Shortest Average Routing Path-Based d-hop Clustering in wireless sensor networks
Ailian Jiangl; Weili Wu; Keming Xie; Donghyun Kirn; Wei Wang
2010-01-01
In the paper, we propose a new d-hop Clustering method for a clustering-based multi-hop routing scheme in large-scale wireless sensor network. d-hop clustering means that each cluster contains all nodes that are at distance at most d-hops from the clusterhead, so that the number of clusters can be getting smaller to make it possible to guarantee the combined system performances
The All-Pair Shortest-Path Problem in Shared-Memory Heterogeneous Systems
Llanos, Diego R.
-Arranz, Yuri Torres, Diego R. Llanos, Ph.D., and Arturo Gonzalez-Escribano, Ph.D. Departamento de Inform, ed.). By Hector Ortega-Arranz, Yuri Torres, Diego R. Llanos and Arturo Gonzalez-Escribano Copyright c
Weifeng Huang; Anan Osothsilp; Farzad Pourboghrat
2010-01-01
In this paper, a vision-based obstacle avoiding path generation problem is considered for autonomous mobile robots under a top-view workspace. The collision-free path planning problem is converted to a convex optimization problem that can be solved numerically using linear matrix inequalities (LMI). A new optimal (shortest) path cost formulation is given for LMI optimization using a novel Line of Sight
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.
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.
Optimization of Operation Sequence in CNC Machine Tools Using Genetic Algorithm
NASA Astrophysics Data System (ADS)
Abu Qudeiri, Jaber; Yamamoto, Hidehiko; Ramli, Rizauddin
The productivity of machine tools is significantly improved by using microcomputer based CAD/CAM systems for NC program generation. Currently, many commercial CAD/CAM packages that provide automatic NC programming have been developed and applied to various cutting processes. Many cutting processes machined by CNC machine tools. In this paper, we attempt to find an efficient solution approach to determine the best sequence of operations for a set of operations that located in asymmetrical locations and different levels. In order to find the best sequence of operations that achieves the shortest cutting tool travel path (CTTP), genetic algorithm is introduced. After the sequence is optimized, the G-codes that use to code for the travel time is created. CTTP can be formulated as a special case of the traveling salesman problem (TSP). The incorporation of genetic algorithm and TSP can be included in the commercial CAD/CAM packages to optimize the CTTP during automatic generation of NC programs.
Continuous Path Planning with Multiple Constraints
Mitchell, Ian
paths for unmanned aerial vehicles through enviroments with varying levels of threat. Paths an algorithm which generates paths whose costs lie on the Pareto optimal surface for each possible destina destination can be rapidly evaluated. To handle constraints, we sample the Pareto optimal surface looking
Removing False Paths from Combinational Modules 1
Yuji Kukimoto; Robert K. Brayton
The existence of false paths complicates the task of accurate tim- ing analysis significantly. A technique to remove false paths from a combinational circuit without degrading its performance h as a prac- tical value since topological timing analysis is then good e nough to estimate the performance of false-path-free circuits accu rately. One can think of the KMS algorithm (1)
Reliable routing algorithm based on fuzzy logic for Mobile Ad Hoc Network
Golnoosh Ghalavand; A. Dana; A. Ghalavand; Mahnaz Rezahosieni
2010-01-01
For unpredictable manner of mobile ad hoc network (manet), due to mobility of nodes in network, the shortest path is not necessarily the better path. If we do not consider the stability of routing path, then wireless links may be easily broken. Hence it is important to find a route that endures a longer time. Recently, efforts in this field
Blind Alley Aware ACO Routing Algorithm
NASA Astrophysics Data System (ADS)
Yoshikawa, Masaya; Otani, Kazuo
2010-10-01
The routing problem is applied to various engineering fields. Many researchers study this problem. In this paper, we propose a new routing algorithm which is based on Ant Colony Optimization. The proposed algorithm introduces the tabu search mechanism to escape the blind alley. Thus, the proposed algorithm enables to find the shortest route, even if the map data contains the blind alley. Experiments using map data prove the effectiveness in comparison with Dijkstra algorithm which is the most popular conventional routing algorithm.
Metabolic PathFinding: inferring relevant pathways in biochemical networks.
Croes, Didier; Couche, Fabian; Wodak, Shoshana J; van Helden, Jacques
2005-07-01
Our knowledge of metabolism can be represented as a network comprising several thousands of nodes (compounds and reactions). Several groups applied graph theory to analyse the topological properties of this network and to infer metabolic pathways by path finding. This is, however, not straightforward, with a major problem caused by traversing irrelevant shortcuts through highly connected nodes, which correspond to pool metabolites and co-factors (e.g. H2O, NADP and H+). In this study, we present a web server implementing two simple approaches, which circumvent this problem, thereby improving the relevance of the inferred pathways. In the simplest approach, the shortest path is computed, while filtering out the selection of highly connected compounds. In the second approach, the shortest path is computed on the weighted metabolic graph where each compound is assigned a weight equal to its connectivity in the network. This approach significantly increases the accuracy of the inferred pathways, enabling the correct inference of relatively long pathways (e.g. with as many as eight intermediate reactions). Available options include the calculation of the k-shortest paths between two specified seed nodes (either compounds or reactions). Multiple requests can be submitted in a queue. Results are returned by email, in textual as well as graphical formats (available in http://www.scmbb.ulb.ac.be/pathfinding/). PMID:15980483
Adaptive tool path planning applied in manufacturing optimization
J. Radej; L. Budin; Z. Mihajlovic
2004-01-01
Paper describes research done on algorithms for the generation of gouge-free nonisoparametric tool paths across surface plane segments obtained through triangulation partitioning. Along with contiguous trajectory sequences, adaptive tool path planning introduces partially discontinuous tool trajectories. Algorithm achieves the necessary trajectory continuity by the insertion of the auxiliary tool-orientation trajectories. The tool passes over the path gaps are accomplished through
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.
Algorithm Engineering: It's All About Speed
Moret, Bernard
? Research Tools: run many experiments to test hypotheses and for discovery Production Tools: obviously, save, shortest paths, convex hulls, Delaunay triangulations, matching and flow). Rome School on Alg. Eng. p.8 to enable the design of much better solutions than are possible for the general problem. Rome School on Alg
Best-path planning for public transportation systems
Chao-Lin Liu
2002-01-01
The author examines methods for a special class of path planning problems in which the routes are constrained. General search algorithms assume that we can move around in the traffic network freely, so they extend the partial paths from the very last location to each of its neighbors to form more partial paths. The best partial paths are then selected
Research on Improved Multidimensional Scaling Localization Algorithm for Wireless Sensor Network
Liang Tao; Xu Shuai; Chen Haiyong; Xun Hexu
2010-01-01
Wireless sensor networks, which are energy limited, low hardware configuration and proneness to invalidation, puts a high demand on the positioning algorithm. Therefore the improved multidimensional scaling (IMDS) algorithm is proposed. In IMDS, firstly, local positioning areas (LPA) are established by an adaptive search algorithm. So the centralized multidimensional scaling algorithm is changed into a distributed algorithm. Then the shortest
UAV Intelligent Path Planning for Wilderness Search and Rescue Computer Science Department
Goodrich, Michael A.
UAV Intelligent Path Planning for Wilderness Search and Rescue Lanny Lin Computer Science in order to find the missing person in the shortest expected time. When using a UAV to support search of the limited UAV flying time. I. INTRODUCTION The use of mini-UAVs (Unmanned Aerial Vehicles) in Wilderness
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
Realtime motion path generation using subtargets in a changing environment
Dennis Bruijnen; Jeroen van Helvoort; R. van de Molengraft
2006-01-01
In this work an algorithm is proposed for path planning in a changing environment. The algorithm is computationally cheap and generates a sub-optimal smooth path with bounds on the allowed velocity, acceleration and jerk. It outperforms potential field algorithms regarding both convergence and optimality. Furthermore, it is able to adapt fast in a changing environment in contrast with computationally more
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. [Department of Computer Science, University of New Mexico, Albuquerque, New Mexico 87131 (United States); Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, Indiana 46556 (United States); Swedish Cancer Institute, Seattle, Washington 98104 (United States); Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, Indiana 46556 (United States); Swedish Cancer Institute, Seattle, Washington 98104 (United States); Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, Maryland 21201 (United States)
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.
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.
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.
Solving shortest and closest vector problems: The decomposition approach
as a modified sieving algorithm for which the vectors of the intermediate sets lie in overlattices or translated of an overlattice. The complexity analysis relies on the Gaussian heuristic. This heuristic is backed by experiments the exact solution are at least exponential in the dimension of the lattice. These algorithms also serve
Fairness in optimal routing algorithms
Goos, Jeffrey Alan
1988-01-01
. Tsei Dr. Pierce E. Cantrell A study of fairness in multiple path optimal routing algorithms is discussed. Fair- ness measures are developed to evaluate multiple path routing in virtual circuit and datagram implementations. Several objective...
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 and as an educational tool...
Multiresolution Path Planning Via Sector Decompositions
Tsiotras, Panagiotis
Multiresolution Path Planning Via Sector Decompositions Compatible to On-Board Sensor Data that includes actual path length along with a risk-induced metric. We use a multi-resolution cell decomposition or popup threats. Several multi-resolution or hierarchical algorithms have been proposed in the literature
Greedy algorithms in disordered systems
NASA Astrophysics Data System (ADS)
Duxbury, P. M.; Dobrin, R.
1999-08-01
We discuss search, minimal path and minimal spanning tree algorithms and their applications to disordered systems. Greedy algorithms solve these problems exactly, and are related to extremal dynamics in physics. Minimal cost path (Dijkstra) and minimal cost spanning tree (Prim) algorithms provide extremal dynamics for a polymer in a random medium (the KPZ universality class) and invasion percolation (without trapping) respectively.
Jue, Jason P.
Abstract-- Path protection requires finding a working path and a protection path that are link disjoint. In this paper, we consider the dynamic lightpath protection problem in WDM mesh networks under-disjoint lightpaths on a single wavelength; however, such algorithms fail if the working and protection lightpaths
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
Parallelism and Greedy Algorithms
Richard Anderson; Ernst Mayr
Abstract A number,of greedy algorithms,are examined,
Method for Rapid Recovery Path Computation on Mesh IP Network
T. Masayuki
2008-01-01
A collection of slides from the authorpsilas seminar presentation is given. These discuss centralized management architecture, path computation and restoration, recovery by descending order, greedy algorithm, heuristic algorithm, computation time, network for simulation, test for optimality.
Performance Evaluation of Two New Disk Scheduling algorithms for Real-Time Systems
Shenze Chen; John A. Stankovic; James F. Kurose; Donald F. Towsley
1991-01-01
In this paper, we present two new disk scheduling algorithms for real-time systems. The twoalgorithms, called SSEDO(for Shortest Seek and Earliest Deadline by Ordering) and SSEDV(forShortest Seek and Earliest Deadline by Value), combine deadline information and disk servicetime information in different ways. The basic idea behind these new algorithms is to give thedisk I\\/O request with the earliest deadline a
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.
Bellaïche, Yohanns; Bosveld, Floris; Graner, François; Mikula, Karol; Remesíková, Mariana; Smísek, Michal
2011-01-01
In this paper, we present a novel algorithm for tracking cells in time lapse confocal microscopy movie of a Drosophila epithelial tissue during pupal morphogenesis. We consider a 2D + time video as a 3D static image, where frames are stacked atop each other, and using a spatio-temporal segmentation algorithm we obtain information about spatio-temporal 3D tubes representing evolutions of cells. The main idea for tracking is the usage of two distance functions--first one from the cells in the initial frame and second one from segmented boundaries. We track the cells backwards in time. The first distance function attracts the subsequently constructed cell trajectories to the cells in the initial frame and the second one forces them to be close to centerlines of the segmented tubular structures. This makes our tracking algorithm robust against noise and missing spatio-temporal boundaries. This approach can be generalized to a 3D + time video analysis, where spatio-temporal tubes are 4D objects. PMID:22255854
Integrated path planning and dynamic steering control for autonomous vehicles
B. Krogh; C. Thorpe
1986-01-01
A method is presented for combining two previously proposed algorithms for path-planning and dynamic steering control into a computationally feasible scheme for real-time feedback control of autonomous vehicles in uncertain environments. In the proposed approach to vehicle guidance and control, Path Relaxation is used to compute critical points along a globally desirable path using a priori information and sensor data.
Integrated Path Planning and ynamic Steering Control for Autonomous Vehicles
Bruce P. I. Krogh; Charles E. Thorpe
1986-01-01
A method is presented for combining two previously proposed algorithms for path-planning and dynamic steering control into a computationally feasible scheme for real-time feedback control of autonomous vehicles in uncertain environments. In the proposed approach to vehicle guidance and control, Path Relaxation is used to compute critical points along a globally desirable path using a priori information and sensor data'.
Path planning in the Proteus rapid prototyping system
Konstantinos A. Tarabanis
2001-01-01
Presents algorithms for determining the paths employed by the Proteus rapid prototyping system when building three-dimensional parts. Proteus is a fused deposition modeling system that extrudes a thermoplastic in beads through a nozzle. Determines within each layer of the layered manufacturing process, the material deposition paths as well as the regions where local structures are required to support these paths.
A Light Formulation of the E Interpolated Path Replanner
Roland Philippsen
The E algorithm is a path planning method capable of dynamic replanning and user- configurable path cost interpolation, it results in more appropriate paths during gradient de- scent. The underlying formulation is based on interpreting navigation functions as a sampled continuous crossing-time map that takes into account a risk measure. Replanning means that changes in the environment model can be
Efficient Path Delay Test Generation with Boolean Satisfiability
Bian, Kun
2013-12-10
delay test generator CodGen. A mixed structural-functional approach was implemented in CodGen where longest paths were detected using the K Longest Path Per Gate (KLPG) algorithm and path justification and dynamic compaction were handled with the SAT...
The impact of signal transition time on path delay computation
Ayman I. Kayssi; Karem A. Sakallah; Trevor N. Mudge
1993-01-01
It has been recognized for some time that nonzero signal rise and fall times contribute to gate propagation delays. Practically, however, most timing analysis tools ignore these contributions when computing path delays and identifying critical paths in combinational circuits. A description is given of how these rise and fall times can be incorporated into path analysis algorithms. It is shown
NSDL National Science Digital Library
For the next two exercises, we will break up into groups of four. Each member of the group will represent one of four waves leaving the source: direct wave, ground roll, reflected wave, and head wave. All four "waves" will leave the source at the same time and travel at a particular speed and path as directed by the instructor. ALL students will record the arrival time of each "wave" at each geophone until all 12 geophones have been used. Plot arrival time versus distance for each "wave". Do any of the time versus distance curves fit a straight line? Do any of them not fit a straight line? Explain why they do or don't fit a straight line. Uses online and/or real-time data Has minimal/no quantitative component
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.
Performance Evaluation of Approximation Algorithms for Multipoint Relay Selection
Mans, Bernard
,nirisha}@ics.mq.edu.au Abstract-- In Mobile Ad Hoc Networks (MANET), the selection of Multipoint Relays provides an efficient routing scheme for efficient broadcast and shortest-path unicast. As such a selection is NP of collision by exploiting the topological properties of the network (without assuming a knowledge
Multiresolution Hierarchical Path-Planning for Small UAVs Panagiotis Tsiotras
Tsiotras, Panagiotis
Multiresolution Hierarchical Path-Planning for Small UAVs Panagiotis Tsiotras School of Aerospace-- In this paper we review some recent results on a new multiresolution hierarchical path planning algorithm-term strategy (planning towards the ultimate goal). Several multi-resolution or hierarchical algorithms have
SUBMITTED TO IEEE TRANSACTIONS ON INFORMATION THEORY 100 Path Partitions and ForwardOnly Trellis
Kavcic, Aleksandar
based algo rithms. We argue that most decoding/detection algorithms de scribed on trellises can be formulated as pathpartitioning algo rithms, with proper definitions of mappings from subsets of paths algorithm, forwardbackward algorithm, forwardonly algorithm, Markov processes, sumproduct algo rithm
Phase Diagram of Optimal Paths
Alex Hansen; Janos Kertesz
2004-02-17
We show that choosing appropriate distributions of the randomness, the search for optimal paths links diverse problems of disordered media like directed percolation, invasion percolation, directed and non-directed spanning polymers. We also introduce a simple and efficient algorithm, which solves the d-dimensional model numerically in order N^(1+d_f/d) steps where d_f is the fractal dimension of the path. Using extensive simulations in two dimensions we identify the phase boundaries of the directed polymer universality class. A new strong-disorder phase occurs where the optimum paths are self-affine with parameter-dependent scaling exponents. Furthermore, the phase diagram contains directed and non-directed percolation as well as the directed random walk models at specific points and lines.
AN EFFICIENT ALGORITHM FOR MINIMIZING A SUM OF EUCLIDEAN NORMS WITH APPLICATIONS
Xue, Guoliang
AN EFFICIENT ALGORITHM FOR MINIMIZING A SUM OF EUCLIDEAN NORMS WITH APPLICATIONS GUOLIANG XUE-time algorithms are derived for the Euclidean single facility location problem, the Euclidean multifacility, interior-point algorithm, minimizing a sum of Euclidean norms, Euclidean facilities location, shortest
An optimal algorithm for scheduling soft-aperiodic tasks in fixed-priority preemptive systems
John P. Lehoczkyt; S. Ramos-thuel
1992-01-01
A novel algorithm for servicing soft deadline aperiodic tasks in a real-time system in which hard deadline periodic tasks are scheduled using a fixed priority algorithm is presented. This algorithm is proved to be optimal in the sense that it provides the shortest aperiodic response time among all possible aperiodic service methods. Simulation studies show that it offers substantial performance
Cooperative organic mine avoidance path planning
NASA Astrophysics Data System (ADS)
McCubbin, Christopher B.; Piatko, Christine D.; Peterson, Adam V.; Donnald, Creighton R.; Cohen, David
2005-06-01
The JHU/APL Path Planning team has developed path planning techniques to look for paths that balance the utility and risk associated with different routes through a minefield. Extending on previous years' efforts, we investigated real-world Naval mine avoidance requirements and developed a tactical decision aid (TDA) that satisfies those requirements. APL has developed new mine path planning techniques using graph based and genetic algorithms which quickly produce near-minimum risk paths for complicated fitness functions incorporating risk, path length, ship kinematics, and naval doctrine. The TDA user interface, a Java Swing application that obtains data via Corba interfaces to path planning databases, allows the operator to explore a fusion of historic and in situ mine field data, control the path planner, and display the planning results. To provide a context for the minefield data, the user interface also renders data from the Digital Nautical Chart database, a database created by the National Geospatial-Intelligence Agency containing charts of the world's ports and coastal regions. This TDA has been developed in conjunction with the COMID (Cooperative Organic Mine Defense) system. This paper presents a description of the algorithms, architecture, and application produced.
Internet's critical path horizon
NASA Astrophysics Data System (ADS)
Valverde, S.; Solé, R. V.
2004-03-01
Internet is known to display a highly heterogeneous structure and complex fluctuations in its traffic dynamics. Congestion seems to be an inevitable result of user's behavior coupled to the network dynamics and it effects should be minimized by choosing appropriate routing strategies. But what are the requirements of routing depth in order to optimize the traffic flow? In this paper we analyse the behavior of Internet traffic with a topologically realistic spatial structure as described in a previous study [S.-H. Yook et al., Proc. Natl Acad. Sci. USA 99, 13382 (2002)]. The model involves self-regulation of packet generation and different levels of routing depth. It is shown that it reproduces the relevant key, statistical features of Internet's traffic. Moreover, we also report the existence of a critical path horizon defining a transition from low-efficient traffic to highly efficient flow. This transition is actually a direct consequence of the web's small world architecture exploited by the routing algorithm. Once routing tables reach the network diameter, the traffic experiences a sudden transition from a low-efficient to a highly-efficient behavior. It is conjectured that routing policies might have spontaneously reached such a compromise in a distributed manner. Internet would thus be operating close to such critical path horizon.
Multipath planning algorithm based on fitness sharing and species evolution
Jing-Juan Zhang; Xue-Lian Li; Yan-Ling Hao
2003-01-01
A new algorithm is proposed for underwater vehicles multi-path planning. This algorithm is based on fitness sharing genetic\\u000a algorithm, clustering and evolution of multiple populations, which can keep the diversity of the solution path, and decrease\\u000a the operating time because of the independent evolution of each subpopulation. The multi-path planning algorithm is demonstrated\\u000a by a number of two-dimensional path planning
BootGraph: probabilistic fiber tractography using bootstrap algorithms and graph theory.
Vorburger, Robert S; Reischauer, Carolin; Boesiger, Peter
2013-02-01
Bootstrap methods have recently been introduced to diffusion-weighted magnetic resonance imaging to estimate the measurement uncertainty of ensuing diffusion parameters directly from the acquired data without the necessity to assume a noise model. These methods have been previously combined with deterministic streamline tractography algorithms to allow for the assessment of connection probabilities in the human brain. Thereby, the local noise induced disturbance in the diffusion data is accumulated additively due to the incremental progression of streamline tractography algorithms. Graph based approaches have been proposed to overcome this drawback of streamline techniques. For this reason, the bootstrap method is in the present work incorporated into a graph setup to derive a new probabilistic fiber tractography method, called BootGraph. The acquired data set is thereby converted into a weighted, undirected graph by defining a vertex in each voxel and edges between adjacent vertices. By means of the cone of uncertainty, which is derived using the wild bootstrap, a weight is thereafter assigned to each edge. Two path finding algorithms are subsequently applied to derive connection probabilities. While the first algorithm is based on the shortest path approach, the second algorithm takes all existing paths between two vertices into consideration. Tracking results are compared to an established algorithm based on the bootstrap method in combination with streamline fiber tractography and to another graph based algorithm. The BootGraph shows a very good performance in crossing situations with respect to false negatives and permits incorporating additional constraints, such as a curvature threshold. By inheriting the advantages of the bootstrap method and graph theory, the BootGraph method provides a computationally efficient and flexible probabilistic tractography setup to compute connection probability maps and virtual fiber pathways without the drawbacks of streamline tractography algorithms or the assumption of a noise distribution. Moreover, the BootGraph can be applied to common DTI data sets without further modifications and shows a high repeatability. Thus, it is very well suited for longitudinal studies and meta-studies based on DTI. PMID:23110883
Jzau-sheng Lin; Mingshou Liu; Nen-fu Huang
2000-01-01
Many network services, such as video conferencing and video on demand, have popularly used the multimedia communications. The attached hosts\\/routers are required to transmit data as multicasting in most multimedia applications. In order to provide an efficient data routing, routers must provide multicast capability. In this paper, a new cooling schedule in Hopfield neural network with annealing strategy is proposed
Path planning on satellite images for unmanned surface vehicles
NASA Astrophysics Data System (ADS)
Yang, Joe-Ming; Tseng, Chien-Ming; Tseng, P. S.
2015-01-01
In recent years, the development of autonomous surface vehicles has been a field of increasing research interest. There are two major areas in this field: control theory and path planning. This study focuses on path planning, and two objectives are discussed: path planning for Unmanned Surface Vehicles (USVs) and implementation of path planning in a real map. In this paper, satellite thermal images are converted into binary images which are used as the maps for the Finite Angle A* algorithm (FAA*), an advanced A* algorithm that is used to determine safer and suboptimal paths for USVs. To plan a collision-free path, the algorithm proposed in this article considers the dimensions of surface vehicles. Furthermore, the turning ability of a surface vehicle is also considered, and a constraint condition is introduced to improve the quality of the path planning algorithm, which makes the traveled path smoother. This study also shows a path planning experiment performed on a real satellite thermal image, and the path planning results can be used by an USV.
Li-Pei Wong; Malcolm Yoke Hean Low; Chin Soon Chong
2011-01-01
Identifying the shortest Hamiltonian circuit is a task which appears in various types of industrial and logistics applications. It is a NP-hard problem (1). This paper intends to find the shortest Hamiltonian circuit of the selected 68 towns\\/cities in Penang state, Malaysia using the generic Bee Colony Optimization (BCO) framework (2). The proposed BCO framework realizes computationally the foraging process
Shortest Division Chains in Imaginary Quadratic Number Fields
Heinrich Rolletschek
1988-01-01
Let O\\u000a\\u000ad\\u000a be the set of algebraic integers in an imaginary quadratic number field Q[d], dd is the discriminant of O\\u000a\\u000ad\\u000a. Consider the Euclidean Algorithm (EA), applied to algebraic integers , O\\u000a\\u000ad\\u000a. It consists in computing a sequence of remainders \\u000a0=, \\u000a1=, \\u000a2, ..., \\u000a\\u000an+1=0, where \\u000a\\u000ai+1=\\u000a\\u000ai–1–\\u000a\\u000ai\\u000a\\u000ai\\u000a for algebraic integers \\u000a\\u000ai\\u000a K,
Development of a potential field estimator for a path-planning application using neural networks
Smith, Darin William
1997-01-01
. . . . . . . . . . . b. Attractive and Repulsive Potentials B. Operational Space Approach . 1. Shortest Path Computation . a. Graph Theory b. Methodology for the SSRMS Problem . BACK-PROPAGATION ARTIFICIAL NEURAL NETWORK THEORY A. IvIotivation . 1. Fuzzy Logic 2... advantages and disadvantages with respe&t to the others. 1. Fuzzy Logic The particular problem being studied is known as a classilication problem. Harral has developed an aircraft situation recognizer using fuzzy logi&:l5). The situation rccognizer...
Robot navigation in unknown terrains: Introductory survey of non-heuristic algorithms
Rao, N.S.V. [Oak Ridge National Lab., TN (US); Kareti, S.; Shi, Weimin [Old Dominion Univ., Norfolk, VA (US). Dept. of Computer Science; Iyengar, S.S. [Louisiana State Univ., Baton Rouge, LA (US). Dept. of Computer Science
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.
An Energy Efficient Stable Election-Based Routing Algorithm for Wireless Sensor Networks
Wang, Jin; Zhang, Zhongqi; Xia, Feng; Yuan, Weiwei; Lee, Sungyoung
2013-01-01
Sensor nodes usually have limited energy supply and they are impractical to recharge. How to balance traffic load in sensors in order to increase network lifetime is a very challenging research issue. Many clustering algorithms have been proposed recently for wireless sensor networks (WSNs). However, sensor networks with one fixed sink node often suffer from a hot spots problem since nodes near sinks have more traffic burden to forward during a multi-hop transmission process. The use of mobile sinks has been shown to be an effective technique to enhance network performance features such as latency, energy efficiency, network lifetime, etc. In this paper, a modified Stable Election Protocol (SEP), which employs a mobile sink, has been proposed for WSNs with non-uniform node distribution. The decision of selecting cluster heads by the sink is based on the minimization of the associated additional energy and residual energy at each node. Besides, the cluster head selects the shortest path to reach the sink between the direct approach and the indirect approach with the use of the nearest cluster head. Simulation results demonstrate that our algorithm has better performance than traditional routing algorithms, such as LEACH and SEP. PMID:24284767
An energy efficient stable election-based routing algorithm for wireless sensor networks.
Wang, Jin; Zhang, Zhongqi; Xia, Feng; Yuan, Weiwei; Lee, Sungyoung
2013-01-01
Sensor nodes usually have limited energy supply and they are impractical to recharge. How to balance traffic load in sensors in order to increase network lifetime is a very challenging research issue. Many clustering algorithms have been proposed recently for wireless sensor networks (WSNs). However, sensor networks with one fixed sink node often suffer from a hot spots problem since nodes near sinks have more traffic burden to forward during a multi-hop transmission process. The use of mobile sinks has been shown to be an effective technique to enhance network performance features such as latency, energy efficiency, network lifetime, etc. In this paper, a modified Stable Election Protocol (SEP), which employs a mobile sink, has been proposed for WSNs with non-uniform node distribution. The decision of selecting cluster heads by the sink is based on the minimization of the associated additional energy and residual energy at each node. Besides, the cluster head selects the shortest path to reach the sink between the direct approach and the indirect approach with the use of the nearest cluster head. Simulation results demonstrate that our algorithm has better performance than traditional routing algorithms, such as LEACH and SEP. PMID:24284767
On the ideal of the shortest vectors in the Leech lattice and other lattices
Martin, Bill
On the ideal of the shortest vectors in the Leech lattice and other lattices William J. Martin, E7, E8, 24 (the Leech lattice) and determine for each: (i) the smallest degree of a non to cometric association schemes. 1 Introduction The Leech lattice 24 is well-studied in several mathematical
Zone-Based Shortest Positioning Time First Scheduling for MEMS-Based Storage Devices
Miller, Ethan L.
Zone-Based Shortest Positioning Time First Scheduling for MEMS-Based Storage Devices Bo Hong, Scott. MEMS-based storage devices use orthog- onal magnetic or physical recording techniques and thou- sands of simultaneously active MEMS-based read-write tips to provide high-density low-latency non-volatile storage
Finding a Shortest Diagonal of a Simple Polygon in Linear John Hershberger
Âknown, for instance, that a closest pair among n points in the plane can be found in O(n log n) time for finding a closest pair of vertices in a simple polygon---observe that a shortest diagonal is defined by a closest pair of vertices satisfying an additional visibility constraint. 1 #12; 1 Introduction Closest
NASA Astrophysics Data System (ADS)
Lee, Joohyun; Lee, Jaejin
2007-03-01
We present a noise-predictive maximum likelihood (NPML) detection scheme considering both low complexity and effective adaptation. First, for achieving low complexity, we exploit the modified Viterbi decoding method that partially selects the survival paths. The partial path selection method limits the number of selected paths among all survival paths at the Viterbi trellis and selects a path with minimum metric among the selected paths while the original Viterbi algorithm considers all paths and decides the best path. Next, for effective adaptation, we propose an adaptive NPML scheme exploiting a tentative decision value of the Viterbi decoding process.
A Guide to Heuristic-based Path Planning Dave Ferguson, Maxim Likhachev, and Anthony Stentz
Likhachev, Maxim
A Guide to Heuristic-based Path Planning Dave Ferguson, Maxim Likhachev, and Anthony Stentz School developed heuristic- based algorithms used for path planning in the real world. We discuss the fundamental*), and anytime re- planning algorithms (e.g. AD*). We introduce the mo- tivation behind each class of algorithms
Realtime motion path generation using subtargets in a rapidly changing environment
Dennis Bruijnen; Jeroen Van Helvoort; René Van De Molengraft
2007-01-01
In this work an algorithm is proposed for path planning in a changing environment. The algorithm is compu- tationally cheap and generates a sub-optimal smooth path with bounds on the allowed velocity, acceleration and jerk. It outper- forms potential field algorithms regarding both convergence and optimality. Furthermore, it is able to adapt fast in a changing environment in contrast with
Utilization of path length fuzing in the Peacekeeper Weapon System
NASA Astrophysics Data System (ADS)
Jackson, A. D.
This paper presents a discussion of the utilization and implementation of path length fuzing in the Peacekeeper Weapon System. Some background information which introduces the concept of path length fuzing and discusses its applicability to the Peacekeeper is first presented. Mathematical modeling of path length fuzing is discussed, and some novel algorithms and techniques developed by the author for implementation of path length fuzing in the Peacekeeper Operational Flight Program are presented. The scope of this paper is confined to the flight software and targeting aspects of path length fuzing; details of of the fuze hardware and electronics are not addressed.
Approximate path seeking for statistical iterative reconstruction
NASA Astrophysics Data System (ADS)
Wu, Meng; Yang, Qiao; Maier, Andreas; Fahrig, Rebecca
2015-03-01
Statistical iterative reconstruction (IR) techniques have demonstrated many advantages in X-ray CT reconstruction. The statistical iterative reconstruction approach is often modeled as an optimization problem including a data fitting function and a penalty function. The tuning parameter values that regulate the strength of the penalty function are critical for achieving good reconstruction results. However, appropriate tuning parameter values that are suitable for the scan protocols and imaging tasks are often difficult to choose. In this work, we propose a path seeking algorithm that is capable of generating a series of IR images with different strengths of the penalty function. The path seeking algorithm uses the ratio of the gradients of the data fitting function and the penalty function to select pixels for small fixed size updates. We describe the path seeking algorithm for penalized weighted least squares (PWLS) with a Huber penalty function in both the directions of increasing and decreasing tuning parameter value. Simulations using the XCAT phantom show the proposed method produces path images that are very similar to the IR images that are computed via direct optimization. The root-mean- squared-error of one path image generated by the proposed method relative to full iterative reconstruction is about 6 HU for the entire image and 10 HU for a small region. Different path seeking directions, increment sizes and updating percentages of the path seeking algorithm are compared in simulations. The proposed method may reduce the dependence on selection of good tuning parameter values by instead generating multiple IR images, without significantly increasing the computational load.
Jacob Benesty; Steven L. Gay
2002-01-01
Recently, the proportionate normalized least mean square (PNLMS) algorithm was developed for use in network echo cancelers. In comparison to the normalized least mean square (NLMS) algorithm, PNLMS has very fast initial convergence and tracking when the echo path is sparse. Unfortunately, when the impulse response is dispersive, the PNLMS converges much slower than NLMS. This implies that the rule
Fast path planning in virtual colonoscopy.
Lee, Jeongjin; Kim, Gyehyun; Lee, Ho; Shin, Byeong-Seok; Shin, Yeong Gil
2008-09-01
We propose a fast path planning algorithm using multi-resolution path tree propagation and farthest visible point. Initial path points are robustly generated by propagating the path tree, and all internal voxels locally most distant from the colon boundary are connected. The multi-resolution scheme is adopted to increase computational efficiency. Control points representing the navigational path are successively selected from the initial path points by using the farthest visible point. The position of the initial path point in a down-sampled volume is accurately adjusted in the original volume. Using the farthest visible point, the number of control points is adaptively changed according to the curvature of the colon shape so that more control points are assigned to highly curved regions. Furthermore, a smoothing step is unnecessary since our method generates a set of control points to be interpolated with the cubic spline interpolation. We applied our method to 10 computed tomography datasets. Experimental results showed that the path was generated much faster than using conventional methods without sacrificing accuracy, and clinical efficiency. The average processing time was approximately 1s when down-sampling by a factor of 2, 3, or 4. We concluded that our method is useful in diagnosing colon cancer using virtual colonoscopy. PMID:18707681
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.
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...
Traveling salesman path problems
Lam, Fumei
2005-01-01
In the Traveling Salesman Path Problem, we are given a set of cities, traveling costs between city pairs and fixed source and destination cities. The objective is to find a minimum cost path from the source to destination ...
Multiobjective Evolutionary Path Planning via Sugeno-Based Tournament Selection
NASA Technical Reports Server (NTRS)
Dozier, Gerry; McCullough, Shaun; Homaifar, Abdollah; Esterline, Albert
1998-01-01
This paper introduces a new tournament selection algorithm that can be used for evolutionary path planning systems. The fuzzy (Sugeno) tournament selection algorithm (STSA) described in this paper selects candidate paths (CPs) to be parents and undergo reproduction based on: (1) path feasibility, (2) the euclidean distance of a path from the origin to its destination, and (3) the average change in the slope of a path. In this paper, we provide a detailed description of the fuzzy inference system used in the STSA as well as some examples of its usefulness. We then use 12 instances of our STSA to rank a population of CPs based on the above criteria. We also show how the STSA can obviate the need for the development of an explicit (lexicographic multiobjective) evaluation function and use it to develop multiobjective motion paths.
Hard paths, soft paths or no paths? Cross-cultural perceptions of water solutions
Hall, Sharon J.
Hard paths, soft paths or no paths? Cross-cultural perceptions of water solutions Drew Blasco1 to the availability of clean, safe water. In this study we examined cross cultural preferences for soft path vs. hard conceptualize water solutions (hard paths, soft paths, no paths) cross-culturally? 2) What role does development
On the near-optimality of the shortest-latency-time-first drum scheduling discipline
Harold S. Stone; Samuel H. Fuller
1973-01-01
For computer systems in which it is practical to determine the instantaneous drum position, a popular discipline for determining the sequence in which the records are to be accessed is the so-called shortest-latency-time-first, SLTF, discipline. When a collection of varying-length records is to be accessed from specified drum positions, it is known that the SLTF discipline does not necessarily minimize
Twins: The Two Shortest Period Non-Interacting Double Degenerate White Dwarf Stars
F. Mullally; Carles Badenes; Susan E. Thompson; Robert Lupton
2009-01-01
We report on the detection of the two shortest period non-interacting white dwarf binary systems. These systems, SDSS J143633.29+501026.8 and SDSS J105353.89+520031.0, were identified by searching for radial velocity variations in the individual exposures that make up the published spectra from the Sloan Digital Sky Survey. We followed up these systems with time series spectroscopy to measure the period and
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 ...
Heuristic optimization of the scanning path of particle therapy beams.
Pardo, J; Donetti, M; Bourhaleb, F; Ansarinejad, A; Attili, A; Cirio, R; Garella, M A; Giordanengo, S; Givehchi, N; La Rosa, A; Marchetto, F; Monaco, V; Pecka, A; Peroni, C; Russo, G; Sacchi, R
2009-06-01
Quasidiscrete scanning is a delivery strategy for proton and ion beam therapy in which the beam is turned off when a slice is finished and a new energy must be set but not during the scanning between consecutive spots. Different scanning paths lead to different dose distributions due to the contribution of the unintended transit dose between spots. In this work an algorithm to optimize the scanning path for quasidiscrete scanned beams is presented. The classical simulated annealing algorithm is used. It is a heuristic algorithm frequently used in combinatorial optimization problems, which allows us to obtain nearly optimal solutions in acceptable running times. A study focused on the best choice of operational parameters on which the algorithm performance depends is presented. The convergence properties of the algorithm have been further improved by using the next-neighbor algorithm to generate the starting paths. Scanning paths for two clinical treatments have been optimized. The optimized paths are found to be shorter than the back-and-forth, top-to-bottom (zigzag) paths generally provided by the treatment planning systems. The gamma method has been applied to quantify the improvement achieved on the dose distribution. Results show a reduction of the transit dose when the optimized paths are used. The benefit is clear especially when the fluence per spot is low, as in the case of repainting. The minimization of the transit dose can potentially allow the use of higher beam intensities, thus decreasing the treatment time. The algorithm implemented for this work can optimize efficiently the scanning path of quasidiscrete scanned particle beams. Optimized scanning paths decrease the transit dose and lead to better dose distributions. PMID:19610293
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.
Heller, Barbara
Geographic Information Systems, Graphics, Robotics, Numerical methods, Bio-Informatics etc. Consider, common problems include ray-shooting to determine the first object in the line of sight, space Shortest paths with applications in Robotics BSP-trees and applications in graphics. Edited March 2006
Move3D: A generic platform for path planning
T. Simeon; J.-P. Laumond; F. Lamiraux
2001-01-01
Reports on Move3D, a software platform dedicated to collision-free path planning. The algorithms are based on probabilistic approaches and take advantage of the progress of computer performance. The generality comes from a dedicated software architecture allowing a rapid design of path planners. The paper focuses on results obtained in logistics for industrial installations, in graphics animation and in mobile robotics
Real-time Path Planning for Navigation in Unknown Environment
Tao Ruan Wan; H. Chen; Rae A. Earnshaw
2003-01-01
Real-time path planning is a challenging task that has many applications in the fields of AI, moving robots, virtual reality, agent behavior simulation, and action games. The various approaches for path planning have different criteria that have to be met, resulting in a number of algorithms for solutions to specific problems. In this paper, we introduce our approach and recent
Ab initio reaction paths and direct dynamics calculations
Kim K. Baldridge; Mark S. Gordon; Rozeanne Steckler; Donald G. Truhlar
1989-01-01
A detailed study of methods for generating the minimum energy path of a chemical reaction using ab initio electronic structure calculations is presented; the convergence with respect to step size of the geometry and energy along this path is studied with several algorithms. The investigations are extended to the calculation of chemical reaction rate coefficients by interfacing the polyrate code
An Efficient Computation of Statistically Critical Sequential Paths Under Retiming
Mongkol Ekpanyapong; Xin Zhao; Sung Kyu Lim
2007-01-01
In this paper we present the Statistical Retiming- based Timing Analysis (SRTA) algorithm. The goal is to compute the timing slack distribution for the nodes in the timing graph and identify the statistically critical paths under retiming, which are the paths with a high probability of becoming timing- critical after retiming. SRTA enables the designers to perform circuit optimization on
Propagation Path Properties in Iterative Longest-Edge Refinement
J. P. Su are; Angel Plaza; G. F. Care
2003-01-01
In this work we investigate the renemen t propagation process in longest-edge based local renemen t algorithms for unstructured meshes of triangles. The conformity neighborhood of a triangle, the set of additional triangles that is needed to be rened to ensure mesh conformity is introduced to dene the propagation path. We prove that asymptotically the propagation path extends on average
Implementation of the bisection sampling method in path integral simulations
Minnesota, University of
*, Jiali Gao Department of Chemistry, University of Minnesota, Minneapolis, MN 55455, USA Available online of a quantized classical path algorithm to include nuclear quantum effects in path integral simulations and in classical configuration sampling. The results will be useful for future studies of kinetic isotope effects
Ciardo, Gianfranco
Ciardo Department of Computer Science College of William and Mary Williamsburg, VA 23187-8795, USA {gli, ciardo}@cs.wm.edu Abstract In distributed or multi-processor systems, the join the shortest queue (JSQ
Short and Robust Communication Paths in Dynamic Wireless Networks
Yoann Pigné; Frédéric Guinand
2010-01-01
\\u000a We consider the problem of finding and maintaining communication paths in wireless mobile ad hoc networks (MANET). We consider\\u000a this problem as a bi-objective problem when trying to minimize both the length of the constructed paths and the number link\\u000a reconnections. We propose two centralized algorithms that help analyse the problem from a dynamic graph point of view. These\\u000a algorithms
A new MLC segmentation algorithm/software for step-and-shoot IMRT delivery.
Luan, Shuang; Wang, Chao; Chen, Danny Z; Hu, Xiaobo S; Naqvi, Shahid A; Yu, Cedric X; Lee, Chad L
2004-04-01
We present a new MLC segmentation algorithm/software for step-and-shoot IMRT delivery. Our aim in this work is to shorten the treatment time by minimizing the number of segments. Our new segmentation algorithm, called SLS (an abbreviation for static leaf sequencing), is based on graph algorithmic techniques in computer science. It takes advantage of the geometry of intensity maps. In our SLS approach, intensity maps are viewed as three-dimensional (3-D) "mountains" made of unit-sized "cubes." Such a 3-D "mountain" is first partitioned into special-structured submountains using a new mixed partitioning scheme. Then the optimal leaf sequences for each submountain are computed by either a shortest-path algorithm or a maximum-flow algorithm based on graph models. The computations of SLS take only a few minutes. Our comparison studies of SLS with CORVUS (both the 4.0 and 5.0 versions) and with the Xia and Verhey segmentation methods on Elekta Linac systems showed substantial improvements. For instance, for a pancreatic case, SLS used only one-fifth of the number of segments required by CORVUS 4.0 to create the same intensity maps, and the SLS sequences took only 25 min to deliver on an Elekta SL 20 Linac system in contrast to the 72 min for the CORVUS 4.0 sequences (a three-fold improvement). To verify the accuracy of our new leaf sequences, we conducted film and ion-chamber measurements on phantom. The results showed that both the intensity distributions as well as dose distributions of the SLS delivery match well with those of CORVUS delivery. SLS can also be extended to other types of Linac systems. PMID:15124986
Zhu, Daqi; Huang, Huan; Yang, Simon X
2012-08-27
For a 3-D underwater workspace with a variable ocean current, an integrated multiple autonomous underwater vehicle (AUV) dynamic task assignment and path planning algorithm is proposed by combing the improved self-organizing map (SOM) neural network and a novel velocity synthesis approach. The goal is to control a team of AUVs to reach all appointed target locations for only one time on the premise of workload balance and energy sufficiency while guaranteeing the least total and individual consumption in the presence of the variable ocean current. First, the SOM neuron network is developed to assign a team of AUVs to achieve multiple target locations in 3-D ocean environment. The working process involves special definition of the initial neural weights of the SOM network, the rule to select the winner, the computation of the neighborhood function, and the method to update weights. Then, the velocity synthesis approach is applied to plan the shortest path for each AUV to visit the corresponding target in a dynamic environment subject to the ocean current being variable and targets being movable. Lastly, to demonstrate the effectiveness of the proposed approach, simulation results are given in this paper. PMID:22949070
Locating algorithm being needless to harbor based on the quality in wireless sensor networks
NASA Astrophysics Data System (ADS)
Sharifi, Mirali; Tousi, Fatemeh; Kazimov, Tofiq
2011-12-01
From locating techniques in the wireless sensors networks two groups based on harbor and without it can be referred to. Firstly, the harbor nodes distribute the local information in the network and through that the average distance between two groups or the average length of a step is identified. Non-harbor nodes know the shortest path as the number of steps to each of the harbors and determine their distance to the harbors by understanding this average step length and using this estimation compute their location distance. Firstly, the network nodes are clustered. Each harbor is a cluster head and the cluster members using information derived from this cluster head begin locating. This process starts by the nodes located in the common field between two clusters. Although algorithm comparability based on harbor is increased by the nodes clustering, but the algorithm precise and efficiency is still dependent on the number of harbor nodes. Using harbor in all of the conditions causes its usage limitation in the wireless sensor networks. Regarding the algorithms without needing to harbor, algorithm is the first case. This algorithm has invented a new method to make a local graph in the network which is applicable in computing the relative features of nodes. Firstly, each node makes a graph with its own axis. Then the general graph of network is made and each node changes its coordinates by using an algorithm. Because of the current limitations in the trigonometry method used in this algorithm, the computed coordinates are not reliable and face difficulties in many cases. The other algorithms being needless to harbor try to use another methods instead of trigonometry methods in locating. For instance, among these methods, those ones based on graph drawing or mass and coil algorithms can be referred to. These kinds of algorithms take much time and use a lot of energy. In order to upgrade the algorithm results quality and prevent the fault distribution, we define a secondary parameter called the computed location accuracy. This parameter indicates location accuracy and can be a value between zero and one.
A new infeasible interior-point algorithm for linear programming
Miguel Argáez; Leticia Velázquez
2003-01-01
In this paper we present an infeasible path-following interior-point algorithm for solving linear programs using a relaxed notion of the central path, called quasicentral path, as a central region. The algorithm starts from an infeasible point which satisfies that the norm of the dual condition is less than the norm of the primal condition. We use weighted sets as proximity
A Rounding Algorithm for Approximating Minimum Manhattan Networks
Victor Chepoi; Karim Nouioua; Yann Vaxès
2005-01-01
For a set T of n points (terminals) in the plane, a Manhattan network on T is a network N(T) = (V;E) with the property that its edges are horizontal or vertical segments connecting points in VT and for every pair of terminals, the network N(T) contains a shortest l1-path between them. A minimum Manhattan network on T is a
Multi-objective stochastic path planning
Dasgupta, Sumantra
2009-05-15
[6, 7]. Genetic Algorithms have been applied to generate the non-dominated Pareto optimal set in multi- criteria path planning [8]. Potential and value-function approaches have been reported for multi-criteria path planning in [9, 10]. C... per grid, source node, s and destination node, d. The first parameter is the average height (normalized) of the grid and the second parameter is the type of vegetation in the terrain. To be navigable, the average normalized height is set to 3...
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.
Path factorization approach to stochastic simulations.
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. PMID:25526107
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
Twins: The Two Shortest Period Non-Interacting Double Degenerate White Dwarf Stars
F. Mullally; Carles Badenes; Susan E. Thompson; Robert Lupton
2009-01-01
We report on the detection of the two shortest period non-interacting white\\u000adwarf binary systems. These systems, SDSS J143633.29+501026.8 and SDSS\\u000aJ105353.89+520031.0, were identified by searching for radial velocity\\u000avariations in the individual exposures that make up the published spectra from\\u000athe Sloan Digital Sky Survey. We followed up these systems with time series\\u000aspectroscopy to measure the period and
Three-dimensional minimum-cost path planning using cellular automata architectures
NASA Astrophysics Data System (ADS)
Tzionas, Panagiotis G.; Tsalides, Phillippos G.; Thanailakis, Adonios
1993-05-01
A new algorithm for the estimation of the minimum cost path between a pair of points in the 3-D space and it''s proposed VLSI implementation using a 3-D Cellular Automata (CA) architecture, are being presented in this paper. The proposed algorithm guarantees to find the minimum cost path in 3-D space, if such a path exists. The proposed algorithm is especially suitable for real-time 3-D applications, such as 3-D automated navigation, target tracking in 3- D, 3-D path planning, etc.
Real-Time Edge Follow: A New Paradigm to Real-Time Path Search
Cagatay Undeger; Faruk Polat; Ziya Ipekkan
2001-01-01
Path searching and mission planning are challenging problems in many domains such as war games, robotics, military mission planning, computer-generated forces, etc. The objective of this study is to develop a real-time path- planning algorithm to accomplish specified missions on large landscapes. For that purpose, a real-time goal- directed path search algorithm, Real-Time Edge Follow (RTEF), which can work on
Quickest Paths for Different Network Router Mechanisms
Rao, N.S.V.; Grimmell, W.C.; Radhakrishnan, S.; Bang, Y.C.
2000-06-01
The quickest path problem deals with the transmission of a message of size {sigma} from a source to a destination with the minimum end-to-end delay over a network with bandwidth and delay constraints on the links. The authors consider four basic modes and two variations for the message delivery at the nodes reflecting the mechanisms such as circuit switching, Internet protocol, and their combinations. For each of the first three modes, they present O(m{sup 2} + mn log n) time algorithm to compute the quickest path for a given message size {sigma}. For the last mode, the quickest path can be computed in O(m + n log n) time.
Algorithms and Algorithmic Languages.
ERIC Educational Resources Information Center
Veselov, V. M.; Koprov, V. M.
This paper is intended as an introduction to a number of problems connected with the description of algorithms and algorithmic languages, particularly the syntaxes and semantics of algorithmic languages. The terms "letter, word, alphabet" are defined and described. The concept of the algorithm is defined and the relation between the algorithm and…
Yuan-shin Lee
1998-01-01
Presented in this paper is a new approach to 5-axis NC tool path generation for sculptured surface machining. Techniques of feasible machining strip evaluation are used for non-isoparametric 5-axis tool path generation. A searching algorithm is proposed to find the parameter increments of adjacent cutter locations along orthogonal path intervals for optimal non-isoparametric path generation. Compared to the use of
Real-time generation and control of cutter path for 5-axis CNC machining
Chih-Ching Lo
1999-01-01
This paper presents a new approach to real-time generation and control of the cutter path for 5-axis machining applications. The cutter path generation method comprises real-time algorithms for cutter-contact path interpolation, cutter offsetting, and coordinate conversion. In addition, a global feedback loop is closed by the CNC interpolator so as to augment the controlled accuracy in practical cutter path generation.
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.
Predicting Tor path compromise by exit port
Kevin S. Bauer; Dirk Grunwald; Douglas C. Sicker
2009-01-01
Abstract—Tor is currently the most,popular low,latency anonymizing overlay network for TCP-based applications. How- ever, it is well understood that Tor’s path selection algorithm is vulnerable to end-to-end traffic correlation attacks since it chooses Tor routers in proportion to their perceived bandwidth capabilities. Prior work has shown that the fraction of malicious routers and the amount,of adversary-controlled bandwidth are significant factors
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.
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.
NASA Astrophysics Data System (ADS)
Li, Qingquan; Zeng, Zhe; Zhang, Tong; Li, Jonathan; Wu, Zhongheng
2011-02-01
Optimal paths computed by conventional path-planning algorithms are usually not "optimal" since realistic traffic information and local road network characteristics are not considered. We present a new experiential approach that computes optimal paths based on the experience of taxi drivers by mining a huge number of floating car trajectories. The approach consists of three steps. First, routes are recovered from original taxi trajectories. Second, an experiential road hierarchy is constructed using travel frequency and speed information for road segments. Third, experiential optimal paths are planned based on the experiential road hierarchy. Compared with conventional path-planning methods, the proposed method provides better experiential optimal path identification. Experiments demonstrate that the travel time is less for these experiential paths than for paths planned by conventional methods. Results obtained for a case study in the city of Wuhan, China, demonstrate that experiential optimal paths can be flexibly obtained in different time intervals, particularly during peak hours.
Twins: The Two Shortest Period Non-Interacting Double Degenerate White Dwarf Stars
NASA Astrophysics Data System (ADS)
Mullally, F.; Badenes, Carles; Thompson, Susan E.; Lupton, Robert
2009-12-01
We report on the detection of the two shortest period non-interacting white dwarf binary systems. These systems, SDSS J143633.29+501026.8 and SDSS J105353.89+520031.0, were identified by searching for radial velocity variations in the individual exposures that make up the published spectra from the Sloan Digital Sky Survey. We followed up these systems with time series spectroscopy to measure the period and mass ratios of these systems. Although we only place a lower bound on the companion masses, we argue that they must also be white dwarf stars. With periods of approximately 1 hr, we estimate that the systems will merge in less than 100 Myr, but the merger product will likely not be massive enough to result in a Type 1a supernova.
Twins: The Two Shortest Period Non-Interacting Double Degenerate White Dwarf Stars
Mullally, F; Thompson, Susan E; Lupton, Robert
2009-01-01
We report on the detection of the two shortest period non-interacting white dwarf binary systems. These systems, SDSS J143633.29+501026.8 and SDSS J105353.89+520031.0, were identified by searching for radial velocity variations in the individual exposures that make up the published spectra from the Sloan Digital Sky Survey. We followed up these systems with time series spectroscopy to measure the period and mass ratios of these systems. Although we only place a lower bound on the companion masses, we argue that they must also be white dwarf stars. With periods of approximately 1 hour, we estimate that the systems will merge in less than 100 Myr, but the merger product will likely not be massive enough to result in a Type 1a supernova.
TWINS: THE TWO SHORTEST PERIOD NON-INTERACTING DOUBLE DEGENERATE WHITE DWARF STARS
Mullally, F.; Badenes, Carles; Lupton, Robert [Department of Astrophysical Sciences, Princeton University, Princeton, NJ 08544 (United States); Thompson, Susan E., E-mail: fergal@astro.princeton.ed [Department of Physics and Astronomy, University of Delaware, 217 Sharp Lab, Newark, DE 19716 (United States)
2009-12-10
We report on the detection of the two shortest period non-interacting white dwarf binary systems. These systems, SDSS J143633.29+501026.8 and SDSS J105353.89+520031.0, were identified by searching for radial velocity variations in the individual exposures that make up the published spectra from the Sloan Digital Sky Survey. We followed up these systems with time series spectroscopy to measure the period and mass ratios of these systems. Although we only place a lower bound on the companion masses, we argue that they must also be white dwarf stars. With periods of approximately 1 hr, we estimate that the systems will merge in less than 100 Myr, but the merger product will likely not be massive enough to result in a Type 1a supernova.
A Hybrid Genetic Algorithm for the Point to Multipoint Routing Problem with
Wainwright, Roger L.
A Hybrid Genetic Algorithm for the Point to Multipoint Routing Problem with Single Split Paths Words: Genetic Algorithm, Steiner Trees, Point to Multipoint Routing, Telecommunications Network to Multipoint Routing Problem with Single Split Paths. Our hybrid algorithm uses a genetic algorithm
From (2,3)-Motzkin Paths to Schröder Paths
NASA Astrophysics Data System (ADS)
Yan, Sherry H. F.
2007-08-01
In this paper, we provide a bijection between the set of restricted (2,3)-Motzkin paths of length n and the set of Schroder paths of semilength n. Furthermore, we give a one-to-one correspondence between the set of (2,3)-Motzkin paths of length n and the set of little Schroder paths of semilength n+1. By applying the bijections, we get the enumerations of Schroder paths according to the statistics "number of udd's" and "number of hd's".
Adaptive path planning in changing environments
Chen, Pang C.
1993-10-01
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 previous 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 extends our previous work for stationary environments in two directions: For minor environmental change, an object-attached experience abstraction scheme is introduced to increase the flexibility of the learned experience; for major environmental change, an on-demand experience repair scheme is also introduced to retain those experiences that remain valid and useful. In addition to presenting this algorithm, we identify three other variants with different repair strategies. To compare these algorithms, we develop an analytic model to compare the costs and benefits of the corresponding repair processes. Using this model, we formalize the concept of incremental change, and prove the optimality of our proposed algorithm under such change. Empirically, we also characterize the performance curve of each variant, confirm our theoretical optimality results, and demonstrate the practicality of our algorithm.
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.
Automatic generation of NC cutter path from massive data points
Alan C. Lin; Hai-terng Liu
1998-01-01
This paper proposes methodologies and algorithms through which a three-axis NC cutter path can be directly generated from massive data points obtained with contact or non-contact measuring devices. At the beginning, a Z-map model is employed to set up mesh points in order to economize on the use of computer memory. Rough-cut paths are produced by machining volumes of material
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 on the premium class traffic itself, but on all other classes of traffic as well. The shortest hop-count routing, such that (1) no for- warding loop exists in the entire network in the context of hop- by-hop routing; and (2
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 on the premium class traffic itself, but on all other classes of traffic as well. The shortest hop-count routing, such that (1) no forwarding loop exists in the entire network in the context of hop-by-hop routing; and (2
Brian Clow; Tony White
2004-01-01
This paper compares the performance of genetic algorithms (GA) and particle swarm optimization (PSO) when used to train artificial neural networks. The networks are used to control virtual racecars, with the aim of successfully navigating around a track in the shortest possible period of time. Each car is mounted with multiple straight-line distance sensors, which provide the input to the
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.}
Path Integrals and Exotic Options:. Methods and Numerical Results
NASA Astrophysics Data System (ADS)
Bormetti, G.; Montagna, G.; Moreni, N.; Nicrosini, O.
2005-09-01
In the framework of Black-Scholes-Merton model of financial derivatives, a path integral approach to option pricing is presented. A general formula to price path dependent options on multidimensional and correlated underlying assets is obtained and implemented by means of various flexible and efficient algorithms. As an example, we detail the case of Asian call options. The numerical results are compared with those obtained with other procedures used in quantitative finance and found to be in good agreement. In particular, when pricing at the money (ATM) and out of the money (OTM) options, path integral exhibits competitive performances.
Sullivan, Blair D [ORNL; Seymour, Dr. Paul Douglas [Princeton University
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.
The traffic equilibrium problem with nonadditive path costs
Gabriel, S.A. [Argonne National Lab., IL (United States). Mathematics and Computer Science Div.; Bernstein, D. [Princeton Univ., NJ (United States). Dept. of Civil Engineering and Operations Research
1995-08-21
In this paper the authors present a version of the (static) traffic equilibrium problem in which the cost incurred on a path is not simply the sum of the costs on the arcs that constitute that path. The authors motivate this nonadditive version of the problem by describing several situations in which the classical additivity assumption fails. They also present an algorithm for solving nonadditive problems that is based on the recent NE/SQP algorithm, a fast and robust method for the nonlinear complementarity problem. Finally, they present a small example that illustrates both the importance of using nonadditive costs and the effectiveness of the NE/SQP method.
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
NASA Astrophysics Data System (ADS)
Chen, Changjun; Huang, Yanzhao; Ji, Xiaofeng; Xiao, Yi
2013-04-01
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.
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
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…
Jeffrey Michael Hebert
2001-01-01
This dissertation explores optimal path planning for air vehicles. An air vehicle exposed to illumination by a tracking radar is considered and the problem of determining an optimal planar trajectory connecting two prespecified points is addressed. An analytic solution yielding the trajectory minimizing the received radar energy reflected from the target is derived using the Calculus of Variations. Additionally, the
Danil Sokolov; Ivan Poliakov; Alexandre Yakovlev
2007-01-01
A token-based model for asynchronous data path is formally defined and three token game semantics, spread token, antitoken and counterflow, are introduced. These semantics are studied and their advantages and drawbacks are highlighted. For analysis and comparison a software tool is developed which integrates these models into a consistent framework. The models are verified by mapping them into Petri nets
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
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.
A new, simpler linear-time dominators algorithm
Adam L. Buchsbaum; Haim Kaplan; Anne Rogers; Jeffery R. Westbrook
1998-01-01
We present a new linear-time algorithm to find the immediate dominators of all vertices in a flowgraph. Our algorithm is simpler than previous linear-time algorithms: rather than employ complicated data structures, we combine the use of microtrees and memoization with new observations on a restricted class of path compressions. We have implemented our algorithm, and we report experimental results that
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
Atmospheric Science Data Center
2014-12-08
... every 233 revolutions around the Earth, it is natural to name each of these different trajectories or paths. For MISR, the path is the generic name (actually the numeric label) of all orbits that observe the same areas ...
Path Following with Slip Compensation for a Mars Rover
NASA Technical Reports Server (NTRS)
Helmick, Daniel; Cheng, Yang; Clouse, Daniel; Matthies, Larry; Roumeliotis, Stergios
2005-01-01
A software system for autonomous operation of a Mars rover is composed of several key algorithms that enable the rover to accurately follow a designated path, compensate for slippage of its wheels on terrain, and reach intended goals. The techniques implemented by the algorithms are visual odometry, full vehicle kinematics, a Kalman filter, and path following with slip compensation. The visual-odometry algorithm tracks distinctive scene features in stereo imagery to estimate rover motion between successively acquired stereo image pairs, by use of a maximum-likelihood motion-estimation algorithm. The full-vehicle kinematics algorithm estimates motion, with a no-slip assumption, from measured wheel rates, steering angles, and angles of rockers and bogies in the rover suspension system. The Kalman filter merges data from an inertial measurement unit (IMU) and the visual-odometry algorithm. The merged estimate is then compared to the kinematic estimate to determine whether and how much slippage has occurred. The kinematic estimate is used to complement the Kalman-filter estimate if no statistically significant slippage has occurred. If slippage has occurred, then a slip vector is calculated by subtracting the current Kalman filter estimate from the kinematic estimate. This slip vector is then used, in conjunction with the inverse kinematics, to determine the wheel velocities and steering angles needed to compensate for slip and follow the desired path.
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.
Demonstration of scan path optimization in proton therapy.
Kang, Joanne H; Wilkens, Jan J; Oelfke, Uwe
2007-09-01
A three-dimensional (3D) intensity modulated proton therapy treatment plan to be delivered by magnetic scanning may comprise thousands of discrete beam positions. This research presents the minimization of the total scan path length by application of a fast simulated annealing (FSA) optimization algorithm. Treatment plans for clinical prostate and head and neck cases were sequenced for continuous raster scanning in two ways, and the resulting scan path lengths were compared: (1) A simple back-and-forth, top-to-bottom (zigzag) succession, and (2) an optimized path produced as a solution of the FSA algorithm. Using a first approximation of the scanning dynamics, the delivery times for the scan sequences before and after path optimization were calculated for comparison. In these clinical examples, the FSA optimization shortened the total scan path length for the 3D target volumes by approximately 13%-56%. The number of extraneous spilled particles was correspondingly reduced by about 13%-54% due to the more efficient scanning maps that eliminated multiple crossings through regions of zero fluence. The relative decrease in delivery time due to path length minimization was estimated to be less than 1%, due to both a high scanning speed and time requirements that could not be altered by optimization (e.g., time required to change the beam energy). In a preliminary consideration of application to rescanning techniques, the decrease in delivery time was estimated to be 4%-20%. PMID:17926947
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.
Bike path Schools Bike friendly
Crews, Stephen
Bike path Schools Parks Greenways Bike lane Bike friendly Bike path on sidewalk (uphill only a left turn, merge with motor vehicle traffic well in advance of the intersection. When bicycle paths stopping distance in inclement weather. Use a backpack or bike bag to carry items. Reasons to Bike
Autonomous ground vehicle path tracking
Jeff Wit; Carl D. Crane III; David G. Armstrong II
2004-01-01
Autonomous ground vehicle navigation requires the integration of many technologies such as path planning, position and orientation sensing, vehicle control, and obstacle avoidance. The work presented here focuses on the control of a nonholonomic ground vehicle as it tracks a given path. A new path tracking technique called ''vector pursuit'' is presented. This new technique is based on the theory
OBSTACLE-AVOIDING PATH PLANNING FOR HIGH VELOCITY WHEELED MOBILE ROBOTS
Jorge Villagra; Hugues Mounier
This paper presents a new motion planning algorithm for wheeled mobile robots in presence of known static obstacles, especially well-suited for high velocity situations. It takes into account several conditions traditionally attached to smooth path planning, i.e. paths with continuous derivative and upper-bounded curvature. It makes use of a global path planner which exploits polynomial G3 curves characteristics. Copyright c
5-axis Flank Milling Tool Path Smoothing Based on Kinematical Behaviour BEUDAERT Xavier1,a
Paris-Sud XI, Université de
to minimize undercut and overcut. The curvature characteristics of these tool paths generate slowdowns in the area of interest. Machining simulation based on a N-buffer algorithm is used to control undercut
Heuristic collision-free path planning for an autonomous platform
Nikolaos G. Bourbakis
1989-01-01
In this paper, a heuristic and learning, algorithmic scheme for collision-free navigation is presented. This scheme determines an optimum collision-free navigation path of an autonomous platform by using a ‘trial and error’ process, past navigation knowledge and current information extracted from the generated surrounding environment.
Multiple Aircraft Deconflicted Path Planning with Weather Avoidance Constraints
Sastry, S. Shankar
Multiple Aircraft Deconflicted Path Planning with Weather Avoidance Constraints Jessica J We present a model predictive control based algorithm for aircraft motion planning that will apply to converging flows of aircraft going through convective weather in the en route airspace. The cost function
Toward Online Probabilistic Path Replanning in Dynamic Environments
Roland Philippsen; Björn Jensen; Roland Siegwart
2006-01-01
This paper presents work on sensor-based motion planning in initially unknown dynamic environments. Motion detection and modeling are combined with a smooth navigation function to perform on-line path planning in cluttered dynamic environments. The SLIP algorithm, an extension of Iterative Closest Point, combines motion detection from a mobile platform with position estimation. This information is used via probabilis- tic prediction
Evaluating go-path measurements to determine faulty components \\
Larry V. Kirkland; Nathan Wilson; Floyd Berghout
2004-01-01
This paper describes the use of multiple go-path measurements, in combination with algorithmic test sequences, to aid in improving test efficiency and accuracy and diagnostics. As an electronic device or circuit is tested, the output of the unit under tests (UUT) may be considered as a function of the input. Through the use of multiple tests designed to exercise system
PATH COUPLED ACCOUNTING MECHANISMS FOR "ALL IP NETWORKS"
Breu, Ruth
PATH COUPLED ACCOUNTING MECHANISMS FOR "ALL IP NETWORKS" Andreas Klenk*, Philipp Schlicker*, Ralph: Accounting, All IP Networks, Meter Selection Algorithms, Distributed Load Balancing, NSIS Abstract Accounting of the services grows the demand for an equally flexible accounting mechanism increases as well. However nowadays
NC machine tool path generation from CSG part representations
James E Bobrow
1985-01-01
Recent improvements in geometric modelling systems hove led to the need for more reliable end highly automated soft- wore for machine tool path generation. Current machining algorithms require that any port geometric information which cannot be determined from the modelling system be supplied by the user. Much geometric information Is needed if the model used to represent the pert is
Visibility in Discrete Geometry: an application to discrete geodesic paths
Paris-Sud XI, Université de
in computational geometry. We present algorithms to compute the set of pixels in a non-convex domain. Introduction In discrete geometry, many Euclidean geometric tools are redefined to take into accountVisibility in Discrete Geometry: an application to discrete geodesic paths David Coeurjolly
Force-directed scheduling in automatic data path synthesis
Pierre G. Paulin; John P. Knight
1987-01-01
The HAL system performs data path synthesis using a new scheduling algorithm that is part of an interdependent scheduling and allocation scheme. This scheme uses an estimate of the hardware allocation to guide and optimize the scheduling subtask. The allocation information includes the number, type, speed and cost of hardware modules as well as the associated multiplexer and interconnect costs.The
C-Space Characterization of Contact Preserving Paths with Application to
Rimon, Elon
C-Space Characterization of Contact Preserving Paths with Application to Tactile-Sensor Based and tactile sensors in an unknown planar environment. The paper focuses on the contact preserving segments. A preliminary tactile-sensor navigation algorithm based on these paths is illustrated with examples. 1
The Design and Evaluation of Path Matching Schemes on Compressed Control Flow Traces
Zhang, Youtao
The Design and Evaluation of Path Matching Schemes on Compressed Control Flow Traces Yongjing Lin and therefore commonly stored in compressed format. On the other hand, control flow traces are frequently an intraprocedural path over control flow traces. While algorithms that perform pattern matching on compressed
Evolutionary path planning for autonomous underwater vehicles in a variable ocean
Alberto Alvarez; Andrea Caiti; Reiner Onken
2004-01-01
This paper proposes a genetic algorithm (GA) for path planning of an autonomous underwater vehicle in an ocean environment characterized by strong currents and enhanced space-time variability. The goal is to find a safe path that takes the vehicle from its starting location to a mission-specified destination, minimizing the energy cost. The GA includes novel genetic operators that ensure the
Optimal field coverage path planning on 2D and 3D surfaces
Jian Jin
2009-01-01
With the rapid adoption of automatic guidance systems, automated path planning has great potential to further optimize field operations. Field operations should be done in a manner that minimizes time, travel over field surfaces and is coordinated with specific field operations, machine characteristics and topographical features of arable lands. To reach this goal, intelligent coverage path planning algorithm is key.
Obstacle-avoidance Path Planning for Soccer Robots Using Particle Swarm Optimization
Li Wang; Yushu Liu; Hongbin Deng; Yuanqing Xu
2006-01-01
Optimal path planning for mobile robots plays an important role in the field of robotics. At present, there are many advanced algorithms used to solve this optimization problem. In this paper a dynamic obstacle-avoidance path planning approach for soccer robot based on particle swarm optimization is presented considering the shape of robot. The mathematical model has been build and a
Collision-Free and Curvature-Continuous Path Smoothing in Cluttered Environments
North Carolina at Chapel Hill, University of
on computation of smooth paths in mobile robotics, because nonsmooth motions can cause slippage and overactuation a fast and reliable algorithm for collision checking between robot and the environment along the B, 12] are frequently used to compute collision-free paths for physical robots and virtual agents
Context-and Path-sensitive Memory Leak Detection Yichen Xie Alex Aiken
Aiken, Alex
Context- and Path-sensitive Memory Leak Detection Yichen Xie Alex Aiken Computer Science Department-sensitive algorithm for de- tecting memory leaks in programs with explicit memory management. Our leak detection that is not deallocated in P and does not escape from P is leaked. We achieve very precise context- and path- sensitivity
All-Pairs Bottleneck Paths in Vertex Weighted Graphs Asaf Shapira
Yuster, Raphael
All-Pairs Bottleneck Paths in Vertex Weighted Graphs Asaf Shapira Raphael Yuster Uri Zwick on its vertices. The bottleneck weight, or the capacity, of a path is the smallest weight of a vertex edge or vertex weights, the algorithm presented for APBP problem works for arbitrary large vertex
Joint Path and Wavelength Selection Using Q-learning in Optical Burst Switching Networks
T. Venkatesh; Y. V. Kiran; C. Siva Ram Murthy
2009-01-01
Contention losses which usually do not indicate congestion is a major issue that hinders the deployment of optical burst switching (OBS) networks. Development of efficient path and wavelength selection algorithms is crucial to minimize the burst loss probability (BLP) in OBS networks. In this paper, we handle path selection and wavelength selection in a joint fashion. We formulate the problem
Identification of limit cycles in multi-nonlinearity, multiple path systems
NASA Technical Reports Server (NTRS)
Mitchell, J. R.; Barron, O. L.
1979-01-01
A method of analysis which identifies limit cycles in autonomous systems with multiple nonlinearities and multiple forward paths is presented. The FORTRAN code for implementing the Harmonic Balance Algorithm is reported. The FORTRAN code is used to identify limit cycles in multiple path and nonlinearity systems while retaining the effects of several harmonic components.
The Longest Path Problem Is Polynomial on Interval Graphs
NASA Astrophysics Data System (ADS)
Ioannidou, Kyriaki; Mertzios, George B.; Nikolopoulos, Stavros D.
The longest path problem is the problem of finding a path of maximum length in a graph. Polynomial solutions for this problem are known only for small classes of graphs, while it is NP-hard on general graphs, as it is a generalization of the Hamiltonian path problem. Motivated by the work of Uehara and Uno in [20], where they left the longest path problem open for the class of interval graphs, in this paper we show that the problem can be solved in polynomial time on interval graphs. The proposed algorithm runs in O(n 4) time, where n is the number of vertices of the input graph, and bases on a dynamic programming approach.
Sequential quadratic programming method for determining the minimum energy path
NASA Astrophysics Data System (ADS)
Burger, Steven K.; Yang, Weitao
2007-10-01
A new method, referred to as the sequential quadratic programming method, is presented for determining minimum energy paths. The method is based on minimizing the points representing the path in the subspace perpendicular to the tangent of the path while using a penalty term to prevent kinks from forming. Rather than taking one full step, the minimization is divided into a number of sequential steps on an approximate quadratic surface. The resulting method can efficiently determine the reaction mechanism, from which transition state can be easily identified and refined with other methods. To improve the resolution of the path close to the transition state, points are clustered close to this region with a reparametrization scheme. The usefulness of the algorithm is demonstrated for the Müller-Brown potential, amide hydrolysis, and an 89 atom cluster taken from the active site of 4-oxalocrotonate tautomerase for the reaction which catalyzes 2-oxo-4-hexenedioate to the intermediate 2-hydroxy-2,4-hexadienedioate.
arXiv:0709.0116v2[cs.AI]29Sep2007 On Ultrametric Algorithmic Information
Sheldon, Nathan D.
of descriptions" has come the minimum description length, or MDL, principle as a computable and practical, to compute it. The shortest effective description length has become known as Kolmogorov complexity, even complex objects. Our algorithmic com- plexity is related to the length of the class of objects, rather
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.
Dynamic Adaptive Windows for High Speed Data Networks with Multiple Paths and Propagation Delays
Debasis Mitra; Judith B. Seery
1991-01-01
The optimal design of windows for virtual circuits has been studied for high-speed, wide-area data networks in an asymptotic framework in which the delay-bandwidth product is the large parameter. The authors (1990) previously proposed and evaluated a new class of algorithms for dynamically adapting windows in single path, multi-hop networks. Here they develop algorithms for networks having multiple paths with
Minimum energy paths for reliable communication in multi-hop wireless networks
Suman Banerjee; Archan Misra
2002-01-01
Current algorithms for minimum-energy routing in wireless networks typically select minimum-cost multi-hop paths. In scenarios where the transmission power is fixed, each link has the same cost and the minimum-hop path is selected. In situations where the transmission power can be varied with the distance of the link, the link cost is higher for longer hops; the energy-aware routing algorithms
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
NLTT 5306: the shortest period detached white dwarf+brown dwarf binary
NASA Astrophysics Data System (ADS)
Steele, P. R.; Saglia, R. P.; Burleigh, M. R.; Marsh, T. R.; Gänsicke, B. T.; Lawrie, K.; Cappetta, M.; Girven, J.; Napiwotzki, R.
2013-03-01
We have spectroscopically confirmed a brown dwarf mass companion to the hydrogen atmosphere white dwarf NLTT 5306. The white dwarf's atmospheric parameters were measured using the Sloan Digital Sky Survey and X-shooter spectroscopy as Teff = 7756 ± 35 K and log(g) = 7.68 ± 0.08, giving a mass for the primary of MWD = 0.44 ± 0.04 M? at a distance of 71 ± 4 pc with a cooling age of 710 ± 50 Myr. The existence of the brown dwarf secondary was confirmed through the near-infrared arm of the X-shooter data and a spectral type of dL4-dL7 was estimated using standard spectral indices. Combined radial velocity measurements from the Sloan Digital Sky Survey, X-shooter and the Hobby-Eberly Telescope's High Resolution Spectrograph of the white dwarf give a minimum mass of 56 ± 3 MJup for the secondary, confirming the substellar nature. The period of the binary was measured as 101.88 ± 0.02 min using both the radial velocity data and i'-band variability detected with the Isaac Newton Telescope. This variability indicates `day' side heating of the brown dwarf companion. We also observe H? emission in our higher resolution data in phase with the white dwarf radial velocity, indicating that this system is in a low level of accretion, most likely via a stellar wind. This system represents the shortest period white dwarf+brown dwarf binary and the secondary has survived a stage of common envelope evolution, much like its longer period counterpart, WD 0137-349. Both systems likely represent bona fide progenitors of cataclysmic variables with a low-mass white dwarf and a brown dwarf donor.
Accretion disc mapping of the shortest period eclipsing binary SDSS J0926+36
NASA Astrophysics Data System (ADS)
Schlindwein, W.; Baptista, R.
2014-10-01
AM CVn stars are ultracompact binaries (P_{orb}< 65 min) where a hydrogen-deficient low-mass, degenerate donor star overfills its Roche lobe and transfers matter to a companion white dwarf via an accretion disc. SDSS J0926+36 is currently the only eclipsing AM CVn star and also the shortest period eclipsing binary known. Its light curve displays deep (˜ 2 mag) eclipses every 28.3 min, which last for ˜ 2 min, as well as ˜ 2 mag amplitude outbursts every ˜ 100-200 d. Superhumps were seen in its quiescent light curve in some occasions, probably as a reminiscence of a (in some cases undetected) previous outburst. Its eclipsing nature allows a unique opportunity to disentangle the emission from several different light sources, and to map the surface brightness distribution of its hydrogen-deficient accretion disc with the aid of maximum entropy eclipse mapping techniques. Here we report the eclipse mapping analysis of optical light curves of SDSS J0926+36, collected with the 2.4 m Liverpool Robotic Telescope, covering 20 orbits of the binary over 5 nights of observations between 2012 February and March. The object was in quiescence at all runs. Our data show no evidence of superhumps nor of orbital modulation due to anisotropic emission from a bright spot at disc rim. Accordingly, the average out-of-eclipse flux level is consistent with that of the superhump-subtracted previous light curves. We combined all runs to obtain an orbital light curve of improved S/N. The corresponding eclipse map shows a compact source at disc centre (T_{b}simeq 17000 K), a faint, cool accretion disc (˜ 4000 K) plus enhanced emission along the gas stream (˜ 6000 K) beyond the impact point at the outer disc rim, suggesting the occurrence of gas stream overflow at that epoch.
Storage-Efficient, Deadlock-Free Packet Routing Algorithms for Torus Networks
Robert Cypher; Luis Gravano
1994-01-01
We present two new packet routing algorithms for parallel computerswith torus interconnection networks of arbitrary size and dimension.Both algorithms use only minimal length paths, are fully adaptive inthe sense that all minimal length paths may be used to avoid congestion,and are free of deadlock, livelock and starvation. Algorithm 1 requiresonly three central queues per routing node. It is the first
Two arm robot path planning in a static environment using polytopes and string stretching. Thesis
NASA Technical Reports Server (NTRS)
Schima, Francis J., III
1990-01-01
The two arm robot path planning problem has been analyzed and reduced into components to be simplified. This thesis examines one component in which two Puma-560 robot arms are simultaneously holding a single object. The problem is to find a path between two points around obstacles which is relatively fast and minimizes the distance. The thesis involves creating a structure on which to form an advanced path planning algorithm which could ideally find the optimum path. An actual path planning method is implemented which is simple though effective in most common situations. Given the limits of computer technology, a 'good' path is currently found. Objects in the workspace are modeled with polytopes. These are used because they can be used for rapid collision detection and still provide a representation which is adequate for path planning.
Regularization Paths for Generalized Linear Models via Coordinate Descent
Friedman, Jerome; Hastie, Trevor; Tibshirani, Rob
2010-01-01
We develop fast algorithms for estimation of generalized linear models with convex penalties. The models include linear regression, two-class logistic regression, and multinomial regression problems while the penalties include ?1 (the lasso), ?2 (ridge regression) and mixtures of the two (the elastic net). The algorithms use cyclical coordinate descent, computed along a regularization path. The methods can handle large problems and can also deal efficiently with sparse features. In comparative timings we find that the new algorithms are considerably faster than competing methods. PMID:20808728
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.