An improved Physarum polycephalum algorithm for the shortest path problem.
Zhang, Xiaoge; Wang, Qing; Adamatzky, Andrew; Chan, Felix T S; Mahadevan, Sankaran; Deng, Yong
2014-01-01
Shortest path is among classical problems of computer science. The problems are solved by hundreds of algorithms, silicon computing architectures and novel substrate, unconventional, computing devices. Acellular slime mould P. polycephalum is originally famous as a computing biological substrate due to its alleged ability to approximate shortest path from its inoculation site to a source of nutrients. Several algorithms were designed based on properties of the slime mould. Many of the Physarum-inspired algorithms suffer from a low converge speed. To accelerate the search of a solution and reduce a number of iterations we combined an original model of Physarum-inspired path solver with a new a parameter, called energy. We undertook a series of computational experiments on approximating shortest paths in networks with different topologies, and number of nodes varying from 15 to 2000. We found that the improved Physarum algorithm matches well with existing Physarum-inspired approaches yet outperforms them in number of iterations executed and a total running time. We also compare our algorithm with other existing algorithms, including the ant colony optimization algorithm and Dijkstra algorithm. PMID:24982960
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
Modeling wildfire propagation with Delaunay triangulation and shortest path algorithms
Smith, J. MacGregor
Modeling wildfire propagation with Delaunay triangulation and shortest path algorithms Alexander In this paper, a methodology for modeling surface wildfire propagation through a complex landscape is presented, wildfire modeling 1 Introduction During the years 2000-2004, the National Interagency Fire Center (NIFC
An improved bio-inspired algorithm for the directed shortest path problem.
Zhang, Xiaoge; Zhang, Yajuan; Deng, Yong
2014-01-01
Because most networks are intrinsically directed, the directed shortest path problem has been one of the fundamental issues in network optimization. In this paper, a novel algorithm for finding the shortest path in directed networks is proposed. It extends a bio-inspired path finding model of Physarum polycephalum, which is designed only for undirected networks, by adopting analog circuit analysis. Illustrative examples are given to show the effectiveness of the proposed algorithm in finding the directed shortest path. PMID:25405318
Dynamic behavior of shortest path routing algorithms for communication networks
NASA Astrophysics Data System (ADS)
Bertsekas, D. P.
1980-06-01
Several proposed routing algorithms for store and forward communication networks, including one currently in operation in the ARPANET, route messages along shortest paths computed by using some set of link lengths. When these lengths depend on current traffic conditions as they must in an adaptive algorithm, dynamic behavior questions such as stability convergence, and speed of convergence are of interest. This paper is the first attempt to analyze systematically these issues. It is shown that minimum queuing delay path algorithms tend to exhibit violent oscillatory behavior in the absence of a damping mechanism. The oscillations can be damped by means of several types of schemes, two of which are analyzed in this paper. In the first scheme a constant bias is added to the queuing delay thereby providing a preference towards paths with a small number of links. In the second scheme the effects of several past routings are averaged as, for example, when the link lengths are computed and communicated asynchronously throughout the network.
An Improved Algorithm in Shortest Path Planning for a Tethered , Peter Brass
Goldman, William
An Improved Algorithm in Shortest Path Planning for a Tethered Robot Ning Xu , Peter Brass , Ivo power supply and stable communication through the tether. Following [1], the shortest path planning consider two different models of the short- est path planning problem. In the first model, the tether
Genetic Algorithm for Solving Fuzzy Shortest Path Problem in a Network with mixed fuzzy arc lengths
NASA Astrophysics Data System (ADS)
Mahdavi, Iraj; Tajdin, Ali; Hassanzadeh, Reza; Mahdavi-Amiri, Nezam; Shafieian, Hosna
2011-06-01
We are concerned with the design of a model and an algorithm for computing a shortest path in a network having various types of fuzzy arc lengths. First, we develop a new technique for the addition of various fuzzy numbers in a path using ? -cuts by proposing a linear least squares model to obtain membership functions for the considered additions. Then, using a recently proposed distance function for comparison of fuzzy numbers. we propose a new approach to solve the fuzzy APSPP using of genetic algorithm. Examples are worked out to illustrate the applicability of the proposed model.
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.
A single source k-shortest paths algorithm to infer regulatory pathways in a gene network
Shih, Yu-Keng; Parthasarathy, Srinivasan
2012-01-01
Motivation: Inferring the underlying regulatory pathways within a gene interaction network is a fundamental problem in Systems Biology to help understand the complex interactions and the regulation and flow of information within a system-of-interest. Given a weighted gene network and a gene in this network, the goal of an inference algorithm is to identify the potential regulatory pathways passing through this gene. Results: In a departure from previous approaches that largely rely on the random walk model, we propose a novel single-source k-shortest paths based algorithm to address this inference problem. An important element of our approach is to explicitly account for and enhance the diversity of paths discovered by our algorithm. The intuition here is that diversity in paths can help enrich different functions and thereby better position one to understand the underlying system-of-interest. Results on the yeast gene network demonstrate the utility of the proposed approach over extant state-of-the-art inference algorithms. Beyond utility, our algorithm achieves a significant speedup over these baselines. Availability: All data and codes are freely available upon request. Contact: srini@cse.ohio-state.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:22689778
Physarum can compute shortest paths.
Bonifaci, Vincenzo; Mehlhorn, Kurt; Varma, Girish
2012-09-21
Physarum polycephalum is a slime mold that is apparently able to solve shortest path problems. A mathematical model has been proposed by Tero et al. (Journal of Theoretical Biology, 244, 2007, pp. 553-564) to describe the feedback mechanism used by the slime mold to adapt its tubular channels while foraging two food sources s(0) and s(1). We prove that, under this model, the mass of the mold will eventually converge to the shortest s(0)-s(1) path of the network that the mold lies on, independently of the structure of the network or of the initial mass distribution. This matches the experimental observations by Tero et al. and can be seen as an example of a "natural algorithm", that is, an algorithm developed by evolution over millions of years. PMID:22732274
Identification of Novel Thyroid Cancer-Related Genes and Chemicals Using Shortest Path Algorithm
Zhang, Peiwei; Li, Li-Peng; He, Yi-Chun; Gao, Ru-jian; Gao, Yu-Fei
2015-01-01
Thyroid cancer is a typical endocrine malignancy. In the past three decades, the continued growth of its incidence has made it urgent to design effective treatments to treat this disease. To this end, it is necessary to uncover the mechanism underlying this disease. Identification of thyroid cancer-related genes and chemicals is helpful to understand the mechanism of thyroid cancer. In this study, we generalized some previous methods to discover both disease genes and chemicals. The method was based on shortest path algorithm and applied to discover novel thyroid cancer-related genes and chemicals. The analysis of the final obtained genes and chemicals suggests that some of them are crucial to the formation and development of thyroid cancer. It is indicated that the proposed method is effective for the discovery of novel disease genes and chemicals. PMID:25874234
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...
Physarum Can Compute Shortest Paths
Bonifaci, Vincenzo; Varma, Girish
2011-01-01
A mathematical model has been proposed by biologists to describe the feedback mechanism used by the Physarum Polycephalum slime mold to adapt its tubular channels while foraging two food sources $s_0$ and $s_1$. We give a proof of the fact that, under this model, the mass of the mold will eventually converge to the shortest $s_0$-$s_1$ path of the network that the mold lies on, independently of the structure of the network or of the initial mass distribution. This matches the experimental observations by the biologists and can be seen as an example of a "natural algorithm", that is, an algorithm developed by evolution over millions of years.
Neural Networks for Dynamic Shortest Path Routing Problems - A Survey
Nallusamy, R
2009-01-01
This paper reviews the overview of the dynamic shortest path routing problem and the various neural networks to solve it. Different shortest path optimization problems can be solved by using various neural networks algorithms. The routing in packet switched multi-hop networks can be described as a classical combinatorial optimization problem i.e. a shortest path routing problem in graphs. The survey shows that the neural networks are the best candidates for the optimization of dynamic shortest path routing problems due to their fastness in computation comparing to other softcomputing and metaheuristics algorithms
A fuzzy shortest path with the highest reliability
NASA Astrophysics Data System (ADS)
Keshavarz, Esmaile; Khorram, Esmaile
2009-08-01
This paper concentrates on a shortest path problem on a network where arc lengths (costs) are not deterministic numbers, but imprecise ones. Here, costs of the shortest path problem are fuzzy intervals with increasing membership functions, whereas the membership function of the total cost of the shortest path is a fuzzy interval with a decreasing linear membership function. By the max-min criterion suggested in [R.E. Bellman, L.A. Zade, Decision-making in a fuzzy environment, Management Science 17B (1970) 141-164], the fuzzy shortest path problem can be treated as a mixed integer nonlinear programming problem. We show that this problem can be simplified into a bi-level programming problem that is very solvable. Here, we propose an efficient algorithm, based on the parametric shortest path problem for solving the bi-level programming problem. An illustrative example is given to demonstrate our proposed algorithm.
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
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.
Using shortest path to discover criminal community
Magalingam, Pritheega; Rao, Asha
2015-01-01
Extracting communities using existing community detection algorithms yields dense sub-networks that are difficult to analyse. Extracting a smaller sample that embodies the relationships of a list of suspects is an important part of the beginning of an investigation. In this paper, we present the efficacy of our shortest paths network search algorithm (SPNSA) that begins with an "algorithm feed", a small subset of nodes of particular interest, and builds an investigative sub-network. The algorithm feed may consist of known criminals or suspects, or persons of influence. This sets our approach apart from existing community detection algorithms. We apply the SPNSA on the Enron Dataset of e-mail communications starting with those convicted of money laundering in relation to the collapse of Enron as the algorithm feed. The algorithm produces sparse and small sub-networks that could feasibly identify a list of persons and relationships to be further investigated. In contrast, we show that identifying sub-networks o...
Shortest Paths Dijkstra's algorithm
Sedgewick, Robert
numbers Â· not necessarily distances Â· need not satisfy the triangle inequality Â· Ex: airline fares [stay. Bellman (1958). Dynamic programming. Moore (1959). Routing long-distance telephone calls for Bell Labs
On the Comparison-Addition Complexity of All-Pairs Shortest Paths ?
Cafarella, Michael J.
programs. We present, in the same vein, an APSP algorithm that makes O(mn log #11;(m; n)) comparisons refer the reader to Zwick's survey [Z01] for a summary of other shortest path algorithms. It is still
Adaptive pyramidal clustering for shortest path determination
NASA Astrophysics Data System (ADS)
Olson, Keith; Speigle, Scott A.
1996-05-01
This paper will present a unique concept implemented in a software design that determines near optimal paths between hundreds of randomly connected nodes of interest in a faster time than current near optimal path determining algorithms. The adaptive pyramidal clustering (APC) approach to determining near optimal paths between numerous nodes uses an adaptive neural network along with classical heuristic search techniques. This combination is represented by a nearest neighbor clustering up function (performed by the neural network) and a trickle down pruning function (performed by the heuristic search). The function of the adaptive neural network is a significant reason why the APC algorithm is superior to several well known approaches. The APC algorithm has already been applied to autonomous route planning for unmanned ground vehicles. The intersections represent navigational waypoints that can be selected as source and destination locations. The APC algorithm then determines a near optimal path to navigate between the selected waypoints.
Locally Constrained Shortest Paths and an Application in Mission Planning
Kunkle, Tom
Locally Constrained Shortest Paths and an Application in Mission Planning Greg Angelides MIT on a feasible path. This problem has applications in robotics and optimal mission planning. We propose planning. 4. RESULTS AND CONTRIBUTIONS A dynamic programming heuristic Dijkstra's classical shortest path
The role of convexity for solving some shortest path problems in plane without triangulation
NASA Astrophysics Data System (ADS)
An, Phan Thanh; Hai, Nguyen Ngoc; Hoai, Tran Van
2013-09-01
Solving shortest path problems inside simple polygons is a very classical problem in motion planning. To date, it has usually relied on triangulation of the polygons. The question: "Can one devise a simple O(n) time algorithm for computing the shortest path between two points in a simple polygon (with n vertices), without resorting to a (complicated) linear-time triangulation algorithm?" raised by J. S. B. Mitchell in Handbook of Computational Geometry (J. Sack and J. Urrutia, eds., Elsevier Science B.V., 2000), is still open. The aim of this paper is to show that convexity contributes to the design of efficient algorithms for solving some versions of shortest path problems (namely, computing the convex hull of a finite set of points and convex rope on rays in 2D, computing approximate shortest path between two points inside a simple polygon) without triangulation on the entire polygons. New algorithms are implemented in C and numerical examples are presented.
Sreenan, Cormac J.
. These networks are subject to failures: the wireless devices are often unre- liable, they have limited battery placement Vertex-disjoint paths a b s t r a c t Wireless sensor networks (WSNs) are prone to failures. To be robust to failures, the net- work topology should provide alternative routes to the sinks so when
ON THE ACCELERATION OF SHORTEST PATH CALCULATIONS IN TRANSPORTATION NETWORKS
BAKER, ZACHARY K.; GOKHALE, MAYA B.
2007-01-08
Shortest path algorithms are a key element of many graph problems. They are used in such applications as online direction finding and navigation, as well as modeling of traffic for large scale simulations of major metropolitan areas. As the shortest path algorithms are an execution bottleneck, it is beneficial to move their execution to parallel hardware such as Field-Programmable Gate Arrays (FPGAs). Hardware implementation is accomplished through the use of a small A core replicated on the order of 20 times on an FPGA device. The objective is to maximize the use of on-board random-access memory bandwidth through the use of multi-threaded latency tolerance. Each shortest path core is responsible for one shortest path calculation, and when it is finished it outputs its result and requests the next source from a queue. One of the innovations of this approach is the use of a small bubble sort core to produce the extract-min function. While bubble sort is not usually considered an appropriate algorithm for any non-trivial usage, it is appropriate in this case as it can produce a single minimum out of the list in O(n) cycles, whwere n is the number of elements in the vertext list. The cost of this min operation does not impact the running time of the architecture, because the queue depth for fetching the next set of edges from memory is roughly equivalent to the number of cores in the system. Additionally, this work provides a collection of simulation results that model the behavior of the node queue in hardware. The results show that a hardware queue, implementing a small bubble-type minimum function, need only be on the order of 16 elements to provide both correct and optimal paths. Because the graph database size is measured in the hundreds of megabytes, the Cray SRAM memory is insufficient. In addition to the A* cores, they have developed a memory management system allowing round-robin servicing of the nodes as well as virtual memory managed over the Hypertransport bus. With support for a DRAM graph store with SRAM-based caching on the FPGA, the system provides a speedup of roughly 8.9x over the CPU-based implementation.
Discrete Approximations to Continuous Shortest-Path: Application to Minimum-Risk Path Planning for
Hespanha, João Pedro
1 Discrete Approximations to Continuous Shortest-Path: Application to Minimum-Risk Path Planning Barbara Research supported by DARPA/IXO MICA program Outline 1. Motivation--minimum-risk path planning 2. Discretization approach to shortest-path 3. Sampling methods 4. Back to minimum-risk path planning... #12
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.
Distributional properties of stochastic shortest paths for smuggled nuclear material
Cuellar, Leticia; Pan, Feng; Roach, Fred; Saeger, Kevin J
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.
Shortest Path Planning for a Tethered Robot or an Anchored Cable
Xavier, P.G.
1999-02-22
We consider the problem of planning shortest paths for a tethered robot with a finite length tether in a 2D environment with polygonal obstacles. We present an algorithm that runs in time O((k{sub 1} + 1){sup 2}n{sup 4}) and finds the shortest path or correctly determines that none exists that obeys the constraints; here n is the number obstacle vertices, and k{sub 1} is the number loops in the initial configuration of the tether. The robot may cross its tether but nothing can cross obstacles, which cause the tether to bend. The algorithm applies as well for planning a shortest path for the free end of an anchored cable.
A Continuous-State Version of Discrete Randomized Shortest-Paths, with Application to Path Planning
Del Moral , Pierre
A Continuous-State Version of Discrete Randomized Shortest-Paths, with Application to Path Planning are of capital importance in a variety of problems, from robot path planning, to maze solving. Path planning [16 RSP is investigated and applied to path planning. By defining a grid where each node has four
Expected Shortest Paths for Landmark-Based Robot Navigation
Scharstein, Daniel
Expected Shortest Paths for Landmark-Based Robot Navigation Amy J. Briggs1 , Carrick Detweiler1 of planning reliable landmark- based robot navigation strategies in the presence of significant sensor uncertainty. The navigation environments are modeled with directed weighted graphs in which edges can
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
The Union of Shortest Path Trees of Functional Brain Networks.
Meier, Jil; Tewarie, Prejaas; Van Mieghem, Piet
2015-11-01
Communication between brain regions is still insufficiently understood. Applying concepts from network science has shown to be successful in gaining insight in the functioning of the brain. Recent work has implicated that especially shortest paths in the structural brain network seem to play a major role in the communication within the brain. So far, for the functional brain network, only the average length of the shortest paths has been analyzed. In this article, we propose to construct the union of shortest path trees (USPT) as a new topology for the functional brain network. The minimum spanning tree, which has been successful in a lot of recent studies to comprise important features of the functional brain network, is always included in the USPT. After interpreting the link weights of the functional brain network as communication probabilities, the USPT of this network can be uniquely defined. Using data from magnetoencephalography, we applied the USPT as a method to find differences in the network topology of multiple sclerosis patients and healthy controls. The new concept of the USPT of the functional brain network also allows interesting interpretations and may represent the highways of the brain. PMID:26027712
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.
Do People Use the Shortest Path? An Empirical Test of Wardrop’s First Principle
Zhu, Shanjiang; Levinson, David
2015-01-01
Most recent route choice models, following either the random utility maximization or rule-based paradigm, require explicit enumeration of feasible routes. The quality of model estimation and prediction is sensitive to the appropriateness of the consideration set. However, few empirical studies of revealed route characteristics have been reported in the literature. This study evaluates the widely applied shortest path assumption by evaluating routes followed by residents of the Minneapolis—St. Paul metropolitan area. Accurate Global Positioning System (GPS) and Geographic Information System (GIS) data were employed to reveal routes people used over an eight to thirteen week period. Most people did not choose the shortest path. Using three weeks of that data, we find that current route choice set generation algorithms do not reveal the majority of paths that individuals took. Findings from this study may guide future efforts in building better route choice models. PMID:26267756
Do people use the shortest path? An empirical test of Wardrop's first principle.
Zhu, Shanjiang; Levinson, David
2015-01-01
Most recent route choice models, following either the random utility maximization or rule-based paradigm, require explicit enumeration of feasible routes. The quality of model estimation and prediction is sensitive to the appropriateness of the consideration set. However, few empirical studies of revealed route characteristics have been reported in the literature. This study evaluates the widely applied shortest path assumption by evaluating routes followed by residents of the Minneapolis-St. Paul metropolitan area. Accurate Global Positioning System (GPS) and Geographic Information System (GIS) data were employed to reveal routes people used over an eight to thirteen week period. Most people did not choose the shortest path. Using three weeks of that data, we find that current route choice set generation algorithms do not reveal the majority of paths that individuals took. Findings from this study may guide future efforts in building better route choice models. PMID:26267756
Makarychev, Konstantin
or involve a compromise, performing more opera- tions than the best sequential algorithm for the same problem. In this paper we introduce a compromise-free algorithm for the single-source shortest path problem on road linear-time traversal of the graph. This indicates that any significant practical improvements
A Graph Search Heuristic for Shortest Distance Paths
Chow, E
2005-03-24
This paper presents a heuristic for guiding A* search for finding the shortest distance path between two vertices in a connected, undirected, and explicitly stored graph. The heuristic requires a small amount of data to be stored at each vertex. The heuristic has application to quickly detecting relationships between two vertices in a large information or knowledge network. We compare the performance of this heuristic with breadth-first search on graphs with various topological properties. The results show that one or more orders of magnitude improvement in the number of vertices expanded is possible for large graphs, including Poisson random graphs.
Damage detection via shortest-path network sampling
NASA Astrophysics Data System (ADS)
Ciulla, Fabio; Perra, Nicola; Baronchelli, Andrea; Vespignani, Alessandro
2014-05-01
Large networked systems are constantly exposed to local damages and failures that can alter their functionality. The knowledge of the structure of these systems is, however, often derived through sampling strategies whose effectiveness at damage detection has not been thoroughly investigated so far. Here, we study the performance of shortest-path sampling for damage detection in large-scale networks. We define appropriate metrics to characterize the sampling process before and after the damage, providing statistical estimates for the status of nodes (damaged, not damaged). The proposed methodology is flexible and allows tuning the trade-off between the accuracy of the damage detection and the number of probes used to sample the network. We test and measure the efficiency of our approach considering both synthetic and real networks data. Remarkably, in all of the systems studied, the number of correctly identified damaged nodes exceeds the number of false positives, allowing us to uncover the damage precisely.
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
Shortest paths and load scaling in scale-free trees
NASA Astrophysics Data System (ADS)
Bollobás, Béla; Riordan, Oliver
2004-03-01
Szabó, Alava, and Kertész [Phys. Rev. E 66, 026101 (2002)] considered two questions about the scale-free random tree given by the m=1 case of the Barabási-Albert (BA) model (identical with a random tree model introduced by Szyma?ski in 1987): what is the distribution of the node to node distances, and what is the distribution of node loads, where the load on a node is the number of shortest paths passing through it? They gave heuristic answers to these questions using a “mean-field” approximation, replacing the random tree by a certain fixed tree with carefully chosen branching ratios. By making use of our earlier results on scale-free random graphs, we shall analyze the random tree rigorously, obtaining and proving very precise answers to these questions. We shall show that, after dividing by N (the number of nodes), the load distribution converges to an integer distribution X with Pr(X=c)=2/[(2c+1)(2c+3)], c=0,1,2,…, confirming the asymptotic power law with exponent -2 predicted by Szabó, Alava, and Kertész. For the distribution of node-node distances, we show asymptotic normality, and give a precise form for the (far from normal) large deviation law. We note that the mean-field methods used by Szabó, Alava, and Kertész give very good results for this model.
Tubule detection in testis images using boundary weighting and circular shortest path.
Zhang, Chao; Sun, Changming; Davey, Rhonda; Su, Ran; Bischof, Leanne; Vallotton, Pascal; Lovell, David; Hope, Shelly; Lehnert, Sigrid; Pham, Tuan D
2013-01-01
In studies of germ cell transplantation, measureing tubule diameters and counting cells from different populations using antibodies as markers are very important. Manual measurement of tubule sizes and cell counts is a tedious and sanity grinding work. In this paper, we propose a new boundary weighting based tubule detection method. We first enhance the linear features of the input image and detect the approximate centers of tubules. Next, a boundary weighting transform is applied to the polar transformed image of each tubule region and a circular shortest path is used for the boundary detection. Then, ellipse fitting is carried out for tubule selection and measurement. The algorithm has been tested on a dataset consisting of 20 images, each having about 20 tubules. Experiments show that the detection results of our algorithm are very close to the results obtained manually. PMID:24110438
A minimum resource neural network framework for solving multiconstraint shortest path problems.
Zhang, Junying; Zhao, Xiaoxue; He, Xiaotao
2014-08-01
Characterized by using minimum hard (structural) and soft (computational) resources, a novel parameter-free minimal resource neural network (MRNN) framework is proposed for solving a wide range of single-source shortest path (SP) problems for various graph types. The problems are the k-shortest time path problems with any combination of three constraints: time, hop, and label constraints, and the graphs can be directed, undirected, or bidirected with symmetric and/or asymmetric traversal time, which can be real and time dependent. Isomorphic to the graph where the SP is to be sought, the network is activated by generating autowave at source neuron and the autowave travels automatically along the paths with the speed of a hop in an iteration. Properties of the network are studied, algorithms are presented, and computation complexity is analyzed. The framework guarantees globally optimal solutions of a series of problems during the iteration process of the network, which provides insight into why even the SP is still too long to be satisfied. The network facilitates very large scale integrated circuit implementation and adapt to very large scale problems due to its massively parallel processing and minimum resource utilization. When implemented in a sequentially processing computer, experiments on synthetic graphs, road maps of cities of the USA, and vehicle routing with time windows indicate that the MRNN is especially efficient for large scale sparse graphs and even dense graphs with some constraints, e.g., the CPU time taken and the iteration number used for the road maps of cities of the USA is even less than ? 2% and 0.5% that of the Dijkstra's algorithm. PMID:25050952
He, Yunyue; Liu, Zhong; Shi, Jianmai; Wang, Yishan; Zhang, Jiaming; Liu, Jinyuan
2015-01-01
Emergency evacuation aims to transport people from dangerous places to safe shelters as quickly as possible. Police play an important role in the evacuation process, as they can handle traffic accidents immediately and help people move smoothly on roads. This paper investigates an evacuation routing problem that involves police resource allocation. We propose a novel k-th-shortest-path-based technique that uses explicit congestion control to optimize evacuation routing and police resource allocation. A nonlinear mixed-integer programming model is presented to formulate the problem. The model’s objective is to minimize the overall evacuation clearance time. Two algorithms are given to solve the problem. The first one linearizes the original model and solves the linearized problem with CPLEX. The second one is a heuristic algorithm that uses a police resource utilization efficiency index to directly solve the original model. This police resource utilization efficiency index significantly aids in the evaluation of road links from an evacuation throughput perspective. The proposed algorithms are tested with a number of examples based on real data from cities of different sizes. The computational results show that the police resource utilization efficiency index is very helpful in finding near-optimal solutions. Additionally, comparing the performance of the heuristic algorithm and the linearization method by using randomly generated examples indicates that the efficiency of the heuristic algorithm is superior. PMID:26226109
He, Yunyue; Liu, Zhong; Shi, Jianmai; Wang, Yishan; Zhang, Jiaming; Liu, Jinyuan
2015-01-01
Emergency evacuation aims to transport people from dangerous places to safe shelters as quickly as possible. Police play an important role in the evacuation process, as they can handle traffic accidents immediately and help people move smoothly on roads. This paper investigates an evacuation routing problem that involves police resource allocation. We propose a novel k-th-shortest-path-based technique that uses explicit congestion control to optimize evacuation routing and police resource allocation. A nonlinear mixed-integer programming model is presented to formulate the problem. The model's objective is to minimize the overall evacuation clearance time. Two algorithms are given to solve the problem. The first one linearizes the original model and solves the linearized problem with CPLEX. The second one is a heuristic algorithm that uses a police resource utilization efficiency index to directly solve the original model. This police resource utilization efficiency index significantly aids in the evaluation of road links from an evacuation throughput perspective. The proposed algorithms are tested with a number of examples based on real data from cities of different sizes. The computational results show that the police resource utilization efficiency index is very helpful in finding near-optimal solutions. Additionally, comparing the performance of the heuristic algorithm and the linearization method by using randomly generated examples indicates that the efficiency of the heuristic algorithm is superior. PMID:26226109
Maximum Entropy Models of Shortest Path and Outbreak Distributions in Networks
Bauckhage, Christian; Hadiji, Fabian
2015-01-01
Properties of networks are often characterized in terms of features such as node degree distributions, average path lengths, diameters, or clustering coefficients. Here, we study shortest path length distributions. On the one hand, average as well as maximum distances can be determined therefrom; on the other hand, they are closely related to the dynamics of network spreading processes. Because of the combinatorial nature of networks, we apply maximum entropy arguments to derive a general, physically plausible model. In particular, we establish the generalized Gamma distribution as a continuous characterization of shortest path length histograms of networks or arbitrary topology. Experimental evaluations corroborate our theoretical results.
Spreading and shortest paths in systems with sparse long-range connections
Cristian F. Moukarzel
1999-05-21
Spreading according to simple rules (e.g. of fire or diseases), and shortest-path distances are studied on d-dimensional systems with a small density p per site of long-range connections (``Small-World'' lattices). The volume V(t) covered by the spreading quantity on an infinite system is exactly calculated in all dimensions. We find that V(t) grows initially as t^d/d for t>t^*$, generalizing a previous result in one dimension. Using the properties of V(t), the average shortest-path distance \\ell(r) can be calculated as a function of Euclidean distance r. It is found that \\ell(r) = r for rr_c. The characteristic length r_c, which governs the behavior of shortest-path lengths, diverges with system size for all p>0. Therefore the mean separation s \\sim p^{-1/d} between shortcut-ends is not a relevant internal length-scale for shortest-path lengths. We notice however that the globally averaged shortest-path length, divided by L, is a function of L/s only.
Discrete Approximation to Continuous Anisotropic Shortest-Path Problem
Hespanha, João Pedro
-Risk Path Planning for Groups of UAVs James Riehl João Hespanha INFORMS Meeting November 6, 2007 #12;start [ ]: ( ( ), ( )) T J x t v t dt = #12;Related Work Rowe and Ross, 1990. · Ground vehicles moving on hilly terrain + #12;Minimum-Risk Path Planning for Groups of UAVs ( , )x v xi xf · Heterogeneous group of M UAVs · K
A Genetic Algorithm for Searching Shortest Lattice Vector of SVP Challenge
International Association for Cryptologic Research (IACR)
A Genetic Algorithm for Searching Shortest Lattice Vector of SVP Challenge Dan Ding1 , Guizhen Zhu2, China P. R. Abstract. In this paper, we propose a genetic algorithm for solving the shortest vector pruning. The experimental results show that the genetic algorithm runs rather good on the SVP challenge
The approach for shortest paths in fire succor based on component GIS technology
NASA Astrophysics Data System (ADS)
Han, Jie; Zhao, Yong; Dai, K. W.
2007-06-01
Fire safety is an important issue for the national economy and people's living. Efficiency and exactness of fire department succor directly relate to safety of peoples' lives and property. Many disadvantages of the traditional fire system have been emerged in practical applications. The preparation of pumpers is guided by wireless communication or wire communication, so its real-time and accurate performances are much poorer. The information about the reported fire, such as the position, disaster and map, et al., for alarm and command was processed by persons, which slows the reaction speed and delays the combat opportunity. In order to solve these disadvantages, it has an important role to construct a modern fire command center based on high technology. The construction of modern fire command center can realize the modernization and automation of fire command and management. It will play a great role in protecting safety of peoples' lives and property. The center can enhance battle ability and can reduce the direct and indirect loss of fire damage at most. With the development of science technology, Geographic Information System (GIS) has becoming a new information industry for hardware production, software development, data collection, space analysis and counseling. With the popularization of computers and the development of GIS, GIS has gained increasing broad applications for its strong functionality. Network analysis is one of the most important functions of GIS, and the most elementary and pivotal issue of network analysis is the calculation of shortest paths. The shortest paths are mostly applied to some emergent systems such as 119 fire alarms. These systems mainly require that the computation time of the optimal path should be 1-3 seconds. And during traveling, the next running path of the vehicles should be calculated in time. So the implement of the shortest paths must have a high efficiency. In this paper, the component GIS technology was applied to collect and record the data information (such as, the situation of this disaster, map and road status et al) of the reported fire firstly. The ant colony optimization was used to calculate the shortest path of fire succor secondly. The optimization results were sent to the pumpers, which can let pumpers choose the shortest paths intelligently and come to fire position with least time. The programming method for shortest paths is proposed in section 3. There are three parts in this section. The elementary framework of the proposed programming method is presented in part one. The systematic framework of GIS component is described in part two. The ant colony optimization employed is presented in part three. In section 4, a simple application instance was presented to demonstrate the proposed programming method. There are three parts in this section. The distributed Web application based on component GIS was described in part one. The optimization results without traffic constraint were presented in part two. The optimization results with traffic constraint were presented in part three. The contributions of this paper can be summarized as follows. (1) It proposed an effective approach for shortest paths in fire succor based on component GIS technology. This proposed approach can achieve the real-time decisions of shortest paths for fire succor. (2) It applied the ant colony optimization to implement the shortest path decision. The traffic information was considered in the shortest path decision using ant colony optimization. The final application instance suggests that the proposed approach is feasible, correct and valid.
LIDS REPORT 2875 1 Stochastic Shortest Path Games and Q-Learning
Yu, Huizhen Janey
stochastic dynamic games (or Markov games) that have a cost-free termination state. Our main focusLIDS REPORT 2875 1 Stochastic Shortest Path Games and Q-Learning Huizhen Yu Abstract We consider a class of two-player zero-sum stochastic games with finite state and compact control spaces, which we
Shortest Path Stochastic Control for Hybrid Electric Vehicles , J.W. Grizzle2
Grizzle, Jessy W.
1 of 28 Shortest Path Stochastic Control for Hybrid Electric Vehicles Ed Tate1 , J.W. Grizzle2 , Huei Peng3 Abstract: When a Hybrid Electric Vehicle (HEV) is certified for emissions and fuel economy this is the Hybrid Electric Vehicle (HEV) which consists of an electric powertrain coupled to a conventional
Fuel-Optimal Centralized Coordination of Truck Platooning Based on Shortest Paths
Dimarogonas, Dimos
Fuel-Optimal Centralized Coordination of Truck Platooning Based on Shortest Paths Sebastian van de fuel consumption of trucks. Vehicles that drive at close inter- vehicle distance assisted by automatic the formation and the breakup of platoons in a fuel-optimal way. We formulate an optimization problem which
Optimal Distributed All Pairs Shortest Paths and Applications
) time. 1 #12;1 Introduction In networks, basically two types of routing algorithms are known: distance the information about the network graph is collected, and then optimal routes between all nodes are computed, using an efficient centralized algorithm. Distance-vector routing protocols on the other hand represent
Hespanha, João Pedro
, in fact, the most basic problem in Calculus of Variations (cf., e.g., [7]). Assuming for simplicity that R defenses, e.g., Surface-to-Air Missiles (SAMs). The computation of shortest-paths has a long history and is
Improved Nguyen-Vidick Heuristic Sieve Algorithm for Shortest Vector Problem
International Association for Cryptologic Research (IACR)
Improved Nguyen-Vidick Heuristic Sieve Algorithm for Shortest Vector Problem Xiaoyun Wang1 of the Nguyen-Vidick heuristic sieve algorithm for shortest vector problem in general lattices, which time, sieve, heuristic, sphere covering 1 Introduction The n-dimensional lattice is generated by the basis B
Fast shortest path distance estimation in large networks
, they require as much as 250 times less space than the current approach in the literature which considers on a daily basis. For graphs of this size even the algorithmic problems that are seemingly simple become including among many others protein interaction networks in biology and route computation in transportation
Modeling the average shortest-path length in growth of word-adjacency networks
NASA Astrophysics Data System (ADS)
Kulig, Andrzej; Dro?d?, Stanis?aw; Kwapie?, Jaros?aw; O?wiÈ©cimka, Pawe?
2015-03-01
We investigate properties of evolving linguistic networks defined by the word-adjacency relation. Such networks belong to the category of networks with accelerated growth but their shortest-path length appears to reveal the network size dependence of different functional form than the ones known so far. We thus compare the networks created from literary texts with their artificial substitutes based on different variants of the Dorogovtsev-Mendes model and observe that none of them is able to properly simulate the novel asymptotics of the shortest-path length. Then, we identify the local chainlike linear growth induced by grammar and style as a missing element in this model and extend it by incorporating such effects. It is in this way that a satisfactory agreement with the empirical result is obtained.
Shortest Path Induced Vertex Ordering and its Application to Multi-agent Formation Path Planning
Yu, Jingjin
2012-01-01
For the task of moving a group of indistinguishable agents on a connected graph with unit edge length into an arbitrary goal formation, it was shown previously that distance optimal paths can be planned to complete with a tight convergence time guarantee. In this study, we show that the problem formulation in fact induces a more fundamental structure on the underlying graph network, which directly leads to an algorithm with similar performance characteristics. We then generalize the results to graphs with integer edge lengths and capacities.
Challenging of path planning algorithms for autonomous robot in known environment
NASA Astrophysics Data System (ADS)
Farah, R. N.; Irwan, N.; Zuraida, Raja Lailatul; Shaharum, Umairah; Hanafi@Omar, Hafiz Mohd
2014-06-01
Most of the mobile robot path planning is estimated to reach its predetermined aim through the shortest path and avoiding the obstacles. This paper is a survey on path planning algorithms of various current research and existing system of Unmanned Ground Vehicles (UGV) where their challenging issues to be intelligent autonomous robot. The focuses are some short reviews on individual papers for UGV in the known environment. Methods and algorithms in path planning for the autonomous robot had been discussed. From the reviews, we obtained that the algorithms proposed are appropriate for some cases such as single or multiple obstacles, static or movement obstacle and optimal shortest path. This paper also describes some pros and cons for every reviewed paper toward algorithms improvement for further work.
Tsiotras, Panagiotis
to Kinodynamic Path Planning Raghvendra V. Cowlagi and Panagiotis Tsiotras Abstract-- A new algorithm of the path to the current node. The algorithm is applied to solve path planning problems with curvature constraints. I. INTRODUCTION The problem of planning a path for an autonomous vehicle in a given environment
Analyzing the applicability of the least risk path algorithm in indoor space
NASA Astrophysics Data System (ADS)
Vanclooster, A.; Viaene, P.; Van de Weghe, N.; Fack, V.; De Maeyer, Ph.
2013-11-01
Over the last couple of years, applications that support navigation and wayfinding in indoor environments have become one of the booming industries. However, the algorithmic support for indoor navigation has so far been left mostly untouched, as most applications mainly rely on adapting Dijkstra's shortest path algorithm to an indoor network. In outdoor space, several alternative algorithms have been proposed adding a more cognitive notion to the calculated paths and as such adhering to the natural wayfinding behavior (e.g. simplest paths, least risk paths). 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…). 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-story building. Several analyses compare shortest and least risk paths in indoor and in outdoor space. The results of these analyses indicate that the current outdoor least risk path algorithm does not calculate less risky paths compared to its shortest paths. In some cases, worse routes have been suggested. Adjustments to the original algorithm are proposed to be more aligned to the specific structure of indoor environments. 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.
Ohya, Akihisa
, , ( ) Obstacle Avoidance Algorithm for Mobile Robot Running on the Planned Path Gao Cheng algorithm by the information obtained with the SOKUIKI sensor for mobile robot running on the planned path Shortest path generation proach to Planning, Sensing and Navigation for Mo- bile Robots ,1993 Preprints
PARALLEL EVOLUTIONARY ALGORITHMS FOR UAV PATH PLANNING
PARALLEL EVOLUTIONARY ALGORITHMS FOR UAV PATH PLANNING Dong Jia Post-Doctoral Research Associate vehicles (UAVs). Premature convergence prevents evolutionary-based algorithms from reaching global optimal. To overcome this problem, this paper presents a framework of parallel evolutionary algorithms for UAV path
Regularization Path Algorithms for Detecting Gene Interactions
Hastie, Trevor
of indicators can be selected simultaneously. Here we introduce another version of group-Lars. In addi- tion, we models. We regard this strategy of using path algorithms as a compromise between our two earlier studies
The Shortest Path to Happiness: Recommending Beautiful, Quiet, and Happy Routes in the City
Quercia, Daniele; Aiello, Luca Maria
2014-01-01
When providing directions to a place, web and mobile mapping services are all able to suggest the shortest route. The goal of this work is to automatically suggest routes that are not only short but also emotionally pleasant. To quantify the extent to which urban locations are pleasant, we use data from a crowd-sourcing platform that shows two street scenes in London (out of hundreds), and a user votes on which one looks more beautiful, quiet, and happy. We consider votes from more than 3.3K individuals and translate them into quantitative measures of location perceptions. We arrange those locations into a graph upon which we learn pleasant routes. Based on a quantitative validation, we find that, compared to the shortest routes, the recommended ones add just a few extra walking minutes and are indeed perceived to be more beautiful, quiet, and happy. To test the generality of our approach, we consider Flickr metadata of more than 3.7M pictures in London and 1.3M in Boston, compute proxies for the crowdsourced...
Yuan, Fei; Zhang, Yu-Hang; Wan, Sibao; Wang, ShaoPeng; Kong, Xiang-Yin
2015-01-01
Pancreatic cancer (PC) is a highly malignant tumor derived from pancreas tissue and is one of the leading causes of death from cancer. Its molecular mechanism has been partially revealed by validating its oncogenes and tumor suppressor genes; however, the available data remain insufficient for medical workers to design effective treatments. Large-scale identification of PC-related genes can promote studies on PC. In this study, we propose a computational method for mining new candidate PC-related genes. A large network was constructed using protein-protein interaction information, and a shortest path approach was applied to mine new candidate genes based on validated PC-related genes. In addition, a permutation test was adopted to further select key candidate genes. Finally, for all discovered candidate genes, the likelihood that the genes are novel PC-related genes is discussed based on their currently known functions. PMID:26613085
Yuan, Fei; Zhou, You; Wang, Meng; Yang, Jing; Wu, Kai; Lu, Changhong; Kong, Xiangyin; Cai, Yu-Dong
2015-01-01
Prostate cancer is a type of cancer that occurs in the male prostate, a gland in the male reproductive system. Because prostate cancer cells may spread to other parts of the body and can influence human reproduction, understanding the mechanisms underlying this disease is critical for designing effective treatments. The identification of as many genes and chemicals related to prostate cancer as possible will enhance our understanding of this disease. In this study, we proposed a computational method to identify new candidate genes and chemicals based on currently known genes and chemicals related to prostate cancer by applying a shortest path approach in a hybrid network. The hybrid network was constructed according to information concerning chemical-chemical interactions, chemical-protein interactions, and protein-protein interactions. Many of the obtained genes and chemicals are associated with prostate cancer. PMID:26504486
Liu, Lei; Cai, Yu-Dong; Chou, Kuo-Chen
2012-01-01
One of the most important and challenging problems in biomedicine and genomics is how to identify the disease genes. In this study, we developed a computational method to identify colorectal cancer-related genes based on (i) the gene expression profiles, and (ii) the shortest path analysis of functional protein association networks. The former has been used to select differentially expressed genes as disease genes for quite a long time, while the latter has been widely used to study the mechanism of diseases. With the existing protein-protein interaction data from STRING (Search Tool for the Retrieval of Interacting Genes), a weighted functional protein association network was constructed. By means of the mRMR (Maximum Relevance Minimum Redundancy) approach, six genes were identified that can distinguish the colorectal tumors and normal adjacent colonic tissues from their gene expression profiles. Meanwhile, according to the shortest path approach, we further found an additional 35 genes, of which some have been reported to be relevant to colorectal cancer and some are very likely to be relevant to it. Interestingly, the genes we identified from both the gene expression profiles and the functional protein association network have more cancer genes than the genes identified from the gene expression profiles alone. Besides, these genes also had greater functional similarity with the reported colorectal cancer genes than the genes identified from the gene expression profiles alone. All these indicate that our method as presented in this paper is quite promising. The method may become a useful tool, or at least plays a complementary role to the existing method, for identifying colorectal cancer genes. It has not escaped our notice that the method can be applied to identify the genes of other diseases as well. PMID:22496748
Kahng, Andrew B.
problem is called the Minimum Rectilinear Steiner Arborescence MRSA problem. Given a set of terminals N. It can be shown that an MSPSA of GHN;N;r is an MRSA of N. Exact methods for the MRSA problem can in the RSA DP algorithm by Leung and Cong 18 . Nastansky et al. 20 formulated the MRSA problem and its D
Kahng, Andrew B.
the Minimum Rectilinear Steiner Arborescence (MRSA) problem. Given a set of terminals N (including the root r be shown that an MSPSA of (GH(N) ; N; r) is an MRSA of N . Exact methods for the MRSA problem can in the RSA/DP algorithm by Leung and Cong [18]. Nastansky et al. [20] formulated the MRSA problem (and its D
Geometric Shortest Paths and Network Optimization Joseph S.B. Mitchell \\Lambda
Mitchell, Joseph S.B.
complex geometry? single shot vs. repetitive mode queries: Do we want to build an effective data structure9504192, and by grants from Boeing Computer Services, Bridgeport Machines, Hughes Aircraft, and Sun extensive lists of results on parallel algorithms in geometry. We will freely use the ``bigOh'' notation
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.
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.
Robot path planning using a genetic algorithm
NASA Technical Reports Server (NTRS)
Cleghorn, Timothy F.; Baffes, Paul T.; Wang, Liu
1988-01-01
Robot path planning can refer either to a mobile vehicle such as a Mars Rover, or to an end effector on an arm moving through a cluttered workspace. In both instances there may exist many solutions, some of which are better than others, either in terms of distance traversed, energy expended, or joint angle or reach capabilities. A path planning program has been developed based upon a genetic algorithm. This program assumes global knowledge of the terrain or workspace, and provides a family of good paths between the initial and final points. Initially, a set of valid random paths are constructed. Successive generations of valid paths are obtained using one of several possible reproduction strategies similar to those found in biological communities. A fitness function is defined to describe the goodness of the path, in this case including length, slope, and obstacle avoidance considerations. It was found that with some reproduction strategies, the average value of the fitness function improved for successive generations, and that by saving the best paths of each generation, one could quite rapidly obtain a collection of good candidate solutions.
Adaptive path planning: Algorithm and analysis
Chen, Pang C.
1995-03-01
To address the need for a fast path planner, we present a learning algorithm that improves path planning by using past experience to enhance future performance. The algorithm relies on an existing path planner to provide solutions difficult tasks. From these solutions, an evolving sparse work of useful robot configurations is learned to support faster planning. More generally, the algorithm provides a framework in which a slow but effective planner may be improved both cost-wise and capability-wise by a faster but less effective planner coupled with experience. We analyze algorithm by formalizing the concept of improvability and deriving conditions under which a planner can be improved within the framework. The analysis is based on two stochastic models, one pessimistic (on task complexity), the other randomized (on experience utility). Using these models, we derive quantitative bounds to predict the learning behavior. We use these estimation tools to characterize the situations in which the algorithm is useful and to provide bounds on the training time. In particular, we show how to predict the maximum achievable speedup. Additionally, our analysis techniques are elementary and should be useful for studying other types of probabilistic learning as well.
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.
Adaptive path planning algorithm for cooperating unmanned air vehicles
Cunningham, C T; Roberts, R S
2001-02-08
An adaptive path planning algorithm is presented for cooperating Unmanned Air Vehicles (UAVs) that are used to deploy and operate land-based sensor networks. The algorithm employs a global cost function to generate paths for the UAVs, and adapts the paths to exceptions that might occur. Examples are provided of the paths and adaptation.
An Adaptive Path Planning Algorithm for Cooperating Unmanned Air Vehicles
Cunningham, C.T.; Roberts, R.S.
2000-09-12
An adaptive path planning algorithm is presented for cooperating Unmanned Air Vehicles (UAVs) that are used to deploy and operate land-based sensor networks. The algorithm employs a global cost function to generate paths for the UAVs, and adapts the paths to exceptions that might occur. Examples are provided of the paths and adaptation.
Adaptive path planning: Algorithm and analysis
Chen, Pang C.
1993-03-01
Path planning has to be fast to support 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 alleviate this problem, we present a learning algorithm that uses past experience to enhance future performance. The algorithm relies on an existing path planner to provide solutions to difficult tasks. From these solutions, an evolving sparse network of useful subgoals is learned to support faster planning. The algorithm is suitable for both stationary and incrementally-changing environments. To analyze our algorithm, we use a previously developed stochastic model that quantifies experience utility. Using this model, we characterize the situations in which the adaptive planner is useful, and provide quantitative bounds to predict its behavior. The results are demonstrated with problems in manipulator planning. Our algorithm and analysis are sufficiently general that they may also be applied to task planning or other planning domains in which experience is useful.
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...
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.
PCB Drill Path Optimization by Combinatorial Cuckoo Search Algorithm
Lim, Wei Chen Esmonde; Kanagaraj, G.; Ponnambalam, S. G.
2014-01-01
Optimization of drill path can lead to significant reduction in machining time which directly improves productivity of manufacturing systems. In a batch production of a large number of items to be drilled such as printed circuit boards (PCB), the travel time of the drilling device is a significant portion of the overall manufacturing process. To increase PCB manufacturing productivity and to reduce production costs, a good option is to minimize the drill path route using an optimization algorithm. This paper reports a combinatorial cuckoo search algorithm for solving drill path optimization problem. The performance of the proposed algorithm is tested and verified with three case studies from the literature. The computational experience conducted in this research indicates that the proposed algorithm is capable of efficiently finding the optimal path for PCB holes drilling process. PMID:24707198
PCB drill path optimization by combinatorial cuckoo search algorithm.
Lim, Wei Chen Esmonde; Kanagaraj, G; Ponnambalam, S G
2014-01-01
Optimization of drill path can lead to significant reduction in machining time which directly improves productivity of manufacturing systems. In a batch production of a large number of items to be drilled such as printed circuit boards (PCB), the travel time of the drilling device is a significant portion of the overall manufacturing process. To increase PCB manufacturing productivity and to reduce production costs, a good option is to minimize the drill path route using an optimization algorithm. This paper reports a combinatorial cuckoo search algorithm for solving drill path optimization problem. The performance of the proposed algorithm is tested and verified with three case studies from the literature. The computational experience conducted in this research indicates that the proposed algorithm is capable of efficiently finding the optimal path for PCB holes drilling process. PMID:24707198
Jiang, Hai, 1979-
2004-01-01
This thesis aims at the development of faster Dynamic Traffic Assignment (DTA) models to meet the computational efficiency required by real world applications. A DTA model can be decomposed into several sub-models, of which ...
Kahng, Andrew B.
]. The rectilinear version of the MSPSA problem is called the Minimum Rectilinear Steiner Arborescence (MRSA) problem(N) ) be the induced Hanan grid graph [10] of N . It can be shown that an MSPSA of (G H(N) ; N; r) is an MRSA of N . Exact methods for the MRSA problem can be classified into (1) dynamic programming, (2) integer
Should QoS routing algorithms prefer shortest paths? Karol Kowalik and Martin Collier
Collier, Martin
-- Multimedia traffic and real-time e-commerce appli- cations can experience quality degradation in traditional resources for future connections. Others advocate load balancing mechanisms so as to increase overall for the traffic flows and so is not suitable for use by multimedia or real-time e-commerce applications
Path querying system on mobile devices
NASA Astrophysics Data System (ADS)
Lin, Xing; Wang, Yifei; Tian, Yuan; Wu, Lun
2006-01-01
Traditional approaches to path querying problems are not efficient and convenient under most circumstances. A more convenient and reliable approach to this problem has to be found. This paper is devoted to a path querying solution on mobile devices. By using an improved Dijkstra's shortest path algorithm and a natural language translating module, this system can help people find the shortest path between two places through their cell phones or other mobile devices. The chosen path is prompted in text of natural language, as well as a map picture. This system would be useful in solving best path querying problems and have potential to be a profitable business system.
Extracting contours of oval-shaped objects by Hough transform and minimal path algorithms
NASA Astrophysics Data System (ADS)
Tleis, Mohamed; Verbeek, Fons J.
2014-04-01
Circular and oval-like objects are very common in cell and micro biology. These objects need to be analyzed, and to that end, digitized images from the microscope are used so as to come to an automated analysis pipeline. It is essential to detect all the objects in an image as well as to extract the exact contour of each individual object. In this manner it becomes possible to perform measurements on these objects, i.e. shape and texture features. Our measurement objective is achieved by probing contour detection through dynamic programming. In this paper we describe a method that uses Hough transform and two minimal path algorithms to detect contours of (ovoid-like) objects. These algorithms are based on an existing grey-weighted distance transform and a new algorithm to extract the circular shortest path in an image. The methods are tested on an artificial dataset of a 1000 images, with an F1-score of 0.972. In a case study with yeast cells, contours from our methods were compared with another solution using Pratt's figure of merit. Results indicate that our methods were more precise based on a comparison with a ground-truth dataset. As far as yeast cells are concerned, the segmentation and measurement results enable, in future work, to retrieve information from different developmental stages of the cell using complex features.
Randomized Algorithms Robert Elsasser
Elsässer, Robert
Randomized Algorithms Robert Els¨asser 20. April 2011 Program of the day: · Computing shortest paths Robert Els¨asser Universit¨at Paderborn Randomized Algorithms SS 11 0 #12;2. Computing Distances2 n) using a randomized algorithms. Robert Els¨asser Universit¨at Paderborn Randomized Algorithms SS
Randomized Algorithms Robert Elsasser
Elsässer, Robert
Randomized Algorithms Robert Els¨asser 27. April 2011 Program of the day: · Computing shortest paths Robert Els¨asser Universit¨at Paderborn Randomized Algorithms SS 11 0 #12;2. Computing Distances2 n) using a randomized algorithms. Robert Els¨asser Universit¨at Paderborn Randomized Algorithms SS
Autonomous routing algorithms for networks with wide-spread failures
Modiano, Eytan H.
We study end-to-end delay performance of different routing algorithms in networks with random failures. Specifically, we compare delay performances of differential backlog (DB) and shortest path (SP) routing algorithms and ...
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.
Optimal Path Planning in Complex Cost Spaces with Sampling-based Algorithms
Kavraki, Lydia E.
1 Optimal Path Planning in Complex Cost Spaces with Sampling-based Algorithms Didier Devaurs, Thierry Sim´eon, and Juan Cort´es Abstract--Sampling-based algorithms for path planning, such as RRT, have with optimal path planning: they ensure convergence toward the optimal path, with respect to a given path
Autonomous Local Path-Planning for a Mobile Robot Using a Genetic Algorithm
Wainwright, Roger L.
Autonomous Local Path-Planning for a Mobile Robot Using a Genetic Algorithm Kamran H. Sedighi presents results of our work in development of a genetic algorithm based path-planning algorithm for local of the path and the number of turns. The proposed path- planning method allows a free movement of the robot
Autonomous Local Path Planning for a Mobile Robot Using a Genetic Algorithm
Manikas, Theodore
Autonomous Local Path Planning for a Mobile Robot Using a Genetic Algorithm Kamran H. Sedighi presents results of our work in development of a genetic algorithm based path-planning algorithm for local of the path and the number of turns. The proposed path-planning method allows a free movement of the robot
Path Cost Optimization Using Genetic Algorithm with Supervised Crossover Operator
Tse, Chi K. "Michael"
Path Cost Optimization Using Genetic Algorithm with Supervised Crossover Operator Chi-Tsun Cheng , Kia Fallahi , Henry Leung and Chi K. Tse Dept. of Electronic & Information Engineering, Hong Kong Polytechnic University, Hong Kong Dept. of Electrical & Computer Engineering, University of Calgary, Calgary
Path Planning Algorithms for Autonomous Border Patrol Vehicles
NASA Astrophysics Data System (ADS)
Lau, George Tin Lam
This thesis presents an online path planning algorithm developed for unmanned vehicles in charge of autonomous border patrol. In this Pursuit-Evasion game, the unmanned vehicle is required to capture multiple trespassers on its own before any of them reach a target safe house where they are safe from capture. The problem formulation is based on Isaacs' Target Guarding problem, but extended to the case of multiple evaders. The proposed path planning method is based on Rapidly-exploring random trees (RRT) and is capable of producing trajectories within several seconds to capture 2 or 3 evaders. Simulations are carried out to demonstrate that the resulting trajectories approach the optimal solution produced by a nonlinear programming-based numerical optimal control solver. Experiments are also conducted on unmanned ground vehicles to show the feasibility of implementing the proposed online path planning algorithm on physical applications.
Tsiotras, Panagiotis
A Hierarchical On-Line Path Planning Scheme using Wavelets Panagiotis Tsiotras and Efstathios Bakolas Abstract-- We present an algorithm for solving the shortest (collision-free) path planning problem representation of W or a discrete one. In this work we propose an algorithm which solves the path planning
M*: A Complete Multirobot Path Planning Algorithm with Performance Glenn Wagner, Howie Choset
Choset, Howie
M*: A Complete Multirobot Path Planning Algorithm with Performance Bounds Glenn Wagner, Howie Choset Abstract-- Multirobot path planning is difficult because the full configuration space a high dimensional configuration space is the fundamental problem of multirobot path planning. Multirobot
Path Planning Algorithms for the Adaptive Sensor Fleet
NASA Technical Reports Server (NTRS)
Stoneking, Eric; Hosler, Jeff
2005-01-01
The Adaptive Sensor Fleet (ASF) is a general purpose fleet management and planning system being developed by NASA in coordination with NOAA. The current mission of ASF is to provide the capability for autonomous cooperative survey and sampling of dynamic oceanographic phenomena such as current systems and algae blooms. Each ASF vessel is a software model that represents a real world platform that carries a variety of sensors. The OASIS platform will provide the first physical vessel, outfitted with the systems and payloads necessary to execute the oceanographic observations described in this paper. The ASF architecture is being designed for extensibility to accommodate heterogenous fleet elements, and is not limited to using the OASIS platform to acquire data. This paper describes the path planning algorithms developed for the acquisition phase of a typical ASF task. Given a polygonal target region to be surveyed, the region is subdivided according to the number of vessels in the fleet. The subdivision algorithm seeks a solution in which all subregions have equal area and minimum mean radius. Once the subregions are defined, a dynamic programming method is used to find a minimum-time path for each vessel from its initial position to its assigned region. This path plan includes the effects of water currents as well as avoidance of known obstacles. A fleet-level planning algorithm then shuffles the individual vessel assignments to find the overall solution which puts all vessels in their assigned regions in the minimum time. This shuffle algorithm may be described as a process of elimination on the sorted list of permutations of a cost matrix. All these path planning algorithms are facilitated by discretizing the region of interest onto a hexagonal tiling.
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.
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.
Reaction Path Optimization without NEB Springs or Interpolation Algorithms.
Plessow, P
2013-03-12
This letter describes a chain-of-states method that optimizes reaction paths under the sole constraint of equally spaced structures. In contrast to NEB and string methods, it requires no spring forces, interpolation algorithms, or other heuristics to control structure distribution. Rigorous use of a quadratic PES allows calculation of an optimization step with a predefined distribution in Cartesian space. The method is a formal extension of single-structure quasi-Newton methods. An initial guess can be evolved, as in the growing string method. PMID:26587592
MOD* Lite: An Incremental Path Planning Algorithm Taking Care of Multiple Objectives.
Oral, Tugcem; Polat, Faruk
2016-01-01
The need for determining a path from an initial location to a target one is a crucial task in many applications, such as virtual simulations, robotics, and computer games. Almost all of the existing algorithms are designed to find optimal or suboptimal solutions considering only a single objective, namely path length. However, in many real life application path length is not the sole criteria for optimization, there are more than one criteria to be optimized that cannot be transformed to each other. In this paper, we introduce a novel multiobjective incremental algorithm, multiobjective D* lite (MOD* lite) built upon a well-known path planning algorithm, D* lite. A number of experiments are designed to compare the solution quality and execution time requirements of MOD* lite with the multiobjective A* algorithm, an alternative genetic algorithm we developed multiobjective genetic path planning and the strength Pareto evolutionary algorithm. PMID:25730837
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 for real-world mobile robots. Ill-designed curves on a path can cause large guidance errors, and also mobile robots. The X4Y4 curve and a control algorithm for an articulated mobile robot following an X4Y4
A fast and accurate algorithm for high-frequency trans-ionospheric path length determination
NASA Astrophysics Data System (ADS)
Wijaya, Dudy D.
2015-12-01
This paper presents a fast and accurate algorithm for high-frequency trans-ionospheric path length determination. The algorithm is merely based on the solution of the Eikonal equation that is solved using the conformal theory of refraction. The main advantages of the algorithm are summarized as follows. First, the algorithm can determine the optical path length without iteratively adjusting both elevation and azimuth angles and, hence, the computational time can be reduced. Second, for the same elevation and azimuth angles, the algorithm can simultaneously determine the phase and group of both ordinary and extra-ordinary optical path lengths for different frequencies. Results from numerical simulations show that the computational time required by the proposed algorithm to accurately determine 8 different optical path lengths is almost 17 times faster than that required by a 3D ionospheric ray-tracing algorithm. It is found that the computational time to determine multiple optical path lengths is the same with that for determining a single optical path length. It is also found that the proposed algorithm is capable of determining the optical path lengths with millimeter level of accuracies, if the magnitude of the squared ratio of the plasma frequency to the transmitted frequency is less than 1.33× 10^{-3}, and hence the proposed algorithm is applicable for geodetic applications.
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.
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
Multiple Manifold Clustering Using Curvature Constrained Path
Babaeian, Amir; Bayestehtashk, Alireza; Bandarabadi, Mojtaba
2015-01-01
The problem of multiple surface clustering is a challenging task, particularly when the surfaces intersect. Available methods such as Isomap fail to capture the true shape of the surface near by the intersection and result in incorrect clustering. The Isomap algorithm uses shortest path between points. The main draw back of the shortest path algorithm is due to the lack of curvature constrained where causes to have a path between points on different surfaces. In this paper we tackle this problem by imposing a curvature constraint to the shortest path algorithm used in Isomap. The algorithm chooses several landmark nodes at random and then checks whether there is a curvature constrained path between each landmark node and every other node in the neighborhood graph. We build a binary feature vector for each point where each entry represents the connectivity of that point to a particular landmark. Then the binary feature vectors could be used as a input of conventional clustering algorithm such as hierarchical clustering. We apply our method to simulated and some real datasets and show, it performs comparably to the best methods such as K-manifold and spectral multi-manifold clustering. PMID:26375819
: A Holistic Path Join Algorithm for Path Query with Not-predicates on XML Data
Ling, Tok Wang
-to-leaf paths in tree-structured XML documents that satisfy certain selection predicates is the basis of complex XML query processing. Such selection predicates are called path queries (i.e., twig queries without applications. As an example of a path query with a not-predicate, consider the XPath query: //supplier
Path planning for mobile robots based on visibility graphs and A* algorithm
NASA Astrophysics Data System (ADS)
Contreras, Juan D.; Martínez S., Fernando; Martínez S., Fredy H.
2015-07-01
One of most worked issues in the last years in robotics has been the study of strategies to path planning for mobile robots in static and observable conditions. This is an open problem without pre-defined rules (non-heuristic), which needs to measure the state of the environment, finds useful information, and uses an algorithm to select the best path. This paper proposes a simple and efficient geometric path planning strategy supported in digital image processing. The image of the environment is processed in order to identify obstacles, and thus the free space for navigation. Then, using visibility graphs, the possible navigation paths guided by the vertices of obstacles are produced. Finally the A* algorithm is used to find a best possible path. The alternative proposed is evaluated by simulation on a large set of test environments, showing in all cases its ability to find a free collision plausible path.
Kulling, Karl Christian
2009-01-01
This thesis presents new algorithms for path planning in a communications constrained environment for teams of unmanned vehicles. This problem involves a lead vehicle that must gather information from a set of locations ...
Branicky, Michael S.
execution deadline arrives. Examples of such systems include ground vehicles (driving on the highway at high from the full path set. One popular strategy for improving online planning time is to precompute a setPath and Trajectory Diversity: Theory and Algorithms Michael S. Branicky Ross A. Knepper James J
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...
ERIC Educational Resources Information Center
Boker, Steven M.; McArdle, J. J.; Neale, Michael
2002-01-01
Presents an algorithm for the production of a graphical diagram from a matrix formula in such a way that its components are logically and hierarchically arranged. The algorithm, which relies on the matrix equations of J. McArdle and R. McDonald (1984), calculates the individual path components of expected covariance between variables and…
Effective evacuation route planning algorithms by updating earliest arrival time of multiple paths
Lim, Sunho
Effective evacuation route planning algorithms by updating earliest arrival time of multiple paths are happening around the globe and in such urgent situations, effective evacuation planning is one of the most critical tools for human safety. Evacuation planning algorithms are different from traditional network
VTL Zone-Aware Path Cloaking Algorithm Bin Zan Peng Hao* Marco Gruteser XueGang Ban*
Gruteser, Marco
VTL Zone-Aware Path Cloaking Algorithm Bin Zan Peng Hao* Marco Gruteser XueGang Ban* WINLAB conditions but do not achieve both. In this paper, we propose a virtual trip line zone-aware path cloaking the intersections of interest and the path cloaking algorithm uses entropy-estimates to decide whether the data can
PathOpt--a global transition state search approach: outline of algorithm.
Grebner, Christoph; Pason, Lukas P; Engels, Bernd
2013-08-01
We propose a new algorithm to determine reaction paths and test its capability for Ar12 and Ar13 clusters. Its main ingredient is a search for the local minima on a (n-1) dimensional hyperplane (n = dimension of the complete system in Cartesian coordinates) lying perpendicular to the straight line connection between initial and final states. These minima are part of possible reaction paths and are, hence, used as starting points for an uphill search to the next transition state. First, path fragments are obtained from subsequent relaxations starting from these transition states. They can be combined with information from the straight line connection procedure to obtain complete paths. Our test computations for Ar12 and Ar13 clusters prove that PathOpt delivers several reaction paths in one round. PMID:23649966
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, ...
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.
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.
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 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.
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.
An Energy-Efficient Algorithm For Conflict-Free AGV Routing On A Linear Path Layout
Zeng, Jianyang "Michael"
1 An Energy-Efficient Algorithm For Conflict-Free AGV Routing On A Linear Path Layout ZENG Jian time and the AGV utilization in dispatching and routing. However, as energy shortage and pollution to environment become major concerns and the competition become more intense, the issue of minimizing the energy
Approximation Algorithms for Disjoint st-Paths with Minimum Activation Cost
Erlebach, Thomas
Approximation Algorithms for Disjoint st-Paths with Minimum Activation Cost Hasna Mohsen Alqahtani.erlebach}@leicester.ac.uk Abstract. In network activation problems we are given a directed or undirected graph G = (V, E) with a family {fuv (xu, xv) : (u, v) E} of monotone non-decreasing activation functions from D2 to {0, 1
Bandwidth Scheduling and Path Computation Algorithms for Connection-Oriented Networks
Sahni, Sartaj K.
, and Bellman-Ford algorithms. We describe a bandwidth management system for UltraScience Net that incorporates are currently underway to develop such capabilities. They include User Controlled Light Paths (UCLP) [19], Ultra management, (e) database management, (f) bandwidth scheduler, and (g) signaling daemon. Based on the network
Robbiano, Lorenzo
Assessing path-following performance for Unmanned Marine Vehicles with algorithms from Numerical on the definition of a new criterion for evaluating the capability of an Unmanned Surface Vehicle (USV) to follow is the definition of standards and rules to be applied to unmanned vehicles (like USVs) in civilian scenarios
AN EVOLUTION BASED PATH PLANNING ALGORITHM FOR AUTONOMOUS MOTION OF A UAV THROUGH UNCERTAIN
1 AN EVOLUTION BASED PATH PLANNING ALGORITHM FOR AUTONOMOUS MOTION OF A UAV THROUGH UNCERTAIN planning is a required part of a fully autonomous UAV. In controlled airspace, such a UAV would have of an unmanned air vehicle (UAV) through a field of obstacles at uncertain locations. We begin with the static
Evolutionary algorithm based offline/online path planner for UAV navigation.
Nikolos, I K; Valavanis, K P; Tsourveloudis, N C; Kostaras, A N
2003-01-01
An evolutionary algorithm based framework, a combination of modified breeder genetic algorithms incorporating characteristics of classic genetic algorithms, is utilized to design an offline/online path planner for unmanned aerial vehicles (UAVs) autonomous navigation. The path planner calculates a curved path line with desired characteristics in a three-dimensional (3-D) rough terrain environment, represented using B-spline curves, with the coordinates of its control points being the evolutionary algorithm artificial chromosome genes. Given a 3-D rough environment and assuming flight envelope restrictions, two problems are solved: i) UAV navigation using an offline planner in a known environment, and, ii) UAV navigation using an online planner in a completely unknown environment. The offline planner produces a single B-Spline curve that connects the starting and target points with a predefined initial direction. The online planner, based on the offline one, is given on-board radar readings which gradually produces a smooth 3-D trajectory aiming at reaching a predetermined target in an unknown environment; the produced trajectory consists of smaller B-spline curves smoothly connected with each other. Both planners have been tested under different scenarios, and they have been proven effective in guiding an UAV to its final destination, providing near-optimal curved paths quickly and efficiently. PMID:18238242
Ferguson, Thomas S.
A Practical Path-planning Algorithm for a Vehicle with a Constrained Turning Radius: a Hamilton of optimal path planning of a forward moving simple car with a minimum turning radius (a Dubins' car Planning Traditionally, combinatorial methods based on path ge- ometry have been the primary tools
On-line reentry guidance algorithm with both path and no-fly zone constraints
NASA Astrophysics Data System (ADS)
Zhang, Da; Liu, Lei; Wang, Yongji
2015-12-01
This study proposes an on-line predictor-corrector reentry guidance algorithm that satisfies path and no-fly zone constraints for hypersonic vehicles with a high lift-to-drag ratio. The proposed guidance algorithm can generate a feasible trajectory at each guidance cycle during the entry flight. In the longitudinal profile, numerical predictor-corrector approaches are used to predict the flight capability from current flight states to expected terminal states and to generate an on-line reference drag acceleration profile. The path constraints on heat rate, aerodynamic load, and dynamic pressure are implemented as a part of the predictor-corrector algorithm. A tracking control law is then designed to track the reference drag acceleration profile. In the lateral profile, a novel guidance algorithm is presented. The velocity azimuth angle error threshold and artificial potential field method are used to reduce heading error and to avoid the no-fly zone. Simulated results for nominal and dispersed cases show that the proposed guidance algorithm not only can avoid the no-fly zone but can also steer a typical entry vehicle along a feasible 3D trajectory that satisfies both terminal and path constraints.
AUTONOMOUS ROBOT NAVIGATION USING A GENETIC ALGORITHM WITH AN EFFICIENT GENOTYPE ADITIA HERMANU
Wainwright, Roger L.
1 AUTONOMOUS ROBOT NAVIGATION USING A GENETIC ALGORITHM WITH AN EFFICIENT GENOTYPE STRUCTURE ADITIA & Computer Sciences Tulsa, Oklahoma ABSTRACT The goal for real-time mobile robots is to travel the shortest robots to plan this path without the need for human intervention. The path- planning problem has been
[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
A path planning algorithm for lane-following-based autonomous mobile robot navigation
NASA Astrophysics Data System (ADS)
Aljeroudi, Yazan; Paulik, Mark; Krishnan, Mohan; Luo, Chaomin
2010-01-01
In this paper we address the problem of autonomous robot navigation in a "roadway" type environment, where the robot has to drive forward on a defined path that could be impeded by the presence of obstacles. The specific context is the Autonomous Challenge of the Intelligent Ground Vehicle Competition (www.igvc.org). The task of the path planner is to ensure that the robot follows the path without turning back, as can happen in switchbacks, and/or leaving the course, as can happen in dashed or single lane line situations. A multi-behavior path planning algorithm is proposed. The first behavior determines a goal using a center of gravity (CoG) computation from the results of image processing techniques designed to extract lane lines. The second behavior is based on developing a sense of the current "general direction" of the contours of the course. This is gauged based on the immediate path history of the robot. An adaptive-weight-based fusion of the two behaviors is used to generate the best overall direction. This multi-behavior path planning strategy has been evaluated successfully in a Player/Stage simulation environment and subsequently implemented in the 2009 IGVC. The details of our experience will be presented at the conference.
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).
From Planning to Searching for the Shortest Plan
Kreinovich, Vladik
with applying A bN=2c ; if this algorithm A bN=2c finds a plan, we then try A bN=4c , otherwise, we apply A b3NFrom Planning to Searching for the Shortest Plan: An Optimal Transition R. Trejo, J. Galloway C frtrejo,vladikg@cs.utep.edu Abstract If we want to find the shortest plan, then usually, we try plans
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.
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.
NASA Astrophysics Data System (ADS)
Zhang, Jie; Lv, Chunhui; Zhao, Yongli; Chen, Bowen; Li, Xin; Huang, Shanguo; Gu, Wanyi
2012-12-01
In this paper, to decrease the traffic loss caused by multiple link failures, we consider the correlated risk among different connection requests when both the primary and backup paths are routed and assigned spectrum. Therefore, a novel shared-path protection algorithm is developed, named shared-path protection algorithm with correlated risk (SPP_CR), in flexible bandwidth optical networks. Based on the correlated risk, the routing can be diverse and the sharing in backup spectral resource will be restricted by SPP_CR algorithm, then the dropped traffic caused by simultaneous multiple failures between primary and backup path can be efficiently decreased. Simulation results show that, SPP_CR algorithm (i) achieves the higher successful service ratio (SSR) than traditional shared-path protection (SPP), shared-path protection with dynamic load balancing (SPP_DLB) and dedicated path protection (DPP); (ii) makes a better tradeoff in blocking probability, protection ratio (PR), average frequency slots consumed (AFSC) and redundancy ratio (RR) than SPP, SPP_DLB and DPP algorithms.
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.
Path planning strategies for autonomous ground vehicles
NASA Astrophysics Data System (ADS)
Gifford, Kevin Kent
Several key issues involved with the planning and executing of optimally generated paths for autonomous vehicles are addressed. Two new path planning algorithms are developed, and examined, which effectively minimize replanning as unmapped hazards are encountered. The individual algorithms are compared via extensive simulation. The search strategy results are implemented and tested using the University of Colorado's autonomous vehicle test-bed, RoboCar, and results show the advantages of solving the single-destination all-paths problem for autonomous vehicle path planning. Both path planners implement a graph search methodology incorporating dynamic programming that solves the single-destination shortest-paths problem. Algorithm 1, termed DP for dynamic programming, searches a state space where each state represents a potential vehicle location in a breadth-first fashion expanding from the goal to all potential start locations in the state space. Algorithm 2, termed DP*, couples the heuristic search power of the well-known A* search procedure (Nilsson-80) with the dynamic programming principle applied to graph searching to efficiently make use of overlapping subproblems. DP* is the primary research contribution of the work contained within this thesis. The advantage of solving the single-destination shortest-paths problem is that the entire terrain map is solved in terms of reaching a specified goal. Therefore, if the robot is diverted from the pre-planned path, an alternative path is already computed. The search algorithms are extended to include a probabilistic approach using empirical loss functions to incorporate terrain map uncertainties into the path considering terrain planning process. The results show the importance of considering terrain uncertainty. If the map representation ignores uncertainty by marking any area with less than perfect confidence as unpassable or assigns it the worst case rating, then the paths are longer than intuitively necessary. A hierarchical software control architecture is introduced that uses as the main guidance function an arbitration-based scheme which is able to efficiently and robustly integrate disparate sensor data. The flexibility provided by such an architecture allows for very easy integration of any type of environmental sensing device into the path planning algorithm.
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.
Gao, Ming-ke; Chen, Yi-min; Liu, Quan; Huang, Chen; Li, Ze-yu; Zhang, Dian-hua
2015-11-01
Preoperative path planning plays a critical role in vascular access surgery. Vascular access surgery has superior difficulties and requires long training periods as well as precise operation. Yet doctors are on different leves, thus bulky size of blood vessels is usually chosen to undergo surgery and other possible optimal path is not considered. Moreover, patients and surgeons will suffer from X-ray radiation during the surgical procedure. The study proposed an improved ant colony algorithm to plan a vascular optimal three-dimensional path with overall consideration of factors such as catheter diameter, vascular length, diameter as well as the curvature and torsion. To protect the doctor and patient from exposing to X-ray long-term, the paper adopted augmented reality technology to register the reconstructed vascular model and physical model meanwhile, locate catheter by the electromagnetic tracking system and used Head Mounted Display to show the planning path in real time and monitor catheter push procedure. The experiment manifests reasonableness of preoperative path planning and proves the reliability of the algorithm. The augmented reality experiment real time and accurately displays the vascular phantom model, planning path and the catheter trajectory and proves the feasibility of this method. The paper presented a useful and feasible surgical scheme which was based on the improved ant colony algorithm to plan vascular three-dimensional path in augmented reality. The study possessed practical guiding significance in preoperative path planning, intraoperative catheter guiding and surgical training, which provided a theoretical method of path planning for vascular access surgery. It was a safe and reliable path planning approach and possessed practical reference value. PMID:26319273
Li, Bai; Gong, Li-gang; Yang, Wen-lun
2014-01-01
Unmanned combat aerial vehicles (UCAVs) have been of great interest to military organizations throughout the world due to their outstanding capabilities to operate in dangerous or hazardous environments. UCAV path planning aims to obtain an optimal flight route with the threats and constraints in the combat field well considered. In this work, a novel artificial bee colony (ABC) algorithm improved by a balance-evolution strategy (BES) is applied in this optimization scheme. In this new algorithm, convergence information during the iteration is fully utilized to manipulate the exploration/exploitation accuracy and to pursue a balance between local exploitation and global exploration capabilities. Simulation results confirm that BE-ABC algorithm is more competent for the UCAV path planning scheme than the conventional ABC algorithm and two other state-of-the-art modified ABC algorithms. PMID:24790555
Herráez, Miguel Arevallilo; Burton, David R; Lalor, Michael J; Gdeisat, Munther A
2002-12-10
We describe what is to our knowledge a novel technique for phase unwrapping. Several algorithms based on unwrapping the most-reliable pixels first have been proposed. These were restricted to continuous paths and were subject to difficulties in defining a starting pixel. The technique described here uses a different type of reliability function and does not follow a continuous path to perform the unwrapping operation. The technique is explained in detail and illustrated with a number of examples. PMID:12502301
A 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.
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.
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.
An Approximation Algorithm for Optimizing Multiple Path Tracking Queries over Sensor Data Streams
NASA Astrophysics Data System (ADS)
Fan, Yao-Chung; Chen, Arbee L. P.
Sensor networks have received considerable attention in recent years and played an important role in data collection applications. Sensor nodes have limited supply of energy. Therefore, one of the major design considerations for sensor applications is to reduce the power consumption. In this paper, we study an application that combines RFID and sensor network technologies to provide an environment for moving object path tracking, which needs efficient join processing. This paper considers multi-query optimization to reduce query evaluation cost, and therefore power consumption. We formulate the multi-query optimization problem and present a novel approximation algorithm which provides solutions with suboptimal guarantees. In addition, extensive experiments are made to demonstrate the performance of the proposed optimization strategy.
NASA Astrophysics Data System (ADS)
Vamo?, C?lin; Cr?ciun, Maria; Suciu, Nicolae
2015-10-01
Fractional Brownian motion (fBm) is a nonstationary self-similar continuous stochastic process used to model many natural phenomena. A realization of the fBm can be numerically approximated by discrete paths which do not entirely preserve the self-similarity. We investigate the self-similarity at different time scales by decomposing the discrete paths of fBm into intrinsic components. The decomposition is realized by an automatic numerical algorithm based on successive smoothings stopped when the maximum monotonic variation of the averaged time series is reached. The spectral properties of the intrinsic components are analyzed through the monotony spectrum defined as the graph of the amplitudes of the monotonic segments with respect to their lengths (characteristic times). We show that, at intermediate time scales, the mean amplitude of the intrinsic components of discrete fBms scales with the mean characteristic time as a power law identical to that of the corresponding continuous fBm. As an application we consider hydrological time series of the transverse component of the transport process generated as a superposition of diffusive movements on advective transport in random velocity fields. We found that the transverse component has a rich structure of scales, which is not revealed by the analysis of the global variance, and that its intrinsic components may be self-similar only in particular cases.
Bowen, J.; Dozier, G.
1996-12-31
This paper introduces a hybrid evolutionary hill-climbing algorithm that quickly solves (Constraint Satisfaction Problems (CSPs)). This hybrid uses opportunistic arc and path revision in an interleaved fashion to reduce the size of the search space and to realize when to quit if a CSP is based on an inconsistent constraint network. This hybrid outperforms a well known hill-climbing algorithm, the Iterative Descent Method, on a test suite of 750 randomly generated CSPs.
Research on optimal path planning algorithm of task-oriented optical remote sensing satellites
NASA Astrophysics Data System (ADS)
Liu, Yunhe; Xu, Shengli; Liu, Fengjing; Yuan, Jingpeng
2015-08-01
GEO task-oriented optical remote sensing satellite, is very suitable for long-term continuous monitoring and quick access to imaging. With the development of high resolution optical payload technology and satellite attitude control technology, GEO optical remote sensing satellites will become an important developing trend for aerospace remote sensing satellite in the near future. In the paper, we focused on GEO optical remote sensing satellite plane array stare imaging characteristics and real-time leading mission of earth observation mode, targeted on satisfying needs of the user with the minimum cost of maneuver, and put forward the optimal path planning algorithm centered on transformation from geographic coordinate space to Field of plane, and finally reduced the burden of the control system. In this algorithm, bounded irregular closed area on the ground would be transformed based on coordinate transformation relations in to the reference plane for field of the satellite payload, and then using the branch and bound method to search for feasible solutions, cutting off the non-feasible solution in the solution space based on pruning strategy; and finally trimming some suboptimal feasible solutions based on the optimization index until a feasible solution for the global optimum. Simulation and visualization presentation software testing results verified the feasibility and effectiveness of the strategy.
Dorfer, Matthias; Kazmar, Tomáš; Šmíd, Mat?j; Sing, Sanchit; Kneißl, Julia; Keller, Simone; Debeir, Olivier; Luber, Birgit; Mattes, Julian
2016-01-01
In this paper we address the problem of recovering spatio-temporal trajectories of cancer cells in phase contrast video-microscopy where the user provides the paths on which the cells are moving. The paths are purely spatial, without temporal information. To recover the temporal information associated to a given path we propose an approach based on automatic cell detection and on a graph-based shortest path search. The nodes in the graph consist of the projections of the cell detections onto the geometrical cell path. The edges relate nodes which correspond to different frames of the sequence and potentially to the same cell and trajectory. In this directed graph we search for the shortest path and use it to define a temporal parametrization of the corresponding geometrical cell path. An evaluation based on 286 paths of 7 phase contrast microscopy videos shows that our algorithm allows to recover 92% of trajectory points with respect to the associated ground truth. We compare our method with a state-of-the-art algorithm for semi-automated cell tracking in phase contrast microscopy which requires interactively placed starting points for the cells to track. The comparison shows that supporting geometrical paths in combination with our algorithm allow us to obtain more reliable cell trajectories. PMID:25987193
Ingram, Mary Ann
-averaged Harmonic Path (SHAPA) algorithm for estimation of heart rate (HR) and respiration rate (RR) with Impulse beat induces fundamental frequencies and their harmonics at the respiration and heart rates. IR's heart rate (HR) and respiration rate (RR) continuously is important as it can lead to identification
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.
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.
Shortest recurrence periods of novae
Kato, Mariko; Saio, Hideyuki; Hachisu, Izumi; Nomoto, Ken'ichi
2014-10-01
Stimulated by the recent discovery of the 1 yr recurrence period nova M31N 2008-12a, we examined the shortest recurrence periods of hydrogen shell flashes on mass-accreting white dwarfs (WDs). We discuss the mechanism that yields a finite minimum recurrence period for a given WD mass. Calculating the unstable flashes for various WD masses and mass accretion rates, we identified a shortest recurrence period of about two months for a non-rotating 1.38 M {sub ?} WD with a mass accretion rate of 3.6 × 10{sup –7} M {sub ?} yr{sup –1}. A 1 yr recurrence period is realized for very massive (? 1.3 M {sub ?}) WDs with very high accretion rates (? 1.5 × 10{sup –7} M {sub ?} yr{sup –1}). We revised our stability limit of hydrogen shell burning, which will be useful for binary evolution calculations toward Type Ia supernovae.
NASA Astrophysics Data System (ADS)
Phanthong, Thanapong; Maki, Toshihiro; Ura, Tamaki; Sakamaki, Takashi; Aiyarak, Pattara
2014-03-01
This paper describes path re-planning techniques and underwater obstacle avoidance for unmanned surface vehicle (USV) based on multi-beam forward looking sonar (FLS). Near-optimal paths in static and dynamic environments with underwater obstacles are computed using a numerical solution procedure based on an A* algorithm. The USV is modeled with a circular shape in 2 degrees of freedom (surge and yaw). In this paper, two-dimensional (2-D) underwater obstacle avoidance and the robust real-time path re-planning technique for actual USV using multi-beam FLS are developed. Our real-time path re-planning algorithm has been tested to regenerate the optimal path for several updated frames in the field of view of the sonar with a proper update frequency of the FLS. The performance of the proposed method was verified through simulations, and sea experiments. For simulations, the USV model can avoid both a single stationary obstacle, multiple stationary obstacles and moving obstacles with the near-optimal trajectory that are performed both in the vehicle and the world reference frame. For sea experiments, the proposed method for an underwater obstacle avoidance system is implemented with a USV test platform. The actual USV is automatically controlled and succeeded in its real-time avoidance against the stationary undersea obstacle in the field of view of the FLS together with the Global Positioning System (GPS) of the USV.
Rowley, Christopher N; Woo, Tom K
2009-12-21
Transition path sampling has been established as a powerful tool for studying the dynamics of rare events. The trajectory generation moves of this Monte Carlo procedure, shooting moves and shifting modes, were developed primarily for rate constant calculations, although this method has been more extensively used to study the dynamics of reactive processes. We have devised and implemented three alternative trajectory generation moves for use with transition path sampling. The centering-shooting move incorporates a shifting move into a shooting move, which centers the transition period in the middle of the trajectory, eliminating the need for shifting moves and generating an ensemble where the transition event consistently occurs near the middle of the trajectory. We have also developed varied-perturbation size shooting moves, wherein smaller perturbations are made if the shooting point is far from the transition event. The trajectories generated using these moves decorrelate significantly faster than with conventional, constant sized perturbations. This results in an increase in the statistical efficiency by a factor of 2.5-5 when compared to the conventional shooting algorithm. On the other hand, the new algorithm breaks detailed balance and introduces a small bias in the transition time distribution. We have developed a modification of this varied-perturbation size shooting algorithm that preserves detailed balance, albeit at the cost of decreased sampling efficiency. Both varied-perturbation size shooting algorithms are found to have improved sampling efficiency when compared to the original constant perturbation size shooting algorithm. PMID:20025309
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.
Solving the Shortest Vector Problem in Lattices Faster Using Quantum Search
Thijs Laarhoven; Michele Mosca; Joop van de Pol
2013-01-25
By applying Grover's quantum search algorithm to the lattice algorithms of Micciancio and Voulgaris, Nguyen and Vidick, Wang et al., and Pujol and Stehl\\'{e}, we obtain improved asymptotic quantum results for solving the shortest vector problem. With quantum computers we can provably find a shortest vector in time $2^{1.799n + o(n)}$, improving upon the classical time complexity of $2^{2.465n + o(n)}$ of Pujol and Stehl\\'{e} and the $2^{2n + o(n)}$ of Micciancio and Voulgaris, while heuristically we expect to find a shortest vector in time $2^{0.312n + o(n)}$, improving upon the classical time complexity of $2^{0.384n + o(n)}$ of Wang et al. These quantum complexities will be an important guide for the selection of parameters for post-quantum cryptosystems based on the hardness of the shortest vector problem.
Research on Taxiway Path Optimization Based on Conflict Detection
Zhou, Hang; Jiang, Xinxin
2015-01-01
Taxiway path planning is one of the effective measures to make full use of the airport resources, and the optimized paths can ensure the safety of the aircraft during the sliding process. In this paper, the taxiway path planning based on conflict detection is considered. Specific steps are shown as follows: firstly, make an improvement on A * algorithm, the conflict detection strategy is added to search for the shortest and safe path in the static taxiway network. Then, according to the sliding speed of aircraft, a time table for each node is determined and the safety interval is treated as the constraint to judge whether there is a conflict or not. The intelligent initial path planning model is established based on the results. Finally, make an example in an airport simulation environment, detect and relieve the conflict to ensure the safety. The results indicate that the model established in this paper is effective and feasible. Meanwhile, make comparison with the improved A*algorithm and other intelligent algorithms, conclude that the improved A*algorithm has great advantages. It could not only optimize taxiway path, but also ensure the safety of the sliding process and improve the operational efficiency. PMID:26226485
Path Planning with obstacle avoidance
NASA Technical Reports Server (NTRS)
Krause, Donald M.
1987-01-01
The research report here summarizes a solution for two dimensional Path Planning with obstacle avoidance in a workspace with stationary obstacles. The solution finds the shortest path for the end effector of a manipulator arm. The program uses an overhead image of the robot work space and the starting and ending positions of the manipulator arm end effector to generate a search graph which is used to find the shortest path through the work area. The solution was originally implemented in VAX Pascal, but was later converted to VAX C.
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 ...
NASA Astrophysics Data System (ADS)
Chen, Jun; Luo, Chaomin; Krishnan, Mohan; Paulik, Mark; Tang, Yipeng
2010-01-01
An enhanced dynamic Delaunay Triangulation-based (DT) path planning approach is proposed for mobile robots to plan and navigate a path successfully in the context of the Autonomous Challenge of the Intelligent Ground Vehicle Competition (www.igvc.org). The Autonomous Challenge course requires the application of vision techniques since it involves path-based navigation in the presence of a tightly clustered obstacle field. Course artifacts such as switchbacks, ramps, dashed lane lines, trap etc. are present which could turn the robot around or cause it to exit the lane. The main contribution of this work is a navigation scheme based on dynamic Delaunay Triangulation (DDT) that is heuristically enhanced on the basis of a sense of general lane direction. The latter is computed through a "GPS (Global Positioning System) tail" vector obtained from the immediate path history of the robot. Using processed data from a LADAR, camera, compass and GPS unit, a composite local map containing both obstacles and lane line segments is built up and Delaunay Triangulation is continuously run to plan a path. This path is heuristically corrected, when necessary, by taking into account the "GPS tail" . With the enhancement of the Delaunay Triangulation by using the "GPS tail", goal selection is successfully achieved in a majority of situations. The robot appears to follow a very stable path while navigating through switchbacks and dashed lane line situations. The proposed enhanced path planning and GPS tail technique has been successfully demonstrated in a Player/Stage simulation environment. In addition, tests on an actual course are very promising and reveal the potential for stable forward navigation.
Hammock-on-Ears Decomposition: A Technique for the E cient Parallel Solution of Shortest
Waldmann, Uwe
Hammock-on-Ears Decomposition: A Technique for the E cient Parallel Solution of Shortest Paths the sequential hammock decomposition technique intro- duced by G. Frederickson and the parallel ear decomposition technique, thus we call it the hammock-on-ears decomposition. We mention that hammock-on-ears decomposi
Sun, Quanping; Chen, Xiaogang; Chen, Qianliang; Dai, Ning; Liao, Wenhe; He, Ning
2009-10-01
Molar crown is very small and has not only thin-wall, but also complex profile, especially, the occlusal surface of each molar crown has many cusps, ridges and fossae being differently distributed. When conventional processing method is used, it is impossible to machine molar prosthesis rapidly and exactly. To enhance machining velocity and improve the surface precision of molar crown, an algorithm of entity rapid offset-based STL format is put forward. By the application of Zigzag toolpath planning and micro-machining cutter, the finishing toolpaths for high speed milling molar prosthesis are generated. In terms of Mikron UCP800 high-speed machine center, the molar all-crown made of alloy aluminum material is successfully machined. The test results show that the algorithm of tool-path generation works fast, the number of toolpaths is small, and the cutter feeds smoothly. PMID:19947500
Information Spread of Emergency Events: Path Searching on Social Networks
Hu, Hongzhi; Wu, Tunan
2014-01-01
Emergency has attracted global attentions of government and the public, and it will easily trigger a series of serious social problems if it is not supervised effectively in the dissemination process. In the Internet world, people communicate with each other and form various virtual communities based on social networks, which lead to a complex and fast information spread pattern of emergency events. This paper collects Internet data based on data acquisition and topic detection technology, analyzes the process of information spread on social networks, describes the diffusions and impacts of that information from the perspective of random graph, and finally seeks the key paths through an improved IBF algorithm. Application cases have shown that this algorithm can search the shortest spread paths efficiently, which may help us to guide and control the information dissemination of emergency events on early warning. PMID:24600323
Approximation Algorithms and Heuristics for a 2-depot, Heterogeneous Hamiltonian Path Problem
Doshi, Riddhi Rajeev
2011-10-21
Various civil and military applications of UAVs, or ground robots, require a set of vehicles to monitor a group of targets. Routing problems naturally arise in this setting where the operators of the vehicles have to plan the paths suitably in order...
Shortest Path Computation with No Information Leakage Kyriakos Mouratidis
Yiu, Man Lung
Systems Singapore Management University kyriakos@smu.edu.sg Man Lung Yiu Department of Computing Hong Kong PIR techniques, which we treat as black-box building blocks. Experiments on real, large-scale road
Fast shortest path distance estimation in large networks
, they require as much as 250 times less space than the current approach in the literature which considers, or instant messaging systems nowadays count hundreds of millions of users that are active on a daily basis others protein interaction networks in biology and route computation in transportation. Recently, new
An EnergyEfficient Algorithm For ConflictFree AGV Routing On A Linear Path Layout
Zeng, Jianyang "Michael"
time and the AGV utilization in dispatching and routing. However, as energy shortage and pollution for short) and the car park are distributed on the side of one lane. The algorithms proposed in [67] can
Efficient algorithms for semiclassical instanton calculations based on discretized path integrals
Kawatsu, Tsutomu E-mail: smiura@mail.kanazawa-u.ac.jp; Miura, Shinichi E-mail: smiura@mail.kanazawa-u.ac.jp
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.
Methodology for Augmenting Existing Paths with Additional Parallel Transects
Wilson, John E.
2013-09-30
Visual Sample Plan (VSP) is sample planning software that is used, among other purposes, to plan transect sampling paths to detect areas that were potentially used for munition training. This module was developed for application on a large site where existing roads and trails were to be used as primary sampling paths. Gap areas between these primary paths needed to found and covered with parallel transect paths. These gap areas represent areas on the site that are more than a specified distance from a primary path. These added parallel paths needed to optionally be connected together into a single path—the shortest path possible. The paths also needed to optionally be attached to existing primary paths, again with the shortest possible path. Finally, the process must be repeatable and predictable so that the same inputs (primary paths, specified distance, and path options) will result in the same set of new paths every time. This methodology was developed to meet those specifications.
Xie, Xian Ming; Zeng, Qing Ning
2015-11-01
This paper presents an efficient and robust phase unwrapping algorithm which combines an unscented Kalman filter (UKF) with a strategy of quantizing a paths-guided map and a pixel classification strategy based on phase quality information. The advantages of the proposed method depend on the following contributions: (1) the strategy of quantizing the paths-guided map can accelerate the process of searching unwrapping paths and greatly reducing time consumption on the unwrapping procedure; (2) the pixel classification strategy proposed by this paper can reduce the error propagation effect by decreasing the amounts of pixels with equal quantized paths-guided value in the process of unwrapping; and (3) the unscented Kalman filter enables simultaneous filtering and unwrapping without the information loss caused by linearization of a nonlinear model. In addition, a new paths-guided map derived from a phase quality map is inserted into the strategy of quantizing the paths-guided map to provide a more robust path of unwrapping, and then ensures better unwrapping results. Results obtained from synthetic data and real data show that the proposed method can efficiently obtain better solutions with respect to some of the most used algorithms. PMID:26560585
Optimization of the mean radius flow path of a multi-stage steam turbine with evolution algorithms
NASA Astrophysics Data System (ADS)
Huttunen, Jukka; Larjola, Jaakko; Turunen-Saaresti, Teemu; Backman, Jari
2011-08-01
A prototype model of the mean radius flow path of a four-stage, high speed 1 MWe axial steam turbine was optimized by using evolution algorithms, DE (differential evolution) algorithm in this case. Also the cost-benefits of the optimization were inspected. The optimization was successfully performed but the accuracy of the optimization was slightly less than hoped when compared to the control modeling executed with the CFD (computational fluid dynamics). The mentioned inaccuracy could have been hardly avoided because of problems with an initial presumption involving semi-empiric calculations and of the uncertainty concerning the absolute areas of qualification of the functions. This kind of algebraic modeling was essential for the success of the optimization because e.g. CFD-calculation could not have been done on each step of the optimization. During the optimization some problems occurred with the adequacy of the computer capacity and with finding a suitable solution that would keep the algorithms within mathematically allowable boundaries but would not restrict the progress of the optimization too much. The rest of the problems were due to the novelty of the application and problems with preciseness when handling the areas of qualification of the functions. Although the accuracy of the optimization results was not exactly in accordance with the objective, they did have a favorable effect on the designing of the turbine. The optimization executed with the help of the DE-algorithm got at least about 3.5 % more power out of the turbine which means about 150 000 € cost-benefit per turbine in the form of additional electricity capacity.
NRMRL-RTP-P- 568 Childers, J.W., Phillips, W.J., Thompson*, E.L., Harris*, D.B., Kirchgessner*, D.A., Natschke, D.F., and Clayton, M.J. Comparison of an Innovative Nonlinear Algorithm to Classical Least Squares for Analyzing Open-Path Fourier Transform Infrared Spectra Collecte...
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 ...
Algorithm Engineering: Concepts and Practice
NASA Astrophysics Data System (ADS)
Chimani, Markus; Klein, Karsten
Over the last years the term algorithm engineering has become wide spread synonym for experimental evaluation in the context of algorithm development. Yet it implies even more. We discuss the major weaknesses of traditional "pen and paper" algorithmics and the ever-growing gap between theory and practice in the context of modern computer hardware and real-world problem instances. We present the key ideas and concepts of the central algorithm engineering cycle that is based on a full feedback loop: It starts with the design of the algorithm, followed by the analysis, implementation, and experimental evaluation. The results of the latter can then be reused for modifications to the algorithmic design, stronger or input-specific theoretic performance guarantees, etc. We describe the individual steps of the cycle, explaining the rationale behind them and giving examples of how to conduct these steps thoughtfully. Thereby we give an introduction to current algorithmic key issues like I/O-efficient or parallel algorithms, succinct data structures, hardware-aware implementations, and others. We conclude with two especially insightful success stories—shortest path problems and text search—where the application of algorithm engineering techniques led to tremendous performance improvements compared with previous state-of-the-art approaches.
Efficient Algorithms and Data Structures for Massive Data Sets
NASA Astrophysics Data System (ADS)
Alka
2010-05-01
For many algorithmic problems, traditional algorithms that optimise on the number of instructions executed prove expensive on I/Os. Novel and very different design techniques, when applied to these problems, can produce algorithms that are I/O efficient. This thesis adds to the growing chorus of such results. The computational models we use are the external memory model and the W-Stream model. On the external memory model, we obtain the following results. (1) An I/O efficient algorithm for computing minimum spanning trees of graphs that improves on the performance of the best known algorithm. (2) The first external memory version of soft heap, an approximate meldable priority queue. (3) Hard heap, the first meldable external memory priority queue that matches the amortised I/O performance of the known external memory priority queues, while allowing a meld operation at the same amortised cost. (4) I/O efficient exact, approximate and randomised algorithms for the minimum cut problem, which has not been explored before on the external memory model. (5) Some lower and upper bounds on I/Os for interval graphs. On the W-Stream model, we obtain the following results. (1) Algorithms for various tree problems and list ranking that match the performance of the best known algorithms and are easier to implement than them. (2) Pass efficient algorithms for sorting, and the maximal independent set problems, that improve on the best known algorithms. (3) Pass efficient algorithms for the graphs problems of finding vertex-colouring, approximate single source shortest paths, maximal matching, and approximate weighted vertex cover. (4) Lower bounds on passes for list ranking and maximal matching. We propose two variants of the W-Stream model, and design algorithms for the maximal independent set, vertex-colouring, and planar graph single source shortest paths problems on those models.
NASA Technical Reports Server (NTRS)
Hueschen, Richard M.
1988-01-01
This report contains results of flight tests for three path update algorithms designed to provide smooth transition for an aircraft guidance system from DME, VORTAC, and barometric navaids to the more precise MLS by modifying the desired 3-D flight path. The first algorithm, called Zero Cross Track, eliminates the discontinuity in cross-track and altitude error at transition by designating the first valid MLS aircraft position as the desired first waypoint, while retaining all subsequent waypoints. The discontinuity in track angle is left unaltered. The second, called Tangent Path, also eliminates the discontinuity in cross-track and altitude errors and chooses a new desired heading to be tangent to the next oncoming circular arc turn. The third, called Continued Track, eliminates the discontinuity in cross-track, altitude, and track angle errors by accepting the current MLS position and track angle as the desired ones and recomputes the location of the next waypoint. The flight tests were conducted on the Transportation Systems Research Vehicle, a small twin-jet transport aircraft modified for research under the Advanced Transport Operating Systems program at Langley Research Center. The flight tests showed that the algorithms provided a smooth transition to MLS.
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.
Link prediction based on path entropy
Xu, Zhongqi; Yang, Jian
2015-01-01
Information theory has been taken as a prospective tool for quantifying the complexity of complex networks. In this paper, we first study the information entropy or uncertainty of a path using the information theory. Then we apply the path entropy to the link prediction problem in real-world networks. Specifically, we propose a new similarity index, namely Path Entropy (PE) index, which considers the information entropies of shortest paths between node pairs with penalization to long paths. Empirical experiments demonstrate that PE index outperforms the mainstream link predictors.
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 ...
Lee, Chankyun; Cao, Xiaoyuan; Yoshikane, Noboru; Tsuritani, Takehiro; Rhee, June-Koo Kevin
2015-10-19
The feasibility of software-defined optical networking (SDON) for a practical application critically depends on scalability of centralized control performance. The paper, highly scalable routing and wavelength assignment (RWA) algorithms are investigated on an OpenFlow-based SDON testbed for proof-of-concept demonstration. Efficient RWA algorithms are proposed to achieve high performance in achieving network capacity with reduced computation cost, which is a significant attribute in a scalable centralized-control SDON. The proposed heuristic RWA algorithms differ in the orders of request processes and in the procedures of routing table updates. Combined in a shortest-path-based routing algorithm, a hottest-request-first processing policy that considers demand intensity and end-to-end distance information offers both the highest throughput of networks and acceptable computation scalability. We further investigate trade-off relationship between network throughput and computation complexity in routing table update procedure by a simulation study. PMID:26480397
Mobile transporter path planning
NASA Technical Reports Server (NTRS)
Baffes, Paul; Wang, Lui
1990-01-01
The use of a genetic algorithm (GA) for solving the mobile transporter path planning problem is investigated. The mobile transporter is a traveling robotic vehicle proposed for the space station which must be able to reach any point of the structure autonomously. Elements of the genetic algorithm are explored in both a theoretical and experimental sense. Specifically, double crossover, greedy crossover, and tournament selection techniques are examined. Additionally, the use of local optimization techniques working in concert with the GA are also explored. Recent developments in genetic algorithm theory are shown to be particularly effective in a path planning problem domain, though problem areas can be cited which require more research.
Efficient mapping algorithms for survivable GMPLS networks
NASA Astrophysics Data System (ADS)
Laborczi, Peter
2003-10-01
With the advent of intelligent IP over optical networks, like GMPLS, connections can be protected against failures effectively; however, to capitalize the advantages, novel sophisticated methods are needed. This paper addresses the task of finding efficient mapping in a survivable multilayer network in order to ensure high availability for connections. Known methods (like running a shortest path algorithm) do not consider finding physically disjoint paths in the upper layer and thus cause failure propagation. Besides formulating the problem, we propose a randomized heuristic method to solve it. The quality of the solution is evaluated (1) by the number of node-pairs for which physically-disjoint path-pair can be found in the upper layer, or (2) by the number of spans used by both working and protection paths (i.e., failure propagation effect). It is shown with numerous simulations that our proposed method finds solution for significantly more node pairs (86% instead of 45% in the 35-node network) than traditional methods. Furthermore, it yields connection availabilities near to the optimum.
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
Algorithmic Strategies in Combinatorial Chemistry
GOLDMAN,DEBORAH; ISTRAIL,SORIN; LANCIA,GIUSEPPE; PICCOLBONI,ANTONIO; WALENZ,BRIAN
2000-08-01
Combinatorial Chemistry is a powerful new technology in drug design and molecular recognition. It is a wet-laboratory methodology aimed at ``massively parallel'' screening of chemical compounds for the discovery of compounds that have a certain biological activity. The power of the method comes from the interaction between experimental design and computational modeling. Principles of ``rational'' drug design are used in the construction of combinatorial libraries to speed up the discovery of lead compounds with the desired biological activity. This paper presents algorithms, software development and computational complexity analysis for problems arising in the design of combinatorial libraries for drug discovery. The authors provide exact polynomial time algorithms and intractability results for several Inverse Problems-formulated as (chemical) graph reconstruction problems-related to the design of combinatorial libraries. These are the first rigorous algorithmic results in the literature. The authors also present results provided by the combinatorial chemistry software package OCOTILLO for combinatorial peptide design using real data libraries. The package provides exact solutions for general inverse problems based on shortest-path topological indices. The results are superior both in accuracy and computing time to the best software reports published in the literature. For 5-peptoid design, the computation is rigorously reduced to an exhaustive search of about 2% of the search space; the exact solutions are found in a few minutes.
MAS 05 Informative Path Planning MAS 05.1 Overview
Soatto, Stefano
MAS 05 Informative Path Planning MAS 05.1 Overview My goal is to create path planning algorithms that robots provide, it is necessary to come up with a path planning algorithm that can choose paths which gather the most useful information. Over the past year, I have focused primarily on path planning
PATH PLANNING FOR NONHOLONOMIC VEHICLES AND ITS APPLICATION TO RADIATION ENVIRONMENTS
Florida, University of
PATH PLANNING FOR NONHOLONOMIC VEHICLES AND ITS APPLICATION TO RADIATION ENVIRONMENTS By ARFATH ..................................................................2 Path Planning Algorithms.............................................................................................3 Offline Path Planning for Car-Like Vehicles
Algorithms for Constrained Route Planning in Road Networks
Rice, Michael Norris
2013-01-01
I Foundations Chapter 1 Introduction Route planning in roadI xiii Foundations 1 Introduction 1.1 Route Planning withRoute Planning with Detour Constraints 5 Generalized Shortest Paths 5.1 Introduction . . . . . . . . . . . . . . . . . . .
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.
Computing the Length of the Shortest Telomere in the Nucleus
NASA Astrophysics Data System (ADS)
Dao Duc, K.; Holcman, D.
2013-11-01
The telomere length can either be shortened or elongated by an enzyme called telomerase after each cell division. Interestingly, the shortest telomere is involved in controlling the ability of a cell to divide. Yet, its dynamics remains elusive. We present here a stochastic approach where we model this dynamics using a Markov jump process. We solve the forward Fokker-Planck equation to obtain the steady state distribution and the statistical moments of telomere lengths. We focus specifically on the shortest one and we estimate its length difference with the second shortest telomere. After extracting key parameters such as elongation and shortening dynamics from experimental data, we compute the length of telomeres in yeast and obtain as a possible prediction the minimum concentration of telomerase required to ensure a proper cell division.
10 Metric Path Planning Chapter objectives
Sukthankar, Gita Reese
10 Metric Path Planning Chapter objectives: Define Cspace, path relaxation, digitization bias, and create a graph suitable for path planning. Apply the A* search algorithm to a graph to find the optimal between continuous and event-driven replanning. 10.1 Objectives and Overview Metric path planning
Advisory Algorithm for Scheduling Open Sectors, Operating Positions, and Workstations
NASA Technical Reports Server (NTRS)
Bloem, Michael; Drew, Michael; Lai, Chok Fung; Bilimoria, Karl D.
2012-01-01
Air traffic controller supervisors configure available sector, operating position, and work-station resources to safely and efficiently control air traffic in a region of airspace. In this paper, an algorithm for assisting supervisors with this task is described and demonstrated on two sample problem instances. The algorithm produces configuration schedule advisories that minimize a cost. The cost is a weighted sum of two competing costs: one penalizing mismatches between configurations and predicted air traffic demand and another penalizing the effort associated with changing configurations. The problem considered by the algorithm is a shortest path problem that is solved with a dynamic programming value iteration algorithm. The cost function contains numerous parameters. Default values for most of these are suggested based on descriptions of air traffic control procedures and subject-matter expert feedback. The parameter determining the relative importance of the two competing costs is tuned by comparing historical configurations with corresponding algorithm advisories. Two sample problem instances for which appropriate configuration advisories are obvious were designed to illustrate characteristics of the algorithm. Results demonstrate how the algorithm suggests advisories that appropriately utilize changes in airspace configurations and changes in the number of operating positions allocated to each open sector. The results also demonstrate how the advisories suggest appropriate times for configuration changes.
Sampling diffusive transition paths
F. Miller III, Thomas; Predescu, Cristian
2006-10-12
We address the problem of sampling double-ended diffusive paths. The ensemble of paths is expressed using a symmetric version of the Onsager-Machlup formula, which only requires evaluation of the force field and which, upon direct time discretization, gives rise to a symmetric integrator that is accurate to second order. Efficiently sampling this ensemble requires avoiding the well-known stiffness problem associated with sampling infinitesimal Brownian increments of the path, as well as a different type of stiffness associated with sampling the coarse features of long paths. The fine-features sampling stiffness is eliminated with the use of the fast sampling algorithm (FSA), and the coarse-feature sampling stiffness is avoided by introducing the sliding and sampling (S&S) algorithm. A key feature of the S&S algorithm is that it enables massively parallel computers to sample diffusive trajectories that are long in time. We use the algorithm to sample the transition path ensemble for the structural interconversion of the 38-atom Lennard-Jones cluster at low temperature.
Energy Science and Technology Software Center (ESTSC)
2014-01-07
PathFinder is a graph search program, traversing a directed cyclic graph to find pathways between labeled nodes. Searches for paths through ordered sequences of labels are termed signatures. Determining the presence of signatures within one or more graphs is the primary function of Path Finder. Path Finder can work in either batch mode or interactively with an analyst. Results are limited to Path Finder whether or not a given signature is present in the graph(s).
Genome comparison without alignment using shortest unique substrings
Haubold, Bernhard; Pierstorff, Nora; Möller, Friedrich; Wiehe, Thomas
2005-01-01
Background Sequence comparison by alignment is a fundamental tool of molecular biology. In this paper we show how a number of sequence comparison tasks, including the detection of unique genomic regions, can be accomplished efficiently without an alignment step. Our procedure for nucleotide sequence comparison is based on shortest unique substrings. These are substrings which occur only once within the sequence or set of sequences analysed and which cannot be further reduced in length without losing the property of uniqueness. Such substrings can be detected using generalized suffix trees. Results We find that the shortest unique substrings in Caenorhabditis elegans, human and mouse are no longer than 11 bp in the autosomes of these organisms. In mouse and human these unique substrings are significantly clustered in upstream regions of known genes. Moreover, the probability of finding such short unique substrings in the genomes of human or mouse by chance is extremely small. We derive an analytical expression for the null distribution of shortest unique substrings, given the GC-content of the query sequences. Furthermore, we apply our method to rapidly detect unique genomic regions in the genome of Staphylococcus aureus strain MSSA476 compared to four other staphylococcal genomes. Conclusion We combine a method to rapidly search for shortest unique substrings in DNA sequences and a derivation of their null distribution. We show that unique regions in an arbitrary sample of genomes can be efficiently detected with this method. The corresponding programs shustring (SHortest Unique subSTRING) and shulen are written in C and available at . PMID:15910684
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, wavelet decomposition, path planning, collision avoidance, adjacency matrix, UAVs I. INTRODUCTION
NASA Technical Reports Server (NTRS)
Ng, Hok K.; Grabbe, Shon; Mukherjee, Avijit
2010-01-01
The optimization of traffic flows in congested airspace with varying convective weather is a challenging problem. One approach is to generate shortest routes between origins and destinations while meeting airspace capacity constraint in the presence of uncertainties, such as weather and airspace demand. This study focuses on development of an optimal flight path search algorithm that optimizes national airspace system throughput and efficiency in the presence of uncertainties. The algorithm is based on dynamic programming and utilizes the predicted probability that an aircraft will deviate around convective weather. It is shown that the running time of the algorithm increases linearly with the total number of links between all stages. The optimal routes minimize a combination of fuel cost and expected cost of route deviation due to convective weather. They are considered as alternatives to the set of coded departure routes which are predefined by FAA to reroute pre-departure flights around weather or air traffic constraints. A formula, which calculates predicted probability of deviation from a given flight path, is also derived. The predicted probability of deviation is calculated for all path candidates. Routes with the best probability are selected as optimal. The predicted probability of deviation serves as a computable measure of reliability in pre-departure rerouting. The algorithm can also be extended to automatically adjust its design parameters to satisfy the desired level of reliability.
NASA Technical Reports Server (NTRS)
Janich, Karl W.
2005-01-01
The At-Least version of the Generalized Minimum Spanning Tree Problem (L-GMST) is a problem in which the optimal solution connects all defined clusters of nodes in a given network at a minimum cost. The L-GMST is NPHard; therefore, metaheuristic algorithms have been used to find reasonable solutions to the problem as opposed to computationally feasible exact algorithms, which many believe do not exist for such a problem. One such metaheuristic uses a swarm-intelligent Ant Colony System (ACS) algorithm, in which agents converge on a solution through the weighing of local heuristics, such as the shortest available path and the number of agents that recently used a given path. However, in a network using a solution derived from the ACS algorithm, some nodes may move around to different clusters and cause small changes in the network makeup. Rerunning the algorithm from the start would be somewhat inefficient due to the significance of the changes, so a genetic algorithm based on the top few solutions found in the ACS algorithm is proposed to quickly and efficiently adapt the network to these small changes.
All-Optical Monitoring Path Computation Using Lower Bounds of Required Number of Paths
NASA Astrophysics Data System (ADS)
Ogino, Nagao; Nakamura, Hajime
To reduce the cost of fault management in all-optical networks, it is a promising approach to detect the degradation of optical signal quality solely at the terminal points of all-optical monitoring paths. The all-optical monitoring paths must be routed so that all single-link failures can be localized using route information of monitoring paths where signal quality degradation is detected. However, route computation for the all-optical monitoring paths that satisfy the above condition is time consuming. This paper proposes a procedure for deriving the lower bounds of the required number of monitoring paths to localize all single-link failures, and proposes an efficient monitoring path computation method based on the derived lower bounds. The proposed method repeats the route computation for the monitoring paths until feasible routes can be found, while the assumed number of monitoring paths increases, starting from the lower bounds. With the proposed method, the minimum number of monitoring paths with the overall shortest routes can be obtained quickly by solving several small-scale integer linear programming problems when the possible terminal nodes of monitoring paths are arbitrarily given. Thus, the proposed method can minimize the required number of monitors for detecting the degradation of signal quality and the total overhead traffic volume transferred through the monitoring paths.
On Distributed Time-Dependent Shortest Paths over Duty-Cycled Wireless Sensor Networks
Ravindran, Binoy
for all nodes. The performance of our solution is evaluated under diverse network configurations, a node periodically switches between active and sleep state. The period for one active/sleep switching, even though the physical propagation condition does not change with time. This raises a non
, Germany 2Center for Infrastructure, Sustainable Transportation and Urban Planning, Indian Institute. The multiagent model is generic in the sense that different public and individual transport agents. While planning, the agents consider both public and individual transportation options. · enhanced
Applied Probability Trust (12 May 2009) SCALING LIMITS FOR SHORTEST PATH LENGTHS ALONG
Schmidt, Volker
OF STATIONARY TESSELLATIONS FLORIAN VOSS, Ulm University CATHERINE GLOAGUEN, Orange Labs VOLKER SCHMIDT, Ulm: Orange Labs, 38-40, rue du GÂ´enÂ´eral Leclerc, 92794 Issy-les-Moulineaux, France 1 #12;2 F. Voss, C.g. an inner-city street system. Thus, we study a class of stochastic network models which has been introduced
A Parametric Copula Approach for Modelling Shortest-Path Trees in Telecommunication Networks
Schmidt, Volker
.neuhaeuser,christian.hirsch,volker.schmidt}@uni-ulm.de http://www.uni-ulm.de/mawi/mawi-stochastik 2 Orange Labs, 38-40 rue du General Leclerc, 92794 Issy engineers are mainly interested in minimising the total length of the telecommunication network in a city companies such as Orange Labs can draw conclusions about ca- pacity problems and cost estimation
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
Watanabe, Shin; Tero, Atsushi; Takamatsu, Atsuko; Nakagaki, Toshiyuki
2011-09-01
Traffic optimization of railroad networks was considered using an algorithm that was biologically inspired by an amoeba-like organism, plasmodium of the true slime mold, Physarum polycephalum. The organism developed a transportation network consisting of a tubular structure to transport protoplasm. It was reported that plasmodium can find the shortest path interconnecting multiple food sites during an adaptation process (Nakagaki et al., 2001. Biophys. Chem. 92, 47-52). By mimicking the adaptation process a path finding algorithm was developed by Tero et al. (2007). In this paper, the algorithm is newly modified for applications of traffic distribution optimization in transportation networks of infrastructure such as railroads under the constraint that the network topology is given. Application of the algorithm to a railroad in metropolitan Tokyo, Japan is demonstrated. The results are evaluated using three performance functions related to cost, traveling efficiency, and network weakness. The traffic distribution suggests that the modified Physarum algorithm balances the performances under a certain parameter range, indicating a biological process. PMID:21620930
Inter-Domain Redundancy Path Computation Methods Based on PCE
NASA Astrophysics Data System (ADS)
Hayashi, Rie; Oki, Eiji; Shiomoto, Kohei
This paper evaluates three inter-domain redundancy path computation methods based on PCE (Path Computation Element). Some inter-domain paths carry traffic that must be assured of high quality and high reliability transfer such as telephony over IP and premium virtual private networks (VPNs). It is, therefore, important to set inter-domain redundancy paths, i. e. primary and secondary paths. The first scheme utilizes an existing protocol and the basic PCE implementation. It does not need any extension or modification. In the second scheme, PCEs make a virtual shortest path tree (VSPT) considering the candidates of primary paths that have corresponding secondary paths. The goal is to reduce blocking probability; corresponding secondary paths may be found more often after a primary path is decided; no protocol extension is necessary. In the third scheme, PCEs make a VSPT considering all candidates of primary and secondary paths. Blocking probability is further decreased since all possible candidates are located, and the sum of primary and secondary path cost is reduced by choosing the pair with minimum cost among all path pairs. Numerical evaluations show that the second and third schemes offer only a few percent reduction in blocking probability and path pair total cost, while the overheads imposed by protocol revision and increase of the amount of calculation and information to be exchanged are large. This suggests that the first scheme, the most basic and simple one, is the best choice.
Multiresolution Path Planning Via Sector Decompositions
Tsiotras, Panagiotis
Multiresolution Path Planning Via Sector Decompositions Compatible to On-Board Sensor Data Efstathios Bakolas and Panagiotis Tsiotras In this paper we present a hybrid local-global path planning-free manner. The path planning algorithm is based on information gathered on-line by the available on
Energy Science and Technology Software Center (ESTSC)
2007-07-14
The PANL software determines path through an Adversary Sequence Diagram (ASD) with minimum Probability of Interruption, P(I), given the ASD information and data about site detection, delay, and response force times. To accomplish this, the software generates each path through the ASD, then applies the Estimate of Adversary Sequence Interruption (EASI) methodology for calculating P(I) to each path, and keeps track of the path with the lowest P(I). Primary use is for training purposes duringmore »courses on physical security design. During such courses PANL will be used to demonstrate to students how more complex software codes are used by the US Department of Energy to determine the most-vulnerable paths and, where security needs improvement, how such codes can help determine physical security upgrades.« less
Efficient algorithms for the computational design of optimal tiling arrays.
Schliep, Alexander; Krause, Roland
2008-01-01
The representation of a genome by oligonucleotide probes is a prerequisite for the analysis of many of its basic properties, such as transcription factor binding sites, chromosomal breakpoints, gene expression of known genes and detection of novel genes, in particular those coding for small RNAs. An ideal representation would consist of a high density set of oligonucleotides with similar melting temperatures that do not cross-hybridize with other regions of the genome and are equidistantly spaced. The implementation of such design is typically called a tiling array or genome array. We formulate the minimal cost tiling path problem for the selection of oligonucleotides from a set of candidates. Computing the selection of probes requires multi-criterion optimization, which we cast into a shortest path problem. Standard algorithms running in linear time allow us to compute globally optimal tiling paths from millions of candidate oligonucleotides on a standard desktop computer for most problem variants. The solutions to this multi-criterion optimization are spatially adaptive to the problem instance. Our formulation incorporates experimental constraints with respect to specific regions of interest and trade offs between hybridization parameters, probe quality and tiling density easily. A web application is available at http://tileomatic.org. PMID:18989043
Path planning under spatial uncertainty.
Wiener, Jan M; Lafon, Matthieu; Berthoz, Alain
2008-04-01
In this article, we present experiments studying path planning under spatial uncertainties. In the main experiment, the participants' task was to navigate the shortest possible path to find an object hidden in one of four places and to bring it to the final destination. The probability of finding the object (probability matrix) was different for each of the four places and varied between conditions. Givensuch uncertainties about the object's location, planning a single path is not sufficient. Participants had to generate multiple consecutive plans (metaplans)--for example: If the object is found in A, proceed to the destination; if the object is not found, proceed to B; and so on. The optimal solution depends on the specific probability matrix. In each condition, participants learned a different probability matrix and were then asked to report the optimal metaplan. Results demonstrate effective integration of the probabilistic information about the object's location during planning. We present a hierarchical planning scheme that could account for participants' behavior, as well as for systematic errors and differences between conditions. PMID:18491490
Open-path Fourier transform infrared (OP/FTIR) spectrometry was used to measure the concentrations of ammonia, methane, and other atmospheric gases at an integrated swine production facility. The concentration-pathlength products of the target gases at this site often exceeded th...
Szymanski, Boleslaw K.
nodes are battery operated. Many sensor network applications require thousands of sensor nodes which will be deployed in remote locations. This makes battery re- placement impractical. Therefore, energy conservation is that sensor nodes are prone to failure. Therefore, in order to extend the rout- ing phase, the employed paths
Hardness of Approximating the Shortest Vector Problem in High L p Norms
Khot, Subhash
Hardness of Approximating the Shortest Vector Problem in High L p Norms Subhash Khot email : khot integers p #21; p(#15;), it is NPÂhard to approximate the Shortest Vector Problem in L p norm within factor hardness shown by Micciancio [27]. 1 #12; 1 Introduction An nÂdimensional lattice L is a set of vectors f P
Approximating Cycles in a Shortest Basis of the First Homology Group from Point Data
Sun, Jian
Approximating Cycles in a Shortest Basis of the First Homology Group from Point Data Tamal K. Dey the rank of the homology groups from point data, but there is no result on approximating the shortest basis its point data is a funda- mental problem arising in many scientific studies and engineering
Pokemon Cards and the Shortest Common Superstring Mark Stamp Austin E Stamp
Stamp, Mark
PokÂ´emon Cards and the Shortest Common Superstring Mark Stamp Austin E Stamp June 12, 2003 Abstract Evidence is presented that certain sequences of PokÂ´emon cards are determined by selecting consecutive (SCS), i.e., the shortest string that contains each of the PokÂ´emon card sequences as a consecutive
Robot path planning with distance-safety criterion
NASA Technical Reports Server (NTRS)
Suh, Suk-Hwan; Shin, Kang G.
1987-01-01
A method for determining an optimal path with a weighted distance-safety criterion is developed. The goal is to strike a compromise between the shortest path and the centerline path, which is safer. The method is composed of three parts: (i) construction of a region map by dividing the workspace, (ii) interregion optimization to determine the entry and departure points of the path in each region, and (iii) intraregion optimization for determining the (optimal) path segment within each region. The region map is generated by using an approximate Voronoi diagram, and region optimization is achieved using variational dynamic programming. Although developed for 2-D problems, the method can be easily extended to a class of 3-D problems. Numerical examples are presented to demonstrate the method.
Heuristically Driven Front Propagation for Geodesic Paths Extraction
Frey, Pascal
tubular structures extraction in 3D medical images [1] to path finding in video games [2]. The ability to compute a lot of geodesic paths can gain benefits from our algorithm. The computa- tional saving is even
White Matter Tract Analysis in 454 Adults using Maximum Density Paths
Thompson, Paul
fuzzy clustering [18], normalized cuts [5], k-means [15], spectral clustering [16], Dirichlet, tractography, MRI, brain, clustering, atlas, Dijk- stra, shortest path, geodesic distance, Hough, connectivity to be clustered for analysis. A wealth of clustering methods have been applied to tractography results including
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.
Notes on Feynman path integral-like methods of quantization on Riemannian manifolds
Yoshihisa Miyanishi
2015-12-20
We propose an alternative method for Feynman path integrals on compact Riemannian manifolds. Our method employs action integrals along the shortest paths. In the case of rank 1 locally symmetric Riemannian manifolds, we prove the strong convergence of time slicing products of oscillatory integrals for low energy functions. Moreover, the strong limit includes Dewitt curvature $R/6$, where $R$ denotes the scalar curvature of a Riemannian manifold.
Minimum-Risk Path Finding by an Adaptive Amoebal Network
NASA Astrophysics Data System (ADS)
Nakagaki, Toshiyuki; Iima, Makoto; Ueda, Tetsuo; Nishiura, Yasumasa; Saigusa, Tetsu; Tero, Atsushi; Kobayashi, Ryo; Showalter, Kenneth
2007-08-01
When two food sources are presented to the slime mold Physarum in the dark, a thick tube for absorbing nutrients is formed that connects the food sources through the shortest route. When the light-avoiding organism is partially illuminated, however, the tube connecting the food sources follows a different route. Defining risk as the experimentally measurable rate of light-avoiding movement, the minimum-risk path is exhibited by the organism, determined by integrating along the path. A model for an adaptive-tube network is presented that is in good agreement with the experimental observations.
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.
Fritz, Sean
2015-01-01
In this study, an interplanetary space flight mission design is established to obtain the minimum \\(\\Delta V\\) required for a rendezvous and sample return mission from an asteroid. Given the initial (observed) conditions of an asteroid, a (robust) genetic algorithm is implemented to determine the optimal choice of \\(\\Delta V\\) required for the rendezvous. Robustness of the optimum solution is demonstrated through incorporated bounded-uncertainties in the outbound \\(\\Delta V\\) maneuver via genetic fitness function. The improved algorithm results in a solution with improved robustness and reduced sensitivity to propulsive errors in the outbound maneuver. This is achieved over a solution optimized solely on \\(\\Delta V\\), while keeping the increase in \\(\\Delta V\\) to a minimum, as desired. Outcomes of the analysis provide significant results in terms of improved robustness in asteroid rendezvous missions.
Path planning by querying persistent stores of trajectory segments
NASA Technical Reports Server (NTRS)
Grossman, Robert L.; Mehta, S.; Qin, Xiao
1993-01-01
We introduce an algorithm for path planning (long duration) paths of dynamical systems, given a persistent object store containing suitable collections of short duration trajectory segments. We also describe experimental results from a proof-of-concept implementation of the algorithm. The basic idea is to interpret a path planning algorithm as a suitable query on a persistent object store consisting of short duration trajectory segments. The query returns a concatenation of short duration trajectory segments which is close to the desired path. The needed short duration segments are computed by using a divide and conquer algorithm to break up the original path into shorter paths; each shorter path is then matched to a nearby trajectory segment which is part of the persistent object store by using a suitable index function.
A novel approach of global path planning for UGV
NASA Astrophysics Data System (ADS)
Choe, TokSon; Park, YongWoon; Kim, Jun; Kang, Sin Cheon; Jee, Tae Young; Ryu, Chul-Hyung
2006-05-01
Global path planning (GPP) is the generation of an optimal trajectory to efficiently move from one position to specified target position with known environment. Most of GPP methodologies offer an optimal 2D-shortest path without considering vehicle parameters on the plain environments. However, it is motivated to consider 3D terrain and vehicle parameters to enhance traversability on the rough terrain. In this paper, we propose a novel approach of GPP method for unmanned ground vehicles (UGVs) by applying distance transform (3D to 2D) based on the slope of terrain. In addition, the generated path is modified by smoothing process based on the local path planning method which considers vehicle stability on the specified candidate curve and speed. The proposed methodology is tested by simulations and shows enhanced performance.
NASA Technical Reports Server (NTRS)
Mcroberts, Malcolm
1990-01-01
Viewgraphs on path planning control are presented. Topics covered include: model based path planning; sensor based path planning; hybrid path planning; proximity sensor array; and applications for fuzzy logic.
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
A Comparison of Three Algorithms for Approximating the Distance Distribution in Real-World Graphs
NASA Astrophysics Data System (ADS)
Crescenzi, Pierluigi; Grossi, Roberto; Lanzi, Leonardo; Marino, Andrea
The distance for a pair of vertices in a graph G is the length of the shortest path between them. The distance distribution for G specifies how many vertex pairs are at distance h, for all feasible values h. We study three fast randomized algorithms to approximate the distance distribution in large graphs. The Eppstein-Wang (ew) algorithm exploits sampling through a limited (logarithmic) number of Breadth-First Searches (bfses). The Size-Estimation Framework (sef) by Cohen employs random ranking and least-element lists to provide several estimators. Finally, the Approximate Neighborhood Function (anf) algorithm by Palmer, Gibbons, and Faloutsos makes use of the probabilistic counting technique introduced by Flajolet and Martin, in order to estimate the number of distinct elements in a large multiset. We investigate how good is the approximation of the distance distribution, when the three algorithms are run in similar settings. The analysis of anf derives from the results on the probabilistic counting method, while the one of sef is given by Cohen. For what concerns ew (originally designed for another problem), we extend its simple analysis in order to bound its error with high probability and to show its convergence. We then perform an experimental study on 30 real-world graphs, showing that our implementation of ew combines the accuracy of sef with the performance of anf.
Fast surface-based travel depth estimation algorithm for macromolecule surface shape description.
Giard, Joachim; Alface, Patrice Rondao; Gala, Jean-Luc; Macq, Benoît
2011-01-01
Travel Depth, introduced by Coleman and Sharp in 2006, is a physical interpretation of molecular depth, a term frequently used to describe the shape of a molecular active site or binding site. Travel Depth can be seen as the physical distance a solvent molecule would have to travel from a point of the surface, i.e., the Solvent-Excluded Surface (SES), to its convex hull. Existing algorithms providing an estimation of the Travel Depth are based on a regular sampling of the molecule volume and the use of the Dijkstra's shortest path algorithm. Since Travel Depth is only defined on the molecular surface, this volume-based approach is characterized by a large computational complexity due to the processing of unnecessary samples lying inside or outside the molecule. In this paper, we propose a surface-based approach that restricts the processing to data defined on the SES. This algorithm significantly reduces the complexity of Travel Depth estimation and makes possible the analysis of large macromolecule surface shape description with high resolution. Experimental results show that compared to existing methods, the proposed algorithm achieves accurate estimations with considerably reduced processing times. PMID:21071797
Approximation Algorithms for Lawn Mowing and Milling Esther M. Arkin
Arkin, Estie
it is permitted for the cutter to "mow" over non-grass regions (e.g., one may push the lawn mower over" problems: Given a region in the plane, and given the shape of a "cutter" (typically, a circle or a square), find a shortest tour/path for the cutter such that every point within the region is covered
The "Join the Club" Interpretation of Some Graph Algorithms
Reiter, Harold
to advances attained by the development of methods and models of graph theory. Computer scientists. Search- ing and sorting, finding shortest paths, constructing spanning trees with desirable properties call the root of the tree. We interpret V as the people living in a community. An edge between two
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.
Efficient Multi-Agent Path Planning Okan Arikan
Forsyth, David
Efficient Multi-Agent Path Planning Okan Arikan University of California at Berkeley Stephen the number of agents is large. In this paper, we introduce an efficient algorithm that creates path plans in significant speedups over running the accurate simulation for all agents. Keywords: path planning, virtual
Multiresolution Path Planning with Wavelets: A Local Replanning Approach
Tsiotras, Panagiotis
Multiresolution Path Planning with Wavelets: A Local Replanning Approach Raghvendra V. Cowlagi and Panagiotis Tsiotras Abstract-- A path planning algorithm based on multireso- lution cell decomposition approaches transform the path planning problem into a graph search problem. In particular, cell decomposition
Path planning by querying persistent stores of trajectory segments
Grossman, Robert
Path planning by querying persistent stores of trajectory segments R. L. Grossman S. Mehta X. Qin at Chicago, September, 1992. Introduction. In this paper, we introduce an algorithm for path planning (long duration) paths of a dynamical system, given a database, or store, contain- ing suitable collections
GRECS: Graph Encryption for Approximate Shortest Distance Queries
Kollios, George
. Other applications include encrypted graph databases and controlled disclosure systems. We propose GRECS Mathematics]: Graph Theory--graph algorithms; H.2.7 [DATABASE MANAGEMENT]: Database Administration encryption 1 Introduction Graph databases that store, manage, and query large graphs have received increased
Mining Preferred Traversal Paths with HITS
NASA Astrophysics Data System (ADS)
Yeh, Jieh-Shan; Lin, Ying-Lin; Chen, Yu-Cheng
Web usage mining can discover useful information hidden in web logs data. However, many previous algorithms do not consider the structure of web pages, but regard all web pages with the same importance. This paper utilizes HITS values and PNT preferences as measures to mine users' preferred traversal paths. Wë structure mining uses HITS (hypertext induced topic selection) to rank web pages. PNT (preferred navigation tree) is an algorithm that finds users' preferred navigation paths. This paper introduces the Preferred Navigation Tree with HITS (PNTH) algorithm, which is an extension of PNT. This algorithm uses the concept of PNT and takes into account the relationships among web pages using HITS algorithm. This algorithm is suitable for E-commerce applications such as improving web site design and web server performance.
Efficient algorithms for wildland fire simulation
NASA Astrophysics Data System (ADS)
Kondratenko, Volodymyr Y.
In this dissertation, we develop the multiple-source shortest path algorithms and examine their application importance in real world problems, such as wildfire modeling. The theoretical basis and its implementation in the Weather Research Forecasting (WRF) model coupled with the fire spread code SFIRE (WRF-SFIRE model) are described. We present a data assimilation method that gives the fire spread model the ability to start the fire simulation from an observed fire perimeter instead of an ignition point. While the model is running, the fire state in the model changes in accordance with the new arriving data by data assimilation. As the fire state changes, the atmospheric state (which is strongly effected by heat flux) does not stay consistent with the fire state. The main difficulty of this methodology occurs in coupled fire-atmosphere models, because once the fire state is modified to match a given starting perimeter, the atmospheric circulation is no longer in sync with it. One of the possible solutions to this problem is a formation of the artificial time of ignition history from an earlier fire state, which is later used to replay the fire progression to the new perimeter with the proper heat fluxes fed into the atmosphere, so that the fire induced circulation is established. In this work, we develop efficient algorithms that start from the fire arrival times given at the set of points (called a perimeter) and create the artificial fire time of ignition and fire spread rate history. Different algorithms were developed in order to suit possible demands of the user, such as implementation in parallel programming, minimization of the required amount of iterations and memory use, and use of the rate of spread as a time dependent variable. For the algorithms that deal with the homogeneous rate of spread, it was proven that the values of fire arrival times they produce are optimal. It was also shown that starting from arbitrary initial state the algorithms have finite convergence and the amount of iterations was estimated. Application of the method on real tests, based on the data taken from the observed fires, has shown the high accuracy of the algorithm and its usefulness. Besides wildfire modeling, this technique has a high application value in different fields, such as epidemiology, demographics control, flood modeling, etc.
Multi-objective stochastic path planning
Dasgupta, Sumantra
2009-05-15
Based: Edges are grown from the center of the search space to various directions until the whole search space is covered. e.g. Rapidly exploring Random Trees (RRT). Usually, when a graph is not given, the search space (for path planning) has...]. Many further extensions and novel point-based algorithms have been reported in [17]. Rapidly exploring Random Trees (RRT) [17] is a very well known tree based graph building algorithm. Further tree-based algorithms can be found in [17...
Evolutionary software for autonomous path planning
Couture, S; Hage, M
1999-02-10
This research project demonstrated the effectiveness of using evolutionary software techniques in the development of path-planning algorithms and control programs for mobile vehicles in radioactive environments. The goal was to take maximum advantage of the programmer's intelligence by tasking the programmer with encoding the measures of success for a path-planning algorithm, rather than developing the path-planning algorithms themselves. Evolutionary software development techniques could then be used to develop algorithms most suitable to the particular environments of interest. The measures of path-planning success were encoded in the form of a fitness function for an evolutionary software development engine. The task for the evolutionary software development engine was to evaluate the performance of individual algorithms, select the best performers for the population based on the fitness function, and breed them to evolve the next generation of algorithms. The process continued for a set number of generations or until the algorithm converged to an optimal solution. The task environment was the navigation of a rover from an initial location to a goal, then to a processing point, in an environment containing physical and radioactive obstacles. Genetic algorithms were developed for a variety of environmental configurations. Algorithms were simple and non-robust strings of behaviors, but they could be evolved to be nearly optimal for a given environment. In addition, a genetic program was evolved in the form of a control algorithm that operates at every motion of the robot. Programs were more complex than algorithms and less optimal in a given environment. However, after training in a variety of different environments, they were more robust and could perform acceptably in environments they were not trained in. This paper describes the evolutionary software development engine and the performance of algorithms and programs evolved by it for the chosen task.
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.
A generalized gradient algorithm for dynamic optimization
NASA Technical Reports Server (NTRS)
Zhao, Yiyuan; Bryson, A. E.; Slattery, R.
1989-01-01
A gradient algorithm is developed that determines optimal trajectories with path equality constraints and terminal constraints. A generalized gradient is formed which improves both the performance index and the path equality constraints simultaneously. The algorithm is extended to treat terminal constraints by using Bryson's impulse response technique. The main features of this algorithm are its numerical stability and smooth convergence near the optimum.
Robot navigation in unknown terrains: Introductory survey of non-heuristic algorithms
Rao, N.S.V.; Kareti, S.; Shi, Weimin; Iyengar, S.S.
1993-07-01
A formal framework for navigating a robot in a geometric terrain by an unknown set of obstacles is considered. Here the terrain model is not a priori known, but the robot is equipped with a sensor system (vision or touch) employed for the purpose of navigation. The focus is restricted to the non-heuristic algorithms which can be theoretically shown to be correct within a given framework of models for the robot, terrain and sensor system. These formulations, although abstract and simplified compared to real-life scenarios, provide foundations for practical systems by highlighting the underlying critical issues. First, the authors consider the algorithms that are shown to navigate correctly without much consideration given to the performance parameters such as distance traversed, etc. Second, they consider non-heuristic algorithms that guarantee bounds on the distance traversed or the ratio of the distance traversed to the shortest path length (computed if the terrain model is known). Then they consider the navigation of robots with very limited computational capabilities such as finite automata, etc.
Buldyrev, Sergey
of Physics, Bar-Ilan University, Ramat Gan, Israel 3 BP Exploration Operating Company Ltd., Sunbury away. For example, in oil recovery the rst passage time from the injection well to a production well
Learning to improve path planning performance
Chen, Pang C.
1995-04-01
In robotics, path planning refers to finding a short. collision-free path from an initial robot configuration to a desired configuratioin. It has to be fast to support real-time task-level 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 remedy this situation, we present and analyze a learning algorithm that uses past experience to increase future performance. The algorithm relies on an existing path planner to provide solutions to difficult tasks. From these solutions, an evolving sparse network of useful robot configurations is learned to support faster planning. More generally, the algorithm provides a speedup-learning framework in which a slow but capable planner may be improved both cost-wise and capability-wise by a faster but less capable planner coupled with experience. The basic algorithm is suitable for stationary environments, and can be extended to accommodate changing environments with on-demand experience repair and object-attached experience abstraction. To analyze the algorithm, we characterize the situations in which the adaptive planner is useful, provide quantitative bounds to predict its behavior, and confirm our theoretical results with experiments in path planning of manipulators. Our algorithm and analysis are sufficiently, general that they may also be applied to other planning domains in which experience is useful.
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.
Coverage Path Planning for Marine Habitat Mapping Enric Galceran and Marc Carreras
Eustice, Ryan
Coverage Path Planning for Marine Habitat Mapping Enric Galceran and Marc Carreras Abstract- work combines two existing coverage path planning algorithms with new ideas to provide automated a survey path that covers the target area is needed. Today, AUV and ASV survey paths are typically planned
An Evolutionary Method for Active Learning of Mobile Robot Path Planning
An Evolutionary Method for Active Learning of Mobile Robot Path Planning Byoung-Tak Zhang Dept evolutionary algorithms have been proposed for robot path planning. Most existing methods for evolutionary path@cient enough for real-time applications. In this paper we present a new method for evolutionary path planning
Tsiotras, Panagiotis
Multi-resolution Path Planning: Theoretical Analysis, Efficient Implementation, and Extensions iterations more efficiently. Finally, we extend this path planning algorithm to dynamic environments, called the geometric path planning level, deals with obstacle avoidance by finding an obstacle-free path
Retaining PathSensitive Relations across ControlFlow Merges Douglas Gregor
Bystroff, Chris
Retaining PathSensitive Relations across ControlFlow Merges Douglas Gregor Dept. of Computer range merge operation that, unlike traditional value range merge operations, preserves arbitrary of the two paths will be merged into a single approximation of both paths. A pathsensitive algorithm
Zone-Based Shortest Positioning Time First Scheduling for MEMS-Based Storage Devices
California at Santa Cruz, University of
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
Vanquishing the XCB Question: The Methodological Discovery of the Last Shortest Single Axiom for the
Fitelson, Branden
1. History, Signi cance, and Terminology With the use of an e ective methodology, we answer the nalVanquishing the XCB Question: The Methodological Discovery of the Last Shortest Single Axiom. With the inclusion of an e ective methodology, this article answers in detail a question that, for a quarter
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...
Path planning using optically computed potential fields
NASA Technical Reports Server (NTRS)
Reid, Max B.
1993-01-01
An algorithm for the optical computation of potential field maps suitable for mobile robot navigation is described and experimentally produced maps and paths are presented. The parallel analog optical computation employs a two-dimensional spatial light modulator on which an image of the potential field map is generated. Optically calculated fields contain no local minima, tend to produce paths centered in gaps between obstacles, and produce paths which give preference to wide gaps. Calculation of 128 x 128 pixel fields at a few hertz are possible with current technology, and calculation time vs. map size scales favorably in comparison to digital electronic computation.
Path Coupling and Aggregate Path Coupling
Yevgeniy Kovchegov; Peter T. Otto
2015-01-13
In this survey paper, we describe and characterize an extension to the classical path coupling method applied statistical mechanical models, referred to as aggregate path coupling. In conjunction with large deviations estimates, we use this aggregate path coupling method to prove rapid mixing of Glauber dynamics for a large class of statistical mechanical models, including models that exhibit discontinuous phase transitions which have traditionally been more difficult to analyze rigorously. The parameter region for rapid mixing for the generalized Curie-Weiss-Potts model is derived as a new application of the aggregate path coupling method.
Path Coupling and Aggregate Path Coupling
Kovchegov, Yevgeniy
2015-01-01
In this survey paper, we describe and characterize an extension to the classical path coupling method applied statistical mechanical models, referred to as aggregate path coupling. In conjunction with large deviations estimates, we use this aggregate path coupling method to prove rapid mixing of Glauber dynamics for a large class of statistical mechanical models, including models that exhibit discontinuous phase transitions which have traditionally been more difficult to analyze rigorously. The parameter region for rapid mixing for the generalized Curie-Weiss-Potts model is derived as a new application of the aggregate path coupling method.
Vervet monkeys use paths consistent with context-specific spatial movement heuristics.
Teichroeb, Julie A
2015-10-01
Animal foraging routes are analogous to the computationally demanding "traveling salesman problem" (TSP), where individuals must find the shortest path among several locations before returning to the start. Humans approximate solutions to TSPs using simple heuristics or "rules of thumb," but our knowledge of how other animals solve multidestination routing problems is incomplete. Most nonhuman primate species have shown limited ability to route plan. However, captive vervets were shown to solve a TSP for six sites. These results were consistent with either planning three steps ahead or a risk-avoidance strategy. I investigated how wild vervet monkeys (Chlorocebus pygerythrus) solved a path problem with six, equally rewarding food sites; where site arrangement allowed assessment of whether vervets found the shortest route and/or used paths consistent with one of three simple heuristics to navigate. Single vervets took the shortest possible path in fewer than half of the trials, usually in ways consistent with the most efficient heuristic (the convex hull). When in competition, vervets' paths were consistent with different, more efficient heuristics dependent on their dominance rank (a cluster strategy for dominants and the nearest neighbor rule for subordinates). These results suggest that, like humans, vervets may solve multidestination routing problems by applying simple, adaptive, context-specific "rules of thumb." The heuristics that were consistent with vervet paths in this study are the same as some of those asserted to be used by humans. These spatial movement strategies may have common evolutionary roots and be part of a universal mental navigational toolkit. Alternatively, they may have emerged through convergent evolution as the optimal way to solve multidestination routing problems. PMID:26668734
Adaptive path planning for flexible manufacturing
Chen, Pang C.
1994-08-01
Path planning needs to be fast to facilitate real-time robot programming. Unfortunately, current planning techniques are still too slow to be effective, as they often require several minutes, if not hours of computation. To overcome this difficulty, we present an adaptive algorithm that uses past experience to speed up future performance. It is a learning algorithm suitable for automating flexible manufacturing in incrementally-changing environments. The algorithm allows the robot to adapt to its environment by having two experience manipulation schemes: For minor environmental change, we use an object-attached experience abstraction scheme to increase the flexibility of the learned experience; for major environmental change, we use an on-demand experience repair scheme to retain those experiences that remain valid and useful. Using this algorithm, we can effectively reduce the overall robot planning time by re-using the computation result for one task to plan a path for another.
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.
Energy Science and Technology Software Center (ESTSC)
2012-05-11
The ap command traveres all symlinks in a given file, directory, or executable name to identify the final absolute path. It can print just the final path, each intermediate link along with the symlink chan, and the permissions and ownership of each directory component in the final path. It has functionality similar to "which", except that it shows the final path instead of the first path. It is also similar to "pwd", but it canmore »provide the absolute path to a relative directory from the current working directory.« less
A global path planning approach for redundant manipulators
NASA Technical Reports Server (NTRS)
Seereeram, Sanjeev; Wen, J.
1993-01-01
A new approach for global path planning of redundant manipulators is proposed. It poses the path planning problem as a finite time nonlinear control problem. The solution is found by a Newton-Raphson type algorithm. This technique is capable of handling various goal task descriptions as well as incorporating both joint and task space constraints. The algorithm has shown promising preliminary results in planning joint path sequences for 3R and 4R planar robots to meet Cartesian tip tracking and goal endpoint planning. It is robust with respect to local path planning problems such as singularity considerations and local minimum problems. Repetitive joint path solutions for cyclic end-effector tasks are also generated. Eventual goals of this work include implementation on full spatial robots, as well as provision of an interface for supervisory input to aid in path planning for more complex problems.
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.
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.
Staff detection with stable paths.
Dos Santos Cardoso, Jaime; Capela, Artur; Rebelo, Ana; Guedes, Carlos; Pinto da Costa, Joaquim
2009-06-01
The preservation of musical works produced in the past requires their digitalization and transformation into a machine-readable format. The processing of handwritten musical scores by computers remains far from ideal. One of the fundamental stages to carry out this task is the staff line detection. We investigate a general-purpose, knowledge-free method for the automatic detection of music staff lines based on a stable path approach. Lines affected by curvature, discontinuities, and inclination are robustly detected. Experimental results show that the proposed technique consistently outperforms well-established algorithms. PMID:19372615
Asymptotically optimal path planning and surface reconstruction for inspection
Papadopoulos, Georgios
2014-01-01
Motivated by inspection applications for marine structures, this thesis develops algorithms to enable their autonomous inspection. Two essential parts of the inspection problem are (1) path planning and (2) surface ...
Path dependent receding horizon control policies for hybrid electric vehicles
Kolmanovsky, Ilya V.
Future hybrid electric vehicles (HEVs) may use path-dependent operating policies to improve fuel economy. In our previous work, we developed a dynamic programming (DP) algorithm for prescribing the battery state of charge ...
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.
2009-06-15
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.
Hot Big Planets Kepler Survey: Measuring the Repopulation Rate of the Shortest-Period Planets
Taylor, Stuart F
2013-01-01
By surveying new fields for the shortest-period "big" planets, the Kepler spacecraft could provide the statistics to more clearly measure the occurrence distributions of giant and medium planets. This would allow separate determinations for giant and medium planets of the relationship between the inward rate of tidal migration of planets and the strength of the stellar tidal dissipation (as expressed by the tidal quality factor Q). We propose a "Hot Big Planets Survey" to find new big planets to better determine the planet occurrence distribution at the shortest period. We call planets that Kepler will be able to find as "big", for the purpose of comparing the distribution of giant and medium planets (above and below 8 earth radii). The distribution of planets from one field has been interpreted to show that the shortest period giant planets are at the end of an ongoing flow of high eccentricity migration, likely from scattering from further out. The numbers of planets at these short periods is still small, l...
NC machine tool path generation from CSG part
Bobrow, James E.
NC machine tool path generation from CSG part representations James E Bobrow Recent improvements for machine tool path generation. Current machining algorithms require that any port geometric information modelling system is used. Thispaper presents o method for generating numerically-controlled milling machine
Path Profile Guided Partial Dead Code Elimination Using Predication \\Lambda
Gupta, Rajiv
Path Profile Guided Partial Dead Code Elimination Using Predication \\Lambda Rajiv Gupta y David A Corporation Pittsburgh, PA 15260 Santa Clara, CA 95052 Abstract We present a path profile guided partial dead code elimination algorithm that uses predication to enable sinking for the removal of deadness along
Vulnerability of complex networks under path-based attacks
NASA Astrophysics Data System (ADS)
Pu, Cun-Lai; Cui, Wei
2015-02-01
We investigate vulnerability of complex networks including model networks and real-world networks subject to path-based attacks. Specifically, we remove approximately the longest simple path from a network iteratively until there are no paths left in the network. We propose two algorithms, the random augmenting approach (RPA) and the Hamilton-path based approach (HPA), for finding the approximately longest simple path in a network. Results demonstrate that steps of longest-path attacks increase with network density linearly for random networks, while exponentially increasing for scale-free networks. The more homogeneous the degree distribution is, the more fragile the network, which is different from the previous results of node or edge attacks. HPA is generally more efficient than RPA in the longest-path attacks of complex networks. These findings further help us understand the vulnerability of complex systems, better protect complex systems, and design more tolerant complex systems.
Path matching and graph matching in biological networks.
Yang, Qingwu; Sze, Sing-Hoi
2007-01-01
We develop algorithms for the following path matching and graph matching problems: (i) given a query path p and a graph G, find a path p' that is most similar to p in G; (ii) given a query graph G (0) and a graph G, find a graph G (0)' that is most similar to G (0) in G. In these problems, p and G (0) represent a given substructure of interest to a biologist, and G represents a large network in which the biologist desires to find a related substructure. These algorithms allow the study of common substructures in biological networks in order to understand how these networks evolve both within and between organisms. We reduce the path matching problem to finding a longest weighted path in a directed acyclic graph and show that the problem of finding top k suboptimal paths can be solved in polynomial time. This is in contrast with most previous approaches that used exponential time algorithms to find simple paths which are practical only when the paths are short. We reduce the graph matching problem to finding highest scoring subgraphs in a graph and give an exact algorithm to solve the problem when the query graph G (0) is of moderate size. This eliminates the need for less accurate heuristic or randomized algorithms. We show that our algorithms are able to extract biologically meaningful pathways from protein interaction networks in the DIP database and metabolic networks in the KEGG database. Software programs implementing these techniques (PathMatch and GraphMatch) are available at http://faculty.cs.tamu.edu/shsze/pathmatch and http://faculty.cs.tamu.edu/shsze/graphmatch. PMID:17381346
Kambhampati, Subbarao
is discussed. I. INTRODUCTION THE PROBLEM of automatic collision-free path planning is central to mobile robot applications. Path planning for mobile robots is inmanyways different from the more familiarcase of path occlusionand reduction in the field of view. Conventional path-planning algorithms can be divided broadly
Attention trees and semantic paths
NASA Astrophysics Data System (ADS)
Giusti, Christian; Pieroni, Goffredo G.; Pieroni, Laura
2007-02-01
In the last few decades several techniques for image content extraction, often based on segmentation, have been proposed. It has been suggested that under the assumption of very general image content, segmentation becomes unstable and classification becomes unreliable. According to recent psychological theories, certain image regions attract the attention of human observers more than others and, generally, the image main meaning appears concentrated in those regions. Initially, regions attracting our attention are perceived as a whole and hypotheses on their content are formulated; successively the components of those regions are carefully analyzed and a more precise interpretation is reached. It is interesting to observe that an image decomposition process performed according to these psychological visual attention theories might present advantages with respect to a traditional segmentation approach. In this paper we propose an automatic procedure generating image decomposition based on the detection of visual attention regions. A new clustering algorithm taking advantage of the Delaunay- Voronoi diagrams for achieving the decomposition target is proposed. By applying that algorithm recursively, starting from the whole image, a transformation of the image into a tree of related meaningful regions is obtained (Attention Tree). Successively, a semantic interpretation of the leaf nodes is carried out by using a structure of Neural Networks (Neural Tree) assisted by a knowledge base (Ontology Net). Starting from leaf nodes, paths toward the root node across the Attention Tree are attempted. The task of the path consists in relating the semantics of each child-parent node pair and, consequently, in merging the corresponding image regions. The relationship detected in this way between two tree nodes generates, as a result, the extension of the interpreted image area through each step of the path. The construction of several Attention Trees has been performed and partial results will be shown.
Energy Science and Technology Software Center (ESTSC)
2013-07-29
The OpenEIS Algorithm package seeks to provide a low-risk path for building owners, service providers and managers to explore analytical methods for improving building control and operational efficiency. Users of this software can analyze building data, and learn how commercial implementations would provide long-term value. The code also serves as a reference implementation for developers who wish to adapt the algorithms for use in commercial tools or service offerings.
Christian Fleischhack
2015-03-21
The symmetries of paths in a manifold $M$ are classified with respect to a given pointwise proper action of a Lie group $G$ on $M$. Here, paths are embeddings of a compact interval into $M$. There are at least two types of symmetries: Firstly, paths that are parts of an integral curve of a fundamental vector field on $M$ (continuous symmetry). Secondly, paths that can be decomposed into finitely many pieces, each of which is the translate of some free segment, where possibly the translate is cut at the two ends of the paths (discrete symmetry). Here, a free segment is a path $e$ whose $G$-translates either equal $e$ or intersect it in at most finitely many points. Note that all the statements above are understood up to the parametrization of the paths. We will show, for the category of analytic manifolds, that each path is of exactly one of either types. For the proof, we use that the overlap of a path $\\gamma$ with one of its translates is encoded uniquely in a mapping between subsets of $\\dom\\gamma$. Running over all translates, these mappings form the so-called reparametrization set to $\\gamma$. It will turn out that, up to conjugation with a diffeomorphism, any such set is given by the action of a Lie subgroup of $O(2)$ on $S^1$, restricted in domain and range to some compact interval on $S^1$. Now, the infinite subgroups correspond to the continuous symmetry above, finite ones to the discrete symmetry.
Variational nature, integration, and properties of Newton reaction path.
Bofill, Josep Maria; Quapp, Wolfgang
2011-02-21
The distinguished coordinate path and the reduced gradient following path or its equivalent formulation, the Newton trajectory, are analyzed and unified using the theory of calculus of variations. It is shown that their minimum character is related to the fact that the curve is located in a valley region. In this case, we say that the Newton trajectory is a reaction path with the category of minimum energy path. In addition to these findings a Runge-Kutta-Fehlberg algorithm to integrate these curves is also proposed. PMID:21341822
Autonomous Path Tracking Using Recorded Orientation and Steering Commands
Hellström, Thomas
. Common algorithms, like Pure Pursuit and Fol- low the Carrot, compute steering commands that make- sults are compared with the Pure-Pursuit and the Follow-the-Carrot algorithms, and show a signifi- cant to the path and the error in orientation. Traditional algo- rithms, like Follow the Carrot (Barton, 2001
Longest jobs first algorithm in solving job shop scheduling using adaptive genetic algorithm (GA)
NASA Astrophysics Data System (ADS)
Alizadeh Sahzabi, Vahid; Karimi, Iman; Alizadeh Sahzabi, Navid; Mamaani Barnaghi, Peiman
2012-01-01
In this paper, genetic algorithm was used to solve job shop scheduling problems. One example discussed in JSSP (Job Shop Scheduling Problem) and I described how we can solve such these problems by genetic algorithm. The goal in JSSP is to gain the shortest process time. Furthermore I proposed a method to obtain best performance on performing all jobs in shortest time. The method mainly, is according to Genetic algorithm (GA) and crossing over between parents always follows the rule which the longest process is at the first in the job queue. In the other word chromosomes is suggested to sorts based on the longest processes to shortest i.e. "longest job first" says firstly look which machine contains most processing time during its performing all its jobs and that is the bottleneck. Secondly, start sort those jobs which are belonging to that specific machine descending. Based on the achieved results," longest jobs first" is the optimized status in job shop scheduling problems. In our results the accuracy would grow up to 94.7% for total processing time and the method improved 4% the accuracy of performing all jobs in the presented example.
Longest jobs first algorithm in solving job shop scheduling using adaptive genetic algorithm (GA)
NASA Astrophysics Data System (ADS)
Alizadeh Sahzabi, Vahid; Karimi, Iman; Alizadeh Sahzabi, Navid; Mamaani Barnaghi, Peiman
2011-12-01
In this paper, genetic algorithm was used to solve job shop scheduling problems. One example discussed in JSSP (Job Shop Scheduling Problem) and I described how we can solve such these problems by genetic algorithm. The goal in JSSP is to gain the shortest process time. Furthermore I proposed a method to obtain best performance on performing all jobs in shortest time. The method mainly, is according to Genetic algorithm (GA) and crossing over between parents always follows the rule which the longest process is at the first in the job queue. In the other word chromosomes is suggested to sorts based on the longest processes to shortest i.e. "longest job first" says firstly look which machine contains most processing time during its performing all its jobs and that is the bottleneck. Secondly, start sort those jobs which are belonging to that specific machine descending. Based on the achieved results," longest jobs first" is the optimized status in job shop scheduling problems. In our results the accuracy would grow up to 94.7% for total processing time and the method improved 4% the accuracy of performing all jobs in the presented example.
Calix[4]pyrroles with Shortest Possible Strap: Exclusively Selective toward Fluoride Ion.
Samanta, Ritwik; Kumar, B Sathish; Panda, Pradeepta K
2015-09-01
Four new calix[4]pyrroles with the shortest possible strap so far through ortho-linking of the aromatic unit have been synthesized, including a naphthalene-derived fluorescent receptor. They show exclusive selectivity toward the fluoride ion as confirmed by (1)H NMR, isothermal titration calorimetry, and fluorescence spectroscopic study. Anion affinity could also be modulated further via functionalization at the strap. Computational analysis displays calix[4]pyrroles binding to fluoride ion in a very unusual 1,3-alternate conformation where the anion resides on the opposite side of the strap. PMID:26313641
Choset, Howie
Probabilistic Path Planning for Multiple Robots with Subdimensional Expansion Glenn Wagner, Minsu) and Probabilistic Roadmaps (PRMs) are powerful path planning algorithms for high dimensional systems, but even of probabilistic planners for multirobot path planning. We accomplish this by exploiting the structure inherent
MODEN: Multi-Robot, Obstacle-Driven Elastic Network Path Planning Francisco S. Melo
Veloso, Manuela M.
MODEN: Multi-Robot, Obstacle-Driven Elastic Network Path Planning Francisco S. Melo Institute-- We propose an efficient and elegant heuristic al- gorithm for path planning that makes use, dubbed as ODEN (Obstacle-Driven Elastic Network), is an improved extension of the path-planning algorithm
Randomized Path Planning on Manifolds based on Higher-Dimensional Continuation
Porta, Josep M.
Randomized Path Planning on Manifolds based on Higher-Dimensional Continuation Josep M. Porta, L Abstract Despite the significant advances in path planning methods, highly constrained problems are still space manifold. In this paper, we present a new path planning algorithm specially tailored for highly
Smooth Path Planning of a Mobile Robot Using Stochastic Particle Swarm Optimization
Li, Yangmin
Smooth Path Planning of a Mobile Robot Using Stochastic Particle Swarm Optimization Xin Chen exploration ability is developed, so that a swarm with small size can accomplish path planning. Simulation results validate the proposed algorithm in a mobile robot path planning. I. INTRODUCTION Smooth navigation
On the Existence and Synthesis of Curvature-Bounded Paths Inside Nonuniform Rectangular Channels
Tsiotras, Panagiotis
in the case of a ground vehicle. from the higher level of planning, and second, constructing a feasible path used in path planning algorithms for vehicles with kinematic and dynamic constraints: first, en- suring to bridge the gap between the (high-level) geometric path planning and the (low-level) trajectory generation
Flight Testing a Real Time Implementation of a UAV Path Planner Using Direct Collocation
Flight Testing a Real Time Implementation of a UAV Path Planner Using Direct Collocation Brian R University, University Park, PA 16802 Flight tests of a path planning algorithm using direct collocation aerial vehicle for these tests. The method plans a path that maximizes the time a target is in view
Enzymatic reaction paths as determined by transition path sampling
NASA Astrophysics Data System (ADS)
Masterson, Jean Emily
Enzymes are biological catalysts capable of enhancing the rates of chemical reactions by many orders of magnitude as compared to solution chemistry. Since the catalytic power of enzymes routinely exceeds that of the best artificial catalysts available, there is much interest in understanding the complete nature of chemical barrier crossing in enzymatic reactions. Two specific questions pertaining to the source of enzymatic rate enhancements are investigated in this work. The first is the issue of how fast protein motions of an enzyme contribute to chemical barrier crossing. Our group has previously identified sub-picosecond protein motions, termed promoting vibrations (PVs), that dynamically modulate chemical transformation in several enzymes. In the case of human heart lactate dehydrogenase (hhLDH), prior studies have shown that a specific axis of residues undergoes a compressional fluctuation towards the active site, decreasing a hydride and a proton donor--acceptor distance on a sub-picosecond timescale to promote particle transfer. To more thoroughly understand the contribution of this dynamic motion to the enzymatic reaction coordinate of hhLDH, we conducted transition path sampling (TPS) using four versions of the enzymatic system: a wild type enzyme with natural isotopic abundance; a heavy enzyme where all the carbons, nitrogens, and non-exchangeable hydrogens were replaced with heavy isotopes; and two versions of the enzyme with mutations in the axis of PV residues. We generated four separate ensembles of reaction paths and analyzed each in terms of the reaction mechanism, time of barrier crossing, dynamics of the PV, and residues involved in the enzymatic reaction coordinate. We found that heavy isotopic substitution of hhLDH altered the sub-picosecond dynamics of the PV, changed the favored reaction mechanism, dramatically increased the time of barrier crossing, but did not have an effect on the specific residues involved in the PV. In the mutant systems, we observed changes in the reaction mechanism and altered contributions of the mutated residues to the enzymatic reaction coordinate, but we did not detect a substantial change in the time of barrier crossing. These results confirm the importance of maintaining the dynamics and structural scaffolding of the hhLDH PV in order to facilitate facile barrier passage. We also utilized TPS to investigate the possible role of fast protein dynamics in the enzymatic reaction coordinate of human dihydrofolate reductase (hsDHFR). We found that sub-picosecond dynamics of hsDHFR do contribute to the reaction coordinate, whereas this is not the case in the E. coli version of the enzyme. This result indicates a shift in the DHFR family to a more dynamic version of catalysis. The second inquiry we addressed in this thesis regarding enzymatic barrier passage concerns the variability of paths through reactive phase space for a given enzymatic reaction. We further investigated the hhLDH-catalyzed reaction using a high-perturbation TPS algorithm. Though we saw that alternate reaction paths were possible, the dominant reaction path we observed corresponded to that previously elucidated in prior hhLDH TPS studies. Since the additional reaction paths we observed were likely high-energy, these results indicate that only the dominant reaction path contributes significantly to the overall reaction rate. In conclusion, we show that the enzymes hhLDH and hsDHFR exhibit paths through reactive phase space where fast protein motions are involved in the enzymatic reaction coordinate and exhibit a non-negligible contribution to chemical barrier crossing.
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
A 2D analytical cylindrical gate tunnel FET (CG-TFET) model: impact of shortest tunneling distance
NASA Astrophysics Data System (ADS)
Dash, S.; Mishra, G. P.
2015-09-01
A 2D analytical tunnel field-effect transistor (FET) potential model with cylindrical gate (CG-TFET) based on the solution of Laplace’s equation is proposed. The band-to-band tunneling (BTBT) current is derived by the help of lateral electric field and the shortest tunneling distance. However, the analysis is extended to obtain the subthreshold swing (SS) and transfer characteristics of the device. The dependency of drain current, SS and transconductance on gate voltage and shortest tunneling distance is discussed. Also, the effect of scaling the gate oxide thickness and the cylindrical body diameter on the electrical parameters of the device is analyzed.
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.
ERIC Educational Resources Information Center
Stegemoller, William; Stegemoller, Rebecca
2004-01-01
The path taken and the turns made as a turtle traces a polygon are examined to discover an important theorem in geometry. A unique tool, the Angle Adder, is implemented in the investigation. (Contains 9 figures.)
ERIC Educational Resources Information Center
Spanier, Graham B.; Glick, Paul C.
1980-01-01
Presents a demographic analysis of the paths to remarriage--the extent and timing of remarriage, social factors associated with remarriage, and the impact of the event which preceded remarriage (divorce or widowhood). (Author)
A quantum algorithm for the dihedral hidden subgroup problem based on algorithm SV
Fada Li; Wansu Bao; Xiangqun Fu
2013-05-29
To accelerate the algorithms for the dihedral hidden subgroup problem, we present a new algorithm based on algorithm SV(shortest vector). A subroutine is given to get a transition quantum state by constructing a phase filter function, then the measurement basis are derived based on the technique for solving low density subset problem. Finally, the parity of slope is revealed by the measurements on the transition quantum state. This algorithm takes O(n) quantum space and O(n^2) classical space, which is superior to existing algorithms, for a relatively small n(n<6400),it takes (n^0.5)*(log(max aij))^3 computation time, which is superior to 2^(O(n^0.5)).
Optimal heuristic algorithms for the image of an injective function Edward A. Hirsch
Hirsch, Edward A.
to the existence of a p-optimal proof system (that is, a proof system that has the shortest possible proofs, and these proofs can be constructed by a polynomial-time algorithm given proofs in any other proof system) [KP89-4089.2010.1 from the President of RF, by the Programme of Fundamental Research of RAS, and by RFBR
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.
Finding Good Paths: Applications of Least Cost Caloric Path Computations
Wood, Zoë J.
Google Earth API to explore the use of least cost caloric path computations to create an interactive path for the creation of crowd path computations that consider the terrain as one factor in agent path computations. The second application builds on the popular Google Earth API to provide a tool for users to compute
TWINS: THE TWO SHORTEST PERIOD NON-INTERACTING DOUBLE DEGENERATE WHITE DWARF STARS
Mullally, F.; Badenes, Carles; Lupton, Robert; Thompson, Susan E.
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.
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.
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.
Adaptive robot path planning in changing environments
Chen, P.C.
1994-08-01
Path planning needs to be fast to facilitate real-time robot programming. Unfortunately, current planning techniques are still too slow to be effective, as they often require several minutes, if not hours of computation. To overcome this difficulty, we present an adaptive algorithm that uses past experience to speed up future performance. It is a learning algorithm suitable for incrementally-changing environments such as those encountered in manufacturing of evolving products and waste-site remediation. The algorithm allows the robot to adapt to its environment by having two experience manipulation schemes: For minor environmental change, we use an object-attached experience abstraction scheme to increase the flexibility of the learned experience; for major environmental change, we use an on-demand experience repair scheme to retain those experiences that remain valid and useful. Using this algorithm, we can effectively reduce the overall robot planning time by re-using the computation result for one task to plan a path for another.
Autonomous Ground Vehicle Path Tracking
Florida, University of
Autonomous Ground Vehicle Path Tracking Jeff Wit Wintec, Inc. 104 Research Road, Building 9738 vehicle navigation requires the integration of many technologies such as path planning, position of a nonholonomic ground vehicle as it tracks a given path. A new path tracking technique called ``vector pursuit
Stentz, Tony
and Efficient Path Planning for PartiallyKnown Environments Anthony Stentz The Robotics Institute; Carnegie an initial path based on known information and then modify the plan locally or replan the entire path respectively. This paper introduces a new algorithm, D*, capable of planning paths in unknown, partially known
Stentz, Tony
and Efficient Path Planning for Partially-Known Environments Anthony Stentz The Robotics Institute; Carnegie an initial path based on known information and then modify the plan locally or replan the entire path respectively. This paper introduces a new algorithm, D*, capable of planning paths in unknown, partially known
Path planning for machine vision assisted, teleoperated pavement crack sealer
Kim, Y.S.; Haas, C.T.; Greer, R.
1998-03-01
During the last few years, several teleoperated and machine-vision-assisted systems have been developed in construction and maintenance areas such as pavement crack sealing, sewer pipe rehabilitation, excavation, surface finishing, and materials handling. This paper presents a path-planning algorithm used for a machine-vision-assisted automatic pavement crack sealing system. In general, path planning is an important task for optimal motion of a robot whether its environment is structured or unstructured. Manual path planning is not always possible or desirable. A simple greedy path algorithm is utilized for optimal motion of the automated pavement crack sealer. Some unique and broadly applicable computational tools and data structures are required to implement the algorithm in a digital image domain. These components are described, then the performance of the algorithm is compared with the implicit manual path plans of system operators. The comparison is based on computational cost versus overall gains in crack-sealing-process efficiency. Applications of this work in teleoperation, graphical control, and other infrastructure maintenance areas are also suggested.
Obstacle-Aware Longest-Path Routing with Constraint Programming and Parallel MILP
NASA Astrophysics Data System (ADS)
Tseng, I.-Lun; Chen, Huan-Wen; Kao, Yung-Wei; Lee, Che-I.
2011-08-01
Longest-path routing problems, which can arise in the design of high-performance printed circuit boards (PCBs), have been proven to be NP-hard. In this article, we propose a constraint programming (CP) formulation and a mixed integer linear programming (MILP) formulation to gridded longest-path routing problems; each of which may contain obstacles. After a longest-path routing problem has been transformed into a CP problem, a CP solver can be used to find optimal solutions. On the other hand, parallel MILP solvers can be used to find optimal solutions after the longest-path routing problem has been transformed into an MILP problem. Also, suboptimal solutions can be generated in exchange for reduced execution time. The proposed formulation methods can also be used to solve shortest-path routing problems. Experimental results show that more than 3,700x speed-up can be achieved by using a parallel MILP solver with 16 threads in solving formulated longest-path routing problems. The execution time can be further reduced if a computer containing more processer cores is available.
Sullivan, Blair D; Seymour, Dr. Paul Douglas
2010-01-01
Say a digraph is k-free if it has no directed cycles of length at most k, for k {element_of} Z{sup +}. Thomasse conjectured that the number of induced 3-vertex directed paths in a simple 2-free digraph on n vertices is at most (n-1)n(n+1)/15. We present an unpublished result of Bondy proving there are at most 2n{sup 3}/25 such paths, and prove that for the class of circular interval digraphs, an upper bound of n{sup 3}/16 holds. We also study the problem of bounding the number of (non-induced) 4-vertex paths in 3-free digraphs. We show an upper bound of 4n{sup 4}/75 using Bondy's result for Thomasse's conjecture.
Optimizing Quantum Adiabatic Algorithm
Hongye Hu; Biao Wu
2015-11-24
In quantum adiabatic algorithm, as the adiabatic parameter $s(t)$ changes slowly from zero to one with finite rate, a transition to excited states inevitably occurs and this induces an intrinsic computational error. We show that this computational error depends not only on the total computation time $T$ but also on the time derivatives of the adiabatic parameter $s(t)$ at the beginning and the end of evolution. Previous work (Phys. Rev. A \\textbf{82}, 052305) also suggested this result. With six typical paths, we systematically demonstrate how to optimally design an adiabatic path to reduce the computational errors. Our method has a clear physical picture and also explains the pattern of computational error. In this paper we focus on quantum adiabatic search algorithm although our results are general.
Generalized gradient algorithm for trajectory optimization
NASA Technical Reports Server (NTRS)
Zhao, Yiyuan; Bryson, A. E.; Slattery, R.
1990-01-01
The generalized gradient algorithm presented and verified as a basis for the solution of trajectory optimization problems improves the performance index while reducing path equality constraints, and terminal equality constraints. The algorithm is conveniently divided into two phases, of which the first, 'feasibility' phase yields a solution satisfying both path and terminal constraints, while the second, 'optimization' phase uses the results of the first phase as initial guesses.
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.
Planning paths through a spatial hierarchy - Eliminating stair-stepping effects
NASA Technical Reports Server (NTRS)
Slack, Marc G.
1989-01-01
Stair-stepping effects are a result of the loss of spatial continuity resulting from the decomposition of space into a grid. This paper presents a path planning algorithm which eliminates stair-stepping effects induced by the grid-based spatial representation. The algorithm exploits a hierarchical spatial model to efficiently plan paths for a mobile robot operating in dynamic domains. The spatial model and path planning algorithm map to a parallel machine, allowing the system to operate incrementally, thereby accounting for unexpected events in the operating space.
Dudek, Gregory
Socially-Driven Collective Path Planning for Robot Missions Juan Camilo Gamboa Higuera, Anqi Xu,anqixu,florian,dudek}@cim.mcgill.ca Abstract--We address the problem of path planning for robot missions based on waypoints suggested. We then propose an approximative path planning algorithm with parameterized control over the degree
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…
ERIC Educational Resources Information Center
McGarvey, Lynn M.; Sterenberg, Gladys Y.; Long, Julie S.
2013-01-01
The authors elucidate what they saw as three important challenges to overcome along the path to becoming elementary school mathematics teacher leaders: marginal interest in math, low self-confidence, and teaching in isolation. To illustrate how these challenges were mitigated, they focus on the stories of two elementary school teachers--Laura and…
DNA Computing Hamiltonian path
Hagiya, Masami
2014 DNA DNA #12;DNA Computing · Feynman · Adleman · DNASIMD · ... · · · · · DNADNA #12;DNA · DNA · · · · DNA · · #12;2000 2005 2010 1995 Hamiltonian path DNA tweezers DNA tile DNA origami DNA box Sierpinski DNA tile self assembly DNA logic gates Whiplash PCR DNA automaton DNA spider MAYA
NASA Technical Reports Server (NTRS)
Bill, R. C.; Johnson, R. D. (inventors)
1979-01-01
A gas path seal suitable for use with a turbine engine or compressor is described. A shroud wearable or abradable by the abrasion of the rotor blades of the turbine or compressor shrouds the rotor bades. A compliant backing surrounds the shroud. The backing is a yieldingly deformable porous material covered with a thin ductile layer. A mounting fixture surrounds the backing.
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.
Damage detection using frequency shift path
NASA Astrophysics Data System (ADS)
Wang, Longqi; Lie, Seng Tjhen; Zhang, Yao
2016-01-01
This paper introduces a novel concept called FREquency Shift (FRESH) path to describe the dynamic behavior of structures with auxiliary mass. FRESH path combines the effects of frequency shifting and amplitude changing into one space curve, providing a tool for analyzing structure health status and properties. A damage index called FRESH curvature is then proposed to detect local stiffness reduction. FRESH curvature can be easily adapted for a particular problem since the sensitivity of the index can be adjusted by changing auxiliary mass or excitation power. An algorithm is proposed to adjust automatically the contribution from frequency and amplitude in the method. Because the extraction of FRESH path requires highly accurate frequency and amplitude estimators; therefore, a procedure based on discrete time Fourier transform is introduced to extract accurate frequency and amplitude with the time complexity of O (n log n), which is verified by simulation signals. Moreover, numerical examples with different damage sizes, severities and damping are presented to demonstrate the validity of the proposed damage index. In addition, applications of FRESH path on two steel beams with different damages are presented and the results show that the proposed method is valid and computational efficient.
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.
Robot path planning for space-truss assembly
NASA Technical Reports Server (NTRS)
Muenger, Rolf; Sanderson, Arthur C.
1992-01-01
Construction, repair, and maintenance of space-based structures will require extensive planning of operations in order to effectively carry out these tasks. The path planning algorithm described here is a general approach to generating paths that guarantee collision avoidance for a single chain nonredundant or redundant robot. The algorithm uses a graph search of feasible points in position space, followed by a local potential field method that guarantees collision avoidance among objects, structures, and the robot arm as well as conformance to joint limit constraints. This algorithm is novel in its computation of goal attractive potential fields in Cartesian space, and computation of obstacle repulsive fields in robot joint space. These effects are combined to generate robot motion. Computation is efficiently implemented through the computation of the robot arm Jacobian and not the full inverse arm kinematics. These planning algorithms have been implemented and evaluated using existing space-truss designs, and are being integrated into the RPI-CIRSSE Testbed environment.
Swift J1753.5-0127: The Black Hole Candidate with the shortest orbital period
C. Zurita; M. Durant; M. A. P. Torres; T. Shahbaz; J. Casares; D. Steeghs
2008-03-17
We present time-resolved photometry of the optical counterpart to the black hole candidate Swift J1753.5-0127, which has remained in the low/hard X-ray state and bright at optical/IR wavelengths since its discovery in 2005. At the time of our observations Swift J1753.5-0127 does not show a decay trend but remains stable at R=16.45 with a night to night variability of ~0.05 mag. The R-band light curves, taken from 2007 June 3 to August 31, are not sinusoidal, but exhibit a complex morphology with remarkable changes in shape and amplitude. The best period determination is 3.2443+-0.0010 hours. This photometric period is likely a superhump period, slightly larger than the orbital period. Therefore, Swift J1753.5-0127 is the black hole candidate with the shortest orbital period observed to date. Our estimation of the distance is comparable to values previously published and likely places Swift J1753.5-0127 in the Galactic halo.
Resonating-Valence-Bond Physics Is Not Always Governed by the Shortest Tunneling Loops.
Ralko, Arnaud; Rousochatzakis, Ioannis
2015-10-16
It is well known that the low-energy sector of quantum spin liquids and other magnetically disordered systems is governed by short-ranged resonating-valence bonds. Here we show that the standard minimal truncation to the nearest-neighbor valence-bond basis fails completely even for systems where it should work the most, according to received wisdom. This paradigm shift is demonstrated for the quantum spin-1/2 square kagome, where strong geometric frustration, similar to the kagome, prevents magnetic ordering down to zero temperature. The shortest tunneling events bear the strongest longer-range singlet fluctuations, leading to amplitudes that do not drop exponentially with the length of the loop L, and to an unexpected loop-six valence-bond crystal, which is otherwise very high in energy at the minimal truncation level. The low-energy effective description gives in addition a clear example of correlated loop processes that depend not only on the type of the loop but also on its lattice embedding, a direct manifestation of the long-range nature of the virtual singlets. PMID:26550898
Resonating-Valence-Bond Physics Is Not Always Governed by the Shortest Tunneling Loops
NASA Astrophysics Data System (ADS)
Ralko, Arnaud; Rousochatzakis, Ioannis
2015-10-01
It is well known that the low-energy sector of quantum spin liquids and other magnetically disordered systems is governed by short-ranged resonating-valence bonds. Here we show that the standard minimal truncation to the nearest-neighbor valence-bond basis fails completely even for systems where it should work the most, according to received wisdom. This paradigm shift is demonstrated for the quantum spin-1 /2 square kagome, where strong geometric frustration, similar to the kagome, prevents magnetic ordering down to zero temperature. The shortest tunneling events bear the strongest longer-range singlet fluctuations, leading to amplitudes that do not drop exponentially with the length of the loop L , and to an unexpected loop-six valence-bond crystal, which is otherwise very high in energy at the minimal truncation level. The low-energy effective description gives in addition a clear example of correlated loop processes that depend not only on the type of the loop but also on its lattice embedding, a direct manifestation of the long-range nature of the virtual singlets.
Practical and conceptual path sampling issues
NASA Astrophysics Data System (ADS)
Bolhuis, P. G.; Dellago, C.
2015-09-01
In the past 15 years transition path sampling (TPS) has evolved from its basic algorithm to an entire collection of methods and a framework for investigating rare events in complex systems. The methodology is applicable to a wide variety of systems and processes, ranging from transitions in small clusters or molecules to chemical reactions, phase transitions, and conformational changes in biomolecules. The basic idea of TPS is to harvest dynamical unbiased trajectories that connect a reactant with a product, by a Markov Chain Monte Carlo procedure called shooting. This simple importance sampling yields the rate constants, the free energy surface, insight in the mechanism of the rare event of interest, and by using the concept of the committor, also access to the reaction coordinate. In the last decade extensions to TPS have been developed, notably the transition interface sampling (TIS) methods, and its generalization multiple state TIS. Combination with advanced sampling methods such as replica exchange and the Wang-Landau algorithm, among others, improves sampling efficiency. Notwithstanding the success of TPS, there are issues left to discuss, and, despite the method's apparent simplicity, many pitfalls to avoid. This paper discusses several of these issues and pitfalls: the choice of stable states and interface order parameters, the problem of positioning the TPS windows and TIS interfaces, the matter of convergence of the path ensemble, the matter of kinetic traps, and the question whether TPS is able to investigate and sample Markov state models. We also review the reweighting technique used to join path ensembles. Finally we discuss the use of the sampled path ensemble to obtain reaction coordinates.
Algorithmic randomness and physical entropy
Zurek, W.H. )
1989-10-15
{ital Algorithmic} {ital randomness} provides a rigorous, entropylike measure of disorder of an individual, microscopic, definite state of a physical system. It is defined by the size (in binary digits) of the shortest message specifying the microstate uniquely up to the assumed resolution. Equivalently, algorithmic randomness can be expressed as the number of bits in the smallest program for a universal computer that can reproduce the state in question (for instance, by plotting it with the assumed accuracy). In contrast to the traditional definitions of entropy, algorithmic randomness can be used to measure disorder without any recourse to probabilities. Algorithmic randomness is typically very difficult to calculate exactly but relatively easy to estimate. In large systems, probabilistic ensemble definitions of entropy (e.g., coarse-grained entropy of Gibbs and Boltzmann's entropy {ital H}=ln{ital W}, as well as Shannon's information-theoretic entropy) provide accurate estimates of the algorithmic entropy of an individual system or its average value for an ensemble. One is thus able to rederive much of thermodynamics and statistical mechanics in a setting very different from the usual. {ital Physical} {ital entropy}, I suggest, is a sum of (i) the missing information measured by Shannon's formula and (ii) of the algorithmic information content---algorithmic randomness---present in the available data about the system. This definition of entropy is essential in describing the operation of thermodynamic engines from the viewpoint of information gathering and using systems. These Maxwell demon-type entities are capable of acquiring and processing information and therefore can decide'' on the basis of the results of their measurements and computations the best strategy for extracting energy from their surroundings. From their internal point of view the outcome of each measurement is definite.
Chew, Geoffrey F
2008-01-01
Arrowed-time divergence-free rules or cosmological quantum dynamics are formulated through stepped Feynman paths across macroscopic slices of Milne spacetime. Slice boundaries house totally-relativistic rays representing elementary entities--preons. Total relativity and the associated preon Fock space, despite distinction from special relativity (which lacks time arrow), are based on the Lorentz group. Each path is a set of cubic vertices connected by straight, directed and stepped arcs that carry inertial, electromagnetic and gravitational action. The action of an arc step comprises increments each bounded by Planck's constant. Action from extremely-distant sources is determined by universe mean energy density. Identifying the arc-step energy that determines inertial action with that determining gravitational action establishes both arc-step length and universe density. Special relativity is accurate for physics at laboratory spacetime scales far below that of Hubble and far above that of Planck.
Geoffrey F. Chew
2008-02-21
Arrowed-time divergence-free rules or cosmological quantum dynamics are formulated through stepped Feynman paths across macroscopic slices of Milne spacetime. Slice boundaries house totally-relativistic rays representing elementary entities--preons. Total relativity and the associated preon Fock space, despite distinction from special relativity (which lacks time arrow), are based on the Lorentz group. Each path is a set of cubic vertices connected by straight, directed and stepped arcs that carry inertial, electromagnetic and gravitational action. The action of an arc step comprises increments each bounded by Planck's constant. Action from extremely-distant sources is determined by universe mean energy density. Identifying the arc-step energy that determines inertial action with that determining gravitational action establishes both arc-step length and universe density. Special relativity is accurate for physics at laboratory spacetime scales far below that of Hubble and far above that of Planck.
Aircraft path planning for optimal imaging using dynamic cost functions
NASA Astrophysics Data System (ADS)
Christie, Gordon; Chaudhry, Haseeb; Kochersberger, Kevin
2015-05-01
Unmanned aircraft development has accelerated with recent technological improvements in sensing and communications, which has resulted in an "applications lag" for how these aircraft can best be utilized. The aircraft are becoming smaller, more maneuverable and have longer endurance to perform sensing and sampling missions, but operating them aggressively to exploit these capabilities has not been a primary focus in unmanned systems development. This paper addresses a means of aerial vehicle path planning to provide a realistic optimal path in acquiring imagery for structure from motion (SfM) reconstructions and performing radiation surveys. This method will allow SfM reconstructions to occur accurately and with minimal flight time so that the reconstructions can be executed efficiently. An assumption is made that we have 3D point cloud data available prior to the flight. A discrete set of scan lines are proposed for the given area that are scored based on visibility of the scene. Our approach finds a time-efficient path and calculates trajectories between scan lines and over obstacles encountered along those scan lines. Aircraft dynamics are incorporated into the path planning algorithm as dynamic cost functions to create optimal imaging paths in minimum time. Simulations of the path planning algorithm are shown for an urban environment. We also present our approach for image-based terrain mapping, which is able to efficiently perform a 3D reconstruction of a large area without the use of GPS data.
Kinematic path planning for space-based robotics
NASA Astrophysics Data System (ADS)
Seereeram, Sanjeev; Wen, John T.
1998-01-01
Future space robotics tasks require manipulators of significant dexterity, achievable through kinematic redundancy and modular reconfigurability, but with a corresponding complexity of motion planning. Existing research aims for full autonomy and completeness, at the expense of efficiency, generality or even user friendliness. Commercial simulators require user-taught joint paths-a significant burden for assembly tasks subject to collision avoidance, kinematic and dynamic constraints. Our research has developed a Kinematic Path Planning (KPP) algorithm which bridges the gap between research and industry to produce a powerful and useful product. KPP consists of three key components: path-space iterative search, probabilistic refinement, and an operator guidance interface. The KPP algorithm has been successfully applied to the SSRMS for PMA relocation and dual-arm truss assembly tasks. Other KPP capabilities include Cartesian path following, hybrid Cartesian endpoint/intermediate via-point planning, redundancy resolution and path optimization. KPP incorporates supervisory (operator) input at any detail to influence the solution, yielding desirable/predictable paths for multi-jointed arms, avoiding obstacles and obeying manipulator limits. This software will eventually form a marketable robotic planner suitable for commercialization in conjunction with existing robotic CAD/CAM packages.
PATHS groundwater hydrologic model
Nelson, R.W.; Schur, J.A.
1980-04-01
A preliminary evaluation capability for two-dimensional groundwater pollution problems was developed as part of the Transport Modeling Task for the Waste Isolation Safety Assessment Program (WISAP). Our approach was to use the data limitations as a guide in setting the level of modeling detail. PATHS Groundwater Hydrologic Model is the first level (simplest) idealized hybrid analytical/numerical model for two-dimensional, saturated groundwater flow and single component transport; homogeneous geology. This document consists of the description of the PATHS groundwater hydrologic model. The preliminary evaluation capability prepared for WISAP, including the enhancements that were made because of the authors' experience using the earlier capability is described. Appendixes A through D supplement the report as follows: complete derivations of the background equations are provided in Appendix A. Appendix B is a comprehensive set of instructions for users of PATHS. It is written for users who have little or no experience with computers. Appendix C is for the programmer. It contains information on how input parameters are passed between programs in the system. It also contains program listings and test case listing. Appendix D is a definition of terms.
Energy aware path planning in complex four dimensional environments
NASA Astrophysics Data System (ADS)
Chakrabarty, Anjan
This dissertation addresses the problem of energy-aware path planning for small autonomous vehicles. While small autonomous vehicles can perform missions that are too risky (or infeasible) for larger vehicles, the missions are limited by the amount of energy that can be carried on board the vehicle. Path planning techniques that either minimize energy consumption or exploit energy available in the environment can thus increase range and endurance. Path planning is complicated by significant spatial (and potentially temporal) variations in the environment. While the main focus is on autonomous aircraft, this research also addresses autonomous ground vehicles. Range and endurance of small unmanned aerial vehicles (UAVs) can be greatly improved by utilizing energy from the atmosphere. Wind can be exploited to minimize energy consumption of a small UAV. But wind, like any other atmospheric component , is a space and time varying phenomenon. To effectively use wind for long range missions, both exploration and exploitation of wind is critical. This research presents a kinematics based tree algorithm which efficiently handles the four dimensional (three spatial and time) path planning problem. The Kinematic Tree algorithm provides a sequence of waypoints, airspeeds, heading and bank angle commands for each segment of the path. The planner is shown to be resolution complete and computationally efficient. Global optimality of the cost function cannot be claimed, as energy is gained from the atmosphere, making the cost function inadmissible. However the Kinematic Tree is shown to be optimal up to resolution if the cost function is admissible. Simulation results show the efficacy of this planning method for a glider in complex real wind data. Simulation results verify that the planner is able to extract energy from the atmosphere enabling long range missions. The Kinematic Tree planning framework, developed to minimize energy consumption of UAVs, is applied for path planning in ground robots. In traditional path planning problem the focus is on obstacle avoidance and navigation. The optimal Kinematic Tree algorithm named Kinematic Tree* is shown to find optimal paths to reach the destination while avoiding obstacles. A more challenging path planning scenario arises for planning in complex terrain. This research shows how the Kinematic Tree* algorithm can be extended to find minimum energy paths for a ground vehicle in difficult mountainous terrain.
Path Similarity Analysis: A Method for Quantifying Macromolecular Pathways
Seyler, Sean L.; Kumar, Avishek; Thorpe, M. F.; Beckstein, Oliver
2015-01-01
Diverse classes of proteins function through large-scale conformational changes and various sophisticated computational algorithms have been proposed to enhance sampling of these macromolecular transition paths. Because such paths are curves in a high-dimensional space, it has been difficult to quantitatively compare multiple paths, a necessary prerequisite to, for instance, assess the quality of different algorithms. We introduce a method named Path Similarity Analysis (PSA) that enables us to quantify the similarity between two arbitrary paths and extract the atomic-scale determinants responsible for their differences. PSA utilizes the full information available in 3N-dimensional configuration space trajectories by employing the Hausdorff or Fréchet metrics (adopted from computational geometry) to quantify the degree of similarity between piecewise-linear curves. It thus completely avoids relying on projections into low dimensional spaces, as used in traditional approaches. To elucidate the principles of PSA, we quantified the effect of path roughness induced by thermal fluctuations using a toy model system. Using, as an example, the closed-to-open transitions of the enzyme adenylate kinase (AdK) in its substrate-free form, we compared a range of protein transition path-generating algorithms. Molecular dynamics-based dynamic importance sampling (DIMS) MD and targeted MD (TMD) and the purely geometric FRODA (Framework Rigidity Optimized Dynamics Algorithm) were tested along with seven other methods publicly available on servers, including several based on the popular elastic network model (ENM). PSA with clustering revealed that paths produced by a given method are more similar to each other than to those from another method and, for instance, that the ENM-based methods produced relatively similar paths. PSA applied to ensembles of DIMS MD and FRODA trajectories of the conformational transition of diphtheria toxin, a particularly challenging example, showed that the geometry-based FRODA occasionally sampled the pathway space of force field-based DIMS MD. For the AdK transition, the new concept of a Hausdorff-pair map enabled us to extract the molecular structural determinants responsible for differences in pathways, namely a set of conserved salt bridges whose charge-charge interactions are fully modelled in DIMS MD but not in FRODA. PSA has the potential to enhance our understanding of transition path sampling methods, validate them, and to provide a new approach to analyzing conformational transitions. PMID:26488417
Geodesically linked active contours: evolution strategy based on minimal paths
Mille, Julien
or retraction component, in order to increase the capture range of the snake. As regards the evolution processGeodesically linked active contours: evolution strategy based on minimal paths Julien MILLE algorithm is used to move vertices towards a configuration minimizing the energy functional. This evolution
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
Start and Stop Rules for Exploratory Path Analysis.
ERIC Educational Resources Information Center
Shipley, Bill
2002-01-01
Describes a method for choosing rejection probabilities for the tests of independence that are used in constraint-based algorithms of exploratory path analysis. The method consists of generating a Markov or semi-Markov model from the equivalence class represented by a partial ancestral graph and then testing the d-separation implications. (SLD)
Smooth Conditional Transition Paths in Dynamical Gaussian Networks
Miekisz, Jacek
a realistic transformation between two sequences of character animations in a virtual environment of the NVIDIA CUDA technology. Keywords: Formation Redeployment, Animation Blending, Transition Path in and out from a parking lot. Finally, the entertainment industry may use our algorithm in real
Multiple Damage Progression Paths in Model-based Prognostics
Daigle, Matthew
of end of life and remaining useful life within a probabilistic framework that supports uncertainty results in its own damage pro- gression path, which all combine to contribute to the over- all degradation to train ma- chine learning algorithms to make end of life and remaining useful life predictions [4
Tool path generation and 3D tolerance analysis for free-form surfaces
Choi, Young Keun
2005-08-29
This dissertation focuses on developing algorithms that generate tool paths for free-form surfaces based on accuracy of desired manufactured part. A manufacturing part is represented by mathematical curves and surfaces. Using the mathematical...
Path planning for off-road vehicles with a simulator-in-the-loop
Hellström, Thomas
system is to extend a standard path-tracking algorithm with a simulator that, in real-time, triesPath planning for off-road vehicles with a simulator-in-the-loop Thomas Hellström, thomash University SE-901 87 Umeå, Sweden May 6, 2008 Abstract This paper describes the development of a real-time
(Nothing else) MATor(s): Monitoring the Anonymity of Tor's Path Selection
International Association for Cryptologic Research (IACR)
(Nothing else) MATor(s): Monitoring the Anonymity of Tor's Path Selection Michael Backes1,2 Aniket we present MATOR: a framework for rigorously assessing the degree of anonymity in the Tor network deployed Tor, such as its path selection algorithm, Tor consensus data, and the preferences
Achieving Guaranteed Anonymity in GPS Traces via Uncertainty-Aware Path Cloaking
Gruteser, Marco
Achieving Guaranteed Anonymity in GPS Traces via Uncertainty-Aware Path Cloaking Baik Hoh, Marco (called uncertainty-aware path cloaking algorithm) that selectively reveals GPS samples to limit--Privacy, GPS, traffic monitoring, uncertainty, anonymity, cloaking. Ç 1 INTRODUCTION COLLABORATIVE sensing
Crack paths in composite materials M. Patricio* R. M. M. Mattheij*
Eindhoven, Technische Universiteit
#12;Crack paths in composite materials M. PatrÂ´icio* R. M. M. Mattheij* *Adress: Department ----------------------------------------------------------------Â Abstract Composites are often exposed to harsh loading conditions. This may lead to crack formation and propagation. In this paper an algorithm is described to predict the path of pre-existing cracks in homogeneous
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.
PATH SELECTION FOR MULTI-PATH STREAMING IN WIRELESS AD HOC NETWORKS1 Wei Wei and Avideh Zakhor
Zakhor, Avideh
] further propose a meta- heuristic approach based on genetic algorithms to solve the above path selection Multiple Description Coded Video (MDC) together with multipath routing for multimedia transport [1-3] have-time. Also the model in [4][5] considers neither the interference of flows on neighboring links, nor
Efficiently Discovering Hammock Paths from Induced Similarity Networks
Hossain, M Shahriar; Ramakrishnan, Naren
2010-01-01
Similarity networks are important abstractions in many information management applications such as recommender systems, corpora analysis, and medical informatics. For instance, by inducing similarity networks between movies rated similarly by users, or between documents containing common terms, and or between clinical trials involving the same themes, we can aim to find the global structure of connectivities underlying the data, and use the network as a basis to make connections between seemingly disparate entities. In the above applications, composing similarities between objects of interest finds uses in serendipitous recommendation, in storytelling, and in clinical diagnosis, respectively. We present an algorithmic framework for traversing similarity paths using the notion of `hammock' paths which are generalization of traditional paths. Our framework is exploratory in nature so that, given starting and ending objects of interest, it explores candidate objects for path following, and heuristics to admissib...
AH Cam: A metal-rich RR Lyrae star with the shortest known Blazhko period
NASA Technical Reports Server (NTRS)
Smith, Horace A.; Matthews, Jaymie M.; Lee, Kevin M.; Williams, Jeffrey; Silbermann, N. A.; Bolte, Michael
1994-01-01
Analysis of 746 new V-band observations of the RR Lyrae star AH Cam obtained during 1989 - 1992 clearly show that its light curve cannot be described by a single period. In fact, at first glance, the Fourier spectrum of the photometry resembles that of a double-mode pulsator, with peaks at a fundamental period of 0.3686 d and an apparent secondary period of 0.2628 d. Nevertheless, the dual-mode solution is a poor fit to the data. Rather, we believe that AH Cam is a single-mode RR Lyrae star undergoing the Blazhko effect: periodic modulation of the amplitude and shape of its light curve. What was originally taken to be the period of the second mode is instead the 1-cycle/d alias of a modulation sidelobe in the Fourier spectrum. The data are well described by a modulation period of just under 11 d, which is the shortest Blazhko period reported to date in the literature and confirms the earlier suggestion by Goranskii. A low-resolution spectrum of AH Cam indicates that it is relatively metal rich, with delta-S less than or = 2. Its high metallicity and short modulation period may provide a critical test of at least one theory for the Blazhko effect. Moskalik's internal resonance model makes specific predictions of the growth rate of the fundamental model vs fundamental period. AH Cam falls outside the regime of other known Blazhko variables and resonance model predictions, but these are appropriate for metal-poor RR Lyrae stars. If the theory matches the behavior of AH Cam for a metal-rich stellar model, this would bolster the resonance hypothesis.
Simulation and validation of subsurface lateral flow paths in an agricultural landscape
NASA Astrophysics Data System (ADS)
Zhu, Q.; Lin, H. S.
2009-04-01
The importance of soil water flow paths to the transport of nutrients and contaminants has long been recognized. However, effective means of detecting subsurface flow paths in a large landscape is still lacking. The flow direction and accumulation algorithm in GIS hydrologic modeling is a cost effective way to simulate potential flow paths over a large area. This study tested this algorithm for simulating lateral flow paths at three interfaces in soil profiles in a 19.5-ha agricultural landscape in central Pennsylvania, USA. These interfaces were (1) the surface plowed layers (Ap1 and Ap2 horizons) interface, (2) the interface with subsoil clay layer where clay content increased to over 40%, and (3) soil-bedrock interface. The simulated flow paths were validated through soil hydrologic monitoring, geophysical surveys, and observable soil morphological features. The results confirmed that subsurface lateral flow occurred at the interfaces with the clay layer and the underlying bedrock. At these two interfaces, the soils on the simulated flow paths were closer to saturation and showed more temporally unstable moisture dynamics than those off the simulated flow paths. Apparent electrical conductivity in the soil on the simulated flow paths was elevated and temporally unstable as compared to those outside the simulated paths. The soil cores collected from the simulated flow paths showed significantly higher Mn contents at these interfaces than those away from the simulated paths. These results suggest that (1) the algorithm is useful in simulating possible subsurface lateral flow paths if used appropriately with sufficiently detailed digital elevation model; (2) repeated electromagnetic surveys can reflect the temporal change of soil water storage and thus is an indicator of soil water movement over the landscape; and (3) observable Mn content in soil profiles can be used as a simple indicator of water flow paths in soils and over the landscape.
Zhu, Xiaoyan
2007-04-25
I would like to express my sincere gratitude to my advisor Dr. Wilbert E. Wilhelm, Department of Industrial Engineering, Texas A&M University, for his continuous guidance and many educational contributions. Throughout my Ph.D. program, I have... learned so many aspects of life from him. Without his guidence and encouragement I could not have finished my Ph.D. studies smoothly. Dr. Wilhelm has co-authored papers that are in review and I am very grateful for his significent contributions...
NASA Technical Reports Server (NTRS)
Robinson, Judith L.; Charles, John B.; Rummel, John A. (Technical Monitor)
2000-01-01
Approximately three years ago, the Agency's lead center for the human elements of spaceflight (the Johnson Space Center), along with the National Biomedical Research Institute (NSBRI) (which has the lead role in developing countermeasures) initiated an activity to identify the most critical risks confronting extended human spaceflight. Two salient factors influenced this activity: first, what information is needed to enable a "go/no go" decision to embark on extended human spaceflight missions; and second, what knowledge and capabilities are needed to address known and potential health, safety and performance risks associated with such missions. A unique approach was used to first define and assess those risks, and then to prioritize them. This activity was called the Critical Path Roadmap (CPR) and it represents an opportunity to develop and implement a focused and evolving program of research and technology designed from a "risk reduction" perspective to prevent or minimize the risks to humans exposed to the space environment. The Critical Path Roadmap provides the foundation needed to ensure that human spaceflight, now and in the future, is as safe, productive and healthy as possible (within the constraints imposed on any particular mission) regardless of mission duration or destination. As a tool, the Critical Path Roadmap enables the decisionmaker to select from among the demonstrated or potential risks those that are to be mitigated, and the completeness of that mitigation. The primary audience for the CPR Web Site is the members of the scientific community who are interested in the research and technology efforts required for ensuring safe and productive human spaceflight. They may already be informed about the various space life sciences research programs or they may be newcomers. Providing the CPR content to potential investigators increases the probability of their delivering effective risk mitigations. Others who will use the CPR Web Site and its content include program managers and administrators who track the program and are involved in decisions regarding resource allocation and program evaluation.
NASA Technical Reports Server (NTRS)
Robinson, Judith L.; Charles, John B.; Rummel, John A. (Technical Monitor)
2000-01-01
Approximately three years ago, the Agency's lead center for the human elements of spaceflight (the Johnson Space Center), along with the National Biomedical Research Institute (NSBRI) (which has the lead role in developing countermeasures) initiated an activity to identify the most critical risks confronting extended human spaceflight. Two salient factors influenced this activity: first, what information is needed to enable a "go/no go" decision to embark on extended human spaceflight missions; and second, what knowledge and capabilities are needed to address known and potential health, safety and performance risks associated with such missions. A unique approach was used to first define and assess those risks, and then to prioritize them. This activity was called the Critical Path Roadmap (CPR) and it represents an opportunity to develop and implement a focused and evolving program of research and technology designed from a "risk reduction" perspective to prevent or minimize the risks to humans exposed to the space environment. The Critical Path Roadmap provides the foundation needed to ensure that human spaceflight, now and in the future, is as safe, productive and healthy as possible (within the constraints imposed on any particular mission) regardless of mission duration or destination. As a tool, the Critical Path Roadmap enables the decision maker to select from among the demonstrated or potential risks those that are to be mitigated, and the completeness of that mitigation. The primary audience for the CPR Web Site is the members of the scientific community who are interested in the research and technology efforts required for ensuring safe and productive human spaceflight. They may already be informed about the various space life sciences research programs or they may be newcomers. Providing the CPR content to potential investigators increases the probability of their delivering effective risk mitigations. Others who will use the CPR Web Site and its content include program managers and administrators who track the program and are involved in decisions regarding resource allocation and program evaluation.
Bleakley, Hoyt; Lin, Jeffrey
2012-01-01
We examine portage sites in the U.S. South, Mid-Atlantic, and Midwest, including those on the fall line, a geomorphological feature in the southeastern U.S. marking the final rapids on rivers before the ocean. Historically, waterborne transport of goods required portage around the falls at these points, while some falls provided water power during early industrialization. These factors attracted commerce and manufacturing. Although these original advantages have long since been made obsolete, we document the continuing importance of these portage sites over time. We interpret these results as path dependence and contrast explanations based on sunk costs interacting with decreasing versus increasing returns to scale. PMID:23935217
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.
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.
Efficient capacity sharing for path protection in meshed optical networks
NASA Astrophysics Data System (ADS)
Dziong, Zbigniew; Nagarajan, Ramesh
2004-03-01
Efficient resource management in meshed optical networks is critical for supporting differentiated services, such as network restoration, in a cost-competitive manner. We propose and study several alternatives for dynamic and distributed selection of primary and protection paths. The focus is on algorithms where the bandwidth can be shared efficiently among protection paths, although other alternatives are considered as well. The routing algorithm and link cost function are based on a Markov decision-process framework. In particular, we use this framework to justify the link cost structure for primary and shared bandwidth. We also propose and study several options for describing the link state, which in turn determines the link cost, with the objective of minimizing the amount of data to be advertised without sacrificing performance. The proposed solutions can be implemented without changing the existing set of protocols. The numerical results show performance and cost savings for the different algorithm options.
Algorithms and architectures for high performance analysis of semantic graphs.
Hendrickson, Bruce Alan
2005-09-01
Semantic graphs offer one promising avenue for intelligence analysis in homeland security. They provide a mechanism for describing a wide variety of relationships between entities of potential interest. The vertices are nouns of various types, e.g. people, organizations, events, etc. Edges in the graph represent different types of relationships between entities, e.g. 'is friends with', 'belongs-to', etc. Semantic graphs offer a number of potential advantages as a knowledge representation system. They allow information of different kinds, and collected in differing ways, to be combined in a seamless manner. A semantic graph is a very compressed representation of some of relationship information. It has been reported that the semantic graph can be two orders of magnitude smaller than the processed intelligence data. This allows for much larger portions of the data universe to be resident in computer memory. Many intelligence queries that are relevant to the terrorist threat are naturally expressed in the language of semantic graphs. One example is the search for 'interesting' relationships between two individuals or between an individual and an event, which can be phrased as a search for short paths in the graph. Another example is the search for an analyst-specified threat pattern, which can be cast as an instance of subgraph isomorphism. It is important to note than many kinds of analysis are not relationship based, so these are not good candidates for semantic graphs. Thus, a semantic graph should always be used in conjunction with traditional knowledge representation and interface methods. Operations that involve looking for chains of relationships (e.g. friend of a friend) are not efficiently executable in a traditional relational database. However, the semantic graph can be thought of as a pre-join of the database, and it is ideally suited for these kinds of operations. Researchers at Sandia National Laboratories are working to facilitate semantic graph analysis. Since intelligence datasets can be extremely large, the focus of this work is on the use of parallel computers. We have been working to develop scalable parallel algorithms that will be at the core of a semantic graph analysis infrastructure. Our work has involved two different thrusts, corresponding to two different computer architectures. The first architecture of interest is distributed memory, message passing computers. These machines are ubiquitous and affordable, but they are challenging targets for graph algorithms. Much of our distributed-memory work to date has been collaborative with researchers at Lawrence Livermore National Laboratory and has focused on finding short paths on distributed memory parallel machines. Our implementation on 32K processors of BlueGene/Light finds shortest paths between two specified vertices in just over a second for random graphs with 4 billion vertices.
Critical Path-Based Thread Placement for NUMA Systems
Su, C Y; Li, D; Nikolopoulos, D S; Grove, M; Cameron, K; de Supinski, B R
2011-11-01
Multicore multiprocessors use a Non Uniform Memory Architecture (NUMA) to improve their scalability. However, NUMA introduces performance penalties due to remote memory accesses. Without efficiently managing data layout and thread mapping to cores, scientific applications, even if they are optimized for NUMA, may suffer performance loss. In this paper, we present algorithms and a runtime system that optimize the execution of OpenMP applications on NUMA architectures. By collecting information from hardware counters, the runtime system directs thread placement and reduces performance penalties by minimizing the critical path of OpenMP parallel regions. The runtime system uses a scalable algorithm that derives placement decisions with negligible overhead. We evaluate our algorithms and runtime system with four NPB applications implemented in OpenMP. On average the algorithms achieve between 8.13% and 25.68% performance improvement compared to the default Linux thread placement scheme. The algorithms miss the optimal thread placement in only 8.9% of the cases.
NASA Technical Reports Server (NTRS)
Wang, Lui; Bayer, Steven E.
1991-01-01
Genetic algorithms are mathematical, highly parallel, adaptive search procedures (i.e., problem solving methods) based loosely on the processes of natural genetics and Darwinian survival of the fittest. Basic genetic algorithms concepts are introduced, genetic algorithm applications are introduced, and results are presented from a project to develop a software tool that will enable the widespread use of genetic algorithm technology.
Guided Vehicle Suboptimal Path Planning For Execution Speed In A Factory Environment
NASA Astrophysics Data System (ADS)
Alley, D.; Iñigo, R. M.
1988-03-01
The methods of path planning for an Automatic Guided Vehicle (AGV) are discussed with regards to algorithm speed and method of world representation. Existing methods of path solution are often too slow for real time execution and must be done off line by the Factory Management System (FMS). By using a linked list world model and a modification of Djikstras algorithm to allow suboptimal results, execution may be sped up by a factor of 10 to 50 with the suboptimal error relative to the optimal path cost being bounded.
MAXI J1659-152: the shortest orbital period black-hole transient in outburst
NASA Astrophysics Data System (ADS)
Kuulkers, E.; Kouveliotou, C.; Belloni, T.; Cadolle Bel, M.; Chenevez, J.; Díaz Trigo, M.; Homan, J.; Ibarra, A.; Kennea, J. A.; Muñoz-Darias, T.; Ness, J.-U.; Parmar, A. N.; Pollock, A. M. T.; van den Heuvel, E. P. J.; van der Horst, A. J.
2013-04-01
MAXI J1659-152 is a bright X-ray transient black-hole candidate binary system discovered in September 2010. We report here on MAXI, RXTE, Swift, and XMM-Newton observations during its 2010/2011 outburst. We find that during the first one and a half week of the outburst the X-ray light curves display drops in intensity at regular intervals, which we interpret as absorption dips. About three weeks into the outbursts, again drops in intensity are seen. These dips have, however, a spectral behaviour opposite to that of the absorption dips, and are related to fast spectral state changes (hence referred to as transition dips). The absorption dips recur with a period of 2.414 ± 0.005 h, which we interpret as the orbital period of the system. This implies that MAXI J1659-152 is the shortest period black-hole candidate binary known to date. The inclination of the accretion disk with respect to the line of sight is estimated to be 65-80°. We propose the companion to the black-hole candidate to be close to an M5 dwarf star, with a mass and radius of about 0.15-0.25 M? and 0.2-0.25 R?, respectively. We derive that the companion had an initial mass of about 1.5 M?, which evolved to its current mass in about 5-6 billion years. The system is rather compact (orbital separation of ?1.33 R?), and is located at a distance of 8.6 ± 3.7 kpc, with a height above the Galactic plane of 2.4 ± 1.0 kpc. The characteristics of short orbital period and high Galactic scale height are shared with two other transient black-hole candidate X-ray binaries, i.e., XTE J1118+480 and Swift J1735.5-0127. We suggest that all three are kicked out of the Galactic plane into the halo, rather than being formed in a globular cluster. Table 1 is available in electronic form at http://www.aanda.org
Computing Path Tables for Quickest Multipaths In Computer Networks
Grimmell, W.C.
2004-12-21
We consider the transmission of a message from a source node to a terminal node in a network with n nodes and m links where the message is divided into parts and each part is transmitted over a different path in a set of paths from the source node to the terminal node. Here each link is characterized by a bandwidth and delay. The set of paths together with their transmission rates used for the message is referred to as a multipath. We present two algorithms that produce a minimum-end-to-end message delay multipath path table that, for every message length, specifies a multipath that will achieve the minimum end-to-end delay. The algorithms also generate a function that maps the minimum end-to-end message delay to the message length. The time complexities of the algorithms are O(n{sup 2}((n{sup 2}/logn) + m)min(D{sub max}, C{sub max})) and O(nm(C{sub max} + nmin(D{sub max}, C{sub max}))) when the link delays and bandwidths are non-negative integers. Here D{sub max} and C{sub max} are respectively the maximum link delay and maximum link bandwidth and C{sub max} and D{sub max} are greater than zero.
Algorithmic design of self-folding polyhedra
Pandey, Shivendra; Ewing, Margaret; Kunas, Andrew; Nguyen, Nghi; Gracias, David H.; Menon, Govind
2011-01-01
Self-assembly has emerged as a paradigm for highly parallel fabrication of complex three-dimensional structures. However, there are few principles that guide a priori design, yield, and defect tolerance of self-assembling structures. We examine with experiment and theory the geometric principles that underlie self-folding of submillimeter-scale higher polyhedra from two-dimensional nets. In particular, we computationally search for nets within a large set of possibilities and then test these nets experimentally. Our main findings are that (i) compactness is a simple and effective design principle for maximizing the yield of self-folding polyhedra; and (ii) shortest paths from 2D nets to 3D polyhedra in the configuration space are important for rationalizing experimentally observed folding pathways. Our work provides a model problem amenable to experimental and theoretical analysis of design principles and pathways in self-assembly. PMID:22139373
A polynomial algorithm for abstract maximum flow
McCormick, S.T.
1996-12-31
Ford and Fulkerson`s original 1956 max flow/min cut paper formulated max flow in terms of flows on paths, rather than the more familiar flows on arcs. In 1974 Hoffman pointed out that Ford and Fulkerson`s original proof was quite abstract, and applied to a wide range of max flow-like problems. In this abstract model we have capacitated elements, and linearly ordered subsets of elements called paths. When two paths share an element ({open_quote}cross{close_quote}), then there must be a path that is a subset of the first path up to the cross, and a subset of the second path after the cross. (Hoffman`s generalization of) Ford and Fulkerson`s proof showed that the max flow/min cut theorem still holds under this weak assumption. However, this proof is non-constructive. To get an algorithm, we assume that we have an oracle whose input is an arbitrary subset of elements, and whose output is either a path contained in that subset, or the statement that no such path exists. We then use complementary slackness to show how to augment any feasible set of path flows to a set with a strictly larger total flow value using a polynomial number of calls to the oracle. Then standard scaling techniques yield an overall polynomial algorithm for finding both a max flow and a min cut. Hoffman`s paper actually considers a sort of supermodular objective on the path flows, which allows him to include transportation problems and thus rain-cost flow in his frame-work. We also discuss extending our algorithm to this more general case.
Handbook of Feynman Path Integrals
NASA Astrophysics Data System (ADS)
Grosche, Christian, Steiner, Frank
The Handbook of Feynman Path Integrals appears just fifty years after Richard Feynman published his pioneering paper in 1948 entitled "Space-Time Approach to Non-Relativistic Quantum Mechanics", in which he introduced his new formulation of quantum mechanics in terms of path integrals. The book presents for the first time a comprehensive table of Feynman path integrals together with an extensive list of references; it will serve the reader as a thorough introduction to the theory of path integrals. As a reference book, it is unique in its scope and will be essential for many physicists, chemists and mathematicians working in different areas of research.
Simulation and validation of concentrated subsurface lateral flow paths in an agricultural landscape
NASA Astrophysics Data System (ADS)
Zhu, Q.; Lin, H. S.
2009-08-01
The importance of soil water flow paths to the transport of nutrients and contaminants has long been recognized. However, effective means of detecting concentrated subsurface flow paths in a large landscape are still lacking. The flow direction and accumulation algorithm based on single-direction flow algorithm (D8) in GIS hydrologic modeling is a cost-effective way to simulate potential concentrated flow paths over a large area once relevant data are collected. This study tested the D8 algorithm for simulating concentrated lateral flow paths at three interfaces in soil profiles in a 19.5-ha agricultural landscape in central Pennsylvania, USA. These interfaces were (1) the interface between surface plowed layers of Ap1 and Ap2 horizons, (2) the interface with subsoil water-restricting clay layer where clay content increased to over 40%, and (3) the soil-bedrock interface. The simulated flow paths were validated through soil hydrologic monitoring, geophysical surveys, and observable soil morphological features. The results confirmed that concentrated subsurface lateral flow occurred at the interfaces with the clay layer and the underlying bedrock. At these two interfaces, the soils on the simulated flow paths were closer to saturation and showed more temporally unstable moisture dynamics than those off the simulated flow paths. Apparent electrical conductivity in the soil on the simulated flow paths was elevated and temporally unstable as compared to those outside the simulated paths. The soil cores collected from the simulated flow paths showed significantly higher Mn content at these interfaces than those away from the simulated paths. These results suggest that (1) the D8 algorithm is useful in simulating possible concentrated subsurface lateral flow paths if used with appropriate threshold value of contributing area and sufficiently detailed digital elevation model (DEM); (2) repeated electromagnetic surveys can reflect the temporal change of soil water storage and thus is a useful indicator of possible subsurface flow path over a large area; and (3) observable Mn distribution in soil profiles can be used as a simple indicator of water flow paths in soils and over the landscape; however, it does require sufficient soil sampling (by excavation or augering) to possibly infer landscape-scale subsurface flow paths. In areas where subsurface interface topography varies similarly with surface topography, surface DEM can be used to simulate potential subsurface lateral flow path reasonably so the cost associated with obtaining depth to subsurface water-restricting layer can be minimized.
Khan, Wajahat Faheem
2008-01-01
We study the performance of a differential backlog routing algorithm in a network with random failures. Differential Backlog routing is a novel routing algorithm where packets are routed through multiple paths to their ...
Solving closest vector instances using an approximate shortest independent vectors oracle
International Association for Cryptologic Research (IACR)
mathematical objects that have been used to efficiently solve many important problems in computer science, most Laboratory of Information Security, Institute of Information Engineering, Chinese Academy of Sciences, this paper studies the algorithms for approximate closest vector problem (CVP) by using an approximate
BENCHMARKING ROBOT PATH PLANNING ANDREW N. HAND, JAGRUTHI GODUGU, KAVEH ASHENAYI,
Wainwright, Roger L.
1 BENCHMARKING ROBOT PATH PLANNING ANDREW N. HAND, JAGRUTHI GODUGU, KAVEH ASHENAYI, THEODORE W Algorithms (GA's) to develop an algorithm for autonomous robot navigation. We have achieved significant in different categories as Easy, Moderate, Difficult and Very Difficult. INTRODUCTION An autonomous robot
Pappas, George J.
Elastic Multi-Particle Systems for Bounded-Curvature Path Planning Ali Ahmadzadeh, Ali Jadbabaie, George J. Pappas and Vijay Kumar Abstract-- This paper investigates a path planning algorithm for Dubins The bounded-curvature path-planning problem, a central problem in robotics, involves planning a collision
The Edge-Disjoint Path Problem on Random Graphs by Message-Passing.
Altarelli, Fabrizio; Braunstein, Alfredo; Dall'Asta, Luca; De Bacco, Caterina; Franz, Silvio
2015-01-01
We present a message-passing algorithm to solve a series of edge-disjoint path problems on graphs based on the zero-temperature cavity equations. Edge-disjoint paths problems are important in the general context of routing, that can be defined by incorporating under a unique framework both traffic optimization and total path length minimization. The computation of the cavity equations can be performed efficiently by exploiting a mapping of a generalized edge-disjoint path problem on a star graph onto a weighted maximum matching problem. We perform extensive numerical simulations on random graphs of various types to test the performance both in terms of path length minimization and maximization of the number of accommodated paths. In addition, we test the performance on benchmark instances on various graphs by comparison with state-of-the-art algorithms and results found in the literature. Our message-passing algorithm always outperforms the others in terms of the number of accommodated paths when considering non trivial instances (otherwise it gives the same trivial results). Remarkably, the largest improvement in performance with respect to the other methods employed is found in the case of benchmarks with meshes, where the validity hypothesis behind message-passing is expected to worsen. In these cases, even though the exact message-passing equations do not converge, by introducing a reinforcement parameter to force convergence towards a sub optimal solution, we were able to always outperform the other algorithms with a peak of 27% performance improvement in terms of accommodated paths. On random graphs, we numerically observe two separated regimes: one in which all paths can be accommodated and one in which this is not possible. We also investigate the behavior of both the number of paths to be accommodated and their minimum total length. PMID:26710102
A Trajectory Algorithm to Support En Route and Terminal Area Self-Spacing Concepts
NASA Technical Reports Server (NTRS)
Abbott, Terence S.
2007-01-01
This document describes an algorithm for the generation of a four dimensional aircraft trajectory. Input data for this algorithm are similar to an augmented Standard Terminal Arrival Route (STAR) with the augmentation in the form of altitude or speed crossing restrictions at waypoints on the route. Wind data at each waypoint are also inputs into this algorithm. The algorithm calculates the altitude, speed, along path distance, and along path time for each waypoint.
Quantum Adiabatic Algorithms and Large Spin Tunnelling
NASA Technical Reports Server (NTRS)
Boulatov, A.; Smelyanskiy, V. N.
2003-01-01
We provide a theoretical study of the quantum adiabatic evolution algorithm with different evolution paths proposed in this paper. The algorithm is applied to a random binary optimization problem (a version of the 3-Satisfiability problem) where the n-bit cost function is symmetric with respect to the permutation of individual bits. The evolution paths are produced, using the generic control Hamiltonians H (r) that preserve the bit symmetry of the underlying optimization problem. In the case where the ground state of H(0) coincides with the totally-symmetric state of an n-qubit system the algorithm dynamics is completely described in terms of the motion of a spin-n/2. We show that different control Hamiltonians can be parameterized by a set of independent parameters that are expansion coefficients of H (r) in a certain universal set of operators. Only one of these operators can be responsible for avoiding the tunnelling in the spin-n/2 system during the quantum adiabatic algorithm. We show that it is possible to select a coefficient for this operator that guarantees a polynomial complexity of the algorithm for all problem instances. We show that a successful evolution path of the algorithm always corresponds to the trajectory of a classical spin-n/2 and provide a complete characterization of such paths.
Hard paths, soft paths or no paths? Cross-cultural perceptions of water solutions
NASA Astrophysics Data System (ADS)
Wutich, A.; White, A. C.; White, D. D.; Larson, K. L.; Brewis, A.; Roberts, C.
2014-01-01
In this study, we examine how development status and water scarcity shape people's perceptions of "hard path" and "soft path" water solutions. Based on ethnographic research conducted in four semi-rural/peri-urban sites (in Bolivia, Fiji, New Zealand, and the US), we use content analysis to conduct statistical and thematic comparisons of interview data. Our results indicate clear differences associated with development status and, to a lesser extent, water scarcity. People in the two less developed sites were more likely to suggest hard path solutions, less likely to suggest soft path solutions, and more likely to see no path to solutions than people in the more developed sites. Thematically, people in the two less developed sites envisioned solutions that involve small-scale water infrastructure and decentralized, community-based solutions, while people in the more developed sites envisioned solutions that involve large-scale infrastructure and centralized, regulatory water solutions. People in the two water-scarce sites were less likely to suggest soft path solutions and more likely to see no path to solutions (but no more likely to suggest hard path solutions) than people in the water-rich sites. Thematically, people in the two water-rich sites seemed to perceive a wider array of unrealized potential soft path solutions than those in the water-scarce sites. On balance, our findings are encouraging in that they indicate that people are receptive to soft path solutions in a range of sites, even those with limited financial or water resources. Our research points to the need for more studies that investigate the social feasibility of soft path water solutions, particularly in sites with significant financial and natural resource constraints.
Hard paths, soft paths or no paths? Cross-cultural perceptions of water solutions
NASA Astrophysics Data System (ADS)
Wutich, A.; White, A. C.; Roberts, C. M.; White, D. D.; Larson, K. L.; Brewis, A.
2013-06-01
In this study, we examine how development status and water scarcity shape people's perceptions of "hard path" and "soft path" water solutions. Based on ethnographic research conducted in four semi-rural/peri-urban sites (in Bolivia, Fiji, New Zealand, and the US), we use content analysis to conduct statistical and thematic comparisons of interview data. Our results indicate clear differences based on development status and, to a lesser extent, water scarcity. People in less developed sites were more likely to suggest hard path solutions, less likely to suggest soft path solutions, and more likely to see no path to solutions than people in more developed sites. Thematically, people in less developed sites envisioned solutions that involve small-scale water infrastructure and decentralized, community based solutions, while people in more developed sites envisioned solutions that involve large-scale infrastructure and centralized, regulatory water solutions. People in water-scarce sites were less likely to suggest soft path solutions and more likely to see no path to solutions (but no more likely to suggest hard path solutions) than people in water-rich sites. Thematically, people in water-rich sites seemed to perceive a wider array of unrealized potential soft path solutions than those in water-scarce sites. On balance, our findings are encouraging in that they indicate that people are receptive to soft path solutions in a range of sites, even those with limited financial or water resources. Our research points to the need for more studies that investigate the social feasibility of soft path water solutions, particularly in sites with significant financial and natural resource constraints.
Heuristically optimal path scanning for high-speed multiphoton circuit imaging.
Sadovsky, Alexander J; Kruskal, Peter B; Kimmel, Joseph M; Ostmeyer, Jared; Neubauer, Florian B; MacLean, Jason N
2011-09-01
Population dynamics of patterned neuronal firing are fundamental to information processing in the brain. Multiphoton microscopy in combination with calcium indicator dyes allows circuit dynamics to be imaged with single-neuron resolution. However, the temporal resolution of fluorescent measures is constrained by the imaging frequency imposed by standard raster scanning techniques. As a result, traditional raster scans limit the ability to detect the relative timing of action potentials in the imaged neuronal population. To maximize the speed of fluorescence measures from large populations of neurons using a standard multiphoton laser scanning microscope (MPLSM) setup, we have developed heuristically optimal path scanning (HOPS). HOPS optimizes the laser travel path length, and thus the temporal resolution of neuronal fluorescent measures, using standard galvanometer scan mirrors. Minimizing the scan path alone is insufficient for prolonged high-speed imaging of neuronal populations. Path stability and the signal-to-noise ratio become increasingly important factors as scan rates increase. HOPS addresses this by characterizing the scan mirror galvanometers to achieve prolonged path stability. In addition, the neuronal dwell time is optimized to sharpen the detection of action potentials while maximizing scan rate. The combination of shortest path calculation and minimization of mirror positioning time allows us to optically monitor a population of neurons in a field of view at high rates with single-spike resolution, ? 125 Hz for 50 neurons and ? 8.5 Hz for 1,000 neurons. Our approach introduces an accessible method for rapid imaging of large neuronal populations using traditional MPLSMs, facilitating new insights into neuronal circuit dynamics. PMID:21715667
Schiefer, H. Peters, S.; Plasswilm, L.; Ingulfsen, N.; Kluckert, J.
2015-03-15
Purpose: For stereotactic radiosurgery, the AAPM Report No. 54 [AAPM Task Group 42 (AAPM, 1995)] requires the overall stability of the isocenter (couch, gantry, and collimator) to be within a 1 mm radius. In reality, a rotating system has no rigid axis and thus no isocenter point which is fixed in space. As a consequence, the isocenter concept is reviewed here. It is the aim to develop a measurement method following the revised definitions. Methods: The mechanical isocenter is defined here by the point which rotates on the shortest path in the room coordinate system. The path is labeled as “isocenter path.” Its center of gravity is assumed to be the mechanical isocenter. Following this definition, an image-based and radiation-free measurement method was developed. Multiple marker pairs in a plane perpendicular to the assumed gantry rotation axis of a linear accelerator are imaged with a smartphone application from several rotation angles. Each marker pair represents an independent measuring system. The room coordinates of the isocenter path and the mechanical isocenter are calculated based on the marker coordinates. The presented measurement method is by this means strictly focused on the mechanical isocenter. Results: The measurement result is available virtually immediately following completion of measurement. When 12 independent measurement systems are evaluated, the standard deviations of the isocenter path points and mechanical isocenter coordinates are 0.02 and 0.002 mm, respectively. Conclusions: The measurement is highly accurate, time efficient, and simple to adapt. It is therefore suitable for regular checks of the mechanical isocenter characteristics of the gantry and collimator rotation axis. When the isocenter path is reproducible and its extent is in the range of the needed geometrical accuracy, it should be taken into account in the planning process. This is especially true for stereotactic treatments and radiosurgery.
Optimal Path to a Laser Fusion Energy Power Plant
NASA Astrophysics Data System (ADS)
Bodner, Stephen
2013-10-01
There was a decision in the mid 1990s to attempt ignition using indirect-drive targets. It is now obvious that this decision was unjustified. The target design was too geometrically complex, too inefficient, and too far above plasma instability thresholds. By that same time, the mid 1990s, there had also been major advances in the direct-drive target concept. It also was not yet ready for a major test. Now, finally, because of significant advances in target designs, laser-target experiments, and laser development, the direct-drive fusion concept is ready for significant enhancements in funding, on the path to commercial fusion energy. There are two laser contenders. A KrF laser is attractive because of its shortest wavelength, broad bandwidth, and superb beam uniformity. A frequency-converted DPSSL has the disadvantage of inherently narrow bandwidth and longer wavelength, but by combining many beams in parallel one might be able to produce at the target the equivalent of an ultra-broad bandwidth. One or both of these lasers may also meet all of the engineering and economic requirements for a reactor. It is time to further develop and evaluate these two lasers as rep-rate systems, in preparation for a future high-gain fusion test.
Topics in Algorithms 2005 Disjoint Paths, Cuts, Arborescences
Hariharan, Ramesh
A . B' A' . B' x x x x #12;The Cactus of Global Cuts All global min-cuts form a cactus. Any disconnection of the cactus is a min-cut. Exercise?? How many global min-cuts does this imply. x x x x x x x x x
A Path to Understanding the Effects of Algorithm Awareness
Karahalios, Karrie G.
- Champaign 1308 W Main Street Urbana, IL 61801-2307 eslamim2@uiuc.edu #12;computer science, an informal-winning professor of medicine. Casually and in user studies, even some Graduate Students in Computer Science who of awareness is indicative of successful design - for shouldn't good interaction design be invisible
Career Path Suggestion using String Matching and Decision Trees
NASA Astrophysics Data System (ADS)
Nagpal, Akshay; P. Panda, Supriya
2015-05-01
High school and college graduates seemingly are often battling for the courses they should major in order to achieve their target career. In this paper, we worked on suggesting a career path to a graduate to reach his/her dream career given the current educational status. Firstly, we collected the career data of professionals and academicians from various career fields and compiled the data set by using the necessary information from the data. Further, this was used as the basis to suggest the most appropriate career path for the person given his/her current educational status. Decision trees and string matching algorithms were employed to suggest the appropriate career path for a person. Finally, an analysis of the result has been done directing to further improvements in the model.
Conditions for transmission path analysis in energy distribution models
NASA Astrophysics Data System (ADS)
Aragonès, Àngels; Guasch, Oriol
2016-02-01
In this work, we explore under which conditions transmission path analysis (TPA) developed for statistical energy analysis (SEA) can be applied to the less restrictive energy distribution (ED) models. It is shown that TPA can be extended without problems to proper-SEA systems whereas the situation is not so clear for quasi-SEA systems. In the general case, it has been found that a TPA can always be performed on an ED model if its inverse influence energy coefficient (EIC) matrix turns to have negative off-diagonal entries. If this condition is satisfied, it can be shown that the inverse EIC matrix automatically becomes an M-matrix. An ED graph can then be defined for it and use can be made of graph theory ranking path algorithms, previously developed for SEA systems, to classify dominant paths in ED models. A small mechanical system consisting of connected plates has been used to illustrate some of the exposed theoretical results.
Sampling-based algorithms for optimal motion planning
Karaman, Sertac
During the last decade, sampling-based path planning algorithms, such as probabilistic roadmaps (PRM) and rapidly exploring random trees (RRT), have been shown to work well in practice and possess theoretical guarantees ...
Multi-link failure restoration with dynamic load balancing in spectrum-elastic optical path networks
NASA Astrophysics Data System (ADS)
Chen, Bowen; Zhang, Jie; Zhao, Yongli; Lv, Chunhui; Zhang, Wei; Huang, Shanguo; Zhang, Xian; Gu, Wanyi
2012-01-01
In this paper, we investigate network performance of multi-link failure restoration in spectrum-elastic optical path networks (SLICE). To efficiently restore traffic under multi-link failures, a novel survivable algorithm, named dynamic load balancing shared-path protection (DLBSPP), is proposed to compute primary and link-disjoint shared backup paths. The DLBSPP algorithm employs first fit (FF) and random fit (RF) schemes to search and assign the available spectrum resource. Traffic-aware restoration (TAR) mechanism is adopted in the DLBSPP algorithm to compute new routes for carrying the traffic affected by the multi-link failures and then the multi-link failures can be efficiently restored. Simulation results show that, compared with the conventional shared-path protection (SPP) algorithm, the DLBSPP algorithm achieves lower blocking probability (BP), better spectrum utilization ratio (SUR), more reasonable average hop (AH) and higher failure restoration ratio (FRR). Thus, the proposed DLBSPP algorithm has much higher spectrum efficiency and much better survivability than SPP algorithm.
NASA Technical Reports Server (NTRS)
Chandler, J. A.
1983-01-01
Long helical vent path cools and releases hot pyrotechnical gas that exits along its spiraling threads. Current design uses 1/4-28 threads with outer diameter of stud reduced by 0.025 in. (0.62 mm). To open or close gassampler bottle, pyrotechnic charges on either one side or other of valve cylinder are actuated. Gases vented slowly over long path are cool enough to present no ignition hazard. Vent used to meter flow in refrigeration, pneumaticcontrol, and fluid-control systems by appropriately adjusting size and length of vent path.
Robust Path Planning and Feedback Design Under Stochastic Uncertainty
NASA Technical Reports Server (NTRS)
Blackmore, Lars
2008-01-01
Autonomous vehicles require optimal path planning algorithms to achieve mission goals while avoiding obstacles and being robust to uncertainties. The uncertainties arise from exogenous disturbances, modeling errors, and sensor noise, which can be characterized via stochastic models. Previous work defined a notion of robustness in a stochastic setting by using the concept of chance constraints. This requires that mission constraint violation can occur with a probability less than a prescribed value.In this paper we describe a novel method for optimal chance constrained path planning with feedback design. The approach optimizes both the reference trajectory to be followed and the feedback controller used to reject uncertainty. Our method extends recent results in constrained control synthesis based on convex optimization to solve control problems with nonconvex constraints. This extension is essential for path planning problems, which inherently have nonconvex obstacle avoidance constraints. Unlike previous approaches to chance constrained path planning, the new approach optimizes the feedback gain as wellas the reference trajectory.The key idea is to couple a fast, nonconvex solver that does not take into account uncertainty, with existing robust approaches that apply only to convex feasible regions. By alternating between robust and nonrobust solutions, the new algorithm guarantees convergence to a global optimum. We apply the new method to an unmanned aircraft and show simulation results that demonstrate the efficacy of the approach.
Subdimensional Expansion for Multirobot Path Glenn Wagner
Choset, Howie
Subdimensional Expansion for Multirobot Path Planning Glenn Wagner , Howie Choset Robotics 4, 2015 #12;Subdimensional Expansion for Multirobot Path Planning Glenn Wagner , Howie Choset framework for multirobot path plan- ning called subdimensional expansion, which initially plans for each
EXTENDING THE PATH-PLANNING Robotics Institute
EXTENDING THE PATH-PLANNING HORIZON Bart Nabbe Robotics Institute Carnegie Mellon University to plan inefficient paths that trace obstacle boundaries. To alleviate this problem, We present an op . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 1.3. Path Planning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 2. Proposed
A Synthesized Heuristic Task Scheduling Algorithm
Dai, Yanyan; Zhang, Xiangli
2014-01-01
Aiming at the static task scheduling problems in heterogeneous environment, a heuristic task scheduling algorithm named HCPPEFT is proposed. In task prioritizing phase, there are three levels of priority in the algorithm to choose task. First, the critical tasks have the highest priority, secondly the tasks with longer path to exit task will be selected, and then algorithm will choose tasks with less predecessors to schedule. In resource selection phase, the algorithm is selected task duplication to reduce the interresource communication cost, besides forecasting the impact of an assignment for all children of the current task permits better decisions to be made in selecting resources. The algorithm proposed is compared with STDH, PEFT, and HEFT algorithms through randomly generated graphs and sets of task graphs. The experimental results show that the new algorithm can achieve better scheduling performance. PMID:25254244
Effective algorithms and protocols for wireless networking: a topological approach
Zhang, Fenghui
2008-10-10
in FPT time. . . . . 97 25 Wireless sensor network andits planarization. (a)The dark(green and black) edges are the planarized network. The light (grey) edges aretheremaining edges intheoriginalnetwork. The original network is a quasi-UDG with N = 2000.../r = 2. . . . . . . . . . . . . . . . . . . . . . 141 37 Algorithm find-paths: extend a set of k?-paths to longer length. . . 149 38 Algorithm Coloring: construct a color coding scheme. . . . . . . . . 160 1 CHAPTER I INTRODUCTION A wireless sensor...
Yen-BSR: A New Approach for the Choice of Routes in WDM Networks
NASA Astrophysics Data System (ADS)
Santos, A. F.; Almeida, R. C.; Assis, K. D. R.
2014-12-01
In this paper we propose to use an iterative algorithm for optimizing the fixed-alternate shortest path routing in the dynamic routing and wavelength assignment (RWA) problem in wavelength routing optical networks. The algorithm performance is compared, in terms of blocking probability, with the Dijkstra and Yen traditional algorithms, as well as with the recently proposed best among the shortest routes (BSR) algorithm. The results suggest that it is feasible to choose an appropriate set of routes for each pair of nodes (source, destination), among the shortest paths and efficiently balance the network load. For all studied scenarios, the proposed heuristic achieved superior performance.
MotifMiner: A Table Driven Greedy Algorithm for DNA Motif Mining
NASA Astrophysics Data System (ADS)
Seeja, K. R.; Alam, M. A.; Jain, S. K.
DNA motif discovery is a much explored problem in functional genomics. This paper describes a table driven greedy algorithm for discovering regulatory motifs in the promoter sequences of co-expressed genes. The proposed algorithm searches both DNA strands for the common patterns or motifs. The inputs to the algorithm are set of promoter sequences, the motif length and minimum Information Content. The algorithm generates subsequences of given length from the shortest input promoter sequence. It stores these subsequences and their reverse complements in a table. Then it searches the remaining sequences for good matches of these subsequences. The Information Content score is used to measure the goodness of the motifs. The algorithm has been tested with synthetic data and real data. The results are found promising. The algorithm could discover meaningful motifs from the muscle specific regulatory sequences.
Multi-agent Path Planning and Network Flow
Yu, Jingjin
2012-01-01
This paper connects multi-agent path planning on graphs (roadmaps) to network flow problems, showing that the former can be reduced to the latter, therefore enabling the application of combinatorial network flow algorithms, as well as general linear program techniques, to multi-agent path planning problems on graphs. Exploiting this connection, we show that when the goals are permutation invariant, the problem always has a feasible solution path set with a longest finish time of no more than $n + V - 1$ steps, in which $n$ is the number of agents and $V$ is the number of vertices of the underlying graph. We then give a complete algorithm that finds such a solution in $O(nVE)$ time, with $E$ being the number of edges of the graph. Taking a further step, we study time and distance optimality of the feasible solutions, show that they have a pairwise Pareto optimal structure, and again provide efficient algorithms for optimizing each of these practical objectives.
Commercializing Biorefineries The Path Forward
Commercializing Biorefineries The Path Forward Bioenergy ExCo 59 Workshop Golden, CO Lawrence J Agricultural lands · Corn stover, wheat straw, soybean residue, manure, switchgrass, poplar/willow energy crops
Collaborative Authoring of Walden's Paths
Li, Yuanling
2012-10-19
The World Wide Web contains rich collections of digital materials that can be used in education and learning settings. The collaborative authoring prototype of Walden's Paths targets two groups of users: educators and learners. From the perspective...
Yong Seung Cho; Soon-Tae Hong
2007-06-01
We consider the path space of a curved manifold on which a point particle is introduced in a conservative physical system with constant total energy to formulate its action functional and geodesic equation together with breaks on the path. The second variation of the action functional is exploited to yield the geodesic deviation equation and to discuss the Jacobi fields on the curved manifold. We investigate the topology of the path space using the action functional on it and its physical meaning by defining the gradient of the action functional, the space of bounded flow energy solutions and the moduli space associated with the critical points of the action functional. We also consider the particle motion on the $n$-sphere $S^{n}$ in the conservative physical system to discuss explicitly the moduli space of the path space and the corresponding homology groups.
COMPUTER SCIENCE: MISCONCEPTIONS, CAREER PATHS
Hristidis, Vagelis
COMPUTER SCIENCE: MISCONCEPTIONS, CAREER PATHS AND RESEARCH CHALLENGES School of Computing Undergraduate Student) #12;Computer Science Misconceptions Intro to Computer Science - Florida International University 2 Some preconceived ideas & stereotypes about Computer Science (CS) are quite common
An introduction to critical paths.
Coffey, Richard J; Richards, Janet S; Remmert, Carl S; LeRoy, Sarah S; Schoville, Rhonda R; Baldwin, Phyllis J
2005-01-01
A critical path defines the optimal sequencing and timing of interventions by physicians, nurses, and other staff for a particular diagnosis or procedure. Critical paths are developed through collaborative efforts of physicians, nurses, pharmacists, and others to improve the quality and value of patient care. They are designed to minimize delays and resource utilization and to maximize quality of care. Critical paths have been shown to reduce variation in the care provided, facilitate expected outcomes, reduce delays, reduce length of stay, and improve cost-effectiveness. The approach and goals of critical paths are consistent with those of total quality management (TQM) and can be an important part of an organization's TQM process. PMID:15739581
Scattering Theory with Path Integrals
R. Rosenfelder
2013-02-25
Starting from well-known expressions for the $T$-matrix and its derivative in standard nonrelativistic potential scattering I rederive recent path-integral formulations due to Efimov and Barbashov et al. Some new relations follow immediately.
Autonomous Path-Following by Approximate Inverse Dynamics and Vector Field Prediction
NASA Astrophysics Data System (ADS)
Gerlach, Adam R.
In this dissertation, we develop two general frameworks for the navigation and control of autonomous vehicles that must follow predefined paths. These frameworks are designed such that they inherently provide accurate navigation and control of a wide class of systems directly from a model of the vehicle's dynamics. The first framework introduced is the inverse dynamics by radial basis function (IDRBF) algorithm, which exploits the best approximation property of radial basis functions to accurately approximate the inverse dynamics of non-linear systems. This approximation is then used with the known, desired state of the system at a future time point to generate the system input that must be applied to reach the desired state in the specified time interval. The IDRBF algorithm is then tested on two non-linear dynamic systems, and accurate path-following is demonstrated. The second framework introduced is the predictive vector field (PVF) algorithm. The PVF algorithm uses the equations of motion and constraints of the system to predict a set of reachable states by sampling the system's configuration space. By finding and minimizing a continuous mapping between the system's configuration space and a cost space relating the reachable states of the system with a vector field (VF), one can determine the system inputs required to follow the VF. The PVF algorithm is then tested on the Dubin's vehicle and aircraft models, and accurate path-following is demonstrated. As the PVF algorithm's performance is dependent on the quality of the underlying system model and VF, algorithms are introduced for automatically generating VFs for constant altitude paths defined by a series of waypoints and for handling modeling uncertainties. Additionally, we provide a mathematical proof showing that this method can automatically produce VFs of the desired form. To handle modeling uncertainties, we enhance the PVF algorithm with the Gaussian process machine learning framework, enabling the algorithm to learn the true system model, online, in the presence of measurement noise. We call this algorithm the PVF-GP algorithm. To demonstrate the PVF-GP algorithm, we compare its performance to the PVF algorithm after introducing modeling uncertainties to the underlying system model and introducing an external wind disturbance. Test results show the PVF-GP algorithm offers dramatically improved path-following performance over the non-learning PVF algorithm.
Path planning for robotic truss assembly
NASA Technical Reports Server (NTRS)
Sanderson, Arthur C.
1993-01-01
A new Potential Fields approach to the robotic path planning problem is proposed and implemented. Our approach, which is based on one originally proposed by Munger, computes an incremental joint vector based upon attraction to a goal and repulsion from obstacles. By repetitively adding and computing these 'steps', it is hoped (but not guaranteed) that the robot will reach its goal. An attractive force exerted by the goal is found by solving for the the minimum norm solution to the linear Jacobian equation. A repulsive force between obstacles and the robot's links is used to avoid collisions. Its magnitude is inversely proportional to the distance. Together, these forces make the goal the global minimum potential point, but local minima can stop the robot from ever reaching that point. Our approach improves on a basic, potential field paradigm developed by Munger by using an active, adaptive field - what we will call a 'flexible' potential field. Active fields are stronger when objects move towards one another and weaker when they move apart. An adaptive field's strength is individually tailored to be just strong enough to avoid any collision. In addition to the local planner, a global planning algorithm helps the planner to avoid local field minima by providing subgoals. These subgoals are based on the obstacles which caused the local planner to fail. A best-first search algorithm A* is used for graph search.
Exploratory Dijkstra forest based automatic vessel segmentation
Tomasi, Carlo
Exploratory Dijkstra forest based automatic vessel segmentation: applications in video indirect's shortest-path algorithm. Our method preserves vessel thickness, requires no manual intervention, and follows vessel branching naturally and efficiently. To test our method, we constructed a retinal video
Path statistics, memory, and coarse-graining of continuous-time random walks on networks.
Manhart, Michael; Kion-Crosby, Willow; Morozov, Alexandre V
2015-12-01
Continuous-time random walks (CTRWs) on discrete state spaces, ranging from regular lattices to complex networks, are ubiquitous across physics, chemistry, and biology. Models with coarse-grained states (for example, those employed in studies of molecular kinetics) or spatial disorder can give rise to memory and non-exponential distributions of waiting times and first-passage statistics. However, existing methods for analyzing CTRWs on complex energy landscapes do not address these effects. Here we use statistical mechanics of the nonequilibrium path ensemble to characterize first-passage CTRWs on networks with arbitrary connectivity, energy landscape, and waiting time distributions. Our approach can be applied to calculating higher moments (beyond the mean) of path length, time, and action, as well as statistics of any conservative or non-conservative force along a path. For homogeneous networks, we derive exact relations between length and time moments, quantifying the validity of approximating a continuous-time process with its discrete-time projection. For more general models, we obtain recursion relations, reminiscent of transfer matrix and exact enumeration techniques, to efficiently calculate path statistics numerically. We have implemented our algorithm in PathMAN (Path Matrix Algorithm for Networks), a Python script that users can apply to their model of choice. We demonstrate the algorithm on a few representative examples which underscore the importance of non-exponential distributions, memory, and coarse-graining in CTRWs. PMID:26646868
NASA Astrophysics Data System (ADS)
Sazawa, Masaki; Ohishi, Kiyoshi; Katsura, Seiichiro
Continuous path tracking control is an important technology for the position control system such as factory automation field. Particulaly, large torque is required for continuous path tracking control at its start position and its goal position. Each AC servo motor of continuous path tracking control have limitation of current and voltage. Therefore, in controlling a multi-degree-of-freedom continuous path tracking control system, even if only the motor torque of one axis has the current limitation, the actual position response is not often equal to the desired trajectory reference. In order to overcome these problems, this paper proposes a new continuous path tracking control algorithm by considering both the saturation of voltage and current. The proposed method assures the coordinated motion by considering the saturation of voltage and current. The effectiveness of the proposed method is confirmed by the experimental results in this paper.
Critical Path-Based Thread Placement for NUMA Systems
Su, Chun-Yi; Li, Dong; Nikolopoulos, Dimitrios; Grove, Matthew; Cameron, Kirk W.; de Supinski, Bronis R.
2012-01-01
Multicore multiprocessors use Non Uniform Memory Architecture (NUMA) to improve their scalability. However,NUMA introduces performance penalties due to remote memory accesses. Without efficiently managing data layout and thread mapping to cores, scientific applications, even if they are optimized for NUMA, may suffer performance loss. In this paper, we present an algorithm that optimizes the placement of OpenMP threads on NUMA processors. By collecting information from hardware counters and defining new metrics to capture the effects of thread placement, the algorithm reduces NUMA performance penalty by minimizing the critical path of OpenMP parallel regions and by avoiding local memory resource contention. We evaluate our algorithm with NPB benchmarks and achieve performance improvement between 8.13% and 25.68%, compared to the OS default scheduling.
Automated Architectural Exploration for Signal Processing Algorithms
Davis, Rhett
Property (IP) cores for system level signal processing algorithms. We present our view of a framework generates the dedicated IP cores and estimates the performance such as area, critical path delay. A solution for mitigating the design process is providing open source IP cores and system-level synthesizers
600.363/463 Algorithms -Fall 2013 Solution to Assignment 9
Amir, Yair
be a sequence of vertices {v1, v2, Â· Â· Â· , vn}. An algorithm A(x, y) verifies HAM-PATH by executing. Therefore the verification algorithm runs in O(V 2) time. Hence HAM-PATH NP. 1 #12;34.3-2 Show that the P the certificate y be the indices {i1, i2, Â· Â· Â· , in}. An algorithm A(x, y) verifies GRAPH
Direction Finding Algorithm with Virtual Antenna Array Background
Arslan, Hüseyin
Direction Finding Algorithm with Virtual Antenna Array Background: Direction finding (DF) based on MUSIC algorithm has been studied and implemented in the wireless communications lab. Simulation results of multi-path, DOA of correlated signals, User separability ... MUSIC DF measurement setup Virtual
Obstacle Bypassing in Optimal Ship Routing Using Simulated Annealing
Kosmas, O. T.; Vlachos, D. S.; Simos, T. E.
2008-11-06
In this paper we are going to discuss a variation on the problem of finding the shortest path between two points in optimal ship routing problems consisting of obstacles that are not allowed to be crossed by the path. Our main goal are going to be the construction of an appropriate algorithm, based in an earlier work by computing the shortest path between two points in the plane that avoids a set of polygonal obstacles.
Path queries for Web data Path queries for Web data
databases, ubiquitous in transactional applications, websites etc. follow the relational model, representing data with a fixed structure. The recent spread of graph-structured data such as linked open data the structure of graph data. Unlike basic SQL queries over relational data, path queries allow to express
Path-dependent entropy production
NASA Astrophysics Data System (ADS)
Kwon, Chulan
2015-09-01
A rigorous derivation of nonequilibrium entropy production via the path-integral formalism is presented. Entropy production is defined as the entropy change piled in a heat reservoir as a result of a nonequilibrium thermodynamic process. It is a central quantity by which various forms of the fluctuation theorem are obtained. The two kinds of the stochastic dynamics are investigated: the Langevin dynamics for an even-parity state and the Brownian motion of a single particle. Mathematical ambiguities in deriving the functional form of the entropy production, which depends on path in state space, are clarified by using a rigorous quantum mechanical approach.
Multiple paths in complex tasks
NASA Technical Reports Server (NTRS)
Galanter, Eugene; Wiegand, Thomas; Mark, Gloria
1987-01-01
The relationship between utility judgments of subtask paths and the utility of the task as a whole was examined. The convergent validation procedure is based on the assumption that measurements of the same quantity done with different methods should covary. The utility measures of the subtasks were obtained during the performance of an aircraft flight controller navigation task. Analyses helped decide among various models of subtask utility combination, whether the utility ratings of subtask paths predict the whole tasks utility rating, and indirectly, whether judgmental models need to include the equivalent of cognitive noise.
Kinetic Constrained Optimization of the Golf Swing Hub Path
Nesbit, Steven M.; McGinnis, Ryan S.
2014-01-01
This study details an optimization of the golf swing, where the hand path and club angular trajectories are manipulated. The optimization goal was to maximize club head velocity at impact within the interaction kinetic limitations (force, torque, work, and power) of the golfer as determined through the analysis of a typical swing using a two-dimensional dynamic model. The study was applied to four subjects with diverse swing capabilities and styles. It was determined that it is possible for all subjects to increase their club head velocity at impact within their respective kinetic limitations through combined modifications to their respective hand path and club angular trajectories. The manner of the modifications, the degree of velocity improvement, the amount of kinetic reduction, and the associated kinetic limitation quantities were subject dependent. By artificially minimizing selected kinetic inputs within the optimization algorithm, it was possible to identify swing trajectory characteristics that indicated relative kinetic weaknesses of a subject. Practical implications are offered based upon the findings of the study. Key Points The hand path trajectory is an important characteristic of the golf swing and greatly affects club head velocity and golfer/club energy transfer. It is possible to increase the energy transfer from the golfer to the club by modifying the hand path and swing trajectories without increasing the kinetic output demands on the golfer. It is possible to identify relative kinetic output strengths and weakness of a golfer through assessment of the hand path and swing trajectories. Increasing any one of the kinetic outputs of the golfer can potentially increase the club head velocity at impact. The hand path trajectory has important influences over the club swing trajectory. PMID:25435779
Kinetic constrained optimization of the golf swing hub path.
Nesbit, Steven M; McGinnis, Ryan S
2014-12-01
This study details an optimization of the golf swing, where the hand path and club angular trajectories are manipulated. The optimization goal was to maximize club head velocity at impact within the interaction kinetic limitations (force, torque, work, and power) of the golfer as determined through the analysis of a typical swing using a two-dimensional dynamic model. The study was applied to four subjects with diverse swing capabilities and styles. It was determined that it is possible for all subjects to increase their club head velocity at impact within their respective kinetic limitations through combined modifications to their respective hand path and club angular trajectories. The manner of the modifications, the degree of velocity improvement, the amount of kinetic reduction, and the associated kinetic limitation quantities were subject dependent. By artificially minimizing selected kinetic inputs within the optimization algorithm, it was possible to identify swing trajectory characteristics that indicated relative kinetic weaknesses of a subject. Practical implications are offered based upon the findings of the study. Key PointsThe hand path trajectory is an important characteristic of the golf swing and greatly affects club head velocity and golfer/club energy transfer.It is possible to increase the energy transfer from the golfer to the club by modifying the hand path and swing trajectories without increasing the kinetic output demands on the golfer.It is possible to identify relative kinetic output strengths and weakness of a golfer through assessment of the hand path and swing trajectories.Increasing any one of the kinetic outputs of the golfer can potentially increase the club head velocity at impact.The hand path trajectory has important influences over the club swing trajectory. PMID:25435779
Sobel, E.; Lange, K.; O`Connell, J.R.
1996-12-31
Haplotyping is the logical process of inferring gene flow in a pedigree based on phenotyping results at a small number of genetic loci. This paper formalizes the haplotyping problem and suggests four algorithms for haplotype reconstruction. These algorithms range from exhaustive enumeration of all haplotype vectors to combinatorial optimization by simulated annealing. Application of the algorithms to published genetic analyses shows that manual haplotyping is often erroneous. Haplotyping is employed in screening pedigrees for phenotyping errors and in positional cloning of disease genes from conserved haplotypes in population isolates. 26 refs., 6 figs., 3 tabs.
Biclique-colouring powers of paths and powers of cycles
Filho, Hélio B Macêdo; Machado, Raphael C S; de Figueiredo, Celina M H
2012-01-01
Biclique-colouring is a colouring of the vertices of a graph in such a way that no maximal complete bipartite subgraph with at least one edge is monochromatic. We show that it is co$\\mathcal{NP}$-complete to check if a colouring of vertices is a valid biclique-colouring, a result that justifies the search for structured classes where the biclique-colouring problem could be efficiently solved. We consider biclique-colouring restricted to powers of paths and powers of cycles. We determine the biclique-chromatic number of powers of paths and powers of cycles. The biclique-chromatic number of a power of a path $P_{n}^{k}$ is $\\max(2k + 2 - n, 2)$ if $n \\geq k + 1$ and exactly $n$ otherwise. The biclique-chromatic number of a power of a cycle $C_n^k$ is at most 3 if $n \\geq 2k + 2$ and exactly $n$ otherwise; we additionally determine the powers of cycles that are 2-biclique-colourable. All the proofs are algorithmic and we provide polynomial-time biclique-colouring algorithms for graphs in the investigated classes...
Benchmarking Gas Path Diagnostic Methods: A Public Approach
NASA Technical Reports Server (NTRS)
Simon, Donald L.; Bird, Jeff; Davison, Craig; Volponi, Al; Iverson, R. Eugene
2008-01-01
Recent technology reviews have identified the need for objective assessments of engine health management (EHM) technology. The need is two-fold: technology developers require relevant data and problems to design and validate new algorithms and techniques while engine system integrators and operators need practical tools to direct development and then evaluate the effectiveness of proposed solutions. This paper presents a publicly available gas path diagnostic benchmark problem that has been developed by the Propulsion and Power Systems Panel of The Technical Cooperation Program (TTCP) to help address these needs. The problem is coded in MATLAB (The MathWorks, Inc.) and coupled with a non-linear turbofan engine simulation to produce "snap-shot" measurements, with relevant noise levels, as if collected from a fleet of engines over their lifetime of use. Each engine within the fleet will experience unique operating and deterioration profiles, and may encounter randomly occurring relevant gas path faults including sensor, actuator and component faults. The challenge to the EHM community is to develop gas path diagnostic algorithms to reliably perform fault detection and isolation. An example solution to the benchmark problem is provided along with associated evaluation metrics. A plan is presented to disseminate this benchmark problem to the engine health management technical community and invite technology solutions.
SSME propellant path leak detection
NASA Technical Reports Server (NTRS)
Crawford, Roger; Shohadaee, Ahmad Ali
1989-01-01
The complicated high-pressure cycle of the space shuttle main engine (SSME) propellant path provides many opportunities for external propellant path leaks while the engine is running. This mode of engine failure may be detected and analyzed with sufficient speed to save critical engine test hardware from destruction. The leaks indicate hardware failures which will damage or destroy an engine if undetected; therefore, detection of both cryogenic and hot gas leaks is the objective of this investigation. The primary objective of this phase of the investigation is the experimental validation of techniques for detecting and analyzing propellant path external leaks which have a high probability of occurring on the SSME. The selection of candidate detection methods requires a good analytic model for leak plumes which would develop from external leaks and an understanding of radiation transfer through the leak plume. One advanced propellant path leak detection technique is obtained by using state-of-the-art technology infrared (IR) thermal imaging systems combined with computer, digital image processing, and expert systems for the engine protection. The feasibility of IR leak plume detection is evaluated on subscale simulated laboratory plumes to determine sensitivity, signal to noise, and general suitability for the application.
Perceived Shrinkage of Motion Paths
ERIC Educational Resources Information Center
Sinico, Michele; Parovel, Giulia; Casco, Clara; Anstis, Stuart
2009-01-01
We show that human observers strongly underestimate a linear or circular trajectory that a luminous spot follows in the dark. At slow speeds, observers are relatively accurate, but, as the speed increases, the size of the path is progressively underestimated, by up to 35%. The underestimation imposes little memory load and does not require…
Immigration: Rubio's path to presidency?
Fernandez, Eduardo
Immigration: Rubio's path to presidency? In media blitz retorting conservative critics, he aims Writer Of the four Democratic and four Republican senators who wrote the immigration reform proposal now, both in Congress and nationwide, need more convincing on immigration reform than Democrats. And Rubio
Employer Resource Manual. Project Path.
ERIC Educational Resources Information Center
Kane, Karen R.; Del George, Eve
Project Path at Illinois' College of DuPage was established to provide pre-employment training and career counseling for disabled students. To encourage the integration of qualified individuals with disabilities into the workplace, the project compiled this resource manual for area businesses, providing tips for interacting with disabled people…
Career Paths in Environmental Sciences
Career paths, current and future, in the environmental sciences will be discussed, based on experiences and observations during the author's 40 + years in the field. An emphasis will be placed on the need for integrated, transdisciplinary systems thinking approaches toward achie...
Career Paths of Academic Deans.
ERIC Educational Resources Information Center
Wolverton, Mimi; Gonzales, Mary Jo
This paper examines various career paths leading to deanship and considers the implications of the findings for women and minorities who aspire to this position. The paper is part of a larger study of academic deanship conducted by the Center for Academic Leadership at Washington State University between October 1996 and January 1997. Data for the…
Live minimal path for interactive segmentation of medical images
NASA Astrophysics Data System (ADS)
Chartrand, Gabriel; Tang, An; Chav, Ramnada; Cresson, Thierry; Chantrel, Steeve; De Guise, Jacques A.
2015-03-01
Medical image segmentation is nowadays required for medical device development and in a growing number of clinical and research applications. Since dedicated automatic segmentation methods are not always available, generic and efficient interactive tools can alleviate the burden of manual segmentation. In this paper we propose an interactive segmentation tool based on image warping and minimal path segmentation that is efficient for a wide variety of segmentation tasks. While the user roughly delineates the desired organs boundary, a narrow band along the cursors path is straightened, providing an ideal subspace for feature aligned filtering and minimal path algorithm. Once the segmentation is performed on the narrow band, the path is warped back onto the original image, precisely delineating the desired structure. This tool was found to have a highly intuitive dynamic behavior. It is especially efficient against misleading edges and required only coarse interaction from the user to achieve good precision. The proposed segmentation method was tested for 10 difficult liver segmentations on CT and MRI images, and the resulting 2D overlap Dice coefficient was 99% on average..
John C. Baez; Mike Stay
2013-02-25
Algorithmic entropy can be seen as a special case of entropy as studied in statistical mechanics. This viewpoint allows us to apply many techniques developed for use in thermodynamics to the subject of algorithmic information theory. In particular, suppose we fix a universal prefix-free Turing machine and let X be the set of programs that halt for this machine. Then we can regard X as a set of 'microstates', and treat any function on X as an 'observable'. For any collection of observables, we can study the Gibbs ensemble that maximizes entropy subject to constraints on expected values of these observables. We illustrate this by taking the log runtime, length, and output of a program as observables analogous to the energy E, volume V and number of molecules N in a container of gas. The conjugate variables of these observables allow us to define quantities which we call the 'algorithmic temperature' T, 'algorithmic pressure' P and algorithmic potential' mu, since they are analogous to the temperature, pressure and chemical potential. We derive an analogue of the fundamental thermodynamic relation dE = T dS - P d V + mu dN, and use it to study thermodynamic cycles analogous to those for heat engines. We also investigate the values of T, P and mu for which the partition function converges. At some points on the boundary of this domain of convergence, the partition function becomes uncomputable. Indeed, at these points the partition function itself has nontrivial algorithmic entropy.
Relations between coherence and path information
Emilio Bagan; Janos A. Bergou; Seth S. Cottrell; Mark Hillery
2015-12-10
We find two relations between coherence and path-information in a multi-path interferometer. The first builds on earlier results for the two-path interferometer, which used minimum-error state discrimination between detector states to provide the path information. For visibility, which was used in the two-path case, we substitute a recently defined $l_{1}$ measure of quantum coherence. The second is an entropic relation in which the path information is characterized by the mutual information between the detector states and the outcome of the measurement performed on them, and the coherence measure is one based on relative entropy.
A Revised Trajectory Algorithm to Support En Route and Terminal Area Self-Spacing Concepts
NASA Technical Reports Server (NTRS)
Abbott, Terence S.
2010-01-01
This document describes an algorithm for the generation of a four dimensional trajectory. Input data for this algorithm are similar to an augmented Standard Terminal Arrival (STAR) with the augmentation in the form of altitude or speed crossing restrictions at waypoints on the route. This version of the algorithm accommodates descent Mach values that are different from the cruise Mach values. Wind data at each waypoint are also inputs into this algorithm. The algorithm calculates the altitude, speed, along path distance, and along path time for each waypoint.
Kinematics, controls, and path planning results for a redundant manipulator
NASA Technical Reports Server (NTRS)
Gretz, Bruce; Tilley, Scott W.
1989-01-01
The inverse kinematics solution, a modal position control algorithm, and path planning results for a 7 degree of freedom manipulator are presented. The redundant arm consists of two links with shoulder and elbow joints and a spherical wrist. The inverse kinematics problem for tip position is solved and the redundant joint is identified. It is also shown that a locus of tip positions exists in which there are kinematic limitations on self-motion. A computationally simple modal position control algorithm has been developed which guarantees a nearly constant closed-loop dynamic response throughout the workspace. If all closed-loop poles are assigned to the same location, the algorithm can be implemented with very little computation. To further reduce the required computation, the modal gains are updated only at discrete time intervals. Criteria are developed for the frequency of these updates. For commanding manipulator movements, a 5th-order spline which minimizes jerk provides a smooth tip-space path. Schemes for deriving a corresponding joint-space trajectory are discussed. Modifying the trajectory to avoid joint torque saturation when a tip payload is added is also considered. Simulation results are presented.
Reynolds, Andy M.; Dutta, Tushar K.; Curtis, Rosane H. C.; Powers, Stephen J.; Gaur, Hari S.; Kerry, Brian R.
2011-01-01
It has long been recognized that chemotaxis is the primary means by which nematodes locate host plants. Nonetheless, chemotaxis has received scant attention. We show that chemotaxis is predicted to take nematodes to a source of a chemo-attractant via the shortest possible routes through the labyrinth of air-filled or water-filled channels within a soil through which the attractant diffuses. There are just two provisos: (i) all of the channels through which the attractant diffuses are accessible to the nematodes and (ii) nematodes can resolve all chemical gradients no matter how small. Previously, this remarkable consequence of chemotaxis had gone unnoticed. The predictions are supported by experimental studies of the movement patterns of the root-knot nematodes Meloidogyne incognita and Meloidogyne graminicola in modified Y-chamber olfactometers filled with Pluronic gel. By providing two routes to a source of the attractant, one long and one short, our experiments, the first to demonstrate the routes taken by nematodes to plant roots, serve to test our predictions. Our data show that nematodes take the most direct route to their preferred hosts (as predicted) but often take the longest route towards poor hosts. We hypothesize that a complex of repellent and attractant chemicals influences the interaction between nematodes and their hosts. PMID:20880854
Image processing meta-algorithm development via genetic manipulation of existing algorithm graphs
NASA Astrophysics Data System (ADS)
Schalkoff, Robert J.; Shaaban, Khaled M.
1999-07-01
Automatic algorithm generation for image processing applications is not a new idea, however previous work is either restricted to morphological operates or impractical. In this paper, we show recent research result in the development and use of meta-algorithms, i.e. algorithms which lead to new algorithms. Although the concept is generally applicable, the application domain in this work is restricted to image processing. The meta-algorithm concept described in this paper is based upon out work in dynamic algorithm. The paper first present the concept of dynamic algorithms which, on the basis of training and archived algorithmic experience embedded in an algorithm graph (AG), dynamically adjust the sequence of operations applied to the input image data. Each node in the tree-based representation of a dynamic algorithm with out degree greater than 2 is a decision node. At these nodes, the algorithm examines the input data and determines which path will most likely achieve the desired results. This is currently done using nearest-neighbor classification. The details of this implementation are shown. The constrained perturbation of existing algorithm graphs, coupled with a suitable search strategy, is one mechanism to achieve meta-algorithm an doffers rich potential for the discovery of new algorithms. In our work, a meta-algorithm autonomously generates new dynamic algorithm graphs via genetic recombination of existing algorithm graphs. The AG representation is well suited to this genetic-like perturbation, using a commonly- employed technique in artificial neural network synthesis, namely the blueprint representation of graphs. A number of exam. One of the principal limitations of our current approach is the need for significant human input in the learning phase. Efforts to overcome this limitation are discussed. Future research directions are indicated.
Nir, Talia M; Villalon-Reina, Julio E; Prasad, Gautam; Jahanshad, Neda; Joshi, Shantanu H; Toga, Arthur W; Bernstein, Matt A; Jack, Clifford R; Weiner, Michael W; Thompson, Paul M
2015-01-01
Characterizing brain changes in Alzheimer's disease (AD) is important for patient prognosis and for assessing brain deterioration in clinical trials. In this diffusion weighted imaging study, we used a new fiber-tract modeling method to investigate white matter integrity in 50 elderly controls (CTL), 113 people with mild cognitive impairment, and 37 AD patients. After clustering tractography using a region-of-interest atlas, we used a shortest path graph search through each bundle's fiber density map to derive maximum density paths (MDPs), which we registered across subjects. We calculated the fractional anisotropy (FA) and mean diffusivity (MD) along all MDPs and found significant MD and FA differences between AD patients and CTL subjects, as well as MD differences between CTL and late mild cognitive impairment subjects. MD and FA were also associated with widely used clinical scores. As an MDP is a compact low-dimensional representation of white matter organization, we tested the utility of diffusion tensor imaging measures along these MDPs as features for support vector machine based classification of AD. PMID:25444597
Time optimal paths for high speed maneuvering
Reister, D.B.; Lenhart, S.M.
1993-01-01
Recent theoretical results have completely solved the problem of determining the minimum length path for a vehicle with a minimum turning radius moving from an initial configuration to a final configuration. Time optimal paths for a constant speed vehicle are a subset of the minimum length paths. This paper uses the Pontryagin maximum principle to find time optimal paths for a constant speed vehicle. The time optimal paths consist of sequences of axes of circles and straight lines. The maximum principle introduces concepts (dual variables, bang-bang solutions, singular solutions, and transversality conditions) that provide important insight into the nature of the time optimal paths. We explore the properties of the optimal paths and present some experimental results for a mobile robot following an optimal path.
Electron Inelastic-Mean-Free-Path Database
National Institute of Standards and Technology Data Gateway
SRD 71 NIST Electron Inelastic-Mean-Free-Path Database (PC database, no charge) This database provides values of electron inelastic mean free paths (IMFPs) for use in quantitative surface analyses by AES and XPS.
Efficient enumeration of monocyclic chemical graphs with given path frequencies
2014-01-01
Background The enumeration of chemical graphs (molecular graphs) satisfying given constraints is one of the fundamental problems in chemoinformatics and bioinformatics because it leads to a variety of useful applications including structure determination and development of novel chemical compounds. Results We consider the problem of enumerating chemical graphs with monocyclic structure (a graph structure that contains exactly one cycle) from a given set of feature vectors, where a feature vector represents the frequency of the prescribed paths in a chemical compound to be constructed and the set is specified by a pair of upper and lower feature vectors. To enumerate all tree-like (acyclic) chemical graphs from a given set of feature vectors, Shimizu et al. and Suzuki et al. proposed efficient branch-and-bound algorithms based on a fast tree enumeration algorithm. In this study, we devise a novel method for extending these algorithms to enumeration of chemical graphs with monocyclic structure by designing a fast algorithm for testing uniqueness. The results of computational experiments reveal that the computational efficiency of the new algorithm is as good as those for enumeration of tree-like chemical compounds. Conclusions We succeed in expanding the class of chemical graphs that are able to be enumerated efficiently. PMID:24955135
Path-independent digital image correlation with high accuracy, speed and robustness
NASA Astrophysics Data System (ADS)
Jiang, Zhenyu; Kemao, Qian; Miao, Hong; Yang, Jinglei; Tang, Liqun
2015-02-01
The initial guess transferring mechanism is widely used in iterative DIC algorithms and leads to path-dependence. Using the known deformation at a processed point to estimate the initial guess at its neighboring points could save considerable computation time, and a cogitatively-selected processing path contributes to the improved robustness. In this work, our experimental study demonstrates that a path-independent DIC method is capable to achieve high accuracy, efficiency and robustness in full-field measurement of deformation, by combining an inverse compositional Gauss-Newton (IC-GN) algorithm for sub-pixel registration with a fast Fourier transform-based cross correlation (FFT-CC) algorithm to estimate the initial guess. In the proposed DIC method, the determination of initial guess accelerated by well developed software library can be a negligible burden of computation. The path-independence also endows the DIC method with the ability to handle the images containing large discontinuity of deformation without manual intervention. Furthermore, the possible performance of the proposed path-independent DIC method on parallel computing device is estimated, which shows the feasibility of the development of real-time DIC with high-accuracy.
NASA Astrophysics Data System (ADS)
Boz, Utku; Basdogan, Ipek
2015-12-01
Structural vibrations is a major cause for noise problems, discomfort and mechanical failures in aerospace, automotive and marine systems, which are mainly composed of plate-like structures. In order to reduce structural vibrations on these structures, active vibration control (AVC) is an effective approach. Adaptive filtering methodologies are preferred in AVC due to their ability to adjust themselves for varying dynamics of the structure during the operation. The filtered-X LMS (FXLMS) algorithm is a simple adaptive filtering algorithm widely implemented in active control applications. Proper implementation of FXLMS requires availability of a reference signal to mimic the disturbance and model of the dynamics between the control actuator and the error sensor, namely the secondary path. However, the controller output could interfere with the reference signal and the secondary path dynamics may change during the operation. This interference problem can be resolved by using an infinite impulse response (IIR) filter which considers feedback of the one or more previous control signals to the controller output and the changing secondary path dynamics can be updated using an online modeling technique. In this paper, IIR filtering based filtered-U LMS (FULMS) controller is combined with online secondary path modeling algorithm to suppress the vibrations of a plate-like structure. The results are validated through numerical and experimental studies. The results show that the FULMS with online secondary path modeling approach has more vibration rejection capabilities with higher convergence rate than the FXLMS counterpart.
Spacetime path formalism: localized states
Ed Seidewitz
2010-11-14
This note is an addendum to quant-ph/0507115. In that paper, I present a formalism for relativistic quantum mechanics in which the spacetime paths of particles are considered fundamental, reproducing the standard results of the traditional formulation of relativistic quantum mechanics and quantum field theory. Now, it is well known that there are issues with the ability to localize the position of particles in the usual formulation of relativistic quantum mechanics. The present note shows how, in the spacetime path formalism, the natural representation of on-shell 3-momentum states is effectively a Foldy-Wouthuysen transformation of the traditional representation, addressing the localization issues of position states and, further, providing a straightforward non-relativistic limit.
Multiple Paths to Encephalization and Technical Civilizations
NASA Astrophysics Data System (ADS)
Schwartzman, David; Middendorf, George
2011-12-01
We propose consideration of at least two possible evolutionary paths for the emergence of intelligent life with the potential for technical civilization. The first is the path via encephalization of homeothermic animals; the second is the path to swarm intelligence of so-called superorganisms, in particular the social insects. The path to each appears to be facilitated by environmental change: homeothermic animals by decreased climatic temperature and for swarm intelligence by increased oxygen levels.
Squeezed states and path integrals
NASA Technical Reports Server (NTRS)
Daubechies, Ingrid; Klauder, John R.
1992-01-01
The continuous-time regularization scheme for defining phase-space path integrals is briefly reviewed as a method to define a quantization procedure that is completely covariant under all smooth canonical coordinate transformations. As an illustration of this method, a limited set of transformations is discussed that have an image in the set of the usual squeezed states. It is noteworthy that even this limited set of transformations offers new possibilities for stationary phase approximations to quantum mechanical propagators.
Continuous Path Planning with Multiple Constraints
Mitchell, Ian
Continuous Path Planning with Multiple Constraints Ian M. Mitchell and Shankar Sastry Department examine the problem of planning a path through a low di- mensional continuous state space subject to upper Few problems are as well studied as the path planning or routing prob- lem; it appears in engineering
Evaluation of the Learning Path Specification
ERIC Educational Resources Information Center
Janssen, Jose; Berlanga, Adriana J.; Koper, Rob
2011-01-01
Flexible lifelong learning requires that learners can compare and select learning paths that best meet individual needs, not just in terms of learning goals, but also in terms of planning, costs etc. To this end a learning path specification was developed, which describes both the contents and the structure of any learning path, be it formal,…
Analogical Path Planning Saul Simhon, Gregory Dudek
Dudek, Gregory
Analogical Path Planning Saul Simhon, Gregory Dudek Centre for Intelligent Machines Mc for path planning that considers trajectories constrained by both the environment and an ensemble of the path, and planning in the presence of such constraints in often difficult (an automobile
Clearance Based Path Optimization for Motion Planning
Utrecht, Universiteit
Clearance Based Path Optimization for Motion Planning Roland Geraerts Mark Overmars institute;Clearance Based Path Optimization for Motion Planning Roland Geraerts Mark Overmars Institute of Information to generate paths of a much higher quality than previous approaches. 1 Introduction Motion planning can
Clearance Based Path Optimization for Motion Planning
Utrecht, Universiteit
Clearance Based Path Optimization for Motion Planning Roland Geraerts Mark Overmars institute; Clearance Based Path Optimization for Motion Planning Roland Geraerts Mark Overmars Institute of Information to generate paths of a much higher quality than previous approaches. 1 Introduction Motion planning can
CALIFORNIA PATH PROGRAM INSTITUTE OF TRANSPORTATION STUDIES
Agogino, Alice M.
CALIFORNIA PATH PROGRAM INSTITUTE OF TRANSPORTATION STUDIES UNIVERFITY OF CALIFORNIA, BERKELEY Agogino, Kai Goebel SatnamAlag University of California,Berkeley CaliforniaPATH Research Report UCB-ITS-PRR-97-31 This work was performed as part of the CaliforniaPATH Program of the University of California
Universal Path Spaces W. A. Bogley
Universal Path Spaces W. A. Bogley Oregon State University A. J. Sieradski University of Oregon Abstract This paper examines a theory of universal path spaces that properly includes the covering space is a wild metric 2-complex, the universal path space is simply connected if and only if the fundamental
Robust, common path, phase shifting interferometer and optical profilometer
Tumbar, Remy; Marks, Daniel L.; Brady, David J
2008-04-01
We describe an improved implementation of our previously reported common-path, phase shifting, and shearing interferometer. Using a time-multiplexed phase shifting scheme, we demonstrate higher sampling resolution, better light sensitivity, and use of arbitrary phase shifting algorithms. We describe microscopic imaging of the surface profile of a copper-plated silicon wafer and demonstrate that the system is vibration insensitive with {approx}{lambda}/100repeatability. In a more general discussion of our method, we describe the different functional elements and suggest alternative designs and improvements. Possible uses include full-field coherent imaging and high dynamic range wavefront sensing, which we briefly discuss.
Computing LS factor by runoff paths on TIN
NASA Astrophysics Data System (ADS)
Kavka, Petr; Krasa, Josef; Bek, Stanislav
2013-04-01
The article shows results of topographic factor (the LS factor in USLE) derivation enhancement focused on detailed Airborne Laser Scanning (ALS) based DEMs. It describes a flow paths generation technique using triangulated irregular network (TIN) for terrain morphology description, which is not yet established in soil loss computations. This technique was compared with other procedures of flow direction and flow paths generation based on commonly used raster model (DEM). These overland flow characteristics together with therefrom derived flow accumulation are significant inputs for many scientific models. Particularly they are used in all USLE-based soil erosion models, from which USLE2D, RUSLE3D, Watem/Sedem or USPED can be named as the most acknowledged. Flow routing characteristics are also essential parameters in physically based hydrological and soil erosion models like HEC-HMS, Wepp, Erosion3D, LISEM, SMODERP, etc. Mentioned models are based on regular raster grids, where the identification of runoff direction is problematic. The most common method is Steepest descent (one directional flow), which corresponds well with the concentration of surface runoff into concentrated flow. The Steepest descent algorithm for the flow routing doesn't provide satisfying results, it often creates parallel and narrow flow lines while not respecting real morphological conditions. To overcome this problem, other methods (such as Flux Decomposition, Multiple flow, Deterministic Infinity algorithm etc.) separate the outflow into several components. This approach leads to unrealistic diffusion propagation of the runoff and makes it impossible to be used for simulation of dominant morphological features, such as artificial rills, hedges, sediment traps etc. The modern methods of mapping ground elevations, especially ALS, provide very detailed models even for large river basins, including morphological details. New algorithms for derivation a runoff direction have been developed as a part of the Atlas DMT software package. Starting points for the flow direction generation remain in regular grid (allowing easy contributing area assessment) while realistic direction paths are generated directly at TIN. It turns out that this procedure allows predicting actual runoff paths while ensuring the continuity of the potential runoff by sophisticated filling of sinks and flats. The algorithm is being implemented in a new USLE based erosion model ATLAS EROSION aiming to enhance designing of technical (morphological) soil erosion measures using detailed DEMs. The research has been supported by the research project No. TA02020647 " Atlas EROZE - a modern tool for soil erosion assessment".
Context-and Path-sensitive Memory Leak Detection Yichen Xie Alex Aiken
Aiken, Alex
detection system known to us. · Our memory leak checker is computationally intensive. Analysis of more thanContext- 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
The Path Inference Filter: Model-Based Low-Latency Map Matching of Probe
and 2 minutes. We introduce a new class of algorithms, collectively called path inference filter (PIF, the progressive integration of smart- phones and car infrastructure, the rise of Web 2.0, and the progressive emer this data sparse. In particular, it is very common common today for GPS traces to be sampled at very low
The path inference filter: model-based low-latency map matching of probe
Abbeel, Pieter
and 2 minutes. We introduce a new class of algorithms, collectively called path inference filter (PIF integration of smart- phones and car infrastructure, the rise of Web 2.0, and the progressive emer- gence. In particular, it is very common common today for GPS traces to be sampled at very low frequencies (on the order
NASA Astrophysics Data System (ADS)
Wang, Po-Jen; Keyawa, Nicholas R.; Euler, Craig
2012-01-01
In order to achieve highly accurate motion control and path planning for a mobile robot, an obstacle avoidance algorithm that provided a desired instantaneous turning radius and velocity was generated. This type of obstacle avoidance algorithm, which has been implemented in California State University Northridge's Intelligent Ground Vehicle (IGV), is known as Radial Polar Histogram (RPH). The RPH algorithm utilizes raw data in the form of a polar histogram that is read from a Laser Range Finder (LRF) and a camera. A desired open block is determined from the raw data utilizing a navigational heading and an elliptical approximation. The left and right most radii are determined from the calculated edges of the open block and provide the range of possible radial paths the IGV can travel through. In addition, the calculated obstacle edge positions allow the IGV to recognize complex obstacle arrangements and to slow down accordingly. A radial path optimization function calculates the best radial path between the left and right most radii and is sent to motion control for speed determination. Overall, the RPH algorithm allows the IGV to autonomously travel at average speeds of 3mph while avoiding all obstacles, with a processing time of approximately 10ms.
Improving Performance of Deterministic Single-path Routing on 2-Level Generalized Fat-trees
Yuan, Xin
Improving Performance of Deterministic Single-path Routing on 2-Level Generalized Fat-trees Wickus on 2-level generalized fat-trees. We develop a routing algorithm that is optimal in terms of worst permutation patterns, and dissemination (Bruck) patterns on various 2-level generalized fat
Influence of Legibility on Perceived Safety in a Virtual Human-Robot Path Crossing Task
Hirche, Sandra
in first person perspective. The robot is moving with two different navigation algorithms which allows us: Perceived Safety describes the user's perception of the level of danger when interacting with a robotInfluence of Legibility on Perceived Safety in a Virtual Human-Robot Path Crossing Task Christina
Exploiting The Path Of Least Resistance In Evolution Gearoid Murphy and Conor Ryan
Fernandez, Thomas
Exploiting The Path Of Least Resistance In Evolution Gearoid Murphy and Conor Ryan Biocomputing as it traverses the expression space. Unfortunately, it sometimes makes the wrong decision, resulting analysis of this selection method and produce a new algorithm for controlling evolution, one which can ef
Computer correction of turbulent distortions of image of extended objects on near-Earth paths
Averin, A P; Morozov, Yu B; Pryanichkov, V S; Tyapin, V V
2011-05-31
An algorithm of computer-based correction of images of extended objects distorted by turbulent atmosphere is developed. The method of computer correction is used to correct a distorted image of an extended object on a horizontal 2300-m-long observation path. The angular size of the corrected-image region was 15'. (image processing)
NASA Technical Reports Server (NTRS)
Goldhirsh, J.
1978-01-01
Yearly, monthly, and time of day fade statistics are presented and characterized. A 19.04 GHz yearly fade distribution, corresponding to a second COMSTAR beacon frequency, is predicted using the concept of effective path length, disdrometer, and rain rate results. The yearly attenuation and rain rate distributions follow with good approximation log normal variations for most fade and rain rate levels. Attenuations were exceeded for the longest and shortest periods of times for all fades in August and February, respectively. The eight hour time period showing the maximum and minimum number of minutes over the year for which fades exceeded 12 db were approximately between 1600 to 2400, and 0400 to 1200 hours, respectively. In employing the predictive method for obtaining the 19.04 GHz fade distribution, it is demonstrated theoretically that the ratio of attenuations at two frequencies is minimally dependent of raindrop size distribution providing these frequencies are not widely separated.
Booth, Thomas E; Gubernatis, James E
2008-01-01
We present a procedure that in many cases enables the Monte Carlo sampling of states of a large system from the sampling of states of a smaller system. We illustrate this procedure, which we call the sewing algorithm, for sampling states from the transfer matrix of the two-dimensional Ising model.
THE SHORTEST PERIOD sdB PLUS WHITE DWARF BINARY CD-30 11223 (GALEX J1411-3053)
Vennes, S.; Kawka, A.; Nemeth, P.; O'Toole, S. J.; Burton, D.
2012-11-01
We report on the discovery of the shortest period binary comprising a hot subdwarf star (CD-30 11223, GALEX J1411-3053) and a massive unseen companion. Photometric data from the All Sky Automated Survey show ellipsoidal variations of the hot subdwarf primary and spectroscopic series revealed an orbital period of 70.5 minutes. The large velocity amplitude suggests the presence of a massive white dwarf in the system (M{sub 2}/M{sub Sun} {approx}> 0.77) assuming a canonical mass for the hot subdwarf (0.48 M{sub Sun }), although a white dwarf mass as low as 0.75 M{sub Sun} is allowable by postulating a subdwarf mass as low as 0.44 M{sub Sun }. The amplitude of ellipsoidal variations and a high rotation velocity imposed a high-inclination to the system (i {approx}> 68 Degree-Sign ) and, possibly, observable secondary transits (i {approx}> 74 Degree-Sign ). At the lowest permissible inclination and assuming a subdwarf mass of {approx}0.48 M{sub Sun }, the total mass of the system reaches the Chandrasekhar mass limit at 1.35 M{sub Sun} and would exceed it for a subdwarf mass above 0.48 M{sub Sun }. The system should be considered, like its sibling KPD 1930+2752, a candidate progenitor for a Type Ia supernova. The system should become semi-detached and initiate mass transfer within Almost-Equal-To 30 Myr.
Path planning method for UUV homing and docking in movement disorders environment.
Yan, Zheping; Deng, Chao; Chi, Dongnan; Chen, Tao; Hou, Shuping
2014-01-01
Path planning method for unmanned underwater vehicles (UUV) homing and docking in movement disorders environment is proposed in this paper. Firstly, cost function is proposed for path planning. Then, a novel particle swarm optimization (NPSO) is proposed and applied to find the waypoint with minimum value of cost function. Then, a strategy for UUV enters into the mother vessel with a fixed angle being proposed. Finally, the test function is introduced to analyze the performance of NPSO and compare with basic particle swarm optimization (BPSO), inertia weight particle swarm optimization (LWPSO, EPSO), and time-varying acceleration coefficient (TVAC). It has turned out that, for unimodal functions, NPSO performed better searching accuracy and stability than other algorithms, and, for multimodal functions, the performance of NPSO is similar to TVAC. Then, the simulation of UUV path planning is presented, and it showed that, with the strategy proposed in this paper, UUV can dodge obstacles and threats, and search for the efficiency path. PMID:25054169
The reaction path intrinsic reaction coordinate method and the Hamilton-Jacobi theory.
Crehuet, Ramon; Bofill, Josep Maria
2005-06-15
The definition and location of an intrinsic reaction coordinate path is of crucial importance in many areas of theoretical chemistry. Differential equations used to define the path hitherto are complemented in this study with a variational principle of Fermat type, as Fukui [Int. J. Quantum Chem., Quantum Chem. Symp. 15, 633 (1981)] reported in a more general form some time ago. This definition is more suitable for problems where initial and final points are given. The variational definition can naturally be recast into a Hamilton-Jacobi equation. The character of the variational solution is studied via the Weierstrass necessary and sufficient conditions. The characterization of the local minima character of the intrinsic reaction coordinate is proved. Such result leads to a numerical algorithm to find intrinsic reaction coordinate paths based on the successive minimizations of the Weierstrass E-function evaluated on a guess curve connecting the initial and final points of the desired path. PMID:16008428
Path Planning Method for UUV Homing and Docking in Movement Disorders Environment
Yan, Zheping; Deng, Chao; Chi, Dongnan; Hou, Shuping
2014-01-01
Path planning method for unmanned underwater vehicles (UUV) homing and docking in movement disorders environment is proposed in this paper. Firstly, cost function is proposed for path planning. Then, a novel particle swarm optimization (NPSO) is proposed and applied to find the waypoint with minimum value of cost function. Then, a strategy for UUV enters into the mother vessel with a fixed angle being proposed. Finally, the test function is introduced to analyze the performance of NPSO and compare with basic particle swarm optimization (BPSO), inertia weight particle swarm optimization (LWPSO, EPSO), and time-varying acceleration coefficient (TVAC). It has turned out that, for unimodal functions, NPSO performed better searching accuracy and stability than other algorithms, and, for multimodal functions, the performance of NPSO is similar to TVAC. Then, the simulation of UUV path planning is presented, and it showed that, with the strategy proposed in this paper, UUV can dodge obstacles and threats, and search for the efficiency path. PMID:25054169
Processor Would Find Best Paths On Map
NASA Technical Reports Server (NTRS)
Eberhardt, Silvio P.
1990-01-01
Proposed very-large-scale integrated (VLSI) circuit image-data processor finds path of least cost from specified origin to any destination on map. Cost of traversal assigned to each picture element of map. Path of least cost from originating picture element to every other picture element computed as path that preserves as much as possible of signal transmitted by originating picture element. Dedicated microprocessor at each picture element stores cost of traversal and performs its share of computations of paths of least cost. Least-cost-path problem occurs in research, military maneuvers, and in planning routes of vehicles.
Mechanics of the crack path formation
NASA Technical Reports Server (NTRS)
Rubinstein, Asher A.
1989-01-01
A detailed analysis of experimentally obtained curvilinear crack path trajectories formed in a heterogeneous stress field is presented. Experimental crack path trajectories were used as data for numerical simulations, recreating the actual stress field governing the development of the crack path. Thus, the current theories of crack curving and kinking could be examined by comparing them with the actual stress field parameters as they develop along the experimentally observed crack path. The experimental curvilinear crack path trajectories were formed in the tensile specimens with a hole positioned in the vicinity of a potential crack path. The numerical simulation, based on the solution of equivalent boundary value problems with the possible perturbations of the crack path, is presented here.
Arithmetic area for m planar Brownian paths
NASA Astrophysics Data System (ADS)
Desbois, Jean; Ouvry, Stéphane
2012-05-01
We pursue the analysis made in Desbois and Ouvry (2011 J. Stat. Mech. P05024) on the arithmetic area enclosed by m closed Brownian paths. We pay particular attention to the random variable Sn1, n2,..., nm(m), which is the arithmetic area of the set of points, also called winding sectors, enclosed n1 times by path 1, n2 times by path 2,..., and nm times by path m. Various results are obtained in the asymptotic limit m\\to \\infty . A key observation is that, since the paths are independent, one can use in the m-path case the SLE information, valid in the one-path case, on the zero-winding sectors arithmetic area.
Path planning for assembly of strut-based structures. Thesis
NASA Technical Reports Server (NTRS)
Muenger, Rolf
1991-01-01
A path planning method with collision avoidance for a general single chain nonredundant or redundant robot is proposed. Joint range boundary overruns are also avoided. The result is a sequence of joint vectors which are passed to a trajectory planner. A potential field algorithm in joint space computes incremental joint vectors delta-q = delta-q(sub a) + delta-q(sub c) + delta-q(sub r). Adding delta-q to the robot's current joint vector leads to the next step in the path. Delta-q(sub a) is obtained by computing the minimum norm solution of the underdetermined linear system J delta-q(sub a) = x(sub a) where x(sub a) is a translational and rotational force vector that attracts the robot to its goal position and orientation. J is the manipulator Jacobian. Delta-q(sub c) is a collision avoidance term encompassing collisions between the robot (links and payload) and obstacles in the environment as well as collisions among links and payload of the robot themselves. It is obtained in joint space directly. Delta-q(sub r) is a function of the current joint vector and avoids joint range overruns. A higher level discrete search over candidate safe positions is used to provide alternatives in case the potential field algorithm encounters a local minimum and thus fails to reach the goal. The best first search algorithm A* is used for graph search. Symmetry properties of the payload and equivalent rotations are exploited to further enlarge the number of alternatives passed to the potential field algorithm.
Data Resource Profile: Pathways to Health and Social Equity for Children (PATHS Equity for Children)
Nickel, Nathan C; Chateau, Dan G; Martens, Patricia J; Brownell, Marni D; Katz, Alan; Burland, Elaine MJ; Walld, Randy; Hu, Mingming; Taylor, Carole R; Sarkar, Joykrishna; Goh, Chun Yan
2014-01-01
The PATHS Data Resource is a unique database comprising data that follow individuals from the prenatal period to adulthood. The PATHS Resource was developed for conducting longitudinal epidemiological research into child health and health equity. It contains individual-level data on health, socioeconomic status, social services and education. Individuals’ data are linkable across these domains, allowing researchers to follow children through childhood and across a variety of sectors. PATHS includes nearly all individuals that were born between 1984 and 2012 and registered with Manitoba’s universal health insurance programme at some point during childhood. All PATHS data are anonymized. Key concepts, definitions and algorithms necessary to work with the PATHS Resource are freely accessible online and an interactive forum is available to new researchers working with these data. The PATHS Resource is one of the richest and most complete databases assembled for conducting longitudinal epidemiological research, incorporating many variables that address the social determinants of health and health equity. Interested researchers are encouraged to contact [mchp_access@cpe.umanitoba.ca] to obtain access to PATHS to use in their own programmes of research. PMID:25212478
Least expected time paths in stochastic, time-varying transportation networks
Miller-Hooks, E.D.; Mahmassani, H.S.
1999-06-01
The authors consider stochastic, time-varying transportation networks, where the arc weights (arc travel times) are random variables with probability distribution functions that vary with time. Efficient procedures are widely available for determining least time paths in deterministic networks. In stochastic but time-invariant networks, least expected time paths can be determined by setting each random arc weight to its expected value and solving an equivalent deterministic problem. This paper addresses the problem of determining least expected time paths in stochastic, time-varying networks. Two procedures are presented. The first procedure determines the a priori least expected time paths from all origins to a single destination for each departure time in the peak period. The second procedure determines lower bounds on the expected times of these a priori least expected time paths. This procedure determines an exact solution for the problem where the driver is permitted to react to revealed travel times on traveled links en route, i.e. in a time-adaptive route choice framework. Modifications to each of these procedures for determining least expected cost (where cost is not necessarily travel time) paths and lower bounds on the expected costs of these paths are given. Extensive numerical tests are conducted to illustrate the algorithms` computational performance as well as the properties of the solution.
Characterizing the Evolutionary Path(s) to Early Homo
Schroeder, Lauren; Roseman, Charles C.; Cheverud, James M.; Ackermann, Rebecca R.
2014-01-01
Numerous studies suggest that the transition from Australopithecus to Homo was characterized by evolutionary innovation, resulting in the emergence and coexistence of a diversity of forms. However, the evolutionary processes necessary to drive such a transition have not been examined. Here, we apply statistical tests developed from quantitative evolutionary theory to assess whether morphological differences among late australopith and early Homo species in Africa have been shaped by natural selection. Where selection is demonstrated, we identify aspects of morphology that were most likely under selective pressure, and determine the nature (type, rate) of that selection. Results demonstrate that selection must be invoked to explain an Au. africanus—Au. sediba—Homo transition, while transitions from late australopiths to various early Homo species that exclude Au. sediba can be achieved through drift alone. Rate tests indicate that selection is largely directional, acting to rapidly differentiate these taxa. Reconstructions of patterns of directional selection needed to drive the Au. africanus—Au. sediba—Homo transition suggest that selection would have affected all regions of the skull. These results may indicate that an evolutionary path to Homo without Au. sediba is the simpler path and/or provide evidence that this pathway involved more reliance on cultural adaptations to cope with environmental change. PMID:25470780
A simple way to improve path consistency processing in interval algebra networks
Bessiere, C.
1996-12-31
Reasoning about qualitative temporal information is essential in many artificial intelligence problems. In particular, many tasks can be solved using the interval-based temporal algebra introduced by Allen (A1183). In this framework, one of the main tasks is to compute the transitive closure of a network of relations between intervals (also called path consistency in a CSP-like terminology). Almost all previous path consistency algorithms proposed in the temporal reasoning literature were based on the constraint reasoning algorithms PC-1 and PC-2 (Mac77). In this paper, we first show that the most efficient of these algorithms is the one which stays the closest to PC-2. Afterwards, we propose a new algorithm, using the idea {open_quotes}one support is sufficient{close_quotes} (as AC-3 (Mac77) does for arc consistency in constraint networks). Actually, to apply this idea, we simply changed the way composition-intersection of relations was achieved during the path consistency process in previous algorithms.
Transition paths of Met-enkephalin from Markov state modeling of a molecular dynamics trajectory.
Banerjee, Rahul; Cukier, Robert I
2014-03-20
Conformational states and their interconversion pathways of the zwitterionic form of the pentapeptide Met-enkephalin (MetEnk) are identified. An explicit solvent molecular dynamics (MD) trajectory is used to construct a Markov state model (MSM) based on dihedral space clustering of the trajectory, and transition path theory (TPT) is applied to identify pathways between open and closed conformers. In the MD trajectory, only four of the eight backbone dihedrals exhibit bistable behavior. Defining a conformer as the string XXXX with X = "+" or "-" denoting, respectively, positive or negative values of a given dihedral angle and obtaining the populations of these conformers shows that only four conformers are highly populated, implying a strong correlation among these dihedrals. Clustering in dihedral space to construct the MSM finds the same four bistable dihedral angles. These state populations are very similar to those found directly from the MD trajectory. TPT is used to obtain pathways, parametrized by committor values, in dihedral state space that are followed in transitioning from closed to open states. Pathway costs are estimated by introducing a kinetics-based procedure that orders pathways from least (shortest) to greater cost paths. The least costly pathways in dihedral space are found to only involve the same XXXX set of dihedral angles, and the conformers accessed in the closed to open transition pathways are identified. For these major pathways, a correlation between reaction path progress (committors) and the end-to-end distance is identified. A dihedral space principal component analysis of the MD trajectory shows that the first three modes capture most of the overall fluctuation, and pick out the same four dihedrals having essentially all the weight in those modes. A MSM based on root-mean-square backbone clustering was also carried out, with good agreement found with dihedral clustering for the static information, but with results that differ significantly for the pathway analysis. PMID:24571787
Multiple order common path spectrometer
NASA Technical Reports Server (NTRS)
Newbury, Amy B. (Inventor)
2010-01-01
The present invention relates to a dispersive spectrometer. The spectrometer allows detection of multiple orders of light on a single focal plane array by splitting the orders spatially using a dichroic assembly. A conventional dispersion mechanism such as a defraction grating disperses the light spectrally. As a result, multiple wavelength orders can be imaged on a single focal plane array of limited spectral extent, doubling (or more) the number of spectral channels as compared to a conventional spectrometer. In addition, this is achieved in a common path device.
Communication path for extreme environments
NASA Technical Reports Server (NTRS)
Jorgensen, Charles C. (Inventor); Betts, Bradley J. (Inventor)
2010-01-01
Methods and systems for using one or more radio frequency identification devices (RFIDs), or other suitable signal transmitters and/or receivers, to provide a sensor information communication path, to provide location and/or spatial orientation information for an emergency service worker (ESW), to provide an ESW escape route, to indicate a direction from an ESW to an ES appliance, to provide updated information on a region or structure that presents an extreme environment (fire, hazardous fluid leak, underwater, nuclear, etc.) in which an ESW works, and to provide accumulated thermal load or thermal breakdown information on one or more locations in the region.
Contemporary data path design optimization
Liu, Jianhua
2006-01-01
FPGA device [34], and compare the implementation with a division IP coreIP core (no DSP) PST (DSP) PST (no DSP) PSTp (DSP) PSTp (no DSP) Table V.3 FPGAFPGA applications, The PST algorithm also shows signi?cant delay and power reduction comparing with current division IP core
Planning Paths Through Singularities in the Center of Mass Space
NASA Technical Reports Server (NTRS)
Doggett, William R.; Messner, William C.; Juang, Jer-Nan
1998-01-01
The center of mass space is a convenient space for planning motions that minimize reaction forces at the robot's base or optimize the stability of a mechanism. A unique problem associated with path planning in the center of mass space is the potential existence of multiple center of mass images for a single Cartesian obstacle, since a single center of mass location can correspond to multiple robot joint configurations. The existence of multiple images results in a need to either maintain multiple center of mass obstacle maps or to update obstacle locations when the robot passes through a singularity, such as when it moves from an elbow-up to an elbow-down configuration. To illustrate the concepts presented in this paper, a path is planned for an example task requiring motion through multiple center of mass space maps. The object of the path planning algorithm is to locate the bang- bang acceleration profile that minimizes the robot's base reactions in the presence of a single Cartesian obstacle. To simplify the presentation, only non-redundant robots are considered and joint non-linearities are neglected.
Path Query Processing in Large-Scale XML Databases
NASA Astrophysics Data System (ADS)
Haw, Su-Cheng; Radha Krishna Rao, G. S. V.
With the ever-increasing popularity of XML (e-Xtensible Markup Language) as data representation and exchange on the Internet, querying XML data has become an important issue to be address. In Native XML Database (NXD), XML documents are usually modeled as trees and XML queries are typically specified in path expression. In path expression, the primitive structural relationships are Parent-Child (P-C) and Ancestor-Descendant (A-D). Thus, finding all occurrences of these relationships is crucial for XML query processing. Current methods for query processing on NXD usually employ either sequential traversing of tree-structured model or a decomposition-matching-merging processes. We adopt the later approach and propose a novel hybrid query optimization technique, INLAB comprising both indexing and labeling technologies. Furthermore, we also propose several algorithms to create INLAB encoding and analyze the path query. We implemented our technique and present performance results over several benchmarking datasets, which prove the viability of our approach.
SSME propellant path leak detection
NASA Technical Reports Server (NTRS)
Crawford, Roger; Shohadaee, Ahmad Ali; Powers, W. T.
1995-01-01
The primary objective of this phase of the investigation is the experimental validation of techniques for detecting and analyzing propellant path external leaks which have a high probability of occurring on the SSME. The selection of candidate detection methods requires a good analytic model for leak plumes which would develop from external leaks and an understanding of radiation transfer through the leak plume. One advanced propellant path leak detection technique is obtained by using state-of-art technology of infrared (IR) thermal imaging systems combined with computer, digital image processing and expert systems for the engine protection. The feasibility of the IR leak plume detection will be evaluated on subscale simulated laboratory plumes to determine sensitivity, signal to noise, and general suitability for the application. The theoretical analysis was undertaken with the objective of developing and testing simple, easy-to-use models to predict the amount of radiation coming from a radiation source, background plate (BP), which can be absorbed, emitted and scattered by the gas leaks.
A Trajectory Algorithm to Support En Route and Terminal Area Self-Spacing Concepts: Third Revision
NASA Technical Reports Server (NTRS)
Abbott, Terence S.
2012-01-01
This document describes an algorithm for the generation of a four dimensional trajectory. Input data for this algorithm are similar to an augmented Standard Terminal Arrival (STAR) with the augmentation in the form of altitude or speed crossing restrictions at waypoints on the route. This version of the algorithm accommodates constant radius turns and cruise altitude waypoints with calibrated airspeed, versus Mach, constraints. The algorithm calculates the altitude, speed, along path distance, and along path time for each waypoint. Wind data at each of these waypoints are also used for the calculation of ground speed and turn radius.
Stereoscopic depth perception for robot vision: algorithms and architectures
Safranek, R.J.; Kak, A.C.
1983-01-01
The implementation of depth perception algorithms for computer vision is considered. In automated manufacturing, depth information is vital for tasks such as path planning and 3-d scene analysis. The presentation begins with a survey of computer algorithms for stereoscopic depth perception. The emphasis is on the Marr-Poggio paradigm of human stereo vision and its computer implementation. In addition, a stereo matching algorithm based on the relaxation labelling technique is examined. A computer architecture designed to efficiently implement stereo matching algorithms, an MIMD array interfaced to a global memory, is presented. 9 references.
Choset, Howie
[9] H. Noborio and T. Yoshioka. An online and deadlockfree pathplanning algorithm based on world. Sankaranarayanan and M. Vidyasagar. Path planning for moving a point object amidst unknown obstacles in a plane on Robotics and Automation, pages 1734-- 1941, 1991. [15] A. Stentz. Optimal and efficient path planning
Janssen, Hans-Karl; Stenull, Olaf
2012-01-01
Long linear polymers in strongly disordered media are well described by self-avoiding walks (SAWs) on percolation clusters and a lot can be learned about the statistics of these polymers by studying the length distribution of SAWs on percolation clusters. This distribution encompasses 2 distinct averages, viz., the average over the conformations of the underlying cluster and the SAW conformations. For the latter average, there are two basic options, one being static and one being kinetic. It is well known for static averaging that if the disorder of the underlying medium is weak, this disorder is redundant in the sense the renormalization group; i.e., differences to the ordered case appear merely in nonuniversal quantities. Using dynamical field theory, we show that the same holds true for kinetic averaging. Our main focus, however, lies on strong disorder, i.e., the medium being close to the percolation point, where disorder is relevant. Employing a field theory for the nonlinear random resistor network in conjunction with a real-world interpretation of the corresponding Feynman diagrams, we calculate the scaling exponents for the shortest, the longest, and the mean or average SAW to 2-loop order. In addition, we calculate to 2-loop order the entire family of multifractal exponents that governs the moments of the the statistical weights of the elementary constituents (bonds or sites of the underlying fractal cluster) contributing to the SAWs. Our RG analysis reveals that kinetic averaging leads to renormalizability whereas static averaging does not, and hence, we argue that the latter does not lead to a well-defined scaling limit. We discuss the possible implications of this finding for experiments and numerical simulations which have produced widespread results for the exponent of the average SAW. To corroborate our results, we also study the well-known Meir-Harris model for SAWs on percolation clusters. We demonstrate that the Meir-Harris model leads back up to 2-loop order to the renormalizable real-world formulation with kinetic averaging if the replica limit is consistently performed at the first possible instant in the course of the calculation. PMID:22400528
Path integral measure factorization in path integrals for diffusion of Yang--Mills fields
S. N. Storchak
2007-11-19
Factorization of the (formal) path integral measure in a Wiener path integrals for Yang--Mills diffusion is studied. Using the nonlinear filtering stochastic differential equation, we perform the transformation of the path integral defined on a total space of the Yang--Mills principal fiber bundle and come to the reduced path integral on a Coulomb gauge surface. Integral relation between the path integral representing the "quantum" evolution given on the original manifold of Yang--Mills fields and the path integral on the reduced manifold defined by the Coulomb gauge is obtained.
Sequential Path Entanglement for Quantum Metrology
Jin, Xian-Min; Peng, Cheng-Zhi; Deng, Youjin; Barbieri, Marco; Nunn, Joshua; Walmsley, Ian A.
2013-01-01
Path entanglement is a key resource for quantum metrology. Using path-entangled states, the standard quantum limit can be beaten, and the Heisenberg limit can be achieved. However, the preparation and detection of such states scales unfavourably with the number of photons. Here we introduce sequential path entanglement, in which photons are distributed across distinct time bins with arbitrary separation, as a resource for quantum metrology. We demonstrate a scheme for converting polarization Greenberger-Horne-Zeilinger entanglement into sequential path entanglement. We observe the same enhanced phase resolution expected for conventional path entanglement, independent of the delay between consecutive photons. Sequential path entanglement can be prepared comparably easily from polarization entanglement, can be detected without using photon-number-resolving detectors, and enables novel applications.
Recursive Branching Simulated Annealing Algorithm
NASA Technical Reports Server (NTRS)
Bolcar, Matthew; Smith, J. Scott; Aronstein, David
2012-01-01
This innovation is a variation of a simulated-annealing optimization algorithm that uses a recursive-branching structure to parallelize the search of a parameter space for the globally optimal solution to an objective. The algorithm has been demonstrated to be more effective at searching a parameter space than traditional simulated-annealing methods for a particular problem of interest, and it can readily be applied to a wide variety of optimization problems, including those with a parameter space having both discrete-value parameters (combinatorial) and continuous-variable parameters. It can take the place of a conventional simulated- annealing, Monte-Carlo, or random- walk algorithm. In a conventional simulated-annealing (SA) algorithm, a starting configuration is randomly selected within the parameter space. The algorithm randomly selects another configuration from the parameter space and evaluates the objective function for that configuration. If the objective function value is better than the previous value, the new configuration is adopted as the new point of interest in the parameter space. If the objective function value is worse than the previous value, the new configuration may be adopted, with a probability determined by a temperature parameter, used in analogy to annealing in metals. As the optimization continues, the region of the parameter space from which new configurations can be selected shrinks, and in conjunction with lowering the annealing temperature (and thus lowering the probability for adopting configurations in parameter space with worse objective functions), the algorithm can converge on the globally optimal configuration. The Recursive Branching Simulated Annealing (RBSA) algorithm shares some features with the SA algorithm, notably including the basic principles that a starting configuration is randomly selected from within the parameter space, the algorithm tests other configurations with the goal of finding the globally optimal solution, and the region from which new configurations can be selected shrinks as the search continues. The key difference between these algorithms is that in the SA algorithm, a single path, or trajectory, is taken in parameter space, from the starting point to the globally optimal solution, while in the RBSA algorithm, many trajectories are taken; by exploring multiple regions of the parameter space simultaneously, the algorithm has been shown to converge on the globally optimal solution about an order of magnitude faster than when using conventional algorithms. Novel features of the RBSA algorithm include: 1. More efficient searching of the parameter space due to the branching structure, in which multiple random configurations are generated and multiple promising regions of the parameter space are explored; 2. The implementation of a trust region for each parameter in the parameter space, which provides a natural way of enforcing upper- and lower-bound constraints on the parameters; and 3. The optional use of a constrained gradient- search optimization, performed on the continuous variables around each branch s configuration in parameter space to improve search efficiency by allowing for fast fine-tuning of the continuous variables within the trust region at that configuration point.
Path integral for Koenigs spaces
Grosche, C.
2008-05-15
I discuss a path-integral approach for the quantum motion on two-dimensional spaces according to Koenigs, for short 'Koenigs spaces'. Their construction is simple: one takes a Hamiltonian from a two-dimensional flat space and divides it by a two-dimensional superintegrable potential. These superintegrable potentials are the isotropic singular oscillator, the Holt potential, and the Coulomb potential. In all cases, a nontrivial space of nonconstant curvature is generated. We can study free motion and the motion with an additional superintegrable potential. For possible bound-state solutions, we find in all three cases an equation of the eighth order in the energy E. The special cases of the Darboux spaces are easily recovered by choosing the parameters accordingly.
Fragmentation paths in dynamical models
M. Colonna; A. Ono; J. Rizzo
2010-11-05
We undertake a quantitative comparison of multi-fragmentation reactions, as modeled by two different approaches: the Antisymmetrized Molecular Dynamics (AMD) and the momentum-dependent stochastic mean-field (SMF) model. Fragment observables and pre-equilibrium (nucleon and light cluster) emission are analyzed, in connection to the underlying compression-expansion dynamics in each model. Considering reactions between neutron-rich systems, observables related to the isotopic properties of emitted particles and fragments are also discussed, as a function of the parametrization employed for the isovector part of the nuclear interaction. We find that the reaction path, particularly the mechanism of fragmentation, is different in the two models and reflects on some properties of the reaction products, including their isospin content. This should be taken into account in the study of the density dependence of the symmetry energy from such collisions.
Fragmentation paths in dynamical models
Colonna, M.; Rizzo, J.; Ono, A.
2010-11-15
We undertake a quantitative comparison of multifragmentation reactions, as modeled by two different approaches: the antisymmetrized molecular dynamics (AMD) and the momentum-dependent stochastic mean-field (SMF) model. Fragment observables and pre-equilibrium (nucleon and light cluster) emission are analyzed, in connection with the underlying compression-expansion dynamics in each model. Considering reactions between neutron-rich systems, observables related to the isotopic properties of emitted particles and fragments are also discussed, as a function of the parametrization employed for the isovector part of the nuclear interaction. We find that the reaction path, particularly the mechanism of fragmentation, is different in the two models and reflects on some properties of the reaction products, including their isospin content. This should be taken into account in the study of the density dependence of the symmetry energy from such collisions.
Euclid's Algorithm, Guass' Elimination and Buchberger's Algorithm
International Association for Cryptologic Research (IACR)
Euclid's Algorithm, Guass' Elimination and Buchberger's Algorithm Shaohua Zhang School of Mathematics, Shandong University, Jinan, Shandong, 250100, PRC Abstract: It is known that Euclid's algorithm of several positive integers, which can be regarded as the generalization of Euclid's algorithm. This enables
Flexible-Path Human Exploration
NASA Technical Reports Server (NTRS)
Sherwood, B.; Adler, M.; Alkalai, L.; Burdick, G.; Coulter, D.; Jordan, F.; Naderi, F.; Graham, L.; Landis, R.; Drake, B.; Hoffman, S.; Grunsfeld, J.; Seery, B. D.
2010-01-01
In the fourth quarter of 2009 an in-house, multi-center NASA study team briefly examined "Flexible Path" concepts to begin understanding characteristics, content, and roles of potential missions consistent with the strategy proposed by the Augustine Committee. We present an overview of the study findings. Three illustrative human/robotic mission concepts not requiring planet surface operations are described: assembly of very large in-space telescopes in cis-lunar space; exploration of near Earth objects (NEOs); exploration of Mars' moon Phobos. For each, a representative mission is described, technology and science objectives are outlined, and a basic mission operations concept is quantified. A fourth type of mission, using the lunar surface as preparation for Mars, is also described. Each mission's "capability legacy" is summarized. All four illustrative missions could achieve NASA's stated human space exploration objectives and advance human space flight toward Mars surface exploration. Telescope assembly missions would require the fewest new system developments. NEO missions would offer a wide range of deep-space trip times between several months and two years. Phobos exploration would retire several Marsclass risks, leaving another large remainder set (associated with entry, descent, surface operations, and ascent) for retirement by subsequent missions. And extended lunar surface operations would build confidence for Mars surface missions by addressing a complementary set of risks. Six enabling developments (robotic precursors, ISS exploration testbed, heavy-lift launch, deep-space-capable crew capsule, deep-space habitat, and reusable in-space propulsion stage) would apply across multiple program sequence options, and thus could be started even without committing to a specific mission sequence now. Flexible Path appears to be a viable strategy, with meaningful and worthy mission content.
Principal Investigator: Dr. Abdella Battou
2009-05-22
The major accomplishments of the project are the successful software implementation of the Phase I scheduling algorithms for GMPLS Label Switched Paths (LSPs) and the extension of the IETF Path Computation Element (PCE) Protocol to support scheduling extensions. In performing this work, we have demonstrated the theoretical work of Phase I, analyzed key issues, and made relevant extensions. Regarding the software implementation, we developed a proof of concept prototype as part of our Algorithm Evaluation System (AES). This implementation uses the Linux operating system to provide software portability and will be the foundation for our commercial software. To demonstrate proof of concept, we have implemented LSP scheduling algorithms to support two of the key GMPLS switching technologies (Lambda and Packet) and support both Fixed Path (FP) and Switched Path (SP) routing. We chose Lambda and Packet because we felt it was essential to include both circuit and packet switching technologies as well as to address all-optical switching in the study. As conceptualized in Phase I, the FP algorithms use a traditional approach where the LSP uses the same physical path for the entire service duration while the innovative SP algorithms allow the physical path to vary during the service duration. As part of this study, we have used the AES to conduct a performance analysis using metro size networks (up to 32 nodes) that showed that these algorithms are suitable for commercial implementation. Our results showed that the CPU time required to compute an LSP schedule was small compared to expected inter-arrival time between LSP requests. Also, when the network size increased from 7 to 15 to 32 nodes with 10, 26, and 56 TE links, the CPU processing time showed excellent scaling properties. When Fixed Path and Switched Path routing were compared, SP provided only modestly better performance with respect to LSP completion rate, service duration, path length, and start time deviation. In addition, the SP routing required somewhat more CPU time than the FP routing. However, when the allowable range for the start time is increased, the CPU time for SP increased less rapidly than FP such that the CPU processing times became comparable. Therefore, SP routing may scale better than FP routing. The Path Computation Element Working Group is a complementary working group to the GMPLS working group (CCAMP) in the IETF and is developing standards to discover, manage, and access elements that compute routes for GMPLS for LSPs. The algorithms used to compute the routes are not subject to standardization. Since the PCE supports only standard GMPLS LSPs, it does not support scheduled LSPs. Therefore, it is a natural extension of our Phase I work to introduce this enhancement into the PCE. In addition, the PCE adds another dimension to our product line because the PCE by itself may be a product with a standard interface.
NASA Technical Reports Server (NTRS)
Pines, S.
1982-01-01
The necessary algorithms to reconstruct the glideslope change waypoint along a straight line in the event the aircraft encounters a valid MLS update and transition in the terminal approach area are presented. Results of a simulation of the Langley B737 aircraft utilizing these algorithms are presented. The method is shown to reconstruct the necessary flight path during MLS transition resulting in zero cross track error, zero track angle error, and zero altitude error, thus requiring minimal aircraft response.
Transition Path Theory E. Vanden-Eijnden
Van Den Eijnden, Eric
Transition Path Theory E. Vanden-Eijnden Courant Institute of Mathematical Sciences, New York University New York, NY 10012 eve2cims.nyu.edu Eric Vanden-Eijnden E. Vanden-Eijnden: Transition Path Theory of the Current and Transition Tubes . . . . . . . . . . . . . . . . . . . . . . 451 5 Comparison with Transition
Realistic Human Walking Paths David C. Brogan
Brogan, David
Realistic Human Walking Paths David C. Brogan Department of Computer Science University of Virginia are influenced by kinematic and dynami- cal constraints. A realistic model of human walking paths is an important natural human behavior than previous models. 1. Introduction Realistic walking animations are required