Dynamic Shortest Path Algorithms for Hypergraphs
2014-01-01
hypergraphs, energy efficient routing in multichannel multiradio networks, and the Enron email data set. The experiment with the Enron email data set...efficient routing inmultichannel multiradio networks, and the Enron email data set. The experiment with the Enron email data set illustrates the application...FOR HYPERGRAPHS 3 of each actor. In Section VII, we apply the proposed shortest hy- perpath algorithms to the Enron e-mail data set. We propose a
Dynamic Shortest Path Algorithms for Hypergraphs
2012-01-01
geometric hypergraphs and the Enron email data set. The latter illustrates the application of the proposed algorithms in social networks for identifying...analyze the time complexity of the proposed algorithms and perform simulation experiments for both random geometric hypergraphs and the Enron email data...geometric hypergraph model and a real data set of a social network ( Enron email data set), we study the average performance of these two algorithms in
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
Multiple object tracking using the shortest path faster association algorithm.
Xi, Zhenghao; Liu, Heping; Liu, Huaping; Yang, Bin
2014-01-01
To solve the persistently multiple object tracking in cluttered environments, this paper presents a novel tracking association approach based on the shortest path faster algorithm. First, the multiple object tracking is formulated as an integer programming problem of the flow network. Then we relax the integer programming to a standard linear programming problem. Therefore, the global optimum can be quickly obtained using the shortest path faster algorithm. The proposed method avoids the difficulties of integer programming, and it has a lower worst-case complexity than competing methods but better robustness and tracking accuracy in complex environments. Simulation results show that the proposed algorithm takes less time than other state-of-the-art methods and can operate in real time.
A Successive Shortest Path Algorithm for the Assignment Problem.
1980-08-01
a refinement of the Dinic-Kronrod algorithm [ 7 ]. We have used SSP to develop a computer code which is very efficient for solving large, sparse...x .. / - Node,i Predecessor,Pt Distance,D iI I lD, 3 none 0 2 3 6 2 3 1 1 4 3 3 (,2 4 5 1 3 6 2 10 7 1 1 6 Fig. 1. A shortest path tree. 4 In a...denote the number of elements in $I: j = Ail. The modified assignment problem relative to (C,A) is defined as follows: I 7 Minimize cij xij (i,j E
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 bio-inspired algorithm for the directed shortest path problem.
Zhang, Xiaoge; Zhang, Yajuan; Deng, Yong
2014-11-18
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.
Algorithm for shortest path search in Geographic Information Systems by using reduced graphs.
Rodríguez-Puente, Rafael; Lazo-Cortés, Manuel S
2013-01-01
The use of Geographic Information Systems has increased considerably since the eighties and nineties. As one of their most demanding applications we can mention shortest paths search. Several studies about shortest path search show the feasibility of using graphs for this purpose. Dijkstra's algorithm is one of the classic shortest path search algorithms. This algorithm is not well suited for shortest path search in large graphs. This is the reason why various modifications to Dijkstra's algorithm have been proposed by several authors using heuristics to reduce the run time of shortest path search. One of the most used heuristic algorithms is the A* algorithm, the main goal is to reduce the run time by reducing the search space. This article proposes a modification of Dijkstra's shortest path search algorithm in reduced graphs. It shows that the cost of the path found in this work, is equal to the cost of the path found using Dijkstra's algorithm in the original graph. The results of finding the shortest path, applying the proposed algorithm, Dijkstra's algorithm and A* algorithm, are compared. This comparison shows that, by applying the approach proposed, it is possible to obtain the optimal path in a similar or even in less time than when using heuristic algorithms.
A circuitous shortest path algorithm labeled by previous-arc vector group in navigation GIS
NASA Astrophysics Data System (ADS)
Yang, Lin; Zhou, Shunping; Wan, Bo; Pan, Xiaofang
2008-10-01
Path planning, as the core module of navigation GIS, its efficiency and accuracy has a crucial impact on the navigation system. General shortest-path algorithm is based on the classic node label-setting algorithm, which does not consider the situation of including circuitous road sections. Therefore, sometimes it will neglect the closer circuitous path at hand but find the farther path or even failed to find any path in the real road network with complicated traffic restrictions. For the sake of finding more accurate path, this paper presents a circuitous shortest path algorithm labeled by previous-arc vector group. Firstly, we generate incremental network topological relationships according to two random positions travelers are interested in. Secondly, we construct a vector group including previous arc, and seek the way by labeling the previous-arc vector group. Finally, the shortest path in the sense of mathematics which may contain circuitous road sections can be acquired. An experimental work has been done with this algorithm using the map of Beijing, which showed that the algorithm not only well improved the accuracy of the shortest path result between the two random positions in the road network, but also kept the efficiency of the classic node labeled algorithm.
Finding splitting lines for touching cell nuclei with a shortest path algorithm.
Bai, Xiangzhi; Wang, Peng; Sun, Changming; Zhang, Yu; Zhou, Fugen; Meng, Cai
2015-08-01
A shortest path-based algorithm is proposed in this paper to find splitting lines for touching cell nuclei. First, an initial splitting line is obtained through the distance transform of a marker image and the watershed algorithm. The initial splitting line is then separated into different line segments as necessary, and the endpoint positions of these line segments are adjusted to the concave points on the contour. Finally, a shortest path algorithm is used to find the accurate splitting line between the starting-point and the end-point, and the final split can be achieved by the contour of the touching cell nuclei and the splitting lines. Comparisons of experimental results show that the proposed algorithm is effective for segmentation of different types of touching cell nuclei.
a Modified Genetic Algorithm for Finding Fuzzy Shortest Paths in Uncertain Networks
NASA Astrophysics Data System (ADS)
Heidari, A. A.; Delavar, M. R.
2016-06-01
In realistic network analysis, there are several uncertainties in the measurements and computation of the arcs and vertices. These uncertainties should also be considered in realizing the shortest path problem (SPP) due to the inherent fuzziness in the body of expert's knowledge. In this paper, we investigated the SPP under uncertainty to evaluate our modified genetic strategy. We improved the performance of genetic algorithm (GA) to investigate a class of shortest path problems on networks with vague arc weights. The solutions of the uncertain SPP with considering fuzzy path lengths are examined and compared in detail. As a robust metaheuristic, GA algorithm is modified and evaluated to tackle the fuzzy SPP (FSPP) with uncertain arcs. For this purpose, first, a dynamic operation is implemented to enrich the exploration/exploitation patterns of the conventional procedure and mitigate the premature convergence of GA technique. Then, the modified GA (MGA) strategy is used to resolve the FSPP. The attained results of the proposed strategy are compared to those of GA with regard to the cost, quality of paths and CPU times. Numerical instances are provided to demonstrate the success of the proposed MGA-FSPP strategy in comparison with GA. The simulations affirm that not only the proposed technique can outperform GA, but also the qualities of the paths are effectively improved. The results clarify that the competence of the proposed GA is preferred in view of quality quantities. The results also demonstrate that the proposed method can efficiently be utilized to handle FSPP in uncertain networks.
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.
Protein-fold recognition using an improved single-source K diverse shortest paths algorithm.
Lhota, John; Xie, Lei
2016-04-01
Protein structure prediction, when construed as a fold recognition problem, is one of the most important applications of similarity search in bioinformatics. A new protein-fold recognition method is reported which combines a single-source K diverse shortest path (SSKDSP) algorithm with Enrichment of Network Topological Similarity (ENTS) algorithm to search a graphic feature space generated using sequence similarity and structural similarity metrics. A modified, more efficient SSKDSP algorithm is developed to improve the performance of graph searching. The new implementation of the SSKDSP algorithm empirically requires 82% less memory and 61% less time than the current implementation, allowing for the analysis of larger, denser graphs. Furthermore, the statistical significance of fold ranking generated from SSKDSP is assessed using ENTS. The reported ENTS-SSKDSP algorithm outperforms original ENTS that uses random walk with restart for the graph search as well as other state-of-the-art protein structure prediction algorithms HHSearch and Sparks-X, as evaluated by a benchmark of 600 query proteins. The reported methods may easily be extended to other similarity search problems in bioinformatics and chemoinformatics. The SSKDSP software is available at http://compsci.hunter.cuny.edu/~leixie/sskdsp.html.
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 κ = 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
An optimal antenna motion generation using shortest path planning
NASA Astrophysics Data System (ADS)
Jeon, Moon-Jin; Kwon, Dong-Soo
2017-03-01
This paper considers an angular velocity minimization method for a satellite antenna. For high speed transmission of science data, a directional antenna with a two-axis gimbal is generally used. When a satellite passes over a ground station while pointing directly at it, the angular velocity of the satellite antenna can increase rapidly due to the gimbal kinematics. The high angular velocity could exceed the dynamic constraint of the antenna. Furthermore, micro vibration induced by high speed antenna rotation during an imaging operation might cause jitter, which can degrade the satellite image quality. To solve this problem, a minimum-velocity antenna motion generation method is proposed. Boundaries of the azimuth and elevation angles of the antenna within an effective beam width are derived using antenna geometry. A minimum-velocity azimuth profile and elevation profile within the boundaries are generated sequentially using a shortest path planning method. For fast and correct generation of the shortest path, a new algorithm called a string nailing algorithm is proposed. A numerical simulation shows that the antenna profile generated by the shortest path planning has a much lower angular velocity than the profiles generated by previous methods. The proposed string nailing algorithm also spends much less computation time than a search-based shortest path planning algorithm to generate almost the same antenna profiles.
Competition for shortest paths on sparse graphs.
Yeung, Chi Ho; Saad, David
2012-05-18
Optimal paths connecting randomly selected network nodes and fixed routers are studied analytically in the presence of a nonlinear overlap cost that penalizes congestion. Routing becomes more difficult as the number of selected nodes increases and exhibits ergodicity breaking in the case of multiple routers. The ground state of such systems reveals nonmonotonic complex behaviors in average path length and algorithmic convergence, depending on the network topology, and densities of communicating nodes and routers. A distributed linearly scalable routing algorithm is also devised.
Al Nasr, Kamal; Ranjan, Desh; Zubair, Mohammad; Chen, Lin; He, Jing
2014-01-01
Electron cryomicroscopy is becoming a major experimental technique in solving the structures of large molecular assemblies. More and more three-dimensional images have been obtained at the medium resolutions between 5 and 10 Å. At this resolution range, major α-helices can be detected as cylindrical sticks and β-sheets can be detected as plain-like regions. A critical question in de novo modeling from cryo-EM images is to determine the match between the detected secondary structures from the image and those on the protein sequence. We formulate this matching problem into a constrained graph problem and present an O(Δ(2)N(2)2(N)) algorithm to this NP-Hard problem. The algorithm incorporates the dynamic programming approach into a constrained K-shortest path algorithm. Our method, DP-TOSS, has been tested using α-proteins with maximum 33 helices and α-β proteins up to five helices and 12 β-strands. The correct match was ranked within the top 35 for 19 of the 20 α-proteins and all nine α-β proteins tested. The results demonstrate that DP-TOSS improves accuracy, time and memory space in deriving the topologies of the secondary structure elements for proteins with a large number of secondary structures and a complex skeleton.
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
Cai, Yu-Dong; Zhang, Qing; Zhang, Yu-Hang; Chen, Lei; Huang, Tao
2017-02-03
Tumor metastasis is defined as the spread of tumor cells from one organ or part to another that is not directly connected to it, which significantly contributes to the progression and aggravation of tumorigenesis. Because it always involves multiple organs, the metastatic process is difficult to study in its entirety. Complete identification of the genes related to this process is an alternative way to study metastasis. In this study, we developed a computational method to identify such genes. To test our method, we selected breast cancer bone metastasis. A large network was constructed using human protein-protein interactions. On the basis of the validated genes related to breast and bone cancer, a shortest path algorithm was applied to the network to search for novel genes that may mediate breast cancer metastasis to bone. In addition, further rules constructed using the permutation FDR, the betweenness ratio, and the max-min interaction score were also employed in the method to make the inferred genes more reliable. Eighteen putative genes were identified by the method and were extensively analyzed. The confirmation results indicate that these genes participate in metastasis.
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.
Two betweenness centrality measures based on Randomized Shortest Paths
Kivimäki, Ilkka; Lebichot, Bertrand; Saramäki, Jari; Saerens, Marco
2016-01-01
This paper introduces two new closely related betweenness centrality measures based on the Randomized Shortest Paths (RSP) framework, which fill a gap between traditional network centrality measures based on shortest paths and more recent methods considering random walks or current flows. The framework defines Boltzmann probability distributions over paths of the network which focus on the shortest paths, but also take into account longer paths depending on an inverse temperature parameter. RSP’s have previously proven to be useful in defining distance measures on networks. In this work we study their utility in quantifying the importance of the nodes of a network. The proposed RSP betweenness centralities combine, in an optimal way, the ideas of using the shortest and purely random paths for analysing the roles of network nodes, avoiding issues involving these two paradigms. We present the derivations of these measures and how they can be computed in an efficient way. In addition, we show with real world examples the potential of the RSP betweenness centralities in identifying interesting nodes of a network that more traditional methods might fail to notice. PMID:26838176
Multiple Object Tracking Using K-Shortest Paths Optimization.
Berclaz, Jérôme; Fleuret, François; Türetken, Engin; Fua, Pascal
2011-09-01
Multi-object tracking can be achieved by detecting objects in individual frames and then linking detections across frames. Such an approach can be made very robust to the occasional detection failure: If an object is not detected in a frame but is in previous and following ones, a correct trajectory will nevertheless be produced. By contrast, a false-positive detection in a few frames will be ignored. However, when dealing with a multiple target problem, the linking step results in a difficult optimization problem in the space of all possible families of trajectories. This is usually dealt with by sampling or greedy search based on variants of Dynamic Programming which can easily miss the global optimum. In this paper, we show that reformulating that step as a constrained flow optimization results in a convex problem. We take advantage of its particular structure to solve it using the k-shortest paths algorithm, which is very fast. This new approach is far simpler formally and algorithmically than existing techniques and lets us demonstrate excellent performance in two very different contexts.
Traffic-engineering-aware shortest-path routing and its application in IP-over-WDM networks [Invited
NASA Astrophysics Data System (ADS)
Lee, Youngseok; Mukherjee, Biswanath
2004-03-01
Single shortest-path routing is known to perform poorly for Internet traffic engineering (TE) where the typical optimization objective is to minimize the maximum link load. Splitting traffic uniformly over equal-cost multiple shortest paths in open shortest path first and intermediate system-intermediate system protocols does not always minimize the maximum link load when multiple paths are not carefully selected for the global traffic demand matrix. However, a TE-aware shortest path among all the equal-cost multiple shortest paths between each ingress-egress pair can be selected such that the maximum link load is significantly reduced. IP routers can use the globally optimal TE-aware shortest path without any change to existing routing protocols and without any serious configuration overhead. While calculating TE-aware shortest paths, the destination-based forwarding constraint at a node should be satisfied, because an IP router will forward a packet to the next hop toward the destination by looking up the destination prefix. We present a mathematical problem formulation for finding a set of TE-aware shortest paths for the given network as an integer linear program, and we propose a simple heuristic for solving large instances of the problem. Then we explore the usage of our proposed algorithm for the integrated TE method in IP-over-WDM networks. The proposed algorithm is evaluated through simulations in IP networks as well as in IP-over-WDM networks.
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.
Randomized shortest-path problems: two related models.
Saerens, Marco; Achbany, Youssef; Fouss, François; Yen, Luh
2009-08-01
This letter addresses the problem of designing the transition probabilities of a finite Markov chain (the policy) in order to minimize the expected cost for reaching a destination node from a source node while maintaining a fixed level of entropy spread throughout the network (the exploration). It is motivated by the following scenario. Suppose you have to route agents through a network in some optimal way, for instance, by minimizing the total travel cost-nothing particular up to now-you could use a standard shortest-path algorithm. Suppose, however, that you want to avoid pure deterministic routing policies in order, for instance, to allow some continual exploration of the network, avoid congestion, or avoid complete predictability of your routing strategy. In other words, you want to introduce some randomness or unpredictability in the routing policy (i.e., the routing policy is randomized). This problem, which will be called the randomized shortest-path problem (RSP), is investigated in this work. The global level of randomness of the routing policy is quantified by the expected Shannon entropy spread throughout the network and is provided a priori by the designer. Then, necessary conditions to compute the optimal randomized policy-minimizing the expected routing cost-are derived. Iterating these necessary conditions, reminiscent of Bellman's value iteration equations, allows computing an optimal policy, that is, a set of transition probabilities in each node. Interestingly and surprisingly enough, this first model, while formulated in a totally different framework, is equivalent to Akamatsu's model ( 1996 ), appearing in transportation science, for a special choice of the entropy constraint. We therefore revisit Akamatsu's model by recasting it into a sum-over-paths statistical physics formalism allowing easy derivation of all the quantities of interest in an elegant, unified way. For instance, it is shown that the unique optimal policy can be obtained by
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.
The d-edge shortest-path problem for a Monge graph
Bein, W.W.; Larmore, L.L.; Park, J.K.
1992-07-14
A complete edge-weighted directed graph on vertices 1,2,...,n that assigns cost c(i,j) to the edge (i,j) is called Monge if its edge costs form a Monge array, i.e., for all i < k and j < l, c[i, j]+c[k,l]{le} < c[i,l]+c[k,j]. One reason Monge graphs are interesting is that shortest paths can be computed quite quickly in such graphs. In particular, Wilber showed that the shortest path from vertex 1 to vertex n of a Monge graph can be computed in O(n) time, and Aggarwal, Klawe, Moran, Shor, and Wilber showed that the shortest d-edge 1-to-n path (i.e., the shortest path among all 1-to-n paths with exactly d edges) can be computed in O(dn) time. This paper`s contribution is a new algorithm for the latter problem. Assuming 0 {le} c[i,j] {le} U and c[i,j + 1] + c[i + 1,j] {minus} c[i,j] {minus} c[i + 1, j + 1] {ge} L > 0 for all i and j, our algorithm runs in O(n(1 + 1g(U/L))) time. Thus, when d {much_gt} 1 + 1g(U/L), our algorithm represents a significant improvement over Aggarwal et al.`s O(dn)-time algorithm. We also present several applications of our algorithm; they include length-limited Huffman coding, finding the maximum-perimeter d-gon inscribed in a given convex n-gon, and a digital-signal-compression problem.
A Bio-Inspired Method for the Constrained Shortest Path Problem
Wang, Hongping; Lu, Xi; Wang, Qing
2014-01-01
The constrained shortest path (CSP) problem has been widely used in transportation optimization, crew scheduling, network routing and so on. It is an open issue since it is a NP-hard problem. In this paper, we propose an innovative method which is based on the internal mechanism of the adaptive amoeba algorithm. The proposed method is divided into two parts. In the first part, we employ the original amoeba algorithm to solve the shortest path problem in directed networks. In the second part, we combine the Physarum algorithm with a bio-inspired rule to deal with the CSP. Finally, by comparing the results with other method using an examples in DCLC problem, we demonstrate the accuracy of the proposed method. PMID:24959603
A bio-inspired method for the constrained shortest path problem.
Wang, Hongping; Lu, Xi; Zhang, Xiaoge; Wang, Qing; Deng, Yong
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.
Effect of Congestion Costs on Shortest Paths Through Complex Networks
NASA Astrophysics Data System (ADS)
Ashton, Douglas J.; Jarrett, Timothy C.; Johnson, Neil F.
2005-02-01
We analyze analytically the effect of congestion costs within a physically relevant, yet exactly solvable, network model featuring central hubs. These costs lead to a competition between centralized and decentralized transport pathways. In stark contrast to conventional no-cost networks, there now exists an optimal number of connections to the central hub in order to minimize the shortest path. Our results shed light on an open problem in biology, informatics, and sociology, concerning the extent to which decentralized versus centralized design benefits real-world complex networks.
Effect of congestion costs on shortest paths through complex networks.
Ashton, Douglas J; Jarrett, Timothy C; Johnson, Neil F
2005-02-11
We analyze analytically the effect of congestion costs within a physically relevant, yet exactly solvable, network model featuring central hubs. These costs lead to a competition between centralized and decentralized transport pathways. In stark contrast to conventional no-cost networks, there now exists an optimal number of connections to the central hub in order to minimize the shortest path. Our results shed light on an open problem in biology, informatics, and sociology, concerning the extent to which decentralized versus centralized design benefits real-world complex networks.
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.
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(μ(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
Membrane Boundary Extraction Using a Circular Shortest Path Technique
NASA Astrophysics Data System (ADS)
Sun, Changming; Vallotton, Pascal; Wang, Dadong; Lopez, Jamie; Ng, Yvonne; James, David
2007-11-01
Membrane proteins represent over 50% of known drug targets. Accordingly, several widely used assays in the High Content Analysis area rely on quantitative measures of the translocation of proteins between intracellular organelles and the cell surface. In order to increase the sensitivity of these assays, one needs to measure the signal specifically along the membrane, requiring a precise segmentation of this compartment. Doing this manually is a very time-consuming practice, limited to an academic setting. Manual tracing of the membrane compartment also confronts us with issues of objectivity and reproducibility. In this paper, we present an approach based on a circular shortest path technique that enables us to segment the membrane compartment accurately and rapidly. This feature is illustrated using cells expressing epitope-tagged membrane proteins.
Efficient shortest-path-tree computation in network routing based on pulse-coupled neural networks.
Qu, Hong; Yi, Zhang; Yang, Simon X
2013-06-01
Shortest path tree (SPT) computation is a critical issue for routers using link-state routing protocols, such as the most commonly used open shortest path first and intermediate system to intermediate system. Each router needs to recompute a new SPT rooted from itself whenever a change happens in the link state. Most commercial routers do this computation by deleting the current SPT and building a new one using static algorithms such as the Dijkstra algorithm at the beginning. Such recomputation of an entire SPT is inefficient, which may consume a considerable amount of CPU time and result in a time delay in the network. Some dynamic updating methods using the information in the updated SPT have been proposed in recent years. However, there are still many limitations in those dynamic algorithms. In this paper, a new modified model of pulse-coupled neural networks (M-PCNNs) is proposed for the SPT computation. It is rigorously proved that the proposed model is capable of solving some optimization problems, such as the SPT. A static algorithm is proposed based on the M-PCNNs to compute the SPT efficiently for large-scale problems. In addition, a dynamic algorithm that makes use of the structure of the previously computed SPT is proposed, which significantly improves the efficiency of the algorithm. Simulation results demonstrate the effective and efficient performance of the proposed approach.
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.
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
NASA Astrophysics Data System (ADS)
Xuan, Qi; Li, Yanjun; Wu, Tie-Jun
2009-04-01
Homogeneous entangled networks characterized by small world, large girths, and no community structure have attracted much attention due to some of their favorable performances. However, the optimization algorithm proposed by Donetti et al. is very time-consuming and will lose its efficiency when the size of the target network becomes large. In this paper, an alternative optimization algorithm is provided to get optimal symmetric networks by minimizing the average shortest path length. It is shown that the synchronizability of a symmetric network is enhanced when the average shortest path length of the network is shortened as the optimization proceeds, which suggests that the optimal symmetric networks in terms of minimizing average shortest path length will be very close to those entangled networks. In order to overcome the time-consuming obstacle of the optimization algorithms proposed by us and Donetti et al., a growth model is proposed to get large scale sub-optimal symmetric networks. Numerical simulations show that the symmetric networks derived by our growth model will have small-world property, and besides, these networks will have many other similar favorable performances as entangled networks, e.g., robustness against errors and attacks, very good load balancing ability, and strong synchronizability.
Minimizing Communication in All-Pairs Shortest Paths
2013-02-13
and C. Budak. Solving path problems on the GPU. Parallel Computing, 36(5-6):241 – 253, 2010. [12] L. E. Cannon. A cellular computer to implement the...and J. van Leeuwen, editors, Automata , Languages and Programming, volume 2076 of Lecture Notes in Computer Science, pages 178–189. Springer Berlin
NASA Astrophysics Data System (ADS)
Kröger, Martin
2005-06-01
We present an algorithm which returns a shortest path and related number of entanglements for a given configuration of a polymeric system in 2 or 3 dimensions. Rubinstein and Helfand, and later Everaers et al. introduced a concept to extract primitive paths for dense polymeric melts made of linear chains (a multiple disconnected multibead 'path'), where each primitive path is defined as a path connecting the (space-fixed) ends of a polymer under the constraint of non-interpenetration (excluded volume) between primitive paths of different chains, such that the multiple disconnected path fulfills a minimization criterion. The present algorithm uses geometrical operations and provides a—model independent—efficient approximate solution to this challenging problem. Primitive paths are treated as 'infinitely' thin (we further allow for finite thickness to model excluded volume), and tensionless lines rather than multibead chains, excluded volume is taken into account without a force law. The present implementation allows to construct a shortest multiple disconnected path (SP) for 2D systems (polymeric chain within spherical obstacles) and an optimal SP for 3D systems (collection of polymeric chains). The number of entanglements is then simply obtained from the SP as either the number of interior kinks, or from the average length of a line segment. Further, information about structure and potentially also the dynamics of entanglements is immediately available from the SP. We apply the method to study the 'concentration' dependence of the degree of entanglement in phantom chain systems. Program summaryTitle of program:Z Catalogue number:ADVG Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADVG Program obtainable from: CPC Program Library, Queen's University of Belfast, N. Ireland Computer for which the program is designed and others on which it has been tested: Silicon Graphics (Irix), Sun (Solaris), PC (Linux) Operating systems or monitors under which the
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
A time-delay neural network for solving time-dependent shortest path problem.
Huang, Wei; Yan, Chunwang; Wang, Jinsong; Wang, Wei
2017-03-21
This paper concerns the time-dependent shortest path problem, which is difficult to come up with global optimal solution by means of classical shortest path approaches such as Dijkstra, and pulse-coupled neural network (PCNN). In this study, we propose a time-delay neural network (TDNN) framework that comes with the globally optimal solution when solving the time-dependent shortest path problem. The underlying idea of TDNN comes from the following mechanism: the shortest path depends on the earliest auto-wave (from start node) that arrives at the destination node. In the design of TDNN, each node on a network is considered as a neuron, which comes in the form of two units: time-window unit and auto-wave unit. Time-window unit is used to generate auto-wave in each time window, while auto-wave unit is exploited here to update the state of auto-wave. Whether or not an auto-wave leaves a node (neuron) depends on the state of auto-wave. The evaluation of the performance of the proposed approach was carried out based on online public Cordeau instances and New York Road instances. The proposed TDNN was also compared with the quality of classical approaches such as Dijkstra and PCNN.
Li, Longxiang; Gong, Jianhua; Zhou, Jieping
2014-01-01
Effective assessments of air-pollution exposure depend on the ability to accurately predict pollutant concentrations at unmonitored locations, which can be achieved through spatial interpolation. However, most interpolation approaches currently in use are based on the Euclidean distance, which cannot account for the complex nonlinear features displayed by air-pollution distributions in the wind-field. In this study, an interpolation method based on the shortest path distance is developed to characterize the impact of complex urban wind-field on the distribution of the particulate matter concentration. In this method, the wind-field is incorporated by first interpolating the observed wind-field from a meteorological-station network, then using this continuous wind-field to construct a cost surface based on Gaussian dispersion model and calculating the shortest wind-field path distances between locations, and finally replacing the Euclidean distances typically used in Inverse Distance Weighting (IDW) with the shortest wind-field path distances. This proposed methodology is used to generate daily and hourly estimation surfaces for the particulate matter concentration in the urban area of Beijing in May 2013. This study demonstrates that wind-fields can be incorporated into an interpolation framework using the shortest wind-field path distance, which leads to a remarkable improvement in both the prediction accuracy and the visual reproduction of the wind-flow effect, both of which are of great importance for the assessment of the effects of pollutants on human health.
Modeling the average shortest-path length in growth of word-adjacency networks
NASA Astrophysics Data System (ADS)
Kulig, Andrzej; DroŻdŻ, Stanisław; Kwapień, Jarosław; OświÈ©cimka, Paweł
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.
Larsen, Kristian; Faulkner, Guy E. J.; Stone, Michelle R.
2013-01-01
Objectives. School route measurement often involves estimating the shortest network path. We challenged the relatively uncritical adoption of this method in school travel research and tested the route discordance hypothesis that several types of difference exist between shortest network paths and reported school routes. Methods. We constructed the mapped and shortest path through network routes for a sample of 759 children aged 9 to 13 years in grades 5 and 6 (boys = 45%, girls = 54%, unreported gender = 1%), in Toronto, Ontario, Canada. We used Wilcoxon signed-rank tests to compare reported with shortest-path route measures including distance, route directness, intersection crossings, and route overlap. Measurement difference was explored by mode and location. Results. We found statistical evidence of route discordance for walkers and children who were driven and detected it more often for inner suburban cases. Evidence of route discordance varied by mode and school location. Conclusions. We found statistically significant differences for route structure and built environment variables measured along reported and geographic information systems–based shortest-path school routes. Uncertainty produced by the shortest-path approach challenges its conceptual and empirical validity in school travel research. PMID:23865648
NASA Astrophysics Data System (ADS)
Schwarzer, Stefan; Havlin, Shlomo; Bunde, Armin
1999-03-01
We study several structural properties including the shortest path l between two sites separated by a Euclidean distance r of invasion percolation with trapping (TIP) and without trapping (NIP). For the trapping case we find that the mass M scales with l as M~ldl with dl=1.510+/-0.005 and l scales with r as l~rdmin with dmin=1.213+/-0.005, whereas in the nontrapping case dl=1.671+/-0.006 and dmin=1.133+/-0.005. These values further support previous results that NIP and TIP are in distinct universality classes. We also study numerically using scaling approaches the distribution N(l,r) of the lengths of the shortest paths connecting two sites at distance r in NIP and TIP. We find that it obeys a scaling form N(l,r)~rdf-1-d minf(l/rdmin). The scaling function has a power-law tail for large x values, f(x)~x-h, with a universal value of h~2 for both models within our numerical accuracy.
Quan, Chanqin
2016-01-01
The state-of-the-art methods for protein-protein interaction (PPI) extraction are primarily based on kernel methods, and their performances strongly depend on the handcraft features. In this paper, we tackle PPI extraction by using convolutional neural networks (CNN) and propose a shortest dependency path based CNN (sdpCNN) model. The proposed method (1) only takes the sdp and word embedding as input and (2) could avoid bias from feature selection by using CNN. We performed experiments on standard Aimed and BioInfer datasets, and the experimental results demonstrated that our approach outperformed state-of-the-art kernel based methods. In particular, by tracking the sdpCNN model, we find that sdpCNN could extract key features automatically and it is verified that pretrained word embedding is crucial in PPI task. PMID:27493967
Panzacchi, Manuela; Van Moorter, Bram; Strand, Olav; Saerens, Marco; Kivimäki, Ilkka; St Clair, Colleen C; Herfindal, Ivar; Boitani, Luigi
2016-01-01
The loss, fragmentation and degradation of habitat everywhere on Earth prompts increasing attention to identifying landscape features that support animal movement (corridors) or impedes it (barriers). Most algorithms used to predict corridors assume that animals move through preferred habitat either optimally (e.g. least cost path) or as random walkers (e.g. current models), but neither extreme is realistic. We propose that corridors and barriers are two sides of the same coin and that animals experience landscapes as spatiotemporally dynamic corridor-barrier continua connecting (separating) functional areas where individuals fulfil specific ecological processes. Based on this conceptual framework, we propose a novel methodological approach that uses high-resolution individual-based movement data to predict corridor-barrier continua with increased realism. Our approach consists of two innovations. First, we use step selection functions (SSF) to predict friction maps quantifying corridor-barrier continua for tactical steps between consecutive locations. Secondly, we introduce to movement ecology the randomized shortest path algorithm (RSP) which operates on friction maps to predict the corridor-barrier continuum for strategic movements between functional areas. By modulating the parameter Ѳ, which controls the trade-off between exploration and optimal exploitation of the environment, RSP bridges the gap between algorithms assuming optimal movements (when Ѳ approaches infinity, RSP is equivalent to LCP) or random walk (when Ѳ → 0, RSP → current models). Using this approach, we identify migration corridors for GPS-monitored wild reindeer (Rangifer t. tarandus) in Norway. We demonstrate that reindeer movement is best predicted by an intermediate value of Ѳ, indicative of a movement trade-off between optimization and exploration. Model calibration allows identification of a corridor-barrier continuum that closely fits empirical data and demonstrates that RSP
Kwon, TaeKyu; Agrawal, Kunal; Li, Yunfeng; Pizlo, Zygmunt
2015-01-01
Finding the occluding contours of objects in real 2D retinal images of natural 3D scenes is done by determining, which contour fragments are relevant, and the order in which they should be connected. We developed a model that finds the closed contour represented in the image by solving a shortest path problem that uses a log-polar representation of the image; the kind of representation known to exist in area V1 of the primate cortex. The shortest path in a log-polar representation favors the smooth, convex and closed contours in the retinal image that have the smallest number of gaps. This approach is practical because finding a globally-optimal solution to a shortest path problem is computationally easy. Our model was tested in four psychophysical experiments. In the first two experiments, the subject was presented with a fragmented convex or concave polygon target among a large number of unrelated pieces of contour (distracters). The density of these pieces of contour was uniform all over the screen to minimize spatially-local cues. The orientation of each target contour fragment was randomly perturbed by varying the levels of jitter. Subjects drew a closed contour that represented the target’s contour on a screen. The subjects’ performance was nearly perfect when the jitter-level was low. Their performance deteriorated as jitter-levels were increased. The performance of our model was very similar to our subjects’. In two subsequent experiments, the subject was asked to discriminate a briefly-presented egg-shaped object while maintaining fixation at several different positions relative to the closed contour of the shape. The subject’s discrimination performance was affected by the fixation position in much the same way as the model’s. PMID:26241462
NASA Astrophysics Data System (ADS)
Shen, Yi; Ren, Gang; Liu, Yang
2016-06-01
In this paper, we propose a biased-shortest path method with minimal congestion. In the method, we use linear-prediction to estimate the queue length of nodes, and propose a dynamic accepting probability function for nodes to decide whether accept or reject the incoming packets. The dynamic accepting probability function is based on the idea of homogeneous network flow and is developed to enable nodes to coordinate their queue length to avoid congestion. A path strategy incorporated with the linear-prediction of the queue length and the dynamic accepting probability function of nodes is designed to allow packets to be automatically delivered on un-congested paths with short traveling time. Our method has the advantage of low computation cost because the optimal paths are dynamically self-organized by nodes in the delivering process of packets with local traffic information. We compare our method with the existing methods such as the efficient path method (EPS) and the optimal path method (OPS) on the BA scale-free networks and a real example. The numerical computations show that our method performs best for low network load and has minimum run time due to its low computational cost and local routing scheme.
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.
A Multilevel Probabilistic Beam Search Algorithm for the Shortest Common Supersequence Problem
Gallardo, José E.
2012-01-01
The shortest common supersequence problem is a classical problem with many applications in different fields such as planning, Artificial Intelligence and especially in Bioinformatics. Due to its NP-hardness, we can not expect to efficiently solve this problem using conventional exact techniques. This paper presents a heuristic to tackle this problem based on the use at different levels of a probabilistic variant of a classical heuristic known as Beam Search. The proposed algorithm is empirically analysed and compared to current approaches in the literature. Experiments show that it provides better quality solutions in a reasonable time for medium and large instances of the problem. For very large instances, our heuristic also provides better solutions, but required execution times may increase considerably. PMID:23300667
NASA Astrophysics Data System (ADS)
Wang, Xuewu; Shi, Yingpan; Ding, Dongyan; Gu, Xingsheng
2016-02-01
Spot-welding robots have a wide range of applications in manufacturing industries. There are usually many weld joints in a welding task, and a reasonable welding path to traverse these weld joints has a significant impact on welding efficiency. Traditional manual path planning techniques can handle a few weld joints effectively, but when the number of weld joints is large, it is difficult to obtain the optimal path. The traditional manual path planning method is also time consuming and inefficient, and cannot guarantee optimality. Double global optimum genetic algorithm-particle swarm optimization (GA-PSO) based on the GA and PSO algorithms is proposed to solve the welding robot path planning problem, where the shortest collision-free paths are used as the criteria to optimize the welding path. Besides algorithm effectiveness analysis and verification, the simulation results indicate that the algorithm has strong searching ability and practicality, and is suitable for welding robot path planning.
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
Su, Fangchu; Chen, Lei; Huang, Tao; Cai, Yu-Dong
2016-01-01
Biologically, fruits are defined as seed-bearing reproductive structures in angiosperms that develop from the ovary. The fertilization, development and maturation of fruits are crucial for plant reproduction and are precisely regulated by intrinsic genetic regulatory factors. In this study, we used Arabidopsis thaliana as a model organism and attempted to identify novel genes related to fruit-associated biological processes. Specifically, using validated genes, we applied a shortest-path-based method to identify several novel genes in a large network constructed using the protein-protein interactions observed in Arabidopsis thaliana. The described analyses indicate that several of the discovered genes are associated with fruit fertilization, development and maturation in Arabidopsis thaliana. PMID:27434024
Applications to determine the shortest tower BTS distance using Dijkstra algorithm
NASA Astrophysics Data System (ADS)
Mardana, Herwin; Maharani, Septya; Hatta, Heliza Rahmania
2017-02-01
Telecommunications Tower or so-called BTS (Base Transceiver System) Toweris one of the main components in the network infrastructure that has experienced an increase in the number of construction. Telecommunications tower function as a place to put the antenna signal transmitter (access network) to provide communication services to customers around the tower. In addition, other use of telecommunications tower also to place the transmission signal antenna (transport network using microwave technology) for connecting customers with a central area. Therefore, in needed of a decision support system that can provide recommendations planting route of fiber optic cable with the shortest distance in purpose the use of fiber optic cable becoming more efficient. The results of the research were the shortest rule information, showing the distance to be travelled and the map view to enabling users to look at these.
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.
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.
A-star algorithm based path planning for the glasses-free three-dimensional display system
NASA Astrophysics Data System (ADS)
Yang, Bin; Sang, Xinzhu; Xing, Shujun; Cui, Huilong; Yan, Binbin; Yu, Chongxiu; Dou, Wenhua; Xiao, Liquan
2016-10-01
A-Star (A*) algorithm is a heuristic directed search algorithm to evaluate the cost of moving along a particular path in the search space, which can get the shortest path. Here, path planning between any two points on the map is carried out. The STAGE tool is used to manually add way points on the map and determine their spatial location. The adjacent waypoint with a waypoint ID is connected by the line segment to form the navigation graph. A* algorithm can search the navigation graph to find the shortest path from a starting point to the destination. The A* algorithm can restart searching for path from a certain point, and the complex path can be divided in a plurality of frames. Since the navigation graph consists of the movable space, it is considered the obstacle formed by static objects in the scene, and collision detection between the character and static objects is not considered. A-star algorithm based path planning is experimentally demonstrated on a glasses-free three-dimensional display equipment, so that 3D effect of path finding can be perceived.
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.
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.
Incremental Multi-Scale Search Algorithm for Dynamic Path Planning With Low Worst-Case Complexity.
Yibiao Lu; Xiaoming Huo; Arslan, O; Tsiotras, P
2011-12-01
Path-planning (equivalently, path-finding) problems are fundamental in many applications, such as transportation, VLSI design, robot navigation, and many more. In this paper, we consider dynamic shortest path-planning problems on a graph with a single endpoint pair and with potentially changing edge weights over time. Several algorithms exist in the literature that solve this problem, notably among them the Lifelong Planning algorithm. The algorithm is an incremental search algorithm that replans the path when there are changes in the environment. In numerical experiments, however, it was observed that the performance of is sensitive in the number of vertex expansions required to update the graph when an edge weight value changes or when a vertex is added or deleted. Although, in most cases, the classical requires a relatively small number of updates, in some other cases the amount of work required by the to find the optimal path can be overwhelming. To address this issue, in this paper, we propose an extension of the baseline algorithm, by making efficient use of a multiscale representation of the environment. This multiscale representation allows one to quickly localize the changed edges, and subsequently update the priority queue efficiently. This incremental multiscale ( for short) algorithm leads to an improvement both in terms of robustness and computational complexity-in the worst case-when compared to the classical . Numerical experiments validate the aforementioned claims.
2012-09-13
38 2.4 Computational Complexity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40 2.5 Transportation Mode Selection...allowing the decision maker to tradeoff increases in the value obtained versus the number of arcs used. 9. Computational complexity proofs for the MASP... computational complexity , and transportation mode selection. Chapter 3 is a tutorial on Value Focused Thinking for Supply Chain Applications
Smith, Keith; Abasolo, Daniel; Escudero, Javier; Smith, Keith; Abasolo, Daniel; Escudero, Javier; Escudero, Javier; Smith, Keith; Abasolo, Daniel
2016-08-01
The Cluster-Span Threshold (CST) is a recently introduced unbiased threshold for functional connectivity networks. This binarisation technique offers a natural trade-off of sparsity and density of information by balancing the ratio of closed to open triples in the network topology. Here we present findings comparing it with the Union of Shortest Paths (USP), another recently proposed objective method. We analyse standard network metrics of binarised networks for sensitivity to clinical Alzheimer's disease in the Beta band of Electroencephalogram activity. We find that the CST outperforms the USP, as well as subjective thresholds based on fixing the network density, as a sensitive threshold for distinguishing differences in the functional connectivity between Alzheimer's disease patients and control. This study provides the first evidence of the usefulness of the CST for clinical research purposes.
Chen, Lei; Huang, Tao; Zhang, Yu-Hang; Jiang, Yang; Zheng, Mingyue; Cai, Yu-Dong
2016-01-01
Tumors are formed by the abnormal proliferation of somatic cells with disordered growth regulation under the influence of tumorigenic factors. Recently, the theory of “cancer drivers” connects tumor initiation with several specific mutations in the so-called cancer driver genes. According to the differentiation of four basic levels between tumor and adjacent normal tissues, the cancer drivers can be divided into the following: (1) Methylation level, (2) microRNA level, (3) mutation level, and (4) mRNA level. In this study, a computational method is proposed to identify novel lung adenocarcinoma drivers based on dysfunctional genes on the methylation, microRNA, mutation and mRNA levels. First, a large network was constructed using protein-protein interactions. Next, we searched all of the shortest paths connecting dysfunctional genes on different levels and extracted new candidate genes lying on these paths. Finally, the obtained candidate genes were filtered by a permutation test and an additional strict selection procedure involving a betweenness ratio and an interaction score. Several candidate genes remained, which are deemed to be related to two different levels of cancer. The analyses confirmed our assertions that some have the potential to contribute to the tumorigenesis process on multiple levels. PMID:27412431
NASA Astrophysics Data System (ADS)
Chen, Lei; Huang, Tao; Zhang, Yu-Hang; Jiang, Yang; Zheng, Mingyue; Cai, Yu-Dong
2016-07-01
Tumors are formed by the abnormal proliferation of somatic cells with disordered growth regulation under the influence of tumorigenic factors. Recently, the theory of “cancer drivers” connects tumor initiation with several specific mutations in the so-called cancer driver genes. According to the differentiation of four basic levels between tumor and adjacent normal tissues, the cancer drivers can be divided into the following: (1) Methylation level, (2) microRNA level, (3) mutation level, and (4) mRNA level. In this study, a computational method is proposed to identify novel lung adenocarcinoma drivers based on dysfunctional genes on the methylation, microRNA, mutation and mRNA levels. First, a large network was constructed using protein-protein interactions. Next, we searched all of the shortest paths connecting dysfunctional genes on different levels and extracted new candidate genes lying on these paths. Finally, the obtained candidate genes were filtered by a permutation test and an additional strict selection procedure involving a betweenness ratio and an interaction score. Several candidate genes remained, which are deemed to be related to two different levels of cancer. The analyses confirmed our assertions that some have the potential to contribute to the tumorigenesis process on multiple levels.
Zhang, Yu-Hang; Kong, Xiang-Yin
2017-01-01
Identification of disease genes is a hot topic in biomedicine and genomics. However, it is a challenging problem because of the complexity of diseases. Inflammatory bowel disease (IBD) is an idiopathic disease caused by a dysregulated immune response to host intestinal microflora. It has been proven to be associated with the development of intestinal malignancies. Although the specific pathological characteristics and genetic background of IBD have been partially revealed, it is still an overdetermined disease and the blueprint of all genetic variants still needs to be improved. In this study, a novel computational method was built to identify genes related to IBD. Samples from two subtypes of IBD (ulcerative colitis and Crohn's disease) and normal samples were employed. By analyzing the gene expression profiles of these samples using minimum redundancy maximum relevance and incremental feature selection, 21 genes were obtained that could effectively distinguish samples from the two subtypes of IBD and the normal samples. Then, the shortest-path approach was used to search for an additional 20 genes in a large network constructed using protein-protein interactions based on the above-mentioned 21 genes. Analyses of the 41 genes obtained indicate that they are closely associated with this disease. PMID:28293637
An ordinary differential equation based solution path algorithm.
Wu, Yichao
2011-01-01
Efron, Hastie, Johnstone and Tibshirani (2004) proposed Least Angle Regression (LAR), a solution path algorithm for the least squares regression. They pointed out that a slight modification of the LAR gives the LASSO (Tibshirani, 1996) solution path. However it is largely unknown how to extend this solution path algorithm to models beyond the least squares regression. In this work, we propose an extension of the LAR for generalized linear models and the quasi-likelihood model by showing that the corresponding solution path is piecewise given by solutions of ordinary differential equation systems. Our contribution is twofold. First, we provide a theoretical understanding on how the corresponding solution path propagates. Second, we propose an ordinary differential equation based algorithm to obtain the whole solution path.
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.
NASA Astrophysics Data System (ADS)
Mohammadi, E.; Hunter, A.
2012-07-01
Path finding solutions are becoming a major part of many GIS applications including location based services and web-based GIS services. Most traditional path finding solutions are based on shortest path algorithms that tend to minimize the cost of travel from one point to another. These algorithms make use of some cost criteria that is usually an attribute of the edges in the graph network. Providing one shortest path limits user's flexibility when choosing a possible route, especially when more than one parameter is utilized to calculate cost (e.g., when length, number of traffic lights, and number of turns are used to calculate network cost.) K shortest path solutions tend to overcome this problem by providing second, third, and Kth shortest paths. These algorithms are efficient as long as the graphs edge weight does not change dynamically and no other parameters affect edge weights. In this paper we try to go beyond finding shortest paths based on some cost value, and provide all possible paths disregarding any parameter that may affect total cost. After finding all possible paths, we can rank the results by any parameter or combination of parameters, without a substantial increase in time complexity.
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.
Algorithm of Finding Hypo-Critical Path in Network Planning
NASA Astrophysics Data System (ADS)
Qi, Jianxun; Zhao, Xiuhua
Network planning technology could be used to represent project plan management, such Critical Path Method (CPM for short) and Performance Evaluation Review Technique (PERT for short) etc. Aiming at problem that how to find hypo-critical path in network planning, firstly, properties of total float. free float and safety float are analyzed, and total float theorem is deduced on the basis of above analysis; and secondly, simple algorithm of finding the hypo-critical path is designed by using these properties of float and total theorem, and correctness of the algorithm is analyzed. Proof shows that the algorithm could realize effect of whole optimization could be realized by part optimization. Finally, one illustration is given to expatiate the algorithm.
Room Acoustical Simulation Algorithm Based on the Free Path Distribution
NASA Astrophysics Data System (ADS)
VORLÄNDER, M.
2000-04-01
A new algorithm is presented which provides estimates of impulse responses in rooms. It is applicable to arbitrary shaped rooms, thus including non-diffuse spaces like workrooms or offices. In the latter cases, for instance, sound propagation curves are of interest to be applied in noise control. In the case of concert halls and opera houses, the method enables very fast predictions of room acoustical criteria like reverberation time, strength or clarity. The method is based on a low-resolved ray tracing and recording of the free paths. Estimates of impulse responses are derived from evaluation of the free path distribution and of the free path transition probabilities.
Smell Detection Agent Based Optimization Algorithm
NASA Astrophysics Data System (ADS)
Vinod Chandra, S. S.
2016-09-01
In this paper, a novel nature-inspired optimization algorithm has been employed and the trained behaviour of dogs in detecting smell trails is adapted into computational agents for problem solving. The algorithm involves creation of a surface with smell trails and subsequent iteration of the agents in resolving a path. This algorithm can be applied in different computational constraints that incorporate path-based problems. Implementation of the algorithm can be treated as a shortest path problem for a variety of datasets. The simulated agents have been used to evolve the shortest path between two nodes in a graph. This algorithm is useful to solve NP-hard problems that are related to path discovery. This algorithm is also useful to solve many practical optimization problems. The extensive derivation of the algorithm can be enabled to solve shortest path problems.
A Bat Algorithm with Mutation for UCAV Path Planning
Wang, Gaige; Guo, Lihong; Duan, Hong; Liu, Luo; Wang, Heqi
2012-01-01
Path planning for uninhabited combat air vehicle (UCAV) is a complicated high dimension optimization problem, which mainly centralizes on optimizing the flight route considering the different kinds of constrains under complicated battle field environments. Original bat algorithm (BA) is used to solve the UCAV path planning problem. Furthermore, a new bat algorithm with mutation (BAM) is proposed to solve the UCAV path planning problem, and a modification is applied to mutate between bats during the process of the new solutions updating. Then, the UCAV can find the safe path by connecting the chosen nodes of the coordinates while avoiding the threat areas and costing minimum fuel. This new approach can accelerate the global convergence speed while preserving the strong robustness of the basic BA. The realization procedure for original BA and this improved metaheuristic approach BAM is also presented. To prove the performance of this proposed metaheuristic method, BAM is compared with BA and other population-based optimization methods, such as ACO, BBO, DE, ES, GA, PBIL, PSO, and SGA. The experiment shows that the proposed approach is more effective and feasible in UCAV path planning than the other models. PMID:23365518
Path Planning Algorithms for the Adaptive Sensor Fleet
NASA Technical Reports Server (NTRS)
Stoneking, Eric; Hosler, Jeff
2005-01-01
The Adaptive Sensor Fleet (ASF) is a general purpose fleet management and planning system being developed by NASA in coordination with NOAA. The current mission of ASF is to provide the capability for autonomous cooperative survey and sampling of dynamic oceanographic phenomena such as current systems and algae blooms. Each ASF vessel is a software model that represents a real world platform that carries a variety of sensors. The OASIS platform will provide the first physical vessel, outfitted with the systems and payloads necessary to execute the oceanographic observations described in this paper. The ASF architecture is being designed for extensibility to accommodate heterogenous fleet elements, and is not limited to using the OASIS platform to acquire data. This paper describes the path planning algorithms developed for the acquisition phase of a typical ASF task. Given a polygonal target region to be surveyed, the region is subdivided according to the number of vessels in the fleet. The subdivision algorithm seeks a solution in which all subregions have equal area and minimum mean radius. Once the subregions are defined, a dynamic programming method is used to find a minimum-time path for each vessel from its initial position to its assigned region. This path plan includes the effects of water currents as well as avoidance of known obstacles. A fleet-level planning algorithm then shuffles the individual vessel assignments to find the overall solution which puts all vessels in their assigned regions in the minimum time. This shuffle algorithm may be described as a process of elimination on the sorted list of permutations of a cost matrix. All these path planning algorithms are facilitated by discretizing the region of interest onto a hexagonal tiling.
Analysis of the contact graph routing algorithm: Bounding interplanetary paths
NASA Astrophysics Data System (ADS)
Birrane, Edward; Burleigh, Scott; Kasch, Niels
2012-06-01
Interplanetary communication networks comprise orbiters, deep-space relays, and stations on planetary surfaces. These networks must overcome node mobility, constrained resources, and significant propagation delays. Opportunities for wireless contact rely on calculating transmit and receive opportunities, but the Euclidean-distance diameter of these networks (measured in light-seconds and light-minutes) precludes node discovery and contact negotiation. Propagation delay may be larger than the line-of-sight contact between nodes. For example, Mars and Earth orbiters may be separated by up to 20.8 min of signal propagation time. Such spacecraft may never share line-of-sight, but may uni-directionally communicate if one orbiter knows the other's future position. The Contact Graph Routing (CGR) approach is a family of algorithms presented to solve the messaging problem of interplanetary communications. These algorithms exploit networks where nodes exhibit deterministic mobility. For CGR, mobility and bandwidth information is pre-configured throughout the network allowing nodes to construct transmit opportunities. Once constructed, routing algorithms operate on this contact graph to build an efficient path through the network. The interpretation of the contact graph, and the construction of a bounded approximate path, is critically important for adoption in operational systems. Brute force approaches, while effective in small networks, are computationally expensive and will not scale. Methods of inferring cycles or other librations within the graph are difficult to detect and will guide the practical implementation of any routing algorithm. This paper presents a mathematical analysis of a multi-destination contact graph algorithm (MD-CGR), demonstrates that it is NP-complete, and proposes realistic constraints that make the problem solvable in polynomial time, as is the case with the originally proposed CGR algorithm. An analysis of path construction to complement hop
Improved ant colony algorithm for global path planning
NASA Astrophysics Data System (ADS)
Li, Pengfei; Wang, Hongbo; Li, Xiaogang
2017-03-01
The ant colony algorithm has many advantages compared with other algorithms in path planning, but its shortcomings still cannot be ignored. For example, the convergence speed is very low at initial stage, it is easy to fall into the local optimal solution, and the solution speed is slow and so on. In order to solve these problems and reduce the search time, this paper firstly makes the assignment of the main parameters of α, β, M and ρ in the ant colony algorithm through a large number of experimental data analysis. Then an improved ant colony algorithm based on dynamic parameters and new pheromone updating mechanism is proposed in this paper. Simulation results show that the improved ant colony algorithm can not only greatly shorten the algorithm running time, but also has greater probability to get the global optimal solution, and the convergence rate of algorithm is better than traditional ant colony algorithm. It is very advantageous for solving large-scale optimization problems.
Density shrinking algorithm for community detection with path based similarity
NASA Astrophysics Data System (ADS)
Wu, Jianshe; Hou, Yunting; Jiao, Yang; Li, Yong; Li, Xiaoxiao; Jiao, Licheng
2015-09-01
Community structure is ubiquitous in real world complex networks. Finding the communities is the key to understand the functions of those networks. A lot of works have been done in designing algorithms for community detection, but it remains a challenge in the field. Traditional modularity optimization suffers from the resolution limit problem. Recent researches show that combining the density based technique with the modularity optimization can overcome the resolution limit and an efficient algorithm named DenShrink was provided. The main procedure of DenShrink is repeatedly finding and merging micro-communities (broad sense) into super nodes until they cannot merge. Analyses in this paper show that if the procedure is replaced by finding and merging only dense pairs, both of the detection accuracy and runtime can be obviously improved. Thus an improved density-based algorithm: ImDS is provided. Since the time complexity, path based similarity indexes are difficult to be applied in community detection for high performance. In this paper, the path based Katz index is simplified and used in the ImDS algorithm.
A surface hopping algorithm for nonadiabatic minimum energy path calculations.
Schapiro, Igor; Roca-Sanjuán, Daniel; Lindh, Roland; Olivucci, Massimo
2015-02-15
The article introduces a robust algorithm for the computation of minimum energy paths transiting along regions of near-to or degeneracy of adiabatic states. The method facilitates studies of excited state reactivity involving weakly avoided crossings and conical intersections. Based on the analysis of the change in the multiconfigurational wave function the algorithm takes the decision whether the optimization should continue following the same electronic state or switch to a different state. This algorithm helps to overcome convergence difficulties near degeneracies. The implementation in the MOLCAS quantum chemistry package is discussed. To demonstrate the utility of the proposed procedure four examples of application are provided: thymine, asulam, 1,2-dioxetane, and a three-double-bond model of the 11-cis-retinal protonated Schiff base.
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
Investigation and Implementation of an Algorithm for Computing Optimal Search Paths
1987-09-01
of a convex objective function subject to the flow constraints of an acyclic N x T network . Lower bounds are obtained via the Frank-Wolfe method of...solution specialized for acyclic networks . This technique relies on linearization of the objective function to yield a shortest path problem ,0 D S’Q...function subject to the flow constraints of an acyclic N x T network . Lower bounds are obtained via the Frank-Wolf/e method of solution specialized
Coevolving solutions to the shortest common superstring problem.
Zaritsky, Assaf; Sipper, Moshe
2004-01-01
The shortest common superstring (SCS) problem, known to be NP-Complete, seeks the shortest string that contains all strings from a given set. In this paper we compare four approaches for finding solutions to the SCS problem: a standard genetic algorithm, a novel cooperative-coevolutionary algorithm, a benchmark greedy algorithm, and a parallel coevolutionary-greedy approach. We show the coevolutionary approach produces the best results, and discuss directions for future research.
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.
Robust three-dimensional best-path phase-unwrapping algorithm that avoids singularity loops.
Abdul-Rahman, Hussein; Arevalillo-Herráez, Miguel; Gdeisat, Munther; Burton, David; Lalor, Michael; Lilley, Francis; Moore, Christopher; Sheltraw, Daniel; Qudeisat, Mohammed
2009-08-10
In this paper we propose a novel hybrid three-dimensional phase-unwrapping algorithm, which we refer to here as the three-dimensional best-path avoiding singularity loops (3DBPASL) algorithm. This algorithm combines the advantages and avoids the drawbacks of two well-known 3D phase-unwrapping algorithms, namely, the 3D phase-unwrapping noise-immune technique and the 3D phase-unwrapping best-path technique. The hybrid technique presented here is more robust than its predecessors since it not only follows a discrete unwrapping path depending on a 3D quality map, but it also avoids any singularity loops that may occur in the unwrapping path. Simulation and experimental results have shown that the proposed algorithm outperforms its parent techniques in terms of reliability and robustness.
Chandrasekaran, Srinivas Niranj; Das, Jhuma; Dokholyan, Nikolay V.; Carter, Charles W.
2016-01-01
PATH rapidly computes a path and a transition state between crystal structures by minimizing the Onsager-Machlup action. It requires input parameters whose range of values can generate different transition-state structures that cannot be uniquely compared with those generated by other methods. We outline modifications to estimate these input parameters to circumvent these difficulties and validate the PATH transition states by showing consistency between transition-states derived by different algorithms for unrelated protein systems. Although functional protein conformational change trajectories are to a degree stochastic, they nonetheless pass through a well-defined transition state whose detailed structural properties can rapidly be identified using PATH. PMID:26958584
Birkholz, Adam B.; Schlegel, H. Bernhard
2015-12-28
The development of algorithms to optimize reaction pathways between reactants and products is an active area of study. Existing algorithms typically describe the path as a discrete series of images (chain of states) which are moved downhill toward the path, using various reparameterization schemes, constraints, or fictitious forces to maintain a uniform description of the reaction path. The Variational Reaction Coordinate (VRC) method is a novel approach that finds the reaction path by minimizing the variational reaction energy (VRE) of Quapp and Bofill. The VRE is the line integral of the gradient norm along a path between reactants and products and minimization of VRE has been shown to yield the steepest descent reaction path. In the VRC method, we represent the reaction path by a linear expansion in a set of continuous basis functions and find the optimized path by minimizing the VRE with respect to the linear expansion coefficients. Improved convergence is obtained by applying constraints to the spacing of the basis functions and coupling the minimization of the VRE to the minimization of one or more points along the path that correspond to intermediates and transition states. The VRC method is demonstrated by optimizing the reaction path for the Müller-Brown surface and by finding a reaction path passing through 5 transition states and 4 intermediates for a 10 atom Lennard-Jones cluster.
An algorithm to find critical execution paths of software based on complex network
NASA Astrophysics Data System (ADS)
Huang, Guoyan; Zhang, Bing; Ren, Rong; Ren, Jiadong
2015-01-01
The critical execution paths play an important role in software system in terms of reducing the numbers of test date, detecting the vulnerabilities of software structure and analyzing software reliability. However, there are no efficient methods to discover them so far. Thus in this paper, a complex network-based software algorithm is put forward to find critical execution paths (FCEP) in software execution network. First, by analyzing the number of sources and sinks in FCEP, software execution network is divided into AOE subgraphs, and meanwhile, a Software Execution Network Serialization (SENS) approach is designed to generate execution path set in each AOE subgraph, which not only reduces ring structure's influence on path generation, but also guarantees the nodes' integrity in network. Second, according to a novel path similarity metric, similarity matrix is created to calculate the similarity among sets of path sequences. Third, an efficient method is taken to cluster paths through similarity matrices, and the maximum-length path in each cluster is extracted as the critical execution path. At last, a set of critical execution paths is derived. The experimental results show that the FCEP algorithm is efficient in mining critical execution path under software complex network.
The Path-of-Probability Algorithm for Steering and Feedback Control of Flexible Needles
Park, Wooram; Wang, Yunfeng; Chirikjian, Gregory S.
2010-01-01
In this paper we develop a new framework for path planning of flexible needles with bevel tips. Based on a stochastic model of needle steering, the probability density function for the needle tip pose is approximated as a Gaussian. The means and covariances are estimated using an error propagation algorithm which has second order accuracy. Then we adapt the path-of-probability (POP) algorithm to path planning of flexible needles with bevel tips. We demonstrate how our planning algorithm can be used for feedback control of flexible needles. We also derive a closed-form solution for the port placement problem for finding good insertion locations for flexible needles in the case when there are no obstacles. Furthermore, we propose a new method using reference splines with the POP algorithm to solve the path planning problem for flexible needles in more general cases that include obstacles. PMID:21151708
A simple and accurate algorithm for path integral molecular dynamics with the Langevin thermostat.
Liu, Jian; Li, Dezhang; Liu, Xinzijian
2016-07-14
We introduce a novel simple algorithm for thermostatting path integral molecular dynamics (PIMD) with the Langevin equation. The staging transformation of path integral beads is employed for demonstration. The optimum friction coefficients for the staging modes in the free particle limit are used for all systems. In comparison to the path integral Langevin equation thermostat, the new algorithm exploits a different order of splitting for the phase space propagator associated to the Langevin equation. While the error analysis is made for both algorithms, they are also employed in the PIMD simulations of three realistic systems (the H2O molecule, liquid para-hydrogen, and liquid water) for comparison. It is shown that the new thermostat increases the time interval of PIMD by a factor of 4-6 or more for achieving the same accuracy. In addition, the supplementary material shows the error analysis made for the algorithms when the normal-mode transformation of path integral beads is used.
A simple and accurate algorithm for path integral molecular dynamics with the Langevin thermostat
NASA Astrophysics Data System (ADS)
Liu, Jian; Li, Dezhang; Liu, Xinzijian
2016-07-01
We introduce a novel simple algorithm for thermostatting path integral molecular dynamics (PIMD) with the Langevin equation. The staging transformation of path integral beads is employed for demonstration. The optimum friction coefficients for the staging modes in the free particle limit are used for all systems. In comparison to the path integral Langevin equation thermostat, the new algorithm exploits a different order of splitting for the phase space propagator associated to the Langevin equation. While the error analysis is made for both algorithms, they are also employed in the PIMD simulations of three realistic systems (the H2O molecule, liquid para-hydrogen, and liquid water) for comparison. It is shown that the new thermostat increases the time interval of PIMD by a factor of 4-6 or more for achieving the same accuracy. In addition, the supplementary material shows the error analysis made for the algorithms when the normal-mode transformation of path integral beads is used.
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
Ghosal, Dipak; Mueller, Stephen Ng
2005-04-01
With multipath routing in mobile ad hoc networks (MANETs), a source can establish multiple routes to a destination for routing data. In MANETs, mulitpath routing can be used to provide route resilience, smaller end-to-end delay, and better load balancing. However, when the multiple paths are close together, transmissions of different paths may interfere with each other, causing degradation in performance. Besides interference, the physical diversity of paths also improves fault tolerance. We present a purely distributed multipath protocol based on the AODV-Multipath (AODVM) protocol called AODVM with Path Diversity (AODVM/PD) that finds multiple paths with a desired degree of correlation between paths specified as an input parameter to the algorithm. We demonstrate through detailed simulation analysis that multiple paths with low degree of correlation determined by AODVM/PD provides both smaller end-to-end delay than AODVM in networks with low mobility and better route resilience in the presence of correlated node failures.
Transport path optimization algorithm based on fuzzy integrated weights
NASA Astrophysics Data System (ADS)
Hou, Yuan-Da; Xu, Xiao-Hao
2014-11-01
Natural disasters cause significant damage to roads, making route selection a complicated logistical problem. To overcome this complexity, we present a method of using a trapezoidal fuzzy number to select the optimal transport path. Using the given trapezoidal fuzzy edge coefficients, we calculate a fuzzy integrated matrix, and incorporate the fuzzy multi-weights into fuzzy integrated weights. The optimal path is determined by taking two sets of vertices and transforming undiscovered vertices into discoverable ones. Our experimental results show that the model is highly accurate, and requires only a few measurement data to confirm the optimal path. The model provides an effective, feasible, and convenient method to obtain weights for different road sections, and can be applied to road planning in intelligent transportation systems.
Efficient algorithms for finding disjoint paths in grids
Chan, Wun-Tat; Chin, F.Y.L.
1997-06-01
The reconfiguration problem on VLSI/WSI processor arrays in the presence of faulty processors can be stated as the following integral multi-source routing problem: Given a set of N nodes (faulty processors or sources) in am m x n rectangular grid where m, n {le} N, the problem to be solved is to connect the N nodes to distinct nodes at the grid boundary using a set of {open_quotes}disjoint{close_quotes} paths. This problem can be referred to as an escape problem which can be solved trivially in O(mnN) time. By exploiting all the properties of the network, planarity and regularity of a grid, integral flow, and unit capacity source/sink/flow, we can optimally compress the size of the grid from O(mn) to O({radical}mnN) and solve the problem in O(d{radical}mnN), where d is the maximum number of disjoint paths found, for both the edge-disjoint and vertex-disjoint cases. In the worst case, d, m, n are O(N) and the result is O(N{sup 2.5}). Note that this routing problem can also be solved with the same time complexity even if the disjoint paths have to be ended at another set of N nodes (sinks) in the grid instead of the grid boundary.
Path Optimization for Single and Multiple Searchers: Models and Algorithms
2008-09-01
the k-th it- eration of Algorithm 11, the master problem MP4 (k) defined below is solved. The optimal value and optimal solution of MP4 (k) are denoted z...k) and y(k), respectively. In each iteration of Algorithm 11, U cuts are generated at once. Formulation of Master problem : MP4 (k) min z = ∑U u=1...master problem MP4 (k), and obtain its optimal value z(k) and optimal solution y(k). If z(k) > q, then q = z(k). Step 3. Calculate fu(y (k)) and fu(y (k
An Innovative Multi-Agent Search-and-Rescue Path Planning Approach
2015-03-09
path planning may be found in the robotics literature in the area of robot motion planning [8] and, namely, terrain acquisition [9], [10] and coverage...path planning [11],[12], [13]. Robot motion planning explored search path planning, primarily providing constrained shortest path type solutions...involving unknown sparsely distributed static targets and obstacles. Separate work on robot search algorithms is also referenced on the pursuit
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.
Spatial interpolation of river channel topography using the shortest temporal distance
NASA Astrophysics Data System (ADS)
Zhang, Yanjun; Xian, Cuiling; Chen, Huajin; Grieneisen, Michael L.; Liu, Jiaming; Zhang, Minghua
2016-11-01
It is difficult to interpolate river channel topography due to complex anisotropy. As the anisotropy is often caused by river flow, especially the hydrodynamic and transport mechanisms, it is reasonable to incorporate flow velocity into topography interpolator for decreasing the effect of anisotropy. In this study, two new distance metrics defined as the time taken by water flow to travel between two locations are developed, and replace the spatial distance metric or Euclidean distance that is currently used to interpolate topography. One is a shortest temporal distance (STD) metric. The temporal distance (TD) of a path between two nodes is calculated by spatial distance divided by the tangent component of flow velocity along the path, and the STD is searched using the Dijkstra algorithm in all possible paths between two nodes. The other is a modified shortest temporal distance (MSTD) metric in which both the tangent and normal components of flow velocity were combined. They are used to construct the methods for the interpolation of river channel topography. The proposed methods are used to generate the topography of Wuhan Section of Changjiang River and compared with Universal Kriging (UK) and Inverse Distance Weighting (IDW). The results clearly showed that the STD and MSTD based on flow velocity were reliable spatial interpolators. The MSTD, followed by the STD, presents improvement in prediction accuracy relative to both UK and IDW.
A Scheduling Algorithm for Cloud Computing System Based on the Driver of Dynamic Essential Path.
Xie, Zhiqiang; Shao, Xia; Xin, Yu
2016-01-01
To solve the problem of task scheduling in the cloud computing system, this paper proposes a scheduling algorithm for cloud computing based on the driver of dynamic essential path (DDEP). This algorithm applies a predecessor-task layer priority strategy to solve the problem of constraint relations among task nodes. The strategy assigns different priority values to every task node based on the scheduling order of task node as affected by the constraint relations among task nodes, and the task node list is generated by the different priority value. To address the scheduling order problem in which task nodes have the same priority value, the dynamic essential long path strategy is proposed. This strategy computes the dynamic essential path of the pre-scheduling task nodes based on the actual computation cost and communication cost of task node in the scheduling process. The task node that has the longest dynamic essential path is scheduled first as the completion time of task graph is indirectly influenced by the finishing time of task nodes in the longest dynamic essential path. Finally, we demonstrate the proposed algorithm via simulation experiments using Matlab tools. The experimental results indicate that the proposed algorithm can effectively reduce the task Makespan in most cases and meet a high quality performance objective.
A Scheduling Algorithm for Cloud Computing System Based on the Driver of Dynamic Essential Path
Xie, Zhiqiang; Shao, Xia; Xin, Yu
2016-01-01
To solve the problem of task scheduling in the cloud computing system, this paper proposes a scheduling algorithm for cloud computing based on the driver of dynamic essential path (DDEP). This algorithm applies a predecessor-task layer priority strategy to solve the problem of constraint relations among task nodes. The strategy assigns different priority values to every task node based on the scheduling order of task node as affected by the constraint relations among task nodes, and the task node list is generated by the different priority value. To address the scheduling order problem in which task nodes have the same priority value, the dynamic essential long path strategy is proposed. This strategy computes the dynamic essential path of the pre-scheduling task nodes based on the actual computation cost and communication cost of task node in the scheduling process. The task node that has the longest dynamic essential path is scheduled first as the completion time of task graph is indirectly influenced by the finishing time of task nodes in the longest dynamic essential path. Finally, we demonstrate the proposed algorithm via simulation experiments using Matlab tools. The experimental results indicate that the proposed algorithm can effectively reduce the task Makespan in most cases and meet a high quality performance objective. PMID:27490901
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 new chirp scaling algorithm of bistatic SAR with parallel flight paths
NASA Astrophysics Data System (ADS)
Li, Ning; Wang, Luping
2011-10-01
The precise point target reference spectrum of bistatic SAR has been a difficult problem for a long time. Many of the current available algorithms have approximation during deducing. This paper deduces the precise expression in Doppler- Frequency domain with the configuration of parallel flight paths and constant velocity of each platform. Then a new chirp scaling algorithm is put forward. At last, simulations are given to demonstrate the good focusing performance.
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.
Generalized Hough transform: A useful algorithm for signal path detection
NASA Astrophysics Data System (ADS)
Monari, Jader; Montebugnoli, Stelio; Orlati, Andrea; Ferri, Massimo; Leone, Giorgio
2006-02-01
How is it possible to recognize ETI signals coming from exoplanets? This is one of the questions that SETI researchers must answer. In early 1998, the Italian SETI program [S. Montebugnoli, et al., SETItalia, A new era in bioastronomy, ASP Conference Series, vol. 213, 2000, pp. 501-504.] started in Medicina with the installation of the Serendip IV 24Million Channel digital spectrometer. This system daily acquires a huge quantity of data to be processed off line, in order to detect possible ETI signals. The programs devoted to this topic are collectively called SALVE 2. Here a natural evolution of a previous effort is presented, which was based on a simple Hough transform and was limited to the detection of short linear tracks in the join time frequency matrix (JTFM) stored by SIV. The new generalized Hough algorithm allows us to detect the sinusoidal tracks by the transformation of the JTF bidimensional Cartesian space (x,y), in the generalized Hough quadridimensional space, where the main vectors are the sine parameters amplitude, frequency, phase and offset. At the end of the paper some results, obtained with the computation of real and simulated JTFM, are shown.
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.
2005-12-01
a user for a patrol mission. To increase the vehicle’s abilities, other behaviours such as obstacle avoidance, path planning or leader / follower augment...15 5.4 Leader / Follower Behaviour . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 5.5 Waypoint Following...Navigation Behaviour - Provide goal directedness in concert with an obstacle avoid- ance algorithm. 3. Leader / Follower - Allow a follower vehicle to
NASA Astrophysics Data System (ADS)
Liu, Wei; Ma, Shunjian; Sun, Mingwei; Yi, Haidong; Wang, Zenghui; Chen, Zengqiang
2016-08-01
Path planning plays an important role in aircraft guided systems. Multiple no-fly zones in the flight area make path planning a constrained nonlinear optimization problem. It is necessary to obtain a feasible optimal solution in real time. In this article, the flight path is specified to be composed of alternate line segments and circular arcs, in order to reformulate the problem into a static optimization one in terms of the waypoints. For the commonly used circular and polygonal no-fly zones, geometric conditions are established to determine whether or not the path intersects with them, and these can be readily programmed. Then, the original problem is transformed into a form that can be solved by the sequential quadratic programming method. The solution can be obtained quickly using the Sparse Nonlinear OPTimizer (SNOPT) package. Mathematical simulations are used to verify the effectiveness and rapidity of the proposed algorithm.
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.
Rao, Akshay; Elara, Mohan Rajesh; Elangovan, Karthikeyan
This paper aims to develop a local path planning algorithm for a bio-inspired, reconfigurable crawling robot. A detailed description of the robotic platform is first provided, and the suitability for deployment of each of the current state-of-the-art local path planners is analyzed after an extensive literature review. The Enhanced Vector Polar Histogram algorithm is described and reformulated to better fit the requirements of the platform. The algorithm is deployed on the robotic platform in crawling configuration and favorably compared with other state-of-the-art local path planning algorithms.
Speed-up hyperspheres homotopic path tracking algorithm for PWL circuits simulations.
Ramirez-Pinero, A; Vazquez-Leal, H; Jimenez-Fernandez, V M; Sedighi, H M; Rashidi, M M; Filobello-Nino, U; Castaneda-Sheissa, R; Huerta-Chua, J; Sarmiento-Reyes, L A; Laguna-Camacho, J R; Castro-Gonzalez, F
2016-01-01
In the present work, we introduce an improved version of the hyperspheres path tracking method adapted for piecewise linear (PWL) circuits. This enhanced version takes advantage of the PWL characteristics from the homotopic curve, achieving faster path tracking and improving the performance of the homotopy continuation method (HCM). Faster computing time allows the study of complex circuits with higher complexity; the proposed method also decrease, significantly, the probability of having a diverging problem when using the Newton-Raphson method because it is applied just twice per linear region on the homotopic path. Equilibrium equations of the studied circuits are obtained applying the modified nodal analysis; this method allows to propose an algorithm for nonlinear circuit analysis. Besides, a starting point criteria is proposed to obtain better performance of the HCM and a technique for avoiding the reversion phenomenon is also proposed. To prove the efficiency of the path tracking method, several cases study with bipolar (BJT) and CMOS transistors are provided. Simulation results show that the proposed approach can be up to twelve times faster than the original path tracking method and also helps to avoid several reversion cases that appears when original hyperspheres path tracking scheme was employed.
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).
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.
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.
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.
Zhao, Tuo; Liu, Han
2016-01-01
We propose an accelerated path-following iterative shrinkage thresholding algorithm (APISTA) for solving high dimensional sparse nonconvex learning problems. The main difference between APISTA and the path-following iterative shrinkage thresholding algorithm (PISTA) is that APISTA exploits an additional coordinate descent subroutine to boost the computational performance. Such a modification, though simple, has profound impact: APISTA not only enjoys the same theoretical guarantee as that of PISTA, i.e., APISTA attains a linear rate of convergence to a unique sparse local optimum with good statistical properties, but also significantly outperforms PISTA in empirical benchmarks. As an application, we apply APISTA to solve a family of nonconvex optimization problems motivated by estimating sparse semiparametric graphical models. APISTA allows us to obtain new statistical recovery results which do not exist in the existing literature. Thorough numerical results are provided to back up our theory. PMID:28133430
A novel load-balanced fixed routing (LBFR) algorithm for wavelength routed optical networks
NASA Astrophysics Data System (ADS)
Shen, Gangxiang; Li, Yongcheng; Peng, Limei
2011-11-01
In the wavelength-routed optical transport networks, fixed shortest path routing is one of major lightpath service provisioning strategies, which shows simplicity in network control and operation. Specifically, once a shortest route is found for a node pair, the route is always used for any future lightpath service provisioning, which therefore does not require network control and management system to maintain any active network-wide link state database. On the other hand, the fixed shortest path routing strategy suffers from the disadvantage of unbalanced network traffic load distribution and network congestion because it keeps on employing the same fixed shortest route between each pair of nodes. To avoid the network congestion and meanwhile retain the operational simplicity, in this study we develop a Load-Balanced Fixed Routing (LBFR) algorithm. Through a training process based on a forecasted network traffic load matrix, the proposed algorithm finds a fixed (or few) route(s) for each node pair and employs the fixed route(s) for lightpath service provisioning. Different from the fixed shortest path routes between node pairs, these routes can well balance traffic load within the network when they are used for lightpath service provisioning. Compared to the traditional fixed shortest path routing algorithm, the LBFR algorithm can achieve much better lightpath blocking performance according to our simulation and analytical studies. Moreover, the performance improvement is more significant with the increase of network nodal degree.
An efficient algorithm for finding the minimum energy path for cation migration in ionic materials.
Rong, Ziqin; Kitchaev, Daniil; Canepa, Pieremanuele; Huang, Wenxuan; Ceder, Gerbrand
2016-08-21
The Nudged Elastic Band (NEB) is an established method for finding minimum-energy paths and energy barriers of ion migration in materials, but has been hampered in its general application by its significant computational expense when coupled with density functional theory (DFT) calculations. Typically, an NEB calculation is initialized from a linear interpolation of successive intermediate structures (also known as images) between known initial and final states. However, the linear interpolation introduces two problems: (1) slow convergence of the calculation, particularly in cases where the final path exhibits notable curvature; (2) divergence of the NEB calculations if any intermediate image comes too close to a non-diffusing species, causing instabilities in the ensuing calculation. In this work, we propose a new scheme to accelerate NEB calculations through an improved path initialization and associated energy estimation workflow. We demonstrate that for cation migration in an ionic framework, initializing the diffusion path as the minimum energy path through a static potential built upon the DFT charge density reproduces the true NEB path within a 0.2 Å deviation and yields up to a 25% improvement in typical NEB runtimes. Furthermore, we find that the locally relaxed energy barrier derived from this initialization yields a good approximation of the NEB barrier, with errors within 20 meV of the true NEB value, while reducing computational expense by up to a factor of 5. Finally, and of critical importance for the automation of migration path calculations in high-throughput studies, we find that the new approach significantly enhances the stability of the calculation by avoiding unphysical image initialization. Our algorithm promises to enable efficient calculations of diffusion pathways, resolving a long-standing obstacle to the computational screening of intercalation compounds for Li-ion and multivalent batteries.
An efficient algorithm for finding the minimum energy path for cation migration in ionic materials
NASA Astrophysics Data System (ADS)
Rong, Ziqin; Kitchaev, Daniil; Canepa, Pieremanuele; Huang, Wenxuan; Ceder, Gerbrand
2016-08-01
The Nudged Elastic Band (NEB) is an established method for finding minimum-energy paths and energy barriers of ion migration in materials, but has been hampered in its general application by its significant computational expense when coupled with density functional theory (DFT) calculations. Typically, an NEB calculation is initialized from a linear interpolation of successive intermediate structures (also known as images) between known initial and final states. However, the linear interpolation introduces two problems: (1) slow convergence of the calculation, particularly in cases where the final path exhibits notable curvature; (2) divergence of the NEB calculations if any intermediate image comes too close to a non-diffusing species, causing instabilities in the ensuing calculation. In this work, we propose a new scheme to accelerate NEB calculations through an improved path initialization and associated energy estimation workflow. We demonstrate that for cation migration in an ionic framework, initializing the diffusion path as the minimum energy path through a static potential built upon the DFT charge density reproduces the true NEB path within a 0.2 Å deviation and yields up to a 25% improvement in typical NEB runtimes. Furthermore, we find that the locally relaxed energy barrier derived from this initialization yields a good approximation of the NEB barrier, with errors within 20 meV of the true NEB value, while reducing computational expense by up to a factor of 5. Finally, and of critical importance for the automation of migration path calculations in high-throughput studies, we find that the new approach significantly enhances the stability of the calculation by avoiding unphysical image initialization. Our algorithm promises to enable efficient calculations of diffusion pathways, resolving a long-standing obstacle to the computational screening of intercalation compounds for Li-ion and multivalent batteries.
NASA Astrophysics Data System (ADS)
Siregar, B.; Gunawan, D.; Andayani, U.; Sari Lubis, Elita; Fahmi, F.
2017-01-01
Food delivery system is one kind of geographical information systems (GIS) that can be applied through digitation process. The main case in food delivery system is the way to determine the shortest path and food delivery vehicle movement tracking. Therefore, to make sure that the digitation process of food delivery system can be applied efficiently, it is needed to add shortest path determination facility and food delivery vehicle tracking. This research uses A Star (A*) algorithm for determining shortest path and location-based system (LBS) programming for moving food delivery vehicle object tracking. According to this research, it is generated the integrated system that can be used by food delivery driver, customer, and administrator in terms of simplifying the food delivery system. Through the application of shortest path and the tracking of moving vehicle, thus the application of food delivery system in the scope of geographical information system (GIS) can be executed.
A one-way shooting algorithm for transition path sampling of asymmetric barriers.
Brotzakis, Z Faidon; Bolhuis, Peter G
2016-10-28
We present a novel transition path sampling shooting algorithm for the efficient sampling of complex (biomolecular) activated processes with asymmetric free energy barriers. The method employs a fictitious potential that biases the shooting point toward the transition state. The method is similar in spirit to the aimless shooting technique by Peters and Trout [J. Chem. Phys. 125, 054108 (2006)], but is targeted for use with the one-way shooting approach, which has been shown to be more effective than two-way shooting algorithms in systems dominated by diffusive dynamics. We illustrate the method on a 2D Langevin toy model, the association of two peptides and the initial step in dissociation of a β-lactoglobulin dimer. In all cases we show a significant increase in efficiency.
A one-way shooting algorithm for transition path sampling of asymmetric barriers
NASA Astrophysics Data System (ADS)
Brotzakis, Z. Faidon; Bolhuis, Peter G.
2016-10-01
We present a novel transition path sampling shooting algorithm for the efficient sampling of complex (biomolecular) activated processes with asymmetric free energy barriers. The method employs a fictitious potential that biases the shooting point toward the transition state. The method is similar in spirit to the aimless shooting technique by Peters and Trout [J. Chem. Phys. 125, 054108 (2006)], but is targeted for use with the one-way shooting approach, which has been shown to be more effective than two-way shooting algorithms in systems dominated by diffusive dynamics. We illustrate the method on a 2D Langevin toy model, the association of two peptides and the initial step in dissociation of a β-lactoglobulin dimer. In all cases we show a significant increase in efficiency.
Xie, XianMing; Li, YingHui
2014-06-20
This paper presents an enhanced phase unwrapping algorithm by combining an unscented Kalman filter, an enhanced local phase gradient estimator based on an amended matrix pencil model, and a path-following strategy. This technology is able to accurately unwrap seriously noisy wrapped phase images by applying the unscented Kalman filter to simultaneously perform noise suppression and phase unwrapping along the path from the high-quality region to the low-quality region of the wrapped phase images. Results obtained with synthetic data and real data validate the effectiveness of the proposed method and show improved performance of this new algorithm with respect to some of the most used algorithms.
NASA Astrophysics Data System (ADS)
Liu, Bing-Yi; Wang, Jun-Yang; Liu, Zhi-Shen
2014-11-01
Spaceborne integrated path differential absorption (IPDA) lidar is an active-detection system which is able to perform global CO2 measurement with high accuracy of 1ppmv at day and night over ground and clouds. To evaluate the detection performance of the system, simulation of the ground return signal and retrieval algorithm for CO2 concentration are presented in this paper. Ground return signals of spaceborne IPDA lidar under various ground surface reflectivity and atmospheric aerosol optical depths are simulated using given system parameters, standard atmosphere profiles and HITRAN database, which can be used as reference for determining system parameters. The simulated signals are further applied to the research on retrieval algorithm for CO2 concentration. The column-weighted dry air mixing ratio of CO2 denoted by XCO2 is obtained. As the deviations of XCO2 between the initial values for simulation and the results from retrieval algorithm are within the expected error ranges, it is proved that the simulation and retrieval algorithm are reliable.
Gao, Ming-ke; Chen, Yi-min; Liu, Quan; Huang, Chen; Li, Ze-yu; Zhang, Dian-hua
2015-11-01
Preoperative path planning plays a critical role in vascular access surgery. Vascular access surgery has superior difficulties and requires long training periods as well as precise operation. Yet doctors are on different leves, thus bulky size of blood vessels is usually chosen to undergo surgery and other possible optimal path is not considered. Moreover, patients and surgeons will suffer from X-ray radiation during the surgical procedure. The study proposed an improved ant colony algorithm to plan a vascular optimal three-dimensional path with overall consideration of factors such as catheter diameter, vascular length, diameter as well as the curvature and torsion. To protect the doctor and patient from exposing to X-ray long-term, the paper adopted augmented reality technology to register the reconstructed vascular model and physical model meanwhile, locate catheter by the electromagnetic tracking system and used Head Mounted Display to show the planning path in real time and monitor catheter push procedure. The experiment manifests reasonableness of preoperative path planning and proves the reliability of the algorithm. The augmented reality experiment real time and accurately displays the vascular phantom model, planning path and the catheter trajectory and proves the feasibility of this method. The paper presented a useful and feasible surgical scheme which was based on the improved ant colony algorithm to plan vascular three-dimensional path in augmented reality. The study possessed practical guiding significance in preoperative path planning, intraoperative catheter guiding and surgical training, which provided a theoretical method of path planning for vascular access surgery. It was a safe and reliable path planning approach and possessed practical reference value.
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
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
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.
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.
A novel routing algorithm of multi-priority label switch path in MPLS over WDM mesh networks
NASA Astrophysics Data System (ADS)
Su, Yang; Xu, Zhanqi; Liu, Zengji
2005-11-01
An extended layered graph of MPLS over WDM mesh networks is proposed in this paper, in which the label switch path (LSP) with various wavelengths and the limitation of optical transceivers at a routing node are both involved. Label switch paths are classified into different priorities according to each quality of service. The corresponding routing algorithm, differentiating integrated routing algorithm (DIRA), is proposed and studied. The quality of service (QoS) of a label switch path and the optimization of network resources utilization are taken into account comprehensively in DIRA. A comparison of DIRA with the representative optical routing algorithms via simulation shows that it can reduce the blocking probability of delay-constraint LSP and improve the network throughput.
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.
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.
Algorithms for Heterogeneous, Multiple Depot, Multiple Unmanned Vehicle Path Planning Problems
Sundar, Kaarthik; Rathinam, Sivakumar
2016-12-26
Unmanned vehicles, both aerial and ground, are being used in several monitoring applications to collect data from a set of targets. This article addresses a problem where a group of heterogeneous aerial or ground vehicles with different motion constraints located at distinct depots visit a set of targets. The vehicles also may be equipped with different sensors, and therefore, a target may not be visited by any vehicle. The objective is to find an optimal path for each vehicle starting and ending at its respective depot such that each target is visited at least once by some vehicle, the vehicle–target constraints are satisfied, and the sum of the length of the paths for all the vehicles is minimized. Two variants of this problem are formulated (one for ground vehicles and another for aerial vehicles) as mixed-integer linear programs and a branchand- cut algorithm is developed to compute an optimal solution to each of the variants. Computational results show that optimal solutions for problems involving 100 targets and 5 vehicles can be obtained within 300 seconds on average, further corroborating the effectiveness of the proposed approach.
Algorithms for Heterogeneous, Multiple Depot, Multiple Unmanned Vehicle Path Planning Problems
Sundar, Kaarthik; Rathinam, Sivakumar
2016-12-26
Unmanned vehicles, both aerial and ground, are being used in several monitoring applications to collect data from a set of targets. This article addresses a problem where a group of heterogeneous aerial or ground vehicles with different motion constraints located at distinct depots visit a set of targets. The vehicles also may be equipped with different sensors, and therefore, a target may not be visited by any vehicle. The objective is to find an optimal path for each vehicle starting and ending at its respective depot such that each target is visited at least once by some vehicle, the vehicle–targetmore » constraints are satisfied, and the sum of the length of the paths for all the vehicles is minimized. Two variants of this problem are formulated (one for ground vehicles and another for aerial vehicles) as mixed-integer linear programs and a branchand- cut algorithm is developed to compute an optimal solution to each of the variants. Computational results show that optimal solutions for problems involving 100 targets and 5 vehicles can be obtained within 300 seconds on average, further corroborating the effectiveness of the proposed approach.« less
NASA Astrophysics Data System (ADS)
Minary, Peter; Martyna, Glenn J.; Tuckerman, Mark E.
2003-02-01
In this paper (Paper I) and a companion paper (Paper II), novel new algorithms and applications of the isokinetic ensemble as generated by Gauss' principle of least constraint, pioneered for use with molecular dynamics 20 years ago, are presented for biophysical, path integral, and Car-Parrinello based ab initio molecular dynamics. In Paper I, a new "extended system" version of the isokinetic equations of motion that overcomes the ergodicity problems inherent in the standard approach, is developed using a new theory of non-Hamiltonian phase space analysis [M. E. Tuckerman et al., Europhys. Lett. 45, 149 (1999); J. Chem. Phys. 115, 1678 (2001)]. Reversible multiple time step integrations schemes for the isokinetic methods, first presented by Zhang [J. Chem. Phys. 106, 6102 (1997)] are reviewed. Next, holonomic constraints are incorporated into the isokinetic methodology for use in fast efficient biomolecular simulation studies. Model and realistic examples are presented in order to evaluate, critically, the performance of the new isokinetic molecular dynamic schemes. Comparisons are made to the, now standard, canonical dynamics method, Nosé-Hoover chain dynamics [G. J. Martyna et al., J. Chem. Phys. 97, 2635 (1992)]. The new isokinetic techniques are found to yield more efficient sampling than the Nosé-Hoover chain method in both path integral molecular dynamics and biophysical molecular dynamics calculations. In Paper II, the use of isokinetic methods in Car-Parrinello based ab initio molecular dynamics calculations is presented.
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.
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
Spreading paths in partially observed social networks
Onnela, Jukka-Pekka; Christakis, Nicholas A.
2012-01-01
Understanding how and how far information, behaviors, or pathogens spread in social networks is an important problem, having implications for both predicting the size of epidemics, as well as for planning effective interventions. There are, however, two main challenges for inferring spreading paths in real-world networks. One is the practical difficulty of observing a dynamic process on a network, and the other is the typical constraint of only partially observing a network. Using a static, structurally realistic social network as a platform for simulations, we juxtapose three distinct paths: (1) the stochastic path taken by a simulated spreading process from source to target; (2) the topologically shortest path in the fully observed network, and hence the single most likely stochastic path, between the two nodes; and (3) the topologically shortest path in a partially observed network. In a sampled network, how closely does the partially observed shortest path (3) emulate the unobserved spreading path (1)? Although partial observation inflates the length of the shortest path, the stochastic nature of the spreading process also frequently derails the dynamic path from the shortest path. We find that the partially observed shortest path does not necessarily give an inflated estimate of the length of the process path; in fact, partial observation may, counterintuitively, make the path seem shorter than it actually is. PMID:22587148
Brief Announcement: A Stabilizing Algorithm for Finding Two Disjoint Paths in Arbitrary Networks
NASA Astrophysics Data System (ADS)
Karaata, Mehmet Hakan; Hadid, Rachid
The problem of finding disjoint paths in a network is a fundamental problem with numerous applications. Two paths in a network are said to be (node) disjoint if they do not share any nodes except for the endpoints. The two node disjoint paths problem is to find two node-disjoint paths in G = (V,E) from source s ∈ V to the target t ∈ V . The two-node-disjoint paths problem is a fundamental problem with several applications in diverse areas including VLSI layout, reliable network routing, secure message transmission, and network survivability. The two node disjoint path problem is fundamental, extensively studied in graph theory.
Ishida, Yusuke; Kato, Yuki; Zhao, Liang; Nagamochi, Hiroshi; Akutsu, Tatsuya
2010-05-24
Computational methods of enumerating chemical graphs have attained great importance in chemoinformatics since they lead to a variety of useful applications including structure determination of novel chemical compounds. Recently, Fujiwara et al. have presented an efficient branch-and-bound algorithm for enumerating treelike chemical graphs with given path frequency. In this paper, we augment Fujiwara et al.'s algorithm by introducing a new bounding operation called detachment-cut to reduce further the search space in the branch-and-bound framework. Experimental results on much chemical compound data show that our proposed algorithm achieves better performance than Fujiwara et al.'s algorithm in computation time. A program that implements our algorithm can be used freely via Web server.
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.
Pohlheim, Hartmut
2006-01-01
Multidimensional scaling as a technique for the presentation of high-dimensional data with standard visualization techniques is presented. The technique used is often known as Sammon mapping. We explain the mathematical foundations of multidimensional scaling and its robust calculation. We also demonstrate the use of this technique in the area of evolutionary algorithms. First, we present the visualization of the path through the search space of the best individuals during an optimization run. We then apply multidimensional scaling to the comparison of multiple runs regarding the variables of individuals and multi-criteria objective values (path through the solution space).
NASA Astrophysics Data System (ADS)
Hou, Rui; Yu, Junle
2011-12-01
Optical burst switching (OBS) has been regarded as the next generation optical switching technology. In this paper, the routing problem based on particle swarm optimization (PSO) algorithm in OBS has been studies and analyzed. Simulation results indicate that, the PSO based routing algorithm will optimal than the conversional shortest path first algorithm in space cost and calculation cost. Conclusions have certain theoretical significances for the improvement of OBS routing protocols.
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.
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.
Chemical reaction optimization for solving shortest common supersequence problem.
Khaled Saifullah, C M; Rafiqul Islam, Md
2016-10-01
Shortest common supersequence (SCS) is a classical NP-hard problem, where a string to be constructed that is the supersequence of a given string set. The SCS problem has an enormous application of data compression, query optimization in the database and different bioinformatics activities. Due to NP-hardness, the exact algorithms fail to compute SCS for larger instances. Many heuristics and meta-heuristics approaches were proposed to solve this problem. In this paper, we propose a meta-heuristics approach based on chemical reaction optimization, CRO_SCS that is designed inspired by the nature of the chemical reactions. For different optimization problems like 0-1 knapsack, quadratic assignment, global numeric optimization problems CRO algorithm shows very good performance. We have redesigned the reaction operators and a new reform function to solve the SCS problem. The outcomes of the proposed CRO_SCS algorithm are compared with those of the enhanced beam search (IBS_SCS), deposition and reduction (DR), ant colony optimization (ACO) and artificial bee colony (ABC) algorithms. The length of supersequence, execution time and standard deviation of all related algorithms show that CRO_SCS gives better results on the average than all other algorithms.
ERIC Educational Resources Information Center
Tran, Huu-Khoa; Chiou, Juing -Shian; Peng, Shou-Tao
2016-01-01
In this paper, the feasibility of a Genetic Algorithm Optimization (GAO) education software based Fuzzy Logic Controller (GAO-FLC) for simulating the flight motion control of Unmanned Aerial Vehicles (UAVs) is designed. The generated flight trajectories integrate the optimized Scaling Factors (SF) fuzzy controller gains by using GAO algorithm. The…
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.
PathGrid: The Transfer of Astronomical Image Algorithms to the Analysis of Medical Microscopy Data
NASA Astrophysics Data System (ADS)
Walton, N. A.; Brenton, J. D.; Caldas, C.; Irwin, M. J.; Akram, A.; Gonzalez-Solares, E.; Lewis, J. R.; MacCullum, P.; Morris, L. J.; Rixon, G. T.
2009-09-01
We describe our pilot `PathGrid' study which applies astronomical image processing and data handling techniques to the challenges involved in analysing Tissue Micro Array (TMA) image data. Image analysis has been applied to the input TMA data using open source solutions developed for an astronomical context. The resulting data products are in turn interfaced to the clinical trials systems in use at the Cambridge Research Institute (Cancer Research-UK).
A surgeon specific automatic path planning algorithm for deep brain stimulation
NASA Astrophysics Data System (ADS)
Liu, Yuan; Dawant, Benoit M.; Pallavaram, Srivatsan; Neimat, Joseph S.; Konrad, Peter E.; D'Haese, Pierre-Francois; Datteri, Ryan D.; Landman, Bennett A.; Noble, Jack H.
2012-02-01
In deep brain stimulation surgeries, stimulating electrodes are placed at specific targets in the deep brain to treat neurological disorders. Reaching these targets safely requires avoiding critical structures in the brain. Meticulous planning is required to find a safe path from the cortical surface to the intended target. Choosing a trajectory automatically is difficult because there is little consensus among neurosurgeons on what is optimal. Our goals are to design a path planning system that is able to learn the preferences of individual surgeons and, eventually, to standardize the surgical approach using this learned information. In this work, we take the first step towards these goals, which is to develop a trajectory planning approach that is able to effectively mimic individual surgeons and is designed such that parameters, which potentially can be automatically learned, are used to describe an individual surgeon's preferences. To validate the approach, two neurosurgeons were asked to choose between their manual and a computed trajectory, blinded to their identity. The results of this experiment showed that the neurosurgeons preferred the computed trajectory over their own in 10 out of 40 cases. The computed trajectory was judged to be equivalent to the manual one or otherwise acceptable in 27 of the remaining cases. These results demonstrate the potential clinical utility of computer-assisted path planning.
Van Nguyen; Javaid, Abdul Q; Weitnauer, Mary Ann
2014-01-01
We introduce the Spectrum-averaged Harmonic Path (SHAPA) algorithm for estimation of heart rate (HR) and respiration rate (RR) with Impulse Radio Ultrawideband (IR-UWB) radar. Periodic movement of human torso caused by respiration and heart beat induces fundamental frequencies and their harmonics at the respiration and heart rates. IR-UWB enables capture of these spectral components and frequency domain processing enables a low cost implementation. Most existing methods of identifying the fundamental component either in frequency or time domain to estimate the HR and/or RR lead to significant error if the fundamental is distorted or cancelled by interference. The SHAPA algorithm (1) takes advantage of the HR harmonics, where there is less interference, and (2) exploits the information in previous spectra to achieve more reliable and robust estimation of the fundamental frequency in the spectrum under consideration. Example experimental results for HR estimation demonstrate how our algorithm eliminates errors caused by interference and produces 16% to 60% more valid estimates.
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.
Gollob, Stephan; Kocur, Georg Karl; Schumacher, Thomas; Mhamdi, Lassaad; Vogel, Thomas
2017-02-01
In acoustic emission analysis, common source location algorithms assume, independently of the nature of the propagation medium, a straight (shortest) wave path between the source and the sensors. For heterogeneous media such as concrete, the wave travels in complex paths due to the interaction with the dissimilar material contents and with the possible geometrical and material irregularities present in these media. For instance, cracks and large air voids present in concrete influence significantly the way the wave travels, by causing wave path deviations. Neglecting these deviations by assuming straight paths can introduce significant errors to the source location results. In this paper, a novel source localization method called FastWay is proposed. It accounts, contrary to most available shortest path-based methods, for the different effects of material discontinuities (cracks and voids). FastWay, based on a heterogeneous velocity model, uses the fastest rather than the shortest travel paths between the source and each sensor. The method was evaluated both numerically and experimentally and the results from both evaluation tests show that, in general, FastWay was able to locate sources of acoustic emissions more accurately and reliably than the traditional source localization methods.
Parallel path planning in unknown terrains
NASA Astrophysics Data System (ADS)
Prassler, Erwin A.; Milios, Evangelos E.
1991-03-01
We present a parallel processing approach to path planning in unknown terrains which combines map-based and sensor-based techniques into a real-time capable navigation system. The method is based on massively parallel computations in a grid of simple processing elements denoted as cells. In the course of a relaxation process a potential distribution is created in the grid which exhibits a monotonous slope from a start cell to the cell corresponding to the robot''s goal position. A shortest path is determined by means of a gradient descent criterion which settles on the steepest descent in the potential distribution. Like high-level path planning algorithms our approach is capable of planning shortest paths through an arbitrarily cluttered large-scale terrain on the basis of its current internal map. Sequentially implemented its complexity is in the order of efficient classical path planning algorithms. Unlike these algorithms however the method is also highly responsive to new obstacles encountered in the terrain. By continuing the planning process during the robot''s locomotion information about previously unknown obstacles immediately affects further path planning without a need to interrupt the ongoing planning process. New obstacles cause distortions of the potential distribution which let the robot find proper detours. By ensuring a monotonous slope in the overall distribution we avoid local minimum effects which may trap a robot in the proximity of an obstacle configuration before it has reached its goal. 1 Until the recent past research on path planning in the presence of obstacles can be assigned to two major categories: map-based high-level planning approaches and sensor-based low-level conLrol approaches. In work such as 12 path planning is treated as a high-level planning task. Assuming that an (accnrae) precompiled map of the terrain is available high-level path planners provide paths which guarantee a collision-free locomotion through an arbitrary
Campodonico, Miguel A; Andrews, Barbara A; Asenjo, Juan A; Palsson, Bernhard O; Feist, Adam M
2014-09-01
The production of 75% of the current drug molecules and 35% of all chemicals could be achieved through bioprocessing (Arundel and Sawaya, 2009). To accelerate the transition from a petroleum-based chemical industry to a sustainable bio-based industry, systems metabolic engineering has emerged to computationally design metabolic pathways for chemical production. Although algorithms able to provide specific metabolic interventions and heterologous production pathways are available, a systematic analysis for all possible production routes to commodity chemicals in Escherichia coli is lacking. Furthermore, a pathway prediction algorithm that combines direct integration of genome-scale models at each step of the search to reduce the search space does not exist. Previous work (Feist et al., 2010) performed a model-driven evaluation of the growth-coupled production potential for E. coli to produce multiple native compounds from different feedstocks. In this study, we extended this analysis for non-native compounds by using an integrated approach through heterologous pathway integration and growth-coupled metabolite production design. In addition to integration with genome-scale model integration, the GEM-Path algorithm developed in this work also contains a novel approach to address reaction promiscuity. In total, 245 unique synthetic pathways for 20 large volume compounds were predicted. Host metabolism with these synthetic pathways was then analyzed for feasible growth-coupled production and designs could be identified for 1271 of the 6615 conditions evaluated. This study characterizes the potential for E. coli to produce commodity chemicals, and outlines a generic strain design workflow to design production strains.
Algorithms for radio networks with dynamic topology
NASA Astrophysics Data System (ADS)
Shacham, Nachum; Ogier, Richard; Rutenburg, Vladislav V.; Garcia-Luna-Aceves, Jose
1991-08-01
The objective of this project was the development of advanced algorithms and protocols that efficiently use network resources to provide optimal or nearly optimal performance in future communication networks with highly dynamic topologies and subject to frequent link failures. As reflected by this report, we have achieved our objective and have significantly advanced the state-of-the-art in this area. The research topics of the papers summarized include the following: efficient distributed algorithms for computing shortest pairs of disjoint paths; minimum-expected-delay alternate routing algorithms for highly dynamic unreliable networks; algorithms for loop-free routing; multipoint communication by hierarchically encoded data; efficient algorithms for extracting the maximum information from event-driven topology updates; methods for the neural network solution of link scheduling and other difficult problems arising in communication networks; and methods for robust routing in networks subject to sophisticated attacks.
A new graph model and algorithms for consistent superstring problems.
Na, Joong Chae; Cho, Sukhyeun; Choi, Siwon; Kim, Jin Wook; Park, Kunsoo; Sim, Jeong Seop
2014-05-28
Problems related to string inclusion and non-inclusion have been vigorously studied in diverse fields such as data compression, molecular biology and computer security. Given a finite set of positive strings P and a finite set of negative strings N, a string α is a consistent superstring if every positive string is a substring of α and no negative string is a substring of α. The shortest (resp. longest) consistent superstring problem is to find a string α that is the shortest (resp. longest) among all the consistent superstrings for the given sets of strings. In this paper, we first propose a new graph model for consistent superstrings for given P and N. In our graph model, the set of strings represented by paths satisfying some conditions is the same as the set of consistent superstrings for P and N. We also present algorithms for the shortest and the longest consistent superstring problems. Our algorithms solve the consistent superstring problems for all cases, including cases that are not considered in previous work. Moreover, our algorithms solve in polynomial time the consistent superstring problems for more cases than the previous algorithms. For the polynomially solvable cases, our algorithms are more efficient than the previous ones.
A new graph model and algorithms for consistent superstring problems†
Na, Joong Chae; Cho, Sukhyeun; Choi, Siwon; Kim, Jin Wook; Park, Kunsoo; Sim, Jeong Seop
2014-01-01
Problems related to string inclusion and non-inclusion have been vigorously studied in diverse fields such as data compression, molecular biology and computer security. Given a finite set of positive strings and a finite set of negative strings , a string α is a consistent superstring if every positive string is a substring of α and no negative string is a substring of α. The shortest (resp. longest) consistent superstring problem is to find a string α that is the shortest (resp. longest) among all the consistent superstrings for the given sets of strings. In this paper, we first propose a new graph model for consistent superstrings for given and . In our graph model, the set of strings represented by paths satisfying some conditions is the same as the set of consistent superstrings for and . We also present algorithms for the shortest and the longest consistent superstring problems. Our algorithms solve the consistent superstring problems for all cases, including cases that are not considered in previous work. Moreover, our algorithms solve in polynomial time the consistent superstring problems for more cases than the previous algorithms. For the polynomially solvable cases, our algorithms are more efficient than the previous ones. PMID:24751868
Benefit of adaptive FEC in shared backup path protected elastic optical network.
Guo, Hong; Dai, Hua; Wang, Chao; Li, Yongcheng; Bose, Sanjay K; Shen, Gangxiang
2015-07-27
We apply an adaptive forward error correction (FEC) allocation strategy to an Elastic Optical Network (EON) operated with shared backup path protection (SBPP). To maximize the protected network capacity that can be carried, an Integer Linear Programing (ILP) model and a spectrum window plane (SWP)-based heuristic algorithm are developed. Simulation results show that the FEC coding overhead required by the adaptive FEC scheme is significantly lower than that needed by a fixed FEC allocation strategy resulting in higher network capacity for the adaptive strategy. The adaptive FEC allocation strategy can also significantly outperform the fixed FEC allocation strategy both in terms of the spare capacity redundancy and the average FEC coding overhead needed per optical channel. The proposed heuristic algorithm is efficient and not only performs closer to the ILP model but also does much better than the shortest-path algorithm.
Multipath Routing Algorithm Applied to Cloud Data Center Services
NASA Astrophysics Data System (ADS)
Matsuura, Hiroshi
Cloud data center services, such as video on demand (VoD) and sensor data monitoring, have become popular. The quality of service (QoS) between a client and a cloud data center should be assured by satisfying each service's required bandwidth and delay. Multipath traffic engineering is effective for dispersing traffic flows on a network; therefore, an improved k-shortest paths first (k-SPF) algorithm is applied to these cloud data center services to satisfy their required QoS. k-SPF can create a set of multipaths between a cloud data center and all edge routers, to which client nodes are connected, within one algorithm process. Thus, k-SPF can produce k shortest simple paths between a cloud data center and every access router faster than with conventional Yen's algorithm. By using a parameter in the algorithm, k-SPF can also impartially use links on a network and shorten the average hop-count and number of necessary MPLS labels for multiple paths that comprise a multipath.
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.
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.
3D Motion Planning Algorithms for Steerable Needles Using Inverse Kinematics
Duindam, Vincent; Xu, Jijie; Alterovitz, Ron; Sastry, Shankar; Goldberg, Ken
2010-01-01
Steerable needles can be used in medical applications to reach targets behind sensitive or impenetrable areas. The kinematics of a steerable needle are nonholonomic and, in 2D, equivalent to a Dubins car with constant radius of curvature. In 3D, the needle can be interpreted as an airplane with constant speed and pitch rate, zero yaw, and controllable roll angle. We present a constant-time motion planning algorithm for steerable needles based on explicit geometric inverse kinematics similar to the classic Paden-Kahan subproblems. Reachability and path competitivity are analyzed using analytic comparisons with shortest path solutions for the Dubins car (for 2D) and numerical simulations (for 3D). We also present an algorithm for local path adaptation using null-space results from redundant manipulator theory. Finally, we discuss several ways to use and extend the inverse kinematics solution to generate needle paths that avoid obstacles. PMID:21359051
1991-02-22
Receive AAP Architecture 84 4.3.3.9 Transmit Architecture 86 4.3.4 Computer Modeling and Simulations 88 4.3.4.1 Introduction 88 4.3.4.2 Simulation...course of this Phase I study are stated briefly below. Detailed descriptions and explanations are provided in section 4.3. o A realistic computer model of...contribution to the paper will be made at that time. o The algorithm was modeled on the computer and its performance was simulated for various signal
NASA Astrophysics Data System (ADS)
Ciesielski, Krzysztof Chris; Udupa, Jayaram K.; Falcão, A. X.; Miranda, P. A. V.
2012-02-01
We present a general graph-cut segmentation framework GGC, in which the delineated objects returned by the algorithms optimize the energy functions associated with the lp norm, 1 <= p <= ∞. Two classes of well known algorithms belong to GGC: the standard graph cut GC (such as the min-cut/max-flow algorithm) and the relative fuzzy connectedness algorithms RFC (including iterative RFC, IRFC). The norm-based description of GGC provides more elegant and mathematically better recognized framework of our earlier results from [18, 19]. Moreover, it allows precise theoretical comparison of GGC representable algorithms with the algorithms discussed in a recent paper [22] (min-cut/max-flow graph cut, random walker, shortest path/geodesic, Voronoi diagram, power watershed/shortest path forest), which optimize, via lp norms, the intermediate segmentation step, the labeling of scene voxels, but for which the final object need not optimize the used lp energy function. Actually, the comparison of the GGC representable algorithms with that encompassed in the framework described in [22] constitutes the main contribution of this work.
NASA Astrophysics Data System (ADS)
Theilmann, Florian
2017-01-01
The classical brachistochrone problem asks for the path on which a mobile point M just driven by its own gravity will travel in the shortest possible time between two given points A and B. The resulting curve, the cycloid, will also be the tautochrone curve, i.e. the travelling time of the mobile point will not depend on its starting position. We discuss three similar problems of increasing complexity that restrict the motion to inclined planes. Without using calculus we derive the respective optimal geometry and compare the theoretical values to measured travelling times. The observed discrepancies are quantitatively modelled by including angular motion and friction. We also investigate the correspondence between the original problem and our setups. The topic provides a conceptually simple yet non-trivial problem setting inviting for problem based learning and complex learning activities such as planing suitable experiments or modelling the relevant kinematics.
Zhong, Zhi; Hao, Bengong; Shan, Mingguang; Wang, Ying; Diao, Ming; Zhang, Yabin
2014-04-01
This paper presents a two-shot common-path phase-shifting interferometer that consists of a 4f optical system with two windows in the input plane and a Ronchi grating in the Fourier plane, and generates two adjacent interferograms using only diffraction orders 0 and +1 and 0 and -1. Four phase-shifted interferograms can be obtained in two shots by modulating two linear polarizers with angle difference of π/4 and translating the grating with only an unknown phase shift. An algorithm similar to the standard four-step algorithm is used to retrieve the phase of a specimen, and it requires no knowledge of the phase shift introduced by translation of the grating. The validity and repeatability of the proposed method is proved through simulations and experiments.
Path similarity skeleton graph matching.
Bai, Xiang; Latecki, Longin Jan
2008-07-01
This paper presents a novel framework to for shape recognition based on object silhouettes. The main idea is to match skeleton graphs by comparing the shortest paths between skeleton endpoints. In contrast to typical tree or graph matching methods, we completely ignore the topological graph structure. Our approach is motivated by the fact that visually similar skeleton graphs may have completely different topological structures. The proposed comparison of shortest paths between endpoints of skeleton graphs yields correct matching results in such cases. The skeletons are pruned by contour partitioning with Discrete Curve Evolution, which implies that the endpoints of skeleton branches correspond to visual parts of the objects. The experimental results demonstrate that our method is able to produce correct results in the presence of articulations, stretching, and occlusion.
NASA Astrophysics Data System (ADS)
Kurennov, D. V.; Petunin, A. A.; Repnitskii, V. B.; Shipacheva, E. N.
2016-12-01
The problem of approximating two-dimensional broken line with composite curve consisting of arc and line segments is considered. The resulting curve nodes have to coincide with source broken line nodes. This problem arises in the development of control programs for CNC (computer numerical control) cutting machines, permitting circular interpolation. An original algorithm is proposed minimizing the number of nodes for resulting composite curve. The algorithm is implemented in the environment of the Russian CAD system T-Flex CAD using its API (Application Program Interface). The algorithm optimality is investigated. The result of test calculation along with its geometrical visualization is given.
Avena-Koenigsberger, Andrea; Mišić, Bratislav; Hawkins, Robert X D; Griffa, Alessandra; Hagmann, Patric; Goñi, Joaquín; Sporns, Olaf
2017-01-01
Computational analysis of communication efficiency of brain networks often relies on graph-theoretic measures based on the shortest paths between network nodes. Here, we explore a communication scheme that relaxes the assumption that information travels exclusively through optimally short paths. The scheme assumes that communication between a pair of brain regions may take place through a path ensemble comprising the k-shortest paths between those regions. To explore this approach, we map path ensembles in a set of anatomical brain networks derived from diffusion imaging and tractography. We show that while considering optimally short paths excludes a significant fraction of network connections from participating in communication, considering k-shortest path ensembles allows all connections in the network to contribute. Path ensembles enable us to assess the resilience of communication pathways between brain regions, by measuring the number of alternative, disjoint paths within the ensemble, and to compare generalized measures of path length and betweenness centrality to those that result when considering only the single shortest path between node pairs. Furthermore, we find a significant correlation, indicative of a trade-off, between communication efficiency and resilience of communication pathways in structural brain networks. Finally, we use k-shortest path ensembles to demonstrate hemispherical lateralization of efficiency and resilience.
NASA Astrophysics Data System (ADS)
Kamibayashi, Yuki; Miura, Shinichi
2016-08-01
In the present study, variational path integral molecular dynamics and associated hybrid Monte Carlo (HMC) methods have been developed on the basis of a fourth order approximation of a density operator. To reveal various parameter dependence of physical quantities, we analytically solve one dimensional harmonic oscillators by the variational path integral; as a byproduct, we obtain the analytical expression of the discretized density matrix using the fourth order approximation for the oscillators. Then, we apply our methods to realistic systems like a water molecule and a para-hydrogen cluster. In the HMC, we adopt two level description to avoid the time consuming Hessian evaluation. For the systems examined in this paper, the HMC method is found to be about three times more efficient than the molecular dynamics method if appropriate HMC parameters are adopted; the advantage of the HMC method is suggested to be more evident for systems described by many body interaction.
NASA Astrophysics Data System (ADS)
Miura, Shinichi; Okazaki, Susumu
2001-09-01
In this paper, the path integral molecular dynamics (PIMD) method has been extended to employ an efficient approximation of the path action referred to as the pair density matrix approximation. Configurations of the isomorphic classical systems were dynamically sampled by introducing fictitious momenta as in the PIMD based on the standard primitive approximation. The indistinguishability of the particles was handled by a pseudopotential of particle permutation that is an extension of our previous one [J. Chem. Phys. 112, 10 116 (2000)]. As a test of our methodology for Boltzmann statistics, calculations have been performed for liquid helium-4 at 4 K. We found that the PIMD with the pair density matrix approximation dramatically reduced the computational cost to obtain the structural as well as dynamical (using the centroid molecular dynamics approximation) properties at the same level of accuracy as that with the primitive approximation. With respect to the identical particles, we performed the calculation of a bosonic triatomic cluster. Unlike the primitive approximation, the pseudopotential scheme based on the pair density matrix approximation described well the bosonic correlation among the interacting atoms. Convergence with a small number of discretization of the path achieved by this approximation enables us to construct a method of avoiding the problem of the vanishing pseudopotential encountered in the calculations by the primitive approximation.
A Dynamic Programming Approach to Identifying the Shortest Path in Virtual Learning Environments
ERIC Educational Resources Information Center
Fazlollahtabar, Hamed
2008-01-01
E-learning has been widely adopted as a promising solution by many organizations to offer learning-on-demand opportunities to individual employees (learners) in order to reduce training time and cost. While successful information systems models have received much attention among researchers, little research has been conducted to assess the success…
1992-12-01
i.e. tabula rasa ) reinforcement learning was exponential for such problems, or that it was tractable (i.e. of polynomial time-complexity) only if the...Figure 1: Navigating on a map studied by [2], [51, [23], [19], [24], and others. [35] showed that reaching a goal state with uninformed (i.e. tabula ... rasa ) reinforcement learning methods can require a number of action executions that is exponential in the size of the state space. [33] has shown that
An Application of Multi-Criteria Shortest Path to a Customizable Hex-Map Environment
2015-03-26
model developed represents the next step in the evolution of the Metz model built by Frawley [12], which is fashioned after the WWII-inspired war game ...foundation of wargaming. The act of engaging in a war- game affects the user as opposed to the environment. In a real life engagement, affecting the...environment or circumstance is the focus, but in 1 a war- game , the focus is on the user: How will the user respond? How does the user problem-solve? How
Poulsen, Jens Aage; Nyman, Gunnar; Rossky, Peter J
2006-11-01
The Feynman-Kleinert Linearized Path Integral (FK-LPI) representation of quantum correlation functions is extended in applications and algorithms. Diffusion including quantum effects for a flexible simple point charge model of liquid water is explored, including new tests of internal consistency. An ab initio quantum correction factor (QCF) is also obtained to correct the far-infrared spectrum of water. After correction, a spectrum based on a classical simulation is in good agreement with the experiment. The FK-LPI QCF is shown to be superior to the so-called harmonic QCF. New computational algorithms are introduced so that the quantum Boltzmann Wigner phase-space density, the central object in the implementation, can be obtained for arbitrary potentials. One scheme requires only that the standard classical force routine be replaced when turning from one molecular problem to another. The new algorithms are applied to the calculation of the Van Hove spectrum of liquid He(4) at 27 K. The spectrum moments are in very good agreement with the experiment. These observations indicate that the FK-LPI approach can be broadly effective for molecular problems involving the dynamics of light nuclei.
Riihimaki, Laura D.; Comstock, Jennifer M.; Anderson, Kevin K.; ...
2016-06-10
Knowledge of cloud phase (liquid, ice, mixed, etc.) is necessary to describe the radiative impact of clouds and their lifetimes, but is a property that is difficult to simulate correctly in climate models. One step towards improving those simulations is to make observations of cloud phase with sufficient accuracy to help constrain model representations of cloud processes. In this study, we outline a methodology using a basic Bayesian classifier to estimate the probabilities of cloud-phase class from Atmospheric Radiation Measurement (ARM) vertically pointing active remote sensors. The advantage of this method over previous ones is that it provides uncertainty informationmore » on the phase classification. We also test the value of including higher moments of the cloud radar Doppler spectrum than are traditionally used operationally. Using training data of known phase from the Mixed-Phase Arctic Cloud Experiment (M-PACE) field campaign, we demonstrate a proof of concept for how the method can be used to train an algorithm that identifies ice, liquid, mixed phase, and snow. Over 95 % of data are identified correctly for pure ice and liquid cases used in this study. Mixed-phase and snow cases are more problematic to identify correctly. When lidar data are not available, including additional information from the Doppler spectrum provides substantial improvement to the algorithm. This is a first step towards an operational algorithm and can be expanded to include additional categories such as drizzle with additional training data.« less
The shortest period detached binary white dwarf system
NASA Astrophysics Data System (ADS)
Kilic, Mukremin; Brown, Warren R.; Kenyon, S. J.; Allende Prieto, Carlos; Andrews, J.; Kleinman, S. J.; Winget, K. I.; Winget, D. E.; Hermes, J. J.
2011-05-01
We identify SDSS J010657.39-100003.3 (hereafter J0106-1000) as the shortest period detached binary white dwarf (WD) system currently known. We targeted J0106-1000 as part of our radial velocity programme to search for companions around known extremely low-mass (ELM; ˜0.2 M⊙) WDs using the 6.5-m Multiple Mirror Telescope. We detect peak-to-peak radial velocity variations of 740 km s-1 with an orbital period of 39.1 min. The mass function and optical photometry rule out a main-sequence star companion. Follow-up high-speed photometric observations obtained at the McDonald 2.1-m telescope reveal ellipsoidal variations from the distorted primary but no eclipses. This is the first example of a tidally distorted WD. Modelling the light curve, we constrain the inclination angle of the system to be 67°± 13°. J0106-1000 contains a pair of WDs (0.17 M⊙ primary + 0.43 M⊙ invisible secondary) at a separation of 0.32 R⊙. The two WDs will merge in 37 Myr and most likely form a core He-burning single subdwarf star. J0106-1000 is the shortest time-scale merger system currently known. The gravitational wave strain from J0106-1000 is at the detection limit of the Laser Interferometer Space Antenna (LISA). However, accurate ephemeris and orbital period measurements may enable LISA to detect J0106-1000 above the Galactic background noise. Based on observations obtained at the Multiple Mirror Telescope (MMT) Observatory, a joint facility of the Smithsonian Institution and the University of Arizona.
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.
Skil: An imperative language with algorithmic skeletons for efficient distributed programming
Botorog, G.H.; Kuchen, H.
1996-12-31
In this paper we present Skil, an imperative language enhanced with higher-order functions and currying, as well as with a polymorphic type system. The high level of Skil allows the integration of algorithmic skeletons, i.e. of higher-order functions representing parallel computation patterns. At the same time, the language can be efficiently implemented. After describing a series of skeletons which work with distributed arrays, we give two examples of parallel programs implemented on the basis of skeletons, namely shortest paths in graphs and Gaussian elimination. Runtime measurements show that we approach the efficiency of message-passing C up to a factor between 1 and 2.5.
Detection of Deregulated Modules Using Deregulatory Linked Path
Hu, Yuxuan; Gao, Lin; Shi, Kai; Chiu, David K. Y.
2013-01-01
The identification of deregulated modules (such as induced by oncogenes) is a crucial step for exploring the pathogenic process of complex diseases. Most of the existing methods focus on deregulation of genes rather than the links of the path among them. In this study, we emphasize on the detection of deregulated links, and develop a novel and effective regulatory path-based approach in finding deregulated modules. Observing that a regulatory pathway between two genes might involve in multiple rather than a single path, we identify condition-specific core regulatory path (CCRP) to detect the significant deregulation of regulatory links. Using time-series gene expression, we define the regulatory strength within each gene pair based on statistical dependence analysis. The CCRPs in regulatory networks can then be identified using the shortest path algorithm. Finally, we derive the deregulated modules by integrating the differential edges (as deregulated links) of the CCRPs between the case and the control group. To demonstrate the effectiveness of our approach, we apply the method to expression data associated with different states of Human Epidermal Growth Factor Receptor 2 (HER2). The experimental results show that the genes as well as the links in the deregulated modules are significantly enriched in multiple KEGG pathways and GO biological processes, most of which can be validated to suffer from impact of this oncogene based on previous studies. Additionally, we find the regulatory mechanism associated with the crucial gene SNAI1 significantly deregulated resulting from the activation of HER2. Hence, our method provides not only a strategy for detecting the deregulated links in regulatory networks, but also a way to identify concerning deregulated modules, thus contributing to the target selection of edgetic drugs. PMID:23894653
NASA Astrophysics Data System (ADS)
Cheng, Jun; Zhang, Jun; Tian, Jinwen
2015-12-01
Based on deep analysis of the LiveWire interactive boundary extraction algorithm, a new algorithm focusing on improving the speed of LiveWire algorithm is proposed in this paper. Firstly, the Haar wavelet transform is carried on the input image, and the boundary is extracted on the low resolution image obtained by the wavelet transform of the input image. Secondly, calculating LiveWire shortest path is based on the control point set direction search by utilizing the spatial relationship between the two control points users provide in real time. Thirdly, the search order of the adjacent points of the starting node is set in advance. An ordinary queue instead of a priority queue is taken as the storage pool of the points when optimizing their shortest path value, thus reducing the complexity of the algorithm from O[n2] to O[n]. Finally, A region iterative backward projection method based on neighborhood pixel polling has been used to convert dual-pixel boundary of the reconstructed image to single-pixel boundary after Haar wavelet inverse transform. The algorithm proposed in this paper combines the advantage of the Haar wavelet transform and the advantage of the optimal path searching method based on control point set direction search. The former has fast speed of image decomposition and reconstruction and is more consistent with the texture features of the image and the latter can reduce the time complexity of the original algorithm. So that the algorithm can improve the speed in interactive boundary extraction as well as reflect the boundary information of the image more comprehensively. All methods mentioned above have a big role in improving the execution efficiency and the robustness of the algorithm.
A Decision Processing Algorithm for CDC Location Under Minimum Cost SCM Network
NASA Astrophysics Data System (ADS)
Park, N. K.; Kim, J. Y.; Choi, W. Y.; Tian, Z. M.; Kim, D. J.
Location of CDC in the matter of network on Supply Chain is becoming on the high concern these days. Present status of methods on CDC has been mainly based on the calculation manually by the spread sheet to achieve the goal of minimum logistics cost. This study is focused on the development of new processing algorithm to overcome the limit of present methods, and examination of the propriety of this algorithm by case study. The algorithm suggested by this study is based on the principle of optimization on the directive GRAPH of SCM model and suggest the algorithm utilizing the traditionally introduced MST, shortest paths finding methods, etc. By the aftermath of this study, it helps to assess suitability of the present on-going SCM network and could be the criterion on the decision-making process for the optimal SCM network building-up for the demand prospect in the future.
Azuri, Asaf; Engel, Hamutal; Doron, Dvir; Major, Dan Thomas
2011-05-10
A practical approach to treat nuclear quantum mechanical (QM) effects in simulations of condensed phases, such as enzymes, is via Feynman path integral (PI) formulations. Typically, the standard primitive approximation (PA) is employed in enzymatic PI simulations. Nonetheless, these PI simulations are computationally demanding due to the large number of discretizations, or beads, required to obtain converged results. The efficiency of PI simulations may be greatly improved if higher order factorizations of the density matrix operator are employed. Herein, we compare the results of model calculations obtained employing the standard PA, the improved operator of Takahashi and Imada (TI), and several gradient-based forward corrector algorithms due to Chin (CH). The quantum partition function is computed for the harmonic oscillator, Morse, symmetric, and asymmetric double well potentials. These potentials are simple models for nuclear quantum effects, such as zero-point energy and tunneling. It is shown that a unique set of CH parameters may be employed for a variety of systems. Additionally, the nuclear QM effects of a water molecule, treated with density functional theory, are computed. Finally, we derive a practical perturbation expression for efficient computation of isotope effects in chemical systems using the staging algorithm. This new isotope effect approach is tested in conjunction with the PA, TI, and CH methods to compute the equilibrium isotope effect in the Schiff base-oxyanion keto-enol tautomerism in the cofactor pyridoxal-5'-phosphate in the enzyme alanine racemase. The study of the different factorization methods reveals that the higher-order actions converge substantially faster than the PA approach, at a moderate computational cost.
Deterministic Agent-Based Path Optimization by Mimicking the Spreading of Ripples.
Hu, Xiao-Bing; Wang, Ming; Leeson, Mark S; Di Paolo, Ezequiel A; Liu, Hao
2016-01-01
Inspirations from nature have contributed fundamentally to the development of evolutionary computation. Learning from the natural ripple-spreading phenomenon, this article proposes a novel ripple-spreading algorithm (RSA) for the path optimization problem (POP). In nature, a ripple spreads at a constant speed in all directions, and the node closest to the source is the first to be reached. This very simple principle forms the foundation of the proposed RSA. In contrast to most deterministic top-down centralized path optimization methods, such as Dijkstra's algorithm, the RSA is a bottom-up decentralized agent-based simulation model. Moreover, it is distinguished from other agent-based algorithms, such as genetic algorithms and ant colony optimization, by being a deterministic method that can always guarantee the global optimal solution with very good scalability. Here, the RSA is specifically applied to four different POPs. The comparative simulation results illustrate the advantages of the RSA in terms of effectiveness and efficiency. Thanks to the agent-based and deterministic features, the RSA opens new opportunities to attack some problems, such as calculating the exact complete Pareto front in multiobjective optimization and determining the kth shortest project time in project management, which are very difficult, if not impossible, for existing methods to resolve. The ripple-spreading optimization principle and the new distinguishing features and capacities of the RSA enrich the theoretical foundations of evolutionary computation.
Rigdon, J. Brian; Smith, Marcus Daniel; Mulder, Samuel A
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).
NASA Astrophysics Data System (ADS)
Smith, Eric A.; Turk, F. Joseph; Farrar, Michael R.; Mugnai, Alberto; Xiang, Xuwu
1997-04-01
This study presents research in support of the design and implementation of a combined radar-radiometer algorithm to be used for precipitation retrieval during the Tropical Rainfall Measuring Mission (TRMM). The combined algorithm approach is expected to overcome various difficulties that arise with a radar-only approach, particularly related to estimates of path-integrated attenuation (PIA) along the TRMM radar beam. A technique is described for estimating PIA at the 13.8-GHz frequency of the TRMM precipitation radar (PR) from 10.7-GHz brightness temperature TB measurements obtained from the TRMM microwave imager. Because the PR measures at an attenuating frequency, an independent estimate of PIA is used to constrain the solution to the radar equation, which incorporates effects of attenuation propagation along a radar beam. Through the use of variational or probabilistic techniques, the independent PIA calculations provide a means to adjust for errors that accumulate in estimates of range-dependent rain rates at progressively increasing range positions from radar reflectivity vectors. The accepted radar approach for obtaining PIA from ocean-viewing radar reflectivity measurements is called the surface reference technique, a scheme based on the difference in ocean surface cross sections between cloud-free and raining radar pixels. This technique has encountered problems, which are discussed and analyzed with the aid of coordinated aircraft radar (Airborne Rain Mapping Radar) and radiometer (Advanced Microwave Precipitation Radiometer) measurements obtained during the west Pacific Tropical Ocean Global Atmosphere Coupled Ocean-Atmosphere Response Experiment in 1993. The derived relationship expressing 13.8-GHz PIAs as a function of 10.7-GHz TB's is based on statistical fitting of many thousands of radiative transfer (RTE) calculations in which the relevant physical and radiative parameters affecting transmission, absorption, and scattering in a raining column and
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.
Integrated flight path planning system and flight control system for unmanned helicopters.
Jan, Shau Shiun; Lin, Yu Hsiang
2011-01-01
This paper focuses on the design of an integrated navigation and guidance system for unmanned helicopters. The integrated navigation system comprises two systems: the Flight Path Planning System (FPPS) and the Flight Control System (FCS). The FPPS finds the shortest flight path by the A-Star (A*) algorithm in an adaptive manner for different flight conditions, and the FPPS can add a forbidden zone to stop the unmanned helicopter from crossing over into dangerous areas. In this paper, the FPPS computation time is reduced by the multi-resolution scheme, and the flight path quality is improved by the path smoothing methods. Meanwhile, the FCS includes the fuzzy inference systems (FISs) based on the fuzzy logic. By using expert knowledge and experience to train the FIS, the controller can operate the unmanned helicopter without dynamic models. The integrated system of the FPPS and the FCS is aimed at providing navigation and guidance to the mission destination and it is implemented by coupling the flight simulation software, X-Plane, and the computing software, MATLAB. Simulations are performed and shown in real time three-dimensional animations. Finally, the integrated system is demonstrated to work successfully in controlling the unmanned helicopter to operate in various terrains of a digital elevation model (DEM).
NASA Astrophysics Data System (ADS)
Luangpaiboon, P.
2009-10-01
Many entrepreneurs face to extreme conditions for instances; costs, quality, sales and services. Moreover, technology has always been intertwined with our demands. Then almost manufacturers or assembling lines adopt it and come out with more complicated process inevitably. At this stage, products and service improvement need to be shifted from competitors with sustainability. So, a simulated process optimisation is an alternative way for solving huge and complex problems. Metaheuristics are sequential processes that perform exploration and exploitation in the solution space aiming to efficiently find near optimal solutions with natural intelligence as a source of inspiration. One of the most well-known metaheuristics is called Ant Colony Optimisation, ACO. This paper is conducted to give an aid in complicatedness of using ACO in terms of its parameters: number of iterations, ants and moves. Proper levels of these parameters are analysed on eight noisy continuous non-linear continuous response surfaces. Considering the solution space in a specified region, some surfaces contain global optimum and multiple local optimums and some are with a curved ridge. ACO parameters are determined through hybridisations of Modified Simplex and Simulated Annealing methods on the path of Steepest Ascent, SAM. SAM was introduced to recommend preferable levels of ACO parameters via statistically significant regression analysis and Taguchi's signal to noise ratio. Other performance achievements include minimax and mean squared error measures. A series of computational experiments using each algorithm were conducted. Experimental results were analysed in terms of mean, design points and best so far solutions. It was found that results obtained from a hybridisation with stochastic procedures of Simulated Annealing method were better than that using Modified Simplex algorithm. However, the average execution time of experimental runs and number of design points using hybridisations were
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.
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.
Performance Analysis of Path Planning Modeling
NASA Astrophysics Data System (ADS)
Wang, Zhirui; Li, Shuanghong; Zhang, Ying; Du, Qiaoling
Ant colony system (ACS) algorithm was applied to the path planning for the robot. In the same working environment, path planning based on MAKLINK graph theory and Voronoi diagram were simulated and compared. MAKLINK graph theory is appropriate to apply to precise searching in small-scale district, and Voronoi diagram is suitable for fast path planning in a large area.
NASA Technical Reports Server (NTRS)
Campbell, R. H.; Kolstad, R. B.; Holle, D. F.; Miller, T. J.; Krause, P.; Horton, K.; Macke, T.
1983-01-01
Path Pascal is high-level experimental programming language based on PASCAL, which incorporates extensions for systems and real-time programming. Pascal is extended to treat real-time concurrent systems.
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...
Optimization of Operation Sequence in CNC Machine Tools Using Genetic Algorithm
NASA Astrophysics Data System (ADS)
Abu Qudeiri, Jaber; Yamamoto, Hidehiko; Ramli, Rizauddin
The productivity of machine tools is significantly improved by using microcomputer based CAD/CAM systems for NC program generation. Currently, many commercial CAD/CAM packages that provide automatic NC programming have been developed and applied to various cutting processes. Many cutting processes machined by CNC machine tools. In this paper, we attempt to find an efficient solution approach to determine the best sequence of operations for a set of operations that located in asymmetrical locations and different levels. In order to find the best sequence of operations that achieves the shortest cutting tool travel path (CTTP), genetic algorithm is introduced. After the sequence is optimized, the G-codes that use to code for the travel time is created. CTTP can be formulated as a special case of the traveling salesman problem (TSP). The incorporation of genetic algorithm and TSP can be included in the commercial CAD/CAM packages to optimize the CTTP during automatic generation of NC programs.
Tracing path-guided apparent motion in human primary visual cortex V1
Akselrod, Michel; Herzog, Michael H.; Öğmen, Haluk
2014-01-01
Vision is a constructive process. For example, a square, flashed at two distinct locations one after the other, appears to move smoothly between the two locations rather than as two separate flashes (apparent motion). Apparent motion is usually perceived along the shortest path between locations. Previous studies have shown that retinotopic activity in V1 correlates well with the subjective filling-in in apparent motion. If V1 activity truly reflects illusory motion, it should flexibly reflect filling-in of any path, subjectively perceived. Here, we used a path-guided apparent motion paradigm in which a faint cue, presented in addition to the squares, leads to a curved illusory motion path. We found retinotopic activity in V1 to reflect the illusory filling-in of the curved path, similarly to filling-in with linear, shortest paths. Moreover, our results show that activity along the linear path was less selective to stimulus conditions than the activity along the curved path. This finding may be interpreted as V1 activity representing a small subset of infinitely many possible solutions to ambiguous stimuli, whilst giving more weight to the shortest path/energy solution. PMID:25317907
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.
Path optimization with limited sensing ability
Kang, Sung Ha Kim, Seong Jun Zhou, Haomin
2015-10-15
We propose a computational strategy to find the optimal path for a mobile sensor with limited coverage to traverse a cluttered region. The goal is to find one of the shortest feasible paths to achieve the complete scan of the environment. We pose the problem in the level set framework, and first consider a related question of placing multiple stationary sensors to obtain the full surveillance of the environment. By connecting the stationary locations using the nearest neighbor strategy, we form the initial guess for the path planning problem of the mobile sensor. Then the path is optimized by reducing its length, via solving a system of ordinary differential equations (ODEs), while maintaining the complete scan of the environment. Furthermore, we use intermittent diffusion, which converts the ODEs into stochastic differential equations (SDEs), to find an optimal path whose length is globally minimal. To improve the computation efficiency, we introduce two techniques, one to remove redundant connecting points to reduce the dimension of the system, and the other to deal with the entangled path so the solution can escape the local traps. Numerical examples are shown to illustrate the effectiveness of the proposed method.
Entanglement by Path Identity.
Krenn, Mario; Hochrainer, Armin; Lahiri, Mayukh; Zeilinger, Anton
2017-02-24
Quantum entanglement is one of the most prominent features of quantum mechanics and forms the basis of quantum information technologies. Here we present a novel method for the creation of quantum entanglement in multipartite and high-dimensional systems. The two ingredients are (i) superposition of photon pairs with different origins and (ii) aligning photons such that their paths are identical. We explain the experimentally feasible creation of various classes of multiphoton entanglement encoded in polarization as well as in high-dimensional Hilbert spaces-starting only from nonentangled photon pairs. For two photons, arbitrary high-dimensional entanglement can be created. The idea of generating entanglement by path identity could also apply to quantum entities other than photons. We discovered the technique by analyzing the output of a computer algorithm. This shows that computer designed quantum experiments can be inspirations for new techniques.
NASA Astrophysics Data System (ADS)
Krenn, Mario; Hochrainer, Armin; Lahiri, Mayukh; Zeilinger, Anton
2017-02-01
Quantum entanglement is one of the most prominent features of quantum mechanics and forms the basis of quantum information technologies. Here we present a novel method for the creation of quantum entanglement in multipartite and high-dimensional systems. The two ingredients are (i) superposition of photon pairs with different origins and (ii) aligning photons such that their paths are identical. We explain the experimentally feasible creation of various classes of multiphoton entanglement encoded in polarization as well as in high-dimensional Hilbert spaces—starting only from nonentangled photon pairs. For two photons, arbitrary high-dimensional entanglement can be created. The idea of generating entanglement by path identity could also apply to quantum entities other than photons. We discovered the technique by analyzing the output of a computer algorithm. This shows that computer designed quantum experiments can be inspirations for new techniques.
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.
Leaf-sequencing for intensity-modulated arc therapy using graph algorithms
Luan Shuang; Wang Chao; Cao Daliang; Chen, Danny Z.; Shepard, David M.; Yu, Cedric X.
2008-01-15
Intensity-modulated arc therapy (IMAT) is a rotational IMRT technique. It uses a set of overlapping or nonoverlapping arcs to create a prescribed dose distribution. Despite its numerous advantages, IMAT has not gained widespread clinical applications. This is mainly due to the lack of an effective IMAT leaf-sequencing algorithm that can convert the optimized intensity patterns for all beam directions into IMAT treatment arcs. To address this problem, we have developed an IMAT leaf-sequencing algorithm and software using graph algorithms in computer science. The input to our leaf-sequencing software includes (1) a set of (continuous) intensity patterns optimized by a treatment planning system at a sequence of equally spaced beam angles (typically 10 deg. apart), (2) a maximum leaf motion constraint, and (3) the number of desired arcs, k. The output is a set of treatment arcs that best approximates the set of optimized intensity patterns at all beam angles with guaranteed smooth delivery without violating the maximum leaf motion constraint. The new algorithm consists of the following key steps. First, the optimized intensity patterns are segmented into intensity profiles that are aligned with individual MLC leaf pairs. Then each intensity profile is segmented into k MLC leaf openings using a k-link shortest path algorithm. The leaf openings for all beam angles are subsequently connected together to form 1D IMAT arcs under the maximum leaf motion constraint using a shortest path algorithm. Finally, the 1D IMAT arcs are combined to form IMAT treatment arcs of MLC apertures. The performance of the implemented leaf-sequencing software has been tested for four treatment sites (prostate, breast, head and neck, and lung). In all cases, our leaf-sequencing algorithm produces efficient and highly conformal IMAT plans that rival their counterpart, the tomotherapy plans, and significantly improve the IMRT plans. Algorithm execution times ranging from a few seconds to 2 min are
A novel algorithm for OSPF link flap damping
NASA Astrophysics Data System (ADS)
Yang, Yang; Liu, Guangyi; Lin, Xiaokang
2005-02-01
Open shortest path first (OSPF) is the most widely used routing protocol in today"s IP networks, and its excellent performance has been proved in wired environments. However, when it is executed under bad channel conditions such as in wireless networks or areas with severe signal interference, links may flap frequently and some terrible problems will appear. This paper proposes a novel algorithm called OSPF link flap damping algorithm (OLFDA). The objective of OLFDA is to reduce the events of link state advertisement (LSA) update and damp the link flap with the precondition that the overall network performance is satisfying. To accomplish this, we can define criteria to identify and dynamically suppress the poorly behaved links. Information of the suppressed links won"t be advertised in OSPF domain and used in calculation of the routing tables. In addition, we can control the maximal number of links suppressed simultaneously by a router to ensure the network connectivity. OLFDA are simulated in many scenarios, and the results indicate that the algorithm has an excellent performance.
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.
NASA Astrophysics Data System (ADS)
Nakamura, T.; Sekimoto, Y.; Usui, T.; Shibasaki, R.
2012-07-01
Nowadays, for the estimation of traffic demand or people flow, modelling route choice activity in road networks is an important task and many algorithms have been developed to generate route choice sets. However, developing an algorithm based on a small amount of data that can be applied generally within a metropolitan area is difficult. This is because the characteristics of road networks vary widely. On the other hand, recently, the collection of people movement data has lately become much easier, especially through mobile phones. Lately, most mobile phones include GPS functionality. Given this background, we propose a data-oriented algorithm to generate route choice sets using mobile phone GPS data. GPS data contain a number of measurement errors; hence, they must be adjusted to account for these errors before use in advanced people movement analysis. However, this is time-consuming and expensive, because an enormous amount of daily data can be obtained. Hence, the objective of this study is to develop an algorithm that can easily manage GPS data. Specifically, at first movement data from all GPS data are selected by calculating the speed. Next, the nearest roads in the road network are selected from the GPS location and count such data for each road. Then An algorithm based on the GSP (Gateway Shortest Path) algorithm is proposed, which searches the shortest path through a given gateway. In the proposed algorithm, the road for which the utilization volume calculated by GPS data is large is selected as the gateway. Thus, route choice sets that are based on trends in real GPS data are generated. To evaluate the proposed method, GPS data from 0.7 million people a year in Japan and DRM (Digital Road Map) as the road network are used. DRM is one of the most detailed road networks in Japan. Route choice sets using the proposed algorithm are generated and the cover rate of the utilization volume of each road under evaluation is calculated. As a result, the proposed
NASA Astrophysics Data System (ADS)
Pan, Zhong-Liang; Chen, Ling; Zhang, Guang-Zhao
2016-04-01
The hybrid CMOS molecular (CMOL) circuit, which combines complementary metal-oxide-semiconductor (CMOS) components with nanoscale wires and switches, can exhibit significantly improved performance. In CMOL circuits, the nanodevices, which are called cells, should be placed appropriately and are connected by nanowires. The cells should be connected such that they follow the shortest path. This paper presents an efficient method of cell allocation in CMOL circuits with the hybrid CMOS/nanodevice structure; the method is based on a cultural algorithm with chaotic behavior. The optimal model of cell allocation is derived, and the coding of an individual representing a cell allocation is described. Then the cultural algorithm with chaotic behavior is designed to solve the optimal model. The cultural algorithm consists of a population space, a belief space, and a protocol that describes how knowledge is exchanged between the population and belief spaces. In this paper, the evolutionary processes of the population space employ a genetic algorithm in which three populations undergo parallel evolution. The evolutionary processes of the belief space use a chaotic ant colony algorithm. Extensive experiments on cell allocation in benchmark circuits showed that a low area usage can be obtained using the proposed method, and the computation time can be reduced greatly compared to that of a conventional genetic algorithm.
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.
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.
NASA Technical Reports Server (NTRS)
Prabhakaran, Nagarajan; Rishe, Naphtali; Athauda, Rukshan
1997-01-01
The South East coastal region experiences hurricane threat for almost six months in every year. To improve the accuracy of hurricane forecasts, meteorologists would need the storm paths of both the present and the past. A hurricane path can be established if we could identify the correct position of the storm at different times right from its birth to the end. We propose a method based on both spatial and temporal image correlations to locate the position of a storm from satellite images. During the hurricane season, the satellite images of the Atlantic ocean near the equator are examined for the hurricane presence. This is accomplished in two steps. In the first step, only segments with more than a particular value of cloud cover are selected for analysis. Next, we apply image processing algorithms to test the presence of a hurricane eye in the segment. If the eye is found, the coordinate of the eye is recorded along with the time stamp of the segment. If the eye is not found, we examine adjacent segments for the existence of hurricane eye. It is probable that more than one hurricane eye could be found from different segments of the same period. Hence, the above process is repeated till the entire potential area for hurricane birth is exhausted. The subsequent/previous position of each hurricane eye will be searched in the appropriate adjacent segments of the next/previous period to mark the hurricane path. The temporal coherence and spatial coherence of the images are taken into account by our scheme in determining the segments and the associated periods required for analysis.
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.
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.
4 x 4 optical cross-point packet switch matrix with minimized path-dependent optical gain.
Varrazza, Riccardo; Djordjevic, Ivan B; Hill, Matthew; Yu, Siyuan
2003-11-15
Packet-switching characteristics are optimized across an integrated 4 x 4 optical cross-point switch matrix based on active vertical coupler switch cells. Optical gain is demonstrated across the entire matrix with a <3-dB difference between the shortest and longest switching paths.
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
Inferring propagation paths for sparsely observed perturbations on complex networks
Massucci, Francesco Alessandro; Wheeler, Jonathan; Beltrán-Debón, Raúl; Joven, Jorge; Sales-Pardo, Marta; Guimerà, Roger
2016-01-01
In a complex system, perturbations propagate by following paths on the network of interactions among the system’s units. In contrast to what happens with the spreading of epidemics, observations of general perturbations are often very sparse in time (there is a single observation of the perturbed system) and in “space” (only a few perturbed and unperturbed units are observed). A major challenge in many areas, from biology to the social sciences, is to infer the propagation paths from observations of the effects of perturbation under these sparsity conditions. We address this problem and show that it is possible to go beyond the usual approach of using the shortest paths connecting the known perturbed nodes. Specifically, we show that a simple and general probabilistic model, which we solved using belief propagation, provides fast and accurate estimates of the probabilities of nodes being perturbed. PMID:27819038
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.
The Thinnest Path Problem for Secure Communications: A Directed Hypergraph Approach
2012-10-01
problem in hypergraphs remains a polynomial-time problem. The static shortest hyperpath problem was considered by Knuth [4] and Gallo et al. [5] in... Knuth , “A generalization of dijkstra’s algorithm,” Information Processing Letters, vol. 6, no. 1, pp. 177–201, February 1977. [5] G. Gallo, G. Longo, S
BootGraph: probabilistic fiber tractography using bootstrap algorithms and graph theory.
Vorburger, Robert S; Reischauer, Carolin; Boesiger, Peter
2013-02-01
Bootstrap methods have recently been introduced to diffusion-weighted magnetic resonance imaging to estimate the measurement uncertainty of ensuing diffusion parameters directly from the acquired data without the necessity to assume a noise model. These methods have been previously combined with deterministic streamline tractography algorithms to allow for the assessment of connection probabilities in the human brain. Thereby, the local noise induced disturbance in the diffusion data is accumulated additively due to the incremental progression of streamline tractography algorithms. Graph based approaches have been proposed to overcome this drawback of streamline techniques. For this reason, the bootstrap method is in the present work incorporated into a graph setup to derive a new probabilistic fiber tractography method, called BootGraph. The acquired data set is thereby converted into a weighted, undirected graph by defining a vertex in each voxel and edges between adjacent vertices. By means of the cone of uncertainty, which is derived using the wild bootstrap, a weight is thereafter assigned to each edge. Two path finding algorithms are subsequently applied to derive connection probabilities. While the first algorithm is based on the shortest path approach, the second algorithm takes all existing paths between two vertices into consideration. Tracking results are compared to an established algorithm based on the bootstrap method in combination with streamline fiber tractography and to another graph based algorithm. The BootGraph shows a very good performance in crossing situations with respect to false negatives and permits incorporating additional constraints, such as a curvature threshold. By inheriting the advantages of the bootstrap method and graph theory, the BootGraph method provides a computationally efficient and flexible probabilistic tractography setup to compute connection probability maps and virtual fiber pathways without the drawbacks of
Path Tracking Using Simple Planar curves
1992-03-01
identify by block number) FIELD IGROUP SUB-GROUP Path Planning, Obstacle Avoidance, Autonomous Vehicle Motion 19. ABSTRACT (Continue on reverse if...algorithm, the method shall be incorporated into a robot’s software system. This path tracking method will lay the groundwork for a dynamic obstacle ...dynamic obstacle avoidance system for a mobile robot. Accesion For NTIS CRA& L U,.a i.O,,-.ed l ju.-Affcation o........................ By D:;t ibutioa i
The prediction of radio-path characteristics
NASA Astrophysics Data System (ADS)
Gitina, G. M.; Kalinin, Iu. K.
The paper examines algorithms for the long-term prediction of radio-path characteristics in the ionosphere, the main characteristic being the MUF at a given distance. The proposed approach is based on long-term memories called DATA BANKS. Attention is given to the characteritics of the various banks, including the BANK OF CITIES, the BANK OF RADIO PATHS, the REFERENCE DATA BANK, and the OUTPUT DATA BANK.
Multiple Objectives and the Path Determination Problem.
1980-07-03
planners. Pipeline systems, water supply systems, communication systems, electronic systems design, aircraft routing, and the routing of shipments of...existing transportation routes and rates as expressed by commercial water , road, rail and air freight charts. Algorithmic approaches to the...path is dropped from further considera- ti on. 3) Path attribute A (or B) is better than the corresponding attribute level of at least one of the label 2
Unbiased sampling of lattice Hamilton path ensembles
NASA Astrophysics Data System (ADS)
Mansfield, Marc L.
2006-10-01
Hamilton paths, or Hamiltonian paths, are walks on a lattice which visit each site exactly once. They have been proposed as models of globular proteins and of compact polymers. A previously published algorithm [Mansfield, Macromolecules 27, 5924 (1994)] for sampling Hamilton paths on simple square and simple cubic lattices is tested for bias and for efficiency. Because the algorithm is a Metropolis Monte Carlo technique obviously satisfying detailed balance, we need only demonstrate ergodicity to ensure unbiased sampling. Two different tests for ergodicity (exact enumeration on small lattices, nonexhaustive enumeration on larger lattices) demonstrate ergodicity unequivocally for small lattices and provide strong support for ergodicity on larger lattices. Two other sampling algorithms [Ramakrishnan et al., J. Chem. Phys. 103, 7592 (1995); Lua et al., Polymer 45, 717 (2004)] are both known to produce biases on both 2×2×2 and 3×3×3 lattices, but it is shown here that the current algorithm gives unbiased sampling on these same lattices. Successive Hamilton paths are strongly correlated, so that many iterations are required between statistically independent samples. Rules for estimating the number of iterations needed to dissipate these correlations are given. However, the iteration time is so fast that the efficiency is still very good except on extremely large lattices. For example, even on lattices of total size 10×10×10 we are able to generate tens of thousands of uncorrelated Hamilton paths per hour of CPU time.
Practical path planning among movable obstacles
Chen, Pang C.; Hwang, Yong K.
1990-09-05
Path planning among movable obstacles is a practical problem that is in need of a solution. In this paper an efficient heuristic algorithm that uses a generate-and-test paradigm: a good'' candidate path is hypothesized by a global planner and subsequently verified by a local planner. In the process of formalizing the problem, we also present a technique for modeling object interactions through contact. Our algorithm has been tested on a variety of examples, and was able to generate solutions within 10 seconds. 5 figs., 27 refs.
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.
An Energy Efficient Stable Election-Based Routing Algorithm for Wireless Sensor Networks
Wang, Jin; Zhang, Zhongqi; Xia, Feng; Yuan, Weiwei; Lee, Sungyoung
2013-01-01
Sensor nodes usually have limited energy supply and they are impractical to recharge. How to balance traffic load in sensors in order to increase network lifetime is a very challenging research issue. Many clustering algorithms have been proposed recently for wireless sensor networks (WSNs). However, sensor networks with one fixed sink node often suffer from a hot spots problem since nodes near sinks have more traffic burden to forward during a multi-hop transmission process. The use of mobile sinks has been shown to be an effective technique to enhance network performance features such as latency, energy efficiency, network lifetime, etc. In this paper, a modified Stable Election Protocol (SEP), which employs a mobile sink, has been proposed for WSNs with non-uniform node distribution. The decision of selecting cluster heads by the sink is based on the minimization of the associated additional energy and residual energy at each node. Besides, the cluster head selects the shortest path to reach the sink between the direct approach and the indirect approach with the use of the nearest cluster head. Simulation results demonstrate that our algorithm has better performance than traditional routing algorithms, such as LEACH and SEP. PMID:24284767
Moody, A.
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 can provide the absolute path to a relative directory from the current working directory.
Mao, Yuxin; Zhu, Ping
2013-01-01
The unreliability and dynamics of mobile wireless sensor networks make it hard to perform end-to-end communications. This paper presents a novel source-initiated on-demand routing mechanism for efficient data transmission in mobile wireless sensor networks. It explores the Thorup-Zwick theory to achieve source-initiated on-demand routing with time efficiency. It is able to find out shortest routing path between source and target in a network and transfer data in linear time. The algorithm is easy to be implemented and performed in resource-constrained mobile wireless sensor networks. We also evaluate the approach by analyzing its cost in detail. It can be seen that the approach is efficient to support data transmission in mobile wireless sensor networks.
Mass measurements of the shortest-lived nuclides à la MISTRAL
NASA Astrophysics Data System (ADS)
Lunney, D.; Vieira, N.; Audi, G.; Gaulard, C.; de Saint Simon, M.; Thibault, C.
2006-04-01
At Princeton in the 1960's, L.G. Smith invented an instrument of astonishing accuracy and rapid measurement time, derived from his so-called mass synchrometer. Using the same principle, a radiofrequency spectrometer was constructed in Orsay to measure masses of the shortest-lived nuclides at Cern's Isolde facility. Smith's spectrometer is now a museum piece, making the Orsay version (since baptized, MISTRAL) the sole example of such an instrument and the only one ever to be used on-line. Here we report on a measurement of the 65[thin space]ms half-life, NDZ nuclide performed with MISTRAL. The measured mass excess of [thin space]keV is compared with that obtained by ISOLTRAP, since independent measurements using different techniques assure a healthy gene pool for the recommended masses of the atomic mass evaluation. The nuclide is the heaviest for which a precise mass is of importance for the so-called Wigner energy. A discussion is presented concerning this Wigner energy, perhaps the last component of nuclear mass formulas resisting microscopic treatment.
Why were Sardinians the shortest Europeans? A journey through genes, infections, nutrition, and sex.
Pes, Giovanni Mario; Tognotti, Eugenia; Poulain, Michel; Chambre, Dany; Dore, Maria Pina
2017-01-31
Since ancient times the Mediterranean island of Sardinia has been known for harboring a population with an average body height shorter than almost every other ethnic group in Europe. After over a century of investigations, the cause(s) at the origin of this uniqueness are not yet clear. The shorter stature of Sardinians appears to have been documented since prehistoric times, as revealed by the analysis of skeletal remains discovered in archaeological sites on the island. Recently, a number of genetic, hormonal, environmental, infective and nutritional factors have been put forward to explain this unique anthropometric feature, which persisted for a long time, even when environmental and living conditions improved around 1960. Although some of the putative factors are supported by sound empirical evidence, weaker support is available for others. The recent advent of whole genome analysis techniques shed new light on specific variants at the origin of this short stature. However, the marked geographical variability of stature across time and space within the island, and the well-known presence of pockets of short height in the population of the southern districts, are still puzzling findings that have attracted the interest of anthropologists and geneticists. The purpose of this review is to focus on the state-of-the-art research on stature, as well as the factors that made Sardinians the shortest among Europeans.
Montenegro, Álvaro; Callaghan, Richard T; Fitzpatrick, Scott M
2016-10-24
The prehistoric colonization of islands in Remote Oceania that began ∼3400 B.P. represents what was arguably the most expansive and ambitious maritime dispersal of humans across any of the world's seas or oceans. Though archaeological evidence has provided a relatively clear picture of when many of the major island groups were colonized, there is still considerable debate as to where these settlers originated from and their strategies/trajectories used to reach habitable land that other datasets (genetic, linguistic) are also still trying to resolve. To address these issues, we have harnessed the power of high-resolution climatic and oceanographic datasets in multiple seafaring simulation platforms to examine major pulses of colonization in the region. Our analysis, which takes into consideration currents, land distribution, wind periodicity, the influence of El Niño Southern Oscillation (ENSO) events, and "shortest-hop" trajectories, demonstrate that (i) seasonal and semiannual climatic changes were highly influential in structuring ancient Pacific voyaging; (ii) western Micronesia was likely settled from somewhere around the Maluku (Molucca) Islands; (iii) Samoa was the most probable staging area for the colonization of East Polynesia; and (iv) although there are major differences in success rates depending on time of year and the occurrence of ENSO events, settlement of Hawai'i and New Zealand is possible from the Marquesas or Society Islands, the same being the case for settlement of Easter Island from Mangareva or the Marquesas.
Molecular definition of the shortest region of deletion overlap in the Langer-Giedion syndrome
Lüdecke, Hermann-Josef; Johnson, Carey; Wagner, Michael J.; Wells, Dan E.; Turleau, Catherine; Tommerup, Niels; Latos-Bielenska, Anna; Sandig, Klaus-Rainer; Meinecke, Peter; Zabel, Bernhard; Horsthemke, Bernhard
1991-01-01
The Langer-Giedion syndrome (LGS), which is characterized by craniofacial dysmorphism and skeletal abnormalities, is caused by a genetic defect in 8q24.1. We have used 13 anonymous DNA markers from an 8q24.1-specific microdissection library, as well as c-myc and thyroglobulin gene probes, to map the deletion breakpoints in 16 patients with LGS. Twelve patients had a cytogenetically visible deletion, two patients had an apparently balanced translocation, and two patients had an apparently normal karyotype. In all cases except one translocation patient, loss of genetic material was detected. The DNA markers fall into 10 deletion intervals. Clone L48 (D8S51) defines the shortest region of deletion overlap (SRO), which is estimated to be less than 2 Mbp. Three clones–pl7-2.3EE (D8S43), L24 (D8S45), and L40 (D8S49)–which flank the SRO recognize evolutionarily conserved sequences. ImagesFigure 1Figure 3Figure 4 PMID:1836105
An Application of Self-Organizing Map for Multirobot Multigoal Path Planning with Minmax Objective
Faigl, Jan
2016-01-01
In this paper, Self-Organizing Map (SOM) for the Multiple Traveling Salesman Problem (MTSP) with minmax objective is applied to the robotic problem of multigoal path planning in the polygonal domain. The main difficulty of such SOM deployment is determination of collision-free paths among obstacles that is required to evaluate the neuron-city distances in the winner selection phase of unsupervised learning. Moreover, a collision-free path is also needed in the adaptation phase, where neurons are adapted towards the presented input signal (city) to the network. Simple approximations of the shortest path are utilized to address this issue and solve the robotic MTSP by SOM. Suitability of the proposed approximations is verified in the context of cooperative inspection, where cities represent sensing locations that guarantee to “see” the whole robots' workspace. The inspection task formulated as the MTSP-Minmax is solved by the proposed SOM approach and compared with the combinatorial heuristic GENIUS. The results indicate that the proposed approach provides competitive results to GENIUS and support applicability of SOM for robotic multigoal path planning with a group of cooperating mobile robots. The proposed combination of approximate shortest paths with unsupervised learning opens further applications of SOM in the field of robotic planning. PMID:27340395
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.
Utilization of path length fuzing in the Peacekeeper Weapon System
NASA Astrophysics Data System (ADS)
Jackson, A. D.
This paper presents a discussion of the utilization and implementation of path length fuzing in the Peacekeeper Weapon System. Some background information which introduces the concept of path length fuzing and discusses its applicability to the Peacekeeper is first presented. Mathematical modeling of path length fuzing is discussed, and some novel algorithms and techniques developed by the author for implementation of path length fuzing in the Peacekeeper Operational Flight Program are presented. The scope of this paper is confined to the flight software and targeting aspects of path length fuzing; details of of the fuze hardware and electronics are not addressed.
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.
Evaluation of concurrent priority queue algorithms. Technical report
Huang, Q.
1991-02-01
The priority queue is a fundamental data structure that is used in a large variety of parallel algorithms, such as multiprocessor scheduling and parallel best-first search of state-space graphs. This thesis addresses the design and experimental evaluation of two novel concurrent priority queues: a parallel Fibonacci heap and a concurrent priority pool, and compares them with the concurrent binary heap. The parallel Fibonacci heap is based on the sequential Fibonacci heap, which is theoretically the most efficient data structure for sequential priority queues. This scheme not only preserves the efficient operation time bounds of its sequential counterpart, but also has very low contention by distributing locks over the entire data structure. The experimental results show its linearly scalable throughput and speedup up to as many processors as tested (currently 18). A concurrent access scheme for a doubly linked list is described as part of the implementation of the parallel Fibonacci heap. The concurrent priority pool is based on the concurrent B-tree and the concurrent pool. The concurrent priority pool has the highest throughput among the priority queues studied. Like the parallel Fibonacci heap, the concurrent priority pool scales linearly up to as many processors as tested. The priority queues are evaluated in terms of throughput and speedup. Some applications of concurrent priority queues such as the vertex cover problem and the single source shortest path problem are tested.
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.
Iwamoto, Takahiro; Slanina, Zdenek; Mizorogi, Naomi; Guo, Jingdong; Akasaka, Takeshi; Nagase, Shigeru; Takaya, Hikaru; Yasuda, Nobuhiro; Kato, Tatsuhisa; Yamago, Shigeru
2014-10-27
[11]Cycloparaphenylene ([11]CPP) selectively encapsulates La@C82 to form the shortest possible metallofullerene-carbon nanotube (CNT) peapod, La@C82 ⊂[11]CPP, in solution and in the solid state. Complexation in solution was affected by the polarity of the solvent and was 16 times stronger in the polar solvent nitrobenzene than in the nonpolar solvent 1,2-dichlorobenzene. Electrochemical analysis revealed that the redox potentials of La@C82 were negatively shifted upon complexation from free La@C82 . Furthermore, the shifts in the redox potentials increased with polarity of the solvent. These results are consistent with formation of a polar complex, (La@C82 )(δ-) ⊂[11]CPP(δ+) , by partial electron transfer from [11]CPP to La@C82 . This is the first observation of such an electronic interaction between a fullerene pea and CPP pod. Theoretical calculations also supported partial charge transfer (0.07) from [11]CPP to La@C82 . The structure of the complex was unambiguously determined by X-ray crystallographic analysis, which showed the La atom inside the C82 near the periphery of the [11]CPP. The dipole moment of La@C82 was projected toward the CPP pea, nearly perpendicular to the CPP axis. The position of the La atom and the direction of the dipole moment in La@C82 ⊂[11]CPP were significantly different from those observed in La@C82 ⊂CNT, thus indicating a difference in orientation of the fullerene peas between fullerene-CPP and fullerene-CNT peapods. These results highlight the importance of pea-pea interactions in determining the orientation of the metallofullerene in metallofullerene-CNT peapods.
Algorithms and Algorithmic Languages.
ERIC Educational Resources Information Center
Veselov, V. M.; Koprov, V. M.
This paper is intended as an introduction to a number of problems connected with the description of algorithms and algorithmic languages, particularly the syntaxes and semantics of algorithmic languages. The terms "letter, word, alphabet" are defined and described. The concept of the algorithm is defined and the relation between the algorithm and…
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.
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.
Heuristic optimization of the scanning path of particle therapy beams.
Pardo, J; Donetti, M; Bourhaleb, F; Ansarinejad, A; Attili, A; Cirio, R; Garella, M A; Giordanengo, S; Givehchi, N; La Rosa, A; Marchetto, F; Monaco, V; Pecka, A; Peroni, C; Russo, G; Sacchi, R
2009-06-01
Quasidiscrete scanning is a delivery strategy for proton and ion beam therapy in which the beam is turned off when a slice is finished and a new energy must be set but not during the scanning between consecutive spots. Different scanning paths lead to different dose distributions due to the contribution of the unintended transit dose between spots. In this work an algorithm to optimize the scanning path for quasidiscrete scanned beams is presented. The classical simulated annealing algorithm is used. It is a heuristic algorithm frequently used in combinatorial optimization problems, which allows us to obtain nearly optimal solutions in acceptable running times. A study focused on the best choice of operational parameters on which the algorithm performance depends is presented. The convergence properties of the algorithm have been further improved by using the next-neighbor algorithm to generate the starting paths. Scanning paths for two clinical treatments have been optimized. The optimized paths are found to be shorter than the back-and-forth, top-to-bottom (zigzag) paths generally provided by the treatment planning systems. The gamma method has been applied to quantify the improvement achieved on the dose distribution. Results show a reduction of the transit dose when the optimized paths are used. The benefit is clear especially when the fluence per spot is low, as in the case of repainting. The minimization of the transit dose can potentially allow the use of higher beam intensities, thus decreasing the treatment time. The algorithm implemented for this work can optimize efficiently the scanning path of quasidiscrete scanned particle beams. Optimized scanning paths decrease the transit dose and lead to better dose distributions.
Path-consistency: When space misses time
Chmeiss, A.; Jegou, P.
1996-12-31
Within the framework of constraint programming, particulary concerning the Constraint Satisfaction Problems (CSPs), the techniques of preprocessing based on filtering algorithms were shown to be very important for the search phase. In particular, two filtering methods have been studied, these methods exploit two properties of local consistency: arc- and path-consistency. Concerning the arc-consistency methods, there is a linear time algorithm (in the size of the problem) which is efficient in practice. But the limitations of the arc-consistency algorithms requires often filtering methods with higher order like path-consistency filterings. The best path-consistency algorithm proposed is PC-6, a natural generalization of AC-6 to path-consistency. Its time complexity is O(n{sup 3}d{sup 4}) and its space complexity is O(n{sup 3}d{sup 4}), where n is the number of variables and d is the size of domains. We have remarked that PC-6, though it is widely better than PC-4, was not very efficient in practice, specially for those classes of problems that require an important space to be run. Therefore, we propose here a new path-consistency algorithm called PC-7, its space complexity is O(n{sup 3}d{sup 4}) but its time complexity is O(n{sup 3}d{sup 4}) i.e. worse than that of PC-6. However, the simplicity of PC-7 as well as the data structures used for its implementation offer really a higher performance than PC-6. Furthermore, it turns out that when the size of domains is a constant of the problems, the time complexity of PC-7 becomes. like PC-6, optimal i.e. O(n{sup 3}).
Understanding disordered systems through numerical simulation and algorithm development
NASA Astrophysics Data System (ADS)
Sweeney, Sean Michael
ferromagnet is studied, which is especially useful since it serves as a prototype for more complicated disordered systems such as the random field Ising model and spin glasses. We investigate the effect that changing boundary spins has on the locations of domain walls in the interior of the random ferromagnet system. We provide an analytic proof that ground state domain walls in the two dimensional system are decomposable, and we map these domain walls to a shortest paths problem. By implementing a multiple-source shortest paths algorithm developed by Philip Klein, we are able to efficiently probe domain wall locations for all possible configurations of boundary spins. We consider lattices with uncorrelated dis- order, as well as disorder that is spatially correlated according to a power law. We present numerical results for the scaling exponent governing the probability that a domain wall can be induced that passes through a particular location in the system's interior, and we compare these results to previous results on the directed polymer problem.
NASA Astrophysics Data System (ADS)
Lloyd, Seth; Dreyer, Olaf
2016-02-01
Path integrals calculate probabilities by summing over classical configurations of variables such as fields, assigning each configuration a phase equal to the action of that configuration. This paper defines a universal path integral, which sums over all computable structures. This path integral contains as sub-integrals all possible computable path integrals, including those of field theory, the standard model of elementary particles, discrete models of quantum gravity, string theory, etc. The universal path integral possesses a well-defined measure that guarantees its finiteness. The probabilities for events corresponding to sub-integrals can be calculated using the method of decoherent histories. The universal path integral supports a quantum theory of the universe in which the world that we see around us arises out of the interference between all computable structures.
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
NASA Astrophysics Data System (ADS)
Janse van Rensburg, E. J.
2010-08-01
In this paper the models of pulled Dyck paths in Janse van Rensburg (2010 J. Phys. A: Math. Theor. 43 215001) are generalized to pulled Motzkin path models. The generating functions of pulled Motzkin paths are determined in terms of series over trinomial coefficients and the elastic response of a Motzkin path pulled at its endpoint (see Orlandini and Whittington (2004 J. Phys. A: Math. Gen. 37 5305-14)) is shown to be R(f) = 0 for forces pushing the endpoint toward the adsorbing line and R(f) = f(1 + 2cosh f))/(2sinh f) → f as f → ∞, for forces pulling the path away from the X-axis. In addition, the elastic response of a Motzkin path pulled at its midpoint is shown to be R(f) = 0 for forces pushing the midpoint toward the adsorbing line and R(f) = f(1 + 2cosh (f/2))/sinh (f/2) → 2f as f → ∞, for forces pulling the path away from the X-axis. Formal combinatorial identities arising from pulled Motzkin path models are also presented. These identities are the generalization of combinatorial identities obtained in directed paths models to their natural trinomial counterparts.
Path Integrals and Hamiltonians
NASA Astrophysics Data System (ADS)
Baaquie, Belal E.
2014-03-01
1. Synopsis; Part I. Fundamental Principles: 2. The mathematical structure of quantum mechanics; 3. Operators; 4. The Feynman path integral; 5. Hamiltonian mechanics; 6. Path integral quantization; Part II. Stochastic Processes: 7. Stochastic systems; Part III. Discrete Degrees of Freedom: 8. Ising model; 9. Ising model: magnetic field; 10. Fermions; Part IV. Quadratic Path Integrals: 11. Simple harmonic oscillators; 12. Gaussian path integrals; Part V. Action with Acceleration: 13. Acceleration Lagrangian; 14. Pseudo-Hermitian Euclidean Hamiltonian; 15. Non-Hermitian Hamiltonian: Jordan blocks; 16. The quartic potential: instantons; 17. Compact degrees of freedom; Index.
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.
Differential-Evolution Control Parameter Optimization for Unmanned Aerial Vehicle Path Planning
Kok, Kai Yit; Rajendran, Parvathy
2016-01-01
The differential evolution algorithm has been widely applied on unmanned aerial vehicle (UAV) path planning. At present, four random tuning parameters exist for differential evolution algorithm, namely, population size, differential weight, crossover, and generation number. These tuning parameters are required, together with user setting on path and computational cost weightage. However, the optimum settings of these tuning parameters vary according to application. Instead of trial and error, this paper presents an optimization method of differential evolution algorithm for tuning the parameters of UAV path planning. The parameters that this research focuses on are population size, differential weight, crossover, and generation number. The developed algorithm enables the user to simply define the weightage desired between the path and computational cost to converge with the minimum generation required based on user requirement. In conclusion, the proposed optimization of tuning parameters in differential evolution algorithm for UAV path planning expedites and improves the final output path and computational cost. PMID:26943630
Differential-Evolution Control Parameter Optimization for Unmanned Aerial Vehicle Path Planning.
Kok, Kai Yit; Rajendran, Parvathy
2016-01-01
The differential evolution algorithm has been widely applied on unmanned aerial vehicle (UAV) path planning. At present, four random tuning parameters exist for differential evolution algorithm, namely, population size, differential weight, crossover, and generation number. These tuning parameters are required, together with user setting on path and computational cost weightage. However, the optimum settings of these tuning parameters vary according to application. Instead of trial and error, this paper presents an optimization method of differential evolution algorithm for tuning the parameters of UAV path planning. The parameters that this research focuses on are population size, differential weight, crossover, and generation number. The developed algorithm enables the user to simply define the weightage desired between the path and computational cost to converge with the minimum generation required based on user requirement. In conclusion, the proposed optimization of tuning parameters in differential evolution algorithm for UAV path planning expedites and improves the final output path and computational cost.
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.
Optical tomography with discretized path integral
Yuan, Bingzhi; Tamaki, Toru; Kushida, Takahiro; Mukaigawa, Yasuhiro; Kubo, Hiroyuki; Raytchev, Bisser; Kaneda, Kazufumi
2015-01-01
Abstract. We present a framework for optical tomography based on a path integral. Instead of directly solving the radiative transport equations, which have been widely used in optical tomography, we use a path integral that has been developed for rendering participating media based on the volume rendering equation in computer graphics. For a discretized two-dimensional layered grid, we develop an algorithm to estimate the extinction coefficients of each voxel with an interior point method. Numerical simulation results are shown to demonstrate that the proposed method works well. PMID:26839903
Optical tomography with discretized path integral.
Yuan, Bingzhi; Tamaki, Toru; Kushida, Takahiro; Mukaigawa, Yasuhiro; Kubo, Hiroyuki; Raytchev, Bisser; Kaneda, Kazufumi
2015-07-01
We present a framework for optical tomography based on a path integral. Instead of directly solving the radiative transport equations, which have been widely used in optical tomography, we use a path integral that has been developed for rendering participating media based on the volume rendering equation in computer graphics. For a discretized two-dimensional layered grid, we develop an algorithm to estimate the extinction coefficients of each voxel with an interior point method. Numerical simulation results are shown to demonstrate that the proposed method works well.
Enzymatic reaction paths as determined by transition path sampling
NASA Astrophysics Data System (ADS)
Masterson, Jean Emily
, 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.
Matvienko, G G; Oshlakov, V K; Sukhanov, A Ya; Stepanov, A N
2015-02-28
We consider the algorithms that implement a broadband ('multiwave') radiative transfer with allowance for multiple (aerosol) scattering and absorption by main atmospheric gases. In the spectral range of 0.6 – 1 μm, a closed numerical simulation of modifications of the supercontinuum component of a probing femtosecond pulse is performed. In the framework of the algorithms for solving the inverse atmospheric-optics problems with the help of a genetic algorithm, we give an interpretation of the experimental backscattered spectrum of the supercontinuum. An adequate reconstruction of the distribution mode for the particles of artificial aerosol with the narrow-modal distributions in a size range of 0.5 – 2 mm and a step of 0.5 mm is obtained. (light scattering)
Least-cost paths in mountainous terrain
NASA Astrophysics Data System (ADS)
Rees, W. G.
2004-04-01
Footpaths in a mountainous area of Wales are modelled as least-cost paths between the start and end points. The cost function is defined on the basis of topography alone, and is defined in such a way that the cost penalty for excessively steep slopes is an adjustable parameter of the model. Least-cost paths are calculated by applying Dijkstra's algorithm to a Digital Elevation Model. Comparison of these calculated least-cost paths with existing footpaths suggests that the latter do not usually follow the least-time route, but instead optimise the metabolic cost for human locomotion. The method developed here is proposed as a means of exploring possible routes for new footpaths in mountainous areas.
ERIC Educational Resources Information Center
Stegemoller, William; Stegemoller, Rebecca
2004-01-01
The path taken and the turns made as a turtle traces a polygon are examined to discover an important theorem in geometry. A unique tool, the Angle Adder, is implemented in the investigation. (Contains 9 figures.)
Tortuous path chemical preconcentrator
Manginell, Ronald P.; Lewis, Patrick R.; Adkins, Douglas R.; Wheeler, David R.; Simonson, Robert J.
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.
NASA Astrophysics Data System (ADS)
Iyer, Sridhar
2016-12-01
The ever-increasing global Internet traffic will inevitably lead to a serious upgrade of the current optical networks' capacity. The legacy infrastructure can be enhanced not only by increasing the capacity but also by adopting advance modulation formats, having increased spectral efficiency at higher data rate. In a transparent mixed-line-rate (MLR) optical network, different line rates, on different wavelengths, can coexist on the same fiber. Migration to data rates higher than 10 Gbps requires the implementation of phase modulation schemes. However, the co-existing on-off keying (OOK) channels cause critical physical layer impairments (PLIs) to the phase modulated channels, mainly due to cross-phase modulation (XPM), which in turn limits the network's performance. In order to mitigate this effect, a more sophisticated PLI-Routing and Wavelength Assignment (PLI-RWA) scheme needs to be adopted. In this paper, we investigate the critical impairment for each data rate and the way it affects the quality of transmission (QoT). In view of the aforementioned, we present a novel dynamic PLI-RWA algorithm for MLR optical networks. The proposed algorithm is compared through simulations with the shortest path and minimum hop routing schemes. The simulation results show that performance of the proposed algorithm is better than the existing schemes.
The lawnmower problem and other geometric path covering problems
Fekete, S.; Arkin, E.; Mitchell, J.
1994-12-31
We discuss the Lawnmower Problem: Given a polygonal region, find the shortest closed path along which we have to move a given object (typically a square or a circle), such that any point of the region will be covered by the object for some position of it movement. In another version of the problem, known as the Milling Problem, the object has to stay within the region at all times. Practical motivations for considering the Lawnmower Problem come from manufacturing (spray painting, quality control), geography (aerial surveys), optimization (tour planning for a large number of clients with limited mobility), and gardening. The Milling Problem has gained attention by its importance for NC pocket machining. We show that both problems are NP-hard and discuss approximation methods for various versions of the problem.
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.
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.
Construction of protein interaction network involved in lung adenocarcinomas using a novel algorithm
Chen, Juan; Yang, Hai-Tao; Li, Zhu; Xu, Ning; Yu, Bo; Xu, Jun-Ping; Zhao, Pei-Ge; Wang, Yan; Zhang, Xiu-Juan; Lin, Dian-Jie
2016-01-01
Studies that only assess differentially-expressed (DE) genes do not contain the information required to investigate the mechanisms of diseases. A complete knowledge of all the direct and indirect interactions between proteins may act as a significant benchmark in the process of forming a comprehensive description of cellular mechanisms and functions. The results of protein interaction network studies are often inconsistent and are based on various methods. In the present study, a combined network was constructed using selected gene pairs, following the conversion and combination of the scores of gene pairs that were obtained across multiple approaches by a novel algorithm. Samples from patients with and without lung adenocarcinoma were compared, and the RankProd package was used to identify DE genes. The empirical Bayesian (EB) meta-analysis approach, the search tool for the retrieval of interacting genes/proteins database (STRING), the weighted gene coexpression network analysis (WGCNA) package and the differentially-coexpressed genes and links package (DCGL) were used for network construction. A combined network was also constructed with a novel rank-based algorithm using a combined score. The topological features of the 5 networks were analyzed and compared. A total of 941 DE genes were screened. The topological analysis indicated that the gene interaction network constructed using the WGCNA method was more likely to produce a small-world property, which has a small average shortest path length and a large clustering coefficient, whereas the combined network was confirmed to be a scale-free network. Gene pairs that were identified using the novel combined method were mostly enriched in the cell cycle and p53 signaling pathway. The present study provided a novel perspective to the network-based analysis. Each method has advantages and disadvantages. Compared with single methods, the combined algorithm used in the present study may provide a novel method to
An Access Path Model for Physical Database Design.
1979-12-28
target system. 4.1 Algebraic Structure for Physical Design For the purposes of implementation-oriented design, we shall use the logical access paths...subsection, we present an algorithm for gen- erating a maximal labelling that specifies superior support for the access paths most heavily travelled. Assume...A.C.M. SIGMOD Conf., (May 79). [CARD731 Cardenas , A. F., "Evaluation and Selection of File Organization - A Model and a System," Comm. A.C.M., V 16, N
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…
NASA Technical Reports Server (NTRS)
Bill, R. C.; Johnson, R. D. (Inventor)
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.
An Algorithm for Linearly Constrained Nonlinear Programming Programming Problems.
1980-01-01
ALGORITHM FOR LINEARLY CONSTRAINED NONLINEAR PROGRAMMING PROBLEMS Mokhtar S. Bazaraa and Jamie J. Goode In this paper an algorithm for solving a linearly...distance pro- gramr.ing, as in the works of Bazaraa and Goode 12], and Wolfe [16 can be used for solving this problem. Special methods that take advantage of...34 Pacific Journal of Mathematics, Volume 16, pp. 1-3, 1966. 2. M. S. Bazaraa and J. j. Goode, "An Algorithm for Finding the Shortest Element of a
Finding reaction paths using the potential energy as reaction coordinate.
Aguilar-Mogas, Antoni; Giménez, Xavier; Bofill, Josep Maria
2008-03-14
The intrinsic reaction coordinate curve (IRC), normally proposed as a representation of a reaction path, is parametrized as a function of the potential energy rather than the arc-length. This change in the parametrization of the curve implies that the values of the energy of the potential energy surface points, where the IRC curve is located, play the role of reaction coordinate. We use Caratheodory's relation to derive in a rigorous manner the proposed parametrization of the IRC path. Since this Caratheodory's relation is the basis of the theory of calculus of variations, then this fact permits to reformulate the IRC model from this mathematical theory. In this mathematical theory, the character of the variational solution (either maximum or minimum) is given through the Weierstrass E-function. As proposed by Crehuet and Bofill [J. Chem. Phys. 122, 234105 (2005)], we use the minimization of the Weierstrass E-function, as a function of the potential energy, to locate an IRC path between two minima from an arbitrary curve on the potential energy surface, and then join these two minima. We also prove, from the analysis of the Weierstrass E-function, the mathematical bases for the algorithms proposed to locate the IRC path. The proposed algorithm is applied to a set of examples. Finally, the algorithm is used to locate a discontinuous, or broken, IRC path, namely, when the path connects two first order saddle points through a valley-ridged inflection point.
A neural network approach to complete coverage path planning.
Yang, Simon X; Luo, Chaomin
2004-02-01
Complete coverage path planning requires the robot path to cover every part of the workspace, which is an essential issue in cleaning robots and many other robotic applications such as vacuum robots, painter robots, land mine detectors, lawn mowers, automated harvesters, and window cleaners. In this paper, a novel neural network approach is proposed for complete coverage path planning with obstacle avoidance of cleaning robots in nonstationary environments. The dynamics of each neuron in the topologically organized neural network is characterized by a shunting equation derived from Hodgkin and Huxley's (1952) membrane equation. There are only local lateral connections among neurons. The robot path is autonomously generated from the dynamic activity landscape of the neural network and the previous robot location. The proposed model algorithm is computationally simple. Simulation results show that the proposed model is capable of planning collision-free complete coverage robot paths.
Path Integrals and Exotic Options:. Methods and Numerical Results
NASA Astrophysics Data System (ADS)
Bormetti, G.; Montagna, G.; Moreni, N.; Nicrosini, O.
2005-09-01
In the framework of Black-Scholes-Merton model of financial derivatives, a path integral approach to option pricing is presented. A general formula to price path dependent options on multidimensional and correlated underlying assets is obtained and implemented by means of various flexible and efficient algorithms. As an example, we detail the case of Asian call options. The numerical results are compared with those obtained with other procedures used in quantitative finance and found to be in good agreement. In particular, when pricing at the money (ATM) and out of the money (OTM) options, path integral exhibits competitive performances.
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.
Privacy-Preserving Relationship Path Discovery in Social Networks
NASA Astrophysics Data System (ADS)
Mezzour, Ghita; Perrig, Adrian; Gligor, Virgil; Papadimitratos, Panos
As social networks sites continue to proliferate and are being used for an increasing variety of purposes, the privacy risks raised by the full access of social networking sites over user data become uncomfortable. A decentralized social network would help alleviate this problem, but offering the functionalities of social networking sites is a distributed manner is a challenging problem. In this paper, we provide techniques to instantiate one of the core functionalities of social networks: discovery of paths between individuals. Our algorithm preserves the privacy of relationship information, and can operate offline during the path discovery phase. We simulate our algorithm on real social network topologies.
The traffic equilibrium problem with nonadditive path costs
Gabriel, S.A.; Bernstein, D.
1995-08-21
In this paper the authors present a version of the (static) traffic equilibrium problem in which the cost incurred on a path is not simply the sum of the costs on the arcs that constitute that path. The authors motivate this nonadditive version of the problem by describing several situations in which the classical additivity assumption fails. They also present an algorithm for solving nonadditive problems that is based on the recent NE/SQP algorithm, a fast and robust method for the nonlinear complementarity problem. Finally, they present a small example that illustrates both the importance of using nonadditive costs and the effectiveness of the NE/SQP method.
ARPANET Routing Algorithm Improvements
1978-10-01
IMPROVEMENTS . .PFOnINI ORG. REPORT MUNDER -- ) _ .. .... 3940 7, AUT(c) .. .. .. CONTRACT Of GRANT NUMSlet e) SJ. M. /Mc~uillan E. C./Rosen I...8217), this problem may persist for a very long time, causing extremely bad performance throughout the whole network (for instance, if w’ reports that one of...algorithm may naturally tend to oscillate between bad routing paths and become itself a major contributor to network congestion. These examples show
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.
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.
Nonadiabatic transition path sampling
NASA Astrophysics Data System (ADS)
Sherman, M. C.; Corcelli, S. A.
2016-07-01
Fewest-switches surface hopping (FSSH) is combined with transition path sampling (TPS) to produce a new method called nonadiabatic path sampling (NAPS). The NAPS method is validated on a model electron transfer system coupled to a Langevin bath. Numerically exact rate constants are computed using the reactive flux (RF) method over a broad range of solvent frictions that span from the energy diffusion (low friction) regime to the spatial diffusion (high friction) regime. The NAPS method is shown to quantitatively reproduce the RF benchmark rate constants over the full range of solvent friction. Integrating FSSH within the TPS framework expands the applicability of both approaches and creates a new method that will be helpful in determining detailed mechanisms for nonadiabatic reactions in the condensed-phase.
Mattie, Mark E.; Staib, Lawrence; Stratmann, Eric; Tagare, Hemant D.; Duncan, James; Miller, Perry L.
2000-01-01
Objective: Currently, when cytopathology images are archived, they are typically stored with a limited text-based description of their content. Such a description inherently fails to quantify the properties of an image and refers to an extremely small fraction of its information content. This paper describes a method for automatically indexing images of individual cells and their associated diagnoses by computationally derived cell descriptors. This methodology may serve to better index data contained in digital image databases, thereby enabling cytologists and pathologists to cross-reference cells of unknown etiology or nature. Design: The indexing method, implemented in a program called PathMaster, uses a series of computer-based feature extraction routines. Descriptors of individual cell characteristics generated by these routines are employed as indexes of cell morphology, texture, color, and spatial orientation. Measurements: The indexing fidelity of the program was tested after populating its database with images of 152 lymphocytes/lymphoma cells captured from lymph node touch preparations stained with hematoxylin and eosin. Images of “unknown” lymphoid cells, previously unprocessed, were then submitted for feature extraction and diagnostic cross-referencing analysis. Results: PathMaster listed the correct diagnosis as its first differential in 94 percent of recognition trials. In the remaining 6 percent of trials, PathMaster listed the correct diagnosis within the first three “differentials.” Conclusion: PathMaster is a pilot cell image indexing program/search engine that creates an indexed reference of images. Use of such a reference may provide assistance in the diagnostic/prognostic process by furnishing a prioritized list of possible identifications for a cell of uncertain etiology. PMID:10887168
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.
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.
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.
The path planning of UAV based on orthogonal particle swarm optimization
NASA Astrophysics Data System (ADS)
Liu, Xin; Wei, Haiguang; Zhou, Chengping; Li, Shujing
2013-10-01
To ensure the attack mission success rate, a trajectory with high survivability and accepted path length and multiple paths with different attack angles must be planned. This paper proposes a novel path planning algorithm based on orthogonal particle swarm optimization, which divides population individual and speed vector into independent orthogonal parts, velocity and individual part update independently, this improvement advances optimization effect of traditional particle swarm optimization in the field of path planning, multiple paths are produced by setting different attacking angles, this method is simulated on electronic chart, the simulation result shows the effect of this method.
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
Reynolds, Andy M; Dutta, Tushar K; Curtis, Rosane H C; Powers, Stephen J; Gaur, Hari S; Kerry, Brian R
2011-04-06
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.
Path Following with Slip Compensation for a Mars Rover
NASA Technical Reports Server (NTRS)
Helmick, Daniel; Cheng, Yang; Clouse, Daniel; Matthies, Larry; Roumeliotis, Stergios
2005-01-01
A software system for autonomous operation of a Mars rover is composed of several key algorithms that enable the rover to accurately follow a designated path, compensate for slippage of its wheels on terrain, and reach intended goals. The techniques implemented by the algorithms are visual odometry, full vehicle kinematics, a Kalman filter, and path following with slip compensation. The visual-odometry algorithm tracks distinctive scene features in stereo imagery to estimate rover motion between successively acquired stereo image pairs, by use of a maximum-likelihood motion-estimation algorithm. The full-vehicle kinematics algorithm estimates motion, with a no-slip assumption, from measured wheel rates, steering angles, and angles of rockers and bogies in the rover suspension system. The Kalman filter merges data from an inertial measurement unit (IMU) and the visual-odometry algorithm. The merged estimate is then compared to the kinematic estimate to determine whether and how much slippage has occurred. The kinematic estimate is used to complement the Kalman-filter estimate if no statistically significant slippage has occurred. If slippage has occurred, then a slip vector is calculated by subtracting the current Kalman filter estimate from the kinematic estimate. This slip vector is then used, in conjunction with the inverse kinematics, to determine the wheel velocities and steering angles needed to compensate for slip and follow the desired path.
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
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
Demonstration of scan path optimization in proton therapy
Kang, Joanne H.; Wilkens, Jan J.; Oelfke, Uwe
2007-09-15
A three-dimensional (3D) intensity modulated proton therapy treatment plan to be delivered by magnetic scanning may comprise thousands of discrete beam positions. This research presents the minimization of the total scan path length by application of a fast simulated annealing (FSA) optimization algorithm. Treatment plans for clinical prostate and head and neck cases were sequenced for continuous raster scanning in two ways, and the resulting scan path lengths were compared: (1) A simple back-and-forth, top-to-bottom (zigzag) succession, and (2) an optimized path produced as a solution of the FSA algorithm. Using a first approximation of the scanning dynamics, the delivery times for the scan sequences before and after path optimization were calculated for comparison. In these clinical examples, the FSA optimization shortened the total scan path length for the 3D target volumes by approximately 13%-56%. The number of extraneous spilled particles was correspondingly reduced by about 13%-54% due to the more efficient scanning maps that eliminated multiple crossings through regions of zero fluence. The relative decrease in delivery time due to path length minimization was estimated to be less than 1%, due to both a high scanning speed and time requirements that could not be altered by optimization (e.g., time required to change the beam energy). In a preliminary consideration of application to rescanning techniques, the decrease in delivery time was estimated to be 4%-20%.
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.
NASA Technical Reports Server (NTRS)
Mehhtz, Peter
2005-01-01
JPF is an explicit state software model checker for Java bytecode. Today, JPF is a swiss army knife for all sort of runtime based verification purposes. This basically means JPF is a Java virtual machine that executes your program not just once (like a normal VM), but theoretically in all possible ways, checking for property violations like deadlocks or unhandled exceptions along all potential execution paths. If it finds an error, JPF reports the whole execution that leads to it. Unlike a normal debugger, JPF keeps track of every step how it got to the defect.
Bleakley, Hoyt; Lin, Jeffrey
2012-01-01
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
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
On the importance of path for phase unwrapping in synthetic aperture radar interferometry.
Osmanoglu, Batuhan; Dixon, Timothy H; Wdowinski, Shimon; Cabral-Cano, Enrique
2011-07-01
Phase unwrapping is a key procedure in interferometric synthetic aperture radar studies, translating ambiguous phase observations to topography, and surface deformation estimates. Some unwrapping algorithms are conducted along specific paths based on different selection criteria. In this study, we analyze six unwrapping paths: line scan, maximum coherence, phase derivative variance, phase derivative variance with branch-cut, second-derivative reliability, and the Fisher distance. The latter is a new path algorithm based on Fisher information theory, which combines the phase derivative with the expected variance to get a more robust path, potentially performing better than others in the case of low image quality. In order to compare only the performance of the paths, the same unwrapping function (phase derivative integral) is used. Results indicate that the Fisher distance algorithm gives better results in most cases.
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)
NASA Astrophysics Data System (ADS)
Moradi, M.; Delavar, M. R.; Moradi, A.
2015-12-01
Being one of the natural disasters, earthquake can seriously damage buildings, urban facilities and cause road blockage. Post-earthquake route planning is problem that has been addressed in frequent researches. The main aim of this research is to present a route planning model for after earthquake. It is assumed in this research that no damage data is available. The presented model tries to find the optimum route based on a number of contributing factors which mainly indicate the length, width and safety of the road. The safety of the road is represented by a number of criteria such as distance to faults, percentage of non-standard buildings and percentage of high buildings around the route. An integration of genetic algorithm and ordered weighted averaging operator is employed in the model. The former searches the problem space among all alternatives, while the latter aggregates the scores of road segments to compute an overall score for each alternative. Ordered weighted averaging operator enables the users of the system to evaluate the alternative routes based on their decision strategy. Based on the proposed model, an optimistic user tries to find the shortest path between the two points, whereas a pessimistic user tends to pay more attention to safety parameters even if it enforces a longer route. The results depicts that decision strategy can considerably alter the optimum route. Moreover, post-earthquake route planning is a function of not only the length of the route but also the probability of the road blockage.
Efficient transition path sampling for systems with multiple reaction pathways
NASA Astrophysics Data System (ADS)
Chen, L. Y.; Nash, P. L.; Horing, N. J. M.
2005-09-01
A new algorithm is developed for sampling transition paths and computing reaction rates. To illustrate the use of this method, we study a two-dimensional system that has two reaction pathways: one pathway is straight with a relatively high barrier and the other is roundabout with a lower barrier. The transition rate and the ratio between the numbers of the straight and roundabout transition paths are computed for a wide range of temperatures. Our study shows that the harmonic approximation for fluctuations about the steepest-descent paths is not valid even at relatively low temperatures and, furthermore, that factors related to entropy have to be determined by the global geometry of the potential-energy surface (rather than just the local curvatures alone) for complex reaction systems. It is reasonable to expect that this algorithm is also applicable to higher dimensional systems.
Path following by a quadrotor using virtual target pursuit guidance
NASA Astrophysics Data System (ADS)
Manjunath, Abhishek
Quadrotors, being more agile than fixed-wing vehicles, are the ideal candidates for autonomous missions in small, compact spaces. The immense challenge to navigate such environments is fulfilled by the concept of path following. Path following is the method of tracking/tracing a fixed, pre-defined path with minimum position error while exerting the lowest possible control effort. In this work, the missile guidance technique of Pure Pursuit is adopted and modified for a 3D quadrotor model to follow fixed, compact trajectories. A specialized hardware testing platform is developed to test this algorithm. The results obtained from simulation and flight tests are compared to results from another technique called Differential Flatness. A small part of this thesis also deals with the stability analysis of the modified 3D Pure Pursuit algorithm to track trajectories expending lower control effort.
NASA Astrophysics Data System (ADS)
Namdari, Mohammad Hasan; Hejazi, Seyed Reza; Palhang, Maziar
2016-06-01
In this paper, modified versions of quadtree/octree, as structures used in path planning, are proposed which we call them cornered quadtree/octree. Also a new method of creating paths in quadtrees/octrees, once quadrants/octants to be passed are determined, is proposed both to improve traveled distance and path smoothness. In proposed modified versions of quadtree/octree, four corner cells of quadrants and eight corner voxels of octants are also considered as nodes of the graph to be searched for finding the shortest path. This causes better quadrant/octant selection during graph search relative to simple quadtrees and octrees. On the other hand, after that all quadrants/octants are determined, multiple gateways are nominated between each two selected nodes and path is constructed by passing through the gateway which its selection leads in shorter and smoother path. Proposed structures in this paper alongside the utilized path construction approach, creates better paths in terms of path length than those created if simple trees are used, somehow equal to the quality of the achieved paths by framed trees, meanwhile interestingly, consumed time and memory in our proposed method are closer to the used time and memory if simple trees are used.
2013-10-01
Problems”, available online at http://arxiv.org/pdf/1212.6176v1.pdf [7] G. Ausiello, G. Italiano , and U. Nanni, “Optimal traversal of directed...algorithm,” Infor- mation Processing Letters, vol. 6, no. 1, pp. 177–201, February 1977. [9] G. Ausiello, U. Nanni, and G.F. Italiano , “Dynamic
Real-time robot path planning based on a modified pulse-coupled neural network model.
Qu, Hong; Yang, Simon X; Willms, Allan R; Yi, Zhang
2009-11-01
This paper presents a modified pulse-coupled neural network (MPCNN) model for real-time collision-free path planning of mobile robots in nonstationary environments. The proposed neural network for robots is topologically organized with only local lateral connections among neurons. It works in dynamic environments and requires no prior knowledge of target or barrier movements. The target neuron fires first, and then the firing event spreads out, through the lateral connections among the neurons, like the propagation of a wave. Obstacles have no connections to their neighbors. Each neuron records its parent, that is, the neighbor that caused it to fire. The real-time optimal path is then the sequence of parents from the robot to the target. In a static case where the barriers and targets are stationary, this paper proves that the generated wave in the network spreads outward with travel times proportional to the linking strength among neurons. Thus, the generated path is always the global shortest path from the robot to the target. In addition, each neuron in the proposed model can propagate a firing event to its neighboring neuron without any comparing computations. The proposed model is applied to generate collision-free paths for a mobile robot to solve a maze-type problem, to circumvent concave U-shaped obstacles, and to track a moving target in an environment with varying obstacles. The effectiveness and efficiency of the proposed approach is demonstrated through simulation and comparison studies.
Hierarchical path planning and control of a small fixed-wing UAV: Theory and experimental validation
NASA Astrophysics Data System (ADS)
Jung, Dongwon
2007-12-01
Recently there has been a tremendous growth of research emphasizing control of unmanned aerial vehicles (UAVs) either in isolation or in teams. As a matter of fact, UAVs increasingly find their way into military and law enforcement applications (e.g., reconnaissance, remote delivery of urgent equipment/material, resource assessment, environmental monitoring, battlefield monitoring, ordnance delivery, etc.). This trend will continue in the future, as UAVs are poised to replace the human-in-the-loop during dangerous missions. Civilian applications of UAVs are also envisioned such as crop dusting, geological surveying, search and rescue operations, etc. In this thesis we propose a new online multiresolution path planning algorithm for a small UAV with limited on-board computational resources. The proposed approach assumes that the UAV has detailed information of the environment and the obstacles only in its vicinity. Information about far-away obstacles is also available, albeit less accurately. The proposed algorithm uses the fast lifting wavelet transform (FLWT) to get a multiresolution cell decomposition of the environment, whose dimension is commensurate to the on-board computational resources. A topological graph representation of the multiresolution cell decomposition is constructed efficiently, directly from the approximation and detail wavelet coefficients. Dynamic path planning is sequentially executed for an optimal path using the A* algorithm over the resulting graph. The proposed path planning algorithm is implemented on-line on a small autopilot. Comparisons with the standard D*-lite algorithm are also presented. We also investigate the problem of generating a smooth, planar reference path from a discrete optimal path. Upon the optimal path being represented as a sequence of cells in square geometry, we derive a smooth B-spline path that is constrained inside a channel that is induced by the geometry of the cells. To this end, a constrained optimization
Nonlinear Dimensionality Reduction via Path-Based Isometric Mapping.
Najafi, Amir; Joudaki, Amir; Fatemizadeh, Emad
2016-07-01
Nonlinear dimensionality reduction methods have demonstrated top-notch performance in many pattern recognition and image classification tasks. Despite their popularity, they suffer from highly expensive time and memory requirements, which render them inapplicable to large-scale datasets. To leverage such cases we propose a new method called "Path-Based Isomap". Similar to Isomap, we exploit geodesic paths to find the low-dimensional embedding. However, instead of preserving pairwise geodesic distances, the low-dimensional embedding is computed via a path-mapping algorithm. Due to the much fewer number of paths compared to number of data points, a significant improvement in time and memory complexity with a comparable performance is achieved. The method demonstrates state-of-the-art performance on well-known synthetic and real-world datasets, as well as in the presence of noise.
A Faster, Unbiased Path Opening by Upper Skeletonization and Weighted Adjacency Graphs.
Asplund, Teo; Luengo Hendriks, Cris L
2016-12-01
The path opening is a filter that preserves bright regions in the image in which a path of a certain length L fits. A path is a (not necessarily straight) line defined by a specific adjacency relation. The most efficient implementation known scales as O(min(L, d, Q) N) with the length of the path, L , the maximum possible path length, d , the number of graylevels, Q , and the image size, N . An approximation exists (parsimonious path opening) that has an execution time independent of path length. This is achieved by preselecting paths, and applying 1D openings along these paths. However, the preselected paths can miss important structures, as described by its authors. Here, we propose a different approximation, in which we preselect paths using a grayvalue skeleton. The skeleton follows all ridges in the image, meaning that no important line structures will be missed. An H-minima transform simplifies the image to reduce the number of branches in the skeleton. A graph-based version of the traditional path opening operates only on the pixels in the skeleton, yielding speedups up to one order of magnitude, depending on image size and filter parameters. The edges of the graph are weighted in order to minimize bias. Experiments show that the proposed algorithm scales linearly with image size, and that it is often slightly faster for longer paths than for shorter paths. The algorithm also yields the most accurate results-as compared with a number of path opening variants-when measuring length distributions.
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.
2014-06-19
the number of possible paths within a program grows exponentially with respect to loops and conditionals. New techniques are needed to address the path...increasing the code coverage. Each algorithm is tested over 66 of the GNU COREUTILS utilities. State merging combined with state pruning outperforms...30 3.6.1 GNU COREUTILS . . . . . . . . . . . . . . . . . . . . . . . . . . 30 3.7 Performance Metrics
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.
Light transport on path-space manifolds
NASA Astrophysics Data System (ADS)
Jakob, Wenzel Alban
The pervasive use of computer-generated graphics in our society has led to strict demands on their visual realism. Generally, users of rendering software want their images to look, in various ways, "real", which has been a key driving force towards methods that are based on the physics of light transport. Until recently, industrial practice has relied on a different set of methods that had comparatively little rigorous grounding in physics---but within the last decade, advances in rendering methods and computing power have come together to create a sudden and dramatic shift, in which physics-based methods that were formerly thought impractical have become the standard tool. As a consequence, considerable attention is now devoted towards making these methods as robust as possible. In this context, robustness refers to an algorithm's ability to process arbitrary input without large increases of the rendering time or degradation of the output image. One particularly challenging aspect of robustness entails simulating the precise interaction of light with all the materials that comprise the input scene. This dissertation focuses on one specific group of materials that has fundamentally been the most important source of difficulties in this process. Specular materials, such as glass windows, mirrors or smooth coatings (e.g. on finished wood), account for a significant percentage of the objects that surround us every day. It is perhaps surprising, then, that it is not well-understood how they can be accommodated within the theoretical framework that underlies some of the most sophisticated rendering methods available today. Many of these methods operate using a theoretical framework known as path space integration. But this framework makes no provisions for specular materials: to date, it is not clear how to write down a path space integral involving something as simple as a piece of glass. Although implementations can in practice still render these materials by side
NASA Technical Reports Server (NTRS)
Horton, Kent; Huffman, Mitch; Eppic, Brian; White, Harrison
2005-01-01
Path Loss Measurements were obtained on three (3) GPS equipped 757 aircraft. Systems measured were Marker Beacon, LOC, VOR, VHF (3), Glide Slope, ATC (2), DME (2), TCAS, and GPS. This data will provide the basis for assessing the EMI (Electromagnetic Interference) safety margins of comm/nav (communication and navigation) systems to portable electronic device emissions. These Portable Electronic Devices (PEDs) include all devices operated in or around the aircraft by crews, passengers, servicing personnel, as well as the general public in the airport terminals. EMI assessment capability is an important step in determining if one system-wide PED EMI policy is appropriate. This data may also be used comparatively with theoretical analysis and computer modeling data sponsored by NASA Langley Research Center and others.
Interactive cutting path analysis programs
NASA Technical Reports Server (NTRS)
Weiner, J. M.; Williams, D. S.; Colley, S. R.
1975-01-01
The operation of numerically controlled machine tools is interactively simulated. Four programs were developed to graphically display the cutting paths for a Monarch lathe, Cintimatic mill, Strippit sheet metal punch, and the wiring path for a Standard wire wrap machine. These programs are run on a IMLAC PDS-ID graphic display system under the DOS-3 disk operating system. The cutting path analysis programs accept input via both paper tape and disk file.
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.
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.
Critical Path-Based Thread Placement for NUMA Systems
Su, C Y; Li, D; Nikolopoulos, D S; Grove, M; Cameron, K; de Supinski, B R
2011-11-01
Multicore multiprocessors use a Non Uniform Memory Architecture (NUMA) to improve their scalability. However, NUMA introduces performance penalties due to remote memory accesses. Without efficiently managing data layout and thread mapping to cores, scientific applications, even if they are optimized for NUMA, may suffer performance loss. In this paper, we present algorithms and a runtime system that optimize the execution of OpenMP applications on NUMA architectures. By collecting information from hardware counters, the runtime system directs thread placement and reduces performance penalties by minimizing the critical path of OpenMP parallel regions. The runtime system uses a scalable algorithm that derives placement decisions with negligible overhead. We evaluate our algorithms and runtime system with four NPB applications implemented in OpenMP. On average the algorithms achieve between 8.13% and 25.68% performance improvement compared to the default Linux thread placement scheme. The algorithms miss the optimal thread placement in only 8.9% of the cases.
Computing Path Tables for Quickest Multipaths In Computer Networks
Grimmell, W.C.
2004-12-21
We consider the transmission of a message from a source node to a terminal node in a network with n nodes and m links where the message is divided into parts and each part is transmitted over a different path in a set of paths from the source node to the terminal node. Here each link is characterized by a bandwidth and delay. The set of paths together with their transmission rates used for the message is referred to as a multipath. We present two algorithms that produce a minimum-end-to-end message delay multipath path table that, for every message length, specifies a multipath that will achieve the minimum end-to-end delay. The algorithms also generate a function that maps the minimum end-to-end message delay to the message length. The time complexities of the algorithms are O(n{sup 2}((n{sup 2}/logn) + m)min(D{sub max}, C{sub max})) and O(nm(C{sub max} + nmin(D{sub max}, C{sub max}))) when the link delays and bandwidths are non-negative integers. Here D{sub max} and C{sub max} are respectively the maximum link delay and maximum link bandwidth and C{sub max} and D{sub max} are greater than zero.
Algorithms and architectures for high performance analysis of semantic graphs.
Hendrickson, Bruce Alan
2005-09-01
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.
Path Analysis: A Brief Introduction.
ERIC Educational Resources Information Center
Carducci, Bernardo J.
Path analysis is presented as a technique that can be used to test on a priori model based on a theoretical conceptualization involving a network of selected variables. This being an introductory source, no previous knowledge of path analysis is assumed, although some understanding of the fundamentals of multiple regression analysis might be…
Collabortive Authoring of Walden's Paths
Li, Yuanling; Bogen II, Paul Logasa; Pogue, Daniel; Furuta, Richard Keith; Shipman, Frank Major
2012-01-01
This paper presents a prototype of an authoring tool to allow users to collaboratively build, annotate, manage, share and reuse collections of distributed resources from the World Wide Web. This extends on the Walden’s Path project’s work to help educators bring resources found on the World Wide Web into a linear contextualized structure. The introduction of collaborative authoring feature fosters collaborative learning activities through social interaction among participants, where participants can coauthor paths in groups. Besides, the prototype supports path sharing, branching and reusing; specifically, individual participant can contribute to the group with private collections of knowledge resources; paths completed by group can be shared among group members, such that participants can tailor, extend, reorder and/or replace nodes to have sub versions of shared paths for different information needs.
NASA Technical Reports Server (NTRS)
Abrams, D.; Williams, C.
1999-01-01
This thesis describes several new quantum algorithms. These include a polynomial time algorithm that uses a quantum fast Fourier transform to find eigenvalues and eigenvectors of a Hamiltonian operator, and that can be applied in cases for which all know classical algorithms require exponential time.
The Edge-Disjoint Path Problem on Random Graphs by Message-Passing
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
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.
NASA Astrophysics Data System (ADS)
vanden-Eijnden, E.
The dynamical behavior of many systems arising in physics, chemistry, biology, etc. is dominated by rare but important transition events between long lived states. For over 70 years, transition state theory (TST) has provided the main theoretical framework for the description of these events [17,33,34]. Yet, while TST and evolutions thereof based on the reactive flux formalism [1, 5] (see also [30,31]) give an accurate estimate of the transition rate of a reaction, at least in principle, the theory tells very little in terms of the mechanism of this reaction. Recent advances, such as transition path sampling (TPS) of Bolhuis, Chandler, Dellago, and Geissler [3, 7] or the action method of Elber [15, 16], may seem to go beyond TST in that respect: these techniques allow indeed to sample the ensemble of reactive trajectories, i.e. the trajectories by which the reaction occurs. And yet, the reactive trajectories may again be rather uninformative about the mechanism of the reaction. This may sound paradoxical at first: what more than actual reactive trajectories could one need to understand a reaction? The problem, however, is that the reactive trajectories by themselves give only a very indirect information about the statistical properties of these trajectories. This is similar to why statistical mechanics is not simply a footnote in books about classical mechanics. What is the probability density that a trajectory be at a given location in state-space conditional on it being reactive? What is the probability current of these reactive trajectories? What is their rate of appearance? These are the questions of interest and they are not easy to answer directly from the ensemble of reactive trajectories. The right framework to tackle these questions also goes beyond standard equilibrium statistical mechanics because of the nontrivial bias that the very definition of the reactive trajectories imply - they must be involved in a reaction. The aim of this chapter is to
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.
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.
An Introduction to Path Analysis
ERIC Educational Resources Information Center
Wolfe, Lee M.
1977-01-01
The analytical procedure of path analysis is described in terms of its use in nonexperimental settings in the social sciences. The description assumes a moderate statistical background on the part of the reader. (JKS)
Scattering theory with path integrals
Rosenfelder, R.
2014-03-15
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.
The path integral picture of quantum systems
NASA Astrophysics Data System (ADS)
Ceperley, David
2011-03-01
The imaginary time path integral ``formalism'' was introduced in 1953 by Feynman to understand the superfluid transition in liquid helium. The equilibrium properties of quantum many body systems is isomorphic to the classical statistical mechanics of cross-linking polymer-like objects. With the Markov Chain Monte Carlo method, invented by Metropolis et al., also in 1953, a potential way of calculating properties of correlated quantum systems was in place. But calculations for many-body quantum systems did not become routine until computers and algorithms had become sufficiently powerful three decades later. Once such simulations could happen, it was realized that simulations provided a deeper insight into boson superfluids, in particular the relation of bose condensation to the polymer end-to-end distance, and the superfluid density to the polymer ``winding number.'' Some recent developments and applications to supersolids, and helium droplets will be given. Finally, limitations of the methodology e.g. to fermion systems are discussed.
Anisotropic path searching for automatic neuron reconstruction.
Xie, Jun; Zhao, Ting; Lee, Tzumin; Myers, Eugene; Peng, Hanchuan
2011-10-01
Full reconstruction of neuron morphology is of fundamental interest for the analysis and understanding of their functioning. We have developed a novel method capable of automatically tracing neurons in three-dimensional microscopy data. In contrast to template-based methods, the proposed approach makes no assumptions about the shape or appearance of neurite structure. Instead, an efficient seeding approach is applied to capture complex neuronal structures and the tracing problem is solved by computing the optimal reconstruction with a weighted graph. The optimality is determined by the cost function designed for the path between each pair of seeds and by topological constraints defining the component interrelations and completeness. In addition, an automated neuron comparison method is introduced for performance evaluation and structure analysis. The proposed algorithm is computationally efficient and has been validated using different types of microscopy data sets including Drosophila's projection neurons and fly neurons with presynaptic sites. In all cases, the approach yielded promising results.
Virtual Door-Based Coverage Path Planning for Mobile Robot
NASA Astrophysics Data System (ADS)
Myung, Hyun; Jeon, Hae-Min; Jeong, Woo-Yeon; Bang, Seok-Won
This paper presents a novel coverage path planning method in indoor environment for a mobile robot such as cleaning robot. Overall region is divided into several sub-regions based on the virtually extracted doors. The algorithm is inspired from the usual way of dividing an indoor environment into sub-regions, i.e., rooms based on the identification of doors. The virtual door algorithm extracts the virtual doors by combining a Generalized Voronoi Diagram (GVD) and a configuration space eroded by the half of the door size. The region to region cleaning algorithm is also proposed based on the closing and opening operations of virtual doors. The performance of the proposed algorithm has been tested on various real indoor environments using a commercially available cleaning robot.
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.
AAO Starbugs: software control and associated algorithms
NASA Astrophysics Data System (ADS)
Lorente, Nuria P. F.; Vuong, Minh V.; Shortridge, Keith; Farrell, Tony J.; Smedley, Scott; Hong, Sungwook E.; Bacigalupo, Carlos; Goodwin, Michael; Kuehn, Kyler; Satorre, Christophe
2016-08-01
The Australian Astronomical Observatory's TAIPAN instrument deploys 150 Starbug robots to position optical fibres to accuracies of 0.3 arcsec, on a 32 cm glass field plate on the focal plane of the 1.2 m UK-Schmidt telescope. This paper describes the software system developed to control and monitor the Starbugs, with particular emphasis on the automated path-finding algorithms, and the metrology software which keeps track of the position and motion of individual Starbugs as they independently move in a crowded field. The software employs a tiered approach to find a collision-free path for every Starbug, from its current position to its target location. This consists of three path-finding stages of increasing complexity and computational cost. For each Starbug a path is attempted using a simple method. If unsuccessful, subsequently more complex (and expensive) methods are tried until a valid path is found or the target is flagged as unreachable.
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.
Lung fissure detection in CT images using global minimal paths
NASA Astrophysics Data System (ADS)
Appia, Vikram; Patil, Uday; Das, Bipul
2010-03-01
Pulmonary fissures separate human lungs into five distinct regions called lobes. Detection of fissure is essential for localization of the lobar distribution of lung diseases, surgical planning and follow-up. Treatment planning also requires calculation of the lobe volume. This volume estimation mandates accurate segmentation of the fissures. Presence of other structures (like vessels) near the fissure, along with its high variational probability in terms of position, shape etc. makes the lobe segmentation a challenging task. Also, false incomplete fissures and occurrence of diseases add to the complications of fissure detection. In this paper, we propose a semi-automated fissure segmentation algorithm using a minimal path approach on CT images. An energy function is defined such that the path integral over the fissure is the global minimum. Based on a few user defined points on a single slice of the CT image, the proposed algorithm minimizes a 2D energy function on the sagital slice computed using (a) intensity (b) distance of the vasculature, (c) curvature in 2D, (d) continuity in 3D. The fissure is the infimum energy path between a representative point on the fissure and nearest lung boundary point in this energy domain. The algorithm has been tested on 10 CT volume datasets acquired from GE scanners at multiple clinical sites. The datasets span through different pathological conditions and varying imaging artifacts.
Linking snow avalanche path characteristics and simulation parameters
NASA Astrophysics Data System (ADS)
Kofler, Andreas; Fischer, Jan-Thomas; Tollinger, Christian; Granig, Matthias; Fellin, Wolfgang
2015-04-01
In this work an objective optimization algorithm is utilized to determine adjusted parameter distributions for avalanche simulation in 3d terrain. Multiple documented extreme avalanche events are investigated to emphasize similarities and differences between adjusted parameter distributions and the corresponding event. A probabilistic simulation setup, using a depth averaged flow model with a simple entrainment and the Voellmy friction law implemented in the SamosAT simulation software, is used to randomly vary the two friction (Coulomb friction, turbulent drag) and one entrainment parameter in their entire physically relevant range. The simulation results (peak pressures and flow depths) are analyzed in 3d terrain, performing a transformation in an avalanche path dependent coordinate system. The model parameters for entrainment and the Voellmy friction relation are systematically optimized, back calculating each documented event by introducing different optimization variables (runout, matched and exceeded affected area, maximum velocity, mass growth, etc.) and maximizing the degree of simulation-observation correspondence. This trial and error approach leads to distributions representing the optimal parameter settings. Different avalanche paths are characterized, distinguishing between avalanche size, total fall height, path shape and others. Statistical dependencies between those path characteristics and the optimal parameters are highlighted. We show that investigating dependencies between optimal parameter distributions and path characteristics is indispensable, when a systematic framework for simulation optimization is applied.
Quantum path analysis of high-order above-threshold ionization
NASA Astrophysics Data System (ADS)
Kopold, R.; Becker, W.; Kleber, M.
2000-05-01
High-order above-threshold ionization spectra are calculated via an improved Keldysh approximation that takes rescattering into account. An approximate method of evaluating the crucial multidimensional integral proceeds via the saddle point method. The saddle points define complex orbits in position space that depart from the ion and return to it to rescatter. The real parts of these orbits are very closely related to the trajectories of the simple-man model. The spectra are analyzed in terms of these quantum orbits whose constructive and destructive interferences generate the spectrum's intricate structures. In most spectral regions, the six trajectories having the shortest travel times between start and return already provide an excellent approximation to the exact calculation. In exceptional cases, more orbits are required. The quantum orbits provide an illuminating illustration of the quantum mechanical path integral.
Genetic algorithms for route discovery.
Gelenbe, Erol; Liu, Peixiang; Lainé, Jeremy
2006-12-01
Packet routing in networks requires knowledge about available paths, which can be either acquired dynamically while the traffic is being forwarded, or statically (in advance) based on prior information of a network's topology. This paper describes an experimental investigation of path discovery using genetic algorithms (GAs). We start with the quality-of-service (QoS)-driven routing protocol called "cognitive packet network" (CPN), which uses smart packets (SPs) to dynamically select routes in a distributed autonomic manner based on a user's QoS requirements. We extend it by introducing a GA at the source routers, which modifies and filters the paths discovered by the CPN. The GA can combine the paths that were previously discovered to create new untested but valid source-to-destination paths, which are then selected on the basis of their "fitness." We present an implementation of this approach, where the GA runs in background mode so as not to overload the ingress routers. Measurements conducted on a network test bed indicate that when the background-traffic load of the network is light to medium, the GA can result in improved QoS. When the background-traffic load is high, it appears that the use of the GA may be detrimental to the QoS experienced by users as compared to CPN routing because the GA uses less timely state information in its decision making.
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.
Mixed time slicing in path integral simulations
NASA Astrophysics Data System (ADS)
Steele, Ryan P.; Zwickl, Jill; Shushkov, Philip; Tully, John C.
2011-02-01
A simple and efficient scheme is presented for using different time slices for different degrees of freedom in path integral calculations. This method bridges the gap between full quantization and the standard mixed quantum-classical (MQC) scheme and, therefore, still provides quantum mechanical effects in the less-quantized variables. Underlying the algorithm is the notion that time slices (beads) may be "collapsed" in a manner that preserves quantization in the less quantum mechanical degrees of freedom. The method is shown to be analogous to multiple-time step integration techniques in classical molecular dynamics. The algorithm and its associated error are demonstrated on model systems containing coupled high- and low-frequency modes; results indicate that convergence of quantum mechanical observables can be achieved with disparate bead numbers in the different modes. Cost estimates indicate that this procedure, much like the MQC method, is most efficient for only a relatively few quantum mechanical degrees of freedom, such as proton transfer. In this regime, however, the cost of a fully quantum mechanical simulation is determined by the quantization of the least quantum mechanical degrees of freedom.
Two Paths Diverged: Exploring Trajectories, Protocols, and Dynamic Phases
NASA Astrophysics Data System (ADS)
Gingrich, Todd Robert
Using tools of statistical mechanics, it is routine to average over the distribution of microscopic configurations to obtain equilibrium free energies. These free energies teach us about the most likely molecular arrangements and the probability of observing deviations from the norm. Frequently, it is necessary to interrogate the probability not just of static arrangements, but of dynamical events, in which case analogous statistical mechanical tools may be applied to study the distribution of molecular trajectories. Numerical study of these trajectory spaces requires algorithms which efficiently sample the possible trajectories. We study in detail one such Monte Carlo algorithm, transition path sampling, and use a non- equilibrium statistical mechanical perspective to illuminate why the algorithm cannot easily be adapted to study some problems involving long-timescale dynamics. Algorithmically generating highly-correlated trajectories, a necessity for transition path sampling, grows exponentially more challenging for longer trajectories unless the dynamics is strongly-guided by the "noise history", the sequence of random numbers representing the noise terms in the stochastic dynamics. Langevin dynamics of Weeks-Chandler-Andersen (WCA) particles in two dimensions lacks this strong noise guidance, so it is challenging to use transition path sampling to study rare dynamical events in long trajectories of WCA particles. The spin flip dynamics of a two-dimensional Ising model, on the other hand, can be guided by the noise history to achieve efficient path sampling. For systems that can be efficiently sampled with path sampling, we show that it is possible to simultaneously sample both the paths and the (potentially vast) space of non-equilibrium protocols to efficiently learn how rate constants vary with protocols and to identify low-dissipation protocols. When high-dimensional molecular dynamics can be coarse-grained and represented by a simplified dynamics on a low
Wiener, J M; Ehbauer, N N; Mallot, H A
2009-09-01
For large numbers of targets, path planning is a complex and computationally expensive task. Humans, however, usually solve such tasks quickly and efficiently. We present experiments studying human path planning performance and the cognitive processes and heuristics involved. Twenty-five places were arranged on a regular grid in a large room. Participants were repeatedly asked to solve traveling salesman problems (TSP), i.e., to find the shortest closed loop connecting a start location with multiple target locations. In Experiment 1, we tested whether humans employed the nearest neighbor (NN) strategy when solving the TSP. Results showed that subjects outperform the NN-strategy, suggesting that it is not sufficient to explain human route planning behavior. As a second possible strategy we tested a hierarchical planning heuristic in Experiment 2, demonstrating that participants first plan a coarse route on the region level that is refined during navigation. To test for the relevance of spatial working memory (SWM) and spatial long-term memory (LTM) for planning performance and the planning heuristics applied, we varied the memory demands between conditions in Experiment 2. In one condition the target locations were directly marked, such that no memory was required; a second condition required participants to memorize the target locations during path planning (SWM); in a third condition, additionally, the locations of targets had to retrieved from LTM (SWM and LTM). Results showed that navigation performance decreased with increasing memory demands while the dependence on the hierarchical planning heuristic increased.
NASA Technical Reports Server (NTRS)
Zuk, J.
1976-01-01
Improved gas-path seals are needed for better fuel economy, longer performance retention, and lower maintenance, particularly in advanced, high-performance gas turbine engines. Problems encountered in gas-path sealing are described, as well as new blade-tip sealing approaches for high-pressure compressors and turbines. These include a lubricant coating for conventional, porous-metal, rub-strip materials used in compressors. An improved hot-press metal alloy shows promise to increase the operating surface temperatures of high-pressure-turbine, blade-tip seals to 1450 K (2150 F). Three ceramic seal materials are also described that have the potential to allow much higher gas-path surface operating temperatures than are possible with metal systems.
Innovative development path of ethnomedicines: the interpretation of the path.
Zhu, Zhaoyun; Fu, Dehuan; Gui, Yali; Cui, Tao; Wang, Jingkun; Wang, Ting; Yang, Zhizhong; Niu, Yanfei; She, Zhennan; Wang, Li
2017-03-01
One of the primary purposes of the innovative development of ethnomedicines is to use their excellent safety and significant efficacy to serve a broader population. To achieve this purpose, modern scientific and technological means should be referenced, and relevant national laws and regulations as well as technical guides should be strictly followed to develop standards and to perform systemic research in producing ethnomedicines. Finally, ethnomedicines, which are applied to a limited extent in ethnic areas, can be transformed into safe, effective, and quality-controllable medical products to relieve the pain of more patients. The innovative development path of ethnomedicines includes the following three primary stages: resource study, standardized development research, and industrialization of the achievements and efforts for internationalization. The implementation of this path is always guaranteed by the research and development platform and the talent team. This article is based on the accumulation of long-term practice and is combined with the relevant disciplines, laws and regulations, and technical guidance from the research and development of ethnomedicines. The intention is to perform an in-depth analysis and explanation of the major research thinking, methods, contents, and technical paths involved in all stages of the innovative development path of ethnomedicines to provide useful references for the development of proper ethnomedicine use.
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
Speckle Imaging Over Horizontal Paths
Carrano, C J
2002-05-21
Atmospheric aberrations reduce the resolution and contrast in surveillance images recorded over horizontal or slant paths. This paper describes our recent horizontal and slant path imaging experiments of extended scenes as well as the results obtained using speckle imaging. The experiments were performed with an 8-inch diameter telescope placed on either a rooftop or hillside and cover ranges of interest from 0.5 km up to 10 km. The scenery includes resolution targets, people, vehicles, and other structures. The improvement in image quality using speckle imaging is dramatic in many cases, and depends significantly upon the atmospheric conditions. We quantify resolution improvement through modulation transfer function measurement comparisons.
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.
Improved transition path sampling methods for simulation of rare events.
Chopra, Manan; Malshe, Rohit; Reddy, Allam S; de Pablo, J J
2008-04-14
The free energy surfaces of a wide variety of systems encountered in physics, chemistry, and biology are characterized by the existence of deep minima separated by numerous barriers. One of the central aims of recent research in computational chemistry and physics has been to determine how transitions occur between deep local minima on rugged free energy landscapes, and transition path sampling (TPS) Monte-Carlo methods have emerged as an effective means for numerical investigation of such transitions. Many of the shortcomings of TPS-like approaches generally stem from their high computational demands. Two new algorithms are presented in this work that improve the efficiency of TPS simulations. The first algorithm uses biased shooting moves to render the sampling of reactive trajectories more efficient. The second algorithm is shown to substantially improve the accuracy of the transition state ensemble by introducing a subset of local transition path simulations in the transition state. The system considered in this work consists of a two-dimensional rough energy surface that is representative of numerous systems encountered in applications. When taken together, these algorithms provide gains in efficiency of over two orders of magnitude when compared to traditional TPS simulations.
NASA Astrophysics Data System (ADS)
Wolfe, William J.; Wood, David; Sorensen, Stephen E.
1996-12-01
This paper discusses automated scheduling as it applies to complex domains such as factories, transportation, and communications systems. The window-constrained-packing problem is introduced as an ideal model of the scheduling trade offs. Specific algorithms are compared in terms of simplicity, speed, and accuracy. In particular, dispatch, look-ahead, and genetic algorithms are statistically compared on randomly generated job sets. The conclusion is that dispatch methods are fast and fairly accurate; while modern algorithms, such as genetic and simulate annealing, have excessive run times, and are too complex to be practical.
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.
Learning-based Nonlinear Model Predictive Control to Improve Vision-based Mobile Robot Path Tracking
2015-07-01
feedback control to generate desired lateral and angular velocities to compensate for vehicle slip rates. Finally, they use the robot’s inverse dynamics to...Learning-based Nonlinear Model Predictive Control to Improve Vision-based Mobile Robot Path Tracking Chris J. Ostafew Institute for Aerospace Studies...paper presents a Learning-based Nonlinear Model Predictive Control (LB-NMPC) algorithm to achieve high-performance path tracking in challenging off-road
NASA Astrophysics Data System (ADS)
Naruse, Fumisato; Yamada, Yoshiyuki; Hasegawa, Hiroshi; Sato, Ken-Ichi
This paper presents a novel “virtual fiber” network service that exploits wavebands. This service provides virtual direct tunnels that directly convey wavelength paths to connect customer facilities. To improve the resource utilization efficiency of the service, a network design algorithm is developed that can allow intermediate path grooming at limited nodes and can determine the best node location. Numerical experiments demonstrate the effectiveness of the proposed service architecture.
A variational path integral molecular dynamics study of a solid helium-4
NASA Astrophysics Data System (ADS)
Miura, Shinichi
2011-01-01
In the present study, a variational path integral molecular dynamics method developed by the author [Chem. Phys. Lett. 482 (2009) 165] is applied to a solid helium-4 in the ground state. The method is a molecular dynamics algorithm for a variational path integral method which can be used to generate the exact ground state numerically. The solid state is shown to successfully be realized by the method, although a poor trial wavefunction that cannot describe the solid state is used.
2017-01-01
The aim of this paper is to propose a new method to identify main paths in a technological domain using patent citations. Previous approaches for using main path analysis have greatly improved our understanding of actual technological trajectories but nonetheless have some limitations. They have high potential to miss some dominant patents from the identified main paths; nonetheless, the high network complexity of their main paths makes qualitative tracing of trajectories problematic. The proposed method searches backward and forward paths from the high-persistence patents which are identified based on a standard genetic knowledge persistence algorithm. We tested the new method by applying it to the desalination and the solar photovoltaic domains and compared the results to output from the same domains using a prior method. The empirical results show that the proposed method can dramatically reduce network complexity without missing any dominantly important patents. The main paths identified by our approach for two test cases are almost 10x less complex than the main paths identified by the existing approach. The proposed approach identifies all dominantly important patents on the main paths, but the main paths identified by the existing approach miss about 20% of dominantly important patents. PMID:28135304
Park, Hyunseok; Magee, Christopher L
2017-01-01
The aim of this paper is to propose a new method to identify main paths in a technological domain using patent citations. Previous approaches for using main path analysis have greatly improved our understanding of actual technological trajectories but nonetheless have some limitations. They have high potential to miss some dominant patents from the identified main paths; nonetheless, the high network complexity of their main paths makes qualitative tracing of trajectories problematic. The proposed method searches backward and forward paths from the high-persistence patents which are identified based on a standard genetic knowledge persistence algorithm. We tested the new method by applying it to the desalination and the solar photovoltaic domains and compared the results to output from the same domains using a prior method. The empirical results show that the proposed method can dramatically reduce network complexity without missing any dominantly important patents. The main paths identified by our approach for two test cases are almost 10x less complex than the main paths identified by the existing approach. The proposed approach identifies all dominantly important patents on the main paths, but the main paths identified by the existing approach miss about 20% of dominantly important patents.
Finding the complete path and weight enumerators of convolutional codes
NASA Technical Reports Server (NTRS)
Onyszchuk, I.
1990-01-01
A method for obtaining the complete path enumerator T(D, L, I) of a convolutional code is described. A system of algebraic equations is solved, using a new algorithm for computing determinants, to obtain T(D, L, I) for the (7,1/2) NASA standard code. Generating functions, derived from T(D, L, I) are used to upper bound Viterbi decoder error rates. This technique is currently feasible for constraint length K less than 10 codes. A practical, fast algorithm is presented for computing the leading nonzero coefficients of the generating functions used to bound the performance of constraint length K less than 20 codes. Code profiles with about 50 nonzero coefficients are obtained with this algorithm for the experimental K = 15, rate 1/4, code in the Galileo mission and for the proposed K = 15, rate 1/6, 2-dB code.
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...
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.
Career Path of School Superintendents.
ERIC Educational Resources Information Center
Mertz, Norma T.; McNeely, Sonja R.
This study of the career paths of 147 Tennessee school superintendents sought to determine to what extent coaching and principalships are routes to that office. The majority of respondents were white males; only one was black, and 10 were female. The data were analyzed by group, race, sex, years in office, and method of selection (elected or…
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…
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…
Path statistics, memory, and coarse-graining of continuous-time random walks on networks.
Manhart, Michael; Kion-Crosby, Willow; Morozov, Alexandre V
2015-12-07
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.
Path statistics, memory, and coarse-graining of continuous-time random walks on networks
Kion-Crosby, Willow; Morozov, Alexandre V.
2015-01-01
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
Path Searching Based Fault Automated Recovery Scheme for Distribution Grid with DG
NASA Astrophysics Data System (ADS)
Xia, Lin; Qun, Wang; Hui, Xue; Simeng, Zhu
2016-12-01
Applying the method of path searching based on distribution network topology in setting software has a good effect, and the path searching method containing DG power source is also applicable to the automatic generation and division of planned islands after the fault. This paper applies path searching algorithm in the automatic division of planned islands after faults: starting from the switch of fault isolation, ending in each power source, and according to the line load that the searching path traverses and the load integrated by important optimized searching path, forming optimized division scheme of planned islands that uses each DG as power source and is balanced to local important load. Finally, COBASE software and distribution network automation software applied are used to illustrate the effectiveness of the realization of such automatic restoration program.
A novel communication mechanism based on node potential multi-path routing
NASA Astrophysics Data System (ADS)
Bu, Youjun; Zhang, Chuanhao; Jiang, YiMing; Zhang, Zhen
2016-10-01
With the network scales rapidly and new network applications emerge frequently, bandwidth supply for today's Internet could not catch up with the rapid increasing requirements. Unfortunately, irrational using of network sources makes things worse. Actual network deploys single-next-hop optimization paths for data transmission, but such "best effort" model leads to the imbalance use of network resources and usually leads to local congestion. On the other hand Multi-path routing can use the aggregation bandwidth of multi paths efficiently and improve the robustness of network, security, load balancing and quality of service. As a result, multi-path has attracted much attention in the routing and switching research fields and many important ideas and solutions have been proposed. This paper focuses on implementing the parallel transmission of multi next-hop data, balancing the network traffic and reducing the congestion. It aimed at exploring the key technologies of the multi-path communication network, which could provide a feasible academic support for subsequent applications of multi-path communication networking. It proposed a novel multi-path algorithm based on node potential in the network. And the algorithm can fully use of the network link resource and effectively balance network link resource utilization.
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.
Human-machine teaming for effective estimation and path planning
NASA Astrophysics Data System (ADS)
McCourt, Michael J.; Mehta, Siddhartha S.; Doucette, Emily A.; Curtis, J. Willard
2016-05-01
While traditional sensors provide accurate measurements of quantifiable information, humans provide better qualitative information and holistic assessments. Sensor fusion approaches that team humans and machines can take advantage of the benefits provided by each while mitigating the shortcomings. These two sensor sources can be fused together using Bayesian fusion, which assumes that there is a method of generating a probabilistic representation of the sensor measurement. This general framework of fusing estimates can also be applied to joint human-machine decision making. In the simple case, binary decisions can be fused by using a probability of taking an action versus inaction from each decision-making source. These are fused together to arrive at a final probability of taking an action, which would be taken if above a specified threshold. In the case of path planning, rather than binary decisions being fused, complex decisions can be fused by allowing the human and machine to interact with each other. For example, the human can draw a suggested path while the machine planning algorithm can refine it to avoid obstacles and remain dynamically feasible. Similarly, the human can revise a suggested path to achieve secondary goals not encoded in the algorithm such as avoiding dangerous areas in the environment.
Aircraft flight path angle display system
NASA Technical Reports Server (NTRS)
Lambregts, Antonius A. (Inventor)
1991-01-01
A display system for use in an aircraft control wheel steering system provides the pilot with a single, quickened flight path angle display to overcome poor handling qualities due to intrinsic flight path angle response lags, while avoiding multiple information display symbology. The control law for the flight path angle control system is designed such that the aircraft's actual flight path angle response lags the pilot's commanded flight path angle by a constant time lag .tau., independent of flight conditions. The synthesized display signal is produced as a predetermined function of the aircraft's actual flight path angle, the time lag .tau. and command inputs from the pilot's column.
Ronacher, B; Westwig, E; Wehner, R
2006-09-01
When performing foraging trips desert ants of the genus Cataglyphis continuously process and update a ;home vector' that enables them to return to their nest on the shortest route. This capacity of path integration requires two types of information: (i) information about the travelling directions, and (ii) odometric information about the distances travelled in a particular direction. We have investigated how these two necessary pieces of information interact within the path integration processor. The specific question is: how do the ants process distance information if there is no simultaneous input from the sky compass available. Ants were trained to forage in a ;Z'-shaped channel system, the three segments of which joined at right angles. Individual animals were transferred from the feeder to a test field where their homing paths could be observed. In the crucial tests the middle segment of the maze was covered by orange Perspex that did not transmit the UV part of the spectrum, and thus precluded the perception of polarization patterns. Changes of the ant's processing of odometric information within this channel segment directly translate into a change in homing direction on the test field. The results indicate that the odometric information about travelling distance is largely ignored for path integration if there is no simultaneous input from the sky-view-based compass. They further show that idiothetic information cannot adequately substitute for the polarization compass to infer travelling directions.
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..
Quantum hyperparallel algorithm for matrix multiplication.
Zhang, Xin-Ding; Zhang, Xiao-Ming; Xue, Zheng-Yuan
2016-04-29
Hyperentangled states, entangled states with more than one degree of freedom, are considered as promising resource in quantum computation. Here we present a hyperparallel quantum algorithm for matrix multiplication with time complexity O(N(2)), which is better than the best known classical algorithm. In our scheme, an N dimensional vector is mapped to the state of a single source, which is separated to N paths. With the assistance of hyperentangled states, the inner product of two vectors can be calculated with a time complexity independent of dimension N. Our algorithm shows that hyperparallel quantum computation may provide a useful tool in quantum machine learning and "big data" analysis.
Quantum hyperparallel algorithm for matrix multiplication
NASA Astrophysics Data System (ADS)
Zhang, Xin-Ding; Zhang, Xiao-Ming; Xue, Zheng-Yuan
2016-04-01
Hyperentangled states, entangled states with more than one degree of freedom, are considered as promising resource in quantum computation. Here we present a hyperparallel quantum algorithm for matrix multiplication with time complexity O(N2), which is better than the best known classical algorithm. In our scheme, an N dimensional vector is mapped to the state of a single source, which is separated to N paths. With the assistance of hyperentangled states, the inner product of two vectors can be calculated with a time complexity independent of dimension N. Our algorithm shows that hyperparallel quantum computation may provide a useful tool in quantum machine learning and “big data” analysis.
Estimating surface flow paths on a digital elevation model using a triangular facet network
NASA Astrophysics Data System (ADS)
Zhou, Qiming; Pilesjö, Petter; Chen, Yumin
2011-07-01
This study attempts to develop a method for the simulation of surface flow paths on a digital elevation model (DEM). The objective is to use a facet-based algorithm to estimate the surface flow paths on a raster DEM. A grid DEM was used to create a triangular facet network (TFN) over which the surface flow paths were determined. Since each facet in the network has a constant slope and aspect, the estimations of, for example, flow direction and divergence/convergence are less complicated compared to traditional raster-based solutions. Experiments were undertaken by estimating the specific catchment area (SCA) over a number of mathematical surfaces, as well as on a real-world DEM. Comparisons were made between the derived SCA by the TFN algorithm with some algorithms reported in the literature. The results show that the TFN algorithm produced the closest outcomes to the theoretical values of the SCA compared with other algorithms, deriving more consistent outcomes and being less influenced by surface shapes. The real-world DEM test also shows that the TFN was capable of modeling flow distribution without noticeable "artifacts," and its ability of tracking flow paths makes it an appropriate platform for dynamic surface flow simulation.
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.
Accelerating cleanup: Paths to closure
Edwards, C.
1998-06-30
This document was previously referred to as the Draft 2006 Plan. As part of the DOE`s national strategy, the Richland Operations Office`s Paths to Closure summarizes an integrated path forward for environmental cleanup at the Hanford Site. The Hanford Site underwent a concerted effort between 1994 and 1996 to accelerate the cleanup of the Site. These efforts are reflected in the current Site Baseline. This document describes the current Site Baseline and suggests strategies for further improvements in scope, schedule and cost. The Environmental Management program decided to change the name of the draft strategy and the document describing it in response to a series of stakeholder concerns, including the practicality of achieving widespread cleanup by 2006. Also, EM was concerned that calling the document a plan could be misconstrued to be a proposal by DOE or a decision-making document. The change in name, however, does not diminish the 2006 vision. To that end, Paths to Closure retains a focus on 2006, which serves as a point in time around which objectives and goals are established.
WDM Multicast Tree Construction Algorithms and Their Comparative Evaluations
NASA Astrophysics Data System (ADS)
Makabe, Tsutomu; Mikoshi, Taiju; Takenaka, Toyofumi
We propose novel tree construction algorithms for multicast communication in photonic networks. Since multicast communications consume many more link resources than unicast communications, effective algorithms for route selection and wavelength assignment are required. We propose a novel tree construction algorithm, called the Weighted Steiner Tree (WST) algorithm and a variation of the WST algorithm, called the Composite Weighted Steiner Tree (CWST) algorithm. Because these algorithms are based on the Steiner Tree algorithm, link resources among source and destination pairs tend to be commonly used and link utilization ratios are improved. Because of this, these algorithms can accept many more multicast requests than other multicast tree construction algorithms based on the Dijkstra algorithm. However, under certain delay constraints, the blocking characteristics of the proposed Weighted Steiner Tree algorithm deteriorate since some light paths between source and destinations use many hops and cannot satisfy the delay constraint. In order to adapt the approach to the delay-sensitive environments, we have devised the Composite Weighted Steiner Tree algorithm comprising the Weighted Steiner Tree algorithm and the Dijkstra algorithm for use in a delay constrained environment such as an IPTV application. In this paper, we also give the results of simulation experiments which demonstrate the superiority of the proposed Composite Weighted Steiner Tree algorithm compared with the Distributed Minimum Hop Tree (DMHT) algorithm, from the viewpoint of the light-tree request blocking.
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.
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.
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.
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.
Path-Based Supports for Hypergraphs
NASA Astrophysics Data System (ADS)
Brandes, Ulrik; Cornelsen, Sabine; Pampel, Barbara; Sallaberry, Arnaud
A path-based support of a hypergraph H is a graph with the same vertex set as H in which each hyperedge induces a Hamiltonian subgraph. While it is NP-complete to compute a path-based support with the minimum number of edges or to decide whether there is a planar path-based support, we show that a path-based tree support can be computed in polynomial time if it exists.
NASA Technical Reports Server (NTRS)
Barth, Timothy J.; Lomax, Harvard
1987-01-01
The past decade has seen considerable activity in algorithm development for the Navier-Stokes equations. This has resulted in a wide variety of useful new techniques. Some examples for the numerical solution of the Navier-Stokes equations are presented, divided into two parts. One is devoted to the incompressible Navier-Stokes equations, and the other to the compressible form.
Schulz, Andreas S.; Shmoys, David B.; Williamson, David P.
1997-01-01
Increasing global competition, rapidly changing markets, and greater consumer awareness have altered the way in which corporations do business. To become more efficient, many industries have sought to model some operational aspects by gigantic optimization problems. It is not atypical to encounter models that capture 106 separate “yes” or “no” decisions to be made. Although one could, in principle, try all 2106 possible solutions to find the optimal one, such a method would be impractically slow. Unfortunately, for most of these models, no algorithms are known that find optimal solutions with reasonable computation times. Typically, industry must rely on solutions of unguaranteed quality that are constructed in an ad hoc manner. Fortunately, for some of these models there are good approximation algorithms: algorithms that produce solutions quickly that are provably close to optimal. Over the past 6 years, there has been a sequence of major breakthroughs in our understanding of the design of approximation algorithms and of limits to obtaining such performance guarantees; this area has been one of the most flourishing areas of discrete mathematics and theoretical computer science. PMID:9370525
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,…
Adaptive PSO using random inertia weight and its application in UAV path planning
NASA Astrophysics Data System (ADS)
Zhu, Hongguo; Zheng, Changwen; Hu, Xiaohui; Li, Xiang
2008-10-01
A novel particle swarm optimization algorithm, called APSO_RW is presented. Random inertia weight improves its global optimization performance and an adaptive reinitialize mechanism is used when the global best particle is detected to be trapped. The new algorithm is tested on a set of benchmark functions and experimental results show its efficiency. APSO_RW is later applied in UAV (Unmanned Aerial Vehicle) path planning.
Path Relaxation: Path Planning for a Mobile Robot.
1984-04-01
15213 April 1984 JUN 5 1984 Copyright © 1984 Mobile Robot Laboratory, Carnegie-Mellon University The CMU Rover has been supported at the Carnegie-Mellon...particular robot or mission. Path Relaxation is part of Fido, the vision and navigation system of the CM L Rover mol)ile robot. [29, 411 The Rover , under...their 31) positions relative to the Rover . The Rover will then move about half a meter, take a new pair of pictires, find the 40 tracked points in each of
Interactive multi-objective path planning through a palette-based user interface
NASA Astrophysics Data System (ADS)
Shaikh, Meher T.; Goodrich, Michael A.; Yi, Daqing; Hoehne, Joseph
2016-05-01
n a problem where a human uses supervisory control to manage robot path-planning, there are times when human does the path planning, and if satisfied commits those paths to be executed by the robot, and the robot executes that plan. In planning a path, the robot often uses an optimization algorithm that maximizes or minimizes an objective. When a human is assigned the task of path planning for robot, the human may care about multiple objectives. This work proposes a graphical user interface (GUI) designed for interactive robot path-planning when an operator may prefer one objective over others or care about how multiple objectives are traded off. The GUI represents multiple objectives using the metaphor of an artist's palette. A distinct color is used to represent each objective, and tradeoffs among objectives are balanced in a manner that an artist mixes colors to get the desired shade of color. Thus, human intent is analogous to the artist's shade of color. We call the GUI an "Adverb Palette" where the word "Adverb" represents a specific type of objective for the path, such as the adverbs "quickly" and "safely" in the commands: "travel the path quickly", "make the journey safely". The novel interactive interface provides the user an opportunity to evaluate various alternatives (that tradeoff between different objectives) by allowing her to visualize the instantaneous outcomes that result from her actions on the interface. In addition to assisting analysis of various solutions given by an optimization algorithm, the palette has additional feature of allowing the user to define and visualize her own paths, by means of waypoints (guiding locations) thereby spanning variety for planning. The goal of the Adverb Palette is thus to provide a way for the user and robot to find an acceptable solution even though they use very different representations of the problem. Subjective evaluations suggest that even non-experts in robotics can carry out the planning tasks with a
Pérez, Alejandro; Tuckerman, Mark E
2011-08-14
Higher order factorization schemes are developed for path integral molecular dynamics in order to improve the convergence of estimators for physical observables as a function of the Trotter number. The methods are based on the Takahashi-Imada and Susuki decompositions of the Boltzmann operator. The methods introduced improve the averages of the estimators by using the classical forces needed to carry out the dynamics to construct a posteriori weighting factors for standard path integral molecular dynamics. The new approaches are straightforward to implement in existing path integral codes and carry no significant overhead. The Suzuki higher order factorization was also used to improve the end-to-end distance estimator in open path integral molecular dynamics. The new schemes are tested in various model systems, including an ab initio path integral molecular dynamics calculation on the hydrogen molecule and a quantum water model. The proposed algorithms have potential utility for reducing the cost of path integral molecular dynamics calculations of bulk systems.
NASA Astrophysics Data System (ADS)
Pérez, Alejandro; Tuckerman, Mark E.
2011-08-01
Higher order factorization schemes are developed for path integral molecular dynamics in order to improve the convergence of estimators for physical observables as a function of the Trotter number. The methods are based on the Takahashi-Imada and Susuki decompositions of the Boltzmann operator. The methods introduced improve the averages of the estimators by using the classical forces needed to carry out the dynamics to construct a posteriori weighting factors for standard path integral molecular dynamics. The new approaches are straightforward to implement in existing path integral codes and carry no significant overhead. The Suzuki higher order factorization was also used to improve the end-to-end distance estimator in open path integral molecular dynamics. The new schemes are tested in various model systems, including an ab initio path integral molecular dynamics calculation on the hydrogen molecule and a quantum water model. The proposed algorithms have potential utility for reducing the cost of path integral molecular dynamics calculations of bulk systems.
A Comparison of Hybrid Approaches for Turbofan Engine Gas Path Fault Diagnosis
NASA Astrophysics Data System (ADS)
Lu, Feng; Wang, Yafan; Huang, Jinquan; Wang, Qihang
2016-09-01
A hybrid diagnostic method utilizing Extended Kalman Filter (EKF) and Adaptive Genetic Algorithm (AGA) is presented for performance degradation estimation and sensor anomaly detection of turbofan engine. The EKF is used to estimate engine component performance degradation for gas path fault diagnosis. The AGA is introduced in the integrated architecture and applied for sensor bias detection. The contributions of this work are the comparisons of Kalman Filters (KF)-AGA algorithms and Neural Networks (NN)-AGA algorithms with a unified framework for gas path fault diagnosis. The NN needs to be trained off-line with a large number of prior fault mode data. When new fault mode occurs, estimation accuracy by the NN evidently decreases. However, the application of the Linearized Kalman Filter (LKF) and EKF will not be restricted in such case. The crossover factor and the mutation factor are adapted to the fitness function at each generation in the AGA, and it consumes less time to search for the optimal sensor bias value compared to the Genetic Algorithm (GA). In a word, we conclude that the hybrid EKF-AGA algorithm is the best choice for gas path fault diagnosis of turbofan engine among the algorithms discussed.
Experimental and analytical study of secondary path variations in active engine mounts
NASA Astrophysics Data System (ADS)
Hausberg, Fabian; Scheiblegger, Christian; Pfeffer, Peter; Plöchl, Manfred; Hecker, Simon; Rupp, Markus
2015-03-01
Active engine mounts (AEMs) provide an effective solution to further improve the acoustic and vibrational comfort of passenger cars. Typically, adaptive feedforward control algorithms, e.g., the filtered-x-least-mean-squares (FxLMS) algorithm, are applied to cancel disturbing engine vibrations. These algorithms require an accurate estimate of the AEM active dynamic characteristics, also known as the secondary path, in order to guarantee control performance and stability. This paper focuses on the experimental and theoretical study of secondary path variations in AEMs. The impact of three major influences, namely nonlinearity, change of preload and component temperature, on the AEM active dynamic characteristics is experimentally analyzed. The obtained test results are theoretically investigated with a linear AEM model which incorporates an appropriate description for elastomeric components. A special experimental set-up extends the model validation of the active dynamic characteristics to higher frequencies up to 400 Hz. The theoretical and experimental results show that significant secondary path variations are merely observed in the frequency range of the AEM actuator's resonance frequency. These variations mainly result from the change of the component temperature. As the stability of the algorithm is primarily affected by the actuator's resonance frequency, the findings of this paper facilitate the design of AEMs with simpler adaptive feedforward algorithms. From a practical point of view it may further be concluded that algorithmic countermeasures against instability are only necessary in the frequency range of the AEM actuator's resonance frequency.
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.
Completely automated open-path FT-IR spectrometry.
Griffiths, Peter R; Shao, Limin; Leytem, April B
2009-01-01
Atmospheric analysis by open-path Fourier-transform infrared (OP/FT-IR) spectrometry has been possible for over two decades but has not been widely used because of the limitations of the software of commercial instruments. In this paper, we describe the current state-of-the-art of the hardware and software that constitutes a contemporary OP/FT-IR spectrometer. We then describe advances that have been made in our laboratory that have enabled many of the limitations of this type of instrument to be overcome. These include not having to acquire a single-beam background spectrum that compensates for absorption features in the spectra of atmospheric water vapor and carbon dioxide. Instead, an easily measured "short path-length" background spectrum is used for calculation of each absorbance spectrum that is measured over a long path-length. To accomplish this goal, the algorithm used to calculate the concentrations of trace atmospheric molecules was changed from classical least-squares regression (CLS) to partial least-squares regression (PLS). For calibration, OP/FT-IR spectra are measured in pristine air over a wide variety of path-lengths, temperatures, and humidities, ratioed against a short-path background, and converted to absorbance; the reference spectrum of each analyte is then multiplied by randomly selected coefficients and added to these background spectra. Automatic baseline correction for small molecules with resolved rotational fine structure, such as ammonia and methane, is effected using wavelet transforms. A novel method of correcting for the effect of the nonlinear response of mercury cadmium telluride detectors is also incorporated. Finally, target factor analysis may be used to detect the onset of a given pollutant when its concentration exceeds a certain threshold. In this way, the concentration of atmospheric species has been obtained from OP/FT-IR spectra measured at intervals of 1 min over a period of many hours with no operator intervention.
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
Common-path digital holographic microscopy and its applications
NASA Astrophysics Data System (ADS)
Zhao, Jianlin; Di, Jianglei; Zhang, Jiwei; Ma, Chaojie
2016-10-01
To significantly increase the stability of the digital holographic microscope, some common-path configurations with a piece of glass plate, Lloyd mirror and lensless structure are introduced in digital holographic microscopy to make up several compact experiment systems. Meanwhile, dual-wavelength technique and some numerical algorithms are also employed to improve the measurement accuracy. As examples, we apply these configurations to measure a mouse osteoblastic cell, laser ablated pit specimen and silicon wafer. The experiment results show the feasibility of the proposed configurations.
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.
Optical path control in the MAM testbed
NASA Technical Reports Server (NTRS)
Regehr, M. W.; Hines, B.; Holmes, B.
2003-01-01
Future space-based optical interferometers will require control of the optical path delay to accomplish some or all of the three objectives: balancing the optical path in the two arms to within a tolerance corresponding to the coherence length of the star light being observed, modulating the optical path in order to observe the phase of the star light interference fringe, and modulating the path length in order to reduce the effect of cyclic errors in the laser metrology system used to measure the optical path length in the two arms of the interferometer.
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
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.
Architecture and design of optical path networks utilizing waveband virtual links
NASA Astrophysics Data System (ADS)
Ito, Yusaku; Mori, Yojiro; Hasegawa, Hiroshi; Sato, Ken-ichi
2016-02-01
We propose a novel optical network architecture that uses waveband virtual links, each of which can carry several optical paths, to directly bridge distant node pairs. Future photonic networks should not only transparently cover extended areas but also expand fiber capacity. However, the traversal of many ROADM nodes impairs the optical signal due to spectrum narrowing. To suppress the degradation, the bandwidth of guard bands needs to be increased, which degrades fiber frequency utilization. Waveband granular switching allows us to apply broader pass-band filtering at ROADMs and to insert sufficient guard bands between wavebands with minimum frequency utilization offset. The scheme resolves the severe spectrum narrowing effect. Moreover, the guard band between optical channels in a waveband can be minimized, which increases the number of paths that can be accommodated per fiber. In the network, wavelength path granular routing is done without utilizing waveband virtual links, and it still suffers from spectrum narrowing. A novel network design algorithm that can bound the spectrum narrowing effect by limiting the number of hops (traversed nodes that need wavelength path level routing) is proposed in this paper. This algorithm dynamically changes the waveband virtual link configuration according to the traffic distribution variation, where optical paths that need many node hops are effectively carried by virtual links. Numerical experiments demonstrate that the number of necessary fibers is reduced by 23% compared with conventional optical path networks.
Gotoh, E; Tanno, Y
2005-05-01
The aim was to develop a simple biodosimetry method for as rapid as possible estimation of absorbed radiation doses in victims of radiation accidents, in particular after high-dose exposure. Human peripheral blood lymphocytes (PBL) were gamma-irradiated in vitro with several doses up to 40 Gy stimulated with phytohaemagglutinin-P (PHA-P) for 2 days and their chromosomes condensed prematurely using 50 nm calyculin A. Chromosome lengths of Giemsa-stained G2 prematurely condensed chromosomes (PCC) were measured using image analysing software and the ratio of the longest/shortest chromosome length was calculated. The length ratio (LR) of the longest/shortest Giemsa-stained chromosome s increased with a good correlation to the square root of the radiation dose (D) up to 40 Gy, i.e. LR = (4.90 x D0.5) + 2.14. The LR of the longest/shortest chromosome might be used as an index for estimating the radiation dose. The blood samples should not be cooled until the start of separation/stimulation of the lymphocytes. A rapid and easy estimation of large doses after whole-body exposure was identified by measuring the ratio of the longest/shortest length of Giemsa-stained G2-PCC induced by calyculin A. This simple protocol will be particularly useful for making therapy decisions for victims of ionizing radiation exposure and has potential for use as a biodosimeter for partial-body exposure accidents.
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.
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.
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 Astrophysics Data System (ADS)
Liu, Huanlin; Zhang, Mingjia; Yi, Pengfei; Chen, Yong
2016-12-01
In order to address the problems of spectrum fragmentation and low sharing degree of spectrum resources in survivable elastic optical networks, an improved algorithm, called shared path protection by reconstructing sharable bandwidth based on spectrum segmentation (SPP-RSB-SS), is proposed in the paper. In the SPP-RSB-SS algorithm, for reducing the number of spectrum fragmentations and improving the success rate of spectrum allocation, the whole spectrum resource is partitioned into several spectrum segments. And each spectrum segment is allocated to the requests with the same bandwidth requirement in priority. Meanwhile, the protection path with higher spectrum sharing degree is selected through optimizing the link cost function and reconstructing sharable bandwidth. Hence, the protection path can maximize the sharable spectrum usage among multiple protection paths. The simulation results indicate that the SPP-RSB-SS algorithm can increase the sharing degree of protection spectrum effectively. Furthermore, the SPP-RSB-SS algorithm can enhance the spectrum utilization, and reduce the bandwidth blocking probability significantly.
Robust Video Stabilization Using Particle Keypoint Update and l1-Optimized Camera Path
Jeon, Semi; Yoon, Inhye; Jang, Jinbeum; Yang, Seungji; Kim, Jisung; Paik, Joonki
2017-01-01
Acquisition of stabilized video is an important issue for various type of digital cameras. This paper presents an adaptive camera path estimation method using robust feature detection to remove shaky artifacts in a video. The proposed algorithm consists of three steps: (i) robust feature detection using particle keypoints between adjacent frames; (ii) camera path estimation and smoothing; and (iii) rendering to reconstruct a stabilized video. As a result, the proposed algorithm can estimate the optimal homography by redefining important feature points in the flat region using particle keypoints. In addition, stabilized frames with less holes can be generated from the optimal, adaptive camera path that minimizes a temporal total variation (TV). The proposed video stabilization method is suitable for enhancing the visual quality for various portable cameras and can be applied to robot vision, driving assistant systems, and visual surveillance systems. PMID:28208622
The Study of Intelligent Vehicle Navigation Path Based on Behavior Coordination of Particle Swarm
Han, Gaining; Fu, Weiping; Wang, Wen
2016-01-01
In the behavior dynamics model, behavior competition leads to the shock problem of the intelligent vehicle navigation path, because of the simultaneous occurrence of the time-variant target behavior and obstacle avoidance behavior. Considering the safety and real-time of intelligent vehicle, the particle swarm optimization (PSO) algorithm is proposed to solve these problems for the optimization of weight coefficients of the heading angle and the path velocity. Firstly, according to the behavior dynamics model, the fitness function is defined concerning the intelligent vehicle driving characteristics, the distance between intelligent vehicle and obstacle, and distance of intelligent vehicle and target. Secondly, behavior coordination parameters that minimize the fitness function are obtained by particle swarm optimization algorithms. Finally, the simulation results show that the optimization method and its fitness function can improve the perturbations of the vehicle planning path and real-time and reliability. PMID:26880881
Robust Video Stabilization Using Particle Keypoint Update and l₁-Optimized Camera Path.
Jeon, Semi; Yoon, Inhye; Jang, Jinbeum; Yang, Seungji; Kim, Jisung; Paik, Joonki
2017-02-10
Acquisition of stabilized video is an important issue for various type of digital cameras. This paper presents an adaptive camera path estimation method using robust feature detection to remove shaky artifacts in a video. The proposed algorithm consists of three steps: (i) robust feature detection using particle keypoints between adjacent frames; (ii) camera path estimation and smoothing; and (iii) rendering to reconstruct a stabilized video. As a result, the proposed algorithm can estimate the optimal homography by redefining important feature points in the flat region using particle keypoints. In addition, stabilized frames with less holes can be generated from the optimal, adaptive camera path that minimizes a temporal total variation (TV). The proposed video stabilization method is suitable for enhancing the visual quality for various portable cameras and can be applied to robot vision, driving assistant systems, and visual surveillance systems.
Path integration: effect of curved path complexity and sensory system on blindfolded walking.
Koutakis, Panagiotis; Mukherjee, Mukul; Vallabhajosula, Srikant; Blanke, Daniel J; Stergiou, Nicholas
2013-02-01
Path integration refers to the ability to integrate continuous information of the direction and distance traveled by the system relative to the origin. Previous studies have investigated path integration through blindfolded walking along simple paths such as straight line and triangles. However, limited knowledge exists regarding the role of path complexity in path integration. Moreover, little is known about how information from different sensory input systems (like vision and proprioception) contributes to accurate path integration. The purpose of the current study was to investigate how sensory information and curved path complexity affect path integration. Forty blindfolded participants had to accurately reproduce a curved path and return to the origin. They were divided into four groups that differed in the curved path, circle (simple) or figure-eight (complex), and received either visual (previously seen) or proprioceptive (previously guided) information about the path before they reproduced it. The dependent variables used were average trajectory error, walking speed, and distance traveled. The results indicated that (a) both groups that walked on a circular path and both groups that received visual information produced greater accuracy in reproducing the path. Moreover, the performance of the group that received proprioceptive information and later walked on a figure-eight path was less accurate than their corresponding circular group. The groups that had the visual information also walked faster compared to the group that had proprioceptive information. Results of the current study highlight the roles of different sensory inputs while performing blindfolded walking for path integration.
Sankovski, Eve; Karro, Kristiina; Sepp, Mari; Kurg, Reet; Ustav, Mart; Abroi, Aare
2015-01-01
Technological advantages in sequencing and proteomics have revealed the remarkable diversity of alternative protein isoforms. Typically, the localization and functions of these isoforms are unknown and cannot be predicted. Also the localization signals leading to particular subnuclear compartments have not been identified and thus, predicting alternative functions due to alternative subnuclear localization is limited only to very few subnuclear compartments. Knowledge of the localization and function of alternative protein isoforms allows for a greater understanding of cellular complexity. In this article, we characterize a short and well-defined signal targeting the bovine papillomavirus type 1 E8/E2 protein to the nuclear matrix. The targeting signal comprises the peptide coded by E8 ORF, which is spliced together with part of the E2 ORF to generate the E8/E2 mRNA. Localization to the nuclear matrix correlates well with the transcription repression activities of E8/E2; a single point mutation directs the E8/E2 protein into the nucleoplasm, and transcription repression activity is lost. Our data prove that adding as few as ˜10 amino acids by alternative transcription/alternative splicing drastically alters the function and subnuclear localization of proteins. To our knowledge, E8 is the shortest known nuclear matrix targeting signal.
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.
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.
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
Wiest, Jennifer H.; Buckner, Gregory D.
2014-01-01
This paper introduces a real-time path optimization and control strategy for shape memory alloy (SMA) actuated cardiac ablation catheters, potentially enabling the creation of more precise lesions with reduced procedure times and improved patient outcomes. Catheter tip locations and orientations are optimized using parallel genetic algorithms to produce continuous ablation paths with near normal tissue contact through physician-specified points. A nonlinear multivariable control strategy is presented to compensate for SMA hysteresis, bandwidth limitations, and coupling between system inputs. Simulated and experimental results demonstrate efficient generation of ablation paths and optimal reference trajectories. Closed-loop control of the SMA-actuated catheter along optimized ablation paths is validated experimentally. PMID:25684857
Bioinspired Coordinated Path Following for Vessels with Speed Saturation Based on Virtual Leader
Fu, Mingyu
2016-01-01
This paper investigates the coordinated path following of multiple marine vessels with speed saturation. Based on virtual leader strategy, the authors show how the neural dynamic model and passivity-based techniques are brought together to yield a distributed control strategy. The desired path following is achieved by means of a virtual dynamic leader, whose controller is designed based on the biological neural shunting model. Utilizing the characteristic of bounded and smooth output of neural dynamic model, the tracking error jump is avoided and speed saturation problem is solved in straight path. Meanwhile, the coordinated path following of multiple vessels with a desired spatial formation is achieved through defining the formation reference point. The consensus of formation reference point is realized by using the synchronization controller based on passivity. Finally, simulation results validate the effectiveness of the proposed coordinated algorithm. PMID:27034652
Pathfinder: Visual Analysis of Paths in Graphs
Partl, C.; Gratzl, S.; Streit, M.; Wassermann, A. M.; Pfister, H.; Schmalstieg, D.; Lex, A.
2016-01-01
The analysis of paths in graphs is highly relevant in many domains. Typically, path-related tasks are performed in node-link layouts. Unfortunately, graph layouts often do not scale to the size of many real world networks. Also, many networks are multivariate, i.e., contain rich attribute sets associated with the nodes and edges. These attributes are often critical in judging paths, but directly visualizing attributes in a graph layout exacerbates the scalability problem. In this paper, we present visual analysis solutions dedicated to path-related tasks in large and highly multivariate graphs. We show that by focusing on paths, we can address the scalability problem of multivariate graph visualization, equipping analysts with a powerful tool to explore large graphs. We introduce Pathfinder (Figure 1), a technique that provides visual methods to query paths, while considering various constraints. The resulting set of paths is visualized in both a ranked list and as a node-link diagram. For the paths in the list, we display rich attribute data associated with nodes and edges, and the node-link diagram provides topological context. The paths can be ranked based on topological properties, such as path length or average node degree, and scores derived from attribute data. Pathfinder is designed to scale to graphs with tens of thousands of nodes and edges by employing strategies such as incremental query results. We demonstrate Pathfinder's fitness for use in scenarios with data from a coauthor network and biological pathways. PMID:27942090
A New Parallel Algorithm Analogous to Elastic Net Method forBipartite Subgraph Problem
NASA Astrophysics Data System (ADS)
Tang, Zheng; Wang, Rong Long; Wang, Jia Hai; Cao, Qi Ping
The goal of the bipartite subgraph problem, which is an NP-complete problem, is to remove the minimum number of edges in a given graph such that the remaining graph is a bipartite graph. Enlightened by the elastic net method that was introduced by Durbin and Willshaw for finding shortest route for the Traveling Salesman Problem (TSP), we proposed a new parallel algorithm for the bipartite subgraph problem. The approach jointly tends to satisfy the constraint condition and minimizes the number of removed edges. The collective computational properties of the proposed approach are also proved theoretically. A large number of instances have been simulated to verify the proposed algorithm. The simulation results show that our algorithm finds a solution superior to that of the best existing parallel algorithms.
Energy-Aware Path Planning for UAS Persistent Sampling and Surveillance
NASA Astrophysics Data System (ADS)
Shaw-Cortez, Wenceslao
The focus of this work is to develop an energy-aware path planning algorithm that maximizes UAS endurance, while performing sampling and surveillance missions in a known, stationary wind environment. The energy-aware aspect is specifically tailored to extract energy from the wind to reduce thrust use, thereby increasing aircraft endurance. Wind energy extraction is performed by static soaring and dynamic soaring. Static soaring involves using upward wind currents to increase altitude and potential energy. Dynamic soaring involves taking advantage of wind gradients to exchange potential and kinetic energy. The path planning algorithm developed in this work uses optimization to combine these soaring trajectories with the overarching sampling and surveillance mission. The path planning algorithm uses a simplified aircraft model to tractably optimize soaring trajectories. This aircraft model is presented and along with the derivation of the equations of motion. A nonlinear program is used to create the soaring trajectories based on a given optimization problem. This optimization problem is defined using a heuristic decision tree, which defines appropriate problems given a sampling and surveillance mission and a wind model. Simulations are performed to assess the path planning algorithm. The results are used to identify properties of soaring trajectories as well as to determine what wind conditions support minimal thrust soaring. Additional results show how the path planning algorithm can be tuned between maximizing aircraft endurance and performing the sampling and surveillance mission. A means of trajectory stitching is demonstrated to show how the periodic soaring segments can be combined together to provide a full solution to an infinite/long horizon problem.
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.
Hironaka, Mantaro; Tojo, Sumio; Nomakuchi, Shintaro; Filippi, Lisa; Hariyama, Takahiko
2007-06-01
Females of the subsocial shield bug, Parastrachia japonensis (Parastrachiidae), are central-place foragers, collecting drupes for their young from nearby host trees by walking along the forest floor both during the day and at night. Because burrows are often some distance from the drupe-shedding tree, the bugs must repeatedly leave their burrows, search for drupes, and return to the burrows. After a bug leaves its burrow, it searches arduously until it encounters a drupe. When a drupe is obtained, the bug always takes the shortest route back to its burrow. It has been clarified that this bug utilizes path integration during diurnal provisioning excursions. In this paper, we examined nocturnal behavior and some parameters of the path integration utilized by P. japonensis. There were no observable differences between day and night in the patterns of foraging and direct-homing behavior. When the bug was displaced to another position during the day or night, it always walked straight toward the fictive burrow, the site where the burrow should be if it had been displaced along with the bug, and then displayed searching behavior in the vicinity of the fictive burrow. The distance of the straight run corresponded accurately with a straight line between the burrow and the place where the bug obtained the drupe. These results indicate that P. japonensis orients toward the burrow using path integration both during diurnal and nocturnal provisioning behavior.
Integrated assignment and path planning
NASA Astrophysics Data System (ADS)
Murphey, Robert A.
2005-11-01
A surge of interest in unmanned systems has exposed many new and challenging research problems across many fields of engineering and mathematics. These systems have the potential of transforming our society by replacing dangerous and dirty jobs with networks of moving machines. This vision is fundamentally separate from the modern view of robotics in that sophisticated behavior is realizable not by increasing individual vehicle complexity, but instead through collaborative teaming that relies on collective perception, abstraction, decision making, and manipulation. Obvious examples where collective robotics will make an impact include planetary exploration, space structure assembly, remote and undersea mining, hazardous material handling and clean-up, and search and rescue. Nonetheless, the phenomenon driving this technology trend is the increasing reliance of the US military on unmanned vehicles, specifically, aircraft. Only a few years ago, following years of resistance to the use of unmanned systems, the military and civilian leadership in the United States reversed itself and have recently demonstrated surprisingly broad acceptance of increasingly pervasive use of unmanned platforms in defense surveillance, and even attack. However, as rapidly as unmanned systems have gained acceptance, the defense research community has discovered the technical pitfalls that lie ahead, especially for operating collective groups of unmanned platforms. A great deal of talent and energy has been devoted to solving these technical problems, which tend to fall into two categories: resource allocation of vehicles to objectives, and path planning of vehicle trajectories. An extensive amount of research has been conducted in each direction, yet, surprisingly, very little work has considered the integrated problem of assignment and path planning. This dissertation presents a framework for studying integrated assignment and path planning and then moves on to suggest an exact
Autonomous path-planning navigation system for site characterization
NASA Astrophysics Data System (ADS)
Rankin, Arturo L.; Crane, Carl D., III; Armstrong, David G., II; Nease, Allen D.; Brown, H. Edward
1996-05-01
The location and removal of buried munitions is an important yet hazardous task. Current development is aimed at performing both the ordnance location and removal tasks autonomously. An autonomous survey vehicle (ASV) named the Gator has been developed at the Center for Intelligent Machines and Robotics, under the direction of Wright Laboratory, Tyndall Air Force Base, Florida, and the Navy Explosive Ordnance Disposal Technology Division, Indian Head, Maryland. The primary task of the survey vehicle is to autonomously traverse an off-road site, towing behind it a trailer containing a sensor package capable of characterizing the sub-surface contents. Achieving 00 percent coverage of the site is critical to fully characterizing the site. This paper presents a strategy for planning efficient paths for the survey vehicle that guarantees near-complete coverage of a site. A small library of three in-house developed path planners are reviewed. A strategy is also presented to keep the trailer on-path and to calculate the percent of coverage of a site with a resolution of 0.01 m2. All of the algorithms discussed in this paper were initially developed in simulation on a Silicon Graphics computer and subsequently implemented on the survey vehicle.
Path planning in uncertain flow fields using ensemble method
NASA Astrophysics Data System (ADS)
Wang, Tong; Le Maître, Olivier P.; Hoteit, Ibrahim; Knio, Omar M.
2016-10-01
An ensemble-based approach is developed to conduct optimal path planning in unsteady ocean currents under uncertainty. We focus our attention on two-dimensional steady and unsteady uncertain flows, and adopt a sampling methodology that is well suited to operational forecasts, where an ensemble of deterministic predictions is used to model and quantify uncertainty. In an operational setting, much about dynamics, topography, and forcing of the ocean environment is uncertain. To address this uncertainty, the flow field is parametrized using a finite number of independent canonical random variables with known densities, and the ensemble is generated by sampling these variables. For each of the resulting realizations of the uncertain current field, we predict the path that minimizes the travel time by solving a boundary value problem (BVP), based on the Pontryagin maximum principle. A family of backward-in-time trajectories starting at the end position is used to generate suitable initial values for the BVP solver. This allows us to examine and analyze the performance of the sampling strategy and to develop insight into extensions dealing with general circulation ocean models. In particular, the ensemble method enables us to perform a statistical analysis of travel times and consequently develop a path planning approach that accounts for these statistics. The proposed methodology is tested for a number of scenarios. We first validate our algorithms by reproducing simple canonical solutions, and then demonstrate our approach in more complex flow fields, including idealized, steady and unsteady double-gyre flows.
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.
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.
Autonomous underwater vehicle adaptive path planning for target classification
NASA Astrophysics Data System (ADS)
Edwards, Joseph R.; Schmidt, Henrik
2002-11-01
Autonomous underwater vehicles (AUVs) are being rapidly developed to carry sensors into the sea in ways that have previously not been possible. The full use of the vehicles, however, is still not near realization due to lack of the true vehicle autonomy that is promised in the label (AUV). AUVs today primarily attempt to follow as closely as possible a preplanned trajectory. The key to increasing the autonomy of the AUV is to provide the vehicle with a means to make decisions based on its sensor receptions. The current work examines the use of active sonar returns from mine-like objects (MLOs) as a basis for sensor-based adaptive path planning, where the path planning objective is to discriminate between real mines and rocks. Once a target is detected in the mine hunting phase, the mine classification phase is initialized with a derivative cost function to emphasize signal differences and enhance classification capability. The AUV moves adaptively to minimize the cost function. The algorithm is verified using at-sea data derived from the joint MIT/SACLANTCEN GOATS experiments and advanced acoustic simulation using SEALAB. The mission oriented operating system (MOOS) real-time simulator is then used to test the onboard implementation of the algorithm.
Extracting Critical Path Graphs from MPI Applications
Schulz, M
2005-07-27
The critical path is one of the fundamental runtime characteristics of a parallel program. It identifies the longest execution sequence without wait delays. In other words, the critical path is the global execution path that inflicts wait operations on other nodes without itself being stalled. Hence, it dictates the overall runtime and knowing it is important to understand an application's runtime and message behavior and to target optimizations. We have developed a toolset that identifies the critical path of MPI applications, extracts it, and then produces a graphical representation of the corresponding program execution graph to visualize it. To implement this, we intercept all MPI library calls, use the information to build the relevant subset of the execution graph, and then extract the critical path from there. We have applied our technique to several scientific benchmarks and successfully produced critical path diagrams for applications running on up to 128 processors.
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.
Counting paths with Schur transitions
NASA Astrophysics Data System (ADS)
Díaz, Pablo; Kemp, Garreth; Véliz-Osorio, Alvaro
2016-10-01
In this work we explore the structure of the branching graph of the unitary group using Schur transitions. We find that these transitions suggest a new combinatorial expression for counting paths in the branching graph. This formula, which is valid for any rank of the unitary group, reproduces known asymptotic results. We proceed to establish the general validity of this expression by a formal proof. The form of this equation strongly hints towards a quantum generalization. Thus, we introduce a notion of quantum relative dimension and subject it to the appropriate consistency tests. This new quantity finds its natural environment in the context of RCFTs and fractional statistics; where the already established notion of quantum dimension has proven to be of great physical importance.
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.
An Algorithm of Semi-structured Data Scheme Extraction Based on OEM Model
NASA Astrophysics Data System (ADS)
Gong, An; Yang, Xue-Wei
In order to get the target model of semi-structured data rapidly, effectively and accurately, by combining the related nature of label path in the paper, this paper proposes an algorithm that can extract target model from the OEM model of semi-structured data directly. The basic idea of the Algorithm is: Using a Depth_First Search to get all of the label path expressions, with the help of the nature2 in this paper can reducing the number of path matching, we can generate all frequent label path expressions by layer. Finally, with the strategy of deletion we can get all of the longest frequent label path expressions effectively. Theoretical analysis and Experimental result shows that this algorithm can improve the accuracy of target model and reduce the size of candidate sets in pattern extraction.
Optimal Hops-Based Adaptive Clustering Algorithm
NASA Astrophysics Data System (ADS)
Xuan, Xin; Chen, Jian; Zhen, Shanshan; Kuo, Yonghong
This paper proposes an optimal hops-based adaptive clustering algorithm (OHACA). The algorithm sets an energy selection threshold before the cluster forms so that the nodes with less energy are more likely to go to sleep immediately. In setup phase, OHACA introduces an adaptive mechanism to adjust cluster head and load balance. And the optimal distance theory is applied to discover the practical optimal routing path to minimize the total energy for transmission. Simulation results show that OHACA prolongs the life of network, improves utilizing rate and transmits more data because of energy balance.
NASA Astrophysics Data System (ADS)
Zhu, Ruijie; Zhao, Yongli; Yang, Hui; Yu, Xiaosong; Zhang, Jie; Yousefpour, Ashkan; Wang, Nannan; Jue, Jason P.
2016-12-01
In this paper, we propose a multi-path fragmentation-aware routing, modulation and spectrum assignment algorithm (RMSA) for advance reservation (AR) and immediate reservation (IR) requests in elastic optical networks. Immediate reservation requests should be provided with service immediately, while advance reservation requests have specific starting times and holding times. As lightpaths are set up and torn down, fragmentation may occur in both spectrum and time domains. To decrease the two-dimensional fragmentation and to solve the problem of resource scarcity, we propose splitting requests into different parts and transferring these parts along one or more paths utilizing sliceable bandwidth variable transponders. We first introduce a model to solve the problem and propose a two-dimensional fragmentation occurrence measurement in spectrum and time domains. Then we propose a multi-path fragmentation-aware RMSA algorithm (MPFA). Simulation results show that MPFA can achieve better performance than existing algorithms in terms of blocking probability and spectrum utilization.
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.
Path planning for persistent surveillance applications using fixed-wing unmanned aerial vehicles
NASA Astrophysics Data System (ADS)
Keller, James F.
This thesis addresses coordinated path planning for fixed-wing Unmanned Aerial Vehicles (UAVs) engaged in persistent surveillance missions. While uniquely suited to this mission, fixed wing vehicles have maneuver constraints that can limit their performance in this role. Current technology vehicles are capable of long duration flight with a minimal acoustic footprint while carrying an array of cameras and sensors. Both military tactical and civilian safety applications can benefit from this technology. We make three main contributions: C1 A sequential path planner that generates a C 2 flight plan to persistently acquire a covering set of data over a user designated area of interest. The planner features the following innovations: • A path length abstraction that embeds kino-dynamic motion constraints to estimate feasible path length. • A Traveling Salesman-type planner to generate a covering set route based on the path length abstraction. • A smooth path generator that provides C 2 routes that satisfy user specified curvature constraints. C2 A set of algorithms to coordinate multiple UAVs, including mission commencement from arbitrary locations to the start of a coordinated mission and de-confliction of paths to avoid collisions with other vehicles and fixed obstacles. C3 A numerically robust toolbox of spline-based algorithms tailored for vehicle routing validated through flight test experiments on multiple platforms. A variety of tests and platforms are discussed. The algorithms presented are based on a technical approach with approximately equal emphasis on analysis, computation, dynamic simulation, and flight test experimentation. Our planner (C1) directly takes into account vehicle maneuverability and agility constraints that could otherwise render simple solutions infeasible. This is especially important when surveillance objectives elevate the importance of optimized paths. Researchers have developed a diverse range of solutions for persistent
Recursive Branching Simulated Annealing Algorithm
NASA Technical Reports Server (NTRS)
Bolcar, Matthew; Smith, J. Scott; Aronstein, David
2012-01-01
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.
Optimal Path Choice in Railway Passenger Travel Network Based on Residual Train Capacity
Dou, Fei; Yan, Kai; Huang, Yakun; Jia, Limin
2014-01-01
Passenger's optimal path choice is one of the prominent research topics in the field of railway passenger transport organization. More and more different train types are available, increasing path choices from departure to destination for travelers are unstoppable. However, travelers cannot avoid being confused when they hope to choose a perfect travel plan based on various travel time and cost constraints before departure. In this study, railway passenger travel network is constructed based on train timetable. Both the generalized cost function we developed and the residual train capacity are considered to be the foundation of path searching procedure. The railway passenger travel network topology is analyzed based on residual train capacity. Considering the total travel time, the total travel cost, and the total number of passengers, we propose an optimal path searching algorithm based on residual train capacity in railway passenger travel network. Finally, the rationale of the railway passenger travel network and the optimal path generation algorithm are verified positively by case study. PMID:25097867
Optimal path choice in railway passenger travel network based on residual train capacity.
Dou, Fei; Yan, Kai; Huang, Yakun; Wang, Li; Jia, Limin
2014-01-01
Passenger's optimal path choice is one of the prominent research topics in the field of railway passenger transport organization. More and more different train types are available, increasing path choices from departure to destination for travelers are unstoppable. However, travelers cannot avoid being confused when they hope to choose a perfect travel plan based on various travel time and cost constraints before departure. In this study, railway passenger travel network is constructed based on train timetable. Both the generalized cost function we developed and the residual train capacity are considered to be the foundation of path searching procedure. The railway passenger travel network topology is analyzed based on residual train capacity. Considering the total travel time, the total travel cost, and the total number of passengers, we propose an optimal path searching algorithm based on residual train capacity in railway passenger travel network. Finally, the rationale of the railway passenger travel network and the optimal path generation algorithm are verified positively by case study.
Martinez-Murcia, Francisco J; Górriz, Juan M; Ramírez, Javier; Ortiz, Andres
2016-11-01
The usage of biomedical imaging in the diagnosis of dementia is increasingly widespread. A number of works explore the possibilities of computational techniques and algorithms in what is called computed aided diagnosis. Our work presents an automatic parametrization of the brain structure by means of a path generation algorithm based on hidden Markov models (HMMs). The path is traced using information of intensity and spatial orientation in each node, adapting to the structure of the brain. Each path is itself a useful way to characterize the distribution of the tissue inside the magnetic resonance imaging (MRI) image by, for example, extracting the intensity levels at each node or generating statistical information of the tissue distribution. Additionally, a further processing consisting of a modification of the grey level co-occurrence matrix (GLCM) can be used to characterize the textural changes that occur throughout the path, yielding more meaningful values that could be associated to Alzheimer's disease (AD), as well as providing a significant feature reduction. This methodology achieves moderate performance, up to 80.3% of accuracy using a single path in differential diagnosis involving Alzheimer-affected subjects versus controls belonging to the Alzheimer's disease neuroimaging initiative (ADNI).
Perturbative Methods in Path Integration
NASA Astrophysics Data System (ADS)
Johnson-Freyd, Theodore Paul
This dissertation addresses a number of related questions concerning perturbative "path" integrals. Perturbative methods are one of the few successful ways physicists have worked with (or even defined) these infinite-dimensional integrals, and it is important as mathematicians to check that they are correct. Chapter 0 provides a detailed introduction. We take a classical approach to path integrals in Chapter 1. Following standard arguments, we posit a Feynman-diagrammatic description of the asymptotics of the time-evolution operator for the quantum mechanics of a charged particle moving nonrelativistically through a curved manifold under the influence of an external electromagnetic field. We check that our sum of Feynman diagrams has all desired properties: it is coordinate-independent and well-defined without ultraviolet divergences, it satisfies the correct composition law, and it satisfies Schrodinger's equation thought of as a boundary-value problem in PDE. Path integrals in quantum mechanics and elsewhere in quantum field theory are almost always of the shape ∫ f es for some functions f (the "observable") and s (the "action"). In Chapter 2 we step back to analyze integrals of this type more generally. Integration by parts provides algebraic relations between the values of ∫ (-) es for different inputs, which can be packaged into a Batalin--Vilkovisky-type chain complex. Using some simple homological perturbation theory, we study the version of this complex that arises when f and s are taken to be polynomial functions, and power series are banished. We find that in such cases, the entire scheme-theoretic critical locus (complex points included) of s plays an important role, and that one can uniformly (but noncanonically) integrate out in a purely algebraic way the contributions to the integral from all "higher modes," reducing ∫ f es to an integral over the critical locus. This may help explain the presence of analytic continuation in questions like the
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.
White Noise Path Integrals in Stochastic Neurodynamics
NASA Astrophysics Data System (ADS)
Carpio-Bernido, M. Victoria; Bernido, Christopher C.
2008-06-01
The white noise path integral approach is used in stochastic modeling of neural activity, where the primary dynamical variables are the relative membrane potentials, while information on transmembrane ionic currents is contained in the drift coefficient. The white noise path integral allows a natural framework and can be evaluated explicitly to yield a closed form for the conditional probability density.
The Path of Carbon in Photosynthesis VI.
DOE R&D Accomplishments Database
Calvin, M.
1949-06-30
This paper is a compilation of the essential results of our experimental work in the determination of the path of carbon in photosynthesis. There are discussions of the dark fixation of photosynthesis and methods of separation and identification including paper chromatography and radioautography. The definition of the path of carbon in photosynthesis by the distribution of radioactivity within the compounds is described.
The path dependence of deformation texture development
Takeshita, T.; Kocks, U.F.; Wenk, H.R.
1987-01-01
It is demonstrated for the case of three different strain paths, all of which end up with the same, elongated specimen shape, that the texture developed during straining is path dependent. This is true both for experiments on aluminum polycrystals and for simulations using the LApp code.
Career Path Guide for Adult Career Choices.
ERIC Educational Resources Information Center
Case, Clydia
Intended for adults who are considering career choices or changes, this booklet provides opportunities for self-study and reflection in six career paths. The booklet begins with tips for long-term career survival and myths and realities of career planning. After a brief career survey, readers are introduced to six career paths: arts and…
A Random Walk on a Circular Path
ERIC Educational Resources Information Center
Ching, W.-K.; Lee, M. S.
2005-01-01
This short note introduces an interesting random walk on a circular path with cards of numbers. By using high school probability theory, it is proved that under some assumptions on the number of cards, the probability that a walker will return to a fixed position will tend to one as the length of the circular path tends to infinity.
Adaptively Ubiquitous Learning in Campus Math Path
ERIC Educational Resources Information Center
Shih, Shu-Chuan; Kuo, Bor-Chen; Liu, Yu-Lung
2012-01-01
The purposes of this study are to develop and evaluate the instructional model and learning system which integrate ubiquitous learning, computerized adaptive diagnostic testing system and campus math path learning. The researcher first creates a ubiquitous learning environment which is called "adaptive U-learning math path system". This…
Connections on decorated path space bundles
NASA Astrophysics Data System (ADS)
Chatterjee, Saikat; Lahiri, Amitabha; Sengupta, Ambar N.
2017-02-01
For a principal bundle P → M equipped with a connection A ¯ , we study an infinite dimensional bundle PA¯ dec P over the space of paths on M, with the points of PA¯ dec P being horizontal paths on P decorated with elements of a second structure group. We construct parallel transport processes on such bundles and study holonomy bundles in this setting.
Evaluation of Calcine Disposition - Path Forward
Steve Birrer
2003-02-01
This document describes an evaluation of the baseline and two alternative disposition paths for the final disposition of the calcine wastes stored at the Idaho Nuclear Technology and Engineering Center at the Idaho National Engineering and Environmental Laboratory. The pathways are evaluated against a prescribed set of criteria and a recommendation is made for the path forward.
Gerbertian paths for the Jubilee
NASA Astrophysics Data System (ADS)
Sigismondi, Costantino
2015-04-01
Gerbert before becoming Pope Sylvester II came several times in Rome, as reported in his Letters and in the biography of Richerus. Eight places in Rome can be connected with Gerbertian memories. 1. The Cathedral of St. John in the Lateran where the gravestone of his tumb is still preserved near the Holy Door; 2. the “Basilica Hierusalem” (Santa Croce) where Gerbert had the stroke on May 3rd 1003 which lead him to death on May 12th; 3. the Aventine hill, with the church of the Knights of Malta in the place where the palace of the Ottonian Emperors was located; 4. the church of St. Bartholomew in the Tiber Island built in 997 under Otto III; 5. the Obelisk of Augustus in Montecitorio to remember the relationship between Gerbert, Astronomy and numbers which led the birth of the legends on Gerbert magician; 6. St. Mary Major end of the procession of August 15, 1000; 7. St. Paul outside the walls with the iconography of the Popes and 8. St. Peter's tumb end of all Romaei pilgrimages. This Gerbertian path in Rome suggests one way to accomplish the pilgrimage suggested by Pope Francis in the Bulla Misericordiae Vultus (14) of indiction of the new Jubilee.
Bergman Kernel from Path Integral
NASA Astrophysics Data System (ADS)
Douglas, Michael R.; Klevtsov, Semyon
2010-01-01
We rederive the expansion of the Bergman kernel on Kähler manifolds developed by Tian, Yau, Zelditch, Lu and Catlin, using path integral and perturbation theory, and generalize it to supersymmetric quantum mechanics. One physics interpretation of this result is as an expansion of the projector of wave functions on the lowest Landau level, in the special case that the magnetic field is proportional to the Kähler form. This is relevant for the quantum Hall effect in curved space, and for its higher dimensional generalizations. Other applications include the theory of coherent states, the study of balanced metrics, noncommutative field theory, and a conjecture on metrics in black hole backgrounds discussed in [24]. We give a short overview of these various topics. From a conceptual point of view, this expansion is noteworthy as it is a geometric expansion, somewhat similar to the DeWitt-Seeley-Gilkey et al short time expansion for the heat kernel, but in this case describing the long time limit, without depending on supersymmetry.
Decision paths in complex tasks
NASA Technical Reports Server (NTRS)
Galanter, Eugene
1991-01-01
Complex real world action and its prediction and control has escaped analysis by the classical methods of psychological research. The reason is that psychologists have no procedures to parse complex tasks into their constituents. Where such a division can be made, based say on expert judgment, there is no natural scale to measure the positive or negative values of the components. Even if we could assign numbers to task parts, we lack rules i.e., a theory, to combine them into a total task representation. We compare here two plausible theories for the amalgamation of the value of task components. Both of these theories require a numerical representation of motivation, for motivation is the primary variable that guides choice and action in well-learned tasks. We address this problem of motivational quantification and performance prediction by developing psychophysical scales of the desireability or aversiveness of task components based on utility scaling methods (Galanter 1990). We modify methods used originally to scale sensory magnitudes (Stevens and Galanter 1957), and that have been applied recently to the measure of task 'workload' by Gopher and Braune (1984). Our modification uses utility comparison scaling techniques which avoid the unnecessary assumptions made by Gopher and Braune. Formula for the utility of complex tasks based on the theoretical models are used to predict decision and choice of alternate paths to the same goal.
Precision Cleaning - Path to Premier
NASA Technical Reports Server (NTRS)
Mackler, Scott E.
2008-01-01
ITT Space Systems Division s new Precision Cleaning facility provides critical cleaning and packaging of aerospace flight hardware and optical payloads to meet customer performance requirements. The Precision Cleaning Path to Premier Project was a 2007 capital project and is a key element in the approved Premier Resource Management - Integrated Supply Chain Footprint Optimization Project. Formerly precision cleaning was located offsite in a leased building. A new facility equipped with modern precision cleaning equipment including advanced process analytical technology and improved capabilities was designed and built after outsourcing solutions were investigated and found lacking in ability to meet quality specifications and schedule needs. SSD cleans parts that can range in size from a single threaded fastener all the way up to large composite structures. Materials that can be processed include optics, composites, metals and various high performance coatings. We are required to provide verification to our customers that we have met their particulate and molecular cleanliness requirements and we have that analytical capability in this new facility. The new facility footprint is approximately half the size of the former leased operation and provides double the amount of throughput. Process improvements and new cleaning equipment are projected to increase 1st pass yield from 78% to 98% avoiding $300K+/yr in rework costs. Cost avoidance of $350K/yr will result from elimination of rent, IT services, transportation, and decreased utility costs. Savings due to reduced staff expected to net $4-500K/yr.
A clinical path for adult diabetes.
Courtney, L; Gordon, M; Romer, L
1997-01-01
The use of clinical paths for patient care management was explored by this development team as a mechanism to provide consistent, high-quality care to hospitalized patients in high-volume, high-risk diagnostic categories. Reviewing the historical aspects and importance of clinical paths helped expand the team's perspective to incorporate pre- and posthospitalization phases of patient care into the clinical path being developed. A multidisciplinary team of physicians, nurses, health educators, and dietitians from both inpatient and outpatient departments of Kaiser-Santa Teresa Medical Center in San Jose, California, devised and implemented an Adult Diabetes Mellitus care path. Staff education preceded the implementation of the care paths. Measurements of quality indicators showed improvements in patient satisfaction, patient education, patient knowledge, and nutrition assessments.
Topological Path Planning in GPS Trajectory Data
Corcoran, Padraig
2016-01-01
This paper proposes a novel solution to the problem of computing a set of topologically inequivalent paths between two points in a space given a set of samples drawn from that space. Specifically, these paths are homotopy inequivalent where homotopy is a topological equivalence relation. This is achieved by computing a basis for the group of homology inequivalent loops in the space. An additional distinct element is then computed where this element corresponds to a loop which passes through the points in question. The set of paths is subsequently obtained by taking the orbit of this element acted on by the group of homology inequivalent loops. Using a number of spaces, including a street network where the samples are GPS trajectories, the proposed method is demonstrated to accurately compute a set of homotopy inequivalent paths. The applications of this method include path and coverage planning. PMID:28009817
NASA Astrophysics Data System (ADS)
Ishii, Katsuhiro; Nishidate, Izumi; Iwai, Toshiaki
2014-05-01
Numerical analysis of optical propagation in highly scattering media is investigated when light is normally incident to the surface and re-emerges backward from the same point. This situation corresponds to practical light scattering setups, such as in optical coherence tomography. The simulation uses the path-length-assigned Monte Carlo method based on an ellipsoidal algorithm. The spatial distribution of the scattered light is determined and the dependence of its width and penetration depth on the path-length is found. The backscattered light is classified into three types, in which ballistic, snake, and diffuse photons are dominant.
Chandrasekaran, Srinivas Niranj; Carter, Charles W.
2017-01-01
PATH algorithms for identifying conformational transition states provide computational parameters—time to the transition state, conformational free energy differences, and transition state activation energies—for comparison to experimental data and can be carried out sufficiently rapidly to use in the “high throughput” mode. These advantages are especially useful for interpreting results from combinatorial mutagenesis experiments. This report updates the previously published algorithm with enhancements that improve correlations between PATH convergence parameters derived from virtual variant structures generated by RosettaBackrub and previously published kinetic data for a complete, four-way combinatorial mutagenesis of a conformational switch in Tryptophanyl-tRNA synthetase. PMID:28289692
The information transmission in community networks
NASA Astrophysics Data System (ADS)
Zhu, Zhi-Qiang; Liu, Chuan-Jian; Wu, Jian-Liang; Liu, Bin
2013-09-01
The community structure has been empirically found in many real networks. This paper proposes an efficient Double Shortest Path routing strategy trying to avoid the modules of traffic congestion, which means that we adopt the shortest routing strategy both in the inter-modules and in the intra-module. Simulations show that this routing algorithm is superior to the traditional shortest path routing protocol with appropriate selection of the tunable parameters. In addition, this algorithm can also be improved by integrating it with several alternative routing strategies.
Fontana, W.
1990-12-13
In this paper complex adaptive systems are defined by a self- referential loop in which objects encode functions that act back on these objects. A model for this loop is presented. It uses a simple recursive formal language, derived from the lambda-calculus, to provide a semantics that maps character strings into functions that manipulate symbols on strings. The interaction between two functions, or algorithms, is defined naturally within the language through function composition, and results in the production of a new function. An iterated map acting on sets of functions and a corresponding graph representation are defined. Their properties are useful to discuss the behavior of a fixed size ensemble of randomly interacting functions. This function gas'', or Turning gas'', is studied under various conditions, and evolves cooperative interaction patterns of considerable intricacy. These patterns adapt under the influence of perturbations consisting in the addition of new random functions to the system. Different organizations emerge depending on the availability of self-replicators.
[The technology of fast spectral reconstruction in the longer optical path difference PEM-FTS].
Zhang, Min-Juan; Wang, Zhao-Ba; Wang, Zhi-Bin; Li, Xiao; Li, Shi-Wei; Li, Jin-Hua
2014-07-01
The optical path difference of the photoelastic modulator Fourier transform spectrometers (PEM-FTS) changes rapidly and nonlinearly, while the instrument preserves the speed as high as about 10(5) interferograms per second, so that the interferograms of PEM-FTS are sampled by equal interval. In order to fleetly and accurately reconstruct these spectrums, the principle of PEM-FTS and accelerated NUFFT algorithm were studied in the present article. The accelerating NUFFT algorithm integrates interpolation based on convolution kernel and fast Fourier transform (FFT). And the velocity and precision of the algorithm are affected by the type and parameter tau of kernel function, the single-side spreading distance q and the oversampling ratio micro, and so on. In the paper these parameters were analysed, under the condition N = 1 024, q = 10, micro = 2 and tau = 1 x 10(-6) in the Gaussian scaling factor, and the accelerated NUFFT algorithm was applied to the longer optical path difference PEM-FTS to rebuild the spectrums of 632. 8 nm laser and Xenon lamp, The frequency error of the rebuilt spectrums of 632.8 nm laser is less than 0.013 52, the spent time of interpolation is less than 0.267 s. the velocity is fast and the error is less. The accelerated nonuniform fast Fourier transform is fit for the longer optical path difference PEM-FTS.
Evolutionary algorithms applied to reliable communication network design
NASA Astrophysics Data System (ADS)
Nesmachnow, Sergio; Cancela, Hector; Alba, Enrique
2007-10-01
Several evolutionary algorithms (EAs) applied to a wide class of communication network design problems modelled under the generalized Steiner problem (GSP) are evaluated. In order to provide a fault-tolerant design, a solution to this problem consists of a preset number of independent paths linking each pair of potentially communicating terminal nodes. This usually requires considering intermediate non-terminal nodes (Steiner nodes), which are used to ensure path redundancy, while trying to minimize the overall cost. The GSP is an NP-hard problem for which few algorithms have been proposed. This article presents a comparative study of pure and hybrid EAs applied to the GSP, codified over MALLBA, a general purpose library for combinatorial optimization. The algorithms were tested on several GSPs, and asset efficient numerical results are reported for both serial and distributed models of the evaluated algorithms.
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
Graph-Based Path-Planning for Titan Balloons
NASA Technical Reports Server (NTRS)
Blackmore, Lars James; Fathpour, Nanaz; Elfes, Alberto
2010-01-01
A document describes a graph-based path-planning algorithm for balloons with vertical control authority and little or no horizontal control authority. The balloons are designed to explore celestial bodies with atmospheres, such as Titan, a moon of Saturn. The algorithm discussed enables the balloon to achieve horizontal motion using the local horizontal winds. The approach is novel because it enables the balloons to use arbitrary wind field models. This is in contrast to prior approaches that used highly simplified wind field models, such as linear, or binary, winds. This new approach works by discretizing the space in which the balloon operates, and representing the possible states of the balloon as a graph whose arcs represent the time taken to move from one node to another. The approach works with arbitrary wind fields, by looking up the wind strength and direction at every node in the graph from an arbitrary wind model. Having generated the graph, search techniques such as Dijkstra s algorithm are then used to find the set of vertical actuation commands that takes the balloon from the start to the goal in minimum time. In addition, the set of reachable locations on the moon or planet can be determined.
Nonholonomic catheter path reconstruction using electromagnetic tracking
NASA Astrophysics Data System (ADS)
Lugez, Elodie; Sadjadi, Hossein; Akl, Selim G.; Fichtinger, Gabor
2015-03-01
Catheter path reconstruction is a necessary step in many clinical procedures, such as cardiovascular interventions and high-dose-rate brachytherapy. To overcome limitations of standard imaging modalities, electromagnetic tracking has been employed to reconstruct catheter paths. However, tracking errors pose a challenge in accurate path reconstructions. We address this challenge by means of a filtering technique incorporating the electromagnetic measurements with the nonholonomic motion constraints of the sensor inside a catheter. The nonholonomic motion model of the sensor within the catheter and the electromagnetic measurement data were integrated using an extended Kalman filter. The performance of our proposed approach was experimentally evaluated using the Ascension's 3D Guidance trakStar electromagnetic tracker. Sensor measurements were recorded during insertions of an electromagnetic sensor (model 55) along ten predefined ground truth paths. Our method was implemented in MATLAB and applied to the measurement data. Our reconstruction results were compared to raw measurements as well as filtered measurements provided by the manufacturer. The mean of the root-mean-square (RMS) errors along the ten paths was 3.7 mm for the raw measurements, and 3.3 mm with manufacturer's filters. Our approach effectively reduced the mean RMS error to 2.7 mm. Compared to other filtering methods, our approach successfully improved the path reconstruction accuracy by exploiting the sensor's nonholonomic motion constraints in its formulation. Our approach seems promising for a variety of clinical procedures involving reconstruction of a catheter path.
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.
Mori, Yoshiharu; Okumura, Hisashi
2015-12-05
Simulated tempering (ST) is a useful method to enhance sampling of molecular simulations. When ST is used, the Metropolis algorithm, which satisfies the detailed balance condition, is usually applied to calculate the transition probability. Recently, an alternative method that satisfies the global balance condition instead of the detailed balance condition has been proposed by Suwa and Todo. In this study, ST method with the Suwa-Todo algorithm is proposed. Molecular dynamics simulations with ST are performed with three algorithms (the Metropolis, heat bath, and Suwa-Todo algorithms) to calculate the transition probability. Among the three algorithms, the Suwa-Todo algorithm yields the highest acceptance ratio and the shortest autocorrelation time. These suggest that sampling by a ST simulation with the Suwa-Todo algorithm is most efficient. In addition, because the acceptance ratio of the Suwa-Todo algorithm is higher than that of the Metropolis algorithm, the number of temperature states can be reduced by 25% for the Suwa-Todo algorithm when compared with the Metropolis algorithm.
All-Optical Implementation of the Ant Colony Optimization Algorithm
Hu, Wenchao; Wu, Kan; Shum, Perry Ping; Zheludev, Nikolay I.; Soci, Cesare
2016-01-01
We report all-optical implementation of the optimization algorithm for the famous “ant colony” problem. Ant colonies progressively optimize pathway to food discovered by one of the ants through identifying the discovered route with volatile chemicals (pheromones) secreted on the way back from the food deposit. Mathematically this is an important example of graph optimization problem with dynamically changing parameters. Using an optical network with nonlinear waveguides to represent the graph and a feedback loop, we experimentally show that photons traveling through the network behave like ants that dynamically modify the environment to find the shortest pathway to any chosen point in the graph. This proof-of-principle demonstration illustrates how transient nonlinearity in the optical system can be exploited to tackle complex optimization problems directly, on the hardware level, which may be used for self-routing of optical signals in transparent communication networks and energy flow in photonic systems. PMID:27222098
All-Optical Implementation of the Ant Colony Optimization Algorithm
NASA Astrophysics Data System (ADS)
Hu, Wenchao; Wu, Kan; Shum, Perry Ping; Zheludev, Nikolay I.; Soci, Cesare
2016-05-01
We report all-optical implementation of the optimization algorithm for the famous “ant colony” problem. Ant colonies progressively optimize pathway to food discovered by one of the ants through identifying the discovered route with volatile chemicals (pheromones) secreted on the way back from the food deposit. Mathematically this is an important example of graph optimization problem with dynamically changing parameters. Using an optical network with nonlinear waveguides to represent the graph and a feedback loop, we experimentally show that photons traveling through the network behave like ants that dynamically modify the environment to find the shortest pathway to any chosen point in the graph. This proof-of-principle demonstration illustrates how transient nonlinearity in the optical system can be exploited to tackle complex optimization problems directly, on the hardware level, which may be used for self-routing of optical signals in transparent communication networks and energy flow in photonic systems.
The terminal area automated path generation problem
NASA Technical Reports Server (NTRS)
Hsin, C.-C.
1977-01-01
The automated terminal area path generation problem in the advanced Air Traffic Control System (ATC), has been studied. Definitions, input, output and the interrelationships with other ATC functions have been discussed. Alternatives in modeling the problem have been identified. Problem formulations and solution techniques are presented. In particular, the solution of a minimum effort path stretching problem (path generation on a given schedule) has been carried out using the Newton-Raphson trajectory optimization method. Discussions are presented on the effect of different delivery time, aircraft entry position, initial guess on the boundary conditions, etc. Recommendations are made on real-world implementations.
A New Proton Dose Algorithm for Radiotherapy
NASA Astrophysics Data System (ADS)
Lee, Chungchi (Chris).
This algorithm recursively propagates the proton distribution in energy, angle and space at one level in an absorbing medium to another, at slightly greater depth, until all the protons are stopped. The angular transition density describing the proton trajectory is based on Moliere's multiple scattering theory and Vavilov's theory of energy loss along the proton's path increment. These multiple scattering and energy loss distributions are sampled using equal probability spacing to optimize computational speed while maintaining calculational accuracy. Nuclear interactions are accounted for by using a simple exponential expression to describe the loss of protons along a given path increment and the fraction of the original energy retained by the proton is deposited locally. Two levels of testing for the algorithm are provided: (1) Absolute dose comparisons with PTRAN Monte Carlo simulations in homogeneous water media. (2) Modeling of a fixed beam line including the scattering system and range modulator and comparisons with measured data in a homogeneous water phantom. The dose accuracy of this algorithm is shown to be within +/-5% throughout the range of a 200-MeV proton when compared to measurements except in the shoulder region of the lateral profile at the Bragg peak where a dose difference as large as 11% can be found. The numerical algorithm has an adequate spatial accuracy of 3 mm. Measured data as input is not required.
Development Paths in Archaeological Surveying
NASA Astrophysics Data System (ADS)
Tabbagh, A.
2005-05-01
Geophysical surveys of archaeological sites began in 1938, when an electrical survey was performed at the historical site of Williamsburg (Virginia, USA). Its full development, however, has been achieved by several European teams, which have continuously worked on it since the fifties. Geophysical survey is one step of archaeological site reconnaissance, which comprises many other non-invasive techniques such as document studies, field walking, air photo interpretation...Nevertheless solely geophysical techniques allow a direct exploration of the underground itself over a significant depth of investigation. Several physical properties can be measured to detect and map archaeological features and/or remains but electrical resistivity and magnetisation has been commonly used for fifty years and dielectric permittivity more recently. The major path of the technical evolution was to increase both the speed of the survey and the size of the area by using short measurement duration (less than 0.1 s) and to incorporate mechanical systems that allow the continuous pulling of the sensors on the field. Magnetic measurements are thus achieved either by fluxgate or optically pumped sensors, while electrical measurements are achieved by mobile multi-pole systems simultaneously over two or three different depths. In such surveys the mesh grid is 1 x 1 m or 0.5 x 0.5 m. Another aim is to limit the size of the surveyed area but to increase the geometrical resolution by using ground penetrating radars (GPR) with a very fine mesh (0.2 x 0.2 m) and by processing the data by `time slices' which allow to follow precisely the extension in depth of the different features. In addition for magnetic features, the simultaneous inversion of magnetic field and susceptibility (and soon viscosity) measurements using linear filtering allows the differentiation among the types of magnetization and allows for an improved determination of the depths of magnetic property contrasts. By considering the
Algorithm Animation with Galant.
Stallmann, Matthias F
2017-01-01
Although surveys suggest positive student attitudes toward the use of algorithm animations, it is not clear that they improve learning outcomes. The Graph Algorithm Animation Tool, or Galant, challenges and motivates students to engage more deeply with algorithm concepts, without distracting them with programming language details or GUIs. Even though Galant is specifically designed for graph algorithms, it has also been used to animate other algorithms, most notably sorting algorithms.
Current-Sensitive Path Planning for an Underactuated Free-Floating Ocean Sensorweb
NASA Technical Reports Server (NTRS)
Dahl, Kristen P.; Thompson, David R.; McLaren, David; Chao, Yi; Chien, Steve
2011-01-01
This work investigates multi-agent path planning in strong, dynamic currents using thousands of highly under-actuated vehicles. We address the specific task of path planning for a global network of ocean-observing floats. These submersibles are typified by the Argo global network consisting of over 3000 sensor platforms. They can control their buoyancy to float at depth for data collection or rise to the surface for satellite communications. Currently, floats drift at a constant depth regardless of the local currents. However, accurate current forecasts have become available which present the possibility of intentionally controlling floats' motion by dynamically commanding them to linger at different depths. This project explores the use of these current predictions to direct float networks to some desired final formation or position. It presents multiple algorithms for such path optimization and demonstrates their advantage over the standard approach of constant-depth drifting.
Bayesian path specific frailty models for multi-state survival data with applications.
de Castro, Mário; Chen, Ming-Hui; Zhang, Yuanye
2015-09-01
Multi-state models can be viewed as generalizations of both the standard and competing risks models for survival data. Models for multi-state data have been the theme of many recent published works. Motivated by bone marrow transplant data, we propose a Bayesian model using the gap times between two successive events in a path of events experienced by a subject. Path specific frailties are introduced to capture the dependence structure of the gap times in the paths with two or more states. Under improper prior distributions for the parameters, we establish propriety of the posterior distribution. An efficient Gibbs sampling algorithm is developed for drawing samples from the posterior distribution. An extensive simulation study is carried out to examine the empirical performance of the proposed approach. A bone marrow transplant data set is analyzed in detail to further demonstrate the proposed methodology.
Bayesian Path Specific Frailty Models for Multi-state Survival Data with Applications
de Castro, Mário; Chen, Ming-Hui; Zhang, Yuanye
2015-01-01
Summary Multi-state models can be viewed as generalizations of both the standard and competing risks models for survival data. Models for multi-state data have been the theme of many recent published works. Motivated by bone marrow transplant data, we propose a Bayesian model using the gap times between two successive events in a path of events experienced by a subject. Path specific frailties are introduced to capture the dependence structure of the gap times in the paths with two or more states. Under improper prior distributions for the parameters, we establish propriety of the posterior distribution. An efficient Gibbs sampling algorithm is developed for drawing samples from the posterior distribution. An extensive simulation study is carried out to examine the empirical performance of the proposed approach. A bone marrow transplant data set is analyzed in detail to further demonstrate the proposed methodology. PMID:25762198
Distributed multiple path routing in complex networks
NASA Astrophysics Data System (ADS)
Chen, Guang; Wang, San-Xiu; Wu, Ling-Wei; Mei, Pan; Yang, Xu-Hua; Wen, Guang-Hui
2016-12-01
Routing in complex transmission networks is an important problem that has garnered extensive research interest in the recent years. In this paper, we propose a novel routing strategy called the distributed multiple path (DMP) routing strategy. For each of the O-D node pairs in a given network, the DMP routing strategy computes and stores multiple short-length paths that overlap less with each other in advance. And during the transmission stage, it rapidly selects an actual routing path which provides low transmission cost from the pre-computed paths for each transmission task, according to the real-time network transmission status information. Computer simulation results obtained for the lattice, ER random, and scale-free networks indicate that the strategy can significantly improve the anti-congestion ability of transmission networks, as well as provide favorable routing robustness against partial network failures.
Animation: Path of 2010 Solar Eclipse
On Sunday, 2010 July 11, a total eclipse of the Sun is visible from within a narrow corridor that traverses Earth's southern hemisphere. The path of the Moon's umbral shadow crosses the South Pacif...
IRIS Optical Instrument and Light Paths
The optical portion of the instrument and the light paths from the primary and secondary mirror of the telescope assembly into the spectrograph. The spectrograph then breaks the light into 2 Near U...
Riemann Curvature Tensor and Closed Geodesic Paths
ERIC Educational Resources Information Center
Morganstern, Ralph E.
1977-01-01
Demonstrates erroneous results obtained if change in a vector under parallel transport about a closed path in Riemannian spacetime is made in a complete circuit rather than just half a circuit. (Author/SL)
Orbital Path of the International Space Station
Astronauts Don Pettit, Andre Kuipers and Dan Burbank explain the orbital path of the International Space Station. Earth video credit: Image Science and Analysis Laboratory, NASA's Johnson Space Cen...
Path Integral Approach to Atomic Collisions
NASA Astrophysics Data System (ADS)
Harris, Allison
2016-09-01
The Path Integral technique is an alternative formulation of quantum mechanics that is based on a Lagrangian approach. In its exact form, it is completely equivalent to the Hamiltonian-based Schrödinger equation approach. Developed by Feynman in the 1940's, following inspiration from Dirac, the path integral approach has been widely used in high energy physics, quantum field theory, and statistical mechanics. However, only in limited cases has the path integral approach been applied to quantum mechanical few-body scattering. We present a theoretical and computational development of the path integral method for use in the study of atomic collisions. Preliminary results are presented for some simple systems. Ultimately, this approach will be applied to few-body ion-atom collisions. Work supported by NSF grant PHY-1505217.
Local-time representation of path integrals.
Jizba, Petr; Zatloukal, Václav
2015-12-01
We derive a local-time path-integral representation for a generic one-dimensional time-independent system. In particular, we show how to rephrase the matrix elements of the Bloch density matrix as a path integral over x-dependent local-time profiles. The latter quantify the time that the sample paths x(t) in the Feynman path integral spend in the vicinity of an arbitrary point x. Generalization of the local-time representation that includes arbitrary functionals of the local time is also provided. We argue that the results obtained represent a powerful alternative to the traditional Feynman-Kac formula, particularly in the high- and low-temperature regimes. To illustrate this point, we apply our local-time representation to analyze the asymptotic behavior of the Bloch density matrix at low temperatures. Further salient issues, such as connections with the Sturm-Liouville theory and the Rayleigh-Ritz variational principle, are also discussed.
A chemist building paths to cell biology.
Weibel, Douglas B
2013-11-01
Galileo is reported to have stated, "Measure what is measurable and make measurable what is not so." My group's trajectory in cell biology has closely followed this philosophy, although it took some searching to find this path.
Identifying decohering paths in closed quantum systems
NASA Technical Reports Server (NTRS)
Albrecht, Andreas
1990-01-01
A specific proposal is discussed for how to identify decohering paths in a wavefunction of the universe. The emphasis is on determining the correlations among subsystems and then considering how these correlations evolve. The proposal is similar to earlier ideas of Schroedinger and of Zeh, but in other ways it is closer to the decoherence functional of Griffiths, Omnes, and Gell-Mann and Hartle. There are interesting differences with each of these which are discussed. Once a given coarse-graining is chosen, the candidate paths are fixed in this scheme, and a single well defined number measures the degree of decoherence for each path. The normal probability sum rules are exactly obeyed (instantaneously) by these paths regardless of the level of decoherence. Also briefly discussed is how one might quantify some other aspects of classicality. The important role that concrete calculations play in testing this and other proposals is stressed.
Comparing Unlabeled Pedigree Graphs via Covering with Bipartite and Path.
Amar, Lamiaa A; Belal, Nahla A; Rashwan, Shaheera
2016-11-01
Family trees, also called pedigrees, have important information about an individual's past and future life. It can be used as a diagnostic tool and help guide decisions about genetic testing for the patient and at-risk family members. There are 2% to 10% of parent-child relationships missing, and this can cause large differences in the pedigree graphs created. Hence, the evaluation of pedigrees is an essential task. In this article, we focus on the problem of isomorphism of unlabeled subpedigrees with a large number of individuals and hundreds of families, given that the two pedigrees being evaluated are generational and mating is between external parents. We address two restricted versions of the unlabeled subpedigree graph problem, Cover Unlabeled subPedigree with a Bipartite graph (CUPB), and Cover Unlabeled subPedigree with a Path (CUPP) problems. Fixed parameter algorithms are presented to solve the two problems, CUPB and CUPP.
Avoiding traps in trajectory space: Metadynamics enhanced transition path sampling
NASA Astrophysics Data System (ADS)
Borrero, E. E.; Dellago, C.
2016-10-01
We propose a transition path sampling (TPS) scheme designed to enhance sampling in systems with multiple reaction channels. In this method, based on a combination of the metadynamics algorithm with the TPS shooting move, a history dependent bias drives the simulation towards unexplored reaction channels. The bias, constructed as a superposition of repulsive Gaussian potentials deposited on the trajectories harvested in the course of the simulation, acts only during the initial stage of the trajectory generation, but leaves the dynamics along the trajectories unaffected such that the sampled pathways are true dynamical trajectories. Simulations carried out for two test systems indicate that the new approach effortlessly switches between distinct reaction channels even if they are separated by high barriers in trajectory space.
Synthetic-Aperture Coherent Imaging From A Circular Path
NASA Technical Reports Server (NTRS)
Jin, Michael Y.
1995-01-01
Imaging algorithms based on exact point-target responses. Developed for use in reconstructing image of target from data gathered by radar, sonar, or other transmitting/receiving coherent-signal sensory apparatus following circular observation path around target. Potential applications include: Wide-beam synthetic-aperture radar (SAR) from aboard spacecraft in circular orbit around target planet; SAR from aboard airplane flying circular course at constant elevation around central ground point, toward which spotlight radar beam pointed; Ultrasonic reflection tomography in medical setting, using one transducer moving in circle around patient or else multiple transducers at fixed positions on circle around patient; and Sonar imaging of sea floor to high resolution, without need for large sensory apparatus.
Monitoring Java Programs with Java PathExplorer
NASA Technical Reports Server (NTRS)
Havelund, Klaus; Rosu, Grigore; Clancy, Daniel (Technical Monitor)
2001-01-01
We present recent work on the development Java PathExplorer (JPAX), a tool for monitoring the execution of Java programs. JPAX can be used during program testing to gain increased information about program executions, and can potentially furthermore be applied during operation to survey safety critical systems. The tool facilitates automated instrumentation of a program's late code which will then omit events to an observer during its execution. The observer checks the events against user provided high level requirement specifications, for example temporal logic formulae, and against lower level error detection procedures, for example concurrency related such as deadlock and data race algorithms. High level requirement specifications together with their underlying logics are defined in the Maude rewriting logic, and then can either be directly checked using the Maude rewriting engine, or be first translated to efficient data structures and then checked in Java.
Virtual coiling of intracranial aneurysms based on dynamic path planning.
Morales, Hernán G; Larrabide, Ignacio; Kim, Minsuok; Villa-Uriol, Maria-Cruz; Macho, Juan M; Blasco, Jordi; San Roman, Luis; Frangi, Alejandro F
2011-01-01
Coiling is possibly the most widespread endovascular treatment for intracranial aneurysms. It consists in the placement of metal wires inside the aneurysm to promote blood coagulation. This work presents a virtual coiling technique for pre-interventional planning and post-operative assessment of coil embolization procedure of aneurysms. The technique uses a dynamic path planning algorithm to mimic coil insertion inside a 3D aneurysm model, which allows to obtain a plausible distribution of coils within a patient-specific anatomy. The technique was tested on two idealized geometries: an sphere and a hexahedron. Subsequently, the proposed technique was applied in 10 realistic aneurysm geometries to show its reliability in anatomical models. The results of the technique was compared to digital substraction angiography images of two aneurysms.
Novel double path shearing interferometer in corneal topography measurements
NASA Astrophysics Data System (ADS)
Licznerski, Tomasz J.; Jaronski, Jaroslaw; Kosz, Dariusz
2005-09-01
The paper presents an approach for measurements of corneal topography by use of a patent pending double path shearing interferometer (DPSI). Laser light reflected from the surface of the cornea is divided and directed to the inputs of two interferometers. The interferometers use lateral shearing of wavefronts in two orthogonal directions. A tilt of one of the mirrors in each interferometric setup perpendicularly to the lateral shear introduces parallel carrier frequency fringes at the output of each interferometer. There is orthogonal linear polarization of the laser light used in two DPSI. Two images of fringe patters are recorded by a high resolution digital camera. The obtained fringe patterns are used for phase difference reconstruction. The phase of the wavefront was reconstructed by use of algorithms for a large grid based on discrete integration. The in vivo method can also be used for tear film stability measurement, artificial tears and contact lens tests.
Automatic Tool Path Generation for Robot Integrated Surface Sculpturing System
NASA Astrophysics Data System (ADS)
Zhu, Jiang; Suzuki, Ryo; Tanaka, Tomohisa; Saito, Yoshio
In this paper, a surface sculpturing system based on 8-axis robot is proposed, the CAD/CAM software and tool path generation algorithm for this sculpturing system are presented. The 8-axis robot is composed of a 6-axis manipulator and a 2-axis worktable, it carves block of polystyrene foams by heated cutting tools. Multi-DOF (Degree of Freedom) robot benefits from the faster fashion than traditional RP (Rapid Prototyping) methods and more flexibility than CNC machining. With its flexibility driven from an 8-axis configuration, as well as efficient custom-developed software for rough cutting and finish cutting, this surface sculpturing system can carve sculptured surface accurately and efficiently.
Java PathExplorer: A Runtime Verification Tool
NASA Technical Reports Server (NTRS)
Havelund, Klaus; Rosu, Grigore; Clancy, Daniel (Technical Monitor)
2001-01-01
We describe recent work on designing an environment called Java PathExplorer for monitoring the execution of Java programs. This environment facilitates the testing of execution traces against high level specifications, including temporal logic formulae. In addition, it contains algorithms for detecting classical error patterns in concurrent programs, such as deadlocks and data races. An initial prototype of the tool has been applied to the executive module of the planetary Rover K9, developed at NASA Ames. In this paper we describe the background and motivation for the development of this tool, including comments on how it relates to formal methods tools as well as to traditional testing, and we then present the tool itself.
A Novel Discrete Differential Evolution Algorithm for the Vehicle Routing Problem in B2C E-Commerce
NASA Astrophysics Data System (ADS)
Xia, Chao; Sheng, Ying; Jiang, Zhong-Zhong; Tan, Chunqiao; Huang, Min; He, Yuanjian
2015-12-01
In this paper, a novel discrete differential evolution (DDE) algorithm is proposed to solve the vehicle routing problems (VRP) in B2C e-commerce, in which VRP is modeled by the incomplete graph based on the actual urban road system. First, a variant of classical VRP is described and a mathematical programming model for the variant is given. Second, the DDE is presented, where individuals are represented as the sequential encoding scheme, and a novel reparation operator is employed to repair the infeasible solutions. Furthermore, a FLOYD operator for dealing with the shortest route is embedded in the proposed DDE. Finally, an extensive computational study is carried out in comparison with the predatory search algorithm and genetic algorithm, and the results show that the proposed DDE is an effective algorithm for VRP in B2C e-commerce.
Path Selection in a Poisson field
NASA Astrophysics Data System (ADS)
Cohen, Yossi; Rothman, Daniel H.
2016-11-01
A criterion for path selection for channels growing in a Poisson field is presented. We invoke a generalization of the principle of local symmetry. We then use this criterion to grow channels in a confined geometry. The channel trajectories reveal a self-similar shape as they reach steady state. Analyzing their paths, we identify a cause for branching that may result in a ramified structure in which the golden ratio appears.
A variational dynamic programming approach to robot-path planning with a distance-safety criterion
NASA Technical Reports Server (NTRS)
Suh, Suk-Hwan; Shin, Kang G.
1988-01-01
An approach to robot-path planning is developed by considering both the traveling distance and the safety of the robot. A computationally-efficient algorithm is developed to find a near-optimal path with a weighted distance-safety criterion by using a variational calculus and dynamic programming (VCDP) method. The algorithm is readily applicable to any factory environment by representing the free workspace as channels. A method for deriving these channels is also proposed. Although it is developed mainly for two-dimensional problems, this method can be easily extended to a class of three-dimensional problems. Numerical examples are presented to demonstrate the utility and power of this method.