ERIC Educational Resources Information Center
Shore, M. L.
1980-01-01
There are many uses for the shortest path algorithm presented which are limited only by our ability to recognize when a problem may be converted into the shortest path in a graph representation. (Author/TG)
An improved Physarum polycephalum algorithm for the shortest path problem.
Zhang, Xiaoge; Wang, Qing; Adamatzky, Andrew; Chan, Felix T S; Mahadevan, Sankaran; Deng, Yong
2014-01-01
Shortest path is among classical problems of computer science. The problems are solved by hundreds of algorithms, silicon computing architectures and novel substrate, unconventional, computing devices. Acellular slime mould P. polycephalum is originally famous as a computing biological substrate due to its alleged ability to approximate shortest path from its inoculation site to a source of nutrients. Several algorithms were designed based on properties of the slime mould. Many of the Physarum-inspired algorithms suffer from a low converge speed. To accelerate the search of a solution and reduce a number of iterations we combined an original model of Physarum-inspired path solver with a new a parameter, called energy. We undertook a series of computational experiments on approximating shortest paths in networks with different topologies, and number of nodes varying from 15 to 2000. We found that the improved Physarum algorithm matches well with existing Physarum-inspired approaches yet outperforms them in number of iterations executed and a total running time. We also compare our algorithm with other existing algorithms, including the ant colony optimization algorithm and Dijkstra algorithm. PMID:24982960
An Improved Physarum polycephalum Algorithm for the Shortest Path Problem
Wang, Qing; Adamatzky, Andrew; Chan, Felix T. S.; Mahadevan, Sankaran
2014-01-01
Shortest path is among classical problems of computer science. The problems are solved by hundreds of algorithms, silicon computing architectures and novel substrate, unconventional, computing devices. Acellular slime mould P. polycephalum is originally famous as a computing biological substrate due to its alleged ability to approximate shortest path from its inoculation site to a source of nutrients. Several algorithms were designed based on properties of the slime mould. Many of the Physarum-inspired algorithms suffer from a low converge speed. To accelerate the search of a solution and reduce a number of iterations we combined an original model of Physarum-inspired path solver with a new a parameter, called energy. We undertook a series of computational experiments on approximating shortest paths in networks with different topologies, and number of nodes varying from 15 to 2000. We found that the improved Physarum algorithm matches well with existing Physarum-inspired approaches yet outperforms them in number of iterations executed and a total running time. We also compare our algorithm with other existing algorithms, including the ant colony optimization algorithm and Dijkstra algorithm. PMID:24982960
An Effective Evolutionary Approach for Bicriteria Shortest Path Routing Problems
NASA Astrophysics Data System (ADS)
Lin, Lin; Gen, Mitsuo
Routing problem is one of the important research issues in communication network fields. In this paper, we consider a bicriteria shortest path routing (bSPR) model dedicated to calculating nondominated paths for (1) the minimum total cost and (2) the minimum transmission delay. To solve this bSPR problem, we propose a new multiobjective genetic algorithm (moGA): (1) an efficient chromosome representation using the priority-based encoding method; (2) a new operator of GA parameters auto-tuning, which is adaptively regulation of exploration and exploitation based on the change of the average fitness of parents and offspring which is occurred at each generation; and (3) an interactive adaptive-weight fitness assignment mechanism is implemented that assigns weights to each objective and combines the weighted objectives into a single objective function. Numerical experiments with various scales of network design problems show the effectiveness and the efficiency of our approach by comparing with the recent researches.
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 role of convexity for solving some shortest path problems in plane without triangulation
NASA Astrophysics Data System (ADS)
An, Phan Thanh; Hai, Nguyen Ngoc; Hoai, Tran Van
2013-09-01
Solving shortest path problems inside simple polygons is a very classical problem in motion planning. To date, it has usually relied on triangulation of the polygons. The question: "Can one devise a simple O(n) time algorithm for computing the shortest path between two points in a simple polygon (with n vertices), without resorting to a (complicated) linear-time triangulation algorithm?" raised by J. S. B. Mitchell in Handbook of Computational Geometry (J. Sack and J. Urrutia, eds., Elsevier Science B.V., 2000), is still open. The aim of this paper is to show that convexity contributes to the design of efficient algorithms for solving some versions of shortest path problems (namely, computing the convex hull of a finite set of points and convex rope on rays in 2D, computing approximate shortest path between two points inside a simple polygon) without triangulation on the entire polygons. New algorithms are implemented in C and numerical examples are presented.
Shortest Paths between Shortest Paths and Independent Sets
NASA Astrophysics Data System (ADS)
Kamiński, Marcin; Medvedev, Paul; Milanič, Martin
We study problems of reconfiguration of shortest paths in graphs. We prove that the shortest reconfiguration sequence can be exponential in the size of the graph and that it is NP-hard to compute the shortest reconfiguration sequence even when we know that the sequence has polynomial length. Moreover, we also study reconfiguration of independent sets in three different models and analyze relationships between these models, observing that shortest path reconfiguration is a special case of independent set reconfiguration in perfect graphs, under any of the three models. Finally, we give polynomial results for restricted classes of graphs (even-hole-free and P 4-free graphs).
An Evaluation of Potentials of Genetic Algorithm in Shortest Path Problem
NASA Astrophysics Data System (ADS)
Hassany Pazooky, S.; Rahmatollahi Namin, Sh; Soleymani, A.; Samadzadegan, F.
2009-04-01
One of the most typical issues considered in combinatorial systems in transportation networks, is the shortest path problem. In such networks, routing has a significant impact on the network's performance. Due to natural complexity in transportation networks and strong impact of routing in different fields of decision making, such as traffic management and vehicle routing problem (VRP), appropriate solutions to solve this problem are crucial to be determined. During last years, in order to solve the shortest path problem, different solutions are proposed. These techniques are divided into two categories of classic and evolutionary approaches. Two well-known classic algorithms are Dijkstra and A*. Dijkstra is known as a robust, but time consuming algorithm in finding the shortest path problem. A* is also another algorithm very similar to Dijkstra, less robust but with a higher performance. On the other hand, Genetic algorithms are introduced as most applicable evolutionary algorithms. Genetic Algorithm uses a parallel search method in several parts of the domain and is not trapped in local optimums. In this paper, the potentiality of Genetic algorithm for finding the shortest path is evaluated by making a comparison between this algorithm and classic algorithms (Dijkstra and A*). Evaluation of the potential of these techniques on a transportation network in an urban area shows that due to the problem of classic methods in their small search space, GA had a better performance in finding the shortest path.
A Bio-Inspired Method for the Constrained Shortest Path Problem
Wang, Hongping; Lu, Xi; Wang, Qing
2014-01-01
The constrained shortest path (CSP) problem has been widely used in transportation optimization, crew scheduling, network routing and so on. It is an open issue since it is a NP-hard problem. In this paper, we propose an innovative method which is based on the internal mechanism of the adaptive amoeba algorithm. The proposed method is divided into two parts. In the first part, we employ the original amoeba algorithm to solve the shortest path problem in directed networks. In the second part, we combine the Physarum algorithm with a bio-inspired rule to deal with the CSP. Finally, by comparing the results with other method using an examples in DCLC problem, we demonstrate the accuracy of the proposed method. PMID:24959603
The 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.
Parallel shortest augmenting path algorithm for the assignment problem. Technical report
Balas, E.; Miller, D.; Pekny, J.; Toth, P.
1989-04-01
We describe a parallel version of the shortest augmenting path algorithm for the assignment problem. While generating the initial dual solution and partial assignment in parallel does not require substantive changes in the sequential algorithm, using several augmenting paths in parallel does require a new dual variable recalculation method. The parallel algorithm was tested on a 14-processor Butterfly Plus computer, on problems with up to 900 million variables. The speedup obtained increases with problem size. The algorithm was also embedded into a parallel branch and bound procedure for the traveling salesman problem on a directed graph, which was tested on the Butterfly Plus on problems involving up to 7,500 cities. To our knowledge, these are the largest assignment problems and traveling salesman problems solved so far.
Physarum can compute shortest paths.
Bonifaci, Vincenzo; Mehlhorn, Kurt; Varma, Girish
2012-09-21
Physarum polycephalum is a slime mold that is apparently able to solve shortest path problems. A mathematical model has been proposed by Tero et al. (Journal of Theoretical Biology, 244, 2007, pp. 553-564) to describe the feedback mechanism used by the slime mold to adapt its tubular channels while foraging two food sources s(0) and s(1). We prove that, under this model, the mass of the mold will eventually converge to the shortest s(0)-s(1) path of the network that the mold lies on, independently of the structure of the network or of the initial mass distribution. This matches the experimental observations by Tero et al. and can be seen as an example of a "natural algorithm", that is, an algorithm developed by evolution over millions of years. PMID:22732274
A minimum resource neural network framework for solving multiconstraint shortest path problems.
Zhang, Junying; Zhao, Xiaoxue; He, Xiaotao
2014-08-01
Characterized by using minimum hard (structural) and soft (computational) resources, a novel parameter-free minimal resource neural network (MRNN) framework is proposed for solving a wide range of single-source shortest path (SP) problems for various graph types. The problems are the k-shortest time path problems with any combination of three constraints: time, hop, and label constraints, and the graphs can be directed, undirected, or bidirected with symmetric and/or asymmetric traversal time, which can be real and time dependent. Isomorphic to the graph where the SP is to be sought, the network is activated by generating autowave at source neuron and the autowave travels automatically along the paths with the speed of a hop in an iteration. Properties of the network are studied, algorithms are presented, and computation complexity is analyzed. The framework guarantees globally optimal solutions of a series of problems during the iteration process of the network, which provides insight into why even the SP is still too long to be satisfied. The network facilitates very large scale integrated circuit implementation and adapt to very large scale problems due to its massively parallel processing and minimum resource utilization. When implemented in a sequentially processing computer, experiments on synthetic graphs, road maps of cities of the USA, and vehicle routing with time windows indicate that the MRNN is especially efficient for large scale sparse graphs and even dense graphs with some constraints, e.g., the CPU time taken and the iteration number used for the road maps of cities of the USA is even less than ∼ 2% and 0.5% that of the Dijkstra's algorithm. PMID:25050952
NASA Astrophysics Data System (ADS)
Yu, Feng; Li, Yanjun; Wu, Tie-Jun
2010-02-01
A large number of networks in the real world have a scale-free structure, and the parameters of the networks change stochastically with time. Searching for the shortest paths in a scale-free dynamic and stochastic network is not only necessary for the estimation of the statistical characteristics such as the average shortest path length of the network, but also challenges the traditional concepts related to the “shortest path” of a network and the design of path searching strategies. In this paper, the concept of shortest path is defined on the basis of a scale-free dynamic and stochastic network model, and a temporal ant colony optimization (TACO) algorithm is proposed for searching for the shortest paths in the network. The convergence and the setup for some important parameters of the TACO algorithm are discussed through theoretical analysis and computer simulations, validating the effectiveness of the proposed algorithm.
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
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.
Multiple Object Tracking Using the Shortest Path Faster Association Algorithm
Liu, Heping; Liu, Huaping; Yang, Bin
2014-01-01
To solve the persistently multiple object tracking in cluttered environments, this paper presents a novel tracking association approach based on the shortest path faster algorithm. First, the multiple object tracking is formulated as an integer programming problem of the flow network. Then we relax the integer programming to a standard linear programming problem. Therefore, the global optimum can be quickly obtained using the shortest path faster algorithm. The proposed method avoids the difficulties of integer programming, and it has a lower worst-case complexity than competing methods but better robustness and tracking accuracy in complex environments. Simulation results show that the proposed algorithm takes less time than other state-of-the-art methods and can operate in real time. PMID:25215322
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. PMID:26355788
Corridor location: the multi-gateway shortest path model
NASA Astrophysics Data System (ADS)
Scaparra, Maria P.; Church, Richard L.; Medrano, F. Antonio
2014-07-01
The problem of corridor location can be found in a number of fields including power transmission, highways, and pipelines. It involves the placement of a corridor or rights-of-way that traverses a landscape starting at an origin and ending at a destination. Since most systems are subject to environmental review, it is important to generate competitive, but different alternatives. This paper addresses the problem of generating efficient, spatially different alternatives to the corridor location problem. We discuss the weaknesses in current models and propose a new approach which is designed to overcome many of these problems. We present an application of this model to a real landscape and compare the results to past work. Overall, the new model called the multi-gateway shortest path problem can generate a wide variety of efficient alignments, which eclipse what could be generated by past work.
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
A shortest path algorithm for satellite time-varying topological network
NASA Astrophysics Data System (ADS)
Zhang, Tao; Liu, Zhongkan; Zhuang, Jun
2005-11-01
Mobile satellite network is a special time-varying network. It is different from the classical fixed network and other time-dependent networks which have been studied. Therefore some classical network theories, such as the shortest path algorithm, can not be applied to it availably. However, no study about its shortest path problem has been done. In this paper, based on the proposed model of satellite time-varying topological network, the classical shortest path algorithm of fixed network, such as the Dijkstra algorithm, is proved to be restrictive when it is applied in satellite network. Here, a novel shortest path algorithm for satellite time-varying topological network is given and optimized. Correlative simulation indicates that this algorithm can be effectively applied to the satellite time-varying topological network.
Optimal Design of Pipeline Based on the Shortest Path
NASA Astrophysics Data System (ADS)
Chu, Fei-xue; Chen, Shi-yi
Design and operation of long-distance pipeline are complex engineering tasks. Even small improvement in the design of a pipeline system can lead to substantial savings in capital. In this paper, graph theory was used to analyze the problem of pipeline optimal design. The candidate pump station locations were taken as the vertexes and the total cost of the pipeline system between the two vertexes corresponded to the edge weight. An algorithm recursively calling the Dijkstra algorithm was designed and analyzed to obtain N shortest paths. The optimal process program and the quasi-optimal process programs were obtained at the same time, which could be used in decision-making. The algorithm was tested by a real example. The result showed that it could meet the need of real application.
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
Tree-based shortest-path routing algorithm
NASA Astrophysics Data System (ADS)
Long, Y. H.; Ho, T. K.; Rad, A. B.; Lam, S. P. S.
1998-12-01
A tree-based shortest path routing algorithm is introduced in this paper. With this algorithm, every network node can maintain a shortest path routing tree topology of the network with itself as the root. In this algorithm, every node constructs its own routing tree based upon its neighbors' routing trees. Initially, the routing tree at each node has the root only, the node itself. As information exchanges, every node's routing tree will evolve until a complete tree is obtained. This algorithm is a trade-off between distance vector algorithm and link state algorithm. Loops are automatically deleted, so there is no count-to- infinity effect. A simple routing tree information storage approach and a protocol data until format to transmit the tree information are given. Some special issues, such as adaptation to topology change, implementation of the algorithm on LAN, convergence and computation overhead etc., are also discussed in the paper.
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.
von Thienen, Wolfhard; Metzler, Dirk; Witte, Volker
2015-05-01
The emergence of self-organizing behavior in ants has been modeled in various theoretical approaches in the past decades. One model explains experimental observations in which Argentine ants (Linepithema humile) selected the shorter of two alternative paths from their nest to a food source (shortest path experiments). This model serves as an important example for the emergence of collective behavior and self-organization in biological systems. In addition, it inspired the development of computer algorithms for optimization problems called ant colony optimization (ACO). In the model, a choice function describing how ants react to different pheromone concentrations is fundamental. However, the parameters of the choice function were not deduced experimentally but freely adapted so that the model fitted the observations of the shortest path experiments. Thus, important knowledge was lacking about crucial model assumptions. A recent study on the Argentine ant provided this information by measuring the response of the ants to varying pheromone concentrations. In said study, the above mentioned choice function was fitted to the experimental data and its parameters were deduced. In addition, a psychometric function was fitted to the data and its parameters deduced. Based on these findings, it is possible to test the shortest path model by applying realistic parameter values. Here we present the results of such tests using Monte Carlo simulations of shortest path experiments with Argentine ants. We compare the choice function and the psychometric function, both with parameter values deduced from the above-mentioned experiments. Our results show that by applying the psychometric function, the shortest path experiments can be explained satisfactorily by the model. The study represents the first example of how psychophysical theory can be used to understand and model collective foraging behavior of ants based on trail pheromones. These findings may be important for other
Damage detection via shortest-path network sampling
NASA Astrophysics Data System (ADS)
Ciulla, Fabio; Perra, Nicola; Baronchelli, Andrea; Vespignani, Alessandro
2014-05-01
Large networked systems are constantly exposed to local damages and failures that can alter their functionality. The knowledge of the structure of these systems is, however, often derived through sampling strategies whose effectiveness at damage detection has not been thoroughly investigated so far. Here, we study the performance of shortest-path sampling for damage detection in large-scale networks. We define appropriate metrics to characterize the sampling process before and after the damage, providing statistical estimates for the status of nodes (damaged, not damaged). The proposed methodology is flexible and allows tuning the trade-off between the accuracy of the damage detection and the number of probes used to sample the network. We test and measure the efficiency of our approach considering both synthetic and real networks data. Remarkably, in all of the systems studied, the number of correctly identified damaged nodes exceeds the number of false positives, allowing us to uncover the damage precisely.
A Hybrid Shortest Path Algorithm for Navigation System
NASA Astrophysics Data System (ADS)
Cho, Hsun-Jung; Lan, Chien-Lun
2007-12-01
Combined with Geographic Information System (GIS) and Global Positioning System (GPS), the vehicle navigation system had become a quite popular product in daily life. A key component of the navigation system is the Shortest Path Algorithm. Navigation in real world must face a network consists of tens of thousands nodes and links, and even more. Under the limited computation capability of vehicle navigation equipment, it is difficult to satisfy the realtime response requirement that user expected. Hence, this study focused on shortest path algorithm that enhances the computation speed with less memory requirement. Several well-known algorithms such as Dijkstra, A* and hierarchical concepts were integrated to build hybrid algorithms that reduce searching space and improve searching speed. Numerical examples were conducted on Taiwan highway network that consists of more than four hundred thousands of links and nearly three hundred thousands of nodes. This real network was divided into two connected sub-networks (layers). The upper layer is constructed by freeways and expressways; the lower layer is constructed by local networks. Test origin-destination pairs were chosen randomly and divided into three distance categories; short, medium and long distances. The evaluation of outcome is judged by actual length and travel time. The numerical example reveals that the hybrid algorithm proposed by this research might be tens of thousands times faster than traditional Dijkstra algorithm; the memory requirement of the hybrid algorithm is also much smaller than the tradition algorithm. This outcome shows that this proposed algorithm would have an advantage over vehicle navigation system.
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.
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.
Training shortest-path tractography: Automatic learning of spatial priors.
Kasenburg, Niklas; Liptrot, Matthew; Reislev, Nina Linde; Ørting, Silas N; Nielsen, Mads; Garde, Ellen; Feragen, Aasa
2016-04-15
Tractography is the standard tool for automatic delineation of white matter tracts from diffusion weighted images. However, the output of tractography often requires post-processing to remove false positives and ensure a robust delineation of the studied tract, and this demands expert prior knowledge. Here we demonstrate how such prior knowledge, or indeed any prior spatial information, can be automatically incorporated into a shortest-path tractography approach to produce more robust results. We describe how such a prior can be automatically generated (learned) from a population, and we demonstrate that our framework also retains support for conventional interactive constraints such as waypoint regions. We apply our approach to the open access, high quality Human Connectome Project data, as well as a dataset acquired on a typical clinical scanner. Our results show that the use of a learned prior substantially increases the overlap of tractography output with a reference atlas on both populations, and this is confirmed by visual inspection. Furthermore, we demonstrate how a prior learned on the high quality dataset significantly increases the overlap with the reference for the more typical yet lower quality data acquired on a clinical scanner. We hope that such automatic incorporation of prior knowledge and the obviation of expert interactive tract delineation on every subject, will improve the feasibility of large clinical tractography studies. PMID:26804779
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.
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. PMID:24010024
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. PMID:23144039
Performance of Thorup's Shortest Path Algorithm for Large-Scale Network Simulation
NASA Astrophysics Data System (ADS)
Sakumoto, Yusuke; Ohsaki, Hiroyuki; Imase, Makoto
In this paper, we investigate the performance of Thorup's algorithm by comparing it to Dijkstra's algorithm for large-scale network simulations. One of the challenges toward the realization of large-scale network simulations is the efficient execution to find shortest paths in a graph with N vertices and M edges. The time complexity for solving a single-source shortest path (SSSP) problem with Dijkstra's algorithm with a binary heap (DIJKSTRA-BH) is O((M+N)log N). An sophisticated algorithm called Thorup's algorithm has been proposed. The original version of Thorup's algorithm (THORUP-FR) has the time complexity of O(M+N). A simplified version of Thorup's algorithm (THORUP-KL) has the time complexity of O(Mα(N)+N) where α(N) is the functional inverse of the Ackerman function. In this paper, we compare the performances (i.e., execution time and memory consumption) of THORUP-KL and DIJKSTRA-BH since it is known that THORUP-FR is at least ten times slower than Dijkstra's algorithm with a Fibonaccii heap. We find that (1) THORUP-KL is almost always faster than DIJKSTRA-BH for large-scale network simulations, and (2) the performances of THORUP-KL and DIJKSTRA-BH deviate from their time complexities due to the presence of the memory cache in the microprocessor.
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.
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
Li, Longxiang; Gong, Jianhua; Zhou, Jieping
2014-01-01
Effective assessments of air-pollution exposure depend on the ability to accurately predict pollutant concentrations at unmonitored locations, which can be achieved through spatial interpolation. However, most interpolation approaches currently in use are based on the Euclidean distance, which cannot account for the complex nonlinear features displayed by air-pollution distributions in the wind-field. In this study, an interpolation method based on the shortest path distance is developed to characterize the impact of complex urban wind-field on the distribution of the particulate matter concentration. In this method, the wind-field is incorporated by first interpolating the observed wind-field from a meteorological-station network, then using this continuous wind-field to construct a cost surface based on Gaussian dispersion model and calculating the shortest wind-field path distances between locations, and finally replacing the Euclidean distances typically used in Inverse Distance Weighting (IDW) with the shortest wind-field path distances. This proposed methodology is used to generate daily and hourly estimation surfaces for the particulate matter concentration in the urban area of Beijing in May 2013. This study demonstrates that wind-fields can be incorporated into an interpolation framework using the shortest wind-field path distance, which leads to a remarkable improvement in both the prediction accuracy and the visual reproduction of the wind-flow effect, both of which are of great importance for the assessment of the effects of pollutants on human health. PMID:24798197
Li, Longxiang; Gong, Jianhua; Zhou, Jieping
2014-01-01
Effective assessments of air-pollution exposure depend on the ability to accurately predict pollutant concentrations at unmonitored locations, which can be achieved through spatial interpolation. However, most interpolation approaches currently in use are based on the Euclidean distance, which cannot account for the complex nonlinear features displayed by air-pollution distributions in the wind-field. In this study, an interpolation method based on the shortest path distance is developed to characterize the impact of complex urban wind-field on the distribution of the particulate matter concentration. In this method, the wind-field is incorporated by first interpolating the observed wind-field from a meteorological-station network, then using this continuous wind-field to construct a cost surface based on Gaussian dispersion model and calculating the shortest wind-field path distances between locations, and finally replacing the Euclidean distances typically used in Inverse Distance Weighting (IDW) with the shortest wind-field path distances. This proposed methodology is used to generate daily and hourly estimation surfaces for the particulate matter concentration in the urban area of Beijing in May 2013. This study demonstrates that wind-fields can be incorporated into an interpolation framework using the shortest wind-field path distance, which leads to a remarkable improvement in both the prediction accuracy and the visual reproduction of the wind-flow effect, both of which are of great importance for the assessment of the effects of pollutants on human health. PMID:24798197
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
Do People Use the Shortest Path? An Empirical Test of Wardrop’s First Principle
Zhu, Shanjiang; Levinson, David
2015-01-01
Most recent route choice models, following either the random utility maximization or rule-based paradigm, require explicit enumeration of feasible routes. The quality of model estimation and prediction is sensitive to the appropriateness of the consideration set. However, few empirical studies of revealed route characteristics have been reported in the literature. This study evaluates the widely applied shortest path assumption by evaluating routes followed by residents of the Minneapolis—St. Paul metropolitan area. Accurate Global Positioning System (GPS) and Geographic Information System (GIS) data were employed to reveal routes people used over an eight to thirteen week period. Most people did not choose the shortest path. Using three weeks of that data, we find that current route choice set generation algorithms do not reveal the majority of paths that individuals took. Findings from this study may guide future efforts in building better route choice models. PMID:26267756
Do people use the shortest path? An empirical test of Wardrop's first principle.
Zhu, Shanjiang; Levinson, David
2015-01-01
Most recent route choice models, following either the random utility maximization or rule-based paradigm, require explicit enumeration of feasible routes. The quality of model estimation and prediction is sensitive to the appropriateness of the consideration set. However, few empirical studies of revealed route characteristics have been reported in the literature. This study evaluates the widely applied shortest path assumption by evaluating routes followed by residents of the Minneapolis-St. Paul metropolitan area. Accurate Global Positioning System (GPS) and Geographic Information System (GIS) data were employed to reveal routes people used over an eight to thirteen week period. Most people did not choose the shortest path. Using three weeks of that data, we find that current route choice set generation algorithms do not reveal the majority of paths that individuals took. Findings from this study may guide future efforts in building better route choice models. PMID:26267756
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. Proteins 2016; 84:467-472. © 2016 Wiley Periodicals, Inc. PMID:26800480
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.
Modeling the average shortest-path length in growth of word-adjacency networks.
Kulig, Andrzej; Drożdż, Stanisław; Kwapień, Jarosław; Oświȩcimka, 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. PMID:25871160
Task-parallel implementation of 3D shortest path raytracing for geophysical applications
NASA Astrophysics Data System (ADS)
Giroux, Bernard; Larouche, Benoît
2013-04-01
This paper discusses two variants of the shortest path method and their parallel implementation on a shared-memory system. One variant is designed to perform raytracing in models with stepwise distributions of interval velocity while the other is better suited for continuous velocity models. Both rely on a discretization scheme where primary nodes are located at the corners of cuboid cells and where secondary nodes are found on the edges and sides of the cells. The parallel implementations allow raytracing concurrently for different sources, providing an attractive framework for ray-based tomography. The accuracy and performance of the implementations were measured by comparison with the analytic solution for a layered model and for a vertical gradient model. Mean relative error less than 0.2% was obtained with 5 secondary nodes for the layered model and 9 secondary nodes for the gradient model. Parallel performance depends on the level of discretization refinement, on the number of threads, and on the problem size, with the most determinant variable being the level of discretization refinement (number of secondary nodes). The results indicate that a good trade-off between speed and accuracy is achieved with the number of secondary nodes equal to 5. The programs are written in C++ and rely on the Standard Template Library and OpenMP.
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)
Schafer, Sebastian; Singh, Vikas; Hoffmann, Kenneth R.; Noël, Peter B.; Xu, Jinhui
2007-03-01
Endovascular interventional procedures are being used more frequently in cardiovascular surgery. Unfortunately, procedural failure, e.g., vessel dissection, may occur and is often related to improper guidewire and/or device selection. To support the surgeon's decision process and because of the importance of the guidewire in positioning devices, we propose a method to determine the guidewire path prior to insertion using a model of its elastic potential energy coupled with a representative graph construction. The 3D vessel centerline and sizes are determined for a specified vessel. Points in planes perpendicular to the vessel centerline are generated. For each pair of consecutive planes, a vector set is generated which joins all points in these planes. We construct a graph representing these vector sets as nodes. The nodes representing adjacent vector sets are joined by edges with weights calculated as a function of the angle between the corresponding vectors (nodes). The optimal path through this weighted directed graph is then determined using shortest path algorithms, such as topological sort based shortest path algorithm or Dijkstra's algorithm. Volumetric data of an internal carotid artery phantom (Ø 3.5mm) were acquired. Several independent guidewire (Ø 0.4mm) placements were performed, and the 3D paths were determined using rotational angiography. The average RMS distance between the actual and the average simulated guidewire path was 0.7mm; the computation time to determine the path was 3 seconds. The ability to predict the guidewire path inside vessels may facilitate calculation of vessel-branch access and force estimation on devices and the vessel wall.
An improved real-time endovascular guidewire position simulation using shortest path algorithm.
Qiu, Jianpeng; Qu, Zhiyi; Qiu, Haiquan; Zhang, Xiaomin
2016-09-01
In this study, we propose a new graph-theoretical method to simulate guidewire paths inside the carotid artery. The minimum energy guidewire path can be obtained by applying the shortest path algorithm, such as Dijkstra's algorithm for graphs, based on the principle of the minimal total energy. Compared to previous results, experiments of three phantoms were validated, revealing that the first and second phantoms overlap completely between simulated and real guidewires. In addition, 95 % of the third phantom overlaps completely, and the remaining 5 % closely coincides. The results demonstrate that our method achieves 87 and 80 % improvements for the first and third phantoms under the same conditions, respectively. Furthermore, 91 % improvements were obtained for the second phantom under the condition with reduced graph construction complexity. PMID:26467345
Freight Network Modeling System. Volume IV. Shortest-Path Analysis and Display user's guide
Not Available
1985-04-01
The Freight Network Modeling System (FNEM) is a general and flexible modeling system designed to have wide applicability to a variety of freight transportation analyses. The system consists of compatible network data bases, data management software, models of freight transportation, report generators, and graphics output. In many studies, a model as comprehensive as FNEM is not required. The second model, Shortest-Path Analysis and Display (SPAD), is a simpler model that optimizes routings of single shipments. The routing criteria that can be used are numerous - including minimizing cost, minimizing delay, minimizing population exposure (useful when considering shipments of hazardous materials), and minimizing accident risk. In addition to the above criteria, the routes can also be restricted to those with clearance for oversized loads or with sufficient load capabilities. SPAD can be used interactively and the routes can be displayed graphically. This volume contains a user's guide for SPAD including preprocessor programs and SPAD execution. 7 figs., 19 tabs.
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
Hua, Lei; 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
NASA Astrophysics Data System (ADS)
Ben Haddou, N.; Ez-zahraouy, H.; Rachadi, A.
2016-07-01
The shortest path is a basic routing model which is still used in many systems. However, due to the low exploitation of the delivery capacity of peripheral nodes, the performance achieved by this policy is very limited. Starting from the fact that changing all network routers by others more robust is not practical, we propose the improvement of the capacity of a scale-free network under the shortest path strategy by the implantation of global dynamic routers. We have studied two targeting approaches to designate specific nodes to route the packets following the global dynamic protocol; one is based on node degree and the other on its betweenness. We show that we already exceed twice the capacity under the shortest path protocol with only 4% of global dynamic routers when we target nodes with high betweenness and 10% when we target nodes with high degrees. Moreover, the average travelling time remains low while the network capacity increases.
Identification of Thyroid Carcinoma Related Genes with mRMR and Shortest Path Approaches
Ji, Zhenhua; Liu, Haibin; Liu, Yueyang; Peng, Hu; Wu, Jian; Fan, Jingping
2014-01-01
Thyroid cancer is a malignant neoplasm originated from thyroid cells. It can be classified into papillary carcinomas (PTCs) and anaplastic carcinomas (ATCs). Although ATCs are in an very aggressive status and cause more death than PTCs, their difference is poorly understood at molecular level. In this study, we focus on the transcriptome difference among PTCs, ATCs and normal tissue from a published dataset including 45 normal tissues, 49 PTCs and 11 ATCs, by applying a machine learning method, maximum relevance minimum redundancy, and identified 9 genes (BCL2, MRPS31, ID4, RASAL2, DLG2, MY01B, ZBTB5, PRKCQ and PPP6C) and 1 miscRNA (miscellaneous RNA, LOC646736) as important candidates involved in the progression of thyroid cancer. We further identified the protein-protein interaction (PPI) sub network from the shortest paths among the 9 genes in a PPI network constructed based on STRING database. Our results may provide insights to the molecular mechanism of the progression of thyroid cancer. PMID:24718460
NASA Astrophysics Data System (ADS)
Wu, Zikai; Hou, Baoyu; Zhang, Hongjuan; Jin, Feng
2014-04-01
Deterministic network models have been attractive media for discussing dynamical processes' dependence on network structural features. On the other hand, the heterogeneity of weights affect dynamical processes taking place on networks. In this paper, we present a family of weighted expanded Koch networks based on Koch networks. They originate from a r-polygon, and each node of current generation produces m r-polygons including the node and whose weighted edges are scaled by factor w in subsequent evolutionary step. We derive closed-form expressions for average weighted shortest path length (AWSP). In large network, AWSP stays bounded with network order growing (0 < w < 1). Then, we focus on a special random walks and trapping issue on the networks. In more detail, we calculate exactly the average receiving time (ART). ART exhibits a sub-linear dependence on network order (0 < w < 1), which implies that nontrivial weighted expanded Koch networks are more efficient than un-weighted expanded Koch networks in receiving information. Besides, efficiency of receiving information at hub nodes is also dependent on parameters m and r. These findings may pave the way for controlling information transportation on general weighted networks.
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.
NASA Astrophysics Data System (ADS)
Huang, Guo-Jiao; Bai, Chao-Ying; Greenhalgh, Stewart
2013-09-01
The traditional grid/cell-based wavefront expansion algorithms, such as the shortest path algorithm, can only find the first arrivals or multiply reflected (or mode converted) waves transmitted from subsurface interfaces, but cannot calculate the other later reflections/conversions having a minimax time path. In order to overcome the above limitations, we introduce the concept of a stationary minimax time path of Fermat's Principle into the multistage irregular shortest path method. Here we extend it from Cartesian coordinates for a flat earth model to global ray tracing of multiple phases in a 3-D complex spherical earth model. The ray tracing results for 49 different kinds of crustal, mantle and core phases show that the maximum absolute traveltime error is less than 0.12 s and the average absolute traveltime error is within 0.09 s when compared with the AK135 theoretical traveltime tables for a 1-D reference model. Numerical tests in terms of computational accuracy and CPU time consumption indicate that the new scheme is an accurate, efficient and a practical way to perform 3-D multiphase arrival tracking in regional or global traveltime tomography.
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.
Calculation of the shortest-time path for traversal of an obstacle course by a robot
NASA Astrophysics Data System (ADS)
Khar, Rishi T.; Hall, Ernest L.
2004-10-01
The problem of sequencing the movement of a robot so that it can carry out a given task in the minimum required time is of considerable importance, because of the efficiency of such a solution. The problem considered is an application of this idea, as applied to the context of the Navigation Challenge in the International Guided Vehicle Competition (IGVC). The objective is to find a sequence of points and a path in space that the robot has to traverse in order to complete the objective of the competition. A mathematical programming based model and example solution for the Bearcat Robot is given. The challenge in this event is for a robot to autonomously travel, using Differential GPS, from a starting point to a number of target destinations, while recognizing and avoiding the obstacles present, given only a map showing the coordinates of those targets, in the least possible time. The solution can be implemented easily using the Excel Solver, or AMPL. These solutions are practically applicable and easy to run in the competition since they give the sequence of points to be followed. In addition, the program is used together with a heuristic for situations where there are velocity constraints on the robot.
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
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
Yuan, Fei; Zhang, Yu-Hang; Wan, Sibao; Wang, ShaoPeng; Kong, Xiang-Yin
2015-01-01
Pancreatic cancer (PC) is a highly malignant tumor derived from pancreas tissue and is one of the leading causes of death from cancer. Its molecular mechanism has been partially revealed by validating its oncogenes and tumor suppressor genes; however, the available data remain insufficient for medical workers to design effective treatments. Large-scale identification of PC-related genes can promote studies on PC. In this study, we propose a computational method for mining new candidate PC-related genes. A large network was constructed using protein-protein interaction information, and a shortest path approach was applied to mine new candidate genes based on validated PC-related genes. In addition, a permutation test was adopted to further select key candidate genes. Finally, for all discovered candidate genes, the likelihood that the genes are novel PC-related genes is discussed based on their currently known functions. PMID:26613085
Yuan, Fei; Zhou, You; Wang, Meng; Yang, Jing; Wu, Kai; Lu, Changhong; Kong, Xiangyin; Cai, Yu-Dong
2015-01-01
Prostate cancer is a type of cancer that occurs in the male prostate, a gland in the male reproductive system. Because prostate cancer cells may spread to other parts of the body and can influence human reproduction, understanding the mechanisms underlying this disease is critical for designing effective treatments. The identification of as many genes and chemicals related to prostate cancer as possible will enhance our understanding of this disease. In this study, we proposed a computational method to identify new candidate genes and chemicals based on currently known genes and chemicals related to prostate cancer by applying a shortest path approach in a hybrid network. The hybrid network was constructed according to information concerning chemical-chemical interactions, chemical-protein interactions, and protein-protein interactions. Many of the obtained genes and chemicals are associated with prostate cancer. PMID:26504486
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
Magnetic Response in 1d Non-Interacting Mesoscopic Rings:. Long-Range Hopping in Shortest Path
NASA Astrophysics Data System (ADS)
Maiti, Santanu K.
Persistent current and low-field magnetic susceptibility in single-channel normal metal rings threaded by a magnetic flux ϕ are studied in the tight-binding model considering long-range hopping of the electrons in shortest path. The higher order hopping integrals try to reduce the effect of disorder by delocalizing the energy eigenstates and accordingly, current amplitude in disordered rings is comparable to that of an ordered ring. The calculations of low-field magnetic susceptibility predict that the sign of the currents can be mentioned precisely for the rings with fixed number of electrons even in the presence of impurity in the rings. At low-fields current shows only diamagnetic sign in perfect rings irrespective of the total number of electrons, Ne. On the other hand, in disordered rings it exhibits diamagnetic and paramagnetic sign, respectively, for the rings with odd and even Ne. In the rings described by fixed chemical potentials μ, the sign of the low-field currents cannot be predicted precisely since then it strongly depends on the values of μ and the specific realizations of disordered configurations.
NASA Astrophysics Data System (ADS)
Meyer, Ulrich; Negoescu, Andrei; Weichert, Volker
Despite disillusioning worst-case behavior, classic algorithms for single-source shortest-paths (SSSP) like Bellman-Ford are still being used in practice, especially due to their simple data structures. However, surprisingly little is known about the average-case complexity of these approaches. We provide new theoretical and experimental results for the performance of classic label-correcting SSSP algorithms on graph classes with non-negative random edge weights. In particular, we prove a tight lower bound of Ω(n 2) for the running times of Bellman-Ford on a class of sparse graphs with O(n) nodes and edges; the best previous bound was Ω(n 4/3 - ɛ ). The same improvements are shown for Pallottino's algorithm. We also lift a lower bound for the approximate bucket implementation of Dijkstra's algorithm from Ω(n logn / loglogn) to Ω(n 1.2 - ɛ ). Furthermore, we provide an experimental evaluation of our new graph classes in comparison with previously used test inputs.
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
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.
DNA computing the Hamiltonian path problem.
Lee, C M; Kim, S W; Kim, S M; Sohn, U
1999-10-31
The directed Hamiltonian path (DHP) problem is one of the hard computational problems for which there is no practical algorithm on a conventional computer available. Many problems, including the traveling sales person problem and the longest path problem, can be translated into the DHP problem, which implies that an algorithm for DHP can also solve all the translated problems. To study the robustness of the laboratory protocol of the pioneering DNA computing for the DHP problem performed by Leonard Adleman (1994), we investigated how the graph size, multiplicity of the Hamiltonian paths, and the size of oligonucleotides that encode the vertices would affect the laboratory procedures. We applied Adleman's protocol with 18-mer oligonucleotide per node to a graph with 8 vertices and 14 edges containing two Hamiltonian paths (Adleman used 20-mer oligonucleotides for a graph with 7 nodes, 14 edges and one Hamiltonian path). We found that depending on the graph characteristics such as the number of short cycles, the oligonucleotide size, and the hybridization conditions that used to encode the graph, the protocol should be executed with different parameters from Adleman's. PMID:10597033
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
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
Gap Filling as Exact Path Length Problem.
Salmela, Leena; Sahlin, Kristoffer; Mäkinen, Veli; Tomescu, Alexandru I
2016-05-01
One of the last steps in a genome assembly project is filling the gaps between consecutive contigs in the scaffolds. This problem can be naturally stated as finding an s-t path in a directed graph whose sum of arc costs belongs to a given range (the estimate on the gap length). Here s and t are any two contigs flanking a gap. This problem is known to be NP-hard in general. Here we derive a simpler dynamic programming solution than already known, pseudo-polynomial in the maximum value of the input range. We implemented various practical optimizations to it, and compared our exact gap-filling solution experimentally to popular gap-filling tools. Summing over all the bacterial assemblies considered in our experiments, we can in total fill 76% more gaps than the best previous tool, and the gaps filled by our method span 136% more sequence. Furthermore, the error level of the newly introduced sequence is comparable to that of the previous tools. The experiments also show that our exact approach does not easily scale to larger genomes, where the problem is in general difficult for all tools. PMID:26959081
Path querying system on mobile devices
NASA Astrophysics Data System (ADS)
Lin, Xing; Wang, Yifei; Tian, Yuan; Wu, Lun
2006-01-01
Traditional approaches to path querying problems are not efficient and convenient under most circumstances. A more convenient and reliable approach to this problem has to be found. This paper is devoted to a path querying solution on mobile devices. By using an improved Dijkstra's shortest path algorithm and a natural language translating module, this system can help people find the shortest path between two places through their cell phones or other mobile devices. The chosen path is prompted in text of natural language, as well as a map picture. This system would be useful in solving best path querying problems and have potential to be a profitable business system.
The graph-theoretic minimum energy path problem for ionic conduction
NASA Astrophysics Data System (ADS)
Kishida, Ippei
2015-10-01
A new computational method was developed to analyze the ionic conduction mechanism in crystals through graph theory. The graph was organized into nodes, which represent the crystal structures modeled by ionic site occupation, and edges, which represent structure transitions via ionic jumps. We proposed a minimum energy path problem, which is similar to the shortest path problem. An effective algorithm to solve the problem was established. Since our method does not use randomized algorithm and time parameters, the computational cost to analyze conduction paths and a migration energy is very low. The power of the method was verified by applying it to α-AgI and the ionic conduction mechanism in α-AgI was revealed. The analysis using single point calculations found the minimum energy path for long-distance ionic conduction, which consists of 12 steps of ionic jumps in a unit cell. From the results, the detailed theoretical migration energy was calculated as 0.11 eV by geometry optimization and nudged elastic band method. Our method can refine candidates for possible jumps in crystals and it can be adapted to other computational methods, such as the nudged elastic band method. We expect that our method will be a powerful tool for analyzing ionic conduction mechanisms, even for large complex crystals.
Neighboring extremals of dynamic optimization problems with path equality constraints
NASA Technical Reports Server (NTRS)
Lee, A. Y.
1988-01-01
Neighboring extremals of dynamic optimization problems with path equality constraints and with an unknown parameter vector are considered in this paper. With some simplifications, the problem is reduced to solving a linear, time-varying two-point boundary-value problem with integral path equality constraints. A modified backward sweep method is used to solve this problem. Two example problems are solved to illustrate the validity and usefulness of the solution technique.
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.
An Application of Calculus: Optimum Parabolic Path Problem
ERIC Educational Resources Information Center
Atasever, Merve; Pakdemirli, Mehmet; Yurtsever, Hasan Ali
2009-01-01
A practical and technological application of calculus problem is posed to motivate freshman students or junior high school students. A variable coefficient of friction is used in modelling air friction. The case in which the coefficient of friction is a decreasing function of altitude is considered. The optimum parabolic path for a flying object…
Solving a Hamiltonian Path Problem with a bacterial computer
Baumgardner, Jordan; Acker, Karen; Adefuye, Oyinade; Crowley, Samuel Thomas; DeLoache, Will; Dickson, James O; Heard, Lane; Martens, Andrew T; Morton, Nickolaus; Ritter, Michelle; Shoecraft, Amber; Treece, Jessica; Unzicker, Matthew; Valencia, Amanda; Waters, Mike; Campbell, A Malcolm; Heyer, Laurie J; Poet, Jeffrey L; Eckdahl, Todd T
2009-01-01
Background The Hamiltonian Path Problem asks whether there is a route in a directed graph from a beginning node to an ending node, visiting each node exactly once. The Hamiltonian Path Problem is NP complete, achieving surprising computational complexity with modest increases in size. This challenge has inspired researchers to broaden the definition of a computer. DNA computers have been developed that solve NP complete problems. Bacterial computers can be programmed by constructing genetic circuits to execute an algorithm that is responsive to the environment and whose result can be observed. Each bacterium can examine a solution to a mathematical problem and billions of them can explore billions of possible solutions. Bacterial computers can be automated, made responsive to selection, and reproduce themselves so that more processing capacity is applied to problems over time. Results We programmed bacteria with a genetic circuit that enables them to evaluate all possible paths in a directed graph in order to find a Hamiltonian path. We encoded a three node directed graph as DNA segments that were autonomously shuffled randomly inside bacteria by a Hin/hixC recombination system we previously adapted from Salmonella typhimurium for use in Escherichia coli. We represented nodes in the graph as linked halves of two different genes encoding red or green fluorescent proteins. Bacterial populations displayed phenotypes that reflected random ordering of edges in the graph. Individual bacterial clones that found a Hamiltonian path reported their success by fluorescing both red and green, resulting in yellow colonies. We used DNA sequencing to verify that the yellow phenotype resulted from genotypes that represented Hamiltonian path solutions, demonstrating that our bacterial computer functioned as expected. Conclusion We successfully designed, constructed, and tested a bacterial computer capable of finding a Hamiltonian path in a three node directed graph. This proof
On path-following methods for structural failure problems
NASA Astrophysics Data System (ADS)
Stanić, Andjelka; Brank, Boštjan; Korelc, Jože
2016-08-01
We revisit the consistently linearized path-following method that can be applied in the nonlinear finite element analysis of solids and structures in order to compute a solution path. Within this framework, two constraint equations are considered: a quadratic one (that includes as special cases popular spherical and cylindrical forms of constraint equation), and another one that constrains only one degree-of-freedom (DOF), the critical DOF. In both cases, the constrained DOFs may vary from one solution increment to another. The former constraint equation is successful in analysing geometrically nonlinear and/or standard inelastic problems with snap-throughs, snap-backs and bifurcation points. However, it cannot handle problems with the material softening that are computed e.g. by the embedded-discontinuity finite elements. This kind of problems can be solved by using the latter constraint equation. The plusses and minuses of the both presented constraint equations are discussed and illustrated on a set of numerical examples. Some of the examples also include direct computation of critical points and branch switching. The direct computation of the critical points is performed in the framework of the path-following method by using yet another constraint function, which is eigenvector-free and suited to detect critical points.
NASA Astrophysics Data System (ADS)
Pahlavani, Parham; Delavar, Mahmoud R.; Frank, Andrew U.
2012-08-01
The personalized urban multi-criteria quasi-optimum path problem (PUMQPP) is a branch of multi-criteria shortest path problems (MSPPs) and it is classified as a NP-hard problem. To solve the PUMQPP, by considering dependent criteria in route selection, there is a need for approaches that achieve the best compromise of possible solutions/routes. Recently, invasive weed optimization (IWO) algorithm is introduced and used as a novel algorithm to solve many continuous optimization problems. In this study, the modified algorithm of IWO was designed, implemented, evaluated, and compared with the genetic algorithm (GA) to solve the PUMQPP in a directed urban transportation network. In comparison with the GA, the results have shown the significant superiority of the proposed modified IWO algorithm in exploring a discrete search-space of the urban transportation network. In this regard, the proposed modified IWO algorithm has reached better results in fitness function, quality metric and running-time values in comparison with those of the GA.
Nonlinear multi-agent path search method based on OFDM communication
NASA Astrophysics Data System (ADS)
Sato, Masatoshi; Igarashi, Yusuke; Tanaka, Mamoru
This paper presents novel shortest paths searching system based on analog circuit analysis which is called sequential local current comparison method on alternating-current (AC) circuit (AC-SLCC). Local current comparison (LCC) method is a path searching method where path is selected in the direction of the maximum current in a direct-current (DC) resistive circuit. Since a plurality of shortest paths searching by LCC method can be done by solving the current distribution on the resistive circuit analysis, the shortest path problem can be solved at supersonic speed. AC-SLCC method is a novel LCC method with orthogonal frequency division multiplexing (OFDM) communication on AC circuit. It is able to send data with the shortest path and without major data loss, and this suggest the possibility of application to various things (especially OFDM communication techniques).
Link prediction based on path entropy
NASA Astrophysics Data System (ADS)
Xu, Zhongqi; Pu, Cunlai; Yang, Jian
2016-08-01
Information theory has been taken as a prospective tool for quantifying the complexity of complex networks. In this paper, first we study the information entropy or uncertainty of a path using the information theory. After that, we apply the path entropy to the link prediction problem in real-world networks. Specifically, we propose a new similarity index, namely Path Entropy (PE) index, which considers the information entropies of shortest paths between node pairs with penalization to long paths. Empirical experiments demonstrate that PE index outperforms the mainstream of link predictors.
NASA Astrophysics Data System (ADS)
Shakeri, Nadim; Jalili, Saeed; Ahmadi, Vahid; Rasoulzadeh Zali, Aref; Goliaei, Sama
2015-01-01
The problem of finding the Hamiltonian path in a graph, or deciding whether a graph has a Hamiltonian path or not, is an NP-complete problem. No exact solution has been found yet, to solve this problem using polynomial amount of time and space. In this paper, we propose a two dimensional (2-D) optical architecture based on optical electronic devices such as micro ring resonators, optical circulators and MEMS based mirror (MEMS-M) to solve the Hamiltonian Path Problem, for undirected graphs in linear time. It uses a heuristic algorithm and employs n+1 different wavelengths of a light ray, to check whether a Hamiltonian path exists or not on a graph with n vertices. Then if a Hamiltonian path exists, it reports the path. The device complexity of the proposed architecture is O(n2).
Fusion proteins as alternate crystallization paths to difficult structure problems
NASA Technical Reports Server (NTRS)
Carter, Daniel C.; Rueker, Florian; Ho, Joseph X.; Lim, Kap; Keeling, Kim; Gilliland, Gary; Ji, Xinhua
1994-01-01
The three-dimensional structure of a peptide fusion product with glutathione transferase from Schistosoma japonicum (SjGST) has been solved by crystallographic methods to 2.5 A resolution. Peptides or proteins can be fused to SjGST and expressed in a plasmid for rapid synthesis in Escherichia coli. Fusion proteins created by this commercial method can be purified rapidly by chromatography on immobilized glutathione. The potential utility of using SjGST fusion proteins as alternate paths to the crystallization and structure determination of proteins is demonstrated.
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
The Edge-Disjoint Path Problem on Random Graphs by Message-Passing.
Altarelli, Fabrizio; Braunstein, Alfredo; Dall'Asta, Luca; De Bacco, Caterina; Franz, Silvio
2015-01-01
We present a message-passing algorithm to solve a series of edge-disjoint path problems on graphs based on the zero-temperature cavity equations. Edge-disjoint paths problems are important in the general context of routing, that can be defined by incorporating under a unique framework both traffic optimization and total path length minimization. The computation of the cavity equations can be performed efficiently by exploiting a mapping of a generalized edge-disjoint path problem on a star graph onto a weighted maximum matching problem. We perform extensive numerical simulations on random graphs of various types to test the performance both in terms of path length minimization and maximization of the number of accommodated paths. In addition, we test the performance on benchmark instances on various graphs by comparison with state-of-the-art algorithms and results found in the literature. Our message-passing algorithm always outperforms the others in terms of the number of accommodated paths when considering non trivial instances (otherwise it gives the same trivial results). Remarkably, the largest improvement in performance with respect to the other methods employed is found in the case of benchmarks with meshes, where the validity hypothesis behind message-passing is expected to worsen. In these cases, even though the exact message-passing equations do not converge, by introducing a reinforcement parameter to force convergence towards a sub optimal solution, we were able to always outperform the other algorithms with a peak of 27% performance improvement in terms of accommodated paths. On random graphs, we numerically observe two separated regimes: one in which all paths can be accommodated and one in which this is not possible. We also investigate the behavior of both the number of paths to be accommodated and their minimum total length. PMID:26710102
Genetic algorithms, path relinking, and the flowshop sequencing problem.
Reeves, C R; Yamada, T
1998-01-01
In a previous paper, a simple genetic algorithm (GA) was developed for finding (approximately) the minimum makespan of the n-job, m-machine permutation flowshop sequencing problem (PFSP). The performance of the algorithm was comparable to that of a naive neighborhood search technique and a proven simulated annealing algorithm. However, recent results have demonstrated the superiority of a tabu search method in solving the PFSP. In this paper, we reconsider the implementation of a GA for this problem and show that by taking into account the features of the landscape generated by the operators used, we are able to improve its performance significantly. PMID:10021740
NASA Astrophysics Data System (ADS)
Diot, Emilie; Gavoille, Cyril
In this paper we investigate the structural properties of k-path separable graphs, that are the graphs that can be separated by a set of k shortest paths. We identify several graph families having such path separability, and we show that this property is closed under minor taking. In particular we establish a list of forbidden minors for 1-path separable graphs.
Mean free path effects in the shock-implosion problem
NASA Astrophysics Data System (ADS)
Goldsworthy, M. J.; Pullin, D. I.
2009-02-01
The effects of finite Knudsen number in the problem of a cylindrically imploding shock wave in a monatomic gas are investigated. Numerical solutions of the flow field are obtained with initial conditions in the ranges 1.25≤M0≤5 and 0.005≤Kn0≤0.1 using the direct simulation Monte Carlo method. Results show that as Kn0 decreases and M0 increases, the maximum implosion temperature scales increasingly well with the similarity exponent predicted in the Guderley solution for an imploding strong shock in the Euler limit. When the radius of curvature is large, the cylindrical shock thickness is found to be almost identical to the thickness of a planar shock for a given shock Mach number. For small radii of curvature, the cylindrical shock was found to be thicker than the corresponding planar shock.
Instability Paths in the Kirchhoff-Plateau Problem
NASA Astrophysics Data System (ADS)
Giusteri, Giulio G.; Franceschini, Paolo; Fried, Eliot
2016-04-01
The Kirchhoff-Plateau problem concerns the equilibrium shapes of a system in which a flexible filament in the form of a closed loop is spanned by a soap film, with the filament being modeled as a Kirchhoff rod and the action of the spanning surface being solely due to surface tension. Adopting a variational approach, we define an energy associated with shape deformations of the system and then derive general equilibrium and (linear) stability conditions by considering the first and second variations of the energy functional. We analyze in detail the transition to instability of flat circular configurations, which are ground states for the system in the absence of surface tension, when the latter is progressively increased. Such a theoretical study is particularly useful here, since the many different perturbations that can lead to instability make it challenging to perform an exhaustive experimental investigation. We generalize previous results, since we allow the filament to possess a curved intrinsic shape and also to display anisotropic flexural properties (as happens when the cross section of the filament is noncircular). This is accomplished by using a rod energy which is familiar from the modeling of DNA filaments. We find that the presence of intrinsic curvature is necessary to obtain a first buckling mode which is not purely tangent to the spanning surface. We also elucidate the role of twisting buckling modes, which become relevant in the presence of flexural anisotropy.
Instability Paths in the Kirchhoff-Plateau Problem
NASA Astrophysics Data System (ADS)
Giusteri, Giulio G.; Franceschini, Paolo; Fried, Eliot
2016-08-01
The Kirchhoff-Plateau problem concerns the equilibrium shapes of a system in which a flexible filament in the form of a closed loop is spanned by a soap film, with the filament being modeled as a Kirchhoff rod and the action of the spanning surface being solely due to surface tension. Adopting a variational approach, we define an energy associated with shape deformations of the system and then derive general equilibrium and (linear) stability conditions by considering the first and second variations of the energy functional. We analyze in detail the transition to instability of flat circular configurations, which are ground states for the system in the absence of surface tension, when the latter is progressively increased. Such a theoretical study is particularly useful here, since the many different perturbations that can lead to instability make it challenging to perform an exhaustive experimental investigation. We generalize previous results, since we allow the filament to possess a curved intrinsic shape and also to display anisotropic flexural properties (as happens when the cross section of the filament is noncircular). This is accomplished by using a rod energy which is familiar from the modeling of DNA filaments. We find that the presence of intrinsic curvature is necessary to obtain a first buckling mode which is not purely tangent to the spanning surface. We also elucidate the role of twisting buckling modes, which become relevant in the presence of flexural anisotropy.
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
Constrained Graph Optimization: Interdiction and Preservation Problems
Schild, Aaron V
2012-07-30
The maximum flow, shortest path, and maximum matching problems are a set of basic graph problems that are critical in theoretical computer science and applications. Constrained graph optimization, a variation of these basic graph problems involving modification of the underlying graph, is equally important but sometimes significantly harder. In particular, one can explore these optimization problems with additional cost constraints. In the preservation case, the optimizer has a budget to preserve vertices or edges of a graph, preventing them from being deleted. The optimizer wants to find the best set of preserved edges/vertices in which the cost constraints are satisfied and the basic graph problems are optimized. For example, in shortest path preservation, the optimizer wants to find a set of edges/vertices within which the shortest path between two predetermined points is smallest. In interdiction problems, one deletes vertices or edges from the graph with a particular cost in order to impede the basic graph problems as much as possible (for example, delete edges/vertices to maximize the shortest path between two predetermined vertices). Applications of preservation problems include optimal road maintenance, power grid maintenance, and job scheduling, while interdiction problems are related to drug trafficking prevention, network stability assessment, and counterterrorism. Computational hardness results are presented, along with heuristic methods for approximating solutions to the matching interdiction problem. Also, efficient algorithms are presented for special cases of graphs, including on planar graphs. The graphs in many of the listed applications are planar, so these algorithms have important practical implications.
Shortest recurrence periods of novae
Kato, Mariko; Saio, Hideyuki; Hachisu, Izumi; Nomoto, Ken'ichi
2014-10-01
Stimulated by the recent discovery of the 1 yr recurrence period nova M31N 2008-12a, we examined the shortest recurrence periods of hydrogen shell flashes on mass-accreting white dwarfs (WDs). We discuss the mechanism that yields a finite minimum recurrence period for a given WD mass. Calculating the unstable flashes for various WD masses and mass accretion rates, we identified a shortest recurrence period of about two months for a non-rotating 1.38 M {sub ☉} WD with a mass accretion rate of 3.6 × 10{sup –7} M {sub ☉} yr{sup –1}. A 1 yr recurrence period is realized for very massive (≳ 1.3 M {sub ☉}) WDs with very high accretion rates (≳ 1.5 × 10{sup –7} M {sub ☉} yr{sup –1}). We revised our stability limit of hydrogen shell burning, which will be useful for binary evolution calculations toward Type Ia supernovae.
NASA Astrophysics Data System (ADS)
Zamirian, M.; Kamyad, A. V.; Farahi, M. H.
2009-09-01
In this Letter a new approach for solving optimal path planning problems for a single rigid and free moving object in a two and three dimensional space in the presence of stationary or moving obstacles is presented. In this approach the path planning problems have some incompatible objectives such as the length of path that must be minimized, the distance between the path and obstacles that must be maximized and etc., then a multi-objective dynamic optimization problem (MODOP) is achieved. Considering the imprecise nature of decision maker's (DM) judgment, these multiple objectives are viewed as fuzzy variables. By determining intervals for the values of these fuzzy variables, flexible monotonic decreasing or increasing membership functions are determined as the degrees of satisfaction of these fuzzy variables on their intervals. Then, the optimal path planning policy is searched by maximizing the aggregated fuzzy decision values, resulting in a fuzzy multi-objective dynamic optimization problem (FMODOP). Using a suitable t-norm, the FMODOP is converted into a non-linear dynamic optimization problem (NLDOP). By using parametrization method and some calculations, the NLDOP is converted into the sequence of conventional non-linear programming problems (NLPP). It is proved that the solution of this sequence of the NLPPs tends to a Pareto optimal solution which, among other Pareto optimal solutions, has the best satisfaction of DM for the MODOP. Finally, the above procedure as a novel algorithm integrating parametrization method and fuzzy aggregation to solve the MODOP is proposed. Efficiency of our approach is confirmed by some numerical examples.
A Path Analysis of Social Problem-Solving as a Predictor of White Racial Identity
ERIC Educational Resources Information Center
Carr, Amanda G.; Caskie, Grace I. L.
2010-01-01
This study examined (a) whether a developmental model or a model in which all subscales' measurement errors are correlated best explains the relationships among White racial identity (WRI) statuses, and (b) social problem-solving (SPS) skills as a predictor of WRI. Path analysis was conducted with a sample of 255 White undergraduate students from…
Search Path Mapping: A Versatile Approach for Visualizing Problem-Solving Behavior.
ERIC Educational Resources Information Center
Stevens, Ronald H.
1991-01-01
Computer-based problem-solving examinations in immunology generate graphic representations of students' search paths, allowing evaluation of how organized and focused their knowledge is, how well their organization relates to critical concepts in immunology, where major misconceptions exist, and whether proper knowledge links exist between content…
Kiosses, Dimitris N.; Arean, Patricia A.; Teri, Linda; Alexopoulos, George S.
2010-01-01
Objectives This preliminary study examines the efficacy of 12-week home-delivered Problem Adaptation Therapy (PATH) vs. home-delivered Supportive Therapy (ST) in reducing depression and disability in 30 depressed, cognitively impaired, disabled older adults. Design A 12-week randomized clinical trial. Research assistants were unaware of the participants' randomization status. Assessments were conducted at baseline, 6 and 12 weeks. Setting Weill Cornell - Advanced Center for Interventions and Services Research (ACISR). Participants Thirty elders with major depression, cognitive impairment, and disability were recruited through advertisement and the Home-Delivered Meals Program of the Westchester County Department of Senior Programs and Services. Intervention PATH is a home-delivered intervention designed to reduce depression and disability in depressed, cognitively impaired, disabled elders. PATH is based on Problem Solving Therapy (PST) and integrates environmental adaptation and caregiver participation. PATH is consistent with Lawton's ecological model of adaptive functioning in aging. Measurements Depression and disability were measured with Hamilton Depression Rating Scale – 24 items and Sheehan Disability Scale, respectively. Client Satisfaction Questionnaire was used to assess patient satisfaction with treatment. Results Mixed-effects model analyses revealed that PATH was more efficacious than ST in reducing depression and disability at 12 weeks. Participants in both treatment groups were satisfied with treatment. Conclusions This preliminary study suggests that PATH is well accepted and efficacious in depressed elders with major depression, cognitive impairment, and disability. Because this population may not adequately respond to antidepressant medication treatment, PATH may provide relief to many patients who would otherwise remain depressed and suffer. PMID:20808092
Nonequilibrium problems in quantum field theory and Schwinger`s closed time path formalism
Cooper, F.
1995-05-01
We review the closed time path formalism of Schwinger using a path integral approach. We apply this formalism to the study of pair production from strong external fields as well as the time evolution of a nonequilibrium chiral phase transition. In 1961 in his classic paper ``Brownian Motion of a Quantum Particle,`` Schwinger solved the formidable technical problem of how to use the action principle to study initial value problems. Previously, the action principle was formulated to study only transition matrix elements from an earlier time to a later time. The elegant solution of this problem was the invention of the closed time path (CTP) formalism. This formalism was first used to study field theory problems by Mahanthappa and Bakshi. With the advent of supercomputers, it has now become possible to use this formalism to numerically solve important field theory questions which are presented as initial value problems. Two of these problems we shall review here. They are (1) The time evolution of the quark- gluon plasma. (2) Dynamical evolution of a non-equilibrium chiral phase transition following a relativistic heavy ion collision.
A Probabilistic PTAS for Shortest Common Superstring
NASA Astrophysics Data System (ADS)
Plociennik, Kai
We consider approximation algorithms for the shortest common superstring problem (SCS). It is well-known that there is a constant f > 1 such that there is no efficient approximation algorithm for SCS achieving a factor of at most f in the worst case, unless P = NP. We study SCS on random inputs and present an approximation scheme that achieves, for every ɛ> 0, a 1 + ɛ-approximation in expected polynomial time. This result applies not only if the letters are chosen independently at random, but also to the more realistic mixing model, which allows dependencies among the letters of the random strings. Our result is based on a sharp tail bound on the optimal compression, which improves a previous result by Frieze and Szpankowski.
Development of the PEBLebl Traveling Salesman Problem Computerized Testbed
ERIC Educational Resources Information Center
Mueller, Shane T.; Perelman, Brandon S.; Tan, Yin Yin; Thanasuan, Kejkaew
2015-01-01
The traveling salesman problem (TSP) is a combinatorial optimization problem that requires finding the shortest path through a set of points ("cities") that returns to the starting point. Because humans provide heuristic near-optimal solutions to Euclidean versions of the problem, it has sometimes been used to investigate human visual…
Hard water problems and soft water paths: The "supply versus demand" conundrum
NASA Astrophysics Data System (ADS)
Gleick, P. H.
2012-12-01
Water problems are complex, interdisciplinary, and have profound effects on human and ecosystem health and well-being. And they are classic "hard" problems. Good science is necessary to solve these problems, but it is rarely sufficient. One of these hard problems is that of "perception" and "frame" - traditional water planners and managers frame freshwater as a "supply" problem, i.e., how can we access and deliver sufficient quantities of water of suitable quality, to satisfy perceived demand. In recent years, however, as water scarcity in different regions has increased due to growing populations and expanding economies, "peak water" limits (including peak renewable, non-renewable, and ecological limits) have started to constrain development of traditional "supply" options (Figure 1). That has led to new thinking about the other side of the equation: what is meant by water "demand" and can demand management tools and approaches offer a way to solve water problems. The "soft path for water" addresses this issue of water demand directly, but implementing demand-side solutions faces serious barriers. This talk will expound on the soft path approach and its potential to overcome some of the gridlock and stagnation in current water policy debates, with examples from both developed and developing countries, and different economic sectors.umulative global reservoir storage (major reservoirs) from 1900 to 2010, showing leveling off of traditional supply expansion. Data from the GRanD database.
NASA Astrophysics Data System (ADS)
Ma, Yong; Wang, Hongwei; Zamirian, M.
2012-01-01
We present a new approach containing two steps to determine conflict-free paths for mobile objects in two and three dimensions with moving obstacles. Firstly, the shortest path of each object is set as goal function which is subject to collision-avoidance criterion, path smoothness, and velocity and acceleration constraints. This problem is formulated as calculus of variation problem (CVP). Using parametrization method, CVP is converted to time-varying nonlinear programming problems (TNLPP) and then resolved. Secondly, move sequence of object is assigned by priority scheme; conflicts are resolved by multilevel conflict resolution strategy. Approach efficiency is confirmed by numerical examples.
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.
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
Going against the flow: finding the optimal path
NASA Astrophysics Data System (ADS)
Talbot, Julian
2010-01-01
We consider the problem of finding the optimum path of a boat traversing a straight in a current. The path of the shortest time is found using the calculus of variations with the constraint that the boat must land directly opposite to its starting point. We compare the optimal trajectory with that where the boat's local orientation is always directed to the arrival point. When analytical solutions cannot be found we use numerical methods. The level of the exposition is suitable for advanced undergraduate students, graduate students and general physicists.
Path optimization with limited sensing ability
NASA Astrophysics Data System (ADS)
Kang, Sung Ha; Kim, Seong Jun; Zhou, Haomin
2015-10-01
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.
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.
ERIC Educational Resources Information Center
MacGregor, James N.; Chronicle, Edward P.; Ormerod, Thomas C.
2006-01-01
We compared the performance of three heuristics with that of subjects on variants of a well-known combinatorial optimization task, the Traveling Salesperson Problem (TSP). The present task consisted of finding the shortest path through an array of points from one side of the array to the other. Like the standard TSP, the task is computationally…
A note on "Solving the find-path problem by good representation of free space".
Wang, Y
1997-01-01
The conditions of a pure translation and a pure rotation for car-like robots and dual-drive robots are derived. Based on these conditions the suitability of the path planning algorithm developed by R.A Brooks (1983) for each of the two kinds of mobile robots is discussed. PMID:18255913
A path-following interior-point algorithm for linear and quadratic problems
Wright, S.J.
1993-12-01
We describe an algorithm for the monotone linear complementarity problem that converges for many positive, not necessarily feasible, starting point and exhibits polynomial complexity if some additional assumptions are made on the starting point. If the problem has a strictly complementary solution, the method converges subquadratically. We show that the algorithm and its convergence extend readily to the mixed monotone linear complementarity problem and, hence, to all the usual formulations of the linear programming and convex quadratic programming problems.
Dorfer, Matthias; Kazmar, Tomáš; Šmíd, Matěj; Sing, Sanchit; Kneißl, Julia; Keller, Simone; Debeir, Olivier; Luber, Birgit; Mattes, Julian
2016-01-01
In this paper we address the problem of recovering spatio-temporal trajectories of cancer cells in phase contrast video-microscopy where the user provides the paths on which the cells are moving. The paths are purely spatial, without temporal information. To recover the temporal information associated to a given path we propose an approach based on automatic cell detection and on a graph-based shortest path search. The nodes in the graph consist of the projections of the cell detections onto the geometrical cell path. The edges relate nodes which correspond to different frames of the sequence and potentially to the same cell and trajectory. In this directed graph we search for the shortest path and use it to define a temporal parametrization of the corresponding geometrical cell path. An evaluation based on 286 paths of 7 phase contrast microscopy videos shows that our algorithm allows to recover 92% of trajectory points with respect to the associated ground truth. We compare our method with a state-of-the-art algorithm for semi-automated cell tracking in phase contrast microscopy which requires interactively placed starting points for the cells to track. The comparison shows that supporting geometrical paths in combination with our algorithm allow us to obtain more reliable cell trajectories. PMID:25987193
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
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
Methodology for Augmenting Existing Paths with Additional Parallel Transects
Wilson, John E.
2013-09-30
Visual Sample Plan (VSP) is sample planning software that is used, among other purposes, to plan transect sampling paths to detect areas that were potentially used for munition training. This module was developed for application on a large site where existing roads and trails were to be used as primary sampling paths. Gap areas between these primary paths needed to found and covered with parallel transect paths. These gap areas represent areas on the site that are more than a specified distance from a primary path. These added parallel paths needed to optionally be connected together into a single path—the shortest path possible. The paths also needed to optionally be attached to existing primary paths, again with the shortest possible path. Finally, the process must be repeatable and predictable so that the same inputs (primary paths, specified distance, and path options) will result in the same set of new paths every time. This methodology was developed to meet those specifications.
Shortest Recurrence Periods of Forced Novae
NASA Astrophysics Data System (ADS)
Hachisu, Izumi; Saio, Hideyuki; Kato, Mariko
2016-06-01
We revisit hydrogen shell burning on white dwarfs (WDs) with higher mass accretion rates than the stability limit, {\\dot{M}}{{stable}}, above which hydrogen burning is stable. Novae occur with mass accretion rates below the limit. For an accretion rate >{\\dot{M}}{{stable}}, a first hydrogen shell flash occurs followed by steady nuclear burning, so the shell burning will not be quenched as long as the WD continuously accretes matter. On the basis of this picture, some persistent supersoft X-ray sources can be explained by binary models with high accretion rates. In some recent studies, however, the claim has been made that no steady hydrogen shell burning exists even for accretion rates >{\\dot{M}}{{stable}}. We demonstrate that, in such cases, repetitive flashes occurred because mass accretion was artificially controlled. If we stop mass accretion during the outburst, no new nuclear fuel is supplied, so the shell burning will eventually stop. If we resume mass accretion after some time, the next outburst eventually occurs. In this way, we can design the duration of outburst and interpulse time with manipulated mass accretion. We call such a controlled nova a “forced nova.” These forced novae, if they exist, could have much shorter recurrence periods than “natural novae.” We have obtained the shortest recurrence periods for forced novae for various WD masses. Based on the results, we revisit WD masses of some recurrent novae, including T Pyx.
Path Model of the Processes Influencing Drinking-Related Problems among College Students.
ERIC Educational Resources Information Center
Fenzel, L. Mickey; Patel, Shreya
This study tested a causal model of the prediction of the rate of occurrence of social and academic problems that results from college students' drinking. The model posited two pathways, one examining self-worth perceptions and symptoms of depression as mediators and one examining binge-drinking frequency as a mediator. Predictors included:…
Status Problem and Expectations of Competence: A Challenging Path for Teachers
ERIC Educational Resources Information Center
Pescarmona, Isabella
2015-01-01
Complex Instruction (CI) is a cooperative learning approach, which aims at improving the equal status interaction among students working in groups who may be at different academic and social levels. Based on an ethnographic research, the article examines how a group of Italian primary school teachers understand the status problem and how the…
Evading the sign problem in the mean-field approximation through Lefschetz-thimble path integral
NASA Astrophysics Data System (ADS)
Tanizaki, Yuya; Nishimura, Hiromichi; Kashiwa, Kouji
2015-05-01
The fermion sign problem appearing in the mean-field approximation is considered, and the systematic computational scheme of the free energy is devised by using the Lefschetz-thimble method. We show that the Lefschetz-thimble method respects the reflection symmetry, which makes physical quantities manifestly real at any order of approximations using complex saddle points. The formula is demonstrated through the Airy integral as an example, and its application to the Polyakov-loop effective model of dense QCD is discussed in detail.
From Parent to Child to Parent…: Paths In and Out of Problem Behavior
Bradley, Robert H.; Corwyn, Robert
2014-01-01
This study used data from the NICHD Study of Early Child Care and Youth Development to examine relations between parenting, self-control and externalizing behavior from early childhood to mid-adolescence (N=956; 49.9% male). Results indicated that maternal sensitivity, parental harshness and productive activity are related to externalizing problems but that patterns of relations change from early childhood to middle childhood to adolescence, with evidence suggesting that externalizing behavior influences parenting more than the reverse from middle childhood onward. Self-control measured during early adolescence partially mediated relations between maternal sensitivity and adolescent-reported externalizing behavior. Parental monitoring during adolescence was also related to externalizing behavior at age 15. Monitoring partially mediated the relation between externalizing behavior in early adolescence and externalizing at age 15. PMID:23135289
A priori least expected time paths in fuzzy, time-variant transportation networks
NASA Astrophysics Data System (ADS)
Wang, Li; Gao, Ziyou; Yang, Lixing
2016-02-01
Dynamics and fuzziness are two significant characteristics of real-world transportation networks. To capture these two features theoretically, this article proposes the concept of a fuzzy, time-variant network characterized by a series of time-dependent fuzzy link travel times. To find an effective route guidance for travelers, the expected travel time is specifically adopted as an evaluation criterion to assess the route generation process. Then the shortest path problem is formulated as a multi-objective 0-1 optimization model for finding the least expected time path over the considered time horizon. Different from the shortest path problem in dynamic and random networks, an efficient method is proposed in this article to calculate the fuzzy expected travel time for each given path. A tabu search algorithm is designed for the problem to generate the best solution under the framework of linear weighted methods. Finally, two numerical experiments are performed to verify the effectiveness and efficiency of the model and algorithm.
Information Spread of Emergency Events: Path Searching on Social Networks
Hu, Hongzhi; Wu, Tunan
2014-01-01
Emergency has attracted global attentions of government and the public, and it will easily trigger a series of serious social problems if it is not supervised effectively in the dissemination process. In the Internet world, people communicate with each other and form various virtual communities based on social networks, which lead to a complex and fast information spread pattern of emergency events. This paper collects Internet data based on data acquisition and topic detection technology, analyzes the process of information spread on social networks, describes the diffusions and impacts of that information from the perspective of random graph, and finally seeks the key paths through an improved IBF algorithm. Application cases have shown that this algorithm can search the shortest spread paths efficiently, which may help us to guide and control the information dissemination of emergency events on early warning. PMID:24600323
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.
Random generation of structured linear optimization problems
Arthur, J.; Frendewey, J. Jr.
1994-12-31
We describe the on-going development of a random generator for linear optimization problems (LPs) founded on the concept of block structure. The general LP: minimize z = cx subject to Ax = b, x {ge} 0 can take a variety of special forms determined (primarily) by predefined structures on the matrix A of constraint coefficients. The authors have developed several random problem generators which provide instances of LPs having such structure; in particular (i) general (non-structured) problems, (ii) generalized upper bound (GUB) constraints, (iii) minimum cost network flow problems, (iv) transportation and assignment problems, (v) shortest path problems, (vi) generalized network flow problems, and (vii) multicommodity network flow problems. This paper discusses the general philosophy behind the construction of these generators. In addition, the task of combining the generators into a single generator -- in which the matrix A can contain various blocks, each of a prescribed structure from those mentioned above -- is described.
NASA Astrophysics Data System (ADS)
Nosikov, I. A.; Bessarab, P. F.; Klimenko, M. V.
2016-06-01
Fundamentals of the method of transverse displacements for calculating the HF radio-wave propagation paths are presented. The method is based on the direct variational principle for the optical path functional, but is not reduced to solving the Euler—Lagrange equations. Instead, the initial guess given by an ordered set of points is transformed successively into a ray path, while its endpoints corresponding to the positions of the transmitter and the receiver are kept fixed throughout the entire iteration process. The results of calculation by the method of transverse displacements are compared with known analytical solutions. The importance of using only transverse displacements of the ray path in the optimization procedure is also demonstrated.
NASA Astrophysics Data System (ADS)
Yun, KiHyun
2016-07-01
We consider a gradient estimate for a conductivity problem whose inclusions are two neighboring insulators in three dimensions. When inclusions with an extreme conductivity (insulators or perfect conductors) are closely located, the gradient can be concentrated in between inclusions and then becomes arbitrarily large as the distance between inclusions approaches zero. The gradient estimate in between insulators in three dimensions has been regarded as a challenging problem, while the optimal blow-up rates in terms of the distance were successfully obtained for the other extreme conductivity problems in two and three dimensions, and are attained on the shortest line segment between inclusions. In this paper, we establish upper and lower bounds of gradients on the shortest line segment between two insulating unit spheres in three dimensions. These bounds present the optimal blow-up rate of gradient on the line segment which is substantially different from the rates in the other problems.
Pair correlations in classical crystals: The shortest-graph method
NASA Astrophysics Data System (ADS)
Yurchenko, Stanislav O.; Kryuchkov, Nikita P.; Ivlev, Alexei V.
2015-07-01
The shortest-graph method is applied to calculate the pair correlation functions of crystals. The method is based on the representation of individual correlation peaks by the Gaussian functions, summed along the shortest graph connecting the two given points. The analytical expressions for the Gaussian parameters are derived for two- and three-dimensional crystals. The obtained results are compared with the pair correlation functions deduced from the molecular dynamics simulations of Yukawa, inverse-power law, Weeks-Chandler-Andersen, and Lennard-Jones crystals. By calculating the Helmholtz free energy, it is shown that the method is particularly accurate for soft interparticle interactions and for low temperatures, i.e., when the anharmonicity effects are insignificant. The accuracy of the method is further demonstrated by deriving the solid-solid transition line for Yukawa crystals, and the compressibility for inverse-power law crystals.
Fast marching methods for the continuous traveling salesman problem
Andrews, J.; Sethian, J.A.
2008-12-01
We consider a problem in which we are given a domain, a cost function which depends on position at each point in the domain, and a subset of points ('cities') in the domain. The goal is to determine the cheapest closed path that visits each city in the domain once. This can be thought of as a version of the Traveling Salesman Problem, in which an underlying known metric determines the cost of moving through each point of the domain, but in which the actual shortest path between cities is unknown at the outset. We describe algorithms for both a heuristic and an optimal solution to this problem. The order of the heuristic algorithm is at worst case M * N logN, where M is the number of cities, and N the size of the computational mesh used to approximate the solutions to the shortest paths problems. The average runtime of the heuristic algorithm is linear in the number of cities and O(N log N) in the size N of the mesh.
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…
NASA Astrophysics Data System (ADS)
Rajagopalan, Srinivasan; Robb, Richard
2006-03-01
The degree of match between the delineation result produced by a segmentation technique and the ground truth can be assessed using robust "presence-absence" resemblance measures. Previously, we had investigated and introduced an exhaustive list of similarity indices for assessing multiple segmentation techniques. However, these measures are highly sensitive to even minor boundary perturbations which imminently manifest in the segmentations of random biphasic spaces reminiscent of the stochastic pore-solid distributions in the tissue engineering scaffolds. This paper investigates the ideas adapted from ecology to emphasize global resemblances and ignore minor local dissimilarities. It uses concepts from graph theory to perform controlled local mutations in order to maximize the similarities. The effect of this adjustment is investigated on a comprehensive list (forty nine) of similarity indices sensitive to the over- and under- estimation errors associated with image delineation tasks.
NASA Astrophysics Data System (ADS)
Ferrante, M. C.
1984-12-01
A distributed aperiodic failsafe algorithm is developed for application in a dedicated circuit allocation and restoral environment using circuit precedence features. The algorithm uses update control messages, initiated by changes in network topology or in user-defined truck weighting parameter, to determine shortest path routes. The number for the connected are compared with an equiprobable multinomial distribution and found to deviate only slightly from the hypothesized standard. Performance is slightly worse for a 16-node network than for an 8-node network. Single truck failures and subsequent circuit restoral indicate that high priority circuits will find new end-to-end paths but that low priority circuits stand little chance of restoral. Finally, attempts to include path suitability constraints verify that problem prone routes may be avoided if slightly larger average hop counts per circuit and fewer total circuit connections are tolerable.
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.
Energy Science and Technology Software Center (ESTSC)
2014-01-07
PathFinder is a graph search program, traversing a directed cyclic graph to find pathways between labeled nodes. Searches for paths through ordered sequences of labels are termed signatures. Determining the presence of signatures within one or more graphs is the primary function of Path Finder. Path Finder can work in either batch mode or interactively with an analyst. Results are limited to Path Finder whether or not a given signature is present in the graph(s).
ERIC Educational Resources Information Center
Wilson, Helen W.; Widom, Cathy Spatz
2010-01-01
Behaviors beginning in childhood or adolescence may mediate the relationship between childhood maltreatment and involvement in prostitution. This paper examines 5 potential mediators: early sexual initiation, running away, juvenile crime, school problems, and early drug use. Using a prospective cohort design, abused and neglected children (ages…
NASA Astrophysics Data System (ADS)
Rehmat, Abeera Parvaiz
As we progress into the 21st century, higher-order thinking skills and achievement in science and math are essential to meet the educational requirement of STEM careers. Educators need to think of innovative ways to engage and prepare students for current and future challenges while cultivating an interest among students in STEM disciplines. An instructional pedagogy that can capture students' attention, support interdisciplinary STEM practices, and foster higher-order thinking skills is problem-based learning. Problem-based learning embedded in the social constructivist view of teaching and learning (Savery & Duffy, 1995) promotes self-regulated learning that is enhanced through exploration, cooperative social activity, and discourse (Fosnot, 1996). This quasi-experimental mixed methods study was conducted with 98 fourth grade students. The study utilized STEM content assessments, a standardized critical thinking test, STEM attitude survey, PBL questionnaire, and field notes from classroom observations to investigate the impact of problem-based learning on students' content knowledge, critical thinking, and their attitude towards STEM. Subsequently, it explored students' experiences of STEM integration in a PBL environment. The quantitative results revealed a significant difference between groups in regards to their content knowledge, critical thinking skills, and STEM attitude. From the qualitative results, three themes emerged: learning approaches, increased interaction, and design and engineering implementation. From the overall data set, students described the PBL environment to be highly interactive that prompted them to employ multiple approaches, including design and engineering to solve the problem.
NASA Astrophysics Data System (ADS)
Law, Richard; Waters, Dave; Morgan, Sven; Stahr, Don; Francsis, Matthew; Ashley, Kyle; Kronenberg, Andreas; Thomas, Jay; Mazza, Sarah; Heaverlo, Nicholas
2013-04-01
The quartz c-axis fabric opening-angle thermometer proposed by Kruhl (1998) offers a potential analytical technique for estimating deformation temperatures in rocks deformed by crystal plastic flow. However, in addition to deformation temperature, opening-angle is also sensitive to other variables such as strain rate, degree of hydrolytic weakening, and 3D strain type. Unless the influence of these individual variables can be quantified, use of fabric opening-angle as a deformation thermometer remains problematic and controversial. Over the last decade close correlations between: a) deformation temperatures indicated by fabric opening-angles and, b) temperatures of metamorphism indicated by trace element and mineral phase equilibria analyses, have been reported from a range of different tectonic settings, thereby arguably giving support to the use of opening-angles as a deformation thermometer. However, it needs to be demonstrated that the similar temperatures estimated by the different methods are related to the same geologic event, and therefore occupy at least a similar position on the PTt path - something that is in practice difficult to achieve for an individual rock sample. In cases where temperatures indicated by opening angles and mineral assemblages are markedly different, these differences could, for example, be explained by penetrative deformation and mineral growth/diffusion occurring at different times. Alternatively, when apparent deformation temperatures based on quartz fabrics are significantly greater than temperatures indicated by synchronous metamorphic mineral assemblages, this might be due to extreme hydrolytic weakening of quartz. We illustrate this talk on the pros and cons of using fabric opening-angles as a deformation thermometer with examples from: a) Aureoles of forcibly emplaced plutons in the White-Inyo Range of eastern California where crystal-plastic deformation and recrystallization was short-lived and synchronous with contact
NASA Astrophysics Data System (ADS)
El-Madany, T.; Griessbaum, F.; Maneke, F.; Chu, H.-S.; Wu, C.-C.; Chang, S. C.; Hsia, Y.-J.; Juang, J.-Y.; Klemm, O.
2010-07-01
To estimate carbon dioxide or water vapor fluxes with the Eddy Covariance method high quality data sets are necessary. Under foggy conditions this is challenging, because open path measurements are influenced by the water droplets that cross the measurement path as well as deposit on the windows of the optical path. For the LI-7500 the deposition of droplets on the window results in an intensity reduction of the infrared beam. To keep the strength of the infrared beam under these conditions, the energy is increased. A measure for the increased energy is given by the AGC value (Automatic Gain Control). Up to a AGC threshold value of 70 % the data from the LI-7500 is assumed to be of good quality (personal communication with LICOR). Due to fog deposition on the windows, the AGC value rises above 70 % and stays there until the fog disappears and the water on the windows evaporates. To gain better data quality during foggy conditions, a blower system was developed that blows the deposited water droplets off the window. The system is triggered if the AGC value rises above 70 %. Then a pneumatic jack will lift the blower system towards the LI-7500 and the water-droplets get blown off with compressed air. After the AGC value drops below 70 %, the pneumatic jack will move back to the idle position. Using this technique showed that not only the fog droplets on the window causing significant problems to the measurement, but also the fog droplets inside the measurement path. Under conditions of very dense fog the measured values of carbon dioxide can get unrealistically high, and for water vapor, negative values can be observed even if the AGC value is below 70 %. The negative values can be explained by the scatter of the infrared beam on the fog droplets. It is assumed, that different types of fog droplet spectra are causing the various error patterns observed. For high quality flux measurements, not only the AGC threshold value of 70 % is important, but also the fluctuation
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. PMID:19775961
Identification of Biochemical Network Modules Based on Shortest Retroactive Distances
Sridharan, Gautham Vivek; Hassoun, Soha; Lee, Kyongbum
2011-01-01
Modularity analysis offers a route to better understand the organization of cellular biochemical networks as well as to derive practically useful, simplified models of these complex systems. While there is general agreement regarding the qualitative properties of a biochemical module, there is no clear consensus on the quantitative criteria that may be used to systematically derive these modules. In this work, we investigate cyclical interactions as the defining characteristic of a biochemical module. We utilize a round trip distance metric, termed Shortest Retroactive Distance (ShReD), to characterize the retroactive connectivity between any two reactions in a biochemical network and to group together network components that mutually influence each other. We evaluate the metric on two types of networks that feature feedback interactions: (i) epidermal growth factor receptor (EGFR) signaling and (ii) liver metabolism supporting drug transformation. For both networks, the ShReD partitions found hierarchically arranged modules that confirm biological intuition. In addition, the partitions also revealed modules that are less intuitive. In particular, ShReD-based partition of the metabolic network identified a ‘redox’ module that couples reactions of glucose, pyruvate, lipid and drug metabolism through shared production and consumption of NADPH. Our results suggest that retroactive interactions arising from feedback loops and metabolic cycles significantly contribute to the modularity of biochemical networks. For metabolic networks, cofactors play an important role as allosteric effectors that mediate the retroactive interactions. PMID:22102800
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.
Snell, Mark K.
2007-07-14
The PANL software determines path through an Adversary Sequence Diagram (ASD) with minimum Probability of Interruption, P(I), given the ASD information and data about site detection, delay, and response force times. To accomplish this, the software generates each path through the ASD, then applies the Estimate of Adversary Sequence Interruption (EASI) methodology for calculating P(I) to each path, and keeps track of the path with the lowest P(I). Primary use is for training purposes during courses on physical security design. During such courses PANL will be used to demonstrate to students how more complex software codes are used by the US Department of Energy to determine the most-vulnerable paths and, where security needs improvement, how such codes can help determine physical security upgrades.
Energy Science and Technology Software Center (ESTSC)
2007-07-14
The PANL software determines path through an Adversary Sequence Diagram (ASD) with minimum Probability of Interruption, P(I), given the ASD information and data about site detection, delay, and response force times. To accomplish this, the software generates each path through the ASD, then applies the Estimate of Adversary Sequence Interruption (EASI) methodology for calculating P(I) to each path, and keeps track of the path with the lowest P(I). Primary use is for training purposes duringmore » courses on physical security design. During such courses PANL will be used to demonstrate to students how more complex software codes are used by the US Department of Energy to determine the most-vulnerable paths and, where security needs improvement, how such codes can help determine physical security upgrades.« less
Inter-Domain Redundancy Path Computation Methods Based on PCE
NASA Astrophysics Data System (ADS)
Hayashi, Rie; Oki, Eiji; Shiomoto, Kohei
This paper evaluates three inter-domain redundancy path computation methods based on PCE (Path Computation Element). Some inter-domain paths carry traffic that must be assured of high quality and high reliability transfer such as telephony over IP and premium virtual private networks (VPNs). It is, therefore, important to set inter-domain redundancy paths, i. e. primary and secondary paths. The first scheme utilizes an existing protocol and the basic PCE implementation. It does not need any extension or modification. In the second scheme, PCEs make a virtual shortest path tree (VSPT) considering the candidates of primary paths that have corresponding secondary paths. The goal is to reduce blocking probability; corresponding secondary paths may be found more often after a primary path is decided; no protocol extension is necessary. In the third scheme, PCEs make a VSPT considering all candidates of primary and secondary paths. Blocking probability is further decreased since all possible candidates are located, and the sum of primary and secondary path cost is reduced by choosing the pair with minimum cost among all path pairs. Numerical evaluations show that the second and third schemes offer only a few percent reduction in blocking probability and path pair total cost, while the overheads imposed by protocol revision and increase of the amount of calculation and information to be exchanged are large. This suggests that the first scheme, the most basic and simple one, is the best choice.
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.
Bicriteria network design problems
Marathe, M.V.; Ravi, R.; Sundaram, R.; Ravi, S.S.; Rosenkrantz, D.J.; Hunt, H.B. III
1994-12-31
We study several bicriteria network design problems phrased as follows: given an undirected graph and two minimization objectives with a budget specified on one objective, find a subgraph satisfying certain connectivity requirements that minimizes the second objective subject to the budget on the first. Define an ({alpha}, {beta})-approximation algorithm as a polynomial-time algorithm that produces a solution in which the first objective value is at most {alpha} times the budget, and the second objective value is at most {alpha} times the minimum cost of a network obeying the budget oil the first objective. We, present the first approximation algorithms for bicriteria problems obtained by combining classical minimization objectives such as the total edge cost of the network, the diameter of the network and a weighted generalization of the maximum degree of any node in the network. We first develop some formalism related to bicriteria problems that leads to a clean way to state bicriteria approximation results. Secondly, when the two objectives are similar but only differ based on the cost function under which they are computed we present a general parametric search technique that yields approximation algorithms by reducing the problem to one of minimizing a single objective of the same type. Thirdly, we present an O(log n, log n)-approximation algorithm for finding a diameter-constrained minimum cost spanning tree of an undirected graph on n nodes generalizing the notion of shallow, light trees and light approximate shortest-path trees that have been studied before. Finally, for the class of treewidth-bounded graphs, we provide pseudopolynomial-time algorithms for a number of bicriteria problems using dynamic programming. These pseudopolynomial-time algorithms can be converted to fully polynomial-time approximation schemes using a scaling technique.
Sampling diffusive transition paths
F. Miller III, Thomas; Predescu, Cristian
2006-10-12
We address the problem of sampling double-ended diffusive paths. The ensemble of paths is expressed using a symmetric version of the Onsager-Machlup formula, which only requires evaluation of the force field and which, upon direct time discretization, gives rise to a symmetric integrator that is accurate to second order. Efficiently sampling this ensemble requires avoiding the well-known stiffness problem associated with sampling infinitesimal Brownian increments of the path, as well as a different type of stiffness associated with sampling the coarse features of long paths. The fine-features sampling stiffness is eliminated with the use of the fast sampling algorithm (FSA), and the coarse-feature sampling stiffness is avoided by introducing the sliding and sampling (S&S) algorithm. A key feature of the S&S algorithm is that it enables massively parallel computers to sample diffusive trajectories that are long in time. We use the algorithm to sample the transition path ensemble for the structural interconversion of the 38-atom Lennard-Jones cluster at low temperature.
Sampling diffusive transition paths.
Miller, Thomas F; Predescu, Cristian
2007-04-14
The authors address the problem of sampling double-ended diffusive paths. The ensemble of paths is expressed using a symmetric version of the Onsager-Machlup formula, which only requires evaluation of the force field and which, upon direct time discretization, gives rise to a symmetric integrator that is accurate to second order. Efficiently sampling this ensemble requires avoiding the well-known stiffness problem associated with the sampling of infinitesimal Brownian increments of the path, as well as a different type of stiffness associated with the sampling of the coarse features of long paths. The fine-feature sampling stiffness is eliminated with the use of the fast sampling algorithm, and the coarse-feature sampling stiffness is avoided by introducing the sliding and sampling (S&S) algorithm. A key feature of the S&S algorithm is that it enables massively parallel computers to sample diffusive trajectories that are long in time. The authors use the algorithm to sample the transition path ensemble for the structural interconversion of the 38-atom Lennard-Jones cluster at low temperature. PMID:17444696
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.
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. PMID:26066805
An Optimal Level of Adding Edges for a Simple Path to a Complete K-ary Tree
NASA Astrophysics Data System (ADS)
Sawada, Kiyoshi
2010-10-01
This study proposes a model of adding edges of forming a simple path to a level of depth N in a complete K-ary (K≥3) tree of height H under giving priority to edges between two nodes of which the deepest common ancestor is deeper. An optimal depth N* is obtained by maximizing the total shortening path length which is the sum of shortening lengths of shortest paths between every pair of all nodes in the complete K-ary tree.
Minimum-Risk Path Finding by an Adaptive Amoebal Network
NASA Astrophysics Data System (ADS)
Nakagaki, Toshiyuki; Iima, Makoto; Ueda, Tetsuo; Nishiura, Yasumasa; Saigusa, Tetsu; Tero, Atsushi; Kobayashi, Ryo; Showalter, Kenneth
2007-08-01
When two food sources are presented to the slime mold Physarum in the dark, a thick tube for absorbing nutrients is formed that connects the food sources through the shortest route. When the light-avoiding organism is partially illuminated, however, the tube connecting the food sources follows a different route. Defining risk as the experimentally measurable rate of light-avoiding movement, the minimum-risk path is exhibited by the organism, determined by integrating along the path. A model for an adaptive-tube network is presented that is in good agreement with the experimental observations.
NASA Astrophysics Data System (ADS)
Ohno, Akiyoshi; Nishi, Tatsushi; Inuiguchi, Masahiro; Takahashi, Satoru; Ueda, Kenji
In this paper, we propose a column generation for the train-set scheduling problem with regular maintenance constraints. The problem is to allocate the minimum train-set to the train operations required to operate a given train timetable. In the proposed method, a tight lower bound can be obtained from the continuous relaxation for Dantzig-Wolfe reformulation by column generation. The subproblem for the column generation is an elementary shortest path problem with resource constraints. A labeling algorithm is applied to solve the subproblem. In order to reduce the computational effort for solving subproblems, a new state space relaxation of the subproblem is developed in the labeling algorithm. An upper bound is computed by a heuristic algorithm. Computational results demonstrate the effectiveness of the proposed method.
Mitchell, J.S.B.; Mount, D.M.; Papadimitriou, C.H.
1987-08-01
The authors present an algorithm for determining the shortest path between a source and a destination on an arbitrary (possibly nonconvex) polyhedral surface. The path is constrained to lie on the surface, and distances are measured according to the Euclidean metric. The algorithm runs in time O(n/sup 2/ log n) and requires O(n/sup 2/) space, where n is the number of edges of the surface. After running the algorithm, the distance from the source to any other destination may be determined using standard techniques in time O(log n) by locating the destination in the subdivision created by the algorithm. The actual shortest path from the source to a destination can be reported in time O(kappa+log n), where kappa is the number of faces crossed by the path. The algorithm generalizes to the case of multiple source points to build the Voronoi diagram on the surface, where n is now the maximum of the number of vertices and the number of sources.
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.
Analyzing methods for path mining with applications in metabolomics.
Tagore, Somnath; Chowdhury, Nirmalya; De, Rajat K
2014-01-25
Metabolomics is one of the key approaches of systems biology that consists of studying biochemical networks having a set of metabolites, enzymes, reactions and their interactions. As biological networks are very complex in nature, proper techniques and models need to be chosen for their better understanding and interpretation. One of the useful strategies in this regard is using path mining strategies and graph-theoretical approaches that help in building hypothetical models and perform quantitative analysis. Furthermore, they also contribute to analyzing topological parameters in metabolome networks. Path mining techniques can be based on grammars, keys, patterns and indexing. Moreover, they can also be used for modeling metabolome networks, finding structural similarities between metabolites, in-silico metabolic engineering, shortest path estimation and for various graph-based analysis. In this manuscript, we have highlighted some core and applied areas of path-mining for modeling and analysis of metabolic networks. PMID:24230973
Calculating Least Risk Paths in 3d Indoor Space
NASA Astrophysics Data System (ADS)
Vanclooster, A.; De Maeyer, Ph.; Fack, V.; Van de Weghe, N.
2013-08-01
Over the last couple of years, research on indoor environments has gained a fresh impetus; more specifically applications that support navigation and wayfinding have become one of the booming industries. Indoor navigation research currently covers the technological aspect of indoor positioning and the modelling of indoor space. The algorithmic development to support navigation has so far been left mostly untouched, as most applications mainly rely on adapting Dijkstra's shortest path algorithm to an indoor network. However, alternative algorithms for outdoor navigation have been proposed adding a more cognitive notion to the calculated paths and as such adhering to the natural wayfinding behaviour (e.g. simplest paths, least risk paths). These algorithms are currently restricted to outdoor applications. The need for indoor cognitive algorithms is highlighted by a more challenged navigation and orientation due to the specific indoor structure (e.g. fragmentation, less visibility, confined areas…). As such, the clarity and easiness of route instructions is of paramount importance when distributing indoor routes. A shortest or fastest path indoors not necessarily aligns with the cognitive mapping of the building. Therefore, the aim of this research is to extend those richer cognitive algorithms to three-dimensional indoor environments. More specifically for this paper, we will focus on the application of the least risk path algorithm of Grum (2005) to an indoor space. The algorithm as proposed by Grum (2005) is duplicated and tested in a complex multi-storey building. The results of several least risk path calculations are compared to the shortest paths in indoor environments in terms of total length, improvement in route description complexity and number of turns. Several scenarios are tested in this comparison: paths covering a single floor, paths crossing several building wings and/or floors. Adjustments to the algorithm are proposed to be more aligned to the
Extremal paths on a random Cayley tree
NASA Astrophysics Data System (ADS)
Majumdar, Satya N.; Krapivsky, P. L.
2000-12-01
We investigate the statistics of extremal path(s) (both the shortest and the longest) from the root to the bottom of a Cayley tree. The lengths of the edges are assumed to be independent identically distributed random variables drawn from a distribution ρ(l). Besides, the number of branches from any node is also random. Exact results are derived for arbitrary distribution ρ(l). In particular, for the binary \\{0,1\\} distribution ρ(l)=pδl,1+(1-p)δl,0, we show that as p increases, the minimal length undergoes an unbinding transition from a ``localized'' phase to a ``moving'' phase at the critical value, p=pc=1-b-1, where b is the average branch number of the tree. As the height n of the tree increases, the minimal length saturates to a finite constant in the localized phase (p
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.
Kochanska, Grazyna; Brock, Rebecca L.; Chen, Kuan-Hua; Aksan, Nazan; Anderson, Steven W.
2014-01-01
Electrodermal hyporeactivity (or low skin conductance level, SCL) has been long established as a correlate of and diathesis for antisocial behavior, aggression, disregard for rules of conduct and feelings of others, and generally, externalizing behavior problems in children and adults. Much less is known, however, about how individual differences in children’s SCL and qualities of their early experiences in relationships with parents interact to produce antisocial outcomes. In a community sample of 102 families (51 girls), we examined children’s SCL, assessed in standard laboratory tasks at age 8 (N=81), as a moderator of the links between parent–child socialization history and children’s externalizing behavior problems at ages 8 and 10, reported by mothers and fathers in well-established instruments and by children in clinical interviews. Mother- and father-child socialization history was assessed in frequent, intensive observations. Parent–child mutually responsive orientation (MRO) was observed from infancy to age 10, parental power assertion was observed from 15 months to age 6 ½, and children reported their attachment security in interviews at age 8 and 10. For children with lower SCL, variations in mothers’ power assertion and father-child MRO were associated with parent-rated externalizing problems. The former interaction was consistent with diathesis-stress, and the latter with differential susceptibility. For children with higher SCL, there were no links between socialization history and externalizing problems. PMID:25218772
Thermoalgebras and path integral
NASA Astrophysics Data System (ADS)
Khanna, F. C.; Malbouisson, A. P. C.; Malbouisson, J. M. C.; Santana, A. E.
2009-09-01
Using a representation for Lie groups closely associated with thermal problems, we derive the algebraic rules of the real-time formalism for thermal quantum field theories, the so-called thermo-field dynamics (TFD), including the tilde conjugation rules for interacting fields. These thermo-group representations provide a unified view of different approaches for finite-temperature quantum fields in terms of a symmetry group. On these grounds, a path integral formalism is constructed, using Bogoliubov transformations, for bosons, fermions and non-abelian gauge fields. The generalization of the results for quantum fields in (S1)d×R topology is addressed.
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.
NASA Technical Reports Server (NTRS)
Smedes, H. W.; Hulstrom, R. L.; Ranson, K. J.
1975-01-01
The results of LANDSAT and Skylab research programs on the effects of the atmosphere on computer mapping of terrain include: (1) the concept of a ground truth map needs to be drastically revised; (2) the concept of training areas and test areas is not as simple as generally thought because of the problem of pixels that represent a mixture of terrain classes; (3) this mixture problem needs to be more widely recognized and dealt with by techniques of calculating spectral signatures of mixed classes, or by other methods; (4) atmospheric effects should be considered in computer mapping of terrain and in monitoring changes; and (5) terrain features may be used as calibration panels on the ground, from which atmospheric conditions can be determined and monitored. Results are presented of a test area in mountainous terrain of south-central Colorado for which an initial classification was made using simulated mixture-class spectral signatures and actual LANDSAT-1-MSS data.
Analyzing the applicability of the least risk path algorithm in indoor space
NASA Astrophysics Data System (ADS)
Vanclooster, A.; Viaene, P.; Van de Weghe, N.; Fack, V.; De Maeyer, Ph.
2013-11-01
Over the last couple of years, applications that support navigation and wayfinding in indoor environments have become one of the booming industries. However, the algorithmic support for indoor navigation has so far been left mostly untouched, as most applications mainly rely on adapting Dijkstra's shortest path algorithm to an indoor network. In outdoor space, several alternative algorithms have been proposed adding a more cognitive notion to the calculated paths and as such adhering to the natural wayfinding behavior (e.g. simplest paths, least risk paths). The need for indoor cognitive algorithms is highlighted by a more challenged navigation and orientation due to the specific indoor structure (e.g. fragmentation, less visibility, confined areas…). Therefore, the aim of this research is to extend those richer cognitive algorithms to three-dimensional indoor environments. More specifically for this paper, we will focus on the application of the least risk path algorithm of Grum (2005) to an indoor space. The algorithm as proposed by Grum (2005) is duplicated and tested in a complex multi-story building. Several analyses compare shortest and least risk paths in indoor and in outdoor space. The results of these analyses indicate that the current outdoor least risk path algorithm does not calculate less risky paths compared to its shortest paths. In some cases, worse routes have been suggested. Adjustments to the original algorithm are proposed to be more aligned to the specific structure of indoor environments. In a later stage, other cognitive algorithms will be implemented and tested in both an indoor and combined indoor-outdoor setting, in an effort to improve the overall user experience during navigation in indoor environments.
Balanced Paths in Colored Graphs
NASA Astrophysics Data System (ADS)
Bianco, Alessandro; Faella, Marco; Mogavero, Fabio; Murano, Aniello
We consider finite graphs whose edges are labeled with elements, called colors, taken from a fixed finite alphabet. We study the problem of determining whether there is an infinite path where either (i) all colors occur with the same asymptotic frequency, or (ii) there is a constant which bounds the difference between the occurrences of any two colors for all prefixes of the path. These two notions can be viewed as refinements of the classical notion of fair path, whose simplest form checks whether all colors occur infinitely often. Our notions provide stronger criteria, particularly suitable for scheduling applications based on a coarse-grained model of the jobs involved. We show that both problems are solvable in polynomial time, by reducing them to the feasibility of a linear program.
Mechanics of the crack path formation
NASA Technical Reports Server (NTRS)
Rubinstein, Asher A.
1991-01-01
A detailed analysis of experimentally obtained curvilinear crack path trajectories formed in a heterogeneous stress field is presented. Experimental crack path trajectories were used as data for the numerical simulations, recreating the actual stress field governing the development of the crack path. Thus, the current theories of crack curving and kinking could be examined by comparing them with the actual stress field parameters as they develop along the experimentally observed crack path. The experimental curvilinear crack path trajectories were formed in the tensile specimens with a hole positioned in the vicinity of a potential crack path. The numerical simulation, based on the solution of equivalent boundary value problems with the possible perturbations of the crack path, is presented.
Mechanics of the crack path formation
NASA Technical Reports Server (NTRS)
Rubinstein, Asher A.
1989-01-01
A detailed analysis of experimentally obtained curvilinear crack path trajectories formed in a heterogeneous stress field is presented. Experimental crack path trajectories were used as data for numerical simulations, recreating the actual stress field governing the development of the crack path. Thus, the current theories of crack curving and kinking could be examined by comparing them with the actual stress field parameters as they develop along the experimentally observed crack path. The experimental curvilinear crack path trajectories were formed in the tensile specimens with a hole positioned in the vicinity of a potential crack path. The numerical simulation, based on the solution of equivalent boundary value problems with the possible perturbations of the crack path, is presented here.
Analog and digital FPGA implementation of BRIN for optimization problems.
Ng, H S; Lam, K P
2003-01-01
The binary relation inference network (BRIN) shows promise in obtaining the global optimal solution for optimization problem, which is time independent of the problem size. However, the realization of this method is dependent on the implementation platforms. We studied analog and digital FPGA implementation platforms. Analog implementation of BRIN for two different directed graph problems is studied. As transitive closure problems can transform to a special case of shortest path problems or a special case of maximum spanning tree problems, two different forms of BRIN are discussed. Their circuits using common analog integrated circuits are investigated. The BRIN solution for critical path problems is expressed and is implemented using the separated building block circuit and the combined building block circuit. As these circuits are different, the response time of these networks will be different. The advancement of field programmable gate arrays (FPGAs) in recent years, allowing millions of gates on a single chip and accompanying with high-level design tools, has allowed the implementation of very complex networks. With this exemption on manual circuit construction and availability of efficient design platform, the BRIN architecture could be built in a much more efficient way. Problems on bandwidth are removed by taking all previous external connections to the inside of the chip. By transforming BRIN to FPGA (Xilinx XC4010XL and XCV800 Virtex), we implement a synchronous network with computations in a finite number of steps. Two case studies are presented, with correct results verified from simulation implementation. Resource consumption on FPGAs is studied showing that Virtex devices are more suitable for the expansion of network in future developments. PMID:18244587
Rabani, Y.
1996-12-31
In the minimum path coloring problem, we are given a list of pairs of vertices of a graph. We are asked to connect each pair by a colored path. Paths of the same color must be edge disjoint. Our objective is to minimize the number of colors used. This problem was raised by Aggarwal et al and Raghavan and Upfal as a model for routing in all-optical networks. It is also related to questions in circuit routing. In this paper, we improve the O (ln N) approximation result of Kleinberg and Tardos for path coloring on the N x N mesh. We give an O(1) approximation algorithm to the number of colors needed, and a poly(ln ln N) approximation algorithm to the choice of paths and colors. To the best of our knowledge, these are the first sub-logarithmic bounds for any network other than trees, rings, or trees of rings. Our results are based on developing new techniques for randomized rounding. These techniques iteratively improve a fractional solution until it approaches integrality. They are motivated by the method used by Leighton, Maggs, and Rao for packet routing.
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.
Energy Science and Technology Software Center (ESTSC)
2012-05-11
The ap command traveres all symlinks in a given file, directory, or executable name to identify the final absolute path. It can print just the final path, each intermediate link along with the symlink chan, and the permissions and ownership of each directory component in the final path. It has functionality similar to "which", except that it shows the final path instead of the first path. It is also similar to "pwd", but it canmore » provide the absolute path to a relative directory from the current working directory.« less
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.
VLBI Observations of the Shortest Orbital Period Black Hole X-Ray Binary
NASA Astrophysics Data System (ADS)
Paragi, Zsolt; Belloni, Tomaso M.; van der Horst, Alexander J.; Miller-Jones, James
The X-ray transient MAXI J1659-152 was discovered by Swift/BAT and it was initially identified as a GRB. Soon its Galactic origin and binary nature were established. There exists a wealth of multi-wavelength monitoring data for this source, providing a great coverage of the full X-ray transition in this candidate black hole binary system. We obtained two epochs of EVN/e-VLBI and four epochs of VLBA data of MAXI J1659-152 which show evidence for some extended emission in the early phases but -against expectations- no major collimated ejecta during the accretion disk state transition. This might be related to the fact that, with a red dwarf donor star, MAXI J1659-152 is the shortest orbital period black hole X-ray binary system.
Research on Taxiway Path Optimization Based on Conflict Detection.
Zhou, Hang; Jiang, Xinxin
2015-01-01
Taxiway path planning is one of the effective measures to make full use of the airport resources, and the optimized paths can ensure the safety of the aircraft during the sliding process. In this paper, the taxiway path planning based on conflict detection is considered. Specific steps are shown as follows: firstly, make an improvement on A * algorithm, the conflict detection strategy is added to search for the shortest and safe path in the static taxiway network. Then, according to the sliding speed of aircraft, a time table for each node is determined and the safety interval is treated as the constraint to judge whether there is a conflict or not. The intelligent initial path planning model is established based on the results. Finally, make an example in an airport simulation environment, detect and relieve the conflict to ensure the safety. The results indicate that the model established in this paper is effective and feasible. Meanwhile, make comparison with the improved A*algorithm and other intelligent algorithms, conclude that the improved A*algorithm has great advantages. It could not only optimize taxiway path, but also ensure the safety of the sliding process and improve the operational efficiency. PMID:26226485
Research on Taxiway Path Optimization Based on Conflict Detection
Zhou, Hang; Jiang, Xinxin
2015-01-01
Taxiway path planning is one of the effective measures to make full use of the airport resources, and the optimized paths can ensure the safety of the aircraft during the sliding process. In this paper, the taxiway path planning based on conflict detection is considered. Specific steps are shown as follows: firstly, make an improvement on A * algorithm, the conflict detection strategy is added to search for the shortest and safe path in the static taxiway network. Then, according to the sliding speed of aircraft, a time table for each node is determined and the safety interval is treated as the constraint to judge whether there is a conflict or not. The intelligent initial path planning model is established based on the results. Finally, make an example in an airport simulation environment, detect and relieve the conflict to ensure the safety. The results indicate that the model established in this paper is effective and feasible. Meanwhile, make comparison with the improved A*algorithm and other intelligent algorithms, conclude that the improved A*algorithm has great advantages. It could not only optimize taxiway path, but also ensure the safety of the sliding process and improve the operational efficiency. PMID:26226485
A 2D analytical cylindrical gate tunnel FET (CG-TFET) model: impact of shortest tunneling distance
NASA Astrophysics Data System (ADS)
Dash, S.; Mishra, G. P.
2015-09-01
A 2D analytical tunnel field-effect transistor (FET) potential model with cylindrical gate (CG-TFET) based on the solution of Laplace’s equation is proposed. The band-to-band tunneling (BTBT) current is derived by the help of lateral electric field and the shortest tunneling distance. However, the analysis is extended to obtain the subthreshold swing (SS) and transfer characteristics of the device. The dependency of drain current, SS and transconductance on gate voltage and shortest tunneling distance is discussed. Also, the effect of scaling the gate oxide thickness and the cylindrical body diameter on the electrical parameters of the device is analyzed.
Numerical evaluation of Feynman path integrals
NASA Astrophysics Data System (ADS)
Baird, William Hugh
1999-11-01
The notion of path integration developed by Feynman, while an incredibly successful method of solving quantum mechanical problems, leads to frequently intractable integrations over an infinite number of paths. Two methods now exist which sidestep this difficulty by defining "densities" of actions which give the relative number of paths found at different values of the action. These densities are sampled by computer generation of paths and the propagators are found to a high degree of accuracy for the case of a particle on the infinite half line and in a finite square well in one dimension. The problem of propagation within a two dimensional radial well is also addressed as the precursor to the problem of a particle in a stadium (quantum billiard).
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.
Resonating-Valence-Bond Physics Is Not Always Governed by the Shortest Tunneling Loops
NASA Astrophysics Data System (ADS)
Ralko, Arnaud; Rousochatzakis, Ioannis
2015-10-01
It is well known that the low-energy sector of quantum spin liquids and other magnetically disordered systems is governed by short-ranged resonating-valence bonds. Here we show that the standard minimal truncation to the nearest-neighbor valence-bond basis fails completely even for systems where it should work the most, according to received wisdom. This paradigm shift is demonstrated for the quantum spin-1 /2 square kagome, where strong geometric frustration, similar to the kagome, prevents magnetic ordering down to zero temperature. The shortest tunneling events bear the strongest longer-range singlet fluctuations, leading to amplitudes that do not drop exponentially with the length of the loop L , and to an unexpected loop-six valence-bond crystal, which is otherwise very high in energy at the minimal truncation level. The low-energy effective description gives in addition a clear example of correlated loop processes that depend not only on the type of the loop but also on its lattice embedding, a direct manifestation of the long-range nature of the virtual singlets.
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.
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.
ERIC Educational Resources Information Center
Guven, Bulent
2008-01-01
As any ordinary person knows, the shortest distance between two points is a straight line. What, then, is the shortest distance between three points? Four points? The study reported in this article deals with the observed actions of Turkish student mathematics teachers as they were working with minimal network problems. Having analysed the…
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.
Accretion disc mapping of the shortest period eclipsing binary SDSS J0926+36
NASA Astrophysics Data System (ADS)
Schlindwein, W.; Baptista, R.
2014-10-01
AM CVn stars are ultracompact binaries (P_{orb}< 65 min) where a hydrogen-deficient low-mass, degenerate donor star overfills its Roche lobe and transfers matter to a companion white dwarf via an accretion disc. SDSS J0926+36 is currently the only eclipsing AM CVn star and also the shortest period eclipsing binary known. Its light curve displays deep (˜ 2 mag) eclipses every 28.3 min, which last for ˜ 2 min, as well as ˜ 2 mag amplitude outbursts every ˜ 100-200 d. Superhumps were seen in its quiescent light curve in some occasions, probably as a reminiscence of a (in some cases undetected) previous outburst. Its eclipsing nature allows a unique opportunity to disentangle the emission from several different light sources, and to map the surface brightness distribution of its hydrogen-deficient accretion disc with the aid of maximum entropy eclipse mapping techniques. Here we report the eclipse mapping analysis of optical light curves of SDSS J0926+36, collected with the 2.4 m Liverpool Robotic Telescope, covering 20 orbits of the binary over 5 nights of observations between 2012 February and March. The object was in quiescence at all runs. Our data show no evidence of superhumps nor of orbital modulation due to anisotropic emission from a bright spot at disc rim. Accordingly, the average out-of-eclipse flux level is consistent with that of the superhump-subtracted previous light curves. We combined all runs to obtain an orbital light curve of improved S/N. The corresponding eclipse map shows a compact source at disc centre (T_{b}simeq 17000 K), a faint, cool accretion disc (˜ 4000 K) plus enhanced emission along the gas stream (˜ 6000 K) beyond the impact point at the outer disc rim, suggesting the occurrence of gas stream overflow at that epoch.
New approximation algorithms for flow shop total completion time problem
NASA Astrophysics Data System (ADS)
Bai, Danyu; Ren, Tao
2013-09-01
This article addresses the flow shop scheduling problem to minimize the sum of the completion times. On the basis of the properties in job sequencing, the triangular shortest processing time (TSPT) first and dynamic triangular shortest processing time first heuristics are designed to solve the static and dynamic versions of this problem, respectively. Moreover, an improvement scheme is provided for these heuristics to enhance the quality of the original solutions. For further numerical evaluation of the heuristics, two new lower bounds with performance guarantees are presented for the two versions of the problem. At the end of the article, a series of numerical experiments is conducted to demonstrate the effectiveness of the algorithms.
An analogue approach to the travelling salesman problem using an elastic net method
NASA Astrophysics Data System (ADS)
Durbin, Richard; Willshaw, David
1987-04-01
The travelling salesman problem1 is a classical problem in the field of combinatorial optimization, concerned with efficient methods for maximizing or minimizing a function of many independent variables. Given the positions of N cities, which in the simplest case lie in the plane, what is the shortest closed tour in which each city can be visited once? We describe how a parallel analogue algorithm, derived from a formal model2-3 for the establishment of topographically ordered projections in the brain4-10, can be applied to the travelling salesman problem1,11,12. Using an iterative procedure, a circular closed path is gradually elongated non-uniformly until it eventually passes sufficiently near to all the cities to define a tour. This produces shorter tour lengths than another recent parallel analogue algorithm13, scales well with the size of the problem, and is naturally extendable to a large class of optimization problems involving topographic mappings between geometrical structures14.
NASA Technical Reports Server (NTRS)
Barker, L. Keith
1998-01-01
The primary purpose of this publication is to develop a mathematical model to describe smooth paths along any combination of circles and tangent lines. Two consecutive circles in a path are either tangent (externally or internally) or they appear on the same (lateral) or opposite (transverse) sides of a connecting tangent line. A path may start or end on either a segment or circle. The approach is to use mathematics common to robotics to design the path as a multilink manipulator. This approach allows a hierarchical view of the problem and keeps the notation manageable. A user simply specifies a few parameters to configure a path. Necessary and sufficient conditions automatically ensure the consistency of the inputs for a smooth path. Two example runway exit paths are given, and an angle to go assists in knowing when to switch from one path element to the next.
Breast Contour Detection with Stable Paths
NASA Astrophysics Data System (ADS)
Cardoso, Jaime S.; Sousa, Ricardo; Teixeira, Luís F.; Cardoso, M. J.
Breast cancer conservative treatment (BCCT), due to its proven oncological safety, is considered, when feasible, the gold standard of breast cancer treatment. However, aesthetic results are heterogeneous and difficult to evaluate in a standardized way, due to the lack of reproducibility of the subjective methods usually applied. The objective assessment methods, considered in the past as being less capable of evaluating all aspects of BCCT, are nowadays being preferred to overcome the drawbacks of the subjective evaluation. A computer-aided medical system was recently developed to objectively and automatically evaluate the aesthetic result of BCCT. In this system, the detection of the breast contour on the patient's digital photograph is a necessary step to extract the features subsequently used in the evaluation process. In this paper an algorithm based on the shortest path on a graph is proposed to detect automatically the breast contour. The proposed method extends an existing semi-automatic algorithm for the same purpose. A comprehensive comparison with manually-drawn contours reveals the strength of the proposed method.
Automatic tracking of neuro vascular tree paths
NASA Astrophysics Data System (ADS)
Suryanarayanan, S.; Gopinath, A.; Mallya, Y.; Shriram, K. S.; Joshi, M.
2006-03-01
3-D analysis of blood vessels from volumetric CT and MR datasets has many applications ranging from examination of pathologies such as aneurysm and calcification to measurement of cross-sections for therapy planning. Segmentation of the vascular structures followed by tracking is an important processing step towards automating the 3-D vessel analysis workflow. This paper demonstrates a fast and automated algorithm for tracking the major arterial structures that have been previously segmented. Our algorithm uses anatomical knowledge to identify the start and end points in the vessel structure that allows automation. Voxel coding scheme is used to code every voxel in the vessel based on its geodesic distance from the start point. A shortest path based iterative region growing is used to extract the vessel tracks that are subsequently smoothed using an active contour method. The algorithm also has the ability to automatically detect bifurcation points of major arteries. Results are shown for tracking the major arteries such as the common carotid, internal carotid, vertebrals, and arteries coming off the Circle of Willis across multiple cases with various data related and pathological challenges from 7 CTA cases and 2 MR Time of Flight (TOF) cases.
MAXI J1659-152: the shortest orbital period black-hole transient in outburst
NASA Astrophysics Data System (ADS)
Kuulkers, E.; Kouveliotou, C.; Belloni, T.; Cadolle Bel, M.; Chenevez, J.; Díaz Trigo, M.; Homan, J.; Ibarra, A.; Kennea, J. A.; Muñoz-Darias, T.; Ness, J.-U.; Parmar, A. N.; Pollock, A. M. T.; van den Heuvel, E. P. J.; van der Horst, A. J.
2013-04-01
MAXI J1659-152 is a bright X-ray transient black-hole candidate binary system discovered in September 2010. We report here on MAXI, RXTE, Swift, and XMM-Newton observations during its 2010/2011 outburst. We find that during the first one and a half week of the outburst the X-ray light curves display drops in intensity at regular intervals, which we interpret as absorption dips. About three weeks into the outbursts, again drops in intensity are seen. These dips have, however, a spectral behaviour opposite to that of the absorption dips, and are related to fast spectral state changes (hence referred to as transition dips). The absorption dips recur with a period of 2.414 ± 0.005 h, which we interpret as the orbital period of the system. This implies that MAXI J1659-152 is the shortest period black-hole candidate binary known to date. The inclination of the accretion disk with respect to the line of sight is estimated to be 65-80°. We propose the companion to the black-hole candidate to be close to an M5 dwarf star, with a mass and radius of about 0.15-0.25 M⊙ and 0.2-0.25 R⊙, respectively. We derive that the companion had an initial mass of about 1.5 M⊙, which evolved to its current mass in about 5-6 billion years. The system is rather compact (orbital separation of ≳1.33 R⊙), and is located at a distance of 8.6 ± 3.7 kpc, with a height above the Galactic plane of 2.4 ± 1.0 kpc. The characteristics of short orbital period and high Galactic scale height are shared with two other transient black-hole candidate X-ray binaries, i.e., XTE J1118+480 and Swift J1735.5-0127. We suggest that all three are kicked out of the Galactic plane into the halo, rather than being formed in a globular cluster. Table 1 is available in electronic form at http://www.aanda.org
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.
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.
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.)
Zhang, Zili; Gao, Chao; Lu, Yuxiao; Liu, Yuxin; Liang, Mingxin
2016-01-01
Bi-objective Traveling Salesman Problem (bTSP) is an important field in the operations research, its solutions can be widely applied in the real world. Many researches of Multi-objective Ant Colony Optimization (MOACOs) have been proposed to solve bTSPs. However, most of MOACOs suffer premature convergence. This paper proposes an optimization strategy for MOACOs by optimizing the initialization of pheromone matrix with the prior knowledge of Physarum-inspired Mathematical Model (PMM). PMM can find the shortest route between two nodes based on the positive feedback mechanism. The optimized algorithms, named as iPM-MOACOs, can enhance the pheromone in the short paths and promote the search ability of ants. A series of experiments are conducted and experimental results show that the proposed strategy can achieve a better compromise solution than the original MOACOs for solving bTSPs. PMID:26751562
Zhang, Zili; Gao, Chao; Lu, Yuxiao; Liu, Yuxin; Liang, Mingxin
2016-01-01
Bi-objective Traveling Salesman Problem (bTSP) is an important field in the operations research, its solutions can be widely applied in the real world. Many researches of Multi-objective Ant Colony Optimization (MOACOs) have been proposed to solve bTSPs. However, most of MOACOs suffer premature convergence. This paper proposes an optimization strategy for MOACOs by optimizing the initialization of pheromone matrix with the prior knowledge of Physarum-inspired Mathematical Model (PMM). PMM can find the shortest route between two nodes based on the positive feedback mechanism. The optimized algorithms, named as iPM-MOACOs, can enhance the pheromone in the short paths and promote the search ability of ants. A series of experiments are conducted and experimental results show that the proposed strategy can achieve a better compromise solution than the original MOACOs for solving bTSPs. PMID:26751562
Method of path coefficients: a trademark of Sewall Wright.
Li, C C
1991-02-01
This address is a tribute to a pioneer of population genetics, including human population genetics. The unique methodology employed by Sewall Wright in many genetic problems is the method of path coefficients. This essay traces the historical landmarks in the development of the path method and then shows how some of the conventional statistical results can be converted into expressions involving path coefficients. The construction of a path diagram to represent such statistical results is explained in terms of examples. In the last section an example of applying the path method to the problem of genetic linkage in a random mating population is given. I hope that, despite the ending of the Sewall Wright era, the path method will continue to serve the scientific world. PMID:2004740
Path efficiency of ant foraging trails in an artificial network.
Vittori, Karla; Talbot, Grégoire; Gautrais, Jacques; Fourcassié, Vincent; Araújo, Aluizio F R; Theraulaz, Guy
2006-04-21
In this paper we present an individual-based model describing the foraging behavior of ants moving in an artificial network of tunnels in which several interconnected paths can be used to reach a single food source. Ants lay a trail pheromone while moving in the network and this pheromone acts as a system of mass recruitment that attracts other ants in the network. The rules implemented in the model are based on measures of the decisions taken by ants at tunnel bifurcations during real experiments. The collective choice of the ants is estimated by measuring their probability to take a given path in the network. Overall, we found a good agreement between the results of the simulations and those of the experiments, showing that simple behavioral rules can lead ants to find the shortest paths in the network. The match between the experiments and the model, however, was better for nestbound than for outbound ants. A sensitivity study of the model suggests that the bias observed in the choice of the ants at asymmetrical bifurcations is a key behavior to reproduce the collective choice observed in the experiments. PMID:16199059
A Critical Path Analysis of Scientific Productivity.
ERIC Educational Resources Information Center
Loehle, Craig
1994-01-01
This article presents a queuing model simulation of scientific productivity utilizing critical path analysis. Creativity is found to have a large positive effect, a negative effect, or no effect on productivity, depending on the stage of the problem-solving process to which it is applied and the nature of the bottlenecks inherent to the specific…
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
Qian, Weixian; Zhou, Xiaojun; Lu, Yingcheng; Xu, Jiang
2015-09-15
Both the Jones and Mueller matrices encounter difficulties when physically modeling mixed materials or rough surfaces due to the complexity of light-matter interactions. To address these issues, we derived a matrix called the paths correlation matrix (PCM), which is a probabilistic mixture of Jones matrices of every light propagation path. Because PCM is related to actual light propagation paths, it is well suited for physical modeling. Experiments were performed, and the reflection PCM of a mixture of polypropylene and graphite was measured. The PCM of the mixed sample was accurately decomposed into pure polypropylene's single reflection, pure graphite's single reflection, and depolarization caused by multiple reflections, which is consistent with the theoretical derivation. Reflection parameters of rough surface can be calculated from PCM decomposition, and the results fit well with the theoretical calculations provided by the Fresnel equations. These theoretical and experimental analyses verify that PCM is an efficient way to physically model light-matter interactions. PMID:26371930
Flux Control in Networks of Diffusion Paths
A. I. Zhmoginov and N. J. Fisch
2009-07-08
A class of optimization problems in networks of intersecting diffusion domains of a special form of thin paths has been considered. The system of equations describing stationary solutions is equivalent to an electrical circuit built of intersecting conductors. The solution of an optimization problem has been obtained and extended to the analogous electrical circuit. The interest in this network arises from, among other applications, an application to wave-particle diffusion through resonant interactions in plasma.
Multi-Level Indoor Path Planning Method
NASA Astrophysics Data System (ADS)
Xiong, Q.; Zhu, Q.; Zlatanova, S.; Du, Z.; Zhang, Y.; Zeng, L.
2015-05-01
Indoor navigation is increasingly widespread in complex indoor environments, and indoor path planning is the most important part of indoor navigation. Path planning generally refers to finding the most suitable path connecting two locations, while avoiding collision with obstacles. However, it is a fundamental problem, especially for 3D complex building model. A common way to solve the issue in some applications has been approached in a number of relevant literature, which primarily operates on 2D drawings or building layouts, possibly with few attached attributes for obstacles. Although several digital building models in the format of 3D CAD have been used for path planning, they usually contain only geometric information while losing abundant semantic information of building components (e.g. types and attributes of building components and their simple relationships). Therefore, it becomes important to develop a reliable method that can enhance application of path planning by combining both geometric and semantic information of building components. This paper introduces a method that support 3D indoor path planning with semantic information.
Minimal entropy probability paths between genome families.
Ahlbrandt, Calvin; Benson, Gary; Casey, William
2004-05-01
We develop a metric for probability distributions with applications to biological sequence analysis. Our distance metric is obtained by minimizing a functional defined on the class of paths over probability measures on N categories. The underlying mathematical theory is connected to a constrained problem in the calculus of variations. The solution presented is a numerical solution, which approximates the true solution in a set of cases called rich paths where none of the components of the path is zero. The functional to be minimized is motivated by entropy considerations, reflecting the idea that nature might efficiently carry out mutations of genome sequences in such a way that the increase in entropy involved in transformation is as small as possible. We characterize sequences by frequency profiles or probability vectors, in the case of DNA where N is 4 and the components of the probability vector are the frequency of occurrence of each of the bases A, C, G and T. Given two probability vectors a and b, we define a distance function based as the infimum of path integrals of the entropy function H( p) over all admissible paths p(t), 0 < or = t< or =1, with p(t) a probability vector such that p(0)=a and p(1)=b. If the probability paths p(t) are parameterized as y(s) in terms of arc length s and the optimal path is smooth with arc length L, then smooth and "rich" optimal probability paths may be numerically estimated by a hybrid method of iterating Newton's method on solutions of a two point boundary value problem, with unknown distance L between the abscissas, for the Euler-Lagrange equations resulting from a multiplier rule for the constrained optimization problem together with linear regression to improve the arc length estimate L. Matlab code for these numerical methods is provided which works only for "rich" optimal probability vectors. These methods motivate a definition of an elementary distance function which is easier and faster to calculate, works on non
Coherence-path duality relations for N paths
NASA Astrophysics Data System (ADS)
Hillery, Mark; Bagan, Emilio; Bergou, Janos; Cottrell, Seth
2016-05-01
For an interferometer with two paths, there is a relation between the information about which path the particle took and the visibility of the interference pattern at the output. The more path information we have, the smaller the visibility, and vice versa. We generalize this relation to a multi-path interferometer, and we substitute two recently defined measures of quantum coherence for the visibility, which results in two duality relations. The path information is provided by attaching a detector to each path. In the first relation, which uses an l1 measure of coherence, the path information is obtained by applying the minimum-error state discrimination procedure to the detector states. In the second, which employs an entropic measure of coherence, the path information is the mutual information between the detector states and the result of measuring them. Both approaches are quantitative versions of complementarity for N-path interferometers. Support provided by the John Templeton Foundation.
ERIC Educational Resources Information Center
Rodia, Becky
2004-01-01
This article profiles Diane Stanley, an author and illustrator of children's books. Although she was studying to be a medical illustrator in graduate school, Stanley's path changed when she got married and had children. As she was raising her children, she became increasingly enamored of the colorful children's books she would check out of the…
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…
Path planning for everday robotics with SANDROS
Watterberg, P.; Xavier, P.; Hwang, Y.
1997-02-01
We discuss the integration of the SANDROS path planner into a general robot simulation and control package with the inclusion of a fast geometry engine for distance calculations. This creates a single system that allows the path to be computed, simulated, and then executed on the physical robot. The architecture and usage procedures are presented. Also, we present examples of its usage in typical environments found in our organization. The resulting system is as easy to use as the general simulation system (which is in common use here) and is fast enough (example problems are solved in seconds) to be used interactively on an everyday basis.
Stochastic Evolutionary Algorithms for Planning Robot Paths
NASA Technical Reports Server (NTRS)
Fink, Wolfgang; Aghazarian, Hrand; Huntsberger, Terrance; Terrile, Richard
2006-01-01
A computer program implements stochastic evolutionary algorithms for planning and optimizing collision-free paths for robots and their jointed limbs. Stochastic evolutionary algorithms can be made to produce acceptably close approximations to exact, optimal solutions for path-planning problems while often demanding much less computation than do exhaustive-search and deterministic inverse-kinematics algorithms that have been used previously for this purpose. Hence, the present software is better suited for application aboard robots having limited computing capabilities (see figure). The stochastic aspect lies in the use of simulated annealing to (1) prevent trapping of an optimization algorithm in local minima of an energy-like error measure by which the fitness of a trial solution is evaluated while (2) ensuring that the entire multidimensional configuration and parameter space of the path-planning problem is sampled efficiently with respect to both robot joint angles and computation time. Simulated annealing is an established technique for avoiding local minima in multidimensional optimization problems, but has not, until now, been applied to planning collision-free robot paths by use of low-power computers.
A load-balance path selection algorithm in automatically swiched optical network (ASON)
NASA Astrophysics Data System (ADS)
Gao, Fei; Lu, Yueming; Ji, Yuefeng
2007-11-01
In this paper, a novel load-balance algorithm is proposed to provide an approach to optimized path selection in automatically swiched optical network (ASON). By using this algorithm, improved survivability and low congestion can be achieved. The static nature of current routing algorithms, such as OSPF or IS-IS, has made the situation worse since the traffic is concentrated on the "least-cost" paths which causes the congestion for some links while leaving other links lightly loaded. So, the key is to select suitable paths to balance the network load to optimize network resource utilization and traffic performance. We present a method to provide the capability to control traffic engineering so that the carriers can define their own strategies for optimizations and apply them to path selection for dynamic load balancing. With considering load distribution and topology information, capacity utilization factor is introduced into Dijkstra (shortest path selection) for path selection to achieve balancing traffic over network. Routing simulations have been done over mesh networks to compare the two different algorithms. With the simulation results, a conclusion can be made on the performance of different algorithms.
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.
Nonadiabatic transition path sampling.
Sherman, M C; Corcelli, S A
2016-07-21
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. PMID:27448877
Studness, C.M.
1995-05-01
The financial community`s focus on utility competition has been riveted on the proceedings now in progress at state regulatory commissions. The fear that something immediately damaging will come out of these proceedings seems to have diminished in recent months, and the stock market has reacted favorably. However, regulatory developments are only one of four paths leading to competition; the others are the marketplace, the legislatures, and the courts. Each could play a critical role in the emergence of competition.
NASA Technical Reports Server (NTRS)
2004-01-01
Scientists created this overlay map by laying navigation and panoramic camera images taken from the surface of Mars on top of one of Spirit's descent images taken as the spacecraft descended to the martian surface. The map was created to help track the path that Spirit has traveled through sol 44 and to put into perspective the distance left to travel before reaching the edge of the large crater nicknamed 'Bonneville.'
The area boxed in yellow contains the ground images that have been matched to and layered on top of the descent image. The yellow line shows the path that Spirit has traveled and the red dashed line shows the intended path for future sols. The blue circles highlight hollowed areas on the surface, such as Sleepy Hollow, near the lander, and Laguna Hollow, the sol 45 drive destination. Scientists use these hollowed areas - which can be seen in both the ground images and the descent image - to correctly match up the overlay.
Field geologists on Earth create maps like this to assist them in tracking their observations.
Path analysis in genetic epidemiology: a critique.
Karlin, S; Cameron, E C; Chakraborty, R
1983-01-01
Path analysis, a form of general linear structural equation models, is used in studies of human genetics data to discern genetic, environmental, and cultural factors contributing to familial resemblance. It postulates a set of linear and additive parametric relationships between phenotypes and genetic and cultural variables and then essentially uses the assumption of multivariate normality to estimate and perform tests of hypothesis on parameters. Such an approach has been advocated for the analysis of genetic epidemiological data by D. C. Rao, N. Morton, C. R. Cloninger, L. J. Eaves, and W. E. Nance, among others. This paper reviews and evaluates the formulations, assumptions, methodological procedures, interpretations, and applications of path analysis. To give perspective, we begin with a discussion of path analysis as it occurs in the form of general linear causal models in several disciplines of the social sciences. Several specific path analysis models applied to lipoprotein concentrations, IQ, and twin data are then reviewed to keep the presentation self-contained. The bulk of the critical discussion that follows is directed toward the following four facets of path analysis: (1) coherence of model specification and applicability to data; (2) plausibility of modeling assumptions; (3) interpretability and utility of the model; and (4) validity of statistical and computational procedures. In the concluding section, a brief discussion of the problem of appropriate model selection is presented, followed by a number of suggestions of essentially model-free alternative methods of use in the treatment of complex structured data such as occurs in genetic epidemiology. PMID:6349335
Path planning and the topology of configuration space
Maciejewski, A.A.; Fox, J.J.
1993-08-01
This work considers the path planning problem for planar revolute manipulators operating in a workspace of polygonal obstacles. This problem is solved by determining the topological characteristics of obstacles in configuration space, thereby determining where feasible paths can be found. A collision-free path is then calculated by using the mathematical description of the boundaries of only those configuration space obstacles with which collisions are possible. The key to this technique is a simple test for determining whether two disjoint obstacles are connected in configuration space. This test allows the path planner to restrict its calculations to regions in which collision-free paths are guaranteed a priori, thus avoiding unnecessary computations and resulting in an efficient implementations. Typical timing results for environments consisting of four polyhedral obstacles comprised of a total of 27 vertices are on the order of 22 ms on a SPARC-IPC workstation.
Tikhonov regularization-based operational transfer path analysis
NASA Astrophysics Data System (ADS)
Cheng, Wei; Lu, Yingying; Zhang, Zhousuo
2016-06-01
To overcome ill-posed problems in operational transfer path analysis (OTPA), and improve the stability of solutions, this paper proposes a novel OTPA based on Tikhonov regularization, which considers both fitting degrees and stability of solutions. Firstly, fundamental theory of Tikhonov regularization-based OTPA is presented, and comparative studies are provided to validate the effectiveness on ill-posed problems. Secondly, transfer path analysis and source contribution evaluations for numerical cases studies on spherical radiating acoustical sources are comparatively studied. Finally, transfer path analysis and source contribution evaluations for experimental case studies on a test bed with thin shell structures are provided. This study provides more accurate transfer path analysis for mechanical systems, which can benefit for vibration reduction by structural path optimization. Furthermore, with accurate evaluation of source contributions, vibration monitoring and control by active controlling vibration sources can be effectively carried out.
Collision avoidance of two moving objects using the anticipated path
NASA Astrophysics Data System (ADS)
Rhee, Seung Hak; Ahmad, Muhammad Bilal; Park, Seung-Jin; Beak, Kyoung-Ju; Park, Jong An
2004-03-01
Collision avoidance is one of the most important problems in autonomous vehicles, ship navigation, and robot manipulators, etc. Image processing technique could be applied for solving the collision avoidance of moving objects. The collision could be avoided if the direction of the moving object could be accurately anticipated. The problem is how to anticipate the expected path of the moving object, so that the other moving objects in the expected path should be detected and avoided for collision avoidance. Collisions could be avoided by searching the obstacles and moving objects in the expected path, but the moving objects, which would come inside the expected path, should also be detected for fully collision avoidance. In this paper, the expected path of the moving object is determined from the previous history of the moving object using the statistical measurements.
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
Path Integrals and Supersolids
NASA Astrophysics Data System (ADS)
Ceperley, D. M.
2008-11-01
Recent experiments by Kim and Chan on solid 4He have been interpreted as discovery of a supersolid phase of matter. Arguments based on wavefunctions have shown that such a phase exists, but do not necessarily apply to solid 4He. Imaginary time path integrals, implemented using Monte Carlo methods, provide a definitive answer; a clean system of solid 4He should be a normal quantum solid, not one with superfluid properties. The Kim-Chan phenomena must be due to defects introduced when the solid is formed.
NASA Technical Reports Server (NTRS)
Mehhtz, Peter
2005-01-01
JPF is an explicit state software model checker for Java bytecode. Today, JPF is a swiss army knife for all sort of runtime based verification purposes. This basically means JPF is a Java virtual machine that executes your program not just once (like a normal VM), but theoretically in all possible ways, checking for property violations like deadlocks or unhandled exceptions along all potential execution paths. If it finds an error, JPF reports the whole execution that leads to it. Unlike a normal debugger, JPF keeps track of every step how it got to the defect.
Bleakley, Hoyt; Lin, Jeffrey
2012-05-01
We examine portage sites in the U.S. South, Mid-Atlantic, and Midwest, including those on the fall line, a geomorphological feature in the southeastern U.S. marking the final rapids on rivers before the ocean. Historically, waterborne transport of goods required portage around the falls at these points, while some falls provided water power during early industrialization. These factors attracted commerce and manufacturing. Although these original advantages have long since been made obsolete, we document the continuing importance of these portage sites over time. We interpret these results as path dependence and contrast explanations based on sunk costs interacting with decreasing versus increasing returns to scale. PMID:23935217
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
ERIC Educational Resources Information Center
Conway, Robert, Ed.; Izard, John, Ed.
Twelve papers produced at an annual convention were selected for inclusion in this work on behavior management and behavior change in Australian children and youth with emotional and/or behavior problems. The papers are: (1) Developing Personal Strengths, Choosing More Effective Behaviours: Control Theory, Reality Therapy and Quality Management…
Internet's critical path horizon
NASA Astrophysics Data System (ADS)
Valverde, S.; Solé, R. V.
2004-03-01
Internet is known to display a highly heterogeneous structure and complex fluctuations in its traffic dynamics. Congestion seems to be an inevitable result of user's behavior coupled to the network dynamics and it effects should be minimized by choosing appropriate routing strategies. But what are the requirements of routing depth in order to optimize the traffic flow? In this paper we analyse the behavior of Internet traffic with a topologically realistic spatial structure as described in a previous study [S.-H. Yook et al., Proc. Natl Acad. Sci. USA 99, 13382 (2002)]. The model involves self-regulation of packet generation and different levels of routing depth. It is shown that it reproduces the relevant key, statistical features of Internet's traffic. Moreover, we also report the existence of a critical path horizon defining a transition from low-efficient traffic to highly efficient flow. This transition is actually a direct consequence of the web's small world architecture exploited by the routing algorithm. Once routing tables reach the network diameter, the traffic experiences a sudden transition from a low-efficient to a highly-efficient behavior. It is conjectured that routing policies might have spontaneously reached such a compromise in a distributed manner. Internet would thus be operating close to such critical path horizon.
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.
IP-oriented control of unidirectional-path-switched-ring-based transport networks
NASA Astrophysics Data System (ADS)
Sharma, Vishal; Das, Abhimanyu; Chen, Charles
2003-03-01
An important requirement in the IP-based control of time-division multiplexing (TDM) optical transport networks is to utilize the in-built protection capabilities of synchronous optical network (SONET) unidirectional path-switched rings (UPSRs) and to automate the UPSR-protected path setup in mixed mesh-ring networks. This requires modifications to existing IP signaling and routing protocols and new processing rules at the network nodes. Here we leverage IP routing and signaling and multiprotocol label switching (MPLS) fast-reroute techniques for accurately advertising UPSR ring topologies to remote nodes and dynamically establishing UPSR-protected paths across a transport network. Our proposal also makes a NUT1-like (nonpreemptible unprotected traffic) feature possible in UPSRs, which allows for efficient utilization of UPSR protection bandwidth. We achieve this by encoding UPSR-specific information in the open shortest-path-first (OSPF) link state advertisements and in signaling messages of the Resource Reservation Protocol (RSVP) with TE extensions. In addition, we modify the signaling and routing state machines at the nodes to interpret and process this information to perform UPSR topology discovery and path computation. The uniqueness of our proposals is that the algorithms and the rules specified here allow for existing IP-based protocols [such as those within the generalized MPLS (GMPLS) framework, which currently applies to mesh networks] to be efficiently adapted for this context while still achieving our objective of exploiting UPSR-protection capabilities.
Star-Paths, Stones and Horizon Astronomy
NASA Astrophysics Data System (ADS)
Brady, Bernadette
2015-05-01
Archaeoastronomers tend to approach ancient monuments focusing on the landscape and the horizon calendar events of sun and moon and, due to problems with precession, generally ignore the movement of the stars. However, locating the position of solar calendar points on the horizon can have other uses apart from calendar and/or cosmological purposes. This paper firstly suggests that the stars do not need to be ignored. By considering the evidence of the Phaenomena, a sky poem by Aratus of Soli, a third century BC Greek poet, and his use of second millennium BC star lore fragments, this paper argues that the stars were a part of the knowledge of horizon astronomy. Aratus' poem implied that the horizon astronomy of the late Neolithic and Bronze Age periods included knowledge of star-paths or 'linear constellations' that were defined by particular horizon calendar events and other azimuths. Knowledge of such star-paths would have enabled navigation and orientation, and by using permanent markers, constructed or natural, to define these paths, they were immune to precession as the stones could redefine a star-path for a future generation. Finally the paper presents other possible intentions behind the diverse orientation of passage tombs and some megalithic sites.
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.
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.
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.
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.
Path Following in the Exact Penalty Method of Convex Programming
Zhou, Hua; Lange, Kenneth
2015-01-01
Classical penalty methods solve a sequence of unconstrained problems that put greater and greater stress on meeting the constraints. In the limit as the penalty constant tends to ∞, one recovers the constrained solution. In the exact penalty method, squared penalties are replaced by absolute value penalties, and the solution is recovered for a finite value of the penalty constant. In practice, the kinks in the penalty and the unknown magnitude of the penalty constant prevent wide application of the exact penalty method in nonlinear programming. In this article, we examine a strategy of path following consistent with the exact penalty method. Instead of performing optimization at a single penalty constant, we trace the solution as a continuous function of the penalty constant. Thus, path following starts at the unconstrained solution and follows the solution path as the penalty constant increases. In the process, the solution path hits, slides along, and exits from the various constraints. For quadratic programming, the solution path is piecewise linear and takes large jumps from constraint to constraint. For a general convex program, the solution path is piecewise smooth, and path following operates by numerically solving an ordinary differential equation segment by segment. Our diverse applications to a) projection onto a convex set, b) nonnegative least squares, c) quadratically constrained quadratic programming, d) geometric programming, and e) semidefinite programming illustrate the mechanics and potential of path following. The final detour to image denoising demonstrates the relevance of path following to regularized estimation in inverse problems. In regularized estimation, one follows the solution path as the penalty constant decreases from a large value. PMID:26366044
Path Planning For A Class Of Cutting Operations
NASA Astrophysics Data System (ADS)
Tavora, Jose
1989-03-01
Optimizing processing time in some contour-cutting operations requires solving the so-called no-load path problem. This problem is formulated and an approximate resolution method (based on heuristic search techniques) is described. Results for real-life instances (clothing layouts in the apparel industry) are presented and evaluated.
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
Detailed Broadband Study of the Shortest Orbital Period Black-hole Binary Maxi J1659-152
NASA Astrophysics Data System (ADS)
Van Der Horst, Alexander Jonathan; Kouveliotou, C.; Paragi, Z.; Linford, J. D.; Taylor, G. B.; Kuulkers, E.; Curran, P. A.; Gorosabel, J.; Guziy, S.; de Ugarte Postigo, A.; Belloni, T.; Miller-Jones, J. C. A.
2011-09-01
MAXI J1659-152 is a hard X-ray source discovered by Swift and MAXI. Optical spectroscopy showed that this source is an X-ray binary, and X-ray timing observations classified it as a black-hole candidate. Based on recurring dips in the X-ray light curves, the source was established as the shortest period black-hole binary candidate known to date, with a period of 2.4 hours. Here we present our results from the broadband follow-up campaign we initiated after the source discovery. We obtained densely sampled light curves over two orders of magnitude in radio frequencies, in the UV/optical bands, and at X- and gamma-ray energies. This enabled us to construct broadband spectral energy distributions with very good spectral coverage at many epochs, covering the various X-ray states of MAXI J1659-152 during its outburst. Very Long Baseline Interferomety observations provide constraints on the size of the radio emitting jet, which, combined with the modeling results of the broadband spectra, present a comprehensive picture of the outburst from this new X-ray binary.
Qian, S.-B.; Zhang, J.; Wang, J.-J.; Zhu, L.-Y.; Liu, L.; Zhao, E. G.; Li, L.-J.; He, J.-J.
2013-08-15
We discovered that the O-C curve of V753 Mon shows an upward parabolic change while undergoing a cyclic variation with a period of 13.5 yr. The upward parabolic change reveals a long-term period increase at a rate of P-dot = +7.8 x 10{sup -8} days yr{sup -1}. Photometric solutions determined using the Wilson-Devinney method confirm that V753 Mon is a semi-detached binary system where the slightly less massive, hotter component star is transferring mass to the more massive one. This is in agreement with the long-term increase of the orbital period. The increase of the orbital period, the mass ratio very close to unity, and the semi-detached configuration with a less massive lobe-filling component all suggest that V753 Mon is on a key evolutionary stage just after the evolutionary stage with the shortest period during mass transfer. The results in this paper will shed light on the formation of massive contact binaries and the evolution of binary stars. The cyclic oscillation in the O-C diagram indicates that V753 Mon may be a triple system containing an extremely cool stellar companion that may play an important role for the formation and evolution in the binary system.
Evolution-based path planning and management for autonomous vehicles
NASA Astrophysics Data System (ADS)
Capozzi, Brian Joseph
2001-07-01
This dissertation describes an approach to adaptive path planning based on the problem solving capabilities witnessed in nature---namely the influence of natural selection in uncovering solutions to the characteristics of the environment. The competition for survival forces organisms to either respond to changes or risk being evolved out of the population. We demonstrate the applicability of this process to the problem of finding paths for an autonomous vehicle through a number of different static and dynamic environments. In doing so, we develop a number of different ways in which these paths can be modeled for the purposes of evolution. Through analysis and experimentation, we develop and reinforce a set of principles and conditions which must hold for the search process to be successful. Having demonstrated the viability of evolution as a guide for path planning, we discuss implications for on-line, real-time planning for autonomous vehicles.
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.
Path integral learning of multidimensional movement trajectories
NASA Astrophysics Data System (ADS)
André, João; Santos, Cristina; Costa, Lino
2013-10-01
This paper explores the use of Path Integral Methods, particularly several variants of the recent Path Integral Policy Improvement (PI2) algorithm in multidimensional movement parametrized policy learning. We rely on Dynamic Movement Primitives (DMPs) to codify discrete and rhythmic trajectories, and apply the PI2-CMA and PIBB methods in the learning of optimal policy parameters, according to different cost functions that inherently encode movement objectives. Additionally we merge both of these variants and propose the PIBB-CMA algorithm, comparing all of them with the vanilla version of PI2. From the obtained results we conclude that PIBB-CMA surpasses all other methods in terms of convergence speed and iterative final cost, which leads to an increased interest in its application to more complex robotic problems.
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.
Path Integral Simulations of Graphene
NASA Astrophysics Data System (ADS)
Yousif, Hosam
2007-10-01
Some properties of graphene are explored using a path integral approach. The path integral method allows us to simulate relatively large systems using monte carlo techniques and extract thermodynamic quantities. We simulate the effects of screening a large external charge potential, as well as conductivity and charge distributions in graphene sheets.
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.
One-dimensional Gromov minimal filling problem
Ivanov, Alexandr O; Tuzhilin, Alexey A
2012-05-31
The paper is devoted to a new branch in the theory of one-dimensional variational problems with branching extremals, the investigation of one-dimensional minimal fillings introduced by the authors. On the one hand, this problem is a one-dimensional version of a generalization of Gromov's minimal fillings problem to the case of stratified manifolds. On the other hand, this problem is interesting in itself and also can be considered as a generalization of another classical problem, the Steiner problem on the construction of a shortest network connecting a given set of terminals. Besides the statement of the problem, we discuss several properties of the minimal fillings and state several conjectures. Bibliography: 38 titles.
Modeling of tool path for the CNC sheet cutting machines
NASA Astrophysics Data System (ADS)
Petunin, Aleksandr A.
2015-11-01
In the paper the problem of tool path optimization for CNC (Computer Numerical Control) cutting machines is considered. The classification of the cutting techniques is offered. We also propose a new classification of toll path problems. The tasks of cost minimization and time minimization for standard cutting technique (Continuous Cutting Problem, CCP) and for one of non-standard cutting techniques (Segment Continuous Cutting Problem, SCCP) are formalized. We show that the optimization tasks can be interpreted as discrete optimization problem (generalized travel salesman problem with additional constraints, GTSP). Formalization of some constraints for these tasks is described. For the solution GTSP we offer to use mathematical model of Prof. Chentsov based on concept of a megalopolis and dynamic programming.
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.
A Flight Examination of Operating Problems of V/STOL Aircraft in STOL-Type Landing and Approach
NASA Technical Reports Server (NTRS)
Innis, Robert C.; Quigley, Hervey C.
1961-01-01
A flight investigation has been conducted using a large twin-engine cargo aircraft to isolate the problems associated with operating propeller-driven aircraft in the STOL speed range where appreciable engine power is used to augment aerodynamic lift. The problems considered would also be representative of those of a large overloaded VTOL aircraft operating in an STOL manner with comparable thrust-to-weight ratios. The study showed that operation at low approach speeds was compromised by the necessity of maintaining high thrust to generate high lift and yet achieving the low lift-drag ratios needed for steep descents. The useable range of airspeed and flight path angle was limited by the pilot's demand for a positive climb margin at the approach speed, a suitable stall margin, and a control and/or performance margin for one engine inoperative. The optimum approach angle over an obstacle was found to be a compromise between obtaining the shortest air distance and the lowest touchdown velocity. In order to realize the greatest low-speed potential from STOL designs, the stability and control characteristics must be satisfactory.
THE SHORTEST PERIOD sdB PLUS WHITE DWARF BINARY CD-30 11223 (GALEX J1411-3053)
Vennes, S.; Kawka, A.; Nemeth, P.; O'Toole, S. J.; Burton, D.
2012-11-01
We report on the discovery of the shortest period binary comprising a hot subdwarf star (CD-30 11223, GALEX J1411-3053) and a massive unseen companion. Photometric data from the All Sky Automated Survey show ellipsoidal variations of the hot subdwarf primary and spectroscopic series revealed an orbital period of 70.5 minutes. The large velocity amplitude suggests the presence of a massive white dwarf in the system (M{sub 2}/M{sub Sun} {approx}> 0.77) assuming a canonical mass for the hot subdwarf (0.48 M{sub Sun }), although a white dwarf mass as low as 0.75 M{sub Sun} is allowable by postulating a subdwarf mass as low as 0.44 M{sub Sun }. The amplitude of ellipsoidal variations and a high rotation velocity imposed a high-inclination to the system (i {approx}> 68 Degree-Sign ) and, possibly, observable secondary transits (i {approx}> 74 Degree-Sign ). At the lowest permissible inclination and assuming a subdwarf mass of {approx}0.48 M{sub Sun }, the total mass of the system reaches the Chandrasekhar mass limit at 1.35 M{sub Sun} and would exceed it for a subdwarf mass above 0.48 M{sub Sun }. The system should be considered, like its sibling KPD 1930+2752, a candidate progenitor for a Type Ia supernova. The system should become semi-detached and initiate mass transfer within Almost-Equal-To 30 Myr.
A Deterministic Approximation Algorithm for Maximum 2-Path Packing
NASA Astrophysics Data System (ADS)
Tanahashi, Ruka; Chen, Zhi-Zhong
This paper deals with the maximum-weight 2-path packing problem (M2PP), which is the problem of computing a set of vertex-disjoint paths of length 2 in a given edge-weighted complete graph so that the total weight of edges in the paths is maximized. Previously, Hassin and Rubinstein gave a randomized cubic-time approximation algorithm for M2PP which achieves an expected ratio of 35/67 - ε ≈ 0.5223 - ε for any constant ε > 0. We refine their algorithm and derandomize it to obtain a deterministic cubic-time approximation algorithm for the problem which achieves a better ratio (namely, 0.5265 - ε for any constant ε > 0).