Structural factoring approach for analyzing stochastic networks

NASA Technical Reports Server (NTRS)

Hayhurst, Kelly J.; Shier, Douglas R.

1991-01-01

The problem of finding the distribution of the shortest path length through a stochastic network is investigated. A general algorithm for determining the exact distribution of the shortest path length is developed based on the concept of conditional factoring, in which a directed, stochastic network is decomposed into an equivalent set of smaller, generally less complex subnetworks. Several network constructs are identified and exploited to reduce significantly the computational effort required to solve a network problem relative to complete enumeration. This algorithm can be applied to two important classes of stochastic path problems: determining the critical path distribution for acyclic networks and the exact two-terminal reliability for probabilistic networks. Computational experience with the algorithm was encouraging and allowed the exact solution of networks that have been previously analyzed only by approximation techniques.

Graphs and matroids weighted in a bounded incline algebra.

PubMed

Lu, Ling-Xia; Zhang, Bei

2014-01-01

Firstly, for a graph weighted in a bounded incline algebra (or called a dioid), a longest path problem (LPP, for short) is presented, which can be considered the uniform approach to the famous shortest path problem, the widest path problem, and the most reliable path problem. The solutions for LPP and related algorithms are given. Secondly, for a matroid weighted in a linear matroid, the maximum independent set problem is studied.

Nearby Search Indekos Based Android Using A Star (A*) Algorithm

NASA Astrophysics Data System (ADS)

Siregar, B.; Nababan, EB; Rumahorbo, JA; Andayani, U.; Fahmi, F.

2018-03-01

Indekos or rented room is a temporary residence for months or years. Society of academicians who come from out of town need a temporary residence, such as Indekos or rented room during their education, teaching, or duties. They are often found difficulty in finding a Indekos because lack of information about the Indekos. Besides, new society of academicians don’t recognize the areas around the campus and desire the shortest path from Indekos to get to the campus. The problem can be solved by implementing A Star (A*) algorithm. This algorithm is one of the shortest path algorithm to a finding shortest path from campus to the Indekos application, where the faculties in the campus as the starting point of the finding. Determination of the starting point used in this study aims to allow students to determine the starting point in finding the Indekos. The mobile based application facilitates the finding anytime and anywhere. Based on the experimental results, A* algorithm can find the shortest path with 86,67% accuracy.

DiversePathsJ: diverse shortest paths for bioimage analysis.

PubMed

Uhlmann, Virginie; Haubold, Carsten; Hamprecht, Fred A; Unser, Michael

2018-02-01

We introduce a formulation for the general task of finding diverse shortest paths between two end-points. Our approach is not linked to a specific biological problem and can be applied to a large variety of images thanks to its generic implementation as a user-friendly ImageJ/Fiji plugin. It relies on the introduction of additional layers in a Viterbi path graph, which requires slight modifications to the standard Viterbi algorithm rules. This layered graph construction allows for the specification of various constraints imposing diversity between solutions. The software allows obtaining a collection of diverse shortest paths under some user-defined constraints through a convenient and user-friendly interface. It can be used alone or be integrated into larger image analysis pipelines. http://bigwww.epfl.ch/algorithms/diversepathsj. michael.unser@epfl.ch or fred.hamprecht@iwr.uni-heidelberg.de. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

Path planning of decentralized multi-quadrotor based on fuzzy-cell decomposition algorithm

NASA Astrophysics Data System (ADS)

Iswanto, Wahyunggoro, Oyas; Cahyadi, Adha Imam

2017-04-01

The paper aims to present a design algorithm for multi quadrotor lanes in order to move towards the goal quickly and avoid obstacles in an area with obstacles. There are several problems in path planning including how to get to the goal position quickly and avoid static and dynamic obstacles. To overcome the problem, therefore, the paper presents fuzzy logic algorithm and fuzzy cell decomposition algorithm. Fuzzy logic algorithm is one of the artificial intelligence algorithms which can be applied to robot path planning that is able to detect static and dynamic obstacles. Cell decomposition algorithm is an algorithm of graph theory used to make a robot path map. By using the two algorithms the robot is able to get to the goal position and avoid obstacles but it takes a considerable time because they are able to find the shortest path. Therefore, this paper describes a modification of the algorithms by adding a potential field algorithm used to provide weight values on the map applied for each quadrotor by using decentralized controlled, so that the quadrotor is able to move to the goal position quickly by finding the shortest path. The simulations conducted have shown that multi-quadrotor can avoid various obstacles and find the shortest path by using the proposed algorithms.

Vervet monkeys use paths consistent with context-specific spatial movement heuristics.

PubMed

Teichroeb, Julie A

2015-10-01

Animal foraging routes are analogous to the computationally demanding "traveling salesman problem" (TSP), where individuals must find the shortest path among several locations before returning to the start. Humans approximate solutions to TSPs using simple heuristics or "rules of thumb," but our knowledge of how other animals solve multidestination routing problems is incomplete. Most nonhuman primate species have shown limited ability to route plan. However, captive vervets were shown to solve a TSP for six sites. These results were consistent with either planning three steps ahead or a risk-avoidance strategy. I investigated how wild vervet monkeys (Chlorocebus pygerythrus) solved a path problem with six, equally rewarding food sites; where site arrangement allowed assessment of whether vervets found the shortest route and/or used paths consistent with one of three simple heuristics to navigate. Single vervets took the shortest possible path in fewer than half of the trials, usually in ways consistent with the most efficient heuristic (the convex hull). When in competition, vervets' paths were consistent with different, more efficient heuristics dependent on their dominance rank (a cluster strategy for dominants and the nearest neighbor rule for subordinates). These results suggest that, like humans, vervets may solve multidestination routing problems by applying simple, adaptive, context-specific "rules of thumb." The heuristics that were consistent with vervet paths in this study are the same as some of those asserted to be used by humans. These spatial movement strategies may have common evolutionary roots and be part of a universal mental navigational toolkit. Alternatively, they may have emerged through convergent evolution as the optimal way to solve multidestination routing problems.

Shortest multiple disconnected path for the analysis of entanglements in two- and three-dimensional polymeric systems

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 program has been tested: UNIX, Linux Program language used: USANSI Fortran 77 and Fortran 90 Memory required to execute with typical data: 1 MByte No. of lines in distributed program, including test data, etc.: 10 660 No. of bytes in distributed program, including test data, etc.: 119 551 Distribution formet:tar.gz Nature of physical problem: The problem is to obtain primitive paths substantiating a shortest multiple disconnected path (SP) for a given polymer configuration (chains of particles, with or without additional single particles as obstacles for the 2D case). Primitive paths are here defined as in [M. Rubinstein, E. Helfand, J. Chem. Phys. 82 (1985) 2477; R. Everaers, S.K. Sukumaran, G.S. Grest, C. Svaneborg, A. Sivasubramanian, K. Kremer, Science 303 (2004) 823] as the shortest line (path) respecting 'topological' constraints (from neighboring polymers or point obstacles) between ends of polymers. There is a unique solution for the 2D case. For the 3D case it is unique if we construct a primitive path of a single chain embedded within fixed line obstacles [J.S.B. Mitchell, Geometric shortest paths and network optimization, in: J.-R. Sack, J. Urrutia (Eds.), Handbook of Computational Geometry, Elsevier, Amsterdam, 2000, pp. 633-701]. For a large 3D configuration made of several chains, short is meant to be the Euclidean shortest multiple disconnected path (SP) where primitive paths are constructed for all chains simultaneously. While the latter problem, in general, does not possess a unique solution, the algorithm must return a locally optimal solution, robust against minor displacements of the disconnected path and chain re-labeling. The problem is solved if the number of kinks (or entanglements Z), explicitly deduced from the SP, is quite insensitive to the exact conformation of the SP which allows to estimate Z with a small error. Efficient method of solution: Primitive paths are constructed from the given polymer configuration (a non-shortest multiple disconnected path, including obstacles, if present) by first replacing each polymer contour by a line with a number of 'kinks' (beads, nodes) and 'segments' (edges). To obtain primitive paths, defined to be uncrossable by any other objects (neighboring primitive paths, line or point obstacles), the algorithm minimizes the length of all primitive paths consecutively, until a final minimum Euclidean length of the SP is reached. Fast geometric operations rather than dynamical methods are used to minimize the contour lengths of the primitive paths. Neighbor lists are used to keep track of potentially intersecting segments of other chains. Periodic boundary conditions are employed. A finite small line thickness is used in order to make sure that entanglements are not 'lost' due to finite precision of representation of numbers. Restrictions on the complexity of the problem: For a single chain embedded within fixed line or point obstacles, the algorithm returns the exact SP. For more complex problems, the algorithm returns a locally optimal SP. Except for exotic, probably rare, configurations it turns out that different locally optimal SPs possess quite an identical number of nodes. In general, the problem constructing the SP is known to be NP-hard [J.S.B. Mitchell, Geometric shortest paths and network optimization, in: J.-R. Sack, J. Urrutia (Eds.), Handbook of Computational Geometry, Elsevier, Amsterdam, 2000, pp. 633-701], and we offer a solution which should suffice to analyze physical problems, and gives an estimate about the precision and uniqueness of the result (from a standard deviation by varying the parameter: cyclicswitch). The program is NOT restricted to handle systems for which segment lengths of the SP exceed half the box size. Typical running time: Typical running times are approximately two orders of magnitude shorter compared with the ones needed for a corresponding molecular dynamics approach, and scale mostly linearly with system size. We provide a benchmark table.

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.

Fast marching methods for the continuous traveling salesman problem.

PubMed

Andrews, June; Sethian, J A

2007-01-23

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 complexity of the heuristic algorithm is at worst case M.N log N, 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.

Metabolic PathFinding: inferring relevant pathways in biochemical networks.

PubMed

Croes, Didier; Couche, Fabian; Wodak, Shoshana J; van Helden, Jacques

2005-07-01

Our knowledge of metabolism can be represented as a network comprising several thousands of nodes (compounds and reactions). Several groups applied graph theory to analyse the topological properties of this network and to infer metabolic pathways by path finding. This is, however, not straightforward, with a major problem caused by traversing irrelevant shortcuts through highly connected nodes, which correspond to pool metabolites and co-factors (e.g. H2O, NADP and H+). In this study, we present a web server implementing two simple approaches, which circumvent this problem, thereby improving the relevance of the inferred pathways. In the simplest approach, the shortest path is computed, while filtering out the selection of highly connected compounds. In the second approach, the shortest path is computed on the weighted metabolic graph where each compound is assigned a weight equal to its connectivity in the network. This approach significantly increases the accuracy of the inferred pathways, enabling the correct inference of relatively long pathways (e.g. with as many as eight intermediate reactions). Available options include the calculation of the k-shortest paths between two specified seed nodes (either compounds or reactions). Multiple requests can be submitted in a queue. Results are returned by email, in textual as well as graphical formats (available in http://www.scmbb.ulb.ac.be/pathfinding/).

Physarum can compute shortest paths.

PubMed

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. Copyright © 2012 Elsevier Ltd. All rights reserved.

Genetic Algorithm for Solving Fuzzy Shortest Path Problem in a Network with mixed fuzzy arc lengths

NASA Astrophysics Data System (ADS)

Mahdavi, Iraj; Tajdin, Ali; Hassanzadeh, Reza; Mahdavi-Amiri, Nezam; Shafieian, Hosna

2011-06-01

We are concerned with the design of a model and an algorithm for computing a shortest path in a network having various types of fuzzy arc lengths. First, we develop a new technique for the addition of various fuzzy numbers in a path using α -cuts by proposing a linear least squares model to obtain membership functions for the considered additions. Then, using a recently proposed distance function for comparison of fuzzy numbers. we propose a new approach to solve the fuzzy APSPP using of genetic algorithm. Examples are worked out to illustrate the applicability of the proposed model.

Network Design for Reliability and Resilience to Attack

DTIC Science & Technology

2014-03-01

attacker can destroy n arcs in the network SPNI Shortest-Path Network-Interdiction problem TSP Traveling Salesman Problem UB upper bound UKR Ukraine...elimination from the traveling salesman problem (TSP). Literature calls a walk that does not contain a cycle a path [19]. The objective function in...arc lengths as random variables with known probability distributions. The m-median problem seeks to design a network with minimum average travel cost

Approaching the Brachistochrone Using Inclined Planes--Striving for Shortest or Equal Travelling Times

ERIC Educational Resources Information Center

Theilmann, Florian

2017-01-01

The classical "brachistochrone" problem asks for the path on which a mobile point M just driven by its own gravity will travel in the shortest possible time between two given points "A" and "B." The resulting curve, the cycloid, will also be the "tautochrone" curve, i.e. the travelling time of the mobile…

Fast marching methods for the continuous traveling salesman problem

PubMed Central

Andrews, June; Sethian, J. A.

2007-01-01

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 complexity of the heuristic algorithm is at worst case M·N log N, 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. PMID:17220271

Fast marching methods for the continuous traveling salesman problem

DOE Office of Scientific and Technical Information (OSTI.GOV)

Andrews, J.; Sethian, J.A.

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 amore » 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.« less

Formal language constrained path problems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Barrett, C.; Jacob, R.; Marathe, M.

1997-07-08

In many path finding problems arising in practice, certain patterns of edge/vertex labels in the labeled graph being traversed are allowed/preferred, while others are disallowed. Motivated by such applications as intermodal transportation planning, the authors investigate the complexity of finding feasible paths in a labeled network, where the mode choice for each traveler is specified by a formal language. The main contributions of this paper include the following: (1) the authors show that the problem of finding a shortest path between a source and destination for a traveler whose mode choice is specified as a context free language is solvablemore » efficiently in polynomial time, when the mode choice is specified as a regular language they provide algorithms with improved space and time bounds; (2) in contrast, they show that the problem of finding simple paths between a source and a given destination is NP-hard, even when restricted to very simple regular expressions and/or very simple graphs; (3) for the class of treewidth bounded graphs, they show that (i) the problem of finding a regular language constrained simple path between source and a destination is solvable in polynomial time and (ii) the extension to finding context free language constrained simple paths is NP-complete. Several extensions of these results are presented in the context of finding shortest paths with additional constraints. These results significantly extend the results in [MW95]. As a corollary of the results, they obtain a polynomial time algorithm for the BEST k-SIMILAR PATH problem studied in [SJB97]. The previous best algorithm was given by [SJB97] and takes exponential time in the worst case.« less

The "path" not taken: exploring structural differences in mapped- versus shortest-network-path school travel routes.

PubMed

Buliung, Ron N; Larsen, Kristian; Faulkner, Guy E J; Stone, Michelle R

2013-09-01

School route measurement often involves estimating the shortest network path. We challenged the relatively uncritical adoption of this method in school travel research and tested the route discordance hypothesis that several types of difference exist between shortest network paths and reported school routes. We constructed the mapped and shortest path through network routes for a sample of 759 children aged 9 to 13 years in grades 5 and 6 (boys = 45%, girls = 54%, unreported gender = 1%), in Toronto, Ontario, Canada. We used Wilcoxon signed-rank tests to compare reported with shortest-path route measures including distance, route directness, intersection crossings, and route overlap. Measurement difference was explored by mode and location. We found statistical evidence of route discordance for walkers and children who were driven and detected it more often for inner suburban cases. Evidence of route discordance varied by mode and school location. We found statistically significant differences for route structure and built environment variables measured along reported and geographic information systems-based shortest-path school routes. Uncertainty produced by the shortest-path approach challenges its conceptual and empirical validity in school travel research.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bromberger, Seth A.; Klymko, Christine F.; Henderson, Keith A.

Betweenness centrality is a graph statistic used to nd vertices that are participants in a large number of shortest paths in a graph. This centrality measure is commonly used in path and network interdiction problems and its complete form requires the calculation of all-pairs shortest paths for each vertex. This leads to a time complexity of O(jV jjEj), which is impractical for large graphs. Estimation of betweenness centrality has focused on performing shortest-path calculations on a subset of randomly- selected vertices. This reduces the complexity of the centrality estimation to O(jSjjEj); jSj < jV j, which can be scaled appropriatelymore » based on the computing resources available. An estimation strategy that uses random selection of vertices for seed selection is fast and simple to implement, but may not provide optimal estimation of betweenness centrality when the number of samples is constrained. Our experimentation has identi ed a number of alternate seed-selection strategies that provide lower error than random selection in common scale-free graphs. These strategies are discussed and experimental results are presented.« less

Solving fuzzy shortest path problem by genetic algorithm

NASA Astrophysics Data System (ADS)

Syarif, A.; Muludi, K.; Adrian, R.; Gen, M.

2018-03-01

Shortest Path Problem (SPP) is known as one of well-studied fields in the area Operations Research and Mathematical Optimization. It has been applied for many engineering and management designs. The objective is usually to determine path(s) in the network with minimum total cost or traveling time. In the past, the cost value for each arc was usually assigned or estimated as a deteministic value. For some specific real world applications, however, it is often difficult to determine the cost value properly. One way of handling such uncertainty in decision making is by introducing fuzzy approach. With this situation, it will become difficult to solve the problem optimally. This paper presents the investigations on the application of Genetic Algorithm (GA) to a new SPP model in which the cost values are represented as Triangular Fuzzy Number (TFN). We adopts the concept of ranking fuzzy numbers to determine how good the solutions. Here, by giving his/her degree value, the decision maker can determine the range of objective value. This would be very valuable for decision support system in the real world applications.Simulation experiments were carried out by modifying several test problems with 10-25 nodes. It is noted that the proposed approach is capable attaining a good solution with different degree of optimism for the tested problems.

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…

The “Path” Not Taken: Exploring Structural Differences in Mapped- Versus Shortest-Network-Path School Travel Routes

PubMed Central

Larsen, Kristian; Faulkner, Guy E. J.; Stone, Michelle R.

2013-01-01

Objectives. School route measurement often involves estimating the shortest network path. We challenged the relatively uncritical adoption of this method in school travel research and tested the route discordance hypothesis that several types of difference exist between shortest network paths and reported school routes. Methods. We constructed the mapped and shortest path through network routes for a sample of 759 children aged 9 to 13 years in grades 5 and 6 (boys = 45%, girls = 54%, unreported gender = 1%), in Toronto, Ontario, Canada. We used Wilcoxon signed-rank tests to compare reported with shortest-path route measures including distance, route directness, intersection crossings, and route overlap. Measurement difference was explored by mode and location. Results. We found statistical evidence of route discordance for walkers and children who were driven and detected it more often for inner suburban cases. Evidence of route discordance varied by mode and school location. Conclusions. We found statistically significant differences for route structure and built environment variables measured along reported and geographic information systems–based shortest-path school routes. Uncertainty produced by the shortest-path approach challenges its conceptual and empirical validity in school travel research. PMID:23865648

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.

Spatially-global integration of closed, fragmented contours by finding the shortest-path in a log-polar representation

PubMed Central

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

Optimal UAS Assignments and Trajectories for Persistent Surveillance and Data Collection from a Wireless Sensor Network

DTIC Science & Technology

2015-12-24

minimizing a weighted sum ofthe time and control effort needed to collect sensor data. This problem formulation is a modified traveling salesman ...29 2.5 The Shortest Path Problem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 2.5.1 Traveling Salesman Problem ...48 3.3.1 Initial Guess by Traveling Salesman Problem Solution

An Application of Self-Organizing Map for Multirobot Multigoal Path Planning with Minmax Objective.

PubMed

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.

An Application of Self-Organizing Map for Multirobot Multigoal Path Planning with Minmax Objective

PubMed Central

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

Dijkstra Methode for Optimalize Recommendation System of Garbage Transportation Time in Surakarta City

NASA Astrophysics Data System (ADS)

Hartatik; Purbayu, A.; Triyono, L.

2018-03-01

Major problem that often occurs in waste transportation in each region is the route of garbage transportation. Determination of this route should become a major concern because it affects fuel consumption and also the working time from the employee. Therefore, in this research we will develop an application to optimize with pigeonhole and dijsktra algorithm. Pigeonhole algorithm is used to determine which garbage trucks should be taken in a particular TPS. Time optimization is done by determining the shortest path that can be skipped for each garbage truck. Data generated from Pigeonhole then used to determine the shortest path by using Dijkstra algorithm.

E-Learning Technologies: Employing Matlab Web Server to Facilitate the Education of Mathematical Programming

ERIC Educational Resources Information Center

Karagiannis, P.; Markelis, I.; Paparrizos, K.; Samaras, N.; Sifaleras, A.

2006-01-01

This paper presents new web-based educational software (webNetPro) for "Linear Network Programming." It includes many algorithms for "Network Optimization" problems, such as shortest path problems, minimum spanning tree problems, maximum flow problems and other search algorithms. Therefore, webNetPro can assist the teaching process of courses such…

Comparison of Decisions Quality of Heuristic Methods with Limited Depth-First Search Techniques in the Graph Shortest Path Problem

NASA Astrophysics Data System (ADS)

Vatutin, Eduard

2017-12-01

The article deals with the problem of analysis of effectiveness of the heuristic methods with limited depth-first search techniques of decision obtaining in the test problem of getting the shortest path in graph. The article briefly describes the group of methods based on the limit of branches number of the combinatorial search tree and limit of analyzed subtree depth used to solve the problem. The methodology of comparing experimental data for the estimation of the quality of solutions based on the performing of computational experiments with samples of graphs with pseudo-random structure and selected vertices and arcs number using the BOINC platform is considered. It also shows description of obtained experimental results which allow to identify the areas of the preferable usage of selected subset of heuristic methods depending on the size of the problem and power of constraints. It is shown that the considered pair of methods is ineffective in the selected problem and significantly inferior to the quality of solutions that are provided by ant colony optimization method and its modification with combinatorial returns.

Two betweenness centrality measures based on Randomized Shortest Paths

PubMed Central

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

Efficient shortest-path-tree computation in network routing based on pulse-coupled neural networks.

PubMed

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.

Optimization for Service Routes of Pallet Service Center Based on the Pallet Pool Mode

PubMed Central

He, Shiwei; Song, Rui

2016-01-01

Service routes optimization (SRO) of pallet service center should meet customers' demand firstly and then, through the reasonable method of lines organization, realize the shortest path of vehicle driving. The routes optimization of pallet service center is similar to the distribution problems of vehicle routing problem (VRP) and Chinese postman problem (CPP), but it has its own characteristics. Based on the relevant research results, the conditions of determining the number of vehicles, the one way of the route, the constraints of loading, and time windows are fully considered, and a chance constrained programming model with stochastic constraints is constructed taking the shortest path of all vehicles for a delivering (recycling) operation as an objective. For the characteristics of the model, a hybrid intelligent algorithm including stochastic simulation, neural network, and immune clonal algorithm is designed to solve the model. Finally, the validity and rationality of the optimization model and algorithm are verified by the case. PMID:27528865

Relevancy in Problem Solving: A Computational Framework

ERIC Educational Resources Information Center

Kwisthout, Johan

2012-01-01

When computer scientists discuss the computational complexity of, for example, finding the shortest path from building A to building B in some town or city, their starting point typically is a formal description of the problem at hand, e.g., a graph with weights on every edge where buildings correspond to vertices, routes between buildings to…

Identification of influential nodes in complex networks: Method from spreading probability viewpoint

NASA Astrophysics Data System (ADS)

Bao, Zhong-Kui; Ma, Chuang; Xiang, Bing-Bing; Zhang, Hai-Feng

2017-02-01

The problem of identifying influential nodes in complex networks has attracted much attention owing to its wide applications, including how to maximize the information diffusion, boost product promotion in a viral marketing campaign, prevent a large scale epidemic and so on. From spreading viewpoint, the probability of one node propagating its information to one other node is closely related to the shortest distance between them, the number of shortest paths and the transmission rate. However, it is difficult to obtain the values of transmission rates for different cases, to overcome such a difficulty, we use the reciprocal of average degree to approximate the transmission rate. Then a semi-local centrality index is proposed to incorporate the shortest distance, the number of shortest paths and the reciprocal of average degree simultaneously. By implementing simulations in real networks as well as synthetic networks, we verify that our proposed centrality can outperform well-known centralities, such as degree centrality, betweenness centrality, closeness centrality, k-shell centrality, and nonbacktracking centrality. In particular, our findings indicate that the performance of our method is the most significant when the transmission rate nears to the epidemic threshold, which is the most meaningful region for the identification of influential nodes.

Constraint-Based Local Search for Constrained Optimum Paths Problems

NASA Astrophysics Data System (ADS)

Pham, Quang Dung; Deville, Yves; van Hentenryck, Pascal

Constrained Optimum Path (COP) problems arise in many real-life applications and are ubiquitous in communication networks. They have been traditionally approached by dedicated algorithms, which are often hard to extend with side constraints and to apply widely. This paper proposes a constraint-based local search (CBLS) framework for COP applications, bringing the compositionality, reuse, and extensibility at the core of CBLS and CP systems. The modeling contribution is the ability to express compositional models for various COP applications at a high level of abstraction, while cleanly separating the model and the search procedure. The main technical contribution is a connected neighborhood based on rooted spanning trees to find high-quality solutions to COP problems. The framework, implemented in COMET, is applied to Resource Constrained Shortest Path (RCSP) problems (with and without side constraints) and to the edge-disjoint paths problem (EDP). Computational results show the potential significance of the approach.

Comparison of Genetic Algorithm and Hill Climbing for Shortest Path Optimization Mapping

NASA Astrophysics Data System (ADS)

Fronita, Mona; Gernowo, Rahmat; Gunawan, Vincencius

2018-02-01

Traveling Salesman Problem (TSP) is an optimization to find the shortest path to reach several destinations in one trip without passing through the same city and back again to the early departure city, the process is applied to the delivery systems. This comparison is done using two methods, namely optimization genetic algorithm and hill climbing. Hill Climbing works by directly selecting a new path that is exchanged with the neighbour's to get the track distance smaller than the previous track, without testing. Genetic algorithms depend on the input parameters, they are the number of population, the probability of crossover, mutation probability and the number of generations. To simplify the process of determining the shortest path supported by the development of software that uses the google map API. Tests carried out as much as 20 times with the number of city 8, 16, 24 and 32 to see which method is optimal in terms of distance and time computation. Based on experiments conducted with a number of cities 3, 4, 5 and 6 producing the same value and optimal distance for the genetic algorithm and hill climbing, the value of this distance begins to differ with the number of city 7. The overall results shows that these tests, hill climbing are more optimal to number of small cities and the number of cities over 30 optimized using genetic algorithms.

The approach for shortest paths in fire succor based on component GIS technology

NASA Astrophysics Data System (ADS)

Han, Jie; Zhao, Yong; Dai, K. W.

2007-06-01

Fire safety is an important issue for the national economy and people's living. Efficiency and exactness of fire department succor directly relate to safety of peoples' lives and property. Many disadvantages of the traditional fire system have been emerged in practical applications. The preparation of pumpers is guided by wireless communication or wire communication, so its real-time and accurate performances are much poorer. The information about the reported fire, such as the position, disaster and map, et al., for alarm and command was processed by persons, which slows the reaction speed and delays the combat opportunity. In order to solve these disadvantages, it has an important role to construct a modern fire command center based on high technology. The construction of modern fire command center can realize the modernization and automation of fire command and management. It will play a great role in protecting safety of peoples' lives and property. The center can enhance battle ability and can reduce the direct and indirect loss of fire damage at most. With the development of science technology, Geographic Information System (GIS) has becoming a new information industry for hardware production, software development, data collection, space analysis and counseling. With the popularization of computers and the development of GIS, GIS has gained increasing broad applications for its strong functionality. Network analysis is one of the most important functions of GIS, and the most elementary and pivotal issue of network analysis is the calculation of shortest paths. The shortest paths are mostly applied to some emergent systems such as 119 fire alarms. These systems mainly require that the computation time of the optimal path should be 1-3 seconds. And during traveling, the next running path of the vehicles should be calculated in time. So the implement of the shortest paths must have a high efficiency. In this paper, the component GIS technology was applied to collect and record the data information (such as, the situation of this disaster, map and road status et al) of the reported fire firstly. The ant colony optimization was used to calculate the shortest path of fire succor secondly. The optimization results were sent to the pumpers, which can let pumpers choose the shortest paths intelligently and come to fire position with least time. The programming method for shortest paths is proposed in section 3. There are three parts in this section. The elementary framework of the proposed programming method is presented in part one. The systematic framework of GIS component is described in part two. The ant colony optimization employed is presented in part three. In section 4, a simple application instance was presented to demonstrate the proposed programming method. There are three parts in this section. The distributed Web application based on component GIS was described in part one. The optimization results without traffic constraint were presented in part two. The optimization results with traffic constraint were presented in part three. The contributions of this paper can be summarized as follows. (1) It proposed an effective approach for shortest paths in fire succor based on component GIS technology. This proposed approach can achieve the real-time decisions of shortest paths for fire succor. (2) It applied the ant colony optimization to implement the shortest path decision. The traffic information was considered in the shortest path decision using ant colony optimization. The final application instance suggests that the proposed approach is feasible, correct and valid.

Mobile robot dynamic path planning based on improved genetic algorithm

NASA Astrophysics Data System (ADS)

Wang, Yong; Zhou, Heng; Wang, Ying

2017-08-01

In dynamic unknown environment, the dynamic path planning of mobile robots is a difficult problem. In this paper, a dynamic path planning method based on genetic algorithm is proposed, and a reward value model is designed to estimate the probability of dynamic obstacles on the path, and the reward value function is applied to the genetic algorithm. Unique coding techniques reduce the computational complexity of the algorithm. The fitness function of the genetic algorithm fully considers three factors: the security of the path, the shortest distance of the path and the reward value of the path. The simulation results show that the proposed genetic algorithm is efficient in all kinds of complex dynamic environments.

String tightening as a self-organizing phenomenon.

PubMed

Banerjee, Bonny

2007-09-01

The phenomenon of self-organization has been of special interest to the neural network community throughout the last couple of decades. In this paper, we study a variant of the self-organizing map (SOM) that models the phenomenon of self-organization of the particles forming a string when the string is tightened from one or both of its ends. The proposed variant, called the string tightening self-organizing neural network (STON), can be used to solve certain practical problems, such as computation of shortest homotopic paths, smoothing paths to avoid sharp turns, computation of convex hull, etc. These problems are of considerable interest in computational geometry, robotics path-planning, artificial intelligence (AI) (diagrammatic reasoning), very large scale integration (VLSI) routing, and geographical information systems. Given a set of obstacles and a string with two fixed terminal points in a 2-D space, the STON model continuously tightens the given string until the unique shortest configuration in terms of the Euclidean metric is reached. The STON minimizes the total length of a string on convergence by dynamically creating and selecting feature vectors in a competitive manner. Proof of correctness of this anytime algorithm and experimental results obtained by its deployment have been presented in the paper.

A Comparison of Heuristic and Human Performance on Open Versions of the Traveling Salesperson Problem

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…

Randomized shortest-path problems: two related models.

PubMed

Saerens, Marco; Achbany, Youssef; Fouss, François; Yen, Luh

2009-08-01

This letter addresses the problem of designing the transition probabilities of a finite Markov chain (the policy) in order to minimize the expected cost for reaching a destination node from a source node while maintaining a fixed level of entropy spread throughout the network (the exploration). It is motivated by the following scenario. Suppose you have to route agents through a network in some optimal way, for instance, by minimizing the total travel cost-nothing particular up to now-you could use a standard shortest-path algorithm. Suppose, however, that you want to avoid pure deterministic routing policies in order, for instance, to allow some continual exploration of the network, avoid congestion, or avoid complete predictability of your routing strategy. In other words, you want to introduce some randomness or unpredictability in the routing policy (i.e., the routing policy is randomized). This problem, which will be called the randomized shortest-path problem (RSP), is investigated in this work. The global level of randomness of the routing policy is quantified by the expected Shannon entropy spread throughout the network and is provided a priori by the designer. Then, necessary conditions to compute the optimal randomized policy-minimizing the expected routing cost-are derived. Iterating these necessary conditions, reminiscent of Bellman's value iteration equations, allows computing an optimal policy, that is, a set of transition probabilities in each node. Interestingly and surprisingly enough, this first model, while formulated in a totally different framework, is equivalent to Akamatsu's model ( 1996 ), appearing in transportation science, for a special choice of the entropy constraint. We therefore revisit Akamatsu's model by recasting it into a sum-over-paths statistical physics formalism allowing easy derivation of all the quantities of interest in an elegant, unified way. For instance, it is shown that the unique optimal policy can be obtained by solving a simple linear system of equations. This second model is therefore more convincing because of its computational efficiency and soundness. Finally, simulation results obtained on simple, illustrative examples show that the models behave as expected.

Selective epidemic vaccination under the performant routing algorithms

NASA Astrophysics Data System (ADS)

Bamaarouf, O.; Alweimine, A. Ould Baba; Rachadi, A.; EZ-Zahraouy, H.

2018-04-01

Despite the extensive research on traffic dynamics and epidemic spreading, the effect of the routing algorithms strategies on the traffic-driven epidemic spreading has not received an adequate attention. It is well known that more performant routing algorithm strategies are used to overcome the congestion problem. However, our main result shows unexpectedly that these algorithms favor the virus spreading more than the case where the shortest path based algorithm is used. In this work, we studied the virus spreading in a complex network using the efficient path and the global dynamic routing algorithms as compared to shortest path strategy. Some previous studies have tried to modify the routing rules to limit the virus spreading, but at the expense of reducing the traffic transport efficiency. This work proposed a solution to overcome this drawback by using a selective vaccination procedure instead of a random vaccination used often in the literature. We found that the selective vaccination succeeded in eradicating the virus better than a pure random intervention for the performant routing algorithm strategies.

A Geographic Optimization Approach to Coast Guard Ship Basing

DTIC Science & Technology

2015-06-01

information found an optimal result for partition- ing. Carlsson applies the travelling salesman problem (tries to find the shortest path to visit a list of...maximum 200 words) This thesis studies the problem of finding efficient ship base locations, area of operations (AO) among bases, and ship assignments...for a coast guard (CG) organization. This problem is faced by many CGs around the world and is motivated by the need to optimize operational outcomes

Split-plot designs for robotic serial dilution assays.

PubMed

Buzas, Jeffrey S; Wager, Carrie G; Lansky, David M

2011-12-01

This article explores effective implementation of split-plot designs in serial dilution bioassay using robots. We show that the shortest path for a robot to fill plate wells for a split-plot design is equivalent to the shortest common supersequence problem in combinatorics. We develop an algorithm for finding the shortest common supersequence, provide an R implementation, and explore the distribution of the number of steps required to implement split-plot designs for bioassay through simulation. We also show how to construct collections of split plots that can be filled in a minimal number of steps, thereby demonstrating that split-plot designs can be implemented with nearly the same effort as strip-plot designs. Finally, we provide guidelines for modeling data that result from these designs. © 2011, The International Biometric Society.

An improved global dynamic routing strategy for scale-free network with tunable clustering

NASA Astrophysics Data System (ADS)

Sun, Lina; Huang, Ning; Zhang, Yue; Bai, Yannan

2016-08-01

An efficient routing strategy can deliver packets quickly to improve the network capacity. Node congestion and transmission path length are inevitable real-time factors for a good routing strategy. Existing dynamic global routing strategies only consider the congestion of neighbor nodes and the shortest path, which ignores other key nodes’ congestion on the path. With the development of detection methods and techniques, global traffic information is readily available and important for the routing choice. Reasonable use of this information can effectively improve the network routing. So, an improved global dynamic routing strategy is proposed, which considers the congestion of all nodes on the shortest path and incorporates the waiting time of the most congested node into the path. We investigate the effectiveness of the proposed routing for scale-free network with different clustering coefficients. The shortest path routing strategy and the traffic awareness routing strategy only considering the waiting time of neighbor node are analyzed comparatively. Simulation results show that network capacity is greatly enhanced compared with the shortest path; congestion state increase is relatively slow compared with the traffic awareness routing strategy. Clustering coefficient increase will not only reduce the network throughput, but also result in transmission average path length increase for scale-free network with tunable clustering. The proposed routing is favorable to ease network congestion and network routing strategy design.

Solving the Secondary Structure Matching Problem in Cryo-EM De Novo Modeling Using a Constrained K-Shortest Path Graph Algorithm.

PubMed

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.

An industrial robot singular trajectories planning based on graphs and neural networks

NASA Astrophysics Data System (ADS)

Łęgowski, Adrian; Niezabitowski, Michał

2016-06-01

Singular trajectories are rarely used because of issues during realization. A method of planning trajectories for given set of points in task space with use of graphs and neural networks is presented. In every desired point the inverse kinematics problem is solved in order to derive all possible solutions. A graph of solutions is made. The shortest path is determined to define required nodes in joint space. Neural networks are used to define the path between these nodes.

Improving the Air Mobility Command’s Air Refueler Route Building Capabilities

DTIC Science & Technology

2014-03-27

routing tool. Sundar and Rathinam [18] also study a traveling salesman version of the problem in the unmanned aerial vehicle realm. Their focus is on...constrained shortest path with fuel limitations. The objective is to minimize the distance traveled . Some aircraft routing problems involve...radius and network density their only limitations. 4 O’Rourke et al. [15] examine a traveling salesman version of aircraft routing in the unmanned aerial

On Compact Book Storage in Libraries.

ERIC Educational Resources Information Center

Ravindran, Arunachalam

The optimal storage of books by size in libraries is considered in this paper. It is shown that for a given collection of books of various sizes, the optimum number of shelf heights to use can be determined by finding the shortest path in an equivalent network. Applications of this model to inventory control, assortment and packaging problems are…

Spatial Interpolation of Fine Particulate Matter Concentrations Using the Shortest Wind-Field Path Distance

PubMed Central

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

Spatial interpolation of fine particulate matter concentrations using the shortest wind-field path distance.

PubMed

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.

Analytic solution of the lifeguard problem

NASA Astrophysics Data System (ADS)

De Luca, Roberto; Di Mauro, Marco; Naddeo, Adele

2018-03-01

A simple version due to Feynman of Fermat’s principle is analyzed. It deals with the path a lifeguard on a beach must follow to reach a drowning swimmer. The solution for the exact point, P(x, 0) , at the beach-sea boundary, corresponding to the fastest path to the swimmer, is worked out in detail and the analogy with light traveling at the air-water boundary is described. The results agree with the known conclusion that the shortest path does not coincide with the fastest one. The relevance of the subject for a basic physics course, at an advanced high school level, is pointed out.

Dynamic Shortest Path Algorithms for Hypergraphs

DTIC Science & Technology

2014-01-01

the concept of relationship tree to indicate the parent –child relationship along shortest hy- perpaths. The concept can be easily explained in the...four possible relationship trees to indicate the parent –child relationship in these shortest hyperpaths. We will show in Section III that the choice of...distance of a vertex to the source on the shortest hyperpath, the parent of in the chosen relationship tree associated with the shortest hyperpaths, This

A shortest-path graph kernel for estimating gene product semantic similarity.

PubMed

Alvarez, Marco A; Qi, Xiaojun; Yan, Changhui

2011-07-29

Existing methods for calculating semantic similarity between gene products using the Gene Ontology (GO) often rely on external resources, which are not part of the ontology. Consequently, changes in these external resources like biased term distribution caused by shifting of hot research topics, will affect the calculation of semantic similarity. One way to avoid this problem is to use semantic methods that are "intrinsic" to the ontology, i.e. independent of external knowledge. We present a shortest-path graph kernel (spgk) method that relies exclusively on the GO and its structure. In spgk, a gene product is represented by an induced subgraph of the GO, which consists of all the GO terms annotating it. Then a shortest-path graph kernel is used to compute the similarity between two graphs. In a comprehensive evaluation using a benchmark dataset, spgk compares favorably with other methods that depend on external resources. Compared with simUI, a method that is also intrinsic to GO, spgk achieves slightly better results on the benchmark dataset. Statistical tests show that the improvement is significant when the resolution and EC similarity correlation coefficient are used to measure the performance, but is insignificant when the Pfam similarity correlation coefficient is used. Spgk uses a graph kernel method in polynomial time to exploit the structure of the GO to calculate semantic similarity between gene products. It provides an alternative to both methods that use external resources and "intrinsic" methods with comparable performance.

Do People Use the Shortest Path? An Empirical Test of Wardrop’s First Principle

PubMed Central

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

Site-directed protein recombination as a shortest-path problem.

PubMed

Endelman, Jeffrey B; Silberg, Jonathan J; Wang, Zhen-Gang; Arnold, Frances H

2004-07-01

Protein function can be tuned using laboratory evolution, in which one rapidly searches through a library of proteins for the properties of interest. In site-directed recombination, n crossovers are chosen in an alignment of p parents to define a set of p(n + 1) peptide fragments. These fragments are then assembled combinatorially to create a library of p(n+1) proteins. We have developed a computational algorithm to enrich these libraries in folded proteins while maintaining an appropriate level of diversity for evolution. For a given set of parents, our algorithm selects crossovers that minimize the average energy of the library, subject to constraints on the length of each fragment. This problem is equivalent to finding the shortest path between nodes in a network, for which the global minimum can be found efficiently. Our algorithm has a running time of O(N(3)p(2) + N(2)n) for a protein of length N. Adjusting the constraints on fragment length generates a set of optimized libraries with varying degrees of diversity. By comparing these optima for different sets of parents, we rapidly determine which parents yield the lowest energy libraries.

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.

A link-adding strategy for transport efficiency of complex networks

NASA Astrophysics Data System (ADS)

Ma, Jinlong; Han, Weizhan; Guo, Qing; Wang, Zhenyong; Zhang, Shuai

2016-12-01

The transport efficiency is one of the critical parameters to evaluate the performance of a network. In this paper, we propose an improved efficient (IE) strategy to enhance the network transport efficiency of complex networks by adding a fraction of links to an existing network based on the node’s local degree centrality and the shortest path length. Simulation results show that the proposed strategy can bring better traffic capacity and shorter average shortest path length than the low-degree-first (LDF) strategy under the shortest path routing protocol. It is found that the proposed strategy is beneficial to the improvement of overall traffic handling and delivering ability of the network. This study can alleviate the congestion in networks, and is helpful to design and optimize realistic networks.

[Not Available].

PubMed

Yanashima, Ryoji; Kitagawa, Noriyuki; Matsubara, Yoshiya; Weatheritt, Robert; Oka, Kotaro; Kikuchi, Shinichi; Tomita, Masaru; Ishizaki, Shun

2009-01-01

The scale-free and small-world network models reflect the functional units of networks. However, when we investigated the network properties of a signaling pathway using these models, no significant differences were found between the original undirected graphs and the graphs in which inactive proteins were eliminated from the gene expression data. We analyzed signaling networks by focusing on those pathways that best reflected cellular function. Therefore, our analysis of pathways started from the ligands and progressed to transcription factors and cytoskeletal proteins. We employed the Python module to assess the target network. This involved comparing the original and restricted signaling cascades as a directed graph using microarray gene expression profiles of late onset Alzheimer's disease. The most commonly used method of shortest-path analysis neglects to consider the influences of alternative pathways that can affect the activation of transcription factors or cytoskeletal proteins. We therefore introduced included k-shortest paths and k-cycles in our network analysis using the Python modules, which allowed us to attain a reasonable computational time and identify k-shortest paths. This technique reflected results found in vivo and identified pathways not found when shortest path or degree analysis was applied. Our module enabled us to comprehensively analyse the characteristics of biomolecular networks and also enabled analysis of the effects of diseases considering the feedback loop and feedforward loop control structures as an alternative path.

Methodology for Augmenting Existing Paths with Additional Parallel Transects

DOE Office of Scientific and Technical Information (OSTI.GOV)

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—themore » 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.« less

Groupwise Image Registration Guided by a Dynamic Digraph of Images.

PubMed

Tang, Zhenyu; Fan, Yong

2016-04-01

For groupwise image registration, graph theoretic methods have been adopted for discovering the manifold of images to be registered so that accurate registration of images to a group center image can be achieved by aligning similar images that are linked by the shortest graph paths. However, the image similarity measures adopted to build a graph of images in the extant methods are essentially pairwise measures, not effective for capturing the groupwise similarity among multiple images. To overcome this problem, we present a groupwise image similarity measure that is built on sparse coding for characterizing image similarity among all input images and build a directed graph (digraph) of images so that similar images are connected by the shortest paths of the digraph. Following the shortest paths determined according to the digraph, images are registered to a group center image in an iterative manner by decomposing a large anatomical deformation field required to register an image to the group center image into a series of small ones between similar images. During the iterative image registration, the digraph of images evolves dynamically at each iteration step to pursue an accurate estimation of the image manifold. Moreover, an adaptive dictionary strategy is adopted in the groupwise image similarity measure to ensure fast convergence of the iterative registration procedure. The proposed method has been validated based on both simulated and real brain images, and experiment results have demonstrated that our method was more effective for learning the manifold of input images and achieved higher registration accuracy than state-of-the-art groupwise image registration methods.

A novel multi-segment path analysis based on a heterogeneous velocity model for the localization of acoustic emission sources in complex propagation media.

PubMed

Gollob, Stephan; Kocur, Georg Karl; Schumacher, Thomas; Mhamdi, Lassaad; Vogel, Thomas

2017-02-01

In acoustic emission analysis, common source location algorithms assume, independently of the nature of the propagation medium, a straight (shortest) wave path between the source and the sensors. For heterogeneous media such as concrete, the wave travels in complex paths due to the interaction with the dissimilar material contents and with the possible geometrical and material irregularities present in these media. For instance, cracks and large air voids present in concrete influence significantly the way the wave travels, by causing wave path deviations. Neglecting these deviations by assuming straight paths can introduce significant errors to the source location results. In this paper, a novel source localization method called FastWay is proposed. It accounts, contrary to most available shortest path-based methods, for the different effects of material discontinuities (cracks and voids). FastWay, based on a heterogeneous velocity model, uses the fastest rather than the shortest travel paths between the source and each sensor. The method was evaluated both numerically and experimentally and the results from both evaluation tests show that, in general, FastWay was able to locate sources of acoustic emissions more accurately and reliably than the traditional source localization methods. Copyright © 2016 Elsevier B.V. All rights reserved.

Path optimization with limited sensing ability

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kang, Sung Ha, E-mail: kang@math.gatech.edu; Kim, Seong Jun, E-mail: skim396@math.gatech.edu; Zhou, Haomin, E-mail: hmzhou@math.gatech.edu

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 reducingmore » 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.« less

Use of graph algorithms in the processing and analysis of images with focus on the biomedical data.

PubMed

Zdimalova, M; Roznovjak, R; Weismann, P; El Falougy, H; Kubikova, E

2017-01-01

Image segmentation is a known problem in the field of image processing. A great number of methods based on different approaches to this issue was created. One of these approaches utilizes the findings of the graph theory. Our work focuses on segmentation using shortest paths in a graph. Specifically, we deal with methods of "Intelligent Scissors," which use Dijkstra's algorithm to find the shortest paths. We created a new software in Microsoft Visual Studio 2013 integrated development environment Visual C++ in the language C++/CLI. We created a format application with a graphical users development environment for system Windows, with using the platform .Net (version 4.5). The program was used for handling and processing the original medical data. The major disadvantage of the method of "Intelligent Scissors" is the computational time length of Dijkstra's algorithm. However, after the implementation of a more efficient priority queue, this problem could be alleviated. The main advantage of this method we see in training that enables to adapt to a particular kind of edge, which we need to segment. The user involvement has a significant influence on the process of segmentation, which enormously aids to achieve high-quality results (Fig. 7, Ref. 13).

Label-based routing for a family of small-world Farey graphs.

PubMed

Zhai, Yinhu; Wang, Yinhe

2016-05-11

We introduce an informative labelling method for vertices in a family of Farey graphs, and deduce a routing algorithm on all the shortest paths between any two vertices in Farey graphs. The label of a vertex is composed of the precise locating position in graphs and the exact time linking to graphs. All the shortest paths routing between any pair of vertices, which number is exactly the product of two Fibonacci numbers, are determined only by their labels, and the time complexity of the algorithm is O(n). It is the first algorithm to figure out all the shortest paths between any pair of vertices in a kind of deterministic graphs. For Farey networks, the existence of an efficient routing protocol is of interest to design practical communication algorithms in relation to dynamical processes (including synchronization and structural controllability) and also to understand the underlying mechanisms that have shaped their particular structure.

Label-based routing for a family of small-world Farey graphs

NASA Astrophysics Data System (ADS)

Zhai, Yinhu; Wang, Yinhe

2016-05-01

We introduce an informative labelling method for vertices in a family of Farey graphs, and deduce a routing algorithm on all the shortest paths between any two vertices in Farey graphs. The label of a vertex is composed of the precise locating position in graphs and the exact time linking to graphs. All the shortest paths routing between any pair of vertices, which number is exactly the product of two Fibonacci numbers, are determined only by their labels, and the time complexity of the algorithm is O(n). It is the first algorithm to figure out all the shortest paths between any pair of vertices in a kind of deterministic graphs. For Farey networks, the existence of an efficient routing protocol is of interest to design practical communication algorithms in relation to dynamical processes (including synchronization and structural controllability) and also to understand the underlying mechanisms that have shaped their particular structure.

Planification de trajectoires pour une flotte d'UAVs

NASA Astrophysics Data System (ADS)

Ait El Cadi, Abdessamad

In this thesis we address the problem of coordinating and controlling a fleet of Unmanned Aerial Vehicles (UAVs) during a surveillance mission in a dynamic context. The problem is vast and is related to several scientific domains. We have studied three important parts of this problem: • modeling the ground with all its constraints; • computing a shortest non-holonomic continuous path in a risky environment with a presence of obstacles; • planning a surveillance mission for a fleet of UAVs in a real context. While investigating the scientific literature related to these topics, we have detected deficiencies in the modeling of the ground and in the computation of the shortest continuous path, two critical aspects for the planning of a mission. So after the literature review, we have proposed answers to these two aspects and have applied our developments to the planning of a mission of a fleet of UAVs in a risky environment with the presence of obstacles. Obstacles could be natural like mountain or any non flyable zone. We have first modeled the ground as a directed graph. However, instead of using a classic mesh, we opted for an intelligent modeling that reduces the computing time on the graph without losing accuracy. The proposed model is based on the concept of visibility graph, and it also takes into account the obstacles, the danger areas and the constraint of non-holonomy of the UAVs- the kinematic constraint of the planes that imposes a maximum steering angle. The graph is then cleaned to keep only the minimum information needed for the calculation of trajectories. The generation of this graph possibly requires a lot of computation time, but it is done only once before the planning and will not affect the performance of trajectory calculations. We have also developed another simpler graph that does not take into account the constraint of non-holonomy. The advantage of this second graph is that it reduces the computation time. However, it requires the use of a correction procedure to make the resulting trajectory non-holonomic. This correction is possible within the context of our missions, but not for all types of autonomous vehicles. Once the directed graph is generated, we propose the use of a procedure for calculating the shortest continuous non-holonomic path in a risky environment with the presence of obstacles. The directed graph already incorporates all the constraints, which makes it possible to model the problem as a shortest path problem with resource a resource constraint (the resource here is the amount of permitted risk). The results are very satisfactory since the resulting routes are non-holonomic paths that meet all constraints. Moreover, the computing time is very short. For cases based on the simpler graph, we have created a procedure for correcting the trajectory to make it non-holonomic. All calculations of non-holonomy are based on Dubins curves (1957). We have finally applied our results to the planning of a mission of a fleet of UAVs in a risky environment with the presence of obstacles. For this purpose, we have developed a directed multi-graph where, for each pair of targets (points of departure and return of the mission included), we calculate a series of shorter trajectories with different limits of risk -- from the risk-free path to the riskiest path. We then use a Tabu Search with two tabu lists. Using these procedures, we have been able to produce routes for a fleet of UAVs that minimize the cost of the mission while respecting the limit of risk and avoiding obstacles. Tests are conducted on examples created on the basis of descriptions given by the Canadian Defense and, also on some instances of the CVRP (Capacitated Vehicle Routing Problem), those described by Christofides et Elion and those described by Christofides, Mingozzi et Toth. The results are of very satisfactory since all trajectories are non-holonomic and the improvement of the objective, when compared to a simple constructive method, achieves in some cases between 10 % and 43 %. We have even obtained an improvement of 69 %, but on a poor solution generated by a greedy algorithm. (Abstract shortened by UMI.)

Seamless Image Mosaicking via Synchronization

NASA Astrophysics Data System (ADS)

Santellani, E.; Maset, E.; Fusiello, A.

2018-05-01

This paper proposes an innovative method to create high-quality seamless planar mosaics. The developed pipeline ensures good robustness against many common mosaicking problems (e.g., misalignments, colour distortion, moving objects, parallax) and differs from other works in the literature because a global approach, known as synchronization, is used for image registration and colour correction. To better conceal the mosaic seamlines, images are cut along specific paths, computed using a Voronoi decomposition of the mosaic area and a shortest path algorithm. Results obtained on challenging real datasets show that the colour correction mitigates significantly the colour variations between the original images and the seams on the final mosaic are not evident.

Dynamic path planning for mobile robot based on particle swarm optimization

NASA Astrophysics Data System (ADS)

Wang, Yong; Cai, Feng; Wang, Ying

2017-08-01

In the contemporary, robots are used in many fields, such as cleaning, medical treatment, space exploration, disaster relief and so on. The dynamic path planning of robot without collision is becoming more and more the focus of people's attention. A new method of path planning is proposed in this paper. Firstly, the motion space model of the robot is established by using the MAKLINK graph method. Then the A* algorithm is used to get the shortest path from the start point to the end point. Secondly, this paper proposes an effective method to detect and avoid obstacles. When an obstacle is detected on the shortest path, the robot will choose the nearest safety point to move. Moreover, calculate the next point which is nearest to the target. Finally, the particle swarm optimization algorithm is used to optimize the path. The experimental results can prove that the proposed method is more effective.

Floyd-warshall algorithm to determine the shortest path based on android

NASA Astrophysics Data System (ADS)

Ramadiani; Bukhori, D.; Azainil; Dengen, N.

2018-04-01

The development of technology has made all areas of life easier now, one of which is the ease of obtaining geographic information. The use of geographic information may vary according to need, for example, the digital map learning, navigation systems, observations area, and much more. With the support of adequate infrastructure, almost no one will ever get lost to a destination even to foreign places or that have never been visited before. The reasons why many institutions and business entities use technology to improve services to consumers and to streamline the production process undertaken and so forth. Speaking of the efficient, there are many elements related to efficiency in navigation systems, and one of them is the efficiency in terms of distance. The shortest distance determination algorithm required in this research is used Floyd-Warshall Algorithm. Floyd-Warshall algorithm is the algorithm to find the fastest path and the shortest distance between 2 nodes, while the program is intended to find the path of more than 2 nodes.

The Threshold Shortest Path Interdiction Problem for Critical Infrastructure Resilience Analysis

DTIC Science & Technology

2017-09-01

being pushed over the minimum designated threshold. 1.4 Motivation A simple setting to motivate this research is the “30 minutes or it’s free” guarantee...parallel network structure in Fig. 4.4 is simple in design , yet shows a relatively high resilience when compared to the other networks in general. The high...United States Naval Academy, 2002 Submitted in partial fulfillment of the requirements for the degree of MASTER OF SCIENCE IN OPERATIONS RESEARCH

Short paths in expander graphs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kleinberg, J.; Rubinfeld, R.

Graph expansion has proved to be a powerful general tool for analyzing the behavior of routing algorithms and the interconnection networks on which they run. We develop new routing algorithms and structural results for bounded-degree expander graphs. Our results are unified by the fact that they are all based upon, and extend, a body of work asserting that expanders are rich in short, disjoint paths. In particular, our work has consequences for the disjoint paths problem, multicommodify flow, and graph minor containment. We show: (i) A greedy algorithm for approximating the maximum disjoint paths problem achieves a polylogarithmic approximation ratiomore » in bounded-degree expanders. Although our algorithm is both deterministic and on-line, its performance guarantee is an improvement over previous bounds in expanders. (ii) For a multicommodily flow problem with arbitrary demands on a bounded-degree expander, there is a (1 + {epsilon})-optimal solution using only flow paths of polylogarithmic length. It follows that the multicommodity flow algorithm of Awerbuch and Leighton runs in nearly linear time per commodity in expanders. Our analysis is based on establishing the following: given edge weights on an expander G, one can increase some of the weights very slightly so the resulting shortest-path metric is smooth - the min-weight path between any pair of nodes uses a polylogarithmic number of edges. (iii) Every bounded-degree expander on n nodes contains every graph with O(n/log{sup O(1)} n) nodes and edges as a minor.« less

Comparison of Dijkstra's algorithm and dynamic programming method in finding shortest path for order picker in a warehouse

NASA Astrophysics Data System (ADS)

Nordin, Noraimi Azlin Mohd; Omar, Mohd; Sharif, S. Sarifah Radiah

2017-04-01

Companies are looking forward to improve their productivity within their warehouse operations and distribution centres. In a typical warehouse operation, order picking contributes more than half percentage of the operating costs. Order picking is a benchmark in measuring the performance and productivity improvement of any warehouse management. Solving order picking problem is crucial in reducing response time and waiting time of a customer in receiving his demands. To reduce the response time, proper routing for picking orders is vital. Moreover, in production line, it is vital to always make sure the supplies arrive on time. Hence, a sample routing network will be applied on EP Manufacturing Berhad (EPMB) as a case study. The Dijkstra's algorithm and Dynamic Programming method are applied to find the shortest distance for an order picker in order picking. The results show that the Dynamic programming method is a simple yet competent approach in finding the shortest distance to pick an order that is applicable in a warehouse within a short time period.

Entanglement-Gradient Routing for Quantum Networks.

PubMed

Gyongyosi, Laszlo; Imre, Sandor

2017-10-27

We define the entanglement-gradient routing scheme for quantum repeater networks. The routing framework fuses the fundamentals of swarm intelligence and quantum Shannon theory. Swarm intelligence provides nature-inspired solutions for problem solving. Motivated by models of social insect behavior, the routing is performed using parallel threads to determine the shortest path via the entanglement gradient coefficient, which describes the feasibility of the entangled links and paths of the network. The routing metrics are derived from the characteristics of entanglement transmission and relevant measures of entanglement distribution in quantum networks. The method allows a moderate complexity decentralized routing in quantum repeater networks. The results can be applied in experimental quantum networking, future quantum Internet, and long-distance quantum communications.

Fair sharing of resources in a supply network with constraints.

PubMed

Carvalho, Rui; Buzna, Lubos; Just, Wolfram; Helbing, Dirk; Arrowsmith, David K

2012-04-01

This paper investigates the effect of network topology on the fair allocation of network resources among a set of agents, an all-important issue for the efficiency of transportation networks all around us. We analyze a generic mechanism that distributes network capacity fairly among existing flow demands. The problem can be solved by semianalytical methods on a nearest-neighbor graph with one source and sink pair, when transport occurs over shortest paths. For this setup, we uncover a broad range of patterns of intersecting shortest paths as a function of the distance between the source and the sink. When the number of intersections is the maximum and the distance between the source and the sink is large, we find that a fair allocation implies a decrease of at least 50% from the maximum throughput. We also find that the histogram of the flow allocations assigned to the agents decays as a power law with exponent -1. Our semianalytical framework suggests possible explanations for the well-known reduction of the throughput in fair allocations. It also suggests that the combination of network topology and routing rules can lead to highly uneven (but fair) distributions of resources, a remark of caution to network designers.

Fair sharing of resources in a supply network with constraints

NASA Astrophysics Data System (ADS)

Carvalho, Rui; Buzna, Lubos; Just, Wolfram; Helbing, Dirk; Arrowsmith, David K.

2012-04-01

This paper investigates the effect of network topology on the fair allocation of network resources among a set of agents, an all-important issue for the efficiency of transportation networks all around us. We analyze a generic mechanism that distributes network capacity fairly among existing flow demands. The problem can be solved by semianalytical methods on a nearest-neighbor graph with one source and sink pair, when transport occurs over shortest paths. For this setup, we uncover a broad range of patterns of intersecting shortest paths as a function of the distance between the source and the sink. When the number of intersections is the maximum and the distance between the source and the sink is large, we find that a fair allocation implies a decrease of at least 50% from the maximum throughput. We also find that the histogram of the flow allocations assigned to the agents decays as a power law with exponent -1. Our semianalytical framework suggests possible explanations for the well-known reduction of the throughput in fair allocations. It also suggests that the combination of network topology and routing rules can lead to highly uneven (but fair) distributions of resources, a remark of caution to network designers.

Information spread of emergency events: path searching on social networks.

PubMed

Dai, Weihui; Hu, Hongzhi; Wu, Tunan; Dai, Yonghui

2014-01-01

Emergency has attracted global attentions of government and the public, and it will easily trigger a series of serious social problems if it is not supervised effectively in the dissemination process. In the Internet world, people communicate with each other and form various virtual communities based on social networks, which lead to a complex and fast information spread pattern of emergency events. This paper collects Internet data based on data acquisition and topic detection technology, analyzes the process of information spread on social networks, describes the diffusions and impacts of that information from the perspective of random graph, and finally seeks the key paths through an improved IBF algorithm. Application cases have shown that this algorithm can search the shortest spread paths efficiently, which may help us to guide and control the information dissemination of emergency events on early warning.

Intelligent emission-sensitive routing for plugin hybrid electric vehicles.

PubMed

Sun, Zhonghao; Zhou, Xingshe

2016-01-01

The existing transportation sector creates heavily environmental impacts and is a prime cause for the current climate change. The need to reduce emissions from this sector has stimulated efforts to speed up the application of electric vehicles (EVs). A subset of EVs, called plug-in hybrid electric vehicles (PHEVs), backup batteries with combustion engine, which makes PHEVs have a comparable driving range to conventional vehicles. However, this hybridization comes at a cost of higher emissions than all-electric vehicles. This paper studies the routing problem for PHEVs to minimize emissions. The existing shortest-path based algorithms cannot be applied to solving this problem, because of the several new challenges: (1) an optimal route may contain circles caused by detour for recharging; (2) emissions of PHEVs not only depend on the driving distance, but also depend on the terrain and the state of charge (SOC) of batteries; (3) batteries can harvest energy by regenerative braking, which makes some road segments have negative energy consumption. To address these challenges, this paper proposes a green navigation algorithm (GNA) which finds the optimal strategies: where to go and where to recharge. GNA discretizes the SOC, then makes the PHEV routing problem to satisfy the principle of optimality. Finally, GNA adopts dynamic programming to solve the problem. We evaluate GNA using synthetic maps generated by the delaunay triangulation. The results show that GNA can save more than 10 % energy and reduce 10 % emissions when compared to the shortest path algorithm. We also observe that PHEVs with the battery capacity of 10-15 KWh detour most and nearly no detour when larger than 30 KWh. This observation gives some insights when developing PHEVs.

Minimizing Communication in All-Pairs Shortest Paths

DTIC Science & Technology

2013-02-13

on a 16,384 vertex, 5% dense graph, is slightly faster using our approach (18.6 vs . 22.6 seconds) than using the replicated Johnson’s algorithm...Oracle and Samsung , as well as MathWorks. Research is also supported by DOE grants DE-SC0004938, DE-SC0005136, DE-SC0003959, DE-SC0008700, and AC02...Brickell, I. S. Dhillon, S. Sra, and J. A. Tropp. The metric nearness problem. SIAM J. Matrix Anal. Appl ., 30:375–396, 2008. [11] A. Buluç, J. R. Gilbert

Rough-Cut Capacity Planning in Multimodal Freight Transportation Networks

DTIC Science & Technology

2012-09-30

transportation system to losses in es - tablished routes or assets? That is, what is the nature and length of system capability degradation due to these...Multimodal Rough-Cut Capacity Planning is mod- eled using the Resource Constrained Shortest Path Problem. We demonstrate how this approach supports...of non-zero ele - ments and the 0 entries depict appropriately dimensioned blocks of 0 entries.∣∣∣∣∑ k Ck ∣∣∣∣ Σ 0 0 0 0 Σ 0 0

The Average Network Flow Problem: Shortest Path and Minimum Cost Flow Formulations, Algorithms, Heuristics, and Complexity

DTIC Science & Technology

2012-09-13

Jordan, Captain, USAF AFIT/DS/ENS/12-09 DEPARTMENT OF THE AIR FORCE AIR UNIVERSITY AIR FORCE INSTITUTE OF TECHNOLOGY Wright- Patterson Air Force Base...Way, Wright- Patterson AFB, Ohio, 45433, USA, +1 937-255-3636, jeremy.jordan@afit.edu jeffery.weir@afit.edu doral.sandlin@afit.edu 1.1 Abstract United...Technology 2950 Hobson Way, Wright- Patterson AFB, Ohio, 45433, USA, +1 937-255-3636, jeremy.jordan@afit.edu jeffery.weir@afit.edu doral.sandlin@afit.edu

A biologically inspired neural network for dynamic programming.

PubMed

Francelin Romero, R A; Kacpryzk, J; Gomide, F

2001-12-01

An artificial neural network with a two-layer feedback topology and generalized recurrent neurons, for solving nonlinear discrete dynamic optimization problems, is developed. A direct method to assign the weights of neural networks is presented. The method is based on Bellmann's Optimality Principle and on the interchange of information which occurs during the synaptic chemical processing among neurons. The neural network based algorithm is an advantageous approach for dynamic programming due to the inherent parallelism of the neural networks; further it reduces the severity of computational problems that can occur in methods like conventional methods. Some illustrative application examples are presented to show how this approach works out including the shortest path and fuzzy decision making problems.

Solving a four-destination traveling salesman problem using Escherichia coli cells as biocomputers.

PubMed

Esau, Michael; Rozema, Mark; Zhang, Tuo Huang; Zeng, Dawson; Chiu, Stephanie; Kwan, Rachel; Moorhouse, Cadence; Murray, Cameron; Tseng, Nien-Tsu; Ridgway, Doug; Sauvageau, Dominic; Ellison, Michael

2014-12-19

The Traveling Salesman Problem involves finding the shortest possible route visiting all destinations on a map only once before returning to the point of origin. The present study demonstrates a strategy for solving Traveling Salesman Problems using modified E. coli cells as processors for massively parallel computing. Sequential, combinatorial DNA assembly was used to generate routes, in the form of plasmids made up of marker genes, each representing a path between destinations, and short connecting linkers, each representing a given destination. Upon growth of the population of modified E. coli, phenotypic selection was used to eliminate invalid routes, and statistical analysis was performed to successfully identify the optimal solution. The strategy was successfully employed to solve a four-destination test problem.

Topics on data transmission problem in software definition network

NASA Astrophysics Data System (ADS)

Gao, Wei; Liang, Li; Xu, Tianwei; Gan, Jianhou

2017-08-01

In normal computer networks, the data transmission between two sites go through the shortest path between two corresponding vertices. However, in the setting of software definition network (SDN), it should monitor the network traffic flow in each site and channel timely, and the data transmission path between two sites in SDN should consider the congestion in current networks. Hence, the difference of available data transmission theory between normal computer network and software definition network is that we should consider the prohibit graph structures in SDN, and these forbidden subgraphs represent the sites and channels in which data can't be passed by the serious congestion. Inspired by theoretical analysis of an available data transmission in SDN, we consider some computational problems from the perspective of the graph theory. Several results determined in the paper imply the sufficient conditions of data transmission in SDN in the various graph settings.

Path similarity skeleton graph matching.

PubMed

Bai, Xiang; Latecki, Longin Jan

2008-07-01

This paper presents a novel framework to for shape recognition based on object silhouettes. The main idea is to match skeleton graphs by comparing the shortest paths between skeleton endpoints. In contrast to typical tree or graph matching methods, we completely ignore the topological graph structure. Our approach is motivated by the fact that visually similar skeleton graphs may have completely different topological structures. The proposed comparison of shortest paths between endpoints of skeleton graphs yields correct matching results in such cases. The skeletons are pruned by contour partitioning with Discrete Curve Evolution, which implies that the endpoints of skeleton branches correspond to visual parts of the objects. The experimental results demonstrate that our method is able to produce correct results in the presence of articulations, stretching, and occlusion.

Which Way Is Jerusalem? Navigating on a Spheroid

ERIC Educational Resources Information Center

Schechter, Murray

2007-01-01

Given two points on a spheroidal planet, what is the direction from the first to the second? The answer depends, of course, on what path you take. This paper compares two paths which suggest themselves, namely, the loxodrome, which is the path in which the direction stays constant, and the geodesic, which is the shortest path. The geodesic does…

Information Spread of Emergency Events: Path Searching on Social Networks

PubMed Central

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

A gradient system solution to Potts mean field equations and its electronic implementation.

PubMed

Urahama, K; Ueno, S

1993-03-01

A gradient system solution method is presented for solving Potts mean field equations for combinatorial optimization problems subject to winner-take-all constraints. In the proposed solution method the optimum solution is searched by using gradient descent differential equations whose trajectory is confined within the feasible solution space of optimization problems. This gradient system is proven theoretically to always produce a legal local optimum solution of combinatorial optimization problems. An elementary analog electronic circuit implementing the presented method is designed on the basis of current-mode subthreshold MOS technologies. The core constituent of the circuit is the winner-take-all circuit developed by Lazzaro et al. Correct functioning of the presented circuit is exemplified with simulations of the circuits implementing the scheme for solving the shortest path problems.

Circuity analyses of HSR network and high-speed train paths in China

PubMed Central

Zhao, Shuo; Huang, Jie; Shan, Xinghua

2017-01-01

Circuity, defined as the ratio of the shortest network distance to the Euclidean distance between one origin–destination (O-D) pair, can be adopted as a helpful evaluation method of indirect degrees of train paths. In this paper, the maximum circuity of the paths of operated trains is set to be the threshold value of the circuity of high-speed train paths. For the shortest paths of any node pairs, if their circuity is not higher than the threshold value, the paths can be regarded as the reasonable paths. With the consideration of a certain relative or absolute error, we cluster the reasonable paths on the basis of their inclusion relationship and the center path of each class represents a passenger transit corridor. We take the high-speed rail (HSR) network in China at the end of 2014 as an example, and obtain 51 passenger transit corridors, which are alternative sets of train paths. Furthermore, we analyze the circuity distribution of paths of all node pairs in the network. We find that the high circuity of train paths can be decreased with the construction of a high-speed railway line, which indicates that the structure of the HSR network in China tends to be more complete and the HSR network can make the Chinese railway network more efficient. PMID:28945757

Biomarker Identification for Prostate Cancer and Lymph Node Metastasis from Microarray Data and Protein Interaction Network Using Gene Prioritization Method

PubMed Central

Arias, Carlos Roberto; Yeh, Hsiang-Yuan; Soo, Von-Wun

2012-01-01

Finding a genetic disease-related gene is not a trivial task. Therefore, computational methods are needed to present clues to the biomedical community to explore genes that are more likely to be related to a specific disease as biomarker. We present biomarker identification problem using gene prioritization method called gene prioritization from microarray data based on shortest paths, extended with structural and biological properties and edge flux using voting scheme (GP-MIDAS-VXEF). The method is based on finding relevant interactions on protein interaction networks, then scoring the genes using shortest paths and topological analysis, integrating the results using a voting scheme and a biological boosting. We applied two experiments, one is prostate primary and normal samples and the other is prostate primary tumor with and without lymph nodes metastasis. We used 137 truly prostate cancer genes as benchmark. In the first experiment, GP-MIDAS-VXEF outperforms all the other state-of-the-art methods in the benchmark by retrieving the truest related genes from the candidate set in the top 50 scores found. We applied the same technique to infer the significant biomarkers in prostate cancer with lymph nodes metastasis which is not established well. PMID:22654636

At-Least Version of the Generalized Minimum Spanning Tree Problem: Optimization Through Ant Colony System and Genetic Algorithms

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.

Calculating Least Risk Paths in 3d Indoor Space

NASA Astrophysics Data System (ADS)

Vanclooster, A.; De Maeyer, Ph.; Fack, V.; Van de Weghe, N.

2013-08-01

Over the last couple of years, research on indoor environments has gained a fresh impetus; more specifically applications that support navigation and wayfinding have become one of the booming industries. Indoor navigation research currently covers the technological aspect of indoor positioning and the modelling of indoor space. The algorithmic development to support navigation has so far been left mostly untouched, as most applications mainly rely on adapting Dijkstra's shortest path algorithm to an indoor network. However, alternative algorithms for outdoor navigation have been proposed adding a more cognitive notion to the calculated paths and as such adhering to the natural wayfinding behaviour (e.g. simplest paths, least risk paths). These algorithms are currently restricted to outdoor applications. The need for indoor cognitive algorithms is highlighted by a more challenged navigation and orientation due to the specific indoor structure (e.g. fragmentation, less visibility, confined areas…). As such, the clarity and easiness of route instructions is of paramount importance when distributing indoor routes. A shortest or fastest path indoors not necessarily aligns with the cognitive mapping of the building. Therefore, the aim of this research is to extend those richer cognitive algorithms to three-dimensional indoor environments. More specifically for this paper, we will focus on the application of the least risk path algorithm of Grum (2005) to an indoor space. The algorithm as proposed by Grum (2005) is duplicated and tested in a complex multi-storey building. The results of several least risk path calculations are compared to the shortest paths in indoor environments in terms of total length, improvement in route description complexity and number of turns. Several scenarios are tested in this comparison: paths covering a single floor, paths crossing several building wings and/or floors. Adjustments to the algorithm are proposed to be more aligned to the specific structure of indoor environments (e.g. no turn restrictions, restricted usage of rooms, vertical movement) and common wayfinding strategies indoors. In a later stage, other cognitive algorithms will be implemented and tested in both an indoor and combined indoor-outdoor setting, in an effort to improve the overall user experience during navigation in indoor environments.

The electrobrachistochrone

NASA Astrophysics Data System (ADS)

Lipscombe, Trevor C.; Mungan, Carl E.

2018-05-01

The brachistochrone problem consists of finding the track of shortest travel time between given initial and final points for a particle sliding frictionlessly along it under the influence of a given external force field. Solvable variations of the standard example of a uniform gravitational field would be suitable for homework and computer projects by undergraduate physics students studying intermediate mechanics and electromagnetism. An electrobrachistochrone problem is here proposed, in which a charged particle moves along a frictionless track under the influence of its electrostatic force of attraction to an image charge in a grounded conducting plane below the track. The path of least time is found to be a foreshortened cycloid and its properties are investigated analytically and graphically.

Interpolating between random walks and optimal transportation routes: Flow with multiple sources and targets

NASA Astrophysics Data System (ADS)

Guex, Guillaume

2016-05-01

In recent articles about graphs, different models proposed a formalism to find a type of path between two nodes, the source and the target, at crossroads between the shortest-path and the random-walk path. These models include a freely adjustable parameter, allowing to tune the behavior of the path toward randomized movements or direct routes. This article presents a natural generalization of these models, namely a model with multiple sources and targets. In this context, source nodes can be viewed as locations with a supply of a certain good (e.g. people, money, information) and target nodes as locations with a demand of the same good. An algorithm is constructed to display the flow of goods in the network between sources and targets. With again a freely adjustable parameter, this flow can be tuned to follow routes of minimum cost, thus displaying the flow in the context of the optimal transportation problem or, by contrast, a random flow, known to be similar to the electrical current flow if the random-walk is reversible. Moreover, a source-targetcoupling can be retrieved from this flow, offering an optimal assignment to the transportation problem. This algorithm is described in the first part of this article and then illustrated with case studies.

Modelling information flow along the human connectome using maximum flow.

PubMed

Lyoo, Youngwook; Kim, Jieun E; Yoon, Sujung

2018-01-01

The human connectome is a complex network that transmits information between interlinked brain regions. Using graph theory, previously well-known network measures of integration between brain regions have been constructed under the key assumption that information flows strictly along the shortest paths possible between two nodes. However, it is now apparent that information does flow through non-shortest paths in many real-world networks such as cellular networks, social networks, and the internet. In the current hypothesis, we present a novel framework using the maximum flow to quantify information flow along all possible paths within the brain, so as to implement an analogy to network traffic. We hypothesize that the connection strengths of brain networks represent a limit on the amount of information that can flow through the connections per unit of time. This allows us to compute the maximum amount of information flow between two brain regions along all possible paths. Using this novel framework of maximum flow, previous network topological measures are expanded to account for information flow through non-shortest paths. The most important advantage of the current approach using maximum flow is that it can integrate the weighted connectivity data in a way that better reflects the real information flow of the brain network. The current framework and its concept regarding maximum flow provides insight on how network structure shapes information flow in contrast to graph theory, and suggests future applications such as investigating structural and functional connectomes at a neuronal level. Copyright © 2017 Elsevier Ltd. All rights reserved.

Tumor-Cut: segmentation of brain tumors on contrast enhanced MR images for radiosurgery applications.

PubMed

Hamamci, Andac; Kucuk, Nadir; Karaman, Kutlay; Engin, Kayihan; Unal, Gozde

2012-03-01

In this paper, we present a fast and robust practical tool for segmentation of solid tumors with minimal user interaction to assist clinicians and researchers in radiosurgery planning and assessment of the response to the therapy. Particularly, a cellular automata (CA) based seeded tumor segmentation method on contrast enhanced T1 weighted magnetic resonance (MR) images, which standardizes the volume of interest (VOI) and seed selection, is proposed. First, we establish the connection of the CA-based segmentation to the graph-theoretic methods to show that the iterative CA framework solves the shortest path problem. In that regard, we modify the state transition function of the CA to calculate the exact shortest path solution. Furthermore, a sensitivity parameter is introduced to adapt to the heterogeneous tumor segmentation problem, and an implicit level set surface is evolved on a tumor probability map constructed from CA states to impose spatial smoothness. Sufficient information to initialize the algorithm is gathered from the user simply by a line drawn on the maximum diameter of the tumor, in line with the clinical practice. Furthermore, an algorithm based on CA is presented to differentiate necrotic and enhancing tumor tissue content, which gains importance for a detailed assessment of radiation therapy response. Validation studies on both clinical and synthetic brain tumor datasets demonstrate 80%-90% overlap performance of the proposed algorithm with an emphasis on less sensitivity to seed initialization, robustness with respect to different and heterogeneous tumor types, and its efficiency in terms of computation time.

An improved least cost routing approach for WDM optical network without wavelength converters

NASA Astrophysics Data System (ADS)

Bonani, Luiz H.; Forghani-elahabad, Majid

2016-12-01

Routing and wavelength assignment (RWA) problem has been an attractive problem in optical networks, and consequently several algorithms have been proposed in the literature to solve this problem. The most known techniques for the dynamic routing subproblem are fixed routing, fixed-alternate routing, and adaptive routing methods. The first one leads to a high blocking probability (BP) and the last one includes a high computational complexity and requires immense backing from the control and management protocols. The second one suggests a trade-off between performance and complexity, and hence we consider it to improve in our work. In fact, considering the RWA problem in a wavelength routed optical network with no wavelength converter, an improved technique is proposed for the routing subproblem in order to decrease the BP of the network. Based on fixed-alternate approach, the first k shortest paths (SPs) between each node pair is determined. We then rearrange the SPs according to a newly defined cost for the links and paths. Upon arriving a connection request, the sorted paths are consecutively checked for an available wavelength according to the most-used technique. We implement our proposed algorithm and the least-hop fixed-alternate algorithm to show how the rearrangement of SPs contributes to a lower BP in the network. The numerical results demonstrate the efficiency of our proposed algorithm in comparison with the others, considering different number of available wavelengths.

Adaptive Bio-Inspired Wireless Network Routing for Planetary Surface Exploration

NASA Technical Reports Server (NTRS)

Alena, Richard I.; Lee, Charles

2004-01-01

Wireless mobile networks suffer connectivity loss when used in a terrain that has hills, and valleys when line of sight is interrupted or range is exceeded. To resolve this problem and achieve acceptable network performance, we have designed an adaptive, configurable, hybrid system to automatically route network packets along the best path between multiple geographically dispersed modules. This is very useful in planetary surface exploration, especially for ad-hoc mobile networks, where computational devices take an active part in creating a network infrastructure, and can actually be used to route data dynamically and even store data for later transmission between networks. Using inspiration from biological systems, this research proposes to use ant trail algorithms with multi-layered information maps (topographic maps, RF coverage maps) to determine the best route through ad-hoc network at real time. The determination of best route is a complex one, and requires research into the appropriate metrics, best method to identify the best path, optimizing traffic capacity, network performance, reliability, processing capabilities and cost. Real ants are capable of finding the shortest path from their nest to a food source without visual sensing through the use of pheromones. They are also able to adapt to changes in the environment using subtle clues. To use ant trail algorithms, we need to define the probability function. The artificial ant is, in this case, a software agent that moves from node to node on a network graph. The function to calculate the fitness (evaluate the better path) includes: length of the network edge, the coverage index, topology graph index, and pheromone trail left behind by other ant agents. Each agent modifies the environment in two different ways: 1) Local trail updating: As the ant moves between nodes it updates the amount of pheromone on the edge; and 2) Global trail updating: When all ants have completed a tour the ant that found the shortest route updates the edges in its path.

Human performance on the traveling salesman problem.

PubMed

MacGregor, J N; Ormerod, T

1996-05-01

Two experiments on performance on the traveling salesman problem (TSP) are reported. The TSP consists of finding the shortest path through a set of points, returning to the origin. It appears to be an intransigent mathematical problem, and heuristics have been developed to find approximate solutions. The first experiment used 10-point, the second, 20-point problems. The experiments tested the hypothesis that complexity of TSPs is a function of number of nonboundary points, not total number of points. Both experiments supported the hypothesis. The experiments provided information on the quality of subjects' solutions. Their solutions clustered close to the best known solutions, were an order of magnitude better than solutions produced by three well-known heuristics, and on average fell beyond the 99.9th percentile in the distribution of random solutions. The solution process appeared to be perceptually based.

Experimental evaluation of certification trails using abstract data type validation

NASA Technical Reports Server (NTRS)

Wilson, Dwight S.; Sullivan, Gregory F.; Masson, Gerald M.

1993-01-01

Certification trails are a recently introduced and promising approach to fault-detection and fault-tolerance. Recent experimental work reveals many cases in which a certification-trail approach allows for significantly faster program execution time than a basic time-redundancy approach. Algorithms for answer-validation of abstract data types allow a certification trail approach to be used for a wide variety of problems. An attempt to assess the performance of algorithms utilizing certification trails on abstract data types is reported. Specifically, this method was applied to the following problems: heapsort, Hullman tree, shortest path, and skyline. Previous results used certification trails specific to a particular problem and implementation. The approach allows certification trails to be localized to 'data structure modules,' making the use of this technique transparent to the user of such modules.

Predictions of first passage times in sparse discrete fracture networks using graph-based reductions

NASA Astrophysics Data System (ADS)

Hyman, J.; Hagberg, A.; Srinivasan, G.; Mohd-Yusof, J.; Viswanathan, H. S.

2017-12-01

We present a graph-based methodology to reduce the computational cost of obtaining first passage times through sparse fracture networks. We derive graph representations of generic three-dimensional discrete fracture networks (DFNs) using the DFN topology and flow boundary conditions. Subgraphs corresponding to the union of the k shortest paths between the inflow and outflow boundaries are identified and transport on their equivalent subnetworks is compared to transport through the full network. The number of paths included in the subgraphs is based on the scaling behavior of the number of edges in the graph with the number of shortest paths. First passage times through the subnetworks are in good agreement with those obtained in the full network, both for individual realizations and in distribution. Accurate estimates of first passage times are obtained with an order of magnitude reduction of CPU time and mesh size using the proposed method.

Predictions of first passage times in sparse discrete fracture networks using graph-based reductions

NASA Astrophysics Data System (ADS)

Hyman, Jeffrey D.; Hagberg, Aric; Srinivasan, Gowri; Mohd-Yusof, Jamaludin; Viswanathan, Hari

2017-07-01

We present a graph-based methodology to reduce the computational cost of obtaining first passage times through sparse fracture networks. We derive graph representations of generic three-dimensional discrete fracture networks (DFNs) using the DFN topology and flow boundary conditions. Subgraphs corresponding to the union of the k shortest paths between the inflow and outflow boundaries are identified and transport on their equivalent subnetworks is compared to transport through the full network. The number of paths included in the subgraphs is based on the scaling behavior of the number of edges in the graph with the number of shortest paths. First passage times through the subnetworks are in good agreement with those obtained in the full network, both for individual realizations and in distribution. Accurate estimates of first passage times are obtained with an order of magnitude reduction of CPU time and mesh size using the proposed method.

Approximate solution of the multiple watchman routes problem with restricted visibility range.

PubMed

Faigl, Jan

2010-10-01

In this paper, a new self-organizing map (SOM) based adaptation procedure is proposed to address the multiple watchman route problem with the restricted visibility range in the polygonal domain W. A watchman route is represented by a ring of connected neuron weights that evolves in W, while obstacles are considered by approximation of the shortest path. The adaptation procedure considers a coverage of W by the ring in order to attract nodes toward uncovered parts of W. The proposed procedure is experimentally verified in a set of environments and several visibility ranges. Performance of the procedure is compared with the decoupled approach based on solutions of the art gallery problem and the consecutive traveling salesman problem. The experimental results show the suitability of the proposed procedure based on relatively simple supporting geometrical structures, enabling application of the SOM principles to watchman route problems in W.

A combinatorial approach to the design of vaccines.

PubMed

Martínez, Luis; Milanič, Martin; Legarreta, Leire; Medvedev, Paul; Malaina, Iker; de la Fuente, Ildefonso M

2015-05-01

We present two new problems of combinatorial optimization and discuss their applications to the computational design of vaccines. In the shortest λ-superstring problem, given a family S1,...,S(k) of strings over a finite alphabet, a set Τ of "target" strings over that alphabet, and an integer λ, the task is to find a string of minimum length containing, for each i, at least λ target strings as substrings of S(i). In the shortest λ-cover superstring problem, given a collection X1,...,X(n) of finite sets of strings over a finite alphabet and an integer λ, the task is to find a string of minimum length containing, for each i, at least λ elements of X(i) as substrings. The two problems are polynomially equivalent, and the shortest λ-cover superstring problem is a common generalization of two well known combinatorial optimization problems, the shortest common superstring problem and the set cover problem. We present two approaches to obtain exact or approximate solutions to the shortest λ-superstring and λ-cover superstring problems: one based on integer programming, and a hill-climbing algorithm. An application is given to the computational design of vaccines and the algorithms are applied to experimental data taken from patients infected by H5N1 and HIV-1.

Extended shortest path selection for package routing of complex networks

NASA Astrophysics Data System (ADS)

Ye, Fan; Zhang, Lei; Wang, Bing-Hong; Liu, Lu; Zhang, Xing-Yi

The routing strategy plays a very important role in complex networks such as Internet system and Peer-to-Peer networks. However, most of the previous work concentrates only on the path selection, e.g. Flooding and Random Walk, or finding the shortest path (SP) and rarely considering the local load information such as SP and Distance Vector Routing. Flow-based Routing mainly considers load balance and still cannot achieve best optimization. Thus, in this paper, we propose a novel dynamic routing strategy on complex network by incorporating the local load information into SP algorithm to enhance the traffic flow routing optimization. It was found that the flow in a network is greatly affected by the waiting time of the network, so we should not consider only choosing optimized path for package transformation but also consider node congestion. As a result, the packages should be transmitted with a global optimized path with smaller congestion and relatively short distance. Analysis work and simulation experiments show that the proposed algorithm can largely enhance the network flow with the maximum throughput within an acceptable calculating time. The detailed analysis of the algorithm will also be provided for explaining the efficiency.

Spatial interpolation of river channel topography using the shortest temporal distance

NASA Astrophysics Data System (ADS)

Zhang, Yanjun; Xian, Cuiling; Chen, Huajin; Grieneisen, Michael L.; Liu, Jiaming; Zhang, Minghua

2016-11-01

It is difficult to interpolate river channel topography due to complex anisotropy. As the anisotropy is often caused by river flow, especially the hydrodynamic and transport mechanisms, it is reasonable to incorporate flow velocity into topography interpolator for decreasing the effect of anisotropy. In this study, two new distance metrics defined as the time taken by water flow to travel between two locations are developed, and replace the spatial distance metric or Euclidean distance that is currently used to interpolate topography. One is a shortest temporal distance (STD) metric. The temporal distance (TD) of a path between two nodes is calculated by spatial distance divided by the tangent component of flow velocity along the path, and the STD is searched using the Dijkstra algorithm in all possible paths between two nodes. The other is a modified shortest temporal distance (MSTD) metric in which both the tangent and normal components of flow velocity were combined. They are used to construct the methods for the interpolation of river channel topography. The proposed methods are used to generate the topography of Wuhan Section of Changjiang River and compared with Universal Kriging (UK) and Inverse Distance Weighting (IDW). The results clearly showed that the STD and MSTD based on flow velocity were reliable spatial interpolators. The MSTD, followed by the STD, presents improvement in prediction accuracy relative to both UK and IDW.

An experimental analysis on OSPF-TE convergence time

NASA Astrophysics Data System (ADS)

Huang, S.; Kitayama, K.; Cugini, F.; Paolucci, F.; Giorgetti, A.; Valcarenghi, L.; Castoldi, P.

2008-11-01

Open shortest path first (OSPF) protocol is commonly used as an interior gateway protocol (IGP) in MPLS and generalized MPLS (GMPLS) networks to determine the topology over which label-switched paths (LSPs) can be established. Traffic-engineering extensions (network states such as link bandwidth information, available wavelengths, signal quality, etc) have been recently enabled in OSPF (henceforth, called OSPF-TE) to support shortest path first (SPF) tree calculation upon different purposes, thus possibly achieving optimal path computation and helping improve resource utilization efficiency. Adding these features into routing phase can exploit the OSPF robustness, and no additional network component is required to manage the traffic-engineering information. However, this traffic-engineering enhancement also complicates OSPF behavior. Since network states change frequently upon the dynamic trafficengineered LSP setup and release, the network is easily driven from a stable state to unstable operating regimes. In this paper, we focus on studying the OSPF-TE stability in terms of convergence time. Convergence time is referred to the time spent by the network to go back to steady states upon any network state change. An external observation method (based on black-box method) is employed to estimate the convergence time. Several experimental test-beds are developed to emulate dynamic LSP setup/release, re-routing upon single-link failure. The experimental results show that with OSPF-TE the network requires more time to converge compared to the conventional OSPF protocol without TE extension. Especially, in case of wavelength-routed optical network (WRON), introducing per wavelength availability and wavelength continuity constraint to OSPF-TE suffers severe convergence time and a large number of advertised link state advertisements (LSAs). Our study implies that long convergence time and large number of LSAs flooded in the network might cause scalability problems in OSPF-TE and impose limitations on OSPF-TE applications. New solutions to mitigate the s convergence time and to reduce the amount of state information are desired in the future.

Predictions of first passage times in sparse discrete fracture networks using graph-based reductions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hyman, Jeffrey De'Haven; Hagberg, Aric Arild; Mohd-Yusof, Jamaludin

Here, we present a graph-based methodology to reduce the computational cost of obtaining first passage times through sparse fracture networks. We also derive graph representations of generic three-dimensional discrete fracture networks (DFNs) using the DFN topology and flow boundary conditions. Subgraphs corresponding to the union of the k shortest paths between the inflow and outflow boundaries are identified and transport on their equivalent subnetworks is compared to transport through the full network. The number of paths included in the subgraphs is based on the scaling behavior of the number of edges in the graph with the number of shortest paths.more » First passage times through the subnetworks are in good agreement with those obtained in the full network, both for individual realizations and in distribution. We obtain accurate estimates of first passage times with an order of magnitude reduction of CPU time and mesh size using the proposed method.« less

Predictions of first passage times in sparse discrete fracture networks using graph-based reductions

DOE PAGES

Hyman, Jeffrey De'Haven; Hagberg, Aric Arild; Mohd-Yusof, Jamaludin; ...

2017-07-10

Here, we present a graph-based methodology to reduce the computational cost of obtaining first passage times through sparse fracture networks. We also derive graph representations of generic three-dimensional discrete fracture networks (DFNs) using the DFN topology and flow boundary conditions. Subgraphs corresponding to the union of the k shortest paths between the inflow and outflow boundaries are identified and transport on their equivalent subnetworks is compared to transport through the full network. The number of paths included in the subgraphs is based on the scaling behavior of the number of edges in the graph with the number of shortest paths.more » First passage times through the subnetworks are in good agreement with those obtained in the full network, both for individual realizations and in distribution. We obtain accurate estimates of first passage times with an order of magnitude reduction of CPU time and mesh size using the proposed method.« less

A novel method for trajectory planning of cooperative mobile manipulators.

PubMed

Bolandi, Hossein; Ehyaei, Amir Farhad

2011-01-01

We have designed a two-stage scheme to consider the trajectory planning problem of two mobile manipulators for cooperative transportation of a rigid body in the presence of static obstacles. In the first stage, with regard to the static obstacles, we develop a method that searches the workspace for the shortest possible path between the start and goal configurations, by constructing a graph on a portion of the configuration space that satisfies the collision and closure constraints. The final stage is to calculate a sequence of time-optimal trajectories to go between the consecutive points of the path, with regard to the nonholonomic constraints and the maximum allowed joint accelerations. This approach allows geometric constraints such as joint limits and closed-chain constraints, along with differential constraints such as nonholonomic velocity constraints and acceleration limits, to be incorporated into the planning scheme. The simulation results illustrate the effectiveness of the proposed method.

A Novel Method for Trajectory Planning of Cooperative Mobile Manipulators

PubMed Central

Bolandi, Hossein; Ehyaei, Amir Farhad

2011-01-01

We have designed a two-stage scheme to consider the trajectory planning problem of two mobile manipulators for cooperative transportation of a rigid body in the presence of static obstacles. In the first stage, with regard to the static obstacles, we develop a method that searches the workspace for the shortest possible path between the start and goal configurations, by constructing a graph on a portion of the configuration space that satisfies the collision and closure constraints. The final stage is to calculate a sequence of time-optimal trajectories to go between the consecutive points of the path, with regard to the nonholonomic constraints and the maximum allowed joint accelerations. This approach allows geometric constraints such as joint limits and closed-chain constraints, along with differential constraints such as nonholonomic velocity constraints and acceleration limits, to be incorporated into the planning scheme. The simulation results illustrate the effectiveness of the proposed method. PMID:22606656

Google Maps for Crowdsourced Emergency Routing

NASA Astrophysics Data System (ADS)

Nedkov, S.; Zlatanova, S.

2012-08-01

Gathering infrastructure data in emergency situations is challenging. The affected by a disaster areas are often large and the needed observations numerous. Spaceborne remote sensing techniques cover large areas but they are of limited use as their field of view may be blocked by clouds, smoke, buildings, highways, etc. Remote sensing products furthermore require specialists to collect and analyze the data. This contrasts the nature of the damage detection problem: almost everyone is capable of observing whether a street is usable or not. The crowd is fit for solving these challenges as its members are numerous, they are willing to help and are often in the vicinity of the disaster thereby forming a highly dispersed sensor network. This paper proposes and implements a small WebGIS application for performing shortest path calculations based on crowdsourced information about the infrastructure health. The application is built on top of Google Maps and uses its routing service to calculate the shortest distance between two locations. Impassable areas are indicated on a map by people performing in-situ observations on a mobile device, and by users on a desktop machine who consult a multitude of information sources.

Comparison of weighted and unweighted network analysis in the case of a pig trade network in Northern Germany.

PubMed

Büttner, Kathrin; Krieter, Joachim

2018-08-01

The analysis of trade networks as well as the spread of diseases within these systems focuses mainly on pure animal movements between farms. However, additional data included as edge weights can complement the informational content of the network analysis. However, the inclusion of edge weights can also alter the outcome of the network analysis. Thus, the aim of the study was to compare unweighted and weighted network analyses of a pork supply chain in Northern Germany and to evaluate the impact on the centrality parameters. Five different weighted network versions were constructed by adding the following edge weights: number of trade contacts, number of delivered livestock, average number of delivered livestock per trade contact, geographical distance and reciprocal geographical distance. Additionally, two different edge weight standardizations were used. The network observed from 2013 to 2014 contained 678 farms which were connected by 1,018 edges. General network characteristics including shortest path structure (e.g. identical shortest paths, shortest path lengths) as well as centrality parameters for each network version were calculated. Furthermore, the targeted and the random removal of farms were performed in order to evaluate the structural changes in the networks. All network versions and edge weight standardizations revealed the same number of shortest paths (1,935). Between 94.4 to 98.9% of the unweighted network and the weighted network versions were identical. Furthermore, depending on the calculated centrality parameters and the edge weight standardization used, it could be shown that the weighted network versions differed from the unweighted network (e.g. for the centrality parameters based on ingoing trade contacts) or did not differ (e.g. for the centrality parameters based on the outgoing trade contacts) with regard to the Spearman Rank Correlation and the targeted removal of farms. The choice of standardization method as well as the inclusion or exclusion of specific farm types (e.g. abattoirs) can alter the results significantly. These facts have to be considered when centrality parameters are to be used for the implementation of prevention and control strategies in the case of an epidemic. Copyright © 2018 Elsevier B.V. All rights reserved.

Fiber tracking of brain white matter based on graph theory.

PubMed

Lu, Meng

2015-01-01

Brain white matter tractography is reconstructed via diffusion-weighted magnetic resonance images. Due to the complex structure of brain white matter fiber bundles, fiber crossing and fiber branching are abundant in human brain. And regular methods with diffusion tensor imaging (DTI) can't accurately handle this problem. the biggest problems of the brain tractography. Therefore, this paper presented a novel brain white matter tractography method based on graph theory, so the fiber tracking between two voxels is transformed into locating the shortest path in a graph. Besides, the presented method uses Q-ball imaging (QBI) as the source data instead of DTI, because QBI can provide accurate information about multiple fiber crossing and branching in one voxel using orientation distribution function (ODF). Experiments showed that the presented method can accurately handle the problem of brain white matter fiber crossing and branching, and reconstruct brain tractograhpy both in phantom data and real brain data.

Tree-space statistics and approximations for large-scale analysis of anatomical trees.

PubMed

Feragen, Aasa; Owen, Megan; Petersen, Jens; Wille, Mathilde M W; Thomsen, Laura H; Dirksen, Asger; de Bruijne, Marleen

2013-01-01

Statistical analysis of anatomical trees is hard to perform due to differences in the topological structure of the trees. In this paper we define statistical properties of leaf-labeled anatomical trees with geometric edge attributes by considering the anatomical trees as points in the geometric space of leaf-labeled trees. This tree-space is a geodesic metric space where any two trees are connected by a unique shortest path, which corresponds to a tree deformation. However, tree-space is not a manifold, and the usual strategy of performing statistical analysis in a tangent space and projecting onto tree-space is not available. Using tree-space and its shortest paths, a variety of statistical properties, such as mean, principal component, hypothesis testing and linear discriminant analysis can be defined. For some of these properties it is still an open problem how to compute them; others (like the mean) can be computed, but efficient alternatives are helpful in speeding up algorithms that use means iteratively, like hypothesis testing. In this paper, we take advantage of a very large dataset (N = 8016) to obtain computable approximations, under the assumption that the data trees parametrize the relevant parts of tree-space well. Using the developed approximate statistics, we illustrate how the structure and geometry of airway trees vary across a population and show that airway trees with Chronic Obstructive Pulmonary Disease come from a different distribution in tree-space than healthy ones. Software is available from http://image.diku.dk/aasa/software.php.

Spatial and temporal allocation of ship exhaust emissions in Australian coastal waters using AIS data: Analysis and treatment of data gaps

NASA Astrophysics Data System (ADS)

Goldsworthy, Brett

2017-08-01

Ship exhaust emissions need to be allocated accurately in both space and time in order to examine many of the associated impacts, including on air quality and health. Data on ship activity from the Automatic Identification System (AIS) allow ship exhaust emissions to be calculated with fine spatial and temporal resolution. However, there are spatial gaps in the coverage afforded by the coastal network of ground stations that are used to collect the AIS data. This paper focuses on the problem of allocating emissions to the coastal gap regions. Allocating emissions to these regions involves generating interpolated ship tracks that both span the gaps and avoid coming too close to land. In most cases, a simple shortest path or straight line interpolation produces tracks that do not overlap or come too close to land. Where the simple method does not produce acceptable results, vessel tracks are steered around land on shortest available paths using a combination of visibility graphs and Dijkstra's algorithm. A geographical cluster analysis is first used to identify the boundary regions of the data gaps. The properties of the data gaps are summarised in terms of the length, duration and speed of the spanning tracks. The interpolation methods are used to improve the spatial distribution of emissions. It is also shown that emissions in the gap regions can contribute substantially to the total ship exhaust emissions in close proximity to highly populated areas.

a Movable Charging Unit for Green Mobility

NASA Astrophysics Data System (ADS)

ElBanhawy, E. Y.; Nassar, K.

2013-05-01

Battery swapping of electric vehicles (EVs) matter appears to be the swiftest and most convenient to users. The existence of swapping stations increases the feasibility of distributed energy storage via the electric grid. However, it is a cost-prohibitive way of charging. Early adaptors' preferences of /perceptions about EV system in general, has its inflectional effects on potential users hence the market penetration level. Yet, the charging matter of electric batteries worries the users and puts more pressure on them with the more rigorous planning-ahead they have to make prior to any trip. This paper presents a distinctive way of charging. It aims at making the overall charging process at ease. From a closer look into the literature, most of EVs' populations depend on domestic charge. Domestic charging gives them more confidence and increases the usability factor of the EV system. Nevertheless, they still need to count on the publically available charging points to reach their destination(s). And when it comes to multifamily residences, it becomes a thorny problem as these apartments do not have a room for charging outlets. Having said the irritating charging time needed to fatten the batteries over the day and the minimal average mileage drove daily, hypothetically, home delivery charging (Movable Charging Unit-MCU) would be a stupendous solution. The paper discusses the integration of shortest path algorithm problem with the information about EV users within a metropolitan area, developing an optimal route for a charging unit. This MCU delivers charging till homes whether by swapping batteries or by fast charging facility. Information about users is to be provided by the service provider of the neighbourhood, which includes charging patterns (timing, power capacity). This problem lies under the shortest path algorithms problem. It provides optimal route of charging that in return shall add more reliability and usability values and alleviate the charging/ limited range / daily planning anxieties. The model is in a very preliminary stage of development, future work is needed to elaborate on the model and developing a complete feasibility study.

An ensemble method for extracting adverse drug events from social media.

PubMed

Liu, Jing; Zhao, Songzheng; Zhang, Xiaodi

2016-06-01

Because adverse drug events (ADEs) are a serious health problem and a leading cause of death, it is of vital importance to identify them correctly and in a timely manner. With the development of Web 2.0, social media has become a large data source for information on ADEs. The objective of this study is to develop a relation extraction system that uses natural language processing techniques to effectively distinguish between ADEs and non-ADEs in informal text on social media. We develop a feature-based approach that utilizes various lexical, syntactic, and semantic features. Information-gain-based feature selection is performed to address high-dimensional features. Then, we evaluate the effectiveness of four well-known kernel-based approaches (i.e., subset tree kernel, tree kernel, shortest dependency path kernel, and all-paths graph kernel) and several ensembles that are generated by adopting different combination methods (i.e., majority voting, weighted averaging, and stacked generalization). All of the approaches are tested using three data sets: two health-related discussion forums and one general social networking site (i.e., Twitter). When investigating the contribution of each feature subset, the feature-based approach attains the best area under the receiver operating characteristics curve (AUC) values, which are 78.6%, 72.2%, and 79.2% on the three data sets. When individual methods are used, we attain the best AUC values of 82.1%, 73.2%, and 77.0% using the subset tree kernel, shortest dependency path kernel, and feature-based approach on the three data sets, respectively. When using classifier ensembles, we achieve the best AUC values of 84.5%, 77.3%, and 84.5% on the three data sets, outperforming the baselines. Our experimental results indicate that ADE extraction from social media can benefit from feature selection. With respect to the effectiveness of different feature subsets, lexical features and semantic features can enhance the ADE extraction capability. Kernel-based approaches, which can stay away from the feature sparsity issue, are qualified to address the ADE extraction problem. Combining different individual classifiers using suitable combination methods can further enhance the ADE extraction effectiveness. Copyright © 2016 Elsevier B.V. All rights reserved.

Planning paths to multiple targets: memory involvement and planning heuristics in spatial problem solving.

PubMed

Wiener, J M; Ehbauer, N N; Mallot, H A

2009-09-01

For large numbers of targets, path planning is a complex and computationally expensive task. Humans, however, usually solve such tasks quickly and efficiently. We present experiments studying human path planning performance and the cognitive processes and heuristics involved. Twenty-five places were arranged on a regular grid in a large room. Participants were repeatedly asked to solve traveling salesman problems (TSP), i.e., to find the shortest closed loop connecting a start location with multiple target locations. In Experiment 1, we tested whether humans employed the nearest neighbor (NN) strategy when solving the TSP. Results showed that subjects outperform the NN-strategy, suggesting that it is not sufficient to explain human route planning behavior. As a second possible strategy we tested a hierarchical planning heuristic in Experiment 2, demonstrating that participants first plan a coarse route on the region level that is refined during navigation. To test for the relevance of spatial working memory (SWM) and spatial long-term memory (LTM) for planning performance and the planning heuristics applied, we varied the memory demands between conditions in Experiment 2. In one condition the target locations were directly marked, such that no memory was required; a second condition required participants to memorize the target locations during path planning (SWM); in a third condition, additionally, the locations of targets had to retrieved from LTM (SWM and LTM). Results showed that navigation performance decreased with increasing memory demands while the dependence on the hierarchical planning heuristic increased.

Time optimized path-choice in the termite hunting ant Megaponera analis.

PubMed

Frank, Erik T; Hönle, Philipp O; Linsenmair, K Eduard

2018-05-10

Trail network systems among ants have received a lot of scientific attention due to their various applications in problem solving of networks. Recent studies have shown that ants select the fastest available path when facing different velocities on different substrates, rather than the shortest distance. The progress of decision-making by these ants is determined by pheromone-based maintenance of paths, which is a collective decision. However, path optimization through individual decision-making remains mostly unexplored. Here we present the first study of time-optimized path selection via individual decision-making by scout ants. Megaponera analis scouts search for termite foraging sites and lead highly organized raid columns to them. The path of the scout determines the path of the column. Through installation of artificial roads around M. analis nests we were able to influence the pathway choice of the raids. After road installation 59% of all recorded raids took place completely or partly on the road, instead of the direct, i.e. distance-optimized, path through grass from the nest to the termites. The raid velocity on the road was more than double the grass velocity, the detour thus saved 34.77±23.01% of the travel time compared to a hypothetical direct path. The pathway choice of the ants was similar to a mathematical model of least time allowing us to hypothesize the underlying mechanisms regulating the behavior. Our results highlight the importance of individual decision-making in the foraging behavior of ants and show a new procedure of pathway optimization. © 2018. Published by The Company of Biologists Ltd.

Surface Navigation Using Optimized Waypoints and Particle Swarm Optimization

NASA Technical Reports Server (NTRS)

Birge, Brian

2013-01-01

The design priority for manned space exploration missions is almost always placed on human safety. Proposed manned surface exploration tasks (lunar, asteroid sample returns, Mars) have the possibility of astronauts traveling several kilometers away from a home base. Deviations from preplanned paths are expected while exploring. In a time-critical emergency situation, there is a need to develop an optimal home base return path. The return path may or may not be similar to the outbound path, and what defines optimal may change with, and even within, each mission. A novel path planning algorithm and prototype program was developed using biologically inspired particle swarm optimization (PSO) that generates an optimal path of traversal while avoiding obstacles. Applications include emergency path planning on lunar, Martian, and/or asteroid surfaces, generating multiple scenarios for outbound missions, Earth-based search and rescue, as well as human manual traversal and/or path integration into robotic control systems. The strategy allows for a changing environment, and can be re-tasked at will and run in real-time situations. Given a random extraterrestrial planetary or small body surface position, the goal was to find the fastest (or shortest) path to an arbitrary position such as a safe zone or geographic objective, subject to possibly varying constraints. The problem requires a workable solution 100% of the time, though it does not require the absolute theoretical optimum. Obstacles should be avoided, but if they cannot be, then the algorithm needs to be smart enough to recognize this and deal with it. With some modifications, it works with non-stationary error topologies as well.

Finite-time convergent recurrent neural network with a hard-limiting activation function for constrained optimization with piecewise-linear objective functions.

PubMed

Liu, Qingshan; Wang, Jun

2011-04-01

This paper presents a one-layer recurrent neural network for solving a class of constrained nonsmooth optimization problems with piecewise-linear objective functions. The proposed neural network is guaranteed to be globally convergent in finite time to the optimal solutions under a mild condition on a derived lower bound of a single gain parameter in the model. The number of neurons in the neural network is the same as the number of decision variables of the optimization problem. Compared with existing neural networks for optimization, the proposed neural network has a couple of salient features such as finite-time convergence and a low model complexity. Specific models for two important special cases, namely, linear programming and nonsmooth optimization, are also presented. In addition, applications to the shortest path problem and constrained least absolute deviation problem are discussed with simulation results to demonstrate the effectiveness and characteristics of the proposed neural network.

A Routing Protocol for Packet Radio Networks

DTIC Science & Technology

1995-01-01

table of node K is a matrix containing, for each destination L and each neighbor of K (say M ), the distance to L ( NEOPRQ ) and the predecessor ( S OP Q...identifier T The distance to the destination ( N OP ) T The predecessor of the shortest path chosen toward L ( S OP ) T The successor ( U OP ) of the shortest...P and the predecessor is updated as S OP À ¾ S Q P . Thus, a node can determine whether or not an update received from M affects its other distance

Identifying New Candidate Genes and Chemicals Related to Prostate Cancer Using a Hybrid Network and Shortest Path Approach

PubMed Central

Wang, Meng; Wu, Kai; Lu, Changhong; Kong, Xiangyin

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

Layered data association using graph-theoretic formulation with applications to tennis ball tracking in monocular sequences.

PubMed

Yan, Fei; Christmas, William; Kittler, Josef

2008-10-01

In this paper, we propose a multilayered data association scheme with graph-theoretic formulation for tracking multiple objects that undergo switching dynamics in clutter. The proposed scheme takes as input object candidates detected in each frame. At the object candidate level, "tracklets'' are "grown'' from sets of candidates that have high probabilities of containing only true positives. At the tracklet level, a directed and weighted graph is constructed, where each node is a tracklet, and the edge weight between two nodes is defined according to the "compatibility'' of the two tracklets. The association problem is then formulated as an all-pairs shortest path (APSP) problem in this graph. Finally, at the path level, by analyzing the APSPs, all object trajectories are identified, and track initiation and track termination are automatically dealt with. By exploiting a special topological property of the graph, we have also developed a more efficient APSP algorithm than the general-purpose ones. The proposed data association scheme is applied to tennis sequences to track tennis balls. Experiments show that it works well on sequences where other data association methods perform poorly or fail completely.

Defect-free atomic array formation using the Hungarian matching algorithm

NASA Astrophysics Data System (ADS)

Lee, Woojun; Kim, Hyosub; Ahn, Jaewook

2017-05-01

Deterministic loading of single atoms onto arbitrary two-dimensional lattice points has recently been demonstrated, where by dynamically controlling the optical-dipole potential, atoms from a probabilistically loaded lattice were relocated to target lattice points to form a zero-entropy atomic lattice. In this atom rearrangement, how to pair atoms with the target sites is a combinatorial optimization problem: brute-force methods search all possible combinations so the process is slow, while heuristic methods are time efficient but optimal solutions are not guaranteed. Here, we use the Hungarian matching algorithm as a fast and rigorous alternative to this problem of defect-free atomic lattice formation. Our approach utilizes an optimization cost function that restricts collision-free guiding paths so that atom loss due to collision is minimized during rearrangement. Experiments were performed with cold rubidium atoms that were trapped and guided with holographically controlled optical-dipole traps. The result of atom relocation from a partially filled 7 ×7 lattice to a 3 ×3 target lattice strongly agrees with the theoretical analysis: using the Hungarian algorithm minimizes the collisional and trespassing paths and results in improved performance, with over 50% higher success probability than the heuristic shortest-move method.

On the strong metric dimension of generalized butterfly graph, starbarbell graph, and {C}_{m}\\odot {P}_{n} graph

NASA Astrophysics Data System (ADS)

Yunia Mayasari, Ratih; Atmojo Kusmayadi, Tri

2018-04-01

Let G be a connected graph with vertex set V(G) and edge set E(G). For every pair of vertices u,v\\in V(G), the interval I[u, v] between u and v to be the collection of all vertices that belong to some shortest u ‑ v path. A vertex s\\in V(G) strongly resolves two vertices u and v if u belongs to a shortest v ‑ s path or v belongs to a shortest u ‑ s path. A vertex set S of G is a strong resolving set of G if every two distinct vertices of G are strongly resolved by some vertex of S. The strong metric basis of G is a strong resolving set with minimal cardinality. The strong metric dimension sdim(G) of a graph G is defined as the cardinality of strong metric basis. In this paper we determine the strong metric dimension of a generalized butterfly graph, starbarbell graph, and {C}mȯ {P}n graph. We obtain the strong metric dimension of generalized butterfly graph is sdim(BFn ) = 2n ‑ 2. The strong metric dimension of starbarbell graph is sdim(S{B}{m1,{m}2,\\ldots,{m}n})={\\sum }i=1n({m}i-1)-1. The strong metric dimension of {C}mȯ {P}n graph are sdim({C}mȯ {P}n)=2m-1 for m > 3 and n = 2, and sdim({C}mȯ {P}n)=2m-2 for m > 3 and n > 2.

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.

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.

A Time-constrained Network Voronoi Construction and Accessibility Analysis in Location-based Service Technology

NASA Astrophysics Data System (ADS)

Yu, W.; Ai, T.

2014-11-01

Accessibility analysis usually requires special models of spatial location analysis based on some geometric constructions, such as Voronoi diagram (abbreviated to VD). There are many achievements in classic Voronoi model research, however suffering from the following limitations for location-based services (LBS) applications. (1) It is difficult to objectively reflect the actual service areas of facilities by using traditional planar VDs, because human activities in LBS are usually constrained only to the network portion of the planar space. (2) Although some researchers have adopted network distance to construct VDs, their approaches are used in a static environment, where unrealistic measures of shortest path distance based on assumptions about constant travel speeds through the network were often used. (3) Due to the computational complexity of the shortest-path distance calculating, previous researches tend to be very time consuming, especially for large datasets and if multiple runs are required. To solve the above problems, a novel algorithm is developed in this paper. We apply network-based quadrat system and 1-D sequential expansion to find the corresponding subnetwork for each focus. The idea is inspired by the natural phenomenon that water flow extends along certain linear channels until meets others or arrives at the end of route. In order to accommodate the changes in traffic conditions, the length of network-quadrat is set upon the traffic condition of the corresponding street. The method has the advantage over Dijkstra's algorithm in that the time cost is avoided, and replaced with a linear time operation.

Integration of geospatial multi-mode transportation Systems in Kuala Lumpur

NASA Astrophysics Data System (ADS)

Ismail, M. A.; Said, M. N.

2014-06-01

Public transportation serves people with mobility and accessibility to workplaces, health facilities, community resources, and recreational areas across the country. Development in the application of Geographical Information Systems (GIS) to transportation problems represents one of the most important areas of GIS-technology today. To show the importance of GIS network analysis, this paper highlights the determination of the optimal path between two or more destinations based on multi-mode concepts. The abstract connector is introduced in this research as an approach to integrate urban public transportation in Kuala Lumpur, Malaysia including facilities such as Light Rapid Transit (LRT), Keretapi Tanah Melayu (KTM) Komuter, Express Rail Link (ERL), KL Monorail, road driving as well as pedestrian modes into a single intelligent data model. To assist such analysis, ArcGIS's Network Analyst functions are used whereby the final output includes the total distance, total travelled time, directional maps produced to find the quickest, shortest paths, and closest facilities based on either time or distance impedance for multi-mode route analysis.

Distribution of shortest cycle lengths in random networks

NASA Astrophysics Data System (ADS)

Bonneau, Haggai; Hassid, Aviv; Biham, Ofer; Kühn, Reimer; Katzav, Eytan

2017-12-01

We present analytical results for the distribution of shortest cycle lengths (DSCL) in random networks. The approach is based on the relation between the DSCL and the distribution of shortest path lengths (DSPL). We apply this approach to configuration model networks, for which analytical results for the DSPL were obtained before. We first calculate the fraction of nodes in the network which reside on at least one cycle. Conditioning on being on a cycle, we provide the DSCL over ensembles of configuration model networks with degree distributions which follow a Poisson distribution (Erdős-Rényi network), degenerate distribution (random regular graph), and a power-law distribution (scale-free network). The mean and variance of the DSCL are calculated. The analytical results are found to be in very good agreement with the results of computer simulations.

Beyond Hosting Capacity: Using Shortest Path Methods to Minimize Upgrade Cost Pathways: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gensollen, Nicolas; Horowitz, Kelsey A; Palmintier, Bryan S

We present in this paper a graph based forwardlooking algorithm applied to distribution planning in the context of distributed PV penetration. We study the target hosting capacity (THC) problem where the objective is to find the cheapest sequence of system upgrades to reach a predefined hosting capacity target value. We show in this paper that commonly used short-term cost minimization approaches lead most of the time to suboptimal solutions. By comparing our method against such myopic techniques on real distribution systems, we show that our algorithm is able to reduce the overall integration costs by looking at future decisions. Becausemore » hosting capacity is hard to compute, this problem requires efficient methods to search the space. We demonstrate here that heuristics using domain specific knowledge can be efficiently used to improve the algorithm performance such that real distribution systems can be studied.« less

Multi-Objective Ant Colony Optimization Based on the Physarum-Inspired Mathematical Model for Bi-Objective Traveling Salesman Problems

PubMed Central

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

Multi-Objective Ant Colony Optimization Based on the Physarum-Inspired Mathematical Model for Bi-Objective Traveling Salesman Problems.

PubMed

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.

Paving the Way Towards Reactive Planar Spanner Construction in Wireless Networks

NASA Astrophysics Data System (ADS)

Frey, Hannes; Rührup, Stefan

A spanner is a subgraph of a given graph that supports the original graph's shortest path lengths up to a constant factor. Planar spanners and their distributed construction are of particular interest for geographic routing, which is an efficient localized routing scheme for wireless ad hoc and sensor networks. Planarity of the network graph is a key criterion for guaranteed delivery, while the spanner property supports efficiency in terms of path length. We consider the problem of reactive local spanner construction, where a node's local topology is determined on demand. Known message-efficient reactive planarization algorithms do not preserve the spanner property, while reactive spanner constructions with a low message overhead have not been described so far. We introduce the concept of direct planarization which may be an enabler of efficient reactive spanner construction. Given an edge, nodes check for all incident intersecting edges a certain geometric criterion and withdraw the edge if this criterion is not satisfied. We use this concept to derive a generic reactive topology control mechanism and consider two geometric criteria. Simulation results show that direct planarization increases the performance of localized geographic routing by providing shorter paths than existing reactive approaches.

Certification trails and software design for testability

NASA Technical Reports Server (NTRS)

Sullivan, Gregory F.; Wilson, Dwight S.; Masson, Gerald M.

1993-01-01

Design techniques which may be applied to make program testing easier were investigated. Methods for modifying a program to generate additional data which we refer to as a certification trail are presented. This additional data is designed to allow the program output to be checked more quickly and effectively. Certification trails were described primarily from a theoretical perspective. A comprehensive attempt to assess experimentally the performance and overall value of the certification trail method is reported. The method was applied to nine fundamental, well-known algorithms for the following problems: convex hull, sorting, huffman tree, shortest path, closest pair, line segment intersection, longest increasing subsequence, skyline, and voronoi diagram. Run-time performance data for each of these problems is given, and selected problems are described in more detail. Our results indicate that there are many cases in which certification trails allow for significantly faster overall program execution time than a 2-version programming approach, and also give further evidence of the breadth of applicability of this method.

Improved Results for Route Planning in Stochastic Transportation Networks

NASA Technical Reports Server (NTRS)

Boyan, Justin; Mitzenmacher, Michael

2000-01-01

In the bus network problem, the goal is to generate a plan for getting from point X to point Y within a city using buses in the smallest expected time. Because bus arrival times are not determined by a fixed schedule but instead may be random. the problem requires more than standard shortest path techniques. In recent work, Datar and Ranade provide algorithms in the case where bus arrivals are assumed to be independent and exponentially distributed. We offer solutions to two important generalizations of the problem, answering open questions posed by Datar and Ranade. First, we provide a polynomial time algorithm for a much wider class of arrival distributions, namely those with increasing failure rate. This class includes not only exponential distributions but also uniform, normal, and gamma distributions. Second, in the case where bus arrival times are independent and geometric discrete random variable,. we provide an algorithm for transportation networks of buses and trains, where trains run according to a fixed schedule.

Maze-solving by chemotaxis

NASA Astrophysics Data System (ADS)

Reynolds, A. M.

2010-06-01

Here, we report on numerical simulations showing that chemotaxis will take a body through a maze via the shortest possible route to the source of a chemoattractant. This is a robust finding that does not depend on the geometrical makeup of the maze. The predictions are supported by recent experimental studies which have shown that by moving down gradients in pH , a droplet of organic solvent can find the shortest of multiple possible paths through a maze to an acid-soaked exit. They are also consistent with numerical and experimental evidence that plant-parasitic nematodes take the shortest route through the labyrinth of air-filled pores within soil to preferred host plants that produce volatile chemoattractants. The predictions support the view that maze-solving is a robust property of chemotaxis and is not specific to particular kinds of maze or to the fractal structure of air-filled channels within soils.

Human performance on visually presented Traveling Salesman problems.

PubMed

Vickers, D; Butavicius, M; Lee, M; Medvedev, A

2001-01-01

Little research has been carried out on human performance in optimization problems, such as the Traveling Salesman problem (TSP). Studies by Polivanova (1974, Voprosy Psikhologii, 4, 41-51) and by MacGregor and Ormerod (1996, Perception & Psychophysics, 58, 527-539) suggest that: (1) the complexity of solutions to visually presented TSPs depends on the number of points on the convex hull; and (2) the perception of optimal structure is an innate tendency of the visual system, not subject to individual differences. Results are reported from two experiments. In the first, measures of the total length and completion speed of pathways, and a measure of path uncertainty were compared with optimal solutions produced by an elastic net algorithm and by several heuristic methods. Performance was also compared under instructions to draw the shortest or the most attractive pathway. In the second, various measures of performance were compared with scores on Raven's advanced progressive matrices (APM). The number of points on the convex hull did not determine the relative optimality of solutions, although both this factor and the total number of points influenced solution speed and path uncertainty. Subjects' solutions showed appreciable individual differences, which had a strong correlation with APM scores. The relation between perceptual organization and the process of solving visually presented TSPs is briefly discussed, as is the potential of optimization for providing a conceptual framework for the study of intelligence.

Current-flow efficiency of networks

NASA Astrophysics Data System (ADS)

Liu, Kai; Yan, Xiaoyong

2018-02-01

Many real-world networks, from infrastructure networks to social and communication networks, can be formulated as flow networks. How to realistically measure the transport efficiency of these networks is of fundamental importance. The shortest-path-based efficiency measurement has limitations, as it assumes that flow travels only along those shortest paths. Here, we propose a new metric named current-flow efficiency, in which we calculate the average reciprocal effective resistance between all pairs of nodes in the network. This metric takes the multipath effect into consideration and is more suitable for measuring the efficiency of many real-world flow equilibrium networks. Moreover, this metric can handle a disconnected graph and can thus be used to identify critical nodes and edges from the efficiency-loss perspective. We further analyze how the topological structure affects the current-flow efficiency of networks based on some model and real-world networks. Our results enable a better understanding of flow networks and shed light on the design and improvement of such networks with higher transport efficiency.

UNICOR: a species connectivity and corridor network simulator

Treesearch

E. L. Landguth; B. K. Hand; J. Glassy; S. A. Cushman; M. A. Sawaya

2012-01-01

We introduce UNIversal CORridor network simulator (UNICOR), a species connectivity and corridor identifi cation tool. UNICOR applies Dijkstra's shortest path algorithm to individual-based simulations. Outputs can be used to designate movement corridors, identify isolated populations, and prioritize conservation plans to promote species persistence. The key...

The traveling salesman problem as a new screening test in early Alzheimer's disease: an exploratory study. Visual problem-solving in AD.

PubMed

De Vreese, Luc Pieter; Pradelli, Samantha; Massini, Giulia; Buscema, Massimo; Savarè, Rita; Grossi, Enzo

2005-12-01

In the clinical setting, brief general mental status tests tend to detect early-stage Alzheimer's disease (AD) less well than more specific cognitive tests. Some preliminary information was collected on the diagnostic accuracy of the Traveling Salesman Problem (TSP) compared with the Mini-Mental State Examination (MMSE) in recognizing early AD from normal aging. Fifteen AD outpatients (mean +/- SD MMSE: 24.45 +/- 2.61) and 30 age- and education-matched controls were submitted in a single blind protocol to a paper-and-pencil visually-presented version of the TSP, containing a random array of 30 points (TSP30). The task consisted of drawing the shortest continuous path, passing through each point once and only once, and returning to the starting point. Path lengths for subjects' solutions were computed and compared with the optimal solution given by a specific evolutionary algorithm called GenD. TP30 discriminated significantly better between AD subjects and controls (ROC curve AUC = 0.976; 95% CI 0.94-1.01) compared with the MMSE corrected for age and education (ROC curve AUC = 0.877; 95% CI 0.74-1.005). A path length of 478.2354, taken as "cut-off point", classified correctly subjects with a sensitivity of 93.3% and a specificity of 99.3%, whereas a score corrected for age and education of 25.85 on the MMSE had a sensitivity of 73.3% and a specificity of 96.7%. The TSP seems to be particularly sensitive to early AD and independent of patient's age and educational level. The high diagnostic ability, simplicity, and independence of age and education make the TSP promising as a screening test for early AD.

Consistent and powerful non-Euclidean graph-based change-point test with applications to segmenting random interfered video data.

PubMed

Shi, Xiaoping; Wu, Yuehua; Rao, Calyampudi Radhakrishna

2018-06-05

The change-point detection has been carried out in terms of the Euclidean minimum spanning tree (MST) and shortest Hamiltonian path (SHP), with successful applications in the determination of authorship of a classic novel, the detection of change in a network over time, the detection of cell divisions, etc. However, these Euclidean graph-based tests may fail if a dataset contains random interferences. To solve this problem, we present a powerful non-Euclidean SHP-based test, which is consistent and distribution-free. The simulation shows that the test is more powerful than both Euclidean MST- and SHP-based tests and the non-Euclidean MST-based test. Its applicability in detecting both landing and departure times in video data of bees' flower visits is illustrated.

Biomimetics in Intelligent Sensor and Actuator Automation Systems

NASA Astrophysics Data System (ADS)

Bruckner, Dietmar; Dietrich, Dietmar; Zucker, Gerhard; Müller, Brit

Intelligent machines are really an old mankind's dream. With increasing technological development, the requirements for intelligent devices also increased. However, up to know, artificial intelligence (AI) lacks solutions to the demands of truly intelligent machines that have no problems to integrate themselves into daily human environments. Current hardware with a processing power of billions of operations per second (but without any model of human-like intelligence) could not substantially contribute to the intelligence of machines when compared with that of the early AI times. There are great results, of course. Machines are able to find the shortest path between far apart cities on the map; algorithms let you find information described only by few key words. But no machine is able to get us a cup of coffee from the kitchen yet.

A class-based link prediction using Distance Dependent Chinese Restaurant Process

NASA Astrophysics Data System (ADS)

Andalib, Azam; Babamir, Seyed Morteza

2016-08-01

One of the important tasks in relational data analysis is link prediction which has been successfully applied on many applications such as bioinformatics, information retrieval, etc. The link prediction is defined as predicting the existence or absence of edges between nodes of a network. In this paper, we propose a novel method for link prediction based on Distance Dependent Chinese Restaurant Process (DDCRP) model which enables us to utilize the information of the topological structure of the network such as shortest path and connectivity of the nodes. We also propose a new Gibbs sampling algorithm for computing the posterior distribution of the hidden variables based on the training data. Experimental results on three real-world datasets show the superiority of the proposed method over other probabilistic models for link prediction problem.

Applications of Temporal Graph Metrics to Real-World Networks

NASA Astrophysics Data System (ADS)

Tang, John; Leontiadis, Ilias; Scellato, Salvatore; Nicosia, Vincenzo; Mascolo, Cecilia; Musolesi, Mirco; Latora, Vito

Real world networks exhibit rich temporal information: friends are added and removed over time in online social networks; the seasons dictate the predator-prey relationship in food webs; and the propagation of a virus depends on the network of human contacts throughout the day. Recent studies have demonstrated that static network analysis is perhaps unsuitable in the study of real world network since static paths ignore time order, which, in turn, results in static shortest paths overestimating available links and underestimating their true corresponding lengths. Temporal extensions to centrality and efficiency metrics based on temporal shortest paths have also been proposed. Firstly, we analyse the roles of key individuals of a corporate network ranked according to temporal centrality within the context of a bankruptcy scandal; secondly, we present how such temporal metrics can be used to study the robustness of temporal networks in presence of random errors and intelligent attacks; thirdly, we study containment schemes for mobile phone malware which can spread via short range radio, similar to biological viruses; finally, we study how the temporal network structure of human interactions can be exploited to effectively immunise human populations. Through these applications we demonstrate that temporal metrics provide a more accurate and effective analysis of real-world networks compared to their static counterparts.

Identification of novel candidate drivers connecting different dysfunctional levels for lung adenocarcinoma using protein-protein interactions and a shortest path approach

NASA Astrophysics Data System (ADS)

Chen, Lei; Huang, Tao; Zhang, Yu-Hang; Jiang, Yang; Zheng, Mingyue; Cai, Yu-Dong

2016-07-01

Tumors are formed by the abnormal proliferation of somatic cells with disordered growth regulation under the influence of tumorigenic factors. Recently, the theory of “cancer drivers” connects tumor initiation with several specific mutations in the so-called cancer driver genes. According to the differentiation of four basic levels between tumor and adjacent normal tissues, the cancer drivers can be divided into the following: (1) Methylation level, (2) microRNA level, (3) mutation level, and (4) mRNA level. In this study, a computational method is proposed to identify novel lung adenocarcinoma drivers based on dysfunctional genes on the methylation, microRNA, mutation and mRNA levels. First, a large network was constructed using protein-protein interactions. Next, we searched all of the shortest paths connecting dysfunctional genes on different levels and extracted new candidate genes lying on these paths. Finally, the obtained candidate genes were filtered by a permutation test and an additional strict selection procedure involving a betweenness ratio and an interaction score. Several candidate genes remained, which are deemed to be related to two different levels of cancer. The analyses confirmed our assertions that some have the potential to contribute to the tumorigenesis process on multiple levels.

Real-time endovascular guidewire position simulation using shortest path algorithms.

PubMed

Schafer, Sebastian; Singh, Vikas; Noël, Peter B; Walczak, Alan M; Xu, Jinhui; Hoffmann, Kenneth R

2009-11-01

Treatment of vascular disease often involves endovascular interventions which use the vascular system for delivering treatment devices via a previously inserted guidewire to the diseased site. Previous studies show relative reproducibility of guidewire position after insertion, indicating that the guidewire position is constrained and could be represented by an energy minimization approach. Such representation would support the surgeon's decision process in guidewire selection. In this paper, we determine the guidewire position using a k-level graph based on 3D vessel information. Guidewire properties are incorporated into the graph as edge weights given by the local bending energy related to the local bending angle. The optimal path through this weighted directed graph is determined using a shortest path algorithm. Volumetric data of two different internal carotid artery phantoms (Ø 3.5-4.6 mm) was acquired. Two guidewires (Ø 0.33 mm) of different material properties (stainless steel, plastic-coated steel core) were inserted into the phantoms. The average RMS distance between actual and simulated guidewire positions varies from 0.9 mm (plastic coated) to 1.3 mm (stainless steel); the computation time to determine the position was <2s. The results indicate that the proposed technique yields reproducible and accurate guidewire positions within a short, clinically relevant time frame. These calculated positions may be useful in facilitating neurovascular interventions.

Achieving Crossed Strong Barrier Coverage in Wireless Sensor Network.

PubMed

Han, Ruisong; Yang, Wei; Zhang, Li

2018-02-10

Barrier coverage has been widely used to detect intrusions in wireless sensor networks (WSNs). It can fulfill the monitoring task while extending the lifetime of the network. Though barrier coverage in WSNs has been intensively studied in recent years, previous research failed to consider the problem of intrusion in transversal directions. If an intruder knows the deployment configuration of sensor nodes, then there is a high probability that it may traverse the whole target region from particular directions, without being detected. In this paper, we introduce the concept of crossed barrier coverage that can overcome this defect. We prove that the problem of finding the maximum number of crossed barriers is NP-hard and integer linear programming (ILP) is used to formulate the optimization problem. The branch-and-bound algorithm is adopted to determine the maximum number of crossed barriers. In addition, we also propose a multi-round shortest path algorithm (MSPA) to solve the optimization problem, which works heuristically to guarantee efficiency while maintaining near-optimal solutions. Several conventional algorithms for finding the maximum number of disjoint strong barriers are also modified to solve the crossed barrier problem and for the purpose of comparison. Extensive simulation studies demonstrate the effectiveness of MSPA.

A characterization of the coupled evolution of grain fabric and pore space using complex networks: Pore connectivity and optimized flows in the presence of shear bands

NASA Astrophysics Data System (ADS)

Russell, Scott; Walker, David M.; Tordesillas, Antoinette

2016-03-01

A framework for the multiscale characterization of the coupled evolution of the solid grain fabric and its associated pore space in dense granular media is developed. In this framework, a pseudo-dual graph transformation of the grain contact network produces a graph of pores which can be readily interpreted as a pore space network. Survivability, a new metric succinctly summarizing the connectivity of the solid grain and pore space networks, measures material robustness. The size distribution and the connectivity of pores can be characterized quantitatively through various network properties. Assortativity characterizes the pore space with respect to the parity of the number of particles enclosing the pore. Multiscale clusters of odd parity versus even parity contact cycles alternate spatially along the shear band: these represent, respectively, local jamming and unjamming regions that continually switch positions in time throughout the failure regime. Optimal paths, established using network shortest paths in favor of large pores, provide clues on preferential paths for interstitial matter transport. In systems with higher rolling resistance at contacts, less tortuous shortest paths thread through larger pores in shear bands. Notably the structural patterns uncovered in the pore space suggest that more robust models of interstitial pore flow through deforming granular systems require a proper consideration of the evolution of in situ shear band and fracture patterns - not just globally, but also inside these localized failure zones.

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.

Comparison of two paradigms for distributed shared memory

DOE Office of Scientific and Technical Information (OSTI.GOV)

Levelt, W.G.; Kaashoek, M.F.; Bal, H.E.

1990-08-01

The paper compares two paradigms for Distributed Shared Memory on loosely coupled computing systems: the shared data-object model as used in Orca, a programming language specially designed for loosely coupled computing systems and the Shared Virtual Memory model. For both paradigms the authors have implemented two systems, one using only point-to-point messages, the other using broadcasting as well. They briefly describe these two paradigms and their implementations. Then they compare their performance on four applications: the traveling salesman problem, alpha-beta search, matrix multiplication and the all pairs shortest paths problem. The measurements show that both paradigms can be used efficientlymore » for programming large-grain parallel applications. Significant speedups were obtained on all applications. The unstructured Shared Virtual Memory paradigm achieves the best absolute performance, although this is largely due to the preliminary nature of the Orca compiler used. The structured shared data-object model achieves the highest speedups and is much easier to program and to debug.« less

Optimization of municipal solid waste collection and transportation routes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Das, Swapan, E-mail: swapan2009sajal@gmail.com; Bhattacharyya, Bidyut Kr., E-mail: bidyut53@yahoo.co.in

2015-09-15

Graphical abstract: Display Omitted - Highlights: • Profitable integrated solid waste management system. • Optimal municipal waste collection scheme between the sources and waste collection centres. • Optimal path calculation between waste collection centres and transfer stations. • Optimal waste routing between the transfer stations and processing plants. - Abstract: Optimization of municipal solid waste (MSW) collection and transportation through source separation becomes one of the major concerns in the MSW management system design, due to the fact that the existing MSW management systems suffer by the high collection and transportation cost. Generally, in a city different waste sources scattermore » throughout the city in heterogeneous way that increase waste collection and transportation cost in the waste management system. Therefore, a shortest waste collection and transportation strategy can effectively reduce waste collection and transportation cost. In this paper, we propose an optimal MSW collection and transportation scheme that focus on the problem of minimizing the length of each waste collection and transportation route. We first formulize the MSW collection and transportation problem into a mixed integer program. Moreover, we propose a heuristic solution for the waste collection and transportation problem that can provide an optimal way for waste collection and transportation. Extensive simulations and real testbed results show that the proposed solution can significantly improve the MSW performance. Results show that the proposed scheme is able to reduce more than 30% of the total waste collection path length.« less

Stratum Weight Determination Using Shortest Path Algorithm

Treesearch

Susan L. King

2005-01-01

Forest Inventory and Analysis uses poststratification to calculate resource estimates. Each county has a different stratification, and the stratification may differ depending on the number of panels of data available. A ?5 by 5 sum? filter was passed over the reclassified forest/nonforest Multi-Resolution Landscape Characterization image used in Phase 1, generating an...

On Finding Shortest Paths on Convex Polyhedra.

DTIC Science & Technology

1985-05-01

versi ty of N laryhrid ml Collge :IJR-. M T) 207-12 COMPUTER SCIENCE TECHNICAL REPR SERWS .UE TE UNIVERSITY OF MARYLAND COLLEGE PARK, MARYLAND S 20742...planar layout can be physically interpreted as cutting the polyhedron along the ridges and unfolding the resulting object onto the plane. o% 4e.. ~16 A o

The Spider and the Fly

ERIC Educational Resources Information Center

Mellinger, Keith E.; Viglione, Raymond

2012-01-01

The Spider and the Fly puzzle, originally attributed to the great puzzler Henry Ernest Dudeney, and now over 100 years old, asks for the shortest path between two points on a particular square prism. We explore a generalization, find that the original solution only holds in certain cases, and suggest how this discovery might be used in the…

Shortest-path constraints for 3D multiobject semiautomatic segmentation via clustering and Graph Cut.

PubMed

Kéchichian, Razmig; Valette, Sébastien; Desvignes, Michel; Prost, Rémy

2013-11-01

We derive shortest-path constraints from graph models of structure adjacency relations and introduce them in a joint centroidal Voronoi image clustering and Graph Cut multiobject semiautomatic segmentation framework. The vicinity prior model thus defined is a piecewise-constant model incurring multiple levels of penalization capturing the spatial configuration of structures in multiobject segmentation. Qualitative and quantitative analyses and comparison with a Potts prior-based approach and our previous contribution on synthetic, simulated, and real medical images show that the vicinity prior allows for the correct segmentation of distinct structures having identical intensity profiles and improves the precision of segmentation boundary placement while being fairly robust to clustering resolution. The clustering approach we take to simplify images prior to segmentation strikes a good balance between boundary adaptivity and cluster compactness criteria furthermore allowing to control the trade-off. Compared with a direct application of segmentation on voxels, the clustering step improves the overall runtime and memory footprint of the segmentation process up to an order of magnitude without compromising the quality of the result.

Distributive routing and congestion control in wireless multihop ad hoc communication networks

NASA Astrophysics Data System (ADS)

Glauche, Ingmar; Krause, Wolfram; Sollacher, Rudolf; Greiner, Martin

2004-10-01

Due to their inherent complexity, engineered wireless multihop ad hoc communication networks represent a technological challenge. Having no mastering infrastructure the nodes have to selforganize themselves in such a way that for example network connectivity, good data traffic performance and robustness are guaranteed. In this contribution the focus is on routing and congestion control. First, random data traffic along shortest path routes is studied by simulations as well as theoretical modeling. Measures of congestion like end-to-end time delay and relaxation times are given. A scaling law of the average time delay with respect to network size is revealed and found to depend on the underlying network topology. In the second step, a distributive routing and congestion control is proposed. Each node locally propagates its routing cost estimates and information about its congestion state to its neighbors, which then update their respective cost estimates. This allows for a flexible adaptation of end-to-end routes to the overall congestion state of the network. Compared to shortest-path routing, the critical network load is significantly increased.

Identification of literary movements using complex networks to represent texts

NASA Astrophysics Data System (ADS)

Amancio, Diego Raphael; Oliveira, Osvaldo N., Jr.; da Fontoura Costa, Luciano

2012-04-01

The use of statistical methods to analyze large databases of text has been useful in unveiling patterns of human behavior and establishing historical links between cultures and languages. In this study, we identified literary movements by treating books published from 1590 to 1922 as complex networks, whose metrics were analyzed with multivariate techniques to generate six clusters of books. The latter correspond to time periods coinciding with relevant literary movements over the last five centuries. The most important factor contributing to the distinctions between different literary styles was the average shortest path length, in particular the asymmetry of its distribution. Furthermore, over time there has emerged a trend toward larger average shortest path lengths, which is correlated with increased syntactic complexity, and a more uniform use of the words reflected in a smaller power-law coefficient for the distribution of word frequency. Changes in literary style were also found to be driven by opposition to earlier writing styles, as revealed by the analysis performed with geometrical concepts. The approaches adopted here are generic and may be extended to analyze a number of features of languages and cultures.

Group Centric Networking: A new Approach for Wireless Multi-Hop Networking to Enable the Internet of Things

DTIC Science & Technology

2015-11-11

reliable data message delivery. The basic mechanism of link-based routing schemes is the broadcasting of a control message (called a “ hello ”) to all of its...short- est path route to a destination by using the set of ex- changed hello messages between users of the network. With sufficiently high frequency... hello messages are suc- cessfully exchanged across a high error link, and since this link is of longer distance, it gets used to build a shortest path

Group Centric Networking: A new Approach for Wireless Multi-Hop Networking to Enable the Internet of Things

DTIC Science & Technology

2015-09-07

reliable data message delivery. The basic mechanism of link-based routing schemes is the broadcasting of a control message (called a “ hello ”) to all of its...short- est path route to a destination by using the set of ex- changed hello messages between users of the network. With sufficiently high frequency... hello messages are suc- cessfully exchanged across a high error link, and since this link is of longer distance, it gets used to build a shortest path

The traveling salesman problem in surgery: economy of motion for the FLS Peg Transfer task.

PubMed

Falcone, John L; Chen, Xiaotian; Hamad, Giselle G

2013-05-01

In the Peg Transfer task in the Fundamentals of Laparoscopic Surgery (FLS) curriculum, six peg objects are sequentially transferred in a bimanual fashion using laparoscopic instruments across a pegboard and back. There are over 268 trillion ways of completing this task. In the setting of many possibilities, the traveling salesman problem is one where the objective is to solve for the shortest distance traveled through a fixed number of points. The goal of this study is to apply the traveling salesman problem to find the shortest two-dimensional path length for this task. A database platform was used with permutation application output to generate all of the single-direction solutions of the FLS Peg Transfer task. A brute-force search was performed using nested Boolean operators and database equations to calculate the overall two-dimensional distances for the efficient and inefficient solutions. The solutions were found by evaluating peg object transfer distances and distances between transfers for the nondominant and dominant hands. For the 518,400 unique single-direction permutations, the mean total two-dimensional peg object travel distance was 33.3 ± 1.4 cm. The range in distances was from 30.3 to 36.5 cm. There were 1,440 (0.28 %) of 518,400 efficient solutions with the minimized peg object travel distance of 30.3 cm. There were 8 (0.0015 %) of 518,400 solutions in the final solution set that minimized the distance of peg object transfer and minimized the distance traveled between peg transfers. Peg objects moved 12.7 cm (17.4 %) less in the efficient solutions compared to the inefficient solutions. The traveling salesman problem can be applied to find efficient solutions for surgical tasks. The eight solutions to the FLS Peg Transfer task are important for any examinee taking the FLS curriculum and for certification by the American Board of Surgery.

Feasible Path Generation Using Bezier Curves for Car-Like Vehicle

NASA Astrophysics Data System (ADS)

Latip, Nor Badariyah Abdul; Omar, Rosli

2017-08-01

When planning a collision-free path for an autonomous vehicle, the main criteria that have to be considered are the shortest distance, lower computation time and completeness, i.e. a path can be found if one exists. Besides that, a feasible path for the autonomous vehicle is also crucial to guarantee that the vehicle can reach the target destination considering its kinematic constraints such as non-holonomic and minimum turning radius. In order to address these constraints, Bezier curves is applied. In this paper, Bezier curves are modeled and simulated using Matlab software and the feasibility of the resulting path is analyzed. Bezier curve is derived from a piece-wise linear pre-planned path. It is found that the Bezier curves has the capability of making the planned path feasible and could be embedded in a path planning algorithm for an autonomous vehicle with kinematic constraints. It is concluded that the length of segments of the pre-planned path have to be greater than a nominal value, derived from the vehicle wheelbase, maximum steering angle and maximum speed to ensure the path for the autonomous car is feasible.

A multilevel probabilistic beam search algorithm for the shortest common supersequence problem.

PubMed

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.

Mandala Networks: ultra-small-world and highly sparse graphs

PubMed Central

Sampaio Filho, Cesar I. N.; Moreira, André A.; Andrade, Roberto F. S.; Herrmann, Hans J.; Andrade, José S.

2015-01-01

The increasing demands in security and reliability of infrastructures call for the optimal design of their embedded complex networks topologies. The following question then arises: what is the optimal layout to fulfill best all the demands? Here we present a general solution for this problem with scale-free networks, like the Internet and airline networks. Precisely, we disclose a way to systematically construct networks which are robust against random failures. Furthermore, as the size of the network increases, its shortest path becomes asymptotically invariant and the density of links goes to zero, making it ultra-small world and highly sparse, respectively. The first property is ideal for communication and navigation purposes, while the second is interesting economically. Finally, we show that some simple changes on the original network formulation can lead to an improved topology against malicious attacks. PMID:25765450

Families of Graph Algorithms: SSSP Case Study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kanewala Appuhamilage, Thejaka Amila Jay; Zalewski, Marcin J.; Lumsdaine, Andrew

2017-08-28

Single-Source Shortest Paths (SSSP) is a well-studied graph problem. Examples of SSSP algorithms include the original Dijkstra’s algorithm and the parallel Δ-stepping and KLA-SSSP algorithms. In this paper, we use a novel Abstract Graph Machine (AGM) model to show that all these algorithms share a common logic and differ from one another by the order in which they perform work. We use the AGM model to thoroughly analyze the family of algorithms that arises from the common logic. We start with the basic algorithm without any ordering (Chaotic), and then we derive the existing and new algorithms by methodically exploringmore » semantic and spatial ordering of work. Our experimental results show that new derived algorithms show better performance than the existing distributed memory parallel algorithms, especially at higher scales.« less

A Fast Numerical Method for Max-Convolution and the Application to Efficient Max-Product Inference in Bayesian Networks.

PubMed

Serang, Oliver

2015-08-01

Observations depending on sums of random variables are common throughout many fields; however, no efficient solution is currently known for performing max-product inference on these sums of general discrete distributions (max-product inference can be used to obtain maximum a posteriori estimates). The limiting step to max-product inference is the max-convolution problem (sometimes presented in log-transformed form and denoted as "infimal convolution," "min-convolution," or "convolution on the tropical semiring"), for which no O(k log(k)) method is currently known. Presented here is an O(k log(k)) numerical method for estimating the max-convolution of two nonnegative vectors (e.g., two probability mass functions), where k is the length of the larger vector. This numerical max-convolution method is then demonstrated by performing fast max-product inference on a convolution tree, a data structure for performing fast inference given information on the sum of n discrete random variables in O(nk log(nk)log(n)) steps (where each random variable has an arbitrary prior distribution on k contiguous possible states). The numerical max-convolution method can be applied to specialized classes of hidden Markov models to reduce the runtime of computing the Viterbi path from nk(2) to nk log(k), and has potential application to the all-pairs shortest paths problem.

Coordinating robot motion, sensing, and control in plans. LDRD project final report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xavier, P.G.; Brown, R.G.; Watterberg, P.A.

1997-08-01

The goal of this project was to develop a framework for robotic planning and execution that provides a continuum of adaptability with respect to model incompleteness, model error, and sensing error. For example, dividing robot motion into gross-motion planning, fine-motion planning, and sensor-augmented control had yielded productive research and solutions to individual problems. Unfortunately, these techniques could only be combined by hand with ad hoc methods and were restricted to systems where all kinematics are completely modeled in planning. The original intent was to develop methods for understanding and autonomously synthesizing plans that coordinate motion, sensing, and control. The projectmore » considered this problem from several perspectives. Results included (1) theoretical methods to combine and extend gross-motion and fine-motion planning; (2) preliminary work in flexible-object manipulation and an implementable algorithm for planning shortest paths through obstacles for the free-end of an anchored cable; (3) development and implementation of a fast swept-body distance algorithm; and (4) integration of Sandia`s C-Space Toolkit geometry engine and SANDROS motion planer and improvements, which yielded a system practical for everyday motion planning, with path-segment planning at interactive speeds. Results (3) and (4) have either led to follow-on work or are being used in current projects, and they believe that (2) will eventually be also.« less

Creative foraging: An experimental paradigm for studying exploration and discovery

PubMed Central

Mayo, Avraham E.; Mayo, Ruth; Rozenkrantz, Liron; Tendler, Avichai; Alon, Uri; Noy, Lior

2017-01-01

Creative exploration is central to science, art and cognitive development. However, research on creative exploration is limited by a lack of high-resolution automated paradigms. To address this, we present such an automated paradigm, the creative foraging game, in which people search for novel and valuable solutions in a large and well-defined space made of all possible shapes made of ten connected squares. Players discovered shape categories such as digits, letters, and airplanes as well as more abstract categories. They exploited each category, then dropped it to explore once again, and so on. Aligned with a prediction of optimal foraging theory (OFT), during exploration phases, people moved along meandering paths that are about three times longer than the shortest paths between shapes; when exploiting a category of related shapes, they moved along the shortest paths. The moment of discovery of a new category was usually done at a non-prototypical and ambiguous shape, which can serve as an experimental proxy for creative leaps. People showed individual differences in their search patterns, along a continuum between two strategies: a mercurial quick-to-discover/quick-to-drop strategy and a thorough slow-to-discover/slow-to-drop strategy. Contrary to optimal foraging theory, players leave exploitation to explore again far before categories are depleted. This paradigm opens the way for automated high-resolution study of creative exploration. PMID:28767668

Programs for road network planning.

Treesearch

Ward W. Carson; Dennis P. Dykstra

1978-01-01

This paper describes four computer programs developed to assist logging engineers to plan transportation in a forest. The objective of these programs, to be used together, is to find the shortest path through a transportation network from a point of departure to a destination. Three of the programs use the digitizing and plotting capabilities of a programable desk-top...

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…

On the Eikonal equation in the pedestrian flow problem

NASA Astrophysics Data System (ADS)

Felcman, J.; Kubera, P.

2017-07-01

We consider the Pedestrian Flow Equations (PFEs) as the coupled system formed by the Eikonal equation and the first order hyperbolic system with the source term. The hyperbolic system consists of the continuity equation and momentum equation of fluid dynamics. Specifying the social and pressure forces in the momentum equation we come to the assumption that each pedestrian is trying to move in a desired direction (e.g. to the exit in the panic situation) with a desired velocity, where his velocity and the direction of movement depend on the density of pedestrians in his neighborhood. In [1] we used the model, where the desired direction of movement is given by the solution of the Eikonal equation (more precisely by the gradient of the solution). Here we avoid the solution of the Eikonal equation, which is the novelty of the paper. Based on the fact that the solution of the Eikonal equation has the meaning of the shortest time to reach the exit, we define explicitly such a function in the framework of the Dijkstra's algorithm for the shortest path in the graph. This is done at the discrete level of the solution. As the graph we use the underlying triangulation, where the norm of each edge is density depending and has the dimension of the time. The numerical examples of the solution of the PFEs with and without the solution of the Eikonal equation are presented.

Design and Evaluation of a Dynamic Programming Flight Routing Algorithm Using the Convective Weather Avoidance Model

NASA Technical Reports Server (NTRS)

Ng, Hok K.; Grabbe, Shon; Mukherjee, Avijit

2010-01-01

The optimization of traffic flows in congested airspace with varying convective weather is a challenging problem. One approach is to generate shortest routes between origins and destinations while meeting airspace capacity constraint in the presence of uncertainties, such as weather and airspace demand. This study focuses on development of an optimal flight path search algorithm that optimizes national airspace system throughput and efficiency in the presence of uncertainties. The algorithm is based on dynamic programming and utilizes the predicted probability that an aircraft will deviate around convective weather. It is shown that the running time of the algorithm increases linearly with the total number of links between all stages. The optimal routes minimize a combination of fuel cost and expected cost of route deviation due to convective weather. They are considered as alternatives to the set of coded departure routes which are predefined by FAA to reroute pre-departure flights around weather or air traffic constraints. A formula, which calculates predicted probability of deviation from a given flight path, is also derived. The predicted probability of deviation is calculated for all path candidates. Routes with the best probability are selected as optimal. The predicted probability of deviation serves as a computable measure of reliability in pre-departure rerouting. The algorithm can also be extended to automatically adjust its design parameters to satisfy the desired level of reliability.

Temporal Constraint Reasoning With Preferences

NASA Technical Reports Server (NTRS)

Khatib, Lina; Morris, Paul; Morris, Robert; Rossi, Francesca

2001-01-01

A number of reasoning problems involving the manipulation of temporal information can naturally be viewed as implicitly inducing an ordering of potential local decisions involving time (specifically, associated with durations or orderings of events) on the basis of preferences. For example. a pair of events might be constrained to occur in a certain order, and, in addition. it might be preferable that the delay between them be as large, or as small, as possible. This paper explores problems in which a set of temporal constraints is specified, where each constraint is associated with preference criteria for making local decisions about the events involved in the constraint, and a reasoner must infer a complete solution to the problem such that, to the extent possible, these local preferences are met in the best way. A constraint framework for reasoning about time is generalized to allow for preferences over event distances and durations, and we study the complexity of solving problems in the resulting formalism. It is shown that while in general such problems are NP-hard, some restrictions on the shape of the preference functions, and on the structure of the preference set, can be enforced to achieve tractability. In these cases, a simple generalization of a single-source shortest path algorithm can be used to compute a globally preferred solution in polynomial time.

Hierarchical Motion Planning for Autonomous Aerial and Terrestrial Vehicles

NASA Astrophysics Data System (ADS)

Cowlagi, Raghvendra V.

Autonomous mobile robots---both aerial and terrestrial vehicles---have gained immense importance due to the broad spectrum of their potential military and civilian applications. One of the indispensable requirements for the autonomy of a mobile vehicle is the vehicle's capability of planning and executing its motion, that is, finding appropriate control inputs for the vehicle such that the resulting vehicle motion satisfies the requirements of the vehicular task. The motion planning and control problem is inherently complex because it involves two disparate sub-problems: (1) satisfaction of the vehicular task requirements, which requires tools from combinatorics and/or formal methods, and (2) design of the vehicle control laws, which requires tools from dynamical systems and control theory. Accordingly, this problem is usually decomposed and solved over two levels of hierarchy. The higher level, called the geometric path planning level, finds a geometric path that satisfies the vehicular task requirements, e.g., obstacle avoidance. The lower level, called the trajectory planning level, involves sufficient smoothening of this geometric path followed by a suitable time parametrization to obtain a reference trajectory for the vehicle. Although simple and efficient, such hierarchical decomposition suffers a serious drawback: the geometric path planner has no information of the kinematical and dynamical constraints of the vehicle. Consequently, the geometric planner may produce paths that the trajectory planner cannot transform into a feasible reference trajectory. Two main ideas appear in the literature to remedy this problem: (a) randomized sampling-based planning, which eliminates the geometric planner altogether by planning in the vehicle state space, and (b) geometric planning supported by feedback control laws. The former class of methods suffer from a lack of optimality of the resultant trajectory, while the latter class of methods makes a restrictive assumption concerning the vehicle kinematical model. We propose a hierarchical motion planning framework based on a novel mode of interaction between these two levels of planning. This interaction rests on the solution of a special shortest-path problem on graphs, namely, one using costs defined on multiple edge transitions in the path instead of the usual single edge transition costs. These costs are provided by a local trajectory generation algorithm, which we implement using model predictive control and the concept of effective target sets for simplifying the non-convex constraints involved in the problem. The proposed motion planner ensures "consistency" between the two levels of planning, i.e., a guarantee that the higher level geometric path is always associated with a kinematically and dynamically feasible trajectory. The main contributions of this thesis are: 1. A motion planning framework based on history-dependent costs (H-costs) in cell decomposition graphs for incorporating vehicle dynamical constraints: this framework offers distinct advantages in comparison with the competing approaches of discretization of the state space, of randomized sampling-based motion planning, and of local feedback-based, decoupled hierarchical motion planning, 2. An efficient and flexible algorithm for finding optimal H-cost paths, 3. A precise and general formulation of a local trajectory problem (the tile motion planning problem) that allows independent development of the discrete planner and the trajectory planner, while maintaining "compatibility" between the two planners, 4. A local trajectory generation algorithm using mpc, and the application of the concept of effective target sets for a significant simplification of the local trajectory generation problem, 5. The geometric analysis of curvature-bounded traversal of rectangular channels, leading to less conservative results in comparison with a result reported in the literature, and also to the efficient construction of effective target sets for the solution of the tile motion planning problem, 6. A wavelet-based multi-resolution path planning scheme, and a proof of completeness of the proposed scheme: such proofs are altogether absent from other works on multi-resolution path planning, 7. A technique for extracting all information about cells---namely, the locations, the sizes, and the associated image intensities---directly from the set of significant detail coefficients considered for path planning at a given iteration, and 8. The extension of the multi-resolution path planning scheme to include vehicle dynamical constraints using the aforementioned history-dependent costs approach. The future work includes an implementation of the proposed framework involving a discrete planner that solves classical planning problems more general than the single-query path planning problem considered thus far, and involving trajectory generation schemes for realistic vehicle dynamical models such as the bicycle model.

Interference Aware Routing Using Spatial Reuse in Wireless Sensor Networks

DTIC Science & Technology

2013-12-01

practice there is no optimal STDMA algorithm due to the computational complexity of the STDMA implementation; therefore, the common approach is to...Applications, Springer Berlin Heidelberg, pp. 653–657, 2001. [26] B. Korte and J. Vygen, “Shortest Paths,” Combinatorial Optimization Theory and...NAVAL POSTGRADUATE SCHOOL MONTEREY, CALIFORNIA THESIS Approved for public release; distribution is unlimited INTERFERENCE

Scopolamine effects on functional brain connectivity: a pharmacological model of Alzheimer's disease.

PubMed

Bajo, R; Pusil, S; López, M E; Canuet, L; Pereda, E; Osipova, D; Maestú, F; Pekkonen, E

2015-07-01

Scopolamine administration may be considered as a psychopharmacological model of Alzheimer's disease (AD). Here, we studied a group of healthy elderly under scopolamine to test whether it elicits similar changes in brain connectivity as those observed in AD, thereby verifying a possible model of AD impairment. We did it by testing healthy elderly subjects in two experimental conditions: glycopyrrolate (placebo) and scopolamine administration. We then analyzed magnetoencephalographic (MEG) data corresponding to both conditions in resting-state with eyes closed. This analysis was performed in source space by combining a nonlinear frequency band-specific measure of functional connectivity (phase locking value, PLV) with network analysis methods. Under scopolamine, functional connectivity between several brain areas was significantly reduced as compared to placebo, in most frequency bands analyzed. Besides, regarding the two complex network indices studied (clustering and shortest path length), clustering significantly decreased in the alpha band while shortest path length significantly increased also in alpha band both after scopolamine administration. Overall our findings indicate that both PLV and graph analysis are suitable tools to measure brain connectivity changes induced by scopolamine, which causes alterations in brain connectivity apparently similar to those reported in AD.

Scaling of average weighted shortest path and average receiving time on weighted expanded Koch networks

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.

Comparison of Perturbed Pathways in Two Different Cell Models for Parkinson's Disease with Structural Equation Model.

PubMed

Pepe, Daniele; Do, Jin Hwan

2015-12-16

Increasing evidence indicates that different morphological types of cell death coexist in the brain of patients with Parkinson's disease (PD), but the molecular explanation for this is still under investigation. In this study, we identified perturbed pathways in two different cell models for PD through the following procedures: (1) enrichment pathway analysis with differentially expressed genes and the Reactome pathway database, and (2) construction of the shortest path model for the enriched pathway and detection of significant shortest path model with fitting time-course microarray data of each PD cell model to structural equation model. Two PD cell models constructed by the same neurotoxin showed different perturbed pathways. That is, one showed perturbation of three Reactome pathways, including cellular senescence, chromatin modifying enzymes, and chromatin organization, while six modules within metabolism pathway represented perturbation in the other. This suggests that the activation of common upstream cell death pathways in PD may result in various down-stream processes, which might be associated with different morphological types of cell death. In addition, our results might provide molecular clues for coexistence of different morphological types of cell death in PD patients.

Efficiency and robustness of different bus network designs

NASA Astrophysics Data System (ADS)

Pang, John Zhen Fu; Bin Othman, Nasri; Ng, Keng Meng; Monterola, Christopher

2015-07-01

We compare the efficiencies and robustness of four transport networks that can be possibly formed as a result of deliberate city planning. The networks are constructed based on their spatial resemblance to the cities of Manhattan (lattice), Sudan (random), Beijing (single-blob) and Greater Cairo (dual-blob). For a given type, a genetic algorithm is employed to obtain an optimized set of the bus routes. We then simulate how commuter travels using Yen's algorithms for k shortest paths on an adjacency matrix. The cost of traveling such as walking between stations is captured by varying the weighted sums of matrices. We also consider the number of transfers a posteriori by looking at the computed shortest paths. With consideration to distances via radius of gyration, redundancies of travel and number of bus transfers, our simulations indicate that random and dual-blob are more efficient than single-blob and lattice networks. Moreover, dual-blob type is least robust when node removals are targeted but is most resilient when node failures are random. The work hopes to guide and provide technical perspectives on how geospatial distribution of a city limits the optimality of transport designs.

Discovery of new candidate genes related to brain development using protein interaction information.

PubMed

Chen, Lei; Chu, Chen; Kong, Xiangyin; Huang, Tao; Cai, Yu-Dong

2015-01-01

Human brain development is a dramatic process composed of a series of complex and fine-tuned spatiotemporal gene expressions. A good comprehension of this process can assist us in developing the potential of our brain. However, we have only limited knowledge about the genes and gene functions that are involved in this biological process. Therefore, a substantial demand remains to discover new brain development-related genes and identify their biological functions. In this study, we aimed to discover new brain-development related genes by building a computational method. We referred to a series of computational methods used to discover new disease-related genes and developed a similar method. In this method, the shortest path algorithm was executed on a weighted graph that was constructed using protein-protein interactions. New candidate genes fell on at least one of the shortest paths connecting two known genes that are related to brain development. A randomization test was then adopted to filter positive discoveries. Of the final identified genes, several have been reported to be associated with brain development, indicating the effectiveness of the method, whereas several of the others may have potential roles in brain development.

To Each According to its Degree: The Meritocracy and Topocracy of Embedded Markets

NASA Astrophysics Data System (ADS)

Borondo, J.; Borondo, F.; Rodriguez-Sickert, C.; Hidalgo, C. A.

2014-01-01

A system is said to be meritocratic if the compensation and power available to individuals is determined by their abilities and merits. A system is topocratic if the compensation and power available to an individual is determined primarily by her position in a network. Here we introduce a model that is perfectly meritocratic for fully connected networks but that becomes topocratic for sparse networks-like the ones in society. In the model, individuals produce and sell content, but also distribute the content produced by others when they belong to the shortest path connecting a buyer and a seller. The production and distribution of content defines two channels of compensation: a meritocratic channel, where individuals are compensated for the content they produce, and a topocratic channel, where individual compensation is based on the number of shortest paths that go through them in the network. We solve the model analytically and show that the distribution of payoffs is meritocratic only if the average degree of the nodes is larger than a root of the total number of nodes. We conclude that, in the light of this model, the sparsity and structure of networks represents a fundamental constraint to the meritocracy of societies.

To each according to its degree: the meritocracy and topocracy of embedded markets.

PubMed

Borondo, J; Borondo, F; Rodriguez-Sickert, C; Hidalgo, C A

2014-01-21

A system is said to be meritocratic if the compensation and power available to individuals is determined by their abilities and merits. A system is topocratic if the compensation and power available to an individual is determined primarily by her position in a network. Here we introduce a model that is perfectly meritocratic for fully connected networks but that becomes topocratic for sparse networks-like the ones in society. In the model, individuals produce and sell content, but also distribute the content produced by others when they belong to the shortest path connecting a buyer and a seller. The production and distribution of content defines two channels of compensation: a meritocratic channel, where individuals are compensated for the content they produce, and a topocratic channel, where individual compensation is based on the number of shortest paths that go through them in the network. We solve the model analytically and show that the distribution of payoffs is meritocratic only if the average degree of the nodes is larger than a root of the total number of nodes. We conclude that, in the light of this model, the sparsity and structure of networks represents a fundamental constraint to the meritocracy of societies.

Optimization of municipal solid waste collection and transportation routes.

PubMed

Das, Swapan; Bhattacharyya, Bidyut Kr

2015-09-01

Optimization of municipal solid waste (MSW) collection and transportation through source separation becomes one of the major concerns in the MSW management system design, due to the fact that the existing MSW management systems suffer by the high collection and transportation cost. Generally, in a city different waste sources scatter throughout the city in heterogeneous way that increase waste collection and transportation cost in the waste management system. Therefore, a shortest waste collection and transportation strategy can effectively reduce waste collection and transportation cost. In this paper, we propose an optimal MSW collection and transportation scheme that focus on the problem of minimizing the length of each waste collection and transportation route. We first formulize the MSW collection and transportation problem into a mixed integer program. Moreover, we propose a heuristic solution for the waste collection and transportation problem that can provide an optimal way for waste collection and transportation. Extensive simulations and real testbed results show that the proposed solution can significantly improve the MSW performance. Results show that the proposed scheme is able to reduce more than 30% of the total waste collection path length. Copyright © 2015 Elsevier Ltd. All rights reserved.

Computational Fact Checking from Knowledge Networks

PubMed Central

Ciampaglia, Giovanni Luca; Shiralkar, Prashant; Rocha, Luis M.; Bollen, Johan; Menczer, Filippo; Flammini, Alessandro

2015-01-01

Traditional fact checking by expert journalists cannot keep up with the enormous volume of information that is now generated online. Computational fact checking may significantly enhance our ability to evaluate the veracity of dubious information. Here we show that the complexities of human fact checking can be approximated quite well by finding the shortest path between concept nodes under properly defined semantic proximity metrics on knowledge graphs. Framed as a network problem this approach is feasible with efficient computational techniques. We evaluate this approach by examining tens of thousands of claims related to history, entertainment, geography, and biographical information using a public knowledge graph extracted from Wikipedia. Statements independently known to be true consistently receive higher support via our method than do false ones. These findings represent a significant step toward scalable computational fact-checking methods that may one day mitigate the spread of harmful misinformation. PMID:26083336

Longest jobs first algorithm in solving job shop scheduling using adaptive genetic algorithm (GA)

NASA Astrophysics Data System (ADS)

Alizadeh Sahzabi, Vahid; Karimi, Iman; Alizadeh Sahzabi, Navid; Mamaani Barnaghi, Peiman

2012-01-01

In this paper, genetic algorithm was used to solve job shop scheduling problems. One example discussed in JSSP (Job Shop Scheduling Problem) and I described how we can solve such these problems by genetic algorithm. The goal in JSSP is to gain the shortest process time. Furthermore I proposed a method to obtain best performance on performing all jobs in shortest time. The method mainly, is according to Genetic algorithm (GA) and crossing over between parents always follows the rule which the longest process is at the first in the job queue. In the other word chromosomes is suggested to sorts based on the longest processes to shortest i.e. "longest job first" says firstly look which machine contains most processing time during its performing all its jobs and that is the bottleneck. Secondly, start sort those jobs which are belonging to that specific machine descending. Based on the achieved results," longest jobs first" is the optimized status in job shop scheduling problems. In our results the accuracy would grow up to 94.7% for total processing time and the method improved 4% the accuracy of performing all jobs in the presented example.

Improved Efficient Routing Strategy on Scale-Free Networks

NASA Astrophysics Data System (ADS)

Jiang, Zhong-Yuan; Liang, Man-Gui

Since the betweenness of nodes in complex networks can theoretically represent the traffic load of nodes under the currently used routing strategy, we propose an improved efficient (IE) routing strategy to enhance to the network traffic capacity based on the betweenness centrality. Any node with the highest betweenness is susceptible to traffic congestion. An efficient way to improve the network traffic capacity is to redistribute the heavy traffic load from these central nodes to non-central nodes, so in this paper, we firstly give a path cost function by considering the sum of node betweenness with a tunable parameter β along the actual path. Then, by minimizing the path cost, our IE routing strategy achieved obvious improvement on the network transport efficiency. Simulations on scale-free Barabási-Albert (BA) networks confirmed the effectiveness of our strategy, when compared with the efficient routing (ER) and the shortest path (SP) routing.

A mathematical model for adaptive transport network in path finding by true slime mold.

PubMed

Tero, Atsushi; Kobayashi, Ryo; Nakagaki, Toshiyuki

2007-02-21

We describe here a mathematical model of the adaptive dynamics of a transport network of the true slime mold Physarum polycephalum, an amoeboid organism that exhibits path-finding behavior in a maze. This organism possesses a network of tubular elements, by means of which nutrients and signals circulate through the plasmodium. When the organism is put in a maze, the network changes its shape to connect two exits by the shortest path. This process of path-finding is attributed to an underlying physiological mechanism: a tube thickens as the flux through it increases. The experimental evidence for this is, however, only qualitative. We constructed a mathematical model of the general form of the tube dynamics. Our model contains a key parameter corresponding to the extent of the feedback regulation between the thickness of a tube and the flux through it. We demonstrate the dependence of the behavior of the model on this parameter.

Cell transmission model of dynamic assignment for urban rail transit networks.

PubMed

Xu, Guangming; Zhao, Shuo; Shi, Feng; Zhang, Feilian

2017-01-01

For urban rail transit network, the space-time flow distribution can play an important role in evaluating and optimizing the space-time resource allocation. For obtaining the space-time flow distribution without the restriction of schedules, a dynamic assignment problem is proposed based on the concept of continuous transmission. To solve the dynamic assignment problem, the cell transmission model is built for urban rail transit networks. The priority principle, queuing process, capacity constraints and congestion effects are considered in the cell transmission mechanism. Then an efficient method is designed to solve the shortest path for an urban rail network, which decreases the computing cost for solving the cell transmission model. The instantaneous dynamic user optimal state can be reached with the method of successive average. Many evaluation indexes of passenger flow can be generated, to provide effective support for the optimization of train schedules and the capacity evaluation for urban rail transit network. Finally, the model and its potential application are demonstrated via two numerical experiments using a small-scale network and the Beijing Metro network.

Image flows and one-liner graphical image representation.

PubMed

Makhervaks, Vadim; Barequet, Gill; Bruckstein, Alfred

2002-10-01

This paper introduces a novel graphical image representation consisting of a single curve-the one-liner. The first step of the algorithm involves the detection and ranking of image edges. A new edge exploration technique is used to perform both tasks simultaneously. This process is based on image flows. It uses a gradient vector field and a new operator to explore image edges. Estimation of the derivatives of the image is performed by using local Taylor expansions in conjunction with a weighted least-squares method. This process finds all the possible image edges without any pruning, and collects information that allows the edges found to be prioritized. This enables the most important edges to be selected to form a skeleton of the representation sought. The next step connects the selected edges into one continuous curve-the one-liner. It orders the selected edges and determines the curves connecting them. These two problems are solved separately. Since the abstract graph setting of the first problem is NP-complete, we reduce it to a variant of the traveling salesman problem and compute an approximate solution to it. We solve the second problem by using Dijkstra's shortest-path algorithm. The full software implementation for the entire one-liner determination process is available.

Advisory Algorithm for Scheduling Open Sectors, Operating Positions, and Workstations

NASA Technical Reports Server (NTRS)

Bloem, Michael; Drew, Michael; Lai, Chok Fung; Bilimoria, Karl D.

2012-01-01

Air traffic controller supervisors configure available sector, operating position, and work-station resources to safely and efficiently control air traffic in a region of airspace. In this paper, an algorithm for assisting supervisors with this task is described and demonstrated on two sample problem instances. The algorithm produces configuration schedule advisories that minimize a cost. The cost is a weighted sum of two competing costs: one penalizing mismatches between configurations and predicted air traffic demand and another penalizing the effort associated with changing configurations. The problem considered by the algorithm is a shortest path problem that is solved with a dynamic programming value iteration algorithm. The cost function contains numerous parameters. Default values for most of these are suggested based on descriptions of air traffic control procedures and subject-matter expert feedback. The parameter determining the relative importance of the two competing costs is tuned by comparing historical configurations with corresponding algorithm advisories. Two sample problem instances for which appropriate configuration advisories are obvious were designed to illustrate characteristics of the algorithm. Results demonstrate how the algorithm suggests advisories that appropriately utilize changes in airspace configurations and changes in the number of operating positions allocated to each open sector. The results also demonstrate how the advisories suggest appropriate times for configuration changes.

Interactogeneous: Disease Gene Prioritization Using Heterogeneous Networks and Full Topology Scores

PubMed Central

Gonçalves, Joana P.; Francisco, Alexandre P.; Moreau, Yves; Madeira, Sara C.

2012-01-01

Disease gene prioritization aims to suggest potential implications of genes in disease susceptibility. Often accomplished in a guilt-by-association scheme, promising candidates are sorted according to their relatedness to known disease genes. Network-based methods have been successfully exploiting this concept by capturing the interaction of genes or proteins into a score. Nonetheless, most current approaches yield at least some of the following limitations: (1) networks comprise only curated physical interactions leading to poor genome coverage and density, and bias toward a particular source; (2) scores focus on adjacencies (direct links) or the most direct paths (shortest paths) within a constrained neighborhood around the disease genes, ignoring potentially informative indirect paths; (3) global clustering is widely applied to partition the network in an unsupervised manner, attributing little importance to prior knowledge; (4) confidence weights and their contribution to edge differentiation and ranking reliability are often disregarded. We hypothesize that network-based prioritization related to local clustering on graphs and considering full topology of weighted gene association networks integrating heterogeneous sources should overcome the above challenges. We term such a strategy Interactogeneous. We conducted cross-validation tests to assess the impact of network sources, alternative path inclusion and confidence weights on the prioritization of putative genes for 29 diseases. Heat diffusion ranking proved the best prioritization method overall, increasing the gap to neighborhood and shortest paths scores mostly on single source networks. Heterogeneous associations consistently delivered superior performance over single source data across the majority of methods. Results on the contribution of confidence weights were inconclusive. Finally, the best Interactogeneous strategy, heat diffusion ranking and associations from the STRING database, was used to prioritize genes for Parkinson’s disease. This method effectively recovered known genes and uncovered interesting candidates which could be linked to pathogenic mechanisms of the disease. PMID:23185389

Use of linkage mapping and centrality analysis across habitat gradients to conserve connectivity of gray wolf populations in western North America.

PubMed

Carroll, Carlos; McRae, Brad H; Brookes, Allen

2012-02-01

Centrality metrics evaluate paths between all possible pairwise combinations of sites on a landscape to rank the contribution of each site to facilitating ecological flows across the network of sites. Computational advances now allow application of centrality metrics to landscapes represented as continuous gradients of habitat quality. This avoids the binary classification of landscapes into patch and matrix required by patch-based graph analyses of connectivity. It also avoids the focus on delineating paths between individual pairs of core areas characteristic of most corridor- or linkage-mapping methods of connectivity analysis. Conservation of regional habitat connectivity has the potential to facilitate recovery of the gray wolf (Canis lupus), a species currently recolonizing portions of its historic range in the western United States. We applied 3 contrasting linkage-mapping methods (shortest path, current flow, and minimum-cost-maximum-flow) to spatial data representing wolf habitat to analyze connectivity between wolf populations in central Idaho and Yellowstone National Park (Wyoming). We then applied 3 analogous betweenness centrality metrics to analyze connectivity of wolf habitat throughout the northwestern United States and southwestern Canada to determine where it might be possible to facilitate range expansion and interpopulation dispersal. We developed software to facilitate application of centrality metrics. Shortest-path betweenness centrality identified a minimal network of linkages analogous to those identified by least-cost-path corridor mapping. Current flow and minimum-cost-maximum-flow betweenness centrality identified diffuse networks that included alternative linkages, which will allow greater flexibility in planning. Minimum-cost-maximum-flow betweenness centrality, by integrating both land cost and habitat capacity, allows connectivity to be considered within planning processes that seek to maximize species protection at minimum cost. Centrality analysis is relevant to conservation and landscape genetics at a range of spatial extents, but it may be most broadly applicable within single- and multispecies planning efforts to conserve regional habitat connectivity. ©2011 Society for Conservation Biology.

An improved hierarchical A * algorithm in the optimization of parking lots

NASA Astrophysics Data System (ADS)

Wang, Yong; Wu, Junjuan; Wang, Ying

2017-08-01

In the parking lot parking path optimization, the traditional evaluation index is the shortest distance as the best index and it does not consider the actual road conditions. Now, the introduction of a more practical evaluation index can not only simplify the hardware design of the boot system but also save the software overhead. Firstly, we establish the parking lot network graph RPCDV mathematical model and all nodes in the network is divided into two layers which were constructed using different evaluation function base on the improved hierarchical A * algorithm which improves the time optimal path search efficiency and search precision of the evaluation index. The final results show that for different sections of the program attribute parameter algorithm always faster the time to find the optimal path.

Highly Asynchronous VisitOr Queue Graph Toolkit

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pearce, R.

2012-10-01

HAVOQGT is a C++ framework that can be used to create highly parallel graph traversal algorithms. The framework stores the graph and algorithmic data structures on external memory that is typically mapped to high performance locally attached NAND FLASH arrays. The framework supports a vertex-centered visitor programming model. The frameworkd has been used to implement breadth first search, connected components, and single source shortest path.

Evaluating CoLiDeS + Pic: The Role of Relevance of Pictures in User Navigation Behaviour

ERIC Educational Resources Information Center

Karanam, Saraschandra; van Oostendorp, Herre; Indurkhya, Bipin

2012-01-01

CoLiDeS + Pic is a cognitive model of web-navigation that incorporates semantic information from pictures into CoLiDeS. In our earlier research, we have demonstrated that by incorporating semantic information from pictures, CoLiDeS + Pic can predict the hyperlinks on the shortest path more frequently, and also with greater information scent,…

Optimal Control of Fully Routed Air Traffic in the Presence of Uncertainty and Kinodynamic Constraints

DTIC Science & Technology

2014-09-18

Operations and Developing Issues . . . . . . . . . . . . . . . . . . 6 2.1.2 Next-Generation Air Transportation System (NextGen...Air Traffic Management ESP Euclidean Shortest Path FAA Federal Aviation Administration FCFS First-Come-First-Served HCS Hybrid Control System KKT...Karush-Kuhn-Tucker LGR Legendre-Gauss-Radau MLD Minimum Lateral Distance NAS National Airspace System NASA National Aeronautics and Space Administration

Purpose-Driven Communities in Multiplex Networks: Thresholding User-Engaged Layer Aggregation

DTIC Science & Technology

2016-06-01

dark networks is a non-trivial yet useful task. Because terrorists work hard to hide their relationships/network, analysts have an incomplete picture...them identify meaningful terrorist communities. This thesis introduces a general-purpose algorithm for community detection in multiplex dark networks...aggregation, dark networks, conductance, cluster adequacy, mod- ularity, Louvain method, shortest path interdiction 15. NUMBER OF PAGES 155 16. PRICE CODE

Short superstrings and the structure of overlapping strings.

PubMed

Armen, C; Stein, C

1995-01-01

Given a collection of strings S = [s1,...,sn] over an alphabet sigma, a superstring alpha of S is a string containing each si as a substring, that is, for each i, 1 < or = i < or = n, alpha contains a block of magnitude of si consecutive characters that match si exactly. The shortest superstring problem is the problem of finding a superstring alpha of minimum length. The shortest superstring problem has applications in both computational biology and data compression. The shortest superstring problem is NP-hard (Gallant et al., 1980); in fact, it was recently shown to be MAX SNP-hard (Blum et al., 1994). Given the importance of the applications, several heuristics and approximation algorithms have been proposed. Constant factor approximation algorithms have been given in Blum et al. (1994) (factor of 3), Teng and Yao (1993) (factor of 2 8/9), Czumaj et al. (1994) (factor of 2 5/6), and Kosaraju et al. (1994) (factor of 2 50/63). Informally, the key to any algorithm for the shortest superstring problem is to identify sets of strings with large amounts of similarity, or overlap. Although the previous algorithms and their analyses have grown increasingly sophisticated, they reveal remarkably little about the structure of strings with large amounts of overlap. In this sense, they are solving a more general problem than the one at hand. In this paper, we study the structure of strings with large amounts of overlap and use our understanding to give an algorithm that finds a superstring whose length is no more than 2 3/4 times that of the optimal superstring. Our algorithm runs in O(magnitude of S + n3) time, which matches that of previous algorithms. We prove several interesting properties about short periodic strings, allowing us to answer questions of the following form: Given a string with some periodic structure, characterize all the possible periodic strings that can have a large amount of overlap with the first string.

Autonomous Navigation by a Mobile Robot

NASA Technical Reports Server (NTRS)

Huntsberger, Terrance; Aghazarian, Hrand

2005-01-01

ROAMAN is a computer program for autonomous navigation of a mobile robot on a long (as much as hundreds of meters) traversal of terrain. Developed for use aboard a robotic vehicle (rover) exploring the surface of a remote planet, ROAMAN could also be adapted to similar use on terrestrial mobile robots. ROAMAN implements a combination of algorithms for (1) long-range path planning based on images acquired by mast-mounted, wide-baseline stereoscopic cameras, and (2) local path planning based on images acquired by body-mounted, narrow-baseline stereoscopic cameras. The long-range path-planning algorithm autonomously generates a series of waypoints that are passed to the local path-planning algorithm, which plans obstacle-avoiding legs between the waypoints. Both the long- and short-range algorithms use an occupancy-grid representation in computations to detect obstacles and plan paths. Maps that are maintained by the long- and short-range portions of the software are not shared because substantial localization errors can accumulate during any long traverse. ROAMAN is not guaranteed to generate an optimal shortest path, but does maintain the safety of the rover.

Understanding disordered systems through numerical simulation and algorithm development

NASA Astrophysics Data System (ADS)

Sweeney, Sean Michael

Disordered systems arise in many physical contexts. Not all matter is uniform, and impurities or heterogeneities can be modeled by fixed random disorder. Numerous complex networks also possess fixed disorder, leading to applications in transportation systems, telecommunications, social networks, and epidemic modeling, to name a few. Due to their random nature and power law critical behavior, disordered systems are difficult to study analytically. Numerical simulation can help overcome this hurdle by allowing for the rapid computation of system states. In order to get precise statistics and extrapolate to the thermodynamic limit, large systems must be studied over many realizations. Thus, innovative algorithm development is essential in order reduce memory or running time requirements of simulations. This thesis presents a review of disordered systems, as well as a thorough study of two particular systems through numerical simulation, algorithm development and optimization, and careful statistical analysis of scaling properties. Chapter 1 provides a thorough overview of disordered systems, the history of their study in the physics community, and the development of techniques used to study them. Topics of quenched disorder, phase transitions, the renormalization group, criticality, and scale invariance are discussed. Several prominent models of disordered systems are also explained. Lastly, analysis techniques used in studying disordered systems are covered. In Chapter 2, minimal spanning trees on critical percolation clusters are studied, motivated in part by an analytic perturbation expansion by Jackson and Read that I check against numerical calculations. This system has a direct mapping to the ground state of the strongly disordered spin glass. We compute the path length fractal dimension of these trees in dimensions d = {2, 3, 4, 5} and find our results to be compatible with the analytic results suggested by Jackson and Read. In Chapter 3, the random bond Ising ferromagnet is studied, which is especially useful since it serves as a prototype for more complicated disordered systems such as the random field Ising model and spin glasses. We investigate the effect that changing boundary spins has on the locations of domain walls in the interior of the random ferromagnet system. We provide an analytic proof that ground state domain walls in the two dimensional system are decomposable, and we map these domain walls to a shortest paths problem. By implementing a multiple-source shortest paths algorithm developed by Philip Klein, we are able to efficiently probe domain wall locations for all possible configurations of boundary spins. We consider lattices with uncorrelated dis- order, as well as disorder that is spatially correlated according to a power law. We present numerical results for the scaling exponent governing the probability that a domain wall can be induced that passes through a particular location in the system's interior, and we compare these results to previous results on the directed polymer problem.

Research on Taxiway Path Optimization Based on Conflict Detection

PubMed Central

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.

PubMed

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.

Evidence of Probabilistic Behaviour in Protein Interaction Networks

DTIC Science & Technology

2008-01-31

Evidence of degree-weighted connectivity in nine PPI networks. a, Homo sapiens (human); b, Drosophila melanogaster (fruit fly); c-e, Saccharomyces...illustrates maps for the networks of Homo sapiens and Dro- sophila melanogaster, while maps for the remaining net- works are provided in Additional file 2. As...protein-protein interaction networks. a, Homo sapiens ; b, Drosophila melanogaster. Distances shown as average shortest path lengths L(k1, k2) between

Modeling Network Interdiction Tasks

DTIC Science & Technology

2015-09-17

they may attack the flaw to cause widespread chaos. Attacks such as these are considered a form of network interdiction. Assessing the networks over...and forms a foundation for the techniques of the measures and models approaches of the research framework, which is depicted in Figure 2. The...ensures the distance of the shortest (i, j) path is computed. This insight is attributed to Warshall [62]. The algorithm’s present form is attributed

Machine learning framework for analysis of transport through complex networks in porous, granular media: A focus on permeability

NASA Astrophysics Data System (ADS)

van der Linden, Joost H.; Narsilio, Guillermo A.; Tordesillas, Antoinette

2016-08-01

We present a data-driven framework to study the relationship between fluid flow at the macroscale and the internal pore structure, across the micro- and mesoscales, in porous, granular media. Sphere packings with varying particle size distribution and confining pressure are generated using the discrete element method. For each sample, a finite element analysis of the fluid flow is performed to compute the permeability. We construct a pore network and a particle contact network to quantify the connectivity of the pores and particles across the mesoscopic spatial scales. Machine learning techniques for feature selection are employed to identify sets of microstructural properties and multiscale complex network features that optimally characterize permeability. We find a linear correlation (in log-log scale) between permeability and the average closeness centrality of the weighted pore network. With the pore network links weighted by the local conductance, the average closeness centrality represents a multiscale measure of efficiency of flow through the pore network in terms of the mean geodesic distance (or shortest path) between all pore bodies in the pore network. Specifically, this study objectively quantifies a hypothesized link between high permeability and efficient shortest paths that thread through relatively large pore bodies connected to each other by high conductance pore throats, embodying connectivity and pore structure.

The drug target genes show higher evolutionary conservation than non-target genes.

PubMed

Lv, Wenhua; Xu, Yongdeng; Guo, Yiying; Yu, Ziqi; Feng, Guanglong; Liu, Panpan; Luan, Meiwei; Zhu, Hongjie; Liu, Guiyou; Zhang, Mingming; Lv, Hongchao; Duan, Lian; Shang, Zhenwei; Li, Jin; Jiang, Yongshuai; Zhang, Ruijie

2016-01-26

Although evidence indicates that drug target genes share some common evolutionary features, there have been few studies analyzing evolutionary features of drug targets from an overall level. Therefore, we conducted an analysis which aimed to investigate the evolutionary characteristics of drug target genes. We compared the evolutionary conservation between human drug target genes and non-target genes by combining both the evolutionary features and network topological properties in human protein-protein interaction network. The evolution rate, conservation score and the percentage of orthologous genes of 21 species were included in our study. Meanwhile, four topological features including the average shortest path length, betweenness centrality, clustering coefficient and degree were considered for comparison analysis. Then we got four results as following: compared with non-drug target genes, 1) drug target genes had lower evolutionary rates; 2) drug target genes had higher conservation scores; 3) drug target genes had higher percentages of orthologous genes and 4) drug target genes had a tighter network structure including higher degrees, betweenness centrality, clustering coefficients and lower average shortest path lengths. These results demonstrate that drug target genes are more evolutionarily conserved than non-drug target genes. We hope that our study will provide valuable information for other researchers who are interested in evolutionary conservation of drug targets.

Indoor Navigation Design Integrated with Smart Phones and Rfid Devices

NASA Astrophysics Data System (ADS)

Ortakci, Y.; Demiral, E.; Atila, U.; Karas, I. R.

2015-10-01

High rise, complex and huge buildings in the cities are almost like a small city with their tens of floors, hundreds of corridors and rooms and passages. Due to size and complexity of these buildings, people need guidance to find their way to the destination in these buildings. In this study, a mobile application is developed to visualize pedestrian's indoor position as 3D in their smartphone and RFID Technology is used to detect the position of pedestrian. While the pedestrian is walking on his/her way on the route, smartphone will guide the pedestrian by displaying the photos of indoor environment on the route. Along the tour, an RFID (Radio-Frequency Identification) device is integrated to the system. The pedestrian will carry the RFID device during his/her tour in the building. The RFID device will send the position data to the server directly in every two seconds periodically. On the other side, the pedestrian will just select the destination point in the mobile application on smartphone and sent the destination point to the server. The shortest path from the pedestrian position to the destination point is found out by the script on the server. This script also sends the environment photo of the first node on the acquired shortest path to the client as an indoor navigation module.

Rapid geodesic mapping of brain functional connectivity: implementation of a dedicated co-processor in a field-programmable gate array (FPGA) and application to resting state functional MRI.

PubMed

Minati, Ludovico; Cercignani, Mara; Chan, Dennis

2013-10-01

Graph theory-based analyses of brain network topology can be used to model the spatiotemporal correlations in neural activity detected through fMRI, and such approaches have wide-ranging potential, from detection of alterations in preclinical Alzheimer's disease through to command identification in brain-machine interfaces. However, due to prohibitive computational costs, graph-based analyses to date have principally focused on measuring connection density rather than mapping the topological architecture in full by exhaustive shortest-path determination. This paper outlines a solution to this problem through parallel implementation of Dijkstra's algorithm in programmable logic. The processor design is optimized for large, sparse graphs and provided in full as synthesizable VHDL code. An acceleration factor between 15 and 18 is obtained on a representative resting-state fMRI dataset, and maps of Euclidean path length reveal the anticipated heterogeneous cortical involvement in long-range integrative processing. These results enable high-resolution geodesic connectivity mapping for resting-state fMRI in patient populations and real-time geodesic mapping to support identification of imagined actions for fMRI-based brain-machine interfaces. Copyright © 2013 IPEM. Published by Elsevier Ltd. All rights reserved.

Towards a Multiscale Approach to Cybersecurity Modeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hogan, Emilie A.; Hui, Peter SY; Choudhury, Sutanay

2013-11-12

We propose a multiscale approach to modeling cyber networks, with the goal of capturing a view of the network and overall situational awareness with respect to a few key properties--- connectivity, distance, and centrality--- for a system under an active attack. We focus on theoretical and algorithmic foundations of multiscale graphs, coming from an algorithmic perspective, with the goal of modeling cyber system defense as a specific use case scenario. We first define a notion of \\emph{multiscale} graphs, in contrast with their well-studied single-scale counterparts. We develop multiscale analogs of paths and distance metrics. As a simple, motivating example ofmore » a common metric, we present a multiscale analog of the all-pairs shortest-path problem, along with a multiscale analog of a well-known algorithm which solves it. From a cyber defense perspective, this metric might be used to model the distance from an attacker's position in the network to a sensitive machine. In addition, we investigate probabilistic models of connectivity. These models exploit the hierarchy to quantify the likelihood that sensitive targets might be reachable from compromised nodes. We believe that our novel multiscale approach to modeling cyber-physical systems will advance several aspects of cyber defense, specifically allowing for a more efficient and agile approach to defending these systems.« less

AWAS: A dynamic work scheduling system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee, Y.; Hao, J.; Kocur, G.

1994-12-31

The Automated Work Administration System (AWAS) is an automated scheduling system developed at GTE. A typical work center has 1000 employees and processes 4000 jobs each day. Jobs are geographically distributed within the service area of the work center, require different skills, and have to be done within specified time windows. Each job can take anywhere from 12 minutes to several hours to complete. Each employee can have his/her individual schedule, skill, or working area. The jobs can enter and leave the system at any time The employees dial up to the system to request for their next job atmore » the beginning of a day or after a job is done. The system is able to respond to the changes dynamically and produce close to optimum solutions at real time. We formulate the real world problem as a minimum cost network flow problem. Both employees and jobs are formulated as nodes. Relationship between jobs and employees are formulated as arcs, and working hours contributed by employees and consumed by jobs are formulated as flow. The goal is to minimize missed commitments. We solve the problem with the successive shortest path algorithm. Combined with pre-processing and post-processing, the system produces reasonable outputs and the response time is very good.« less

The routing, modulation level, and spectrum allocation algorithm in the virtual optical network mapping

NASA Astrophysics Data System (ADS)

Wang, Yunyun; Li, Hui; Liu, Yuze; Ji, Yuefeng; Li, Hongfa

2017-10-01

With the development of large video services and cloud computing, the network is increasingly in the form of services. In SDON, the SDN controller holds the underlying physical resource information, thus allocating the appropriate resources and bandwidth to the VON service. However, for some services that require extremely strict QoT (quality of transmission), the shortest distance path algorithm is often unable to meet the requirements because it does not take the link spectrum resources into account. And in accordance with the choice of the most unoccupied links, there may be more spectrum fragments. So here we propose a new RMLSA (the routing, modulation Level, and spectrum allocation) algorithm to reduce the blocking probability. The results show about 40% less blocking probability than the shortest-distance algorithm and the minimum usage of the spectrum priority algorithm. This algorithm is used to satisfy strict request of QoT for demands.

The impact of self-driving cars on existing transportation networks

NASA Astrophysics Data System (ADS)

Ji, Xiang

2018-04-01

In this paper, considering the usage of self-driving, I research the congestion problems of traffic networks from both macro and micro levels. Firstly, the macroscopic mathematical model is established using the Greenshields function, analytic hierarchy process and Monte Carlo simulation, where the congestion level is divided into five levels according to the average vehicle speed. The roads with an obvious congestion situation is investigated mainly and the traffic flow and topology of the roads are analyzed firstly. By processing the data, I propose a traffic congestion model. In the model, I assume that half of the non-self-driving cars only take the shortest route and the other half can choose the path randomly. While self-driving cars can obtain vehicle density data of each road and choose the path more reasonable. When the path traffic density exceeds specific value, it cannot be selected. To overcome the dimensional differences of data, I rate the paths by BORDA sorting. The Monte Carlo simulation of Cellular Automaton is used to obtain the negative feedback information of the density of the traffic network, where the vehicles are added into the road network one by one. I then analyze the influence of negative feedback information on path selection of intelligent cars. The conclusion is that the increase of the proportion of intelligent vehicles will make the road load more balanced, and the self-driving cars can avoid the peak and reduce the degree of road congestion. Combined with other models, the optimal self-driving ratio is about sixty-two percent. From the microscopic aspect, by using the single-lane traffic NS rule, another model is established to analyze the road Partition scheme. The self-driving traffic is more intelligent, and their cooperation can reduce the random deceleration probability. By the model, I get the different self-driving ratio of space-time distribution. I also simulate the case of making a lane separately for self-driving, compared to the former model. It is concluded that a single lane is more efficient in a certain interval. However, it is not recommended to offer a lane separately. However, the self-driving also faces the problem of hacker attacks and greater damage after fault. So, when self-driving ratio is higher than a certain value, the increase of traffic flow rate is small. In this article, that value is discussed, and the optimal proportion is determined. Finally, I give a nontechnical explanation of the problem.

Algorithm Engineering: Concepts and Practice

NASA Astrophysics Data System (ADS)

Chimani, Markus; Klein, Karsten

Over the last years the term algorithm engineering has become wide spread synonym for experimental evaluation in the context of algorithm development. Yet it implies even more. We discuss the major weaknesses of traditional "pen and paper" algorithmics and the ever-growing gap between theory and practice in the context of modern computer hardware and real-world problem instances. We present the key ideas and concepts of the central algorithm engineering cycle that is based on a full feedback loop: It starts with the design of the algorithm, followed by the analysis, implementation, and experimental evaluation. The results of the latter can then be reused for modifications to the algorithmic design, stronger or input-specific theoretic performance guarantees, etc. We describe the individual steps of the cycle, explaining the rationale behind them and giving examples of how to conduct these steps thoughtfully. Thereby we give an introduction to current algorithmic key issues like I/O-efficient or parallel algorithms, succinct data structures, hardware-aware implementations, and others. We conclude with two especially insightful success stories—shortest path problems and text search—where the application of algorithm engineering techniques led to tremendous performance improvements compared with previous state-of-the-art approaches.

Benefit of adaptive FEC in shared backup path protected elastic optical network.

PubMed

Guo, Hong; Dai, Hua; Wang, Chao; Li, Yongcheng; Bose, Sanjay K; Shen, Gangxiang

2015-07-27

We apply an adaptive forward error correction (FEC) allocation strategy to an Elastic Optical Network (EON) operated with shared backup path protection (SBPP). To maximize the protected network capacity that can be carried, an Integer Linear Programing (ILP) model and a spectrum window plane (SWP)-based heuristic algorithm are developed. Simulation results show that the FEC coding overhead required by the adaptive FEC scheme is significantly lower than that needed by a fixed FEC allocation strategy resulting in higher network capacity for the adaptive strategy. The adaptive FEC allocation strategy can also significantly outperform the fixed FEC allocation strategy both in terms of the spare capacity redundancy and the average FEC coding overhead needed per optical channel. The proposed heuristic algorithm is efficient and not only performs closer to the ILP model but also does much better than the shortest-path algorithm.

A Spatial Cognitive Map and a Human-Like Memory Model Dedicated to Pedestrian Navigation in Virtual Urban Environments

NASA Astrophysics Data System (ADS)

Thomas, Romain; Donikian, Stéphane

Many articles dealing with agent navigation in an urban environment involve the use of various heuristics. Among them, one is prevalent: the search of the shortest path between two points. This strategy impairs the realism of the resulting behaviour. Indeed, psychological studies state that such a navigation behaviour is conditioned by the knowledge the subject has of its environment. Furthermore, the path a city dweller can follow may be influenced by many factors like his daily habits, or the path simplicity in term of minimum of direction changes. It appeared interesting to us to investigate how to mimic human navigation behavior with an autonomous agent. The solution we propose relies on an architecture based on a generic model of informed environment, a spatial cognitive map model merged with a human-like memory model, representing the agent's temporal knowledge of the environment, it gained along its experiences of navigation.

Optimal path planning for a mobile robot using cuckoo search algorithm

NASA Astrophysics Data System (ADS)

Mohanty, Prases K.; Parhi, Dayal R.

2016-03-01

The shortest/optimal path planning is essential for efficient operation of autonomous vehicles. In this article, a new nature-inspired meta-heuristic algorithm has been applied for mobile robot path planning in an unknown or partially known environment populated by a variety of static obstacles. This meta-heuristic algorithm is based on the levy flight behaviour and brood parasitic behaviour of cuckoos. A new objective function has been formulated between the robots and the target and obstacles, which satisfied the conditions of obstacle avoidance and target-seeking behaviour of robots present in the terrain. Depending upon the objective function value of each nest (cuckoo) in the swarm, the robot avoids obstacles and proceeds towards the target. The smooth optimal trajectory is framed with this algorithm when the robot reaches its goal. Some simulation and experimental results are presented at the end of the paper to show the effectiveness of the proposed navigational controller.

Authorship attribution based on Life-Like Network Automata.

PubMed

Machicao, Jeaneth; Corrêa, Edilson A; Miranda, Gisele H B; Amancio, Diego R; Bruno, Odemir M

2018-01-01

The authorship attribution is a problem of considerable practical and technical interest. Several methods have been designed to infer the authorship of disputed documents in multiple contexts. While traditional statistical methods based solely on word counts and related measurements have provided a simple, yet effective solution in particular cases; they are prone to manipulation. Recently, texts have been successfully modeled as networks, where words are represented by nodes linked according to textual similarity measurements. Such models are useful to identify informative topological patterns for the authorship recognition task. However, there is no consensus on which measurements should be used. Thus, we proposed a novel method to characterize text networks, by considering both topological and dynamical aspects of networks. Using concepts and methods from cellular automata theory, we devised a strategy to grasp informative spatio-temporal patterns from this model. Our experiments revealed an outperformance over structural analysis relying only on topological measurements, such as clustering coefficient, betweenness and shortest paths. The optimized results obtained here pave the way for a better characterization of textual networks.

Simultaneous travel time tomography for updating both velocity and reflector geometry in triangular/tetrahedral cell model

NASA Astrophysics Data System (ADS)

Bai, Chao-ying; He, Lei-yu; Li, Xing-wang; Sun, Jia-yu

2018-05-01

To conduct forward and simultaneous inversion in a complex geological model, including an irregular topography (or irregular reflector or velocity anomaly), we in this paper combined our previous multiphase arrival tracking method (referred as triangular shortest-path method, TSPM) in triangular (2D) or tetrahedral (3D) cell model and a linearized inversion solver (referred to as damped minimum norms and constrained least squares problem solved using the conjugate gradient method, DMNCLS-CG) to formulate a simultaneous travel time inversion method for updating both velocity and reflector geometry by using multiphase arrival times. In the triangular/tetrahedral cells, we deduced the partial derivative of velocity variation with respective to the depth change of reflector. The numerical simulation results show that the computational accuracy can be tuned to a high precision in forward modeling and the irregular velocity anomaly and reflector geometry can be accurately captured in the simultaneous inversion, because the triangular/tetrahedral cell can be easily used to stitch the irregular topography or subsurface interface.

On Modeling and Analysis of MIMO Wireless Mesh Networks with Triangular Overlay Topology

DOE PAGES

Cao, Zhanmao; Wu, Chase Q.; Zhang, Yuanping; ...

2015-01-01

Multiple input multiple output (MIMO) wireless mesh networks (WMNs) aim to provide the last-mile broadband wireless access to the Internet. Along with the algorithmic development for WMNs, some fundamental mathematical problems also emerge in various aspects such as routing, scheduling, and channel assignment, all of which require an effective mathematical model and rigorous analysis of network properties. In this paper, we propose to employ Cartesian product of graphs (CPG) as a multichannel modeling approach and explore a set of unique properties of triangular WMNs. In each layer of CPG with a single channel, we design a node coordinate scheme thatmore » retains the symmetric property of triangular meshes and develop a function for the assignment of node identity numbers based on their coordinates. We also derive a necessary-sufficient condition for interference-free links and combinatorial formulas to determine the number of the shortest paths for channel realization in triangular WMNs.« less

Universal resilience patterns in cascading load model: More capacity is not always better

NASA Astrophysics Data System (ADS)

Wang, Jianwei; Wang, Xue; Cai, Lin; Ni, Chengzhang; Xie, Wei; Xu, Bo

We study the problem of universal resilience patterns in complex networks against cascading failures. We revise the classical betweenness method and overcome its limitation of quantifying the load in cascading model. Considering that the generated load by all nodes should be equal to the transported one by all edges in the whole network, we propose a new method to quantify the load on an edge and construct a simple cascading model. By attacking the edge with the highest load, we show that, if the flow between two nodes is transported along the shortest paths between them, then the resilience of some networks against cascading failures inversely decreases with the enhancement of the capacity of every edge, i.e. the more capacity is not always better. We also observe the abnormal fluctuation of the additional load that exceeds the capacity of each edge. By a simple graph, we analyze the propagation of cascading failures step by step, and give a reasonable explanation of the abnormal fluctuation of cascading dynamics.

Simultaneous travel time tomography for updating both velocity and reflector geometry in triangular/tetrahedral cell model

NASA Astrophysics Data System (ADS)

Bai, Chao-ying; He, Lei-yu; Li, Xing-wang; Sun, Jia-yu

2017-12-01

To conduct forward and simultaneous inversion in a complex geological model, including an irregular topography (or irregular reflector or velocity anomaly), we in this paper combined our previous multiphase arrival tracking method (referred as triangular shortest-path method, TSPM) in triangular (2D) or tetrahedral (3D) cell model and a linearized inversion solver (referred to as damped minimum norms and constrained least squares problem solved using the conjugate gradient method, DMNCLS-CG) to formulate a simultaneous travel time inversion method for updating both velocity and reflector geometry by using multiphase arrival times. In the triangular/tetrahedral cells, we deduced the partial derivative of velocity variation with respective to the depth change of reflector. The numerical simulation results show that the computational accuracy can be tuned to a high precision in forward modeling and the irregular velocity anomaly and reflector geometry can be accurately captured in the simultaneous inversion, because the triangular/tetrahedral cell can be easily used to stitch the irregular topography or subsurface interface.

Routing channels in VLSI layout

NASA Astrophysics Data System (ADS)

Cai, Hong

A number of algorithms for the automatic routing of interconnections in Very Large Scale Integration (VLSI) building-block layouts are presented. Algorithms for the topological definition of channels, the global routing and the geometrical definition of channels are presented. In contrast to traditional approaches the definition and ordering of the channels is done after the global routing. This approach has the advantage that global routing information can be taken into account to select the optimal channel structure. A polynomial algorithm for the channel definition and ordering problem is presented. The existence of a conflict-free channel structure is guaranteed by enforcing a sliceable placement. Algorithms for finding the shortest connection path are described. A separate algorithm is developed for the power net routing, because the two power nets must be planarly routed with variable wire width. An integrated placement and routing system for generating building-block layout is briefly described. Some experimental results and design experiences in using the system are also presented. Very good results are obtained.

Topological analysis of metabolic networks integrating co-segregating transcriptomes and metabolomes in type 2 diabetic rat congenic series.

PubMed

Dumas, Marc-Emmanuel; Domange, Céline; Calderari, Sophie; Martínez, Andrea Rodríguez; Ayala, Rafael; Wilder, Steven P; Suárez-Zamorano, Nicolas; Collins, Stephan C; Wallis, Robert H; Gu, Quan; Wang, Yulan; Hue, Christophe; Otto, Georg W; Argoud, Karène; Navratil, Vincent; Mitchell, Steve C; Lindon, John C; Holmes, Elaine; Cazier, Jean-Baptiste; Nicholson, Jeremy K; Gauguier, Dominique

2016-09-30

The genetic regulation of metabolic phenotypes (i.e., metabotypes) in type 2 diabetes mellitus occurs through complex organ-specific cellular mechanisms and networks contributing to impaired insulin secretion and insulin resistance. Genome-wide gene expression profiling systems can dissect the genetic contributions to metabolome and transcriptome regulations. The integrative analysis of multiple gene expression traits and metabolic phenotypes (i.e., metabotypes) together with their underlying genetic regulation remains a challenge. Here, we introduce a systems genetics approach based on the topological analysis of a combined molecular network made of genes and metabolites identified through expression and metabotype quantitative trait locus mapping (i.e., eQTL and mQTL) to prioritise biological characterisation of candidate genes and traits. We used systematic metabotyping by 1 H NMR spectroscopy and genome-wide gene expression in white adipose tissue to map molecular phenotypes to genomic blocks associated with obesity and insulin secretion in a series of rat congenic strains derived from spontaneously diabetic Goto-Kakizaki (GK) and normoglycemic Brown-Norway (BN) rats. We implemented a network biology strategy approach to visualize the shortest paths between metabolites and genes significantly associated with each genomic block. Despite strong genomic similarities (95-99 %) among congenics, each strain exhibited specific patterns of gene expression and metabotypes, reflecting the metabolic consequences of series of linked genetic polymorphisms in the congenic intervals. We subsequently used the congenic panel to map quantitative trait loci underlying specific mQTLs and genome-wide eQTLs. Variation in key metabolites like glucose, succinate, lactate, or 3-hydroxybutyrate and second messenger precursors like inositol was associated with several independent genomic intervals, indicating functional redundancy in these regions. To navigate through the complexity of these association networks we mapped candidate genes and metabolites onto metabolic pathways and implemented a shortest path strategy to highlight potential mechanistic links between metabolites and transcripts at colocalized mQTLs and eQTLs. Minimizing the shortest path length drove prioritization of biological validations by gene silencing. These results underline the importance of network-based integration of multilevel systems genetics datasets to improve understanding of the genetic architecture of metabotype and transcriptomic regulation and to characterize novel functional roles for genes determining tissue-specific metabolism.

Routing optimization in networks based on traffic gravitational field model

NASA Astrophysics Data System (ADS)

Liu, Longgeng; Luo, Guangchun

2017-04-01

For research on the gravitational field routing mechanism on complex networks, we further analyze the gravitational effect of paths. In this study, we introduce the concept of path confidence degree to evaluate the unblocked reliability of paths that it takes the traffic state of all nodes on the path into account from the overall. On the basis of this, we propose an improved gravitational field routing protocol considering all the nodes’ gravities on the path and the path confidence degree. In order to evaluate the transmission performance of the routing strategy, an order parameter is introduced to measure the network throughput by the critical value of phase transition from a free-flow phase to a jammed phase, and the betweenness centrality is used to evaluate the transmission performance and traffic congestion of the network. Simulation results show that compared with the shortest-path routing strategy and the previous gravitational field routing strategy, the proposed algorithm improves the network throughput considerably and effectively balances the traffic load within the network, and all nodes in the network are utilized high efficiently. As long as γ ≥ α, the transmission performance can reach the maximum and remains unchanged for different α and γ, which ensures that the proposed routing protocol is high efficient and stable.

Stabilization of a locally minimal forest

NASA Astrophysics Data System (ADS)

Ivanov, A. O.; Mel'nikova, A. E.; Tuzhilin, A. A.

2014-03-01

The method of partial stabilization of locally minimal networks, which was invented by Ivanov and Tuzhilin to construct examples of shortest trees with given topology, is developed. According to this method, boundary vertices of degree 2 are not added to all edges of the original locally minimal tree, but only to some of them. The problem of partial stabilization of locally minimal trees in a finite-dimensional Euclidean space is solved completely in the paper, that is, without any restrictions imposed on the number of edges remaining free of subdivision. A criterion for the realizability of such stabilization is established. In addition, the general problem of searching for the shortest forest connecting a finite family of boundary compact sets in an arbitrary metric space is formalized; it is shown that such forests exist for any family of compact sets if and only if for any finite subset of the ambient space there exists a shortest tree connecting it. The theory developed here allows us to establish further generalizations of the stabilization theorem both for arbitrary metric spaces and for metric spaces with some special properties. Bibliography: 10 titles.

LiveWire interactive boundary extraction algorithm based on Haar wavelet transform and control point set direction search

NASA Astrophysics Data System (ADS)

Cheng, Jun; Zhang, Jun; Tian, Jinwen

2015-12-01

Based on deep analysis of the LiveWire interactive boundary extraction algorithm, a new algorithm focusing on improving the speed of LiveWire algorithm is proposed in this paper. Firstly, the Haar wavelet transform is carried on the input image, and the boundary is extracted on the low resolution image obtained by the wavelet transform of the input image. Secondly, calculating LiveWire shortest path is based on the control point set direction search by utilizing the spatial relationship between the two control points users provide in real time. Thirdly, the search order of the adjacent points of the starting node is set in advance. An ordinary queue instead of a priority queue is taken as the storage pool of the points when optimizing their shortest path value, thus reducing the complexity of the algorithm from O[n2] to O[n]. Finally, A region iterative backward projection method based on neighborhood pixel polling has been used to convert dual-pixel boundary of the reconstructed image to single-pixel boundary after Haar wavelet inverse transform. The algorithm proposed in this paper combines the advantage of the Haar wavelet transform and the advantage of the optimal path searching method based on control point set direction search. The former has fast speed of image decomposition and reconstruction and is more consistent with the texture features of the image and the latter can reduce the time complexity of the original algorithm. So that the algorithm can improve the speed in interactive boundary extraction as well as reflect the boundary information of the image more comprehensively. All methods mentioned above have a big role in improving the execution efficiency and the robustness of the algorithm.

Effective Task Assignment and Motion Planning for Complex UAV Operations

DTIC Science & Technology

2011-09-01

shortest path must be one of the following six different combinations of line segments and curvature arcs: RLR , LRL, RSR, LSL, RSL, LSR, where R is a...RSL, RLR , and their mirror images LSL, LSR, LRL, respectively. This section will discuss the minimum number of waypoints required in order for Dubins...point. Then the vehicle will fly to the third waypoint along it’s turn circle. Lemma 10. For the Dubins trajectories RLR and LRL, three waypoints

Why our patients (and we) need basic science research.

PubMed

Schor, Nina F

2013-05-28

In times of fiscal austerity, the tendency is to seek instant, inexpensive gratification. In the case of biomedical research, this means the shortest path to practical clinical implementation. But fueling the translational pipeline with discovery depends critically on allowing the biomedical research community to follow their science where it takes them. Fiscal constraints carry with them the risk of squelching creativity and forfeiting the power of serendipity to provide the substrate for the translational engine in the future.

The Structure and Evolution of Buyer-Supplier Networks

PubMed Central

Mizuno, Takayuki; Souma, Wataru; Watanabe, Tsutomu

2014-01-01

In this paper, we investigate the structure and evolution of customer-supplier networks in Japan using a unique dataset that contains information on customer and supplier linkages for more than 500,000 incorporated non-financial firms for the five years from 2008 to 2012. We find, first, that the number of customer links is unequal across firms; the customer link distribution has a power-law tail with an exponent of unity (i.e., it follows Zipf's law). We interpret this as implying that competition among firms to acquire new customers yields winners with a large number of customers, as well as losers with fewer customers. We also show that the shortest path length for any pair of firms is, on average, 4.3 links. Second, we find that link switching is relatively rare. Our estimates indicate that the survival rate per year for customer links is 92 percent and for supplier links 93 percent. Third and finally, we find that firm growth rates tend to be more highly correlated the closer two firms are to each other in a customer-supplier network (i.e., the smaller is the shortest path length for the two firms). This suggests that a non-negligible portion of fluctuations in firm growth stems from the propagation of microeconomic shocks – shocks affecting only a particular firm – through customer-supplier chains. PMID:25000368

The structure and evolution of buyer-supplier networks.

PubMed

Mizuno, Takayuki; Souma, Wataru; Watanabe, Tsutomu

2014-01-01

In this paper, we investigate the structure and evolution of customer-supplier networks in Japan using a unique dataset that contains information on customer and supplier linkages for more than 500,000 incorporated non-financial firms for the five years from 2008 to 2012. We find, first, that the number of customer links is unequal across firms; the customer link distribution has a power-law tail with an exponent of unity (i.e., it follows Zipf's law). We interpret this as implying that competition among firms to acquire new customers yields winners with a large number of customers, as well as losers with fewer customers. We also show that the shortest path length for any pair of firms is, on average, 4.3 links. Second, we find that link switching is relatively rare. Our estimates indicate that the survival rate per year for customer links is 92 percent and for supplier links 93 percent. Third and finally, we find that firm growth rates tend to be more highly correlated the closer two firms are to each other in a customer-supplier network (i.e., the smaller is the shortest path length for the two firms). This suggests that a non-negligible portion of fluctuations in firm growth stems from the propagation of microeconomic shocks - shocks affecting only a particular firm - through customer-supplier chains.

Mobility based multicast routing in wireless mesh networks

NASA Astrophysics Data System (ADS)

Jain, Sanjeev; Tripathi, Vijay S.; Tiwari, Sudarshan

2013-01-01

There exist two fundamental approaches to multicast routing namely minimum cost trees and shortest path trees. The (MCT's) minimum cost tree is one which connects receiver and sources by providing a minimum number of transmissions (MNTs) the MNTs approach is generally used for energy constraint sensor and mobile ad hoc networks. In this paper we have considered node mobility and try to find out simulation based comparison of the (SPT's) shortest path tree, (MST's) minimum steiner trees and minimum number of transmission trees in wireless mesh networks by using the performance metrics like as an end to end delay, average jitter, throughput and packet delivery ratio, average unicast packet delivery ratio, etc. We have also evaluated multicast performance in the small and large wireless mesh networks. In case of multicast performance in the small networks we have found that when the traffic load is moderate or high the SPTs outperform the MSTs and MNTs in all cases. The SPTs have lowest end to end delay and average jitter in almost all cases. In case of multicast performance in the large network we have seen that the MSTs provide minimum total edge cost and minimum number of transmissions. We have also found that the one drawback of SPTs, when the group size is large and rate of multicast sending is high SPTs causes more packet losses to other flows as MCTs.

Betweenness centrality in a weighted network

NASA Astrophysics Data System (ADS)

Wang, Huijuan; Hernandez, Javier Martin; van Mieghem, Piet

2008-04-01

When transport in networks follows the shortest paths, the union of all shortest path trees G∪SPT can be regarded as the “transport overlay network.” Overlay networks such as peer-to-peer networks or virtual private networks can be considered as a subgraph of G∪SPT . The traffic through the network is examined by the betweenness Bl of links in the overlay G∪SPT . The strength of disorder can be controlled by, e.g., tuning the extreme value index α of the independent and identically distributed polynomial link weights. In the strong disorder limit (α→0) , all transport flows over a critical backbone, the minimum spanning tree (MST). We investigate the betweenness distributions of wide classes of trees, such as the MST of those well-known network models and of various real-world complex networks. All these trees with different degree distributions (e.g., uniform, exponential, or power law) are found to possess a power law betweenness distribution Pr[Bl=j]˜j-c . The exponent c seems to be positively correlated with the degree variance of the tree and to be insensitive of the size N of a network. In the weak disorder regime, transport in the network traverses many links. We show that a link with smaller link weight tends to carry more traffic. This negative correlation between link weight and betweenness depends on α and the structure of the underlying topology.

Effective distances for epidemics spreading on complex networks.

PubMed

Iannelli, Flavio; Koher, Andreas; Brockmann, Dirk; Hövel, Philipp; Sokolov, Igor M

2017-01-01

We show that the recently introduced logarithmic metrics used to predict disease arrival times on complex networks are approximations of more general network-based measures derived from random walks theory. Using the daily air-traffic transportation data we perform numerical experiments to compare the infection arrival time with this alternative metric that is obtained by accounting for multiple walks instead of only the most probable path. The comparison with direct simulations reveals a higher correlation compared to the shortest-path approach used previously. In addition our method allows to connect fundamental observables in epidemic spreading with the cumulant-generating function of the hitting time for a Markov chain. Our results provides a general and computationally efficient approach using only algebraic methods.

Effective distances for epidemics spreading on complex networks

NASA Astrophysics Data System (ADS)

Iannelli, Flavio; Koher, Andreas; Brockmann, Dirk; Hövel, Philipp; Sokolov, Igor M.

2017-01-01

We show that the recently introduced logarithmic metrics used to predict disease arrival times on complex networks are approximations of more general network-based measures derived from random walks theory. Using the daily air-traffic transportation data we perform numerical experiments to compare the infection arrival time with this alternative metric that is obtained by accounting for multiple walks instead of only the most probable path. The comparison with direct simulations reveals a higher correlation compared to the shortest-path approach used previously. In addition our method allows to connect fundamental observables in epidemic spreading with the cumulant-generating function of the hitting time for a Markov chain. Our results provides a general and computationally efficient approach using only algebraic methods.

An efficient routing strategy for traffic dynamics on two-layer complex networks

NASA Astrophysics Data System (ADS)

Ma, Jinlong; Wang, Huiling; Zhang, Zhuxi; Zhang, Yi; Duan, Congwen; Qi, Zhaohui; Liu, Yu

2018-05-01

In order to alleviate traffic congestion on multilayer networks, designing an efficient routing strategy is one of the most important ways. In this paper, a novel routing strategy is proposed to reduce traffic congestion on two-layer networks. In the proposed strategy, the optimal paths in the physical layer are chosen by comprehensively considering the roles of nodes’ degrees of the two layers. Both numerical and analytical results indicate that our routing strategy can reasonably redistribute the traffic load of the physical layer, and thus the traffic capacity of two-layer complex networks are significantly enhanced compared with the shortest path routing (SPR) and the global awareness routing (GAR) strategies. This study may shed some light on the optimization of networked traffic dynamics.

A novel comparator featured with input data characteristic

NASA Astrophysics Data System (ADS)

Jiang, Xiaobo; Ye, Desheng; Xu, Xiangmin; Zheng, Shuai

2016-03-01

Two types of low-power asynchronous comparators featured with input data statistical characteristic are proposed in this article. The asynchronous ripple comparator stops comparing at the first unequal bit but delivers the result to the least significant bit. The pre-stop asynchronous comparator can completely stop comparing and obtain results immediately. The proposed and contrastive comparators were implemented in SMIC 0.18 μm process with different bit widths. Simulation shows that the proposed pre-stop asynchronous comparator features the lowest power consumption, shortest average propagation delay and highest area efficiency among the comparators. Data path of low-density parity check decoder using the proposed pre-stop asynchronous comparators are most power efficient compared with other data paths with synthesised, clock gating and bitwise competition logic comparators.

Statistical Physics of Cascading Failures in Complex Networks

NASA Astrophysics Data System (ADS)

Panduranga, Nagendra Kumar

Systems such as the power grid, world wide web (WWW), and internet are categorized as complex systems because of the presence of a large number of interacting elements. For example, the WWW is estimated to have a billion webpages and understanding the dynamics of such a large number of individual agents (whose individual interactions might not be fully known) is a challenging task. Complex network representations of these systems have proved to be of great utility. Statistical physics is the study of emergence of macroscopic properties of systems from the characteristics of the interactions between individual molecules. Hence, statistical physics of complex networks has been an effective approach to study these systems. In this dissertation, I have used statistical physics to study two distinct phenomena in complex systems: i) Cascading failures and ii) Shortest paths in complex networks. Understanding cascading failures is considered to be one of the "holy grails" in the study of complex systems such as the power grid, transportation networks, and economic systems. Studying failures of these systems as percolation on complex networks has proved to be insightful. Previously, cascading failures have been studied extensively using two different models: k-core percolation and interdependent networks. The first part of this work combines the two models into a general model, solves it analytically, and validates the theoretical predictions through extensive computer simulations. The phase diagram of the percolation transition has been systematically studied as one varies the average local k-core threshold and the coupling between networks. The phase diagram of the combined processes is very rich and includes novel features that do not appear in the models which study each of the processes separately. For example, the phase diagram consists of first- and second-order transition regions separated by two tricritical lines that merge together and enclose a two-stage transition region. In the two-stage transition, the size of the giant component undergoes a first-order jump at a certain occupation probability followed by a continuous second-order transition at a smaller occupation probability. Furthermore, at certain fixed interdependencies, the percolation transition cycles from first-order to second-order to two-stage to first-order as the k-core threshold is increased. We setup the analytical equations describing the phase boundaries of the two-stage transition region and we derive the critical exponents for each type of transition. Understanding the shortest paths between individual elements in systems like communication networks and social media networks is important in the study of information cascades in these systems. Often, large heterogeneity can be present in the connections between nodes in these networks. Certain sets of nodes can be more highly connected among themselves than with the nodes from other sets. These sets of nodes are often referred to as 'communities'. The second part of this work studies the effect of the presence of communities on the distribution of shortest paths in a network using a modular Erdős-Renyi network model. In this model, the number of communities and the degree of modularity of the network can be tuned using the parameters of the model. We find that the model reaches a percolation threshold while tuning the degree of modularity of the network and the distribution of the shortest paths in the network can be used as an indicator of how the communities are connected.

An improved cellular automaton method to model multispecies biofilms.

PubMed

Tang, Youneng; Valocchi, Albert J

2013-10-01

Biomass-spreading rules used in previous cellular automaton methods to simulate multispecies biofilm introduced extensive mixing between different biomass species or resulted in spatially discontinuous biomass concentration and distribution; this caused results based on the cellular automaton methods to deviate from experimental results and those from the more computationally intensive continuous method. To overcome the problems, we propose new biomass-spreading rules in this work: Excess biomass spreads by pushing a line of grid cells that are on the shortest path from the source grid cell to the destination grid cell, and the fractions of different biomass species in the grid cells on the path change due to the spreading. To evaluate the new rules, three two-dimensional simulation examples are used to compare the biomass distribution computed using the continuous method and three cellular automaton methods, one based on the new rules and the other two based on rules presented in two previous studies. The relationship between the biomass species is syntrophic in one example and competitive in the other two examples. Simulation results generated using the cellular automaton method based on the new rules agree much better with the continuous method than do results using the other two cellular automaton methods. The new biomass-spreading rules are no more complex to implement than the existing rules. Copyright © 2013 Elsevier Ltd. All rights reserved.

Reconfigurable routing protocol for free space optical sensor networks.

PubMed

Xie, Rong; Yang, Won-Hyuk; Kim, Young-Chon

2012-01-01

Recently, free space optical sensor networks (FSOSNs), which are based on free space optics (FSO) instead of radio frequency (RF), have gained increasing visibility over traditional wireless sensor networks (WSNs) due to their advantages such as larger capacity, higher security, and lower cost. However, the performance of FSOSNs is restricted to the requirement of a direct line-of-sight (LOS) path between a sender and a receiver pair. Once a node dies of energy depletion, the network would probably suffer from a dramatic decrease of connectivity, resulting in a huge loss of data packets. Thus, this paper proposes a reconfigurable routing protocol (RRP) to overcome this problem by dynamically reconfiguring the network virtual topology. The RRP works in three phases: (1) virtual topology construction, (2) routing establishment, and (3) reconfigurable routing. When data transmission begins, the data packets are first routed through the shortest hop paths. Then a reconfiguration is initiated by the node whose residual energy falls below a threshold. Nodes affected by this dying node are classified into two types, namely maintenance nodes and adjustment nodes, and they are reconfigured according to the types. An energy model is designed to evaluate the performance of RRP through OPNET simulation. Our simulation results indicate that the RRP achieves better performance compared with the simple-link protocol and a direct reconfiguration scheme in terms of connectivity, network lifetime, packet delivery ratio and the number of living nodes.

Creating an Online Laboratory

DTIC Science & Technology

2015-03-18

Problem (TSP) to solve, a canonical computer science problem that involves identifying the shortest itinerary for a hypothetical salesman traveling among a...also created working versions of the travelling salesperson problem , prisoners’ dilemma, public goods game, ultimatum game, word ladders, and...the task within networks of others performing the task. Thus, we built five problems which could be embedded in networks: the traveling salesperson

Minimum expected delay-based routing protocol (MEDR) for Delay Tolerant Mobile Sensor Networks.

PubMed

Feng, Yong; Liu, Ming; Wang, Xiaomin; Gong, Haigang

2010-01-01

It is a challenging work to develop efficient routing protocols for Delay Tolerant Mobile Sensor Networks (DTMSNs), which have several unique characteristics such as sensor mobility, intermittent connectivity, energy limit, and delay tolerability. In this paper, we propose a new routing protocol called Minimum Expected Delay-based Routing (MEDR) tailored for DTMSNs. MEDR achieves a good routing performance by finding and using the connected paths formed dynamically by mobile sensors. In MEDR, each sensor maintains two important parameters: Minimum Expected Delay (MED) and its expiration time. According to MED, messages will be delivered to the sensor that has at least a connected path with their hosting nodes, and has the shortest expected delay to communication directly with the sink node. Because of the changing network topology, the path is fragile and volatile, so we use the expiration time of MED to indicate the valid time of the path, and avoid wrong transmissions. Simulation results show that the proposed MEDR achieves a higher message delivery ratio with lower transmission overhead and data delivery delay than other DTMSN routing approaches.

A star recognition method based on the Adaptive Ant Colony algorithm for star sensors.

PubMed

Quan, Wei; Fang, Jiancheng

2010-01-01

A new star recognition method based on the Adaptive Ant Colony (AAC) algorithm has been developed to increase the star recognition speed and success rate for star sensors. This method draws circles, with the center of each one being a bright star point and the radius being a special angular distance, and uses the parallel processing ability of the AAC algorithm to calculate the angular distance of any pair of star points in the circle. The angular distance of two star points in the circle is solved as the path of the AAC algorithm, and the path optimization feature of the AAC is employed to search for the optimal (shortest) path in the circle. This optimal path is used to recognize the stellar map and enhance the recognition success rate and speed. The experimental results show that when the position error is about 50″, the identification success rate of this method is 98% while the Delaunay identification method is only 94%. The identification time of this method is up to 50 ms.

Graph theory enables drug repurposing--how a mathematical model can drive the discovery of hidden mechanisms of action.

PubMed

Gramatica, Ruggero; Di Matteo, T; Giorgetti, Stefano; Barbiani, Massimo; Bevec, Dorian; Aste, Tomaso

2014-01-01

We introduce a methodology to efficiently exploit natural-language expressed biomedical knowledge for repurposing existing drugs towards diseases for which they were not initially intended. Leveraging on developments in Computational Linguistics and Graph Theory, a methodology is defined to build a graph representation of knowledge, which is automatically analysed to discover hidden relations between any drug and any disease: these relations are specific paths among the biomedical entities of the graph, representing possible Modes of Action for any given pharmacological compound. We propose a measure for the likeliness of these paths based on a stochastic process on the graph. This measure depends on the abundance of indirect paths between a peptide and a disease, rather than solely on the strength of the shortest path connecting them. We provide real-world examples, showing how the method successfully retrieves known pathophysiological Mode of Action and finds new ones by meaningfully selecting and aggregating contributions from known bio-molecular interactions. Applications of this methodology are presented, and prove the efficacy of the method for selecting drugs as treatment options for rare diseases.

Three-axis asymmetric radiation detector system

DOEpatents

Martini, Mario Pierangelo; Gedcke, Dale A.; Raudorf, Thomas W.; Sangsingkeow, Pat

2000-01-01

A three-axis radiation detection system whose inner and outer electrodes are shaped and positioned so that the shortest path between any point on the inner electrode and the outer electrode is a different length whereby the rise time of a pulse derived from a detected radiation event can uniquely define the azimuthal and radial position of that event, and the outer electrode is divided into a plurality of segments in the longitudinal axial direction for locating the axial location of a radiation detection event occurring in the diode.

How networks split when rival leaders emerge

NASA Astrophysics Data System (ADS)

Krawczyk, Malgorzata J.; Kułakowski, Krzysztof

2018-02-01

In a model social network, two hubs are appointed as leaders. Consecutive cutting of links on a shortest path between them splits the network in two. Next, the network is growing again till the initial size. Both processes are cyclically repeated. We investigate the size of a cluster containing the largest hub, the degree, the clustering coefficient, the closeness centrality and the betweenness centrality of the largest hub, as dependent on the number of cycles. The results are interpreted in terms of the leader's benefits from conflicts.

Octave-spanning carrier-envelope phase stabilized visible pulse with sub-3-fs pulse duration.

PubMed

Okamura, Kotaro; Kobayashi, Takayoshi

2011-01-15

The visible second harmonic of the idler output from a noncollinear optical parametric amplifier was compressed using adaptive dispersion control with a deformable mirror. The amplifier was pumped by and seeded in the signal path by a common 400 nm second-harmonic pulse from a Ti:sapphire regenerative amplifier. Thus, both the idler output and the second harmonic of the idler were passively carrier-envelope phase stabilized. The shortest pulse duration achieved was below 3 fs.

Traffic Patrol Service Platform Scheduling and Containment Optimization Strategy

NASA Astrophysics Data System (ADS)

Wang, Tiane; Niu, Taiyang; Wan, Baocheng; Li, Jian

This article is based on the traffic and patrol police service platform settings and scheduling, in order to achieve the main purpose of rapid containment for the suspect in an emergency event. Proposing new boundary definition based on graph theory, using 0-1 programming, Dijkstra algorithm, the shortest path tree (SPT) and some of the related knowledge establish a containment model. Finally, making a combination with a city-specific data and using this model obtain the best containment plan.

Fast Solar-Blind AlGaN/GaN 2DEG UV detector with Transparent Graphene Electrode

DTIC Science & Technology

2017-03-01

graphene and 2D electron gas (2DEG). With introducing the graphene, photo-carriers separated by the polarization electric field of the AlGaN are...photodiodes, due to the strong intrinsic polarization effect of AlGaN. More than 105 of high signal to noise ratio of the UV detectors with fast...intrinsic polarization field vertically inside the AlGaN, the holes and electrons will travel in their shortest paths to graphene and 2DEG

CMPF: class-switching minimized pathfinding in metabolic networks.

PubMed

Lim, Kevin; Wong, Limsoon

2012-01-01

The metabolic network is an aggregation of enzyme catalyzed reactions that converts one compound to another. Paths in a metabolic network are a sequence of enzymes that describe how a chemical compound of interest can be produced in a biological system. As the number of such paths is quite large, many methods have been developed to score paths so that the k-shortest paths represent the set of paths that are biologically meaningful or efficient. However, these approaches do not consider whether the sequence of enzymes can be manufactured in the same pathway/species/localization. As a result, a predicted sequence might consist of groups of enzymes that operate in distinct pathway/species/localization and may not truly reflect the events occurring within cell. We propose a path weighting method CMPF (Class-switching Minimized Pathfinder) to search for routes in a metabolic network which minimizes pathway switching. In biological terms, a pathway is a series of chemical reactions which define a specific function (e.g. glycolysis). We conjecture that routes that cross many pathways are inefficient since different pathways define different metabolic functions. In addition, native routes are also well characterized within pathways, suggesting that reasonable paths should not involve too many pathway switches. Our method can be generalized when reactions participate in a class set (e.g., pathways, species or cellular localization) so that the paths predicted have minimal class crossings. We show that our method generates k-paths that involve the least number of class switching. In addition, we also show that native paths are recoverable and alternative paths deviates less from native paths compared to other methods. This suggests that paths ranked by our method could be a way to predict paths that are likely to occur in biological systems.

Certification of computational results

NASA Technical Reports Server (NTRS)

Sullivan, Gregory F.; Wilson, Dwight S.; Masson, Gerald M.

1993-01-01

A conceptually novel and powerful technique to achieve fault detection and fault tolerance in hardware and software systems is described. When used for software fault detection, this new technique uses time and software redundancy and can be outlined as follows. In the initial phase, a program is run to solve a problem and store the result. In addition, this program leaves behind a trail of data called a certification trail. In the second phase, another program is run which solves the original problem again. This program, however, has access to the certification trail left by the first program. Because of the availability of the certification trail, the second phase can be performed by a less complex program and can execute more quickly. In the final phase, the two results are compared and if they agree the results are accepted as correct; otherwise an error is indicated. An essential aspect of this approach is that the second program must always generate either an error indication or a correct output even when the certification trail it receives from the first program is incorrect. The certification trail approach to fault tolerance is formalized and realizations of it are illustrated by considering algorithms for the following problems: convex hull, sorting, and shortest path. Cases in which the second phase can be run concurrently with the first and act as a monitor are discussed. The certification trail approach are compared to other approaches to fault tolerance.

An optimal routing strategy on scale-free networks

NASA Astrophysics Data System (ADS)

Yang, Yibo; Zhao, Honglin; Ma, Jinlong; Qi, Zhaohui; Zhao, Yongbin

Traffic is one of the most fundamental dynamical processes in networked systems. With the traditional shortest path routing (SPR) protocol, traffic congestion is likely to occur on the hub nodes on scale-free networks. In this paper, we propose an improved optimal routing (IOR) strategy which is based on the betweenness centrality and the degree centrality of nodes in the scale-free networks. With the proposed strategy, the routing paths can accurately bypass hub nodes in the network to enhance the transport efficiency. Simulation results show that the traffic capacity as well as some other indexes reflecting transportation efficiency are further improved with the IOR strategy. Owing to the significantly improved traffic performance, this study is helpful to design more efficient routing strategies in communication or transportation systems.

Trajectory Segmentation Map-Matching Approach for Large-Scale, High-Resolution GPS Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhu, Lei; Holden, Jacob R.; Gonder, Jeffrey D.

With the development of smartphones and portable GPS devices, large-scale, high-resolution GPS data can be collected. Map matching is a critical step in studying vehicle driving activity and recognizing network traffic conditions from the data. A new trajectory segmentation map-matching algorithm is proposed to deal accurately and efficiently with large-scale, high-resolution GPS trajectory data. The new algorithm separated the GPS trajectory into segments. It found the shortest path for each segment in a scientific manner and ultimately generated a best-matched path for the entire trajectory. The similarity of a trajectory segment and its matched path is described by a similaritymore » score system based on the longest common subsequence. The numerical experiment indicated that the proposed map-matching algorithm was very promising in relation to accuracy and computational efficiency. Large-scale data set applications verified that the proposed method is robust and capable of dealing with real-world, large-scale GPS data in a computationally efficient and accurate manner.« less

Trajectory Segmentation Map-Matching Approach for Large-Scale, High-Resolution GPS Data

DOE PAGES

Zhu, Lei; Holden, Jacob R.; Gonder, Jeffrey D.

2017-01-01

With the development of smartphones and portable GPS devices, large-scale, high-resolution GPS data can be collected. Map matching is a critical step in studying vehicle driving activity and recognizing network traffic conditions from the data. A new trajectory segmentation map-matching algorithm is proposed to deal accurately and efficiently with large-scale, high-resolution GPS trajectory data. The new algorithm separated the GPS trajectory into segments. It found the shortest path for each segment in a scientific manner and ultimately generated a best-matched path for the entire trajectory. The similarity of a trajectory segment and its matched path is described by a similaritymore » score system based on the longest common subsequence. The numerical experiment indicated that the proposed map-matching algorithm was very promising in relation to accuracy and computational efficiency. Large-scale data set applications verified that the proposed method is robust and capable of dealing with real-world, large-scale GPS data in a computationally efficient and accurate manner.« less

Altered brain structural connectivity in post-traumatic stress disorder: a diffusion tensor imaging tractography study.

PubMed

Long, Zhiliang; Duan, Xujun; Xie, Bing; Du, Handan; Li, Rong; Xu, Qiang; Wei, Luqing; Zhang, Shao-xiang; Wu, Yi; Gao, Qing; Chen, Huafu

2013-09-25

Post-traumatic stress disorder (PTSD) is characterized by dysfunction of several discrete brain regions such as medial prefrontal gyrus with hypoactivation and amygdala with hyperactivation. However, alterations of large-scale whole brain topological organization of structural networks remain unclear. Seventeen patients with PTSD in motor vehicle accident survivors and 15 normal controls were enrolled in our study. Large-scale structural connectivity network (SCN) was constructed using diffusion tensor tractography, followed by thresholding the mean factional anisotropy matrix of 90 brain regions. Graph theory analysis was then employed to investigate their aberrant topological properties. Both patient and control group showed small-world topology in their SCNs. However, patients with PTSD exhibited abnormal global properties characterized by significantly decreased characteristic shortest path length and normalized characteristic shortest path length. Furthermore, the patient group showed enhanced nodal centralities predominately in salience network including bilateral anterior cingulate and pallidum, and hippocampus/parahippocamus gyrus, and decreased nodal centralities mainly in medial orbital part of superior frontal gyrus. The main limitation of this study is the small sample of PTSD patients, which may lead to decrease the statistic power. Consequently, this study should be considered an exploratory analysis. These results are consistent with the notion that PTSD can be understood by investigating the dysfunction of large-scale, spatially distributed neural networks, and also provide structural evidences for further exploration of neurocircuitry models in PTSD. © 2013 Elsevier B.V. All rights reserved.

Effects of amyloid and small vessel disease on white matter network disruption.

PubMed

Kim, Hee Jin; Im, Kiho; Kwon, Hunki; Lee, Jong Min; Ye, Byoung Seok; Kim, Yeo Jin; Cho, Hanna; Choe, Yearn Seong; Lee, Kyung Han; Kim, Sung Tae; Kim, Jae Seung; Lee, Jae Hong; Na, Duk L; Seo, Sang Won

2015-01-01

There is growing evidence that the human brain is a large scale complex network. The structural network is reported to be disrupted in cognitively impaired patients. However, there have been few studies evaluating the effects of amyloid and small vessel disease (SVD) markers, the common causes of cognitive impairment, on structural networks. Thus, we evaluated the association between amyloid and SVD burdens and structural networks using diffusion tensor imaging (DTI). Furthermore, we determined if network parameters predict cognitive impairments. Graph theoretical analysis was applied to DTI data from 232 cognitively impaired patients with varying degrees of amyloid and SVD burdens. All patients underwent Pittsburgh compound-B (PiB) PET to detect amyloid burden, MRI to detect markers of SVD, including the volume of white matter hyperintensities and the number of lacunes, and detailed neuropsychological testing. The whole-brain network was assessed by network parameters of integration (shortest path length, global efficiency) and segregation (clustering coefficient, transitivity, modularity). PiB retention ratio was not associated with any white matter network parameters. Greater white matter hyperintensity volumes or lacunae numbers were significantly associated with decreased network integration (increased shortest path length, decreased global efficiency) and increased network segregation (increased clustering coefficient, increased transitivity, increased modularity). Decreased network integration or increased network segregation were associated with poor performances in attention, language, visuospatial, memory, and frontal-executive functions. Our results suggest that SVD alters white matter network integration and segregation, which further predicts cognitive dysfunction.

An Adaptive Clustering Approach Based on Minimum Travel Route Planning for Wireless Sensor Networks with a Mobile Sink.

PubMed

Tang, Jiqiang; Yang, Wu; Zhu, Lingyun; Wang, Dong; Feng, Xin

2017-04-26

In recent years, Wireless Sensor Networks with a Mobile Sink (WSN-MS) have been an active research topic due to the widespread use of mobile devices. However, how to get the balance between data delivery latency and energy consumption becomes a key issue of WSN-MS. In this paper, we study the clustering approach by jointly considering the Route planning for mobile sink and Clustering Problem (RCP) for static sensor nodes. We solve the RCP problem by using the minimum travel route clustering approach, which applies the minimum travel route of the mobile sink to guide the clustering process. We formulate the RCP problem as an Integer Non-Linear Programming (INLP) problem to shorten the travel route of the mobile sink under three constraints: the communication hops constraint, the travel route constraint and the loop avoidance constraint. We then propose an Imprecise Induction Algorithm (IIA) based on the property that the solution with a small hop count is more feasible than that with a large hop count. The IIA algorithm includes three processes: initializing travel route planning with a Traveling Salesman Problem (TSP) algorithm, transforming the cluster head to a cluster member and transforming the cluster member to a cluster head. Extensive experimental results show that the IIA algorithm could automatically adjust cluster heads according to the maximum hops parameter and plan a shorter travel route for the mobile sink. Compared with the Shortest Path Tree-based Data-Gathering Algorithm (SPT-DGA), the IIA algorithm has the characteristics of shorter route length, smaller cluster head count and faster convergence rate.

Virtual Network Embedding via Monte Carlo Tree Search.

PubMed

Haeri, Soroush; Trajkovic, Ljiljana

2018-02-01

Network virtualization helps overcome shortcomings of the current Internet architecture. The virtualized network architecture enables coexistence of multiple virtual networks (VNs) on an existing physical infrastructure. VN embedding (VNE) problem, which deals with the embedding of VN components onto a physical network, is known to be -hard. In this paper, we propose two VNE algorithms: MaVEn-M and MaVEn-S. MaVEn-M employs the multicommodity flow algorithm for virtual link mapping while MaVEn-S uses the shortest-path algorithm. They formalize the virtual node mapping problem by using the Markov decision process (MDP) framework and devise action policies (node mappings) for the proposed MDP using the Monte Carlo tree search algorithm. Service providers may adjust the execution time of the MaVEn algorithms based on the traffic load of VN requests. The objective of the algorithms is to maximize the profit of infrastructure providers. We develop a discrete event VNE simulator to implement and evaluate performance of MaVEn-M, MaVEn-S, and several recently proposed VNE algorithms. We introduce profitability as a new performance metric that captures both acceptance and revenue to cost ratios. Simulation results show that the proposed algorithms find more profitable solutions than the existing algorithms. Given additional computation time, they further improve embedding solutions.

Application of cellular automatons and ant algorithms in avionics

NASA Astrophysics Data System (ADS)

Kuznetsov, A. V.; Selvesiuk, N. I.; Platoshin, G. A.; Semenova, E. V.

2018-03-01

The paper considers two algorithms for searching quasi-optimal solutions of discrete optimization problems with regard to the tasks of avionics placing. The first one solves the problem of optimal placement of devices by installation locations, the second one is for the problem of finding the shortest route between devices. Solutions are constructed using a cellular automaton and the ant colony algorithm.

Towards a hybrid energy efficient multi-tree-based optimized routing protocol for wireless networks.

PubMed

Mitton, Nathalie; Razafindralambo, Tahiry; Simplot-Ryl, David; Stojmenovic, Ivan

2012-12-13

This paper considers the problem of designing power efficient routing with guaranteed delivery for sensor networks with unknown geographic locations. We propose HECTOR, a hybrid energy efficient tree-based optimized routing protocol, based on two sets of virtual coordinates. One set is based on rooted tree coordinates, and the other is based on hop distances toward several landmarks. In HECTOR, the node currently holding the packet forwards it to its neighbor that optimizes ratio of power cost over distance progress with landmark coordinates, among nodes that reduce landmark coordinates and do not increase distance in tree coordinates. If such a node does not exist, then forwarding is made to the neighbor that reduces tree-based distance only and optimizes power cost over tree distance progress ratio. We theoretically prove the packet delivery and propose an extension based on the use of multiple trees. Our simulations show the superiority of our algorithm over existing alternatives while guaranteeing delivery, and only up to 30% additional power compared to centralized shortest weighted path algorithm.

Authorship attribution based on Life-Like Network Automata

PubMed Central

Machicao, Jeaneth; Corrêa, Edilson A.; Miranda, Gisele H. B.; Amancio, Diego R.

2018-01-01

The authorship attribution is a problem of considerable practical and technical interest. Several methods have been designed to infer the authorship of disputed documents in multiple contexts. While traditional statistical methods based solely on word counts and related measurements have provided a simple, yet effective solution in particular cases; they are prone to manipulation. Recently, texts have been successfully modeled as networks, where words are represented by nodes linked according to textual similarity measurements. Such models are useful to identify informative topological patterns for the authorship recognition task. However, there is no consensus on which measurements should be used. Thus, we proposed a novel method to characterize text networks, by considering both topological and dynamical aspects of networks. Using concepts and methods from cellular automata theory, we devised a strategy to grasp informative spatio-temporal patterns from this model. Our experiments revealed an outperformance over structural analysis relying only on topological measurements, such as clustering coefficient, betweenness and shortest paths. The optimized results obtained here pave the way for a better characterization of textual networks. PMID:29566100

Towards a Hybrid Energy Efficient Multi-Tree-Based Optimized Routing Protocol for Wireless Networks

PubMed Central

Mitton, Nathalie; Razafindralambo, Tahiry; Simplot-Ryl, David; Stojmenovic, Ivan

2012-01-01

This paper considers the problem of designing power efficient routing with guaranteed delivery for sensor networks with unknown geographic locations. We propose HECTOR, a hybrid energy efficient tree-based optimized routing protocol, based on two sets of virtual coordinates. One set is based on rooted tree coordinates, and the other is based on hop distances toward several landmarks. In HECTOR, the node currently holding the packet forwards it to its neighbor that optimizes ratio of power cost over distance progress with landmark coordinates, among nodes that reduce landmark coordinates and do not increase distance in tree coordinates. If such a node does not exist, then forwarding is made to the neighbor that reduces tree-based distance only and optimizes power cost over tree distance progress ratio. We theoretically prove the packet delivery and propose an extension based on the use of multiple trees. Our simulations show the superiority of our algorithm over existing alternatives while guaranteeing delivery, and only up to 30% additional power compared to centralized shortest weighted path algorithm. PMID:23443398

A research framework for pharmacovigilance in health social media: Identification and evaluation of patient adverse drug event reports.

PubMed

Liu, Xiao; Chen, Hsinchun

2015-12-01

Social media offer insights of patients' medical problems such as drug side effects and treatment failures. Patient reports of adverse drug events from social media have great potential to improve current practice of pharmacovigilance. However, extracting patient adverse drug event reports from social media continues to be an important challenge for health informatics research. In this study, we develop a research framework with advanced natural language processing techniques for integrated and high-performance patient reported adverse drug event extraction. The framework consists of medical entity extraction for recognizing patient discussions of drug and events, adverse drug event extraction with shortest dependency path kernel based statistical learning method and semantic filtering with information from medical knowledge bases, and report source classification to tease out noise. To evaluate the proposed framework, a series of experiments were conducted on a test bed encompassing about postings from major diabetes and heart disease forums in the United States. The results reveal that each component of the framework significantly contributes to its overall effectiveness. Our framework significantly outperforms prior work. Published by Elsevier Inc.

Energetically optimal travel across terrain: visualizations and a new metric of geographic distance with anthropological applications

NASA Astrophysics Data System (ADS)

Wood, Brian M.; Wood, Zoë J.

2006-01-01

We present a visualization and computation tool for modeling the caloric cost of pedestrian travel across three dimensional terrains. This tool is being used in ongoing archaeological research that analyzes how costs of locomotion affect the spatial distribution of trails and artifacts across archaeological landscapes. Throughout human history, traveling by foot has been the most common form of transportation, and therefore analyses of pedestrian travel costs are important for understanding prehistoric patterns of resource acquisition, migration, trade, and political interaction. Traditionally, archaeologists have measured geographic proximity based on "as the crow flies" distance. We propose new methods for terrain visualization and analysis based on measuring paths of least caloric expense, calculated using well established metabolic equations. Our approach provides a human centered metric of geographic closeness, and overcomes significant limitations of available Geographic Information System (GIS) software. We demonstrate such path computations and visualizations applied to archaeological research questions. Our system includes tools to visualize: energetic cost surfaces, comparisons of the elevation profiles of shortest paths versus least cost paths, and the display of paths of least caloric effort on Digital Elevation Models (DEMs). These analysis tools can be applied to calculate and visualize 1) likely locations of prehistoric trails and 2) expected ratios of raw material types to be recovered at archaeological sites.

Integrated Flight Path Planning System and Flight Control System for Unmanned Helicopters

PubMed Central

Jan, Shau Shiun; Lin, Yu Hsiang

2011-01-01

This paper focuses on the design of an integrated navigation and guidance system for unmanned helicopters. The integrated navigation system comprises two systems: the Flight Path Planning System (FPPS) and the Flight Control System (FCS). The FPPS finds the shortest flight path by the A-Star (A*) algorithm in an adaptive manner for different flight conditions, and the FPPS can add a forbidden zone to stop the unmanned helicopter from crossing over into dangerous areas. In this paper, the FPPS computation time is reduced by the multi-resolution scheme, and the flight path quality is improved by the path smoothing methods. Meanwhile, the FCS includes the fuzzy inference systems (FISs) based on the fuzzy logic. By using expert knowledge and experience to train the FIS, the controller can operate the unmanned helicopter without dynamic models. The integrated system of the FPPS and the FCS is aimed at providing navigation and guidance to the mission destination and it is implemented by coupling the flight simulation software, X-Plane, and the computing software, MATLAB. Simulations are performed and shown in real time three-dimensional animations. Finally, the integrated system is demonstrated to work successfully in controlling the unmanned helicopter to operate in various terrains of a digital elevation model (DEM). PMID:22164029

Integrated flight path planning system and flight control system for unmanned helicopters.

PubMed

Jan, Shau Shiun; Lin, Yu Hsiang

2011-01-01

This paper focuses on the design of an integrated navigation and guidance system for unmanned helicopters. The integrated navigation system comprises two systems: the Flight Path Planning System (FPPS) and the Flight Control System (FCS). The FPPS finds the shortest flight path by the A-Star (A*) algorithm in an adaptive manner for different flight conditions, and the FPPS can add a forbidden zone to stop the unmanned helicopter from crossing over into dangerous areas. In this paper, the FPPS computation time is reduced by the multi-resolution scheme, and the flight path quality is improved by the path smoothing methods. Meanwhile, the FCS includes the fuzzy inference systems (FISs) based on the fuzzy logic. By using expert knowledge and experience to train the FIS, the controller can operate the unmanned helicopter without dynamic models. The integrated system of the FPPS and the FCS is aimed at providing navigation and guidance to the mission destination and it is implemented by coupling the flight simulation software, X-Plane, and the computing software, MATLAB. Simulations are performed and shown in real time three-dimensional animations. Finally, the integrated system is demonstrated to work successfully in controlling the unmanned helicopter to operate in various terrains of a digital elevation model (DEM).

Topological patterns in street networks of self-organized urban settlements

NASA Astrophysics Data System (ADS)

Buhl, J.; Gautrais, J.; Reeves, N.; Solé, R. V.; Valverde, S.; Kuntz, P.; Theraulaz, G.

2006-02-01

Many urban settlements result from a spatially distributed, decentralized building process. Here we analyze the topological patterns of organization of a large collection of such settlements using the approach of complex networks. The global efficiency (based on the inverse of shortest-path lengths), robustness to disconnections and cost (in terms of length) of these graphs is studied and their possible origins analyzed. A wide range of patterns is found, from tree-like settlements (highly vulnerable to random failures) to meshed urban patterns. The latter are shown to be more robust and efficient.

Osm-Oriented Method of Multimodal Route Planning

NASA Astrophysics Data System (ADS)

Li, X.; Wu, Q.; Chen, L.; Xiong, W.; Jing, N.

2015-07-01

With the increasing pervasiveness of basic facilitate of transportation and information, the need of multimodal route planning is becoming more essential in the fields of communication and transportation, urban planning, logistics management, etc. This article mainly described an OSM-oriented method of multimodal route planning. Firstly, it introduced how to extract the information we need from OSM data and build proper network model and storage model; then it analysed the accustomed cost standard adopted by most travellers; finally, we used shortest path algorithm to calculate the best route with multiple traffic means.

Automatic Generation of Issue Maps: Structured, Interactive Outputs for Complex Information Needs

DTIC Science & Technology

2012-09-01

much can result in behaviour similar to the shortest-path chains. 24 Ronald Goldman Neil Lewis Judge Lance Ito 1 1 1 1 1 0 0 0 1 1 1 1 1 1 1 jury...Connecting the Dots has also been explored in non-textual domains. The authors of [ Heath et al., 2010] propose building graphs, called Image Webs, to...could imagine a metro map summarizing a dataset of medical records. 2. Images: In [ Heath et al., 2010], Heath et al build graphs called Image Webs to rep

Improved efficient routing strategy on two-layer complex networks

NASA Astrophysics Data System (ADS)

Ma, Jinlong; Han, Weizhan; Guo, Qing; Zhang, Shuai; Wang, Junfang; Wang, Zhihao

2016-10-01

The traffic dynamics of multi-layer networks has become a hot research topic since many networks are comprised of two or more layers of subnetworks. Due to its low traffic capacity, the traditional shortest path routing (SPR) protocol is susceptible to congestion on two-layer complex networks. In this paper, we propose an efficient routing strategy named improved global awareness routing (IGAR) strategy which is based on the betweenness centrality of nodes in the two layers. With the proposed strategy, the routing paths can bypass hub nodes of both layers to enhance the transport efficiency. Simulation results show that the IGAR strategy can bring much better traffic capacity than the SPR and the global awareness routing (GAR) strategies. Because of the significantly improved traffic performance, this study is helpful to alleviate congestion of the two-layer complex networks.

A Model of Adding Relations in Multi-levels to a Formal Organization Structure with Two Subordinates

NASA Astrophysics Data System (ADS)

Sawada, Kiyoshi; Amano, Kazuyuki

2009-10-01

This paper proposes a model of adding relations in multi-levels to a formal organization structure with two subordinates such that the communication of information between every member in the organization becomes the most efficient. When edges between every pair of nodes with the same depth in L (L = 1, 2, …, H) levels are added to a complete binary tree of height H, an optimal set of depths {N1, N2, …, NL} (H⩾N1>N2> …>NL⩾1) 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 binary tree. It is shown that {N1, N2, …, NL}* = {H, H-1, …, H-L+1}.

Eccentric connectivity index of chemical trees

DOE Office of Scientific and Technical Information (OSTI.GOV)

Haoer, R. S., E-mail: raadsehen@gmail.com; Department of Mathematics, Faculty of Computer Sciences and Mathematics, University Of Kufa, Najaf; Atan, K. A., E-mail: kamel@upm.edu.my

Let G = (V, E) be a simple connected molecular graph. In such a simple molecular graph, vertices and edges are depicted atoms and chemical bonds respectively, we refer to the sets of vertices by V (G) and edges by E (G). If d(u, v) be distance between two vertices u, v ∈ V(G) and can be defined as the length of a shortest path joining them. Then, the eccentricity connectivity index (ECI) of a molecular graph G is ξ(G) = ∑{sub v∈V(G)} d(v) ec(v), where d(v) is degree of a vertex v ∈ V(G). ec(v) is the length ofmore » a greatest path linking to another vertex of v. In this study, we focus the general formula for the eccentricity connectivity index (ECI) of some chemical trees as alkenes.« less

Resolving multiple propagation paths in time of flight range cameras using direct and global separation methods

NASA Astrophysics Data System (ADS)

Whyte, Refael; Streeter, Lee; Cree, Michael J.; Dorrington, Adrian A.

2015-11-01

Time of flight (ToF) range cameras illuminate the scene with an amplitude-modulated continuous wave light source and measure the returning modulation envelopes: phase and amplitude. The phase change of the modulation envelope encodes the distance travelled. This technology suffers from measurement errors caused by multiple propagation paths from the light source to the receiving pixel. The multiple paths can be represented as the summation of a direct return, which is the return from the shortest path length, and a global return, which includes all other returns. We develop the use of a sinusoidal pattern from which a closed form solution for the direct and global returns can be computed in nine frames with the constraint that the global return is a spatially lower frequency than the illuminated pattern. In a demonstration on a scene constructed to have strong multipath interference, we find the direct return is not significantly different from the ground truth in 33/136 pixels tested; where for the full-field measurement, it is significantly different for every pixel tested. The variance in the estimated direct phase and amplitude increases by a factor of eight compared with the standard time of flight range camera technique.

Risk-Hedged Approach for Re-Routing Air Traffic Under Weather Uncertainty

NASA Technical Reports Server (NTRS)

Sadovsky, Alexander V.; Bilimoria, Karl D.

2016-01-01

This presentation corresponds to: our paper explores a new risk-hedged approach for re-routing air traffic around forecast convective weather. In this work, flying through a more likely weather instantiation is considered to pose a higher level of risk. Current operational practice strategically plans re-routes to avoid only the most likely (highest risk) weather instantiation, and then tactically makes any necessary adjustments as the weather evolves. The risk-hedged approach strategically plans re-routes by minimizing the risk-adjusted path length, incorporating multiple possible weather instantiations with associated likelihoods (risks). The resulting model is transparent and is readily analyzed for realism and treated with well-understood shortest-path algorithms. Risk-hedged re-routes are computed for some example weather instantiations. The main result is that in some scenarios, relative to an operational-practice proxy solution, the risk-hedged solution provides the benefits of lower risk as well as shorter path length. In other scenarios, the benefits of the risk-hedged solution are ambiguous, because the solution is characterized by a tradeoff between risk and path length. The risk-hedged solution can be executed in those scenarios where it provides a clear benefit over current operational practice.

New approaches to virtual environment surgery

NASA Technical Reports Server (NTRS)

Ross, M. D.; Twombly, A.; Lee, A. W.; Cheng, R.; Senger, S.

1999-01-01

This research focused on two main problems: 1) low cost, high fidelity stereoscopic imaging of complex tissues and organs; and 2) virtual cutting of tissue. A further objective was to develop these images and virtual tissue cutting methods for use in a telemedicine project that would connect remote sites using the Next Generation Internet. For goal one we used a CT scan of a human heart, a desktop PC with an OpenGL graphics accelerator card, and LCD stereoscopic glasses. Use of multiresolution meshes ranging from approximately 1,000,000 to 20,000 polygons speeded interactive rendering rates enormously while retaining general topography of the dataset. For goal two, we used a CT scan of an infant skull with premature closure of the right coronal suture, a Silicon Graphics Onyx workstation, a Fakespace Immersive WorkBench and CrystalEyes LCD glasses. The high fidelity mesh of the skull was reduced from one million to 50,000 polygons. The cut path was automatically calculated as the shortest distance along the mesh between a small number of hand selected vertices. The region outlined by the cut path was then separated from the skull and translated/rotated to assume a new position. The results indicate that widespread high fidelity imaging in virtual environment is possible using ordinary PC capabilities if appropriate mesh reduction methods are employed. The software cutting tool is applicable to heart and other organs for surgery planning, for training surgeons in a virtual environment, and for telemedicine purposes.

Towards an agent based traffic regulation and recommendation system for the on-road air quality control.

PubMed

Sadiq, Abderrahmane; El Fazziki, Abdelaziz; Ouarzazi, Jamal; Sadgal, Mohamed

2016-01-01

This paper presents an integrated and adaptive problem-solving approach to control the on-road air quality by modeling the road infrastructure, managing traffic based on pollution level and generating recommendations for road users. The aim is to reduce vehicle emissions in the most polluted road segments and optimizing the pollution levels. For this we propose the use of historical and real time pollution records and contextual data to calculate the air quality index on road networks and generate recommendations for reassigning traffic flow in order to improve the on-road air quality. The resulting air quality indexes are used in the system's traffic network generation, which the cartography is represented by a weighted graph. The weights evolve according to the pollution indexes and path properties and the graph is therefore dynamic. Furthermore, the systems use the available pollution data and meteorological records in order to predict the on-road pollutant levels by using an artificial neural network based prediction model. The proposed approach combines the benefits of multi-agent systems, Big data technology, machine learning tools and the available data sources. For the shortest path searching in the road network, we use the Dijkstra algorithm over Hadoop MapReduce framework. The use Hadoop framework in the data retrieve and analysis process has significantly improved the performance of the proposed system. Also, the agent technology allowed proposing a suitable solution in terms of robustness and agility.

Roads at risk - the impact of debris flows on road network reliability and vulnerability in southern Norway

NASA Astrophysics Data System (ADS)

Meyer, Nele Kristin; Schwanghart, Wolfgang; Korup, Oliver

2014-05-01

Norwegian's road network is frequently affected by debris flows. Both damage repair and traffic interruption generate high economic losses and necessitate a rigorous assessment of where losses are expected to be high and where preventive measures should be focused on. In recent studies, we have developed susceptibility and trigger probability maps that serve as input into a hazard calculation at the scale of first-order watersheds. Here we combine these results with graph theory to assess the impact of debris flows on the road network of southern Norway. Susceptibility and trigger probability are aggregated for individual road sections to form a reliability index that relates to the failure probability of a link that connects two network vertices, e.g., road junctions. We define link vulnerability as a function of traffic volume and additional link failure distance. Additional link failure distance is the extra length of the alternative path connecting the two associated link vertices in case the network link fails and is calculated by a shortest-path algorithm. The product of network reliability and vulnerability indices represent the risk index. High risk indices identify critical links for the Norwegian road network and are investigated in more detail. Scenarios demonstrating the impact of single or multiple debris flow events are run for the most important routes between seven large cities in southern Norway. First results show that the reliability of the road network is lowest in the central and north-western part of the study area. Road network vulnerability is highest in the mountainous regions in central southern Norway where the road density is low and in the vicinity of cities where the traffic volume is large. The scenarios indicate that city connections that have their shortest path via routes crossing the central part of the study area have the highest risk of route failure.

Complexity, information loss, and model building: from neuro- to cognitive dynamics

NASA Astrophysics Data System (ADS)

Arecchi, F. Tito

2007-06-01

A scientific problem described within a given code is mapped by a corresponding computational problem, We call complexity (algorithmic) the bit length of the shortest instruction which solves the problem. Deterministic chaos in general affects a dynamical systems making the corresponding problem experimentally and computationally heavy, since one must reset the initial conditions at a rate higher than that of information loss (Kolmogorov entropy). One can control chaos by adding to the system new degrees of freedom (information swapping: information lost by chaos is replaced by that arising from the new degrees of freedom). This implies a change of code, or a new augmented model. Within a single code, changing hypotheses is equivalent to fixing different sets of control parameters, each with a different a-priori probability, to be then confirmed and transformed to an a-posteriori probability via Bayes theorem. Sequential application of Bayes rule is nothing else than the Darwinian strategy in evolutionary biology. The sequence is a steepest ascent algorithm, which stops once maximum probability has been reached. At this point the hypothesis exploration stops. By changing code (and hence the set of relevant variables) one can start again to formulate new classes of hypotheses . We call semantic complexity the number of accessible scientific codes, or models, that describe a situation. It is however a fuzzy concept, in so far as this number changes due to interaction of the operator with the system under investigation. These considerations are illustrated with reference to a cognitive task, starting from synchronization of neuron arrays in a perceptual area and tracing the putative path toward a model building.

Three-dimensional curvilinear device reconstruction from two fluoroscopic views

NASA Astrophysics Data System (ADS)

Delmas, Charlotte; Berger, Marie-Odile; Kerrien, Erwan; Riddell, Cyril; Trousset, Yves; Anxionnat, René; Bracard, Serge

2015-03-01

In interventional radiology, navigating devices under the sole guidance of fluoroscopic images inside a complex architecture of tortuous and narrow vessels like the cerebral vascular tree is a difficult task. Visualizing the device in 3D could facilitate this navigation. For curvilinear devices such as guide-wires and catheters, a 3D reconstruction may be achieved using two simultaneous fluoroscopic views, as available on a biplane acquisition system. The purpose of this paper is to present a new automatic three-dimensional curve reconstruction method that has the potential to reconstruct complex 3D curves and does not require a perfect segmentation of the endovascular device. Using epipolar geometry, our algorithm translates the point correspondence problem into a segment correspondence problem. Candidate 3D curves can be formed and evaluated independently after identifying all possible combinations of compatible 3D segments. Correspondence is then inherently solved by looking in 3D space for the most coherent curve in terms of continuity and curvature. This problem can be cast into a graph problem where the most coherent curve corresponds to the shortest path of a weighted graph. We present quantitative results of curve reconstructions performed from numerically simulated projections of tortuous 3D curves extracted from cerebral vascular trees affected with brain arteriovenous malformations as well as fluoroscopic image pairs of a guide-wire from both phantom and clinical sets. Our method was able to select the correct 3D segments in 97.5% of simulated cases thus demonstrating its ability to handle complex 3D curves and can deal with imperfect 2D segmentation.

Investigation of random walks knee cartilage segmentation model using inter-observer reproducibility: Data from the osteoarthritis initiative.

PubMed

Hong-Seng, Gan; Sayuti, Khairil Amir; Karim, Ahmad Helmy Abdul

2017-01-01

Existing knee cartilage segmentation methods have reported several technical drawbacks. In essence, graph cuts remains highly susceptible to image noise despite extended research interest; active shape model is often constraint by the selection of training data while shortest path have demonstrated shortcut problem in the presence of weak boundary, which is a common problem in medical images. The aims of this study is to investigate the capability of random walks as knee cartilage segmentation method. Experts would scribble on knee cartilage image to initialize random walks segmentation. Then, reproducibility of the method is assessed against manual segmentation by using Dice Similarity Index. The evaluation consists of normal cartilage and diseased cartilage sections which is divided into whole and single cartilage categories. A total of 15 normal images and 10 osteoarthritic images were included. The results showed that random walks method has demonstrated high reproducibility in both normal cartilage (observer 1: 0.83±0.028 and observer 2: 0.82±0.026) and osteoarthritic cartilage (observer 1: 0.80±0.069 and observer 2: 0.83±0.029). Besides, results from both experts were found to be consistent with each other, suggesting the inter-observer variation is insignificant (Normal: P=0.21; Diseased: P=0.15). The proposed segmentation model has overcame technical problems reported by existing semi-automated techniques and demonstrated highly reproducible and consistent results against manual segmentation method.

Complex networks in confined comminution

NASA Astrophysics Data System (ADS)

Walker, David M.; Tordesillas, Antoinette; Einav, Itai; Small, Michael

2011-08-01

The physical process of confined comminution is investigated within the framework of complex networks. We first characterize the topology of the unweighted contact networks as generated by the confined comminution process. We find this process gives rise to an ultimate contact network which exhibits a scale-free degree distribution and small world properties. In particular, if viewed in the context of networks through which information travels along shortest paths, we find that the global average of the node vulnerability decreases as the comminution process continues, with individual node vulnerability correlating with grain size. A possible application to the design of synthetic networks (e.g., sensor networks) is highlighted. Next we turn our attention to the physics of the granular comminution process and examine force transmission with respect to the weighted contact networks, where each link is weighted by the inverse magnitude of the normal force acting at the associated contact. We find that the strong forces (i.e., force chains) are transmitted along pathways in the network which are mainly following shortest-path routing protocols, as typically found, for example, in communication systems. Motivated by our earlier studies of the building blocks for self-organization in dense granular systems, we also explore the properties of the minimal contact cycles. The distribution of the contact strain energy intensity of 4-cycle motifs in the ultimate state of the confined comminution process is shown to be consistent with a scale-free distribution with infinite variance, thereby suggesting that 4-cycle arrangements of grains are capable of storing vast amounts of energy in their contacts without breaking.

Complex Network Theory Applied to the Growth of Kuala Lumpur's Public Urban Rail Transit Network.

PubMed

Ding, Rui; Ujang, Norsidah; Hamid, Hussain Bin; Wu, Jianjun

2015-01-01

Recently, the number of studies involving complex network applications in transportation has increased steadily as scholars from various fields analyze traffic networks. Nonetheless, research on rail network growth is relatively rare. This research examines the evolution of the Public Urban Rail Transit Networks of Kuala Lumpur (PURTNoKL) based on complex network theory and covers both the topological structure of the rail system and future trends in network growth. In addition, network performance when facing different attack strategies is also assessed. Three topological network characteristics are considered: connections, clustering and centrality. In PURTNoKL, we found that the total number of nodes and edges exhibit a linear relationship and that the average degree stays within the interval [2.0488, 2.6774] with heavy-tailed distributions. The evolutionary process shows that the cumulative probability distribution (CPD) of degree and the average shortest path length show good fit with exponential distribution and normal distribution, respectively. Moreover, PURTNoKL exhibits clear cluster characteristics; most of the nodes have a 2-core value, and the CPDs of the centrality's closeness and betweenness follow a normal distribution function and an exponential distribution, respectively. Finally, we discuss four different types of network growth styles and the line extension process, which reveal that the rail network's growth is likely based on the nodes with the biggest lengths of the shortest path and that network protection should emphasize those nodes with the largest degrees and the highest betweenness values. This research may enhance the networkability of the rail system and better shape the future growth of public rail networks.

Influence of Time-Series Normalization, Number of Nodes, Connectivity and Graph Measure Selection on Seizure-Onset Zone Localization from Intracranial EEG.

PubMed

van Mierlo, Pieter; Lie, Octavian; Staljanssens, Willeke; Coito, Ana; Vulliémoz, Serge

2018-04-26

We investigated the influence of processing steps in the estimation of multivariate directed functional connectivity during seizures recorded with intracranial EEG (iEEG) on seizure-onset zone (SOZ) localization. We studied the effect of (i) the number of nodes, (ii) time-series normalization, (iii) the choice of multivariate time-varying connectivity measure: Adaptive Directed Transfer Function (ADTF) or Adaptive Partial Directed Coherence (APDC) and (iv) graph theory measure: outdegree or shortest path length. First, simulations were performed to quantify the influence of the various processing steps on the accuracy to localize the SOZ. Afterwards, the SOZ was estimated from a 113-electrodes iEEG seizure recording and compared with the resection that rendered the patient seizure-free. The simulations revealed that ADTF is preferred over APDC to localize the SOZ from ictal iEEG recordings. Normalizing the time series before analysis resulted in an increase of 25-35% of correctly localized SOZ, while adding more nodes to the connectivity analysis led to a moderate decrease of 10%, when comparing 128 with 32 input nodes. The real-seizure connectivity estimates localized the SOZ inside the resection area using the ADTF coupled to outdegree or shortest path length. Our study showed that normalizing the time-series is an important pre-processing step, while adding nodes to the analysis did only marginally affect the SOZ localization. The study shows that directed multivariate Granger-based connectivity analysis is feasible with many input nodes (> 100) and that normalization of the time-series before connectivity analysis is preferred.

Distribution of shortest path lengths in a class of node duplication network models

NASA Astrophysics Data System (ADS)

Steinbock, Chanania; Biham, Ofer; Katzav, Eytan

2017-09-01

We present analytical results for the distribution of shortest path lengths (DSPL) in a network growth model which evolves by node duplication (ND). The model captures essential properties of the structure and growth dynamics of social networks, acquaintance networks, and scientific citation networks, where duplication mechanisms play a major role. Starting from an initial seed network, at each time step a random node, referred to as a mother node, is selected for duplication. Its daughter node is added to the network, forming a link to the mother node, and with probability p to each one of its neighbors. The degree distribution of the resulting network turns out to follow a power-law distribution, thus the ND network is a scale-free network. To calculate the DSPL we derive a master equation for the time evolution of the probability Pt(L =ℓ ) , ℓ =1 ,2 ,⋯ , where L is the distance between a pair of nodes and t is the time. Finding an exact analytical solution of the master equation, we obtain a closed form expression for Pt(L =ℓ ) . The mean distance 〈L〉 t and the diameter Δt are found to scale like lnt , namely, the ND network is a small-world network. The variance of the DSPL is also found to scale like lnt . Interestingly, the mean distance and the diameter exhibit properties of a small-world network, rather than the ultrasmall-world network behavior observed in other scale-free networks, in which 〈L〉 t˜lnlnt .

An Adaptive Clustering Approach Based on Minimum Travel Route Planning for Wireless Sensor Networks with a Mobile Sink

PubMed Central

Tang, Jiqiang; Yang, Wu; Zhu, Lingyun; Wang, Dong; Feng, Xin

2017-01-01

In recent years, Wireless Sensor Networks with a Mobile Sink (WSN-MS) have been an active research topic due to the widespread use of mobile devices. However, how to get the balance between data delivery latency and energy consumption becomes a key issue of WSN-MS. In this paper, we study the clustering approach by jointly considering the Route planning for mobile sink and Clustering Problem (RCP) for static sensor nodes. We solve the RCP problem by using the minimum travel route clustering approach, which applies the minimum travel route of the mobile sink to guide the clustering process. We formulate the RCP problem as an Integer Non-Linear Programming (INLP) problem to shorten the travel route of the mobile sink under three constraints: the communication hops constraint, the travel route constraint and the loop avoidance constraint. We then propose an Imprecise Induction Algorithm (IIA) based on the property that the solution with a small hop count is more feasible than that with a large hop count. The IIA algorithm includes three processes: initializing travel route planning with a Traveling Salesman Problem (TSP) algorithm, transforming the cluster head to a cluster member and transforming the cluster member to a cluster head. Extensive experimental results show that the IIA algorithm could automatically adjust cluster heads according to the maximum hops parameter and plan a shorter travel route for the mobile sink. Compared with the Shortest Path Tree-based Data-Gathering Algorithm (SPT-DGA), the IIA algorithm has the characteristics of shorter route length, smaller cluster head count and faster convergence rate. PMID:28445434

Fuzzy logic and A* algorithm implementation on goat foraging games

NASA Astrophysics Data System (ADS)

Harsani, P.; Mulyana, I.; Zakaria, D.

2018-03-01

Goat foraging is one of the games that apply the search techniques within the scope of artificial intelligence. This game involves several actors including players and enemies. The method used in this research is fuzzy logic and Algorithm A*. Fuzzy logic is used to determine enemy behaviour. The A* algorithm is used to search for the shortest path. There are two input variables: the distance between the player and the enemy and the anger level of the goat. The output variable that has been defined is the enemy behaviour. The A* algorithm is used to determine the closest path between the player and the enemy and define the enemy's escape path to avoid the player. There are 4 types of enemies namely farmers, planters, farmers and sellers of plants. Players are goats that aims to find a meal that is a plant. In this game goats aim to spend grass in the garden in the form of a maze while avoiding the enemy. The game provides an application of artificial intelligence and is made in four difficulty levels.

A Hybrid Computational Method for the Discovery of Novel Reproduction-Related Genes

PubMed Central

Chen, Lei; Chu, Chen; Kong, Xiangyin; Huang, Guohua; Huang, Tao; Cai, Yu-Dong

2015-01-01

Uncovering the molecular mechanisms underlying reproduction is of great importance to infertility treatment and to the generation of healthy offspring. In this study, we discovered novel reproduction-related genes with a hybrid computational method, integrating three different types of method, which offered new clues for further reproduction research. This method was first executed on a weighted graph, constructed based on known protein-protein interactions, to search the shortest paths connecting any two known reproduction-related genes. Genes occurring in these paths were deemed to have a special relationship with reproduction. These newly discovered genes were filtered with a randomization test. Then, the remaining genes were further selected according to their associations with known reproduction-related genes measured by protein-protein interaction score and alignment score obtained by BLAST. The in-depth analysis of the high confidence novel reproduction genes revealed hidden mechanisms of reproduction and provided guidelines for further experimental validations. PMID:25768094

A hybrid computational method for the discovery of novel reproduction-related genes.

PubMed

Chen, Lei; Chu, Chen; Kong, Xiangyin; Huang, Guohua; Huang, Tao; Cai, Yu-Dong

2015-01-01

Uncovering the molecular mechanisms underlying reproduction is of great importance to infertility treatment and to the generation of healthy offspring. In this study, we discovered novel reproduction-related genes with a hybrid computational method, integrating three different types of method, which offered new clues for further reproduction research. This method was first executed on a weighted graph, constructed based on known protein-protein interactions, to search the shortest paths connecting any two known reproduction-related genes. Genes occurring in these paths were deemed to have a special relationship with reproduction. These newly discovered genes were filtered with a randomization test. Then, the remaining genes were further selected according to their associations with known reproduction-related genes measured by protein-protein interaction score and alignment score obtained by BLAST. The in-depth analysis of the high confidence novel reproduction genes revealed hidden mechanisms of reproduction and provided guidelines for further experimental validations.

Guiding brine shrimp through mazes by solving reaction diffusion equations

NASA Astrophysics Data System (ADS)

Singal, Krishma; Fenton, Flavio

Excitable systems driven by reaction diffusion equations have been shown to not only find solutions to mazes but to also to find the shortest path between the beginning and the end of the maze. In this talk we describe how we can use the Fitzhugh-Nagumo model, a generic model for excitable media, to solve a maze by varying the basin of attraction of its two fixed points. We demonstrate how two dimensional mazes are solved numerically using a Java Applet and then accelerated to run in real time by using graphic processors (GPUs). An application of this work is shown by guiding phototactic brine shrimp through a maze solved by the algorithm. Once the path is obtained, an Arduino directs the shrimp through the maze using lights from LEDs placed at the floor of the Maze. This method running in real time could be eventually used for guiding robots and cars through traffic.

Efficient packet transportation on complex networks with nonuniform node capacity distribution

NASA Astrophysics Data System (ADS)

He, Xuan; Niu, Kai; He, Zhiqiang; Lin, Jiaru; Jiang, Zhong-Yuan

2015-03-01

Provided that node delivery capacity may be not uniformly distributed in many realistic networks, we present a node delivery capacity distribution in which each node capacity is composed of uniform fraction and degree related proportion. Based on the node delivery capacity distribution, we construct a novel routing mechanism called efficient weighted routing (EWR) strategy to enhance network traffic capacity and transportation efficiency. Compared with the shortest path routing and the efficient routing strategies, the EWR achieves the highest traffic capacity. After investigating average path length, network diameter, maximum efficient betweenness, average efficient betweenness, average travel time and average traffic load under extensive simulations, it indicates that the EWR appears to be a very effective routing method. The idea of this routing mechanism gives us a good insight into network science research. The practical use of this work is prospective in some real complex systems such as the Internet.

On the existence of binary simplex codes. [using combinatorial construction

NASA Technical Reports Server (NTRS)

Taylor, H.

1977-01-01

Using a simple combinatorial construction, the existence of a binary simplex code with m codewords for all m is greater than or equal to 1 is proved. The problem of the shortest possible length is left open.

Research on Crowdsourcing Emergency Information Extraction of Based on Events' Frame

NASA Astrophysics Data System (ADS)

Yang, Bo; Wang, Jizhou; Ma, Weijun; Mao, Xi

2018-01-01

At present, the common information extraction method cannot extract the structured emergency event information accurately; the general information retrieval tool cannot completely identify the emergency geographic information; these ways also do not have an accurate assessment of these results of distilling. So, this paper proposes an emergency information collection technology based on event framework. This technique is to solve the problem of emergency information picking. It mainly includes emergency information extraction model (EIEM), complete address recognition method (CARM) and the accuracy evaluation model of emergency information (AEMEI). EIEM can be structured to extract emergency information and complements the lack of network data acquisition in emergency mapping. CARM uses a hierarchical model and the shortest path algorithm and allows the toponomy pieces to be joined as a full address. AEMEI analyzes the results of the emergency event and summarizes the advantages and disadvantages of the event framework. Experiments show that event frame technology can solve the problem of emergency information drawing and provides reference cases for other applications. When the emergency disaster is about to occur, the relevant departments query emergency's data that has occurred in the past. They can make arrangements ahead of schedule which defense and reducing disaster. The technology decreases the number of casualties and property damage in the country and world. This is of great significance to the state and society.

Resilience-based optimal design of water distribution network

NASA Astrophysics Data System (ADS)

Suribabu, C. R.

2017-11-01

Optimal design of water distribution network is generally aimed to minimize the capital cost of the investments on tanks, pipes, pumps, and other appurtenances. Minimizing the cost of pipes is usually considered as a prime objective as its proportion in capital cost of the water distribution system project is very high. However, minimizing the capital cost of the pipeline alone may result in economical network configuration, but it may not be a promising solution in terms of resilience point of view. Resilience of the water distribution network has been considered as one of the popular surrogate measures to address ability of network to withstand failure scenarios. To improve the resiliency of the network, the pipe network optimization can be performed with two objectives, namely minimizing the capital cost as first objective and maximizing resilience measure of the configuration as secondary objective. In the present work, these two objectives are combined as single objective and optimization problem is solved by differential evolution technique. The paper illustrates the procedure for normalizing the objective functions having distinct metrics. Two of the existing resilience indices and power efficiency are considered for optimal design of water distribution network. The proposed normalized objective function is found to be efficient under weighted method of handling multi-objective water distribution design problem. The numerical results of the design indicate the importance of sizing pipe telescopically along shortest path of flow to have enhanced resiliency indices.

Evaluation of concurrent priority queue algorithms. Technical report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huang, Q.

1991-02-01

The priority queue is a fundamental data structure that is used in a large variety of parallel algorithms, such as multiprocessor scheduling and parallel best-first search of state-space graphs. This thesis addresses the design and experimental evaluation of two novel concurrent priority queues: a parallel Fibonacci heap and a concurrent priority pool, and compares them with the concurrent binary heap. The parallel Fibonacci heap is based on the sequential Fibonacci heap, which is theoretically the most efficient data structure for sequential priority queues. This scheme not only preserves the efficient operation time bounds of its sequential counterpart, but also hasmore » very low contention by distributing locks over the entire data structure. The experimental results show its linearly scalable throughput and speedup up to as many processors as tested (currently 18). A concurrent access scheme for a doubly linked list is described as part of the implementation of the parallel Fibonacci heap. The concurrent priority pool is based on the concurrent B-tree and the concurrent pool. The concurrent priority pool has the highest throughput among the priority queues studied. Like the parallel Fibonacci heap, the concurrent priority pool scales linearly up to as many processors as tested. The priority queues are evaluated in terms of throughput and speedup. Some applications of concurrent priority queues such as the vertex cover problem and the single source shortest path problem are tested.« less

Correlation based networks of equity returns sampled at different time horizons

NASA Astrophysics Data System (ADS)

Tumminello, M.; di Matteo, T.; Aste, T.; Mantegna, R. N.

2007-01-01

We investigate the planar maximally filtered graphs of the portfolio of the 300 most capitalized stocks traded at the New York Stock Exchange during the time period 2001 2003. Topological properties such as the average length of shortest paths, the betweenness and the degree are computed on different planar maximally filtered graphs generated by sampling the returns at different time horizons ranging from 5 min up to one trading day. This analysis confirms that the selected stocks compose a hierarchical system progressively structuring as the sampling time horizon increases. Finally, a cluster formation, associated to economic sectors, is quantitatively investigated.

Link prediction based on local community properties

NASA Astrophysics Data System (ADS)

Yang, Xu-Hua; Zhang, Hai-Feng; Ling, Fei; Cheng, Zhi; Weng, Guo-Qing; Huang, Yu-Jiao

2016-09-01

The link prediction algorithm is one of the key technologies to reveal the inherent rule of network evolution. This paper proposes a novel link prediction algorithm based on the properties of the local community, which is composed of the common neighbor nodes of any two nodes in the network and the links between these nodes. By referring to the node degree and the condition of assortativity or disassortativity in a network, we comprehensively consider the effect of the shortest path and edge clustering coefficient within the local community on node similarity. We numerically show the proposed method provide good link prediction results.

Automatic Authorship Detection Using Textual Patterns Extracted from Integrated Syntactic Graphs

PubMed Central

Gómez-Adorno, Helena; Sidorov, Grigori; Pinto, David; Vilariño, Darnes; Gelbukh, Alexander

2016-01-01

We apply the integrated syntactic graph feature extraction methodology to the task of automatic authorship detection. This graph-based representation allows integrating different levels of language description into a single structure. We extract textual patterns based on features obtained from shortest path walks over integrated syntactic graphs and apply them to determine the authors of documents. On average, our method outperforms the state of the art approaches and gives consistently high results across different corpora, unlike existing methods. Our results show that our textual patterns are useful for the task of authorship attribution. PMID:27589740

An Ant Colony Optimization algorithm for solving the fixed destination multi-depot multiple traveling salesman problem with non-random parameters

NASA Astrophysics Data System (ADS)

Ramadhani, T.; Hertono, G. F.; Handari, B. D.

2017-07-01

The Multiple Traveling Salesman Problem (MTSP) is the extension of the Traveling Salesman Problem (TSP) in which the shortest routes of m salesmen all of which start and finish in a single city (depot) will be determined. If there is more than one depot and salesmen start from and return to the same depot, then the problem is called Fixed Destination Multi-depot Multiple Traveling Salesman Problem (MMTSP). In this paper, MMTSP will be solved using the Ant Colony Optimization (ACO) algorithm. ACO is a metaheuristic optimization algorithm which is derived from the behavior of ants in finding the shortest route(s) from the anthill to a form of nourishment. In solving the MMTSP, the algorithm is observed with respect to different chosen cities as depots and non-randomly three parameters of MMTSP: m, K, L, those represents the number of salesmen, the fewest cities that must be visited by a salesman, and the most number of cities that can be visited by a salesman, respectively. The implementation is observed with four dataset from TSPLIB. The results show that the different chosen cities as depots and the three parameters of MMTSP, in which m is the most important parameter, affect the solution.

Fuzzy Hungarian Method for Solving Intuitionistic Fuzzy Travelling Salesman Problem

NASA Astrophysics Data System (ADS)

Prabakaran, K.; Ganesan, K.

2018-04-01

The travelling salesman problem is to identify the shortest route that the salesman journey all the places and return the starting place with minimum cost. We develop a fuzzy version of Hungarian algorithm for the solution of intuitionistic fuzzy travelling salesman problem using triangular intuitionistic fuzzy numbers without changing them to classical travelling salesman problem. The purposed method is easy to empathize and to implement for finding solution of intuitionistic travelling salesman problem happening in real life situations. To illustrate the proposed method numerical example are provided.

Spectrum efficient distance-adaptive paths for fixed and fixed-alternate routing in elastic optical networks

NASA Astrophysics Data System (ADS)

Agrawal, Anuj; Bhatia, Vimal; Prakash, Shashi

2018-01-01

Efficient utilization of spectrum is a key concern in the soon to be deployed elastic optical networks (EONs). To perform routing in EONs, various fixed routing (FR), and fixed-alternate routing (FAR) schemes are ubiquitously used. FR, and FAR schemes calculate a fixed route, and a prioritized list of a number of alternate routes, respectively, between different pairs of origin o and target t nodes in the network. The route calculation performed using FR and FAR schemes is predominantly based on either the physical distance, known as k -shortest paths (KSP), or on the hop count (HC). For survivable optical networks, FAR usually calculates link-disjoint (LD) paths. These conventional routing schemes have been efficiently used for decades in communication networks. However, in this paper, it has been demonstrated that these commonly used routing schemes cannot utilize the network spectral resources optimally in the newly introduced EONs. Thus, we propose a new routing scheme for EON, namely, k -distance adaptive paths (KDAP) that efficiently utilizes the benefit of distance-adaptive modulation, and bit rate-adaptive superchannel capability inherited by EON to improve spectrum utilization. In the proposed KDAP, routes are found and prioritized on the basis of bit rate, distance, spectrum granularity, and the number of links used for a particular route. To evaluate the performance of KSP, HC, LD, and the proposed KDAP, simulations have been performed for three different sized networks, namely, 7-node test network (TEST7), NSFNET, and 24-node US backbone network (UBN24). We comprehensively assess the performance of various conventional, and the proposed routing schemes by solving both the RSA and the dual RSA problems under homogeneous and heterogeneous traffic requirements. Simulation results demonstrate that there is a variation amongst the performance of KSP, HC, and LD, depending on the o - t pair, and the network topology and its connectivity. However, the proposed KDAP always performs better for all the considered networks and traffic scenarios, as compared to the conventional routing schemes, namely, KSP, HC, and LD. The proposed KDAP achieves up to 60 % , and 10.46 % improvement in terms of spectrum utilization, and resource utilization ratio, respectively, over the conventional routing schemes.

Fast Transformation of Temporal Plans for Efficient Execution

NASA Technical Reports Server (NTRS)

Tsamardinos, Ioannis; Muscettola, Nicola; Morris, Paul

1998-01-01

Temporal plans permit significant flexibility in specifying the occurrence time of events. Plan execution can make good use of that flexibility. However, the advantage of execution flexibility is counterbalanced by the cost during execution of propagating the time of occurrence of events throughout the flexible plan. To minimize execution latency, this propagation needs to be very efficient. Previous work showed that every temporal plan can be reformulated as a dispatchable plan, i.e., one for which propagation to immediate neighbors is sufficient. A simple algorithm was given that finds a dispatchable plan with a minimum number of edges in cubic time and quadratic space. In this paper, we focus on the efficiency of the reformulation process, and improve on that result. A new algorithm is presented that uses linear space and has time complexity equivalent to Johnson s algorithm for all-pairs shortest-path problems. Experimental evidence confirms the practical effectiveness of the new algorithm. For example, on a large commercial application, the performance is improved by at least two orders of magnitude. We further show that the dispatchable plan, already minimal in the total number of edges, can also be made minimal in the maximum number of edges incoming or outgoing at any node.

Selective randomized load balancing and mesh networks with changing demands

NASA Astrophysics Data System (ADS)

Shepherd, F. B.; Winzer, P. J.

2006-05-01

We consider the problem of building cost-effective networks that are robust to dynamic changes in demand patterns. We compare several architectures using demand-oblivious routing strategies. Traditional approaches include single-hop architectures based on a (static or dynamic) circuit-switched core infrastructure and multihop (packet-switched) architectures based on point-to-point circuits in the core. To address demand uncertainty, we seek minimum cost networks that can carry the class of hose demand matrices. Apart from shortest-path routing, Valiant's randomized load balancing (RLB), and virtual private network (VPN) tree routing, we propose a third, highly attractive approach: selective randomized load balancing (SRLB). This is a blend of dual-hop hub routing and randomized load balancing that combines the advantages of both architectures in terms of network cost, delay, and delay jitter. In particular, we give empirical analyses for the cost (in terms of transport and switching equipment) for the discussed architectures, based on three representative carrier networks. Of these three networks, SRLB maintains the resilience properties of RLB while achieving significant cost reduction over all other architectures, including RLB and multihop Internet protocol/multiprotocol label switching (IP/MPLS) networks using VPN-tree routing.

When Dijkstra Meets Vanishing Point: A Stereo Vision Approach for Road Detection.

PubMed

Zhang, Yigong; Su, Yingna; Yang, Jian; Ponce, Jean; Kong, Hui

2018-05-01

In this paper, we propose a vanishing-point constrained Dijkstra road model for road detection in a stereo-vision paradigm. First, the stereo-camera is used to generate the u- and v-disparity maps of road image, from which the horizon can be extracted. With the horizon and ground region constraints, we can robustly locate the vanishing point of road region. Second, a weighted graph is constructed using all pixels of the image, and the detected vanishing point is treated as the source node of the graph. By computing a vanishing-point constrained Dijkstra minimum-cost map, where both disparity and gradient of gray image are used to calculate cost between two neighbor pixels, the problem of detecting road borders in image is transformed into that of finding two shortest paths that originate from the vanishing point to two pixels in the last row of image. The proposed approach has been implemented and tested over 2600 grayscale images of different road scenes in the KITTI data set. The experimental results demonstrate that this training-free approach can detect horizon, vanishing point, and road regions very accurately and robustly. It can achieve promising performance.

Inferring anatomical therapeutic chemical (ATC) class of drugs using shortest path and random walk with restart algorithms.

PubMed

Chen, Lei; Liu, Tao; Zhao, Xian

2018-06-01

The anatomical therapeutic chemical (ATC) classification system is a widely accepted drug classification scheme. This system comprises five levels and includes several classes in each level. Drugs are classified into classes according to their therapeutic effects and characteristics. The first level includes 14 main classes. In this study, we proposed two network-based models to infer novel potential chemicals deemed to belong in the first level of ATC classification. To build these models, two large chemical networks were constructed using the chemical-chemical interaction information retrieved from the Search Tool for Interactions of Chemicals (STITCH). Two classic network algorithms, shortest path (SP) and random walk with restart (RWR) algorithms, were executed on the corresponding network to mine novel chemicals for each ATC class using the validated drugs in a class as seed nodes. Then, the obtained chemicals yielded by these two algorithms were further evaluated by a permutation test and an association test. The former can exclude chemicals produced by the structure of the network, i.e., false positive discoveries. By contrast, the latter identifies the most important chemicals that have strong associations with the ATC class. Comparisons indicated that the two models can provide quite dissimilar results, suggesting that the results yielded by one model can be essential supplements for those obtained by the other model. In addition, several representative inferred chemicals were analyzed to confirm the reliability of the results generated by the two models. This article is part of a Special Issue entitled: Accelerating Precision Medicine through Genetic and Genomic Big Data Analysis edited by Yudong Cai & Tao Huang. Copyright © 2017 Elsevier B.V. All rights reserved.

Fully-automated segmentation of fluid regions in exudative age-related macular degeneration subjects: Kernel graph cut in neutrosophic domain

PubMed Central

Rashno, Abdolreza; Nazari, Behzad; Koozekanani, Dara D.; Drayna, Paul M.; Sadri, Saeed; Rabbani, Hossein

2017-01-01

A fully-automated method based on graph shortest path, graph cut and neutrosophic (NS) sets is presented for fluid segmentation in OCT volumes for exudative age related macular degeneration (EAMD) subjects. The proposed method includes three main steps: 1) The inner limiting membrane (ILM) and the retinal pigment epithelium (RPE) layers are segmented using proposed methods based on graph shortest path in NS domain. A flattened RPE boundary is calculated such that all three types of fluid regions, intra-retinal, sub-retinal and sub-RPE, are located above it. 2) Seed points for fluid (object) and tissue (background) are initialized for graph cut by the proposed automated method. 3) A new cost function is proposed in kernel space, and is minimized with max-flow/min-cut algorithms, leading to a binary segmentation. Important properties of the proposed steps are proven and quantitative performance of each step is analyzed separately. The proposed method is evaluated using a publicly available dataset referred as Optima and a local dataset from the UMN clinic. For fluid segmentation in 2D individual slices, the proposed method outperforms the previously proposed methods by 18%, 21% with respect to the dice coefficient and sensitivity, respectively, on the Optima dataset, and by 16%, 11% and 12% with respect to the dice coefficient, sensitivity and precision, respectively, on the local UMN dataset. Finally, for 3D fluid volume segmentation, the proposed method achieves true positive rate (TPR) and false positive rate (FPR) of 90% and 0.74%, respectively, with a correlation of 95% between automated and expert manual segmentations using linear regression analysis. PMID:29059257

Seismic wavefield propagation in 2D anisotropic media: Ray theory versus wave-equation simulation

NASA Astrophysics Data System (ADS)

Bai, Chao-ying; Hu, Guang-yi; Zhang, Yan-teng; Li, Zhong-sheng

2014-05-01

Despite the ray theory that is based on the high frequency assumption of the elastic wave-equation, the ray theory and the wave-equation simulation methods should be mutually proof of each other and hence jointly developed, but in fact parallel independent progressively. For this reason, in this paper we try an alternative way to mutually verify and test the computational accuracy and the solution correctness of both the ray theory (the multistage irregular shortest-path method) and the wave-equation simulation method (both the staggered finite difference method and the pseudo-spectral method) in anisotropic VTI and TTI media. Through the analysis and comparison of wavefield snapshot, common source gather profile and synthetic seismogram, it is able not only to verify the accuracy and correctness of each of the methods at least for kinematic features, but also to thoroughly understand the kinematic and dynamic features of the wave propagation in anisotropic media. The results show that both the staggered finite difference method and the pseudo-spectral method are able to yield the same results even for complex anisotropic media (such as a fault model); the multistage irregular shortest-path method is capable of predicting similar kinematic features as the wave-equation simulation method does, which can be used to mutually test each other for methodology accuracy and solution correctness. In addition, with the aid of the ray tracing results, it is easy to identify the multi-phases (or multiples) in the wavefield snapshot, common source point gather seismic section and synthetic seismogram predicted by the wave-equation simulation method, which is a key issue for later seismic application.

Electrochemical immunosensors for Salmonella detection in food

USDA-ARS?s Scientific Manuscript database

Pathogen detection is a critical point for the identification and the prevention of problems related to food safety. Failures at detecting contaminations in food may cause outbreaks with drastic consequences to public health. In spite of the real need for obtaining analytical results in the shortest...

Predicting the continuum between corridors and barriers to animal movements using Step Selection Functions and Randomized Shortest Paths.

PubMed

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 outperforms models that assume either optimality or random walk. The proposed approach models the multiscale cognitive maps by which animals likely navigate real landscapes and generalizes the most common algorithms for identifying corridors. Because suboptimal, but non-random, movement strategies are likely widespread, our approach has the potential to predict more realistic corridor-barrier continua for a wide range of species. © 2015 The Authors. Journal of Animal Ecology © 2015 British Ecological Society.

A deterministic method for estimating free energy genetic network landscapes with applications to cell commitment and reprogramming paths.

PubMed

Olariu, Victor; Manesso, Erica; Peterson, Carsten

2017-06-01

Depicting developmental processes as movements in free energy genetic landscapes is an illustrative tool. However, exploring such landscapes to obtain quantitative or even qualitative predictions is hampered by the lack of free energy functions corresponding to the biochemical Michaelis-Menten or Hill rate equations for the dynamics. Being armed with energy landscapes defined by a network and its interactions would open up the possibility of swiftly identifying cell states and computing optimal paths, including those of cell reprogramming, thereby avoiding exhaustive trial-and-error simulations with rate equations for different parameter sets. It turns out that sigmoidal rate equations do have approximate free energy associations. With this replacement of rate equations, we develop a deterministic method for estimating the free energy surfaces of systems of interacting genes at different noise levels or temperatures. Once such free energy landscape estimates have been established, we adapt a shortest path algorithm to determine optimal routes in the landscapes. We explore the method on three circuits for haematopoiesis and embryonic stem cell development for commitment and reprogramming scenarios and illustrate how the method can be used to determine sequential steps for onsets of external factors, essential for efficient reprogramming.

Improved routing strategy based on gravitational field theory

NASA Astrophysics Data System (ADS)

Song, Hai-Quan; Guo, Jin

2015-10-01

Routing and path selection are crucial for many communication and logistic applications. We study the interaction between nodes and packets and establish a simple model for describing the attraction of the node to the packet in transmission process by using the gravitational field theory, considering the real and potential congestion of the nodes. On the basis of this model, we propose a gravitational field routing strategy that considers the attractions of all of the nodes on the travel path to the packet. In order to illustrate the efficiency of proposed routing algorithm, we introduce the order parameter to measure the throughput of the network by the critical value of phase transition from a free flow phase to a congested phase, and study the distribution of betweenness centrality and traffic jam. Simulations show that, compared with the shortest path routing strategy, the gravitational field routing strategy considerably enhances the throughput of the network and balances the traffic load, and nearly all of the nodes are used efficiently. Project supported by the Technology and Development Research Project of China Railway Corporation (Grant No. 2012X007-D) and the Key Program of Technology and Development Research Foundation of China Railway Corporation (Grant No. 2012X003-A).

A deterministic method for estimating free energy genetic network landscapes with applications to cell commitment and reprogramming paths

PubMed Central

Olariu, Victor; Manesso, Erica

2017-01-01

Depicting developmental processes as movements in free energy genetic landscapes is an illustrative tool. However, exploring such landscapes to obtain quantitative or even qualitative predictions is hampered by the lack of free energy functions corresponding to the biochemical Michaelis–Menten or Hill rate equations for the dynamics. Being armed with energy landscapes defined by a network and its interactions would open up the possibility of swiftly identifying cell states and computing optimal paths, including those of cell reprogramming, thereby avoiding exhaustive trial-and-error simulations with rate equations for different parameter sets. It turns out that sigmoidal rate equations do have approximate free energy associations. With this replacement of rate equations, we develop a deterministic method for estimating the free energy surfaces of systems of interacting genes at different noise levels or temperatures. Once such free energy landscape estimates have been established, we adapt a shortest path algorithm to determine optimal routes in the landscapes. We explore the method on three circuits for haematopoiesis and embryonic stem cell development for commitment and reprogramming scenarios and illustrate how the method can be used to determine sequential steps for onsets of external factors, essential for efficient reprogramming. PMID:28680655

Optimization of the time-dependent traveling salesman problem with Monte Carlo methods.

PubMed

Bentner, J; Bauer, G; Obermair, G M; Morgenstern, I; Schneider, J

2001-09-01

A problem often considered in operations research and computational physics is the traveling salesman problem, in which a traveling salesperson has to find the shortest closed tour between a certain set of cities. This problem has been extended to more realistic scenarios, e.g., the "real" traveling salesperson has to take rush hours into consideration. We will show how this extended problem is treated with physical optimization algorithms. We will present results for a specific instance of Reinelt's library TSPLIB95, in which we define a zone with traffic jams in the afternoon.

Networks model of the East Turkistan terrorism

NASA Astrophysics Data System (ADS)

Li, Ben-xian; Zhu, Jun-fang; Wang, Shun-guo

2015-02-01

The presence of the East Turkistan terrorist network in China can be traced back to the rebellions on the BAREN region in Xinjiang in April 1990. This article intends to research the East Turkistan networks in China and offer a panoramic view. The events, terrorists and their relationship are described using matrices. Then social network analysis is adopted to reveal the network type and the network structure characteristics. We also find the crucial terrorist leader. Ultimately, some results show that the East Turkistan network has big hub nodes and small shortest path, and that the network follows a pattern of small world network with hierarchical structure.

Multilayered complex network datasets for three supply chain network archetypes on an urban road grid.

PubMed

Viljoen, Nadia M; Joubert, Johan W

2018-02-01

This article presents the multilayered complex network formulation for three different supply chain network archetypes on an urban road grid and describes how 500 instances were randomly generated for each archetype. Both the supply chain network layer and the urban road network layer are directed unweighted networks. The shortest path set is calculated for each of the 1 500 experimental instances. The datasets are used to empirically explore the impact that the supply chain's dependence on the transport network has on its vulnerability in Viljoen and Joubert (2017) [1]. The datasets are publicly available on Mendeley (Joubert and Viljoen, 2017) [2].

Topology of the conceptual network of language

NASA Astrophysics Data System (ADS)

Motter, Adilson E.; de Moura, Alessandro P.; Lai, Ying-Cheng; Dasgupta, Partha

2002-06-01

We define two words in a language to be connected if they express similar concepts. The network of connections among the many thousands of words that make up a language is important not only for the study of the structure and evolution of languages, but also for cognitive science. We study this issue quantitatively, by mapping out the conceptual network of the English language, with the connections being defined by the entries in a Thesaurus dictionary. We find that this network presents a small-world structure, with an amazingly small average shortest path, and appears to exhibit an asymptotic scale-free feature with algebraic connectivity distribution.

An improved sampling method of complex network

NASA Astrophysics Data System (ADS)

Gao, Qi; Ding, Xintong; Pan, Feng; Li, Weixing

2014-12-01

Sampling subnet is an important topic of complex network research. Sampling methods influence the structure and characteristics of subnet. Random multiple snowball with Cohen (RMSC) process sampling which combines the advantages of random sampling and snowball sampling is proposed in this paper. It has the ability to explore global information and discover the local structure at the same time. The experiments indicate that this novel sampling method could keep the similarity between sampling subnet and original network on degree distribution, connectivity rate and average shortest path. This method is applicable to the situation where the prior knowledge about degree distribution of original network is not sufficient.

A graph-based network-vulnerability analysis system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Swiler, L.P.; Phillips, C.; Gaylor, T.

1998-05-03

This paper presents a graph based approach to network vulnerability analysis. The method is flexible, allowing analysis of attacks from both outside and inside the network. It can analyze risks to a specific network asset, or examine the universe of possible consequences following a successful attack. The analysis system requires as input a database of common attacks, broken into atomic steps, specific network configuration and topology information, and an attacker profile. The attack information is matched with the network configuration information and an attacker profile to create a superset attack graph. Nodes identify a stage of attack, for example themore » class of machines the attacker has accessed and the user privilege level he or she has compromised. The arcs in the attack graph represent attacks or stages of attacks. By assigning probabilities of success on the arcs or costs representing level of effort for the attacker, various graph algorithms such as shortest path algorithms can identify the attack paths with the highest probability of success.« less

A graph-based network-vulnerability analysis system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Swiler, L.P.; Phillips, C.; Gaylor, T.

1998-01-01

This report presents a graph-based approach to network vulnerability analysis. The method is flexible, allowing analysis of attacks from both outside and inside the network. It can analyze risks to a specific network asset, or examine the universe of possible consequences following a successful attack. The analysis system requires as input a database of common attacks, broken into atomic steps, specific network configuration and topology information, and an attacker profile. The attack information is matched with the network configuration information and an attacker profile to create a superset attack graph. Nodes identify a stage of attack, for example the classmore » of machines the attacker has accessed and the user privilege level he or she has compromised. The arcs in the attack graph represent attacks or stages of attacks. By assigning probabilities of success on the arcs or costs representing level-of-effort for the attacker, various graph algorithms such as shortest-path algorithms can identify the attack paths with the highest probability of success.« less

UMDR: Multi-Path Routing Protocol for Underwater Ad Hoc Networks with Directional Antenna

NASA Astrophysics Data System (ADS)

Yang, Jianmin; Liu, Songzuo; Liu, Qipei; Qiao, Gang

2018-01-01

This paper presents a new routing scheme for underwater ad hoc networks based on directional antennas. Ad hoc networks with directional antennas have become a hot research topic because of space reuse may increase networks capacity. At present, researchers have applied traditional self-organizing routing protocols (such as DSR, AODV) [1] [2] on this type of networks, and the routing scheme is based on the shortest path metric. However, such routing schemes often suffer from long transmission delays and frequent link fragmentation along the intermediate nodes of the selected route. This is caused by a unique feature of directional transmission, often called as “deafness”. In this paper, we take a different approach to explore the advantages of space reuse through multipath routing. This paper introduces the validity of the conventional routing scheme in underwater ad hoc networks with directional antennas, and presents a special design of multipath routing algorithm for directional transmission. The experimental results show a significant performance improvement in throughput and latency.

Cumulative slant path rain attenuation associated with COMSTAR beacon at 28.56 GHz for Wallops Island, Virginia

NASA Technical Reports Server (NTRS)

Goldhirsh, J.

1978-01-01

Yearly, monthly, and time of day fade statistics are presented and characterized. A 19.04 GHz yearly fade distribution, corresponding to a second COMSTAR beacon frequency, is predicted using the concept of effective path length, disdrometer, and rain rate results. The yearly attenuation and rain rate distributions follow with good approximation log normal variations for most fade and rain rate levels. Attenuations were exceeded for the longest and shortest periods of times for all fades in August and February, respectively. The eight hour time period showing the maximum and minimum number of minutes over the year for which fades exceeded 12 db were approximately between 1600 to 2400, and 0400 to 1200 hours, respectively. In employing the predictive method for obtaining the 19.04 GHz fade distribution, it is demonstrated theoretically that the ratio of attenuations at two frequencies is minimally dependent of raindrop size distribution providing these frequencies are not widely separated.

Thirty-Second Walk Test: Expansion of Normative Data.

PubMed

Lieberstein, Michael; Weingarten, Goldie; Vialu, Carlo; Itzkowitz, Adina; Doyle, Maura; Covino, Frank; Kaplan, Sandra L

2018-01-01

To collect 30-second walk test (30sWT) normative data on a large, diverse sample of school children developing typically, ages 5 to 13 years, and describe the influences of gender, body mass index, and path shape on distance walked. Five physical therapists administered the 30sWT on 1223 children developing typically (boys = 517, girls = 706) from 20 urban schools. Average distances (standard deviation) ranged from 139.1 (20.3) to 163.0 (18.6) ft; children aged 10 years walked the farthest and those aged 5 years the shortest. Distance steadily increased from ages 5 to 10 years, steadily decreased from ages 11 to 13 years; children aged 8, 9, and 10 years had statistical but not functionally meaningful gender differences. Body mass index and path shape had no meaningful effects. Distance and velocities are similar to prior studies. This study updated 30sWT normative values with a large, ethnically diverse, urban sample developing typically. Norms may be useful as part of a comprehensive examination.

Integrating shape into an interactive segmentation framework

NASA Astrophysics Data System (ADS)

Kamalakannan, S.; Bryant, B.; Sari-Sarraf, H.; Long, R.; Antani, S.; Thoma, G.

2013-02-01

This paper presents a novel interactive annotation toolbox which extends a well-known user-steered segmentation framework, namely Intelligent Scissors (IS). IS, posed as a shortest path problem, is essentially driven by lower level image based features. All the higher level knowledge about the problem domain is obtained from the user through mouse clicks. The proposed work integrates one higher level feature, namely shape up to a rigid transform, into the IS framework, thus reducing the burden on the user and the subjectivity involved in the annotation procedure, especially during instances of occlusions, broken edges, noise and spurious boundaries. The above mentioned scenarios are commonplace in medical image annotation applications and, hence, such a tool will be of immense help to the medical community. As a first step, an offline training procedure is performed in which a mean shape and the corresponding shape variance is computed by registering training shapes up to a rigid transform in a level-set framework. The user starts the interactive segmentation procedure by providing a training segment, which is a part of the target boundary. A partial shape matching scheme based on a scale-invariant curvature signature is employed in order to extract shape correspondences and subsequently predict the shape of the unsegmented target boundary. A `zone of confidence' is generated for the predicted boundary to accommodate shape variations. The method is evaluated on segmentation of digital chest x-ray images for lung annotation which is a crucial step in developing algorithms for screening Tuberculosis.

One-dimensional Gromov minimal filling problem

NASA Astrophysics Data System (ADS)

Ivanov, Alexandr O.; Tuzhilin, Alexey A.

2012-05-01

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.

UAV path planning using artificial potential field method updated by optimal control theory

NASA Astrophysics Data System (ADS)

Chen, Yong-bo; Luo, Guan-chen; Mei, Yue-song; Yu, Jian-qiao; Su, Xiao-long

2016-04-01

The unmanned aerial vehicle (UAV) path planning problem is an important assignment in the UAV mission planning. Based on the artificial potential field (APF) UAV path planning method, it is reconstructed into the constrained optimisation problem by introducing an additional control force. The constrained optimisation problem is translated into the unconstrained optimisation problem with the help of slack variables in this paper. The functional optimisation method is applied to reform this problem into an optimal control problem. The whole transformation process is deduced in detail, based on a discrete UAV dynamic model. Then, the path planning problem is solved with the help of the optimal control method. The path following process based on the six degrees of freedom simulation model of the quadrotor helicopters is introduced to verify the practicability of this method. Finally, the simulation results show that the improved method is more effective in planning path. In the planning space, the length of the calculated path is shorter and smoother than that using traditional APF method. In addition, the improved method can solve the dead point problem effectively.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schiefer, H., E-mail: johann.schiefer@kssg.ch; Peters, S.; Plasswilm, L.

Purpose: For stereotactic radiosurgery, the AAPM Report No. 54 [AAPM Task Group 42 (AAPM, 1995)] requires the overall stability of the isocenter (couch, gantry, and collimator) to be within a 1 mm radius. In reality, a rotating system has no rigid axis and thus no isocenter point which is fixed in space. As a consequence, the isocenter concept is reviewed here. It is the aim to develop a measurement method following the revised definitions. Methods: The mechanical isocenter is defined here by the point which rotates on the shortest path in the room coordinate system. The path is labeled asmore » “isocenter path.” Its center of gravity is assumed to be the mechanical isocenter. Following this definition, an image-based and radiation-free measurement method was developed. Multiple marker pairs in a plane perpendicular to the assumed gantry rotation axis of a linear accelerator are imaged with a smartphone application from several rotation angles. Each marker pair represents an independent measuring system. The room coordinates of the isocenter path and the mechanical isocenter are calculated based on the marker coordinates. The presented measurement method is by this means strictly focused on the mechanical isocenter. Results: The measurement result is available virtually immediately following completion of measurement. When 12 independent measurement systems are evaluated, the standard deviations of the isocenter path points and mechanical isocenter coordinates are 0.02 and 0.002 mm, respectively. Conclusions: The measurement is highly accurate, time efficient, and simple to adapt. It is therefore suitable for regular checks of the mechanical isocenter characteristics of the gantry and collimator rotation axis. When the isocenter path is reproducible and its extent is in the range of the needed geometrical accuracy, it should be taken into account in the planning process. This is especially true for stereotactic treatments and radiosurgery.« less

A 2-dimensional optical architecture for solving Hamiltonian path problem based on micro ring resonators

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).

Reference View Selection in DIBR-Based Multiview Coding.

PubMed

Maugey, Thomas; Petrazzuoli, Giovanni; Frossard, Pascal; Cagnazzo, Marco; Pesquet-Popescu, Beatrice

2016-04-01

Augmented reality, interactive navigation in 3D scenes, multiview video, and other emerging multimedia applications require large sets of images, hence larger data volumes and increased resources compared with traditional video services. The significant increase in the number of images in multiview systems leads to new challenging problems in data representation and data transmission to provide high quality of experience on resource-constrained environments. In order to reduce the size of the data, different multiview video compression strategies have been proposed recently. Most of them use the concept of reference or key views that are used to estimate other images when there is high correlation in the data set. In such coding schemes, the two following questions become fundamental: 1) how many reference views have to be chosen for keeping a good reconstruction quality under coding cost constraints? And 2) where to place these key views in the multiview data set? As these questions are largely overlooked in the literature, we study the reference view selection problem and propose an algorithm for the optimal selection of reference views in multiview coding systems. Based on a novel metric that measures the similarity between the views, we formulate an optimization problem for the positioning of the reference views, such that both the distortion of the view reconstruction and the coding rate cost are minimized. We solve this new problem with a shortest path algorithm that determines both the optimal number of reference views and their positions in the image set. We experimentally validate our solution in a practical multiview distributed coding system and in the standardized 3D-HEVC multiview coding scheme. We show that considering the 3D scene geometry in the reference view, positioning problem brings significant rate-distortion improvements and outperforms the traditional coding strategy that simply selects key frames based on the distance between cameras.

Design of physical and logical topologies with fault-tolerant ability in wavelength-routed optical network

NASA Astrophysics Data System (ADS)

Chen, Chunfeng; Liu, Hua; Fan, Ge

2005-02-01

In this paper we consider the problem of designing a network of optical cross-connects(OXCs) to provide end-to-end lightpath services to label switched routers (LSRs). Like some previous work, we select the number of OXCs as our objective. Compared with the previous studies, we take into account the fault-tolerant characteristic of logical topology. First of all, using a Prufer number randomly generated, we generate a tree. By adding some edges to the tree, we can obtain a physical topology which consists of a certain number of OXCs and fiber links connecting OXCs. It is notable that we for the first time limit the number of layers of the tree produced according to the method mentioned above. Then we design the logical topologies based on the physical topologies mentioned above. In principle, we will select the shortest path in addition to some consideration on the load balancing of links and the limitation owing to the SRLG. Notably, we implement the routing algorithm for the nodes in increasing order of the degree of the nodes. With regarding to the problem of the wavelength assignment, we adopt the heuristic algorithm of the graph coloring commonly used. It is clear our problem is computationally intractable especially when the scale of the network is large. We adopt the taboo search algorithm to find the near optimal solution to our objective. We present numerical results for up to 1000 LSRs and for a wide range of system parameters such as the number of wavelengths supported by each fiber link and traffic. The results indicate that it is possible to build large-scale optical networks with rich connectivity in a cost-effective manner, using relatively few but properly dimensioned OXCs.

Experimental evaluation of the certification-trail method

NASA Technical Reports Server (NTRS)

Sullivan, Gregory F.; Wilson, Dwight S.; Masson, Gerald M.; Itoh, Mamoru; Smith, Warren W.; Kay, Jonathan S.

1993-01-01

Certification trails are a recently introduced and promising approach to fault-detection and fault-tolerance. A comprehensive attempt to assess experimentally the performance and overall value of the method is reported. The method is applied to algorithms for the following problems: huffman tree, shortest path, minimum spanning tree, sorting, and convex hull. Our results reveal many cases in which an approach using certification-trails allows for significantly faster overall program execution time than a basic time redundancy-approach. Algorithms for the answer-validation problem for abstract data types were also examined. This kind of problem provides a basis for applying the certification-trail method to wide classes of algorithms. Answer-validation solutions for two types of priority queues were implemented and analyzed. In both cases, the algorithm which performs answer-validation is substantially faster than the original algorithm for computing the answer. Next, a probabilistic model and analysis which enables comparison between the certification-trail method and the time-redundancy approach were presented. The analysis reveals some substantial and sometimes surprising advantages for ther certification-trail method. Finally, the work our group performed on the design and implementation of fault injection testbeds for experimental analysis of the certification trail technique is discussed. This work employs two distinct methodologies, software fault injection (modification of instruction, data, and stack segments of programs on a Sun Sparcstation ELC and on an IBM 386 PC) and hardware fault injection (control, address, and data lines of a Motorola MC68000-based target system pulsed at logical zero/one values). Our results indicate the viability of the certification trail technique. It is also believed that the tools developed provide a solid base for additional exploration.

Be-safe travel, a web-based geographic application to explore safe-route in an area

NASA Astrophysics Data System (ADS)

Utamima, Amalia; Djunaidy, Arif

2017-08-01

In large cities in developing countries, the various forms of criminality are often found. For instance, the most prominent crimes in Surabaya, Indonesia is 3C, that is theft with violence (curas), theft by weighting (curat), and motor vehicle theft (curanmor). 3C case most often occurs on the highway and residential areas. Therefore, new entrants in an area should be aware of these kind of crimes. Route Planners System or route planning system such as Google Maps only consider the shortest distance in the calculation of the optimal route. The selection of the optimal path in this study not only consider the shortest distance, but also involves other factors, namely the security level. This research considers at the need for an application to recommend the safest road to be passed by the vehicle passengers while drive an area. This research propose Be-Safe Travel, a web-based application using Google API that can be accessed by people who like to drive in an area, but still lack of knowledge of the pathways which are safe from crime. Be-Safe Travel is not only useful for the new entrants, but also useful for delivery courier of valuables goods to go through the safest streets.

An Energy-Efficient Target-Tracking Strategy for Mobile Sensor Networks.

PubMed

Mahboubi, Hamid; Masoudimansour, Walid; Aghdam, Amir G; Sayrafian-Pour, Kamran

2017-02-01

In this paper, an energy-efficient strategy is proposed for tracking a moving target in an environment with obstacles, using a network of mobile sensors. Typically, the most dominant sources of energy consumption in a mobile sensor network are sensing, communication, and movement. The proposed algorithm first divides the field into a grid of sufficiently small cells. The grid is then represented by a graph whose edges are properly weighted to reflect the energy consumption of sensors. The proposed technique searches for near-optimal locations for the sensors in different time instants to route information from the target to destination, using a shortest path algorithm. Simulations confirm the efficacy of the proposed algorithm.

Fuzzy multi-objective chance-constrained programming model for hazardous materials transportation

NASA Astrophysics Data System (ADS)

Du, Jiaoman; Yu, Lean; Li, Xiang

2016-04-01

Hazardous materials transportation is an important and hot issue of public safety. Based on the shortest path model, this paper presents a fuzzy multi-objective programming model that minimizes the transportation risk to life, travel time and fuel consumption. First, we present the risk model, travel time model and fuel consumption model. Furthermore, we formulate a chance-constrained programming model within the framework of credibility theory, in which the lengths of arcs in the transportation network are assumed to be fuzzy variables. A hybrid intelligent algorithm integrating fuzzy simulation and genetic algorithm is designed for finding a satisfactory solution. Finally, some numerical examples are given to demonstrate the efficiency of the proposed model and algorithm.

Property Measurement

NASA Technical Reports Server (NTRS)

1980-01-01

Van is used by Land Inventory Systems to measure and map property for tax assessment purposes. It is adapted from navigation system of the Lunar Rover wheeled vehicle in which moon-exploring astronauts traveled as much as 20 miles from their Lunar Module base. Astronauts had to know their precise position so that in case of emergency they could take the shortest route back. Computerized navigational system kept a highly accurate record of the directional path providing continuous position report. Distance measuring subsystem was a more accurate counterpart of automobile odometer system counts revolutions of wheels and encoders generate electrical pulses for each fractional revolution and the computer analyzed the pulses to determine the distance traveled in a given direction.

Model of a Frame of Dynamic Routing and Its Equilibrium

NASA Astrophysics Data System (ADS)

Zhang, Shu; Yuan, Yuan; Xu, Jian

Dynamic routing algorithm based on the shortest path principle is criticized due to the oscillation induced by such routing scheme. In the present work, we propose the model of TCP/RED algorithm by a new frame of dynamic routing, based on the measurement of occupation ratio of router buffer for different links, which only requires the information of the queue size at the buffer of the router, to stabilize the system. We classify several types of equilibrium and employ the numerical method to study the stability of the steady state. Our numerical results show that the careful selection of the parameters characterizing the dynamic routing algorithm can stabilize the system in some cases.

Secure data aggregation in wireless sensor networks using homomorphic encryption

NASA Astrophysics Data System (ADS)

Kumar, Manish; Verma, Shekhar; Lata, Kusum

2015-04-01

In a Wireless Sensor Network (WSN), aggregation exploits the correlation between spatially and temporally proximate sensor data to reduce the total data volume to be transmitted to the sink. Mobile agents (MAs) fit into this paradigm, and data can be aggregated and collected by an MA from different sensor nodes using context specific codes. The MA-based data collection suffers due to large size of a typical WSN and is prone to security problems. In this article, homomorphic encryption in a clustered WSN has been proposed for secure and efficient data collection using MAs. The nodes keep encrypted data that are given to an MA for data aggregation tasks. The MA performs all the data aggregation operations upon encrypted data as it migrates between nodes in a tree-like structure in which the nodes are leafs and the cluster head is the root of the tree. It returns and deposits the encrypted aggregated data to the cluster head after traversing through all the intra cluster nodes over a shortest path route. The homomorphic encryption and aggregation processing in encrypted domain makes the data collection process secure. Simulation results confirm the effectiveness of the proposed secure data aggregation mechanism. In addition to security, MA-based mechanism leads to lesser delay and bandwidth requirements.

Estimation of distributed Fermat-point location for wireless sensor networking.

PubMed

Huang, Po-Hsian; Chen, Jiann-Liang; Larosa, Yanuarius Teofilus; Chiang, Tsui-Lien

2011-01-01

This work presents a localization scheme for use in wireless sensor networks (WSNs) that is based on a proposed connectivity-based RF localization strategy called the distributed Fermat-point location estimation algorithm (DFPLE). DFPLE applies triangle area of location estimation formed by intersections of three neighboring beacon nodes. The Fermat point is determined as the shortest path from three vertices of the triangle. The area of estimated location then refined using Fermat point to achieve minimum error in estimating sensor nodes location. DFPLE solves problems of large errors and poor performance encountered by localization schemes that are based on a bounding box algorithm. Performance analysis of a 200-node development environment reveals that, when the number of sensor nodes is below 150, the mean error decreases rapidly as the node density increases, and when the number of sensor nodes exceeds 170, the mean error remains below 1% as the node density increases. Second, when the number of beacon nodes is less than 60, normal nodes lack sufficient beacon nodes to enable their locations to be estimated. However, the mean error changes slightly as the number of beacon nodes increases above 60. Simulation results revealed that the proposed algorithm for estimating sensor positions is more accurate than existing algorithms, and improves upon conventional bounding box strategies.

Dynamic Task Assignment and Path Planning of Multi-AUV System Based on an Improved Self-Organizing Map and Velocity Synthesis Method in Three-Dimensional Underwater Workspace.

PubMed

Zhu, Daqi; Huang, Huan; Yang, S X

2013-04-01

For a 3-D underwater workspace with a variable ocean current, an integrated multiple autonomous underwater vehicle (AUV) dynamic task assignment and path planning algorithm is proposed by combing the improved self-organizing map (SOM) neural network and a novel velocity synthesis approach. The goal is to control a team of AUVs to reach all appointed target locations for only one time on the premise of workload balance and energy sufficiency while guaranteeing the least total and individual consumption in the presence of the variable ocean current. First, the SOM neuron network is developed to assign a team of AUVs to achieve multiple target locations in 3-D ocean environment. The working process involves special definition of the initial neural weights of the SOM network, the rule to select the winner, the computation of the neighborhood function, and the method to update weights. Then, the velocity synthesis approach is applied to plan the shortest path for each AUV to visit the corresponding target in a dynamic environment subject to the ocean current being variable and targets being movable. Lastly, to demonstrate the effectiveness of the proposed approach, simulation results are given in this paper.

A graph-based system for network-vulnerability analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Swiler, L.P.; Phillips, C.

1998-06-01

This paper presents a graph-based approach to network vulnerability analysis. The method is flexible, allowing analysis of attacks from both outside and inside the network. It can analyze risks to a specific network asset, or examine the universe of possible consequences following a successful attack. The graph-based tool can identify the set of attack paths that have a high probability of success (or a low effort cost) for the attacker. The system could be used to test the effectiveness of making configuration changes, implementing an intrusion detection system, etc. The analysis system requires as input a database of common attacks,more » broken into atomic steps, specific network configuration and topology information, and an attacker profile. The attack information is matched with the network configuration information and an attacker profile to create a superset attack graph. Nodes identify a stage of attack, for example the class of machines the attacker has accessed and the user privilege level he or she has compromised. The arcs in the attack graph represent attacks or stages of attacks. By assigning probabilities of success on the arcs or costs representing level-of-effort for the attacker, various graph algorithms such as shortest-path algorithms can identify the attack paths with the highest probability of success.« less

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.

Finding Minimal Addition Chains with a Particle Swarm Optimization Algorithm

NASA Astrophysics Data System (ADS)

León-Javier, Alejandro; Cruz-Cortés, Nareli; Moreno-Armendáriz, Marco A.; Orantes-Jiménez, Sandra

The addition chains with minimal length are the basic block to the optimal computation of finite field exponentiations. It has very important applications in the areas of error-correcting codes and cryptography. However, obtaining the shortest addition chains for a given exponent is a NP-hard problem. In this work we propose the adaptation of a Particle Swarm Optimization algorithm to deal with this problem. Our proposal is tested on several exponents whose addition chains are considered hard to find. We obtained very promising results.

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.

Networks of genetic loci and the scientific literature

NASA Astrophysics Data System (ADS)

Semeiks, J. R.; Grate, L. R.; Mian, I. S.

This work considers biological information graphs, networks in which nodes corre-spond to genetic loci (or "genes") and an (undirected) edge signifies that two genes are discussed in the same article(s) in the scientific literature ("documents"). Operations that utilize the topology of these graphs can assist researchers in the scientific discovery process. For example, a shortest path between two nodes defines an ordered series of genes and documents that can be used to explore the relationship(s) between genes of interest. This work (i) describes how topologies in which edges are likely to reflect genuine relationship(s) can be constructed from human-curated corpora of genes an-notated with documents (or vice versa), and (ii) illustrates the potential of biological information graphs in synthesizing knowledge in order to formulate new hypotheses and generate novel predictions for subsequent experimental study. In particular, the well-known LocusLink corpus is used to construct a biological information graph consisting of 10,297 nodes and 21,910 edges. The large-scale statistical properties of this gene-document network suggest that it is a new example of a power-law network. The segregation of genes on the basis of species and encoded protein molecular function indicate the presence of assortativity, the preference for nodes with similar attributes to be neighbors in a network. The practical utility of a gene-document network is illustrated by using measures such as shortest paths and centrality to analyze a subset of nodes corresponding to genes implicated in aging. Each release of a curated biomedical corpus defines a particular static graph. The topology of a gene-document network changes over time as curators add and/or remove nodes and/or edges. Such a dynamic, evolving corpus provides both the foundation for analyzing the growth and behavior of large complex networks and a substrate for examining trends in biological research.

Fully Automated Segmentation of Fluid/Cyst Regions in Optical Coherence Tomography Images With Diabetic Macular Edema Using Neutrosophic Sets and Graph Algorithms.

PubMed

Rashno, Abdolreza; Koozekanani, Dara D; Drayna, Paul M; Nazari, Behzad; Sadri, Saeed; Rabbani, Hossein; Parhi, Keshab K

2018-05-01

This paper presents a fully automated algorithm to segment fluid-associated (fluid-filled) and cyst regions in optical coherence tomography (OCT) retina images of subjects with diabetic macular edema. The OCT image is segmented using a novel neutrosophic transformation and a graph-based shortest path method. In neutrosophic domain, an image is transformed into three sets: (true), (indeterminate) that represents noise, and (false). This paper makes four key contributions. First, a new method is introduced to compute the indeterminacy set , and a new -correction operation is introduced to compute the set in neutrosophic domain. Second, a graph shortest-path method is applied in neutrosophic domain to segment the inner limiting membrane and the retinal pigment epithelium as regions of interest (ROI) and outer plexiform layer and inner segment myeloid as middle layers using a novel definition of the edge weights . Third, a new cost function for cluster-based fluid/cyst segmentation in ROI is presented which also includes a novel approach in estimating the number of clusters in an automated manner. Fourth, the final fluid regions are achieved by ignoring very small regions and the regions between middle layers. The proposed method is evaluated using two publicly available datasets: Duke, Optima, and a third local dataset from the UMN clinic which is available online. The proposed algorithm outperforms the previously proposed Duke algorithm by 8% with respect to the dice coefficient and by 5% with respect to precision on the Duke dataset, while achieving about the same sensitivity. Also, the proposed algorithm outperforms a prior method for Optima dataset by 6%, 22%, and 23% with respect to the dice coefficient, sensitivity, and precision, respectively. Finally, the proposed algorithm also achieves sensitivity of 67.3%, 88.8%, and 76.7%, for the Duke, Optima, and the university of minnesota (UMN) datasets, respectively.

Effects of environmental features and sport hunting on caribou migration in northwestern Alaska.

PubMed

Fullman, Timothy J; Joly, Kyle; Ackerman, Andrew

2017-01-01

Ungulate movements are influenced by a variety of biotic and abiotic factors, which may affect connectivity between key resource areas and seasonal ranges. In northwestern Alaska, one important question regarding human impacts on ungulate movement involves caribou ( Rangifer tarandus ) response to autumn hunting and related aircraft activity. While concerns have been voiced by local hunters about the influence of transporter aircraft and non-local sport hunters, there has been little quantitative analysis of the effects of hunter activity on caribou movement. We utilized a novel spatial dataset of commercial aircraft landing locations and sport hunter camps in and around Noatak National Preserve to analyze resource selection of caribou in autumn for non-local hunting activity and environmental features. We combined step selection functions with randomized shortest paths to investigate whether terrain ruggedness, river width, land cover, and hunting activity (in the form of aircraft landings and sport hunter camps) facilitated or impeded caribou movement. By varying a parameter in the randomized shortest path models, we also explored the tradeoff between exploration and exploitation in movement behavior exhibited by traveling caribou. We found that caribou avoided rugged terrain and areas with more river, forest, and tall shrubs while selecting for areas dominated by tussock tundra and dwarf shrubs. Migration of caribou through Noatak does not appear to be inhibited by sport hunting activity, though this does not preclude the possibility of temporary effects altering availability of caribou for individual hunters. Caribou exhibited exploratory movement, following predictions of a random walk model. This behavior may facilitate the location of remaining patches of high-quality forage prior to the onset of winter, especially during mild autumns. Understanding animal movement behavior is fundamental to protecting critical areas of connectivity and to informing management decisions. Our study identifies migratory connectivity and hotspots of potential conflict among user groups, enabling development of policies that balance human access with species conservation.

A molecular systems approach to modelling human skin pigmentation: identifying underlying pathways and critical components.

PubMed

Raghunath, Arathi; Sambarey, Awanti; Sharma, Neha; Mahadevan, Usha; Chandra, Nagasuma

2015-04-29

Ultraviolet radiations (UV) serve as an environmental stress for human skin, and result in melanogenesis, with the pigment melanin having protective effects against UV induced damage. This involves a dynamic and complex regulation of various biological processes that results in the expression of melanin in the outer most layers of the epidermis, where it can exert its protective effect. A comprehensive understanding of the underlying cross talk among different signalling molecules and cell types is only possible through a systems perspective. Increasing incidences of both melanoma and non-melanoma skin cancers necessitate the need to better comprehend UV mediated effects on skin pigmentation at a systems level, so as to ultimately evolve knowledge-based strategies for efficient protection and prevention of skin diseases. A network model for UV-mediated skin pigmentation in the epidermis was constructed and subjected to shortest path analysis. Virtual knock-outs were carried out to identify essential signalling components. We describe a network model for UV-mediated skin pigmentation in the epidermis. The model consists of 265 components (nodes) and 429 directed interactions among them, capturing the manner in which one component influences the other and channels information. Through shortest path analysis, we identify novel signalling pathways relevant to pigmentation. Virtual knock-outs or perturbations of specific nodes in the network have led to the identification of alternate modes of signalling as well as enabled determining essential nodes in the process. The model presented provides a comprehensive picture of UV mediated signalling manifesting in human skin pigmentation. A systems perspective helps provide a holistic purview of interconnections and complexity in the processes leading to pigmentation. The model described here is extensive yet amenable to expansion as new data is gathered. Through this study, we provide a list of important proteins essential for pigmentation which can be further explored to better understand normal pigmentation as well as its pathologies including vitiligo and melanoma, and enable therapeutic intervention.

Investigation of the roles of trace elements during hepatitis C virus infection using protein-protein interactions and a shortest path algorithm.

PubMed

Zhu, LiuCun; Chen, XiJia; Kong, Xiangyin; Cai, Yu-Dong

2016-11-01

Hepatitis is a type of infectious disease that induces inflammation of the liver without pinpointing a particular pathogen or pathogenesis. Type C hepatitis, as a type of hepatitis, has been reported to induce cirrhosis and hepatocellular carcinoma within a very short amount of time. It is a great threat to human health. Some studies have revealed that trace elements are associated with infection with and immune rejection against hepatitis C virus (HCV). However, the mechanism underlying this phenomenon is still unclear. In this study, we aimed to expand our knowledge of this phenomenon by designing a computational method to identify genes that may be related to both HCV and trace element metabolic processes. The searching procedure included three stages. First, a shortest path algorithm was applied to a large network, constructed by protein-protein interactions, to identify potential genes of interest. Second, a permutation test was executed to exclude false discoveries. Finally, some rules based on the betweenness and associations between candidate genes and HCV and trace elements were built to select core genes among the remaining genes. 12 lists of genes, corresponding to 12 types of trace elements, were obtained. These genes are deemed to be associated with HCV infection and trace elements metabolism. The analyses indicate that some genes may be related to both HCV and trace element metabolic processes, further confirming the associations between HCV and trace elements. The method was further tested on another set of HCV genes, the results indicate that this method is quite robustness. The newly found genes may partially reveal unknown mechanisms between HCV infection and trace element metabolism. This article is part of a Special Issue entitled "System Genetics" Guest Editor: Dr. Yudong Cai and Dr. Tao Huang. Copyright © 2016 Elsevier B.V. All rights reserved.

The application of muscle wrapping to voxel-based finite element models of skeletal structures.

PubMed

Liu, Jia; Shi, Junfen; Fitton, Laura C; Phillips, Roger; O'Higgins, Paul; Fagan, Michael J

2012-01-01

Finite elements analysis (FEA) is now used routinely to interpret skeletal form in terms of function in both medical and biological applications. To produce accurate predictions from FEA models, it is essential that the loading due to muscle action is applied in a physiologically reasonable manner. However, it is common for muscle forces to be represented as simple force vectors applied at a few nodes on the model's surface. It is certainly rare for any wrapping of the muscles to be considered, and yet wrapping not only alters the directions of muscle forces but also applies an additional compressive load from the muscle belly directly to the underlying bone surface. This paper presents a method of applying muscle wrapping to high-resolution voxel-based finite element (FE) models. Such voxel-based models have a number of advantages over standard (geometry-based) FE models, but the increased resolution with which the load can be distributed over a model's surface is particularly advantageous, reflecting more closely how muscle fibre attachments are distributed. In this paper, the development, application and validation of a muscle wrapping method is illustrated using a simple cylinder. The algorithm: (1) calculates the shortest path over the surface of a bone given the points of origin and ultimate attachment of the muscle fibres; (2) fits a Non-Uniform Rational B-Spline (NURBS) curve from the shortest path and calculates its tangent, normal vectors and curvatures so that normal and tangential components of the muscle force can be calculated and applied along the fibre; and (3) automatically distributes the loads between adjacent fibres to cover the bone surface with a fully distributed muscle force, as is observed in vivo. Finally, we present a practical application of this approach to the wrapping of the temporalis muscle around the cranium of a macaque skull.

Ray tracing of multiple transmitted/reflected/converted waves in 2-D/3-D layered anisotropic TTI media and application to crosswell traveltime tomography

NASA Astrophysics Data System (ADS)

Bai, Chao-Ying; Huang, Guo-Jiao; Li, Xiao-Ling; Zhou, Bing; Greenhalgh, Stewart

2013-11-01

To overcome the deficiency of some current grid-/cell-based ray tracing algorithms, which are only able to handle first arrivals or primary reflections (or conversions) in anisotropic media, we have extended the functionality of the multistage irregular shortest-path method to 2-D/3-D tilted transversely isotropic (TTI) media. The new approach is able to track multiple transmitted/reflected/converted arrivals composed of any kind of combinations of transmissions, reflections and mode conversions. The basic principle is that the seven parameters (five elastic parameters plus two polar angles defining the tilt of the symmetry axis) of the TTI media are sampled at primary nodes, and the group velocity values at secondary nodes are obtained by tri-linear interpolation of the primary nodes across each cell, from which the group velocities of the three wave modes (qP, qSV and qSH) are calculated. Finally, we conduct grid-/cell-based wave front expansion to trace multiple transmitted/reflected/converted arrivals from one region to the next. The results of calculations in uniform anisotropic media indicate that the numerical results agree with the analytical solutions except in directions of SV-wave triplications, at which only the lowest velocity value is selected at the singularity points by the multistage irregular shortest-path anisotropic ray tracing method. This verifies the accuracy of the methodology. Several simulation results show that the new method is able to efficiently and accurately approximate situations involving continuous velocity variations and undulating discontinuities, and that it is suitable for any combination of multiple transmitted/reflected/converted arrival tracking in TTI media of arbitrary strength and tilt. Crosshole synthetic traveltime tomographic tests have been performed, which highlight the importance of using such code when the medium is distinctly anisotropic.

Route 20, Autobahn 7, and Slime Mold: Approximating the Longest Roads in USA and Germany With Slime Mold on 3-D Terrains.

PubMed

Adamatzky, Andrew I

2014-01-01

A cellular slime mould Physarum polycephalum is a monstrously large single cell visible by an unaided eye. The slime mold explores space in parallel, is guided by gradients of chemoattractants, and propagates toward sources of nutrients along nearly shortest paths. The slime mold is a living prototype of amorphous biological computers and robotic devices capable of solving a range of tasks of graph optimization and computational geometry. When presented with a distribution of nutrients, the slime mold spans the sources of nutrients with a network of protoplasmic tubes. This protoplasmic network matches a network of major transport routes of a country when configuration of major urban areas is represented by nutrients. A transport route connecting two cities should ideally be a shortest path, and this is usually the case in computer simulations and laboratory experiments with flat substrates. What searching strategies does the slime mold adopt when exploring 3-D terrains? How are optimal and transport routes approximated by protoplasmic tubes? Do the routes built by the slime mold on 3-D terrain match real-world transport routes? To answer these questions, we conducted pioneer laboratory experiments with Nylon terrains of USA and Germany. We used the slime mold to approximate route 20, the longest road in USA, and autobahn 7, the longest national motorway in Europe. We found that slime mold builds longer transport routes on 3-D terrains, compared to flat substrates yet sufficiently approximates man-made transport routes studied. We demonstrate that nutrients placed in destination sites affect performance of slime mold, and show how the mold navigates around elevations. In cellular automaton models of the slime mold, we have shown variability of the protoplasmic routes might depends on physiological states of the slime mold. Results presented will contribute toward development of novel algorithms for sensorial fusion, information processing, and decision making, and will provide inspirations in design of bioinspired amorphous robotic devices.

Computed tomography airway lumen volumetry in patients with acromegaly: Association with growth hormone levels and lung function.

PubMed

Camilo, Gustavo Bittencourt; Carvalho, Alysson Roncally Silva; Guimarães, Alan Ranieri Medeiros; Kasuki, Leandro; Gadelha, Mônica Roberto; Mogami, Roberto; de Melo, Pedro Lopes; Lopes, Agnaldo José

2017-10-01

The segmentation and skeletonisation of images via computed tomography (CT) airway lumen volumetry provide a new perspective regarding the incorporation of this technique in medical practice. Our aim was to quantify morphological changes in the large airways of patients with acromegaly through CT and, secondarily, to correlate these findings with hormone levels and pulmonary function testing (PFT) parameters. This was a cross-sectional study in which 28 non-smoker patients with acromegaly and 15 control subjects underwent CT analysis of airway lumen volumetry with subsequent image segmentation and skeletonisation. Moreover, all participants were subjected to PFT. Compared with the controls, patients with acromegaly presented higher diameters in the trachea, right main bronchus and left main bronchus. The patients with acromegaly also showed a higher tracheal sinuosity index (the deviation of a line from the shortest path, calculated by dividing total length by shortest possible path) than the controls [1.06 (1.02-1.09) vs. 1.03 (1.02-1.04), P = 0.04], and tracheal stenosis was observed in 25% of these individuals. The tracheal area was correlated with the levels of growth hormone (r s  = 0.45, P = 0.02) and insulin-like growth factor type I (r s  = 0.38, P = 0.04). The ratio between the forced expiratory flow and forced inspiratory flow at 50% of the forced vital capacity was correlated with the tracheal area (r s  = 0.36, P = 0.02) and Δ tracheal diameters (r s  = 0.58, P < 0.0001). Patients with acromegaly exhibit tracheobronchomegaly and tracheal sinuosity/stenosis. Moreover, there are associations between the results of CT airway lumen volumetry, hormone levels and functional parameters of large airway obstruction. © 2017 The Royal Australian and New Zealand College of Radiologists.

Congestion patterns of electric vehicles with limited battery capacity.

PubMed

Jing, Wentao; Ramezani, Mohsen; An, Kun; Kim, Inhi

2018-01-01

The path choice behavior of battery electric vehicle (BEV) drivers is influenced by the lack of public charging stations, limited battery capacity, range anxiety and long battery charging time. This paper investigates the congestion/flow pattern captured by stochastic user equilibrium (SUE) traffic assignment problem in transportation networks with BEVs, where the BEV paths are restricted by their battery capacities. The BEV energy consumption is assumed to be a linear function of path length and path travel time, which addresses both path distance limit problem and road congestion effect. A mathematical programming model is proposed for the path-based SUE traffic assignment where the path cost is the sum of the corresponding link costs and a path specific out-of-energy penalty. We then apply the convergent Lagrangian dual method to transform the original problem into a concave maximization problem and develop a customized gradient projection algorithm to solve it. A column generation procedure is incorporated to generate the path set. Finally, two numerical examples are presented to demonstrate the applicability of the proposed model and the solution algorithm.

Congestion patterns of electric vehicles with limited battery capacity

PubMed Central

2018-01-01

The path choice behavior of battery electric vehicle (BEV) drivers is influenced by the lack of public charging stations, limited battery capacity, range anxiety and long battery charging time. This paper investigates the congestion/flow pattern captured by stochastic user equilibrium (SUE) traffic assignment problem in transportation networks with BEVs, where the BEV paths are restricted by their battery capacities. The BEV energy consumption is assumed to be a linear function of path length and path travel time, which addresses both path distance limit problem and road congestion effect. A mathematical programming model is proposed for the path-based SUE traffic assignment where the path cost is the sum of the corresponding link costs and a path specific out-of-energy penalty. We then apply the convergent Lagrangian dual method to transform the original problem into a concave maximization problem and develop a customized gradient projection algorithm to solve it. A column generation procedure is incorporated to generate the path set. Finally, two numerical examples are presented to demonstrate the applicability of the proposed model and the solution algorithm. PMID:29543875

Online optimal obstacle avoidance for rotary-wing autonomous unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Kang, Keeryun

This thesis presents an integrated framework for online obstacle avoidance of rotary-wing unmanned aerial vehicles (UAVs), which can provide UAVs an obstacle field navigation capability in a partially or completely unknown obstacle-rich environment. The framework is composed of a LIDAR interface, a local obstacle grid generation, a receding horizon (RH) trajectory optimizer, a global shortest path search algorithm, and a climb rate limit detection logic. The key feature of the framework is the use of an optimization-based trajectory generation in which the obstacle avoidance problem is formulated as a nonlinear trajectory optimization problem with state and input constraints over the finite range of the sensor. This local trajectory optimization is combined with a global path search algorithm which provides a useful initial guess to the nonlinear optimization solver. Optimization is the natural process of finding the best trajectory that is dynamically feasible, safe within the vehicle's flight envelope, and collision-free at the same time. The optimal trajectory is continuously updated in real time by the numerical optimization solver, Nonlinear Trajectory Generation (NTG), which is a direct solver based on the spline approximation of trajectory for dynamically flat systems. In fact, the overall approach of this thesis to finding the optimal trajectory is similar to the model predictive control (MPC) or the receding horizon control (RHC), except that this thesis followed a two-layer design; thus, the optimal solution works as a guidance command to be followed by the controller of the vehicle. The framework is implemented in a real-time simulation environment, the Georgia Tech UAV Simulation Tool (GUST), and integrated in the onboard software of the rotary-wing UAV test-bed at Georgia Tech. Initially, the 2D vertical avoidance capability of real obstacles was tested in flight. The flight test evaluations were extended to the benchmark tests for 3D avoidance capability over the virtual obstacles, and finally it was demonstrated on real obstacles located at the McKenna MOUT site in Fort Benning, Georgia. Simulations and flight test evaluations demonstrate the feasibility of the developed framework for UAV applications involving low-altitude flight in an urban area.

Cooperative path following control of multiple nonholonomic mobile robots.

PubMed

Cao, Ke-Cai; Jiang, Bin; Yue, Dong

2017-11-01

Cooperative path following control problem of multiple nonholonomic mobile robots has been considered in this paper. Based on the framework of decomposition, the cooperative path following problem has been transformed into path following problem and cooperative control problem; Then cascaded theory of non-autonomous system has been employed in the design of controllers without resorting to feedback linearization. One time-varying coordinate transformation based on dilation has been introduced to solve the uncontrollable problem of nonholonomic robots when the whole group's reference converges to stationary point. Cooperative path following controllers for nonholonomic robots have been proposed under persistent reference or reference target that converges to stationary point respectively. Simulation results using Matlab have illustrated the effectiveness of the obtained theoretical results. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Grading vascularity from histopathological images based on traveling salesman distance and vessel size

NASA Astrophysics Data System (ADS)

Niazi, M. Khalid Khan; Hemminger, Jessica; Kurt, Habibe; Lozanski, Gerard; Gurcan, Metin

2014-03-01

Vascularity represents an important element of tissue/tumor microenvironment and is implicated in tumor growth, metastatic potential and resistence to therapy. Small blood vessels can be visualized using immunohistochemical stains specific to vascular cells. However, currently used manual methods to assess vascular density are poorly reproducible and are at best semi quantitative. Computer based quantitative and objective methods to measure microvessel density are urgently needed to better understand and clinically utilize microvascular density information. We propose a new method to quantify vascularity from images of bone marrow biopsies stained for CD34 vascular lining cells protein as a model. The method starts by automatically segmenting the blood vessels by methods of maxlink thresholding and minimum graph cuts. The segmentation is followed by morphological post-processing to reduce blast and small spurious objects from the bone marrow images. To classify the images into one of the four grades, we extracted 20 features from the segmented blood vessel images. These features include first four moments of the distribution of the area of blood vessels, first four moments of the distribution of 1) the edge weights in the minimum spanning tree of the blood vessels, 2) the shortest distance between blood vessels, 3) the homogeneity of the shortest distance (absolute difference in distance between consecutive blood vessels along the shortest path) between blood vessels and 5) blood vessel orientation. The method was tested on 26 bone marrow biopsy images stained with CD34 IHC stain, which were evaluated by three pathologists. The pathologists took part in this study by quantifying blood vessel density using gestalt assessment in hematopoietic bone marrow portions of bone marrow core biopsies images. To determine the intra-reader variability, each image was graded twice by each pathologist with two-week interval in between their readings. For each image, the ground truth (grade) was acquired through consensus among the three pathologists at the end of the study. A ranking of the features reveals that the fourth moment of the distribution of the area of blood vessels along with the first moment of the distribution of the shortest distance between blood vessels can correctly grade 68.2% of the bone marrow biopsies, while the intra- and inter-reader variability among the pathologists are 66.9% and 40.0%, respectively.

Action-minimizing solutions of the one-dimensional N-body problem

NASA Astrophysics Data System (ADS)

Yu, Xiang; Zhang, Shiqing

2018-05-01

We supplement the following result of C. Marchal on the Newtonian N-body problem: A path minimizing the Lagrangian action functional between two given configurations is always a true (collision-free) solution when the dimension d of the physical space R^d satisfies d≥2. The focus of this paper is on the fixed-ends problem for the one-dimensional Newtonian N-body problem. We prove that a path minimizing the action functional in the set of paths joining two given configurations and having all the time the same order is always a true (collision-free) solution. Considering the one-dimensional N-body problem with equal masses, we prove that (i) collision instants are isolated for a path minimizing the action functional between two given configurations, (ii) if the particles at two endpoints have the same order, then the path minimizing the action functional is always a true (collision-free) solution and (iii) when the particles at two endpoints have different order, although there must be collisions for any path, we can prove that there are at most N! - 1 collisions for any action-minimizing path.

Decentralized Routing and Diameter Bounds in Entangled Quantum Networks

NASA Astrophysics Data System (ADS)

Gyongyosi, Laszlo; Imre, Sandor

2017-04-01

Entangled quantum networks are a necessity for any future quantum internet, long-distance quantum key distribution, and quantum repeater networks. The entangled quantum nodes can communicate through several different levels of entanglement, leading to a heterogeneous, multi-level entangled network structure. The level of entanglement between the quantum nodes determines the hop distance, the number of spanned nodes, and the probability of the existence of an entangled link in the network. In this work we define a decentralized routing for entangled quantum networks. We show that the probability distribution of the entangled links can be modeled by a specific distribution in a base-graph. The results allow us to perform efficient routing to find the shortest paths in entangled quantum networks by using only local knowledge of the quantum nodes. We give bounds on the maximum value of the total number of entangled links of a path. The proposed scheme can be directly applied in practical quantum communications and quantum networking scenarios. This work was partially supported by the Hungarian Scientific Research Fund - OTKA K-112125.

Greedy data transportation scheme with hard packet deadlines for wireless ad hoc networks.

PubMed

Lee, HyungJune

2014-01-01

We present a greedy data transportation scheme with hard packet deadlines in ad hoc sensor networks of stationary nodes and multiple mobile nodes with scheduled trajectory path and arrival time. In the proposed routing strategy, each stationary ad hoc node en route decides whether to relay a shortest-path stationary node toward destination or a passing-by mobile node that will carry closer to destination. We aim to utilize mobile nodes to minimize the total routing cost as far as the selected route can satisfy the end-to-end packet deadline. We evaluate our proposed routing algorithm in terms of routing cost, packet delivery ratio, packet delivery time, and usability of mobile nodes based on network level simulations. Simulation results show that our proposed algorithm fully exploits the remaining time till packet deadline to turn into networking benefits of reducing the overall routing cost and improving packet delivery performance. Also, we demonstrate that the routing scheme guarantees packet delivery with hard deadlines, contributing to QoS improvement in various network services.

Greedy Data Transportation Scheme with Hard Packet Deadlines for Wireless Ad Hoc Networks

PubMed Central

Lee, HyungJune

2014-01-01

We present a greedy data transportation scheme with hard packet deadlines in ad hoc sensor networks of stationary nodes and multiple mobile nodes with scheduled trajectory path and arrival time. In the proposed routing strategy, each stationary ad hoc node en route decides whether to relay a shortest-path stationary node toward destination or a passing-by mobile node that will carry closer to destination. We aim to utilize mobile nodes to minimize the total routing cost as far as the selected route can satisfy the end-to-end packet deadline. We evaluate our proposed routing algorithm in terms of routing cost, packet delivery ratio, packet delivery time, and usability of mobile nodes based on network level simulations. Simulation results show that our proposed algorithm fully exploits the remaining time till packet deadline to turn into networking benefits of reducing the overall routing cost and improving packet delivery performance. Also, we demonstrate that the routing scheme guarantees packet delivery with hard deadlines, contributing to QoS improvement in various network services. PMID:25258736

Glow discharge based device for solving mazes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dubinov, Alexander E., E-mail: dubinov-ae@yandex.ru; Mironenko, Maxim S.; Selemir, Victor D.

2014-09-15

A glow discharge based device for solving mazes has been designed and tested. The device consists of a gas discharge chamber and maze-transformer of radial-azimuth type. It allows changing of the maze pattern in a short period of time (within several minutes). The device has been tested with low pressure air. Once switched on, a glow discharge has been shown to find the shortest way through the maze from the very first attempt, even if there is a section with potential barrier for electrons on the way. It has been found that ionization waves (striations) can be excited in themore » maze along the length of the plasma channel. The dependancy of discharge voltage on the length of the optimal path through the maze has been measured. A reduction in discharge voltage with one or two potential barriers present has been found and explained. The dependency of the magnitude of discharge ignition voltage on the length of the optimal path through the maze has been measured. The reduction of the ignition voltage with the presence of one or two potential barriers has been observed and explained.« less

Pathways from maternal distress and child problem behavior to adolescent depressive symptoms: a prospective examination from early childhood to adolescence.

PubMed

Nilsen, Wendy; Gustavson, Kristin; Røysamb, Espen; Kjeldsen, Anne; Karevold, Evalill

2013-06-01

The main aim of this study was to identify the pathways from maternal distress and child problem behaviors (i.e., internalizing and externalizing problems) across childhood and their impact on depressive symptoms during adolescence among girls and boys. Data from families of 921 Norwegian children in a 15-year longitudinal community sample were used. Using structural equation modeling, the authors explored the interplay between maternal-reported distress and child problem behaviors measured at 5 time points from early (ages 1.5, 2.5, and 4.5 years) and middle (age 8.5 years) childhood to early adolescence (age 12.5 years), and their prediction of self-reported depressive symptoms during adolescence (ages 14.5 and 16.5 years). The findings revealed paths from internalizing and externalizing problems throughout the development for corresponding problems (homotypic paths) and paths from early externalizing to subsequent internalizing problems (heterotypic paths). The findings suggest 2 pathways linking maternal-rated risk factors to self-reported adolescent depressive symptoms. There was a direct path from early externalizing problems to depressive symptoms. There was an indirect path from early maternal distress going through child problem behavior to depressive symptoms. In general, girls and boys were similar, but some gender-specific effects appeared. Problem behaviors in middle childhood had heterotypic paths to subsequent problems only for girls. The findings highlight the developmental importance of child externalizing problems, as well as the impact of maternal distress as early as age 1.5 years for the development of adolescent depressive symptoms. Findings also indicate a certain vulnerable period in middle childhood for girls. NOTE: See Supplemental Digital Content 1, at http://links.lww.com/JDBP/A45, for a video introduction to this article.

Multiple kernel learning in protein-protein interaction extraction from biomedical literature.

PubMed

Yang, Zhihao; Tang, Nan; Zhang, Xiao; Lin, Hongfei; Li, Yanpeng; Yang, Zhiwei

2011-03-01

Knowledge about protein-protein interactions (PPIs) unveils the molecular mechanisms of biological processes. The volume and content of published biomedical literature on protein interactions is expanding rapidly, making it increasingly difficult for interaction database administrators, responsible for content input and maintenance to detect and manually update protein interaction information. The objective of this work is to develop an effective approach to automatic extraction of PPI information from biomedical literature. We present a weighted multiple kernel learning-based approach for automatic PPI extraction from biomedical literature. The approach combines the following kernels: feature-based, tree, graph and part-of-speech (POS) path. In particular, we extend the shortest path-enclosed tree (SPT) and dependency path tree to capture richer contextual information. Our experimental results show that the combination of SPT and dependency path tree extensions contributes to the improvement of performance by almost 0.7 percentage units in F-score and 2 percentage units in area under the receiver operating characteristics curve (AUC). Combining two or more appropriately weighed individual will further improve the performance. Both on the individual corpus and cross-corpus evaluation our combined kernel can achieve state-of-the-art performance with respect to comparable evaluations, with 64.41% F-score and 88.46% AUC on the AImed corpus. As different kernels calculate the similarity between two sentences from different aspects. Our combined kernel can reduce the risk of missing important features. More specifically, we use a weighted linear combination of individual kernels instead of assigning the same weight to each individual kernel, thus allowing the introduction of each kernel to incrementally contribute to the performance improvement. In addition, SPT and dependency path tree extensions can improve the performance by including richer context information. Copyright © 2010 Elsevier B.V. All rights reserved.

Dual stage potential field method for robotic path planning

NASA Astrophysics Data System (ADS)

Singh, Pradyumna Kumar; Parida, Pramod Kumar

2018-04-01

Path planning for autonomous mobile robots are the root for all autonomous mobile systems. Various methods are used for optimization of path to be followed by the autonomous mobile robots. Artificial potential field based path planning method is one of the most used methods for the researchers. Various algorithms have been proposed using the potential field approach. But in most of the common problems are encounters while heading towards the goal or target. i.e. local minima problem, zero potential regions problem, complex shaped obstacles problem, target near obstacle problem. In this paper we provide a new algorithm in which two types of potential functions are used one after another. The former one is to use to get the probable points and later one for getting the optimum path. In this algorithm we consider only the static obstacle and goal.

Characterization of complex networks by higher order neighborhood properties

NASA Astrophysics Data System (ADS)

Andrade, R. F. S.; Miranda, J. G. V.; Pinho, S. T. R.; Lobão, T. P.

2008-01-01

A concept of higher order neighborhood in complex networks, introduced previously [Phys. Rev. E 73, 046101 (2006)], is systematically explored to investigate larger scale structures in complex networks. The basic idea is to consider each higher order neighborhood as a network in itself, represented by a corresponding adjacency matrix, and to settle a plenty of new parameters in order to obtain a best characterization of the whole network. Usual network indices are then used to evaluate the properties of each neighborhood. The identification of high order neighborhoods is also regarded as intermediary step towards the evaluation of global network properties, like the diameter, average shortest path between node, and network fractal dimension. Results for a large number of typical networks are presented and discussed.

Pheromone routing protocol on a scale-free network.

PubMed

Ling, Xiang; Hu, Mao-Bin; Jiang, Rui; Wang, Ruili; Cao, Xian-Bin; Wu, Qing-Song

2009-12-01

This paper proposes a routing strategy for network systems based on the local information of "pheromone." The overall traffic capacity of a network system can be evaluated by the critical packet generating rate R(c). Under this critical generating rate, the total packet number in the system first increases and then decreases to reach a balance state. The system behaves differently from that with a local routing strategy based on the node degree or shortest path routing strategy. Moreover, the pheromone routing strategy performs much better than the local routing strategy, which is demonstrated by a larger value of the critical generating rate. This protocol can be an alternation for superlarge networks, in which the global topology may not be available.

Pheromone routing protocol on a scale-free network

NASA Astrophysics Data System (ADS)

Ling, Xiang; Hu, Mao-Bin; Jiang, Rui; Wang, Ruili; Cao, Xian-Bin; Wu, Qing-Song

2009-12-01

This paper proposes a routing strategy for network systems based on the local information of “pheromone.” The overall traffic capacity of a network system can be evaluated by the critical packet generating rate Rc . Under this critical generating rate, the total packet number in the system first increases and then decreases to reach a balance state. The system behaves differently from that with a local routing strategy based on the node degree or shortest path routing strategy. Moreover, the pheromone routing strategy performs much better than the local routing strategy, which is demonstrated by a larger value of the critical generating rate. This protocol can be an alternation for superlarge networks, in which the global topology may not be available.

A two-stage path planning approach for multiple car-like robots based on PH curves and a modified harmony search algorithm

NASA Astrophysics Data System (ADS)

Zeng, Wenhui; Yi, Jin; Rao, Xiao; Zheng, Yun

2017-11-01

In this article, collision-avoidance path planning for multiple car-like robots with variable motion is formulated as a two-stage objective optimization problem minimizing both the total length of all paths and the task's completion time. Accordingly, a new approach based on Pythagorean Hodograph (PH) curves and Modified Harmony Search algorithm is proposed to solve the two-stage path-planning problem subject to kinematic constraints such as velocity, acceleration, and minimum turning radius. First, a method of path planning based on PH curves for a single robot is proposed. Second, a mathematical model of the two-stage path-planning problem for multiple car-like robots with variable motion subject to kinematic constraints is constructed that the first-stage minimizes the total length of all paths and the second-stage minimizes the task's completion time. Finally, a modified harmony search algorithm is applied to solve the two-stage optimization problem. A set of experiments demonstrate the effectiveness of the proposed approach.

The bidirectional pathways between internalizing and externalizing problems and academic performance from 6 to 18 years.

PubMed

Van der Ende, Jan; Verhulst, Frank C; Tiemeier, Henning

2016-08-01

Internalizing and externalizing problems are associated with poor academic performance, both concurrently and longitudinally. Important questions are whether problems precede academic performance or vice versa, whether both internalizing and externalizing are associated with academic problems when simultaneously tested, and whether associations and their direction depend on the informant providing information. These questions were addressed in a sample of 816 children who were assessed four times. The children were 6-10 years at baseline and 14-18 years at the last assessment. Parent-reported internalizing and externalizing problems and teacher-reported academic performance were tested in cross-lagged models to examine bidirectional paths between these constructs. These models were compared with cross-lagged models testing paths between teacher-reported internalizing and externalizing problems and parent-reported academic performance. Both final models revealed similar pathways from mostly externalizing problems to academic performance. No paths emerged from internalizing problems to academic performance. Moreover, paths from academic performance to internalizing and externalizing problems were only found when teachers reported on children's problems and not for parent-reported problems. Additional model tests revealed that paths were observed in both childhood and adolescence. Externalizing problems place children at increased risk of poor academic performance and should therefore be the target for interventions.

When Does Changing Representation Improve Problem-Solving Performance?

NASA Technical Reports Server (NTRS)

Holte, Robert; Zimmer, Robert; MacDonald, Alan

1992-01-01

The aim of changing representation is the improvement of problem-solving efficiency. For the most widely studied family of methods of change of representation it is shown that the value of a single parameter, called the expulsion factor, is critical in determining (1) whether the change of representation will improve or degrade problem-solving efficiency and (2) whether the solutions produced using the change of representation will or will not be exponentially longer than the shortest solution. A method of computing the expansion factor for a given change of representation is sketched in general and described in detail for homomorphic changes of representation. The results are illustrated with homomorphic decompositions of the Towers of Hanoi problem.

Alternative Constraint Handling Technique for Four-Bar Linkage Path Generation

NASA Astrophysics Data System (ADS)

Sleesongsom, S.; Bureerat, S.

2018-03-01

This paper proposes an extension of a new concept for path generation from our previous work by adding a new constraint handling technique. The propose technique was initially designed for problems without prescribed timing by avoiding the timing constraint, while remain constraints are solving with a new constraint handling technique. The technique is one kind of penalty technique. The comparative study is optimisation of path generation problems are solved using self-adaptive population size teaching-learning based optimization (SAP-TLBO) and original TLBO. In this study, two traditional path generation test problem are used to test the proposed technique. The results show that the new technique can be applied with the path generation problem without prescribed timing and gives better results than the previous technique. Furthermore, SAP-TLBO outperforms the original one.

On the asymptotic optimality and improved strategies of SPTB heuristic for open-shop scheduling problem

NASA Astrophysics Data System (ADS)

Bai, Danyu; Zhang, Zhihai

2014-08-01

This article investigates the open-shop scheduling problem with the optimal criterion of minimising the sum of quadratic completion times. For this NP-hard problem, the asymptotic optimality of the shortest processing time block (SPTB) heuristic is proven in the sense of limit. Moreover, three different improvements, namely, the job-insert scheme, tabu search and genetic algorithm, are introduced to enhance the quality of the original solution generated by the SPTB heuristic. At the end of the article, a series of numerical experiments demonstrate the convergence of the heuristic, the performance of the improvements and the effectiveness of the quadratic objective.

Virtually assisted optical colonoscopy

NASA Astrophysics Data System (ADS)

Marino, Joseph; Qiu, Feng; Kaufman, Arie

2008-03-01

We present a set of tools used to enhance the optical colonoscopy procedure in a novel manner with the aim of improving both the accuracy and efficiency of this procedure. In order to better present the colon information to the gastroenterologist performing a conventional (optical) colonoscopy, we undistort the radial distortion of the fisheye view of the colonoscope. The radial distortion is modeled with a function that converts the fisheye view to the perspective view, where the shape and size of polyps can be more readily observed. The conversion, accelerated on the graphics processing unit and running in real-time, calculates the corresponding position in the fisheye view of each pixel on the perspective image. We also merge our previous work in computer-aided polyp detection for virtual colonoscopy into the optical colonoscopy environment. The physical colonoscope path in the optical colonoscopy is approximated with the hugging corner shortest path, which is correlated with the centerline in the virtual colonoscopy. With the estimated distance that the colonoscope has been inserted, we are able to provide the gastroenterologist with visual cues along the observation path as to the location of possible polyps found by the detection process. In order to present the information to the gastroenterologist in a non-intrusive manner, we have developed a friendly user interface to enhance the optical colonoscopy without being cumbersome, distracting, or resulting in a more lackadaisical inspection by the gastroenterologist.

Extracting contours of oval-shaped objects by Hough transform and minimal path algorithms

NASA Astrophysics Data System (ADS)

Tleis, Mohamed; Verbeek, Fons J.

2014-04-01

Circular and oval-like objects are very common in cell and micro biology. These objects need to be analyzed, and to that end, digitized images from the microscope are used so as to come to an automated analysis pipeline. It is essential to detect all the objects in an image as well as to extract the exact contour of each individual object. In this manner it becomes possible to perform measurements on these objects, i.e. shape and texture features. Our measurement objective is achieved by probing contour detection through dynamic programming. In this paper we describe a method that uses Hough transform and two minimal path algorithms to detect contours of (ovoid-like) objects. These algorithms are based on an existing grey-weighted distance transform and a new algorithm to extract the circular shortest path in an image. The methods are tested on an artificial dataset of a 1000 images, with an F1-score of 0.972. In a case study with yeast cells, contours from our methods were compared with another solution using Pratt's figure of merit. Results indicate that our methods were more precise based on a comparison with a ground-truth dataset. As far as yeast cells are concerned, the segmentation and measurement results enable, in future work, to retrieve information from different developmental stages of the cell using complex features.

Path optimization method for the sign problem

NASA Astrophysics Data System (ADS)

Ohnishi, Akira; Mori, Yuto; Kashiwa, Kouji

2018-03-01

We propose a path optimization method (POM) to evade the sign problem in the Monte-Carlo calculations for complex actions. Among many approaches to the sign problem, the Lefschetz-thimble path-integral method and the complex Langevin method are promising and extensively discussed. In these methods, real field variables are complexified and the integration manifold is determined by the flow equations or stochastically sampled. When we have singular points of the action or multiple critical points near the original integral surface, however, we have a risk to encounter the residual and global sign problems or the singular drift term problem. One of the ways to avoid the singular points is to optimize the integration path which is designed not to hit the singular points of the Boltzmann weight. By specifying the one-dimensional integration-path as z = t +if(t)(f ɛ R) and by optimizing f(t) to enhance the average phase factor, we demonstrate that we can avoid the sign problem in a one-variable toy model for which the complex Langevin method is found to fail. In this proceedings, we propose POM and discuss how we can avoid the sign problem in a toy model. We also discuss the possibility to utilize the neural network to optimize the path.

Research on cutting path optimization of sheet metal parts based on ant colony algorithm

NASA Astrophysics Data System (ADS)

Wu, Z. Y.; Ling, H.; Li, L.; Wu, L. H.; Liu, N. B.

2017-09-01

In view of the disadvantages of the current cutting path optimization methods of sheet metal parts, a new method based on ant colony algorithm was proposed in this paper. The cutting path optimization problem of sheet metal parts was taken as the research object. The essence and optimization goal of the optimization problem were presented. The traditional serial cutting constraint rule was improved. The cutting constraint rule with cross cutting was proposed. The contour lines of parts were discretized and the mathematical model of cutting path optimization was established. Thus the problem was converted into the selection problem of contour lines of parts. Ant colony algorithm was used to solve the problem. The principle and steps of the algorithm were analyzed.

The Edge-Disjoint Path Problem on Random Graphs by Message-Passing.

PubMed

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.

The Edge-Disjoint Path Problem on Random Graphs by Message-Passing

PubMed Central

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

Network-Based Method for Identifying Co-Regeneration Genes in Bone, Dentin, Nerve and Vessel Tissues

PubMed Central

Pan, Hongying; Zhang, Yu-Hang; Feng, Kaiyan; Kong, XiangYin; Cai, Yu-Dong

2017-01-01

Bone and dental diseases are serious public health problems. Most current clinical treatments for these diseases can produce side effects. Regeneration is a promising therapy for bone and dental diseases, yielding natural tissue recovery with few side effects. Because soft tissues inside the bone and dentin are densely populated with nerves and vessels, the study of bone and dentin regeneration should also consider the co-regeneration of nerves and vessels. In this study, a network-based method to identify co-regeneration genes for bone, dentin, nerve and vessel was constructed based on an extensive network of protein–protein interactions. Three procedures were applied in the network-based method. The first procedure, searching, sought the shortest paths connecting regeneration genes of one tissue type with regeneration genes of other tissues, thereby extracting possible co-regeneration genes. The second procedure, testing, employed a permutation test to evaluate whether possible genes were false discoveries; these genes were excluded by the testing procedure. The last procedure, screening, employed two rules, the betweenness ratio rule and interaction score rule, to select the most essential genes. A total of seventeen genes were inferred by the method, which were deemed to contribute to co-regeneration of at least two tissues. All these seventeen genes were extensively discussed to validate the utility of the method. PMID:28974058

Network-Based Method for Identifying Co- Regeneration Genes in Bone, Dentin, Nerve and Vessel Tissues.

PubMed

Chen, Lei; Pan, Hongying; Zhang, Yu-Hang; Feng, Kaiyan; Kong, XiangYin; Huang, Tao; Cai, Yu-Dong

2017-10-02

Bone and dental diseases are serious public health problems. Most current clinical treatments for these diseases can produce side effects. Regeneration is a promising therapy for bone and dental diseases, yielding natural tissue recovery with few side effects. Because soft tissues inside the bone and dentin are densely populated with nerves and vessels, the study of bone and dentin regeneration should also consider the co-regeneration of nerves and vessels. In this study, a network-based method to identify co-regeneration genes for bone, dentin, nerve and vessel was constructed based on an extensive network of protein-protein interactions. Three procedures were applied in the network-based method. The first procedure, searching, sought the shortest paths connecting regeneration genes of one tissue type with regeneration genes of other tissues, thereby extracting possible co-regeneration genes. The second procedure, testing, employed a permutation test to evaluate whether possible genes were false discoveries; these genes were excluded by the testing procedure. The last procedure, screening, employed two rules, the betweenness ratio rule and interaction score rule, to select the most essential genes. A total of seventeen genes were inferred by the method, which were deemed to contribute to co-regeneration of at least two tissues. All these seventeen genes were extensively discussed to validate the utility of the method.

Hybrid computing using a neural network with dynamic external memory.

PubMed

Graves, Alex; Wayne, Greg; Reynolds, Malcolm; Harley, Tim; Danihelka, Ivo; Grabska-Barwińska, Agnieszka; Colmenarejo, Sergio Gómez; Grefenstette, Edward; Ramalho, Tiago; Agapiou, John; Badia, Adrià Puigdomènech; Hermann, Karl Moritz; Zwols, Yori; Ostrovski, Georg; Cain, Adam; King, Helen; Summerfield, Christopher; Blunsom, Phil; Kavukcuoglu, Koray; Hassabis, Demis

2016-10-27

Artificial neural networks are remarkably adept at sensory processing, sequence learning and reinforcement learning, but are limited in their ability to represent variables and data structures and to store data over long timescales, owing to the lack of an external memory. Here we introduce a machine learning model called a differentiable neural computer (DNC), which consists of a neural network that can read from and write to an external memory matrix, analogous to the random-access memory in a conventional computer. Like a conventional computer, it can use its memory to represent and manipulate complex data structures, but, like a neural network, it can learn to do so from data. When trained with supervised learning, we demonstrate that a DNC can successfully answer synthetic questions designed to emulate reasoning and inference problems in natural language. We show that it can learn tasks such as finding the shortest path between specified points and inferring the missing links in randomly generated graphs, and then generalize these tasks to specific graphs such as transport networks and family trees. When trained with reinforcement learning, a DNC can complete a moving blocks puzzle in which changing goals are specified by sequences of symbols. Taken together, our results demonstrate that DNCs have the capacity to solve complex, structured tasks that are inaccessible to neural networks without external read-write memory.

Virtual-Lattice Based Intrusion Detection Algorithm over Actuator-Assisted Underwater Wireless Sensor Networks

PubMed Central

Yan, Jing; Li, Xiaolei; Luo, Xiaoyuan; Guan, Xinping

2017-01-01

Due to the lack of a physical line of defense, intrusion detection becomes one of the key issues in applications of underwater wireless sensor networks (UWSNs), especially when the confidentiality has prime importance. However, the resource-constrained property of UWSNs such as sparse deployment and energy constraint makes intrusion detection a challenging issue. This paper considers a virtual-lattice-based approach to the intrusion detection problem in UWSNs. Different from most existing works, the UWSNs consist of two kinds of nodes, i.e., sensor nodes (SNs), which cannot move autonomously, and actuator nodes (ANs), which can move autonomously according to the performance requirement. With the cooperation of SNs and ANs, the intruder detection probability is defined. Then, a virtual lattice-based monitor (VLM) algorithm is proposed to detect the intruder. In order to reduce the redundancy of communication links and improve detection probability, an optimal and coordinative lattice-based monitor patrolling (OCLMP) algorithm is further provided for UWSNs, wherein an equal price search strategy is given for ANs to find the shortest patrolling path. Under VLM and OCLMP algorithms, the detection probabilities are calculated, while the topology connectivity can be guaranteed. Finally, simulation results are presented to show that the proposed method in this paper can improve the detection accuracy and save the energy consumption compared with the conventional methods. PMID:28531127

Selecting the proper seed source

Treesearch

Robert Z. Callaham

1959-01-01

A forester faces many problems in selecting the proper seed source of ponderosa pine. He wants a seed source well adapted to all of the conditions of his planting site–one that can tolerate all of the extremes of heat, cold, and drought; that can resist the ravages of insects, diseases, and animals; that can produce the most of the desired product in the shortest time...

Asymptotic analysis of online algorithms and improved scheme for the flow shop scheduling problem with release dates

NASA Astrophysics Data System (ADS)

Bai, Danyu

2015-08-01

This paper discusses the flow shop scheduling problem to minimise the total quadratic completion time (TQCT) with release dates in offline and online environments. For this NP-hard problem, the investigation is focused on the performance of two online algorithms based on the Shortest Processing Time among Available jobs rule. Theoretical results indicate the asymptotic optimality of the algorithms as the problem scale is sufficiently large. To further enhance the quality of the original solutions, the improvement scheme is provided for these algorithms. A new lower bound with performance guarantee is provided, and computational experiments show the effectiveness of these heuristics. Moreover, several results of the single-machine TQCT problem with release dates are also obtained for the deduction of the main theorem.

Elastic Backbone Defines a New Transition in the Percolation Model

NASA Astrophysics Data System (ADS)

Sampaio Filho, Cesar I. N.; Andrade, José S.; Herrmann, Hans J.; Moreira, André A.

2018-04-01

The elastic backbone is the set of all shortest paths. We found a new phase transition at peb above the classical percolation threshold at which the elastic backbone becomes dense. At this transition in 2D, its fractal dimension is 1.750 ±0.003 , and one obtains a novel set of critical exponents βeb=0.50 ±0.02 , γeb=1.97 ±0.05 , and νeb=2.00 ±0.02 , fulfilling consistent critical scaling laws. Interestingly, however, the hyperscaling relation is violated. Using Binder's cumulant, we determine, with high precision, the critical probabilities peb for the triangular and tilted square lattice for site and bond percolation. This transition describes a sudden rigidification as a function of density when stretching a damaged tissue.

Statistical Properties of Cell Topology and Geometry in a Tissue-Growth Model

NASA Astrophysics Data System (ADS)

Sahlin, Patrik; Hamant, Olivier; Jönsson, Henrik

Statistical properties of cell topologies in two-dimensional tissues have recently been suggested to be a consequence of cell divisions. Different rules for the positioning of new walls in plants have been proposed, where e.g. Errara’s rule state that new walls are added with the shortest possible path dividing the mother cell’s volume into two equal parts. Here, we show that for an isotropically growing tissue Errara’s rule results in the correct distributions of number of cell neighbors as well as cellular geometries, in contrast to a random division rule. Further we show that wall mechanics constrain the isotropic growth such that the resulting cell shape distributions more closely agree with experimental data extracted from the shoot apex of Arabidopsis thaliana.

Local versus global knowledge in the Barabási-Albert scale-free network model.

PubMed

Gómez-Gardeñes, Jesús; Moreno, Yamir

2004-03-01

The scale-free model of Barabási and Albert (BA) gave rise to a burst of activity in the field of complex networks. In this paper, we revisit one of the main assumptions of the model, the preferential attachment (PA) rule. We study a model in which the PA rule is applied to a neighborhood of newly created nodes and thus no global knowledge of the network is assumed. We numerically show that global properties of the BA model such as the connectivity distribution and the average shortest path length are quite robust when there is some degree of local knowledge. In contrast, other properties such as the clustering coefficient and degree-degree correlations differ and approach the values measured for real-world networks.

Potential paths for male-mediated gene flow to and from an isolated grizzly bear population

USGS Publications Warehouse

Peck, Christopher P.; van Manen, Frank T.; Costello, Cecily M.; Haroldson, Mark A.; Landenburger, Lisa; Roberts, Lori L.; Bjornlie, Daniel D.; Mace, Richard D.

2017-01-01

For several decades, grizzly bear populations in the Greater Yellowstone Ecosystem (GYE) and the Northern Continental Divide Ecosystem (NCDE) have increased in numbers and range extent. The GYE population remains isolated and although effective population size has increased since the early 1980s, genetic connectivity between these populations remains a long-term management goal. With only ~110 km distance separating current estimates of occupied range for these populations, the potential for gene flow is likely greater now than it has been for many decades. We sought to delineate potential paths that would provide the opportunity for male-mediated gene flow between the two populations. We first developed step-selection functions to generate conductance layers using ecological, physical, and anthropogenic landscape features associated with non-stationary GPS locations of 124 male grizzly bears (199 bear-years). We then used a randomized shortest path (RSP) algorithm to estimate the average number of net passages for all grid cells in the study region, when moving from an origin to a destination node. Given habitat characteristics that were the basis for the conductance layer, movements follow certain grid cell sequences more than others and the resulting RSP values thus provide a measure of movement potential. Repeating this process for 100 pairs of random origin and destination nodes, we identified paths for three levels of random deviation (θ) from the least-cost path. We observed broad-scale concordance between model predictions for paths originating in the NCDE and those originating in the GYE for all three levels of movement exploration. Model predictions indicated that male grizzly bear movement between the ecosystems could involve a variety of routes, and verified observations of grizzly bears outside occupied range supported this finding. Where landscape features concentrated paths into corridors (e.g., because of anthropogenic influence), they typically followed neighboring mountain ranges, of which several could serve as pivotal stepping stones. The RSP layers provide detailed, spatially explicit information for land managers and organizations working with land owners to identify and prioritize conservation measures that maintain or enhance the integrity of potential areas conducive to male grizzly bear dispersal.

Rapid self-organised initiation of ad hoc sensor networks close above the percolation threshold

NASA Astrophysics Data System (ADS)

Korsnes, Reinert

2010-07-01

This work shows potentials for rapid self-organisation of sensor networks where nodes collaborate to relay messages to a common data collecting unit (sink node). The study problem is, in the sense of graph theory, to find a shortest path tree spanning a weighted graph. This is a well-studied problem where for example Dijkstra’s algorithm provides a solution for non-negative edge weights. The present contribution shows by simulation examples that simple modifications of known distributed approaches here can provide significant improvements in performance. Phase transition phenomena, which are known to take place in networks close to percolation thresholds, may explain these observations. An initial method, which here serves as reference, assumes the sink node starts organisation of the network (tree) by transmitting a control message advertising its availability for its neighbours. These neighbours then advertise their current cost estimate for routing a message to the sink. A node which in this way receives a message implying an improved route to the sink, advertises its new finding and remembers which neighbouring node the message came from. This activity proceeds until there are no more improvements to advertise to neighbours. The result is a tree network for cost effective transmission of messages to the sink (root). This distributed approach has potential for simple improvements which are of interest when minimisation of storage and communication of network information are a concern. Fast organisation of the network takes place when the number k of connections for each node ( degree) is close above its critical value for global network percolation and at the same time there is a threshold for the nodes to decide to advertise network route updates.

Apparent motion determined by surface layout not by disparity or three-dimensional distance.

PubMed

He, Z J; Nakayama, K

1994-01-13

The most meaningful events ecologically, including the motion of objects, occur in relation to or on surfaces. We run along the ground, cars travel on roads, balls roll across lawns, and so on. Even though there are other motions, such as flying of birds, it is likely that motion along surfaces is more frequent and more significant biologically. To examine whether events occurring in relation to surfaces have a preferred status in terms of visual representation, we asked whether the phenomenon of apparent motion would show a preference for motion attached to surfaces. We used a competitive three-dimensional motion paradigm and found that there is a preference to see motion between tokens placed within the same disparity as opposed to different planes. Supporting our surface-layout hypothesis, the effect of disparity was eliminated either by slanting the tokens so that they were all seen within the same surface plane or by inserting a single slanted background surface upon which the tokens could rest. Additionally, a highly curved stereoscopic surface led to the perception of a more circuitous motion path defined by that surface, instead of the shortest path in three-dimensional space.

Current Trends in Metric Conversion in the United States: Potential Trouble for National Defense.

DTIC Science & Technology

1980-05-01

measures in the United States appears inevitable, but is being prolonged due to present legisla- *tion which allows each industrial sector to convert...centralized government planning and leadership toward metrication in the shortest possible time. II. Problem: Spurred by the automotive industry , voluntary...conversion among major U.S. industries is snowballing while public resistance to met- rication is stiffening. This confrontation threatens to

Differences in physical environmental characteristics between adolescents' actual and shortest cycling routes: a study using a Google Street View-based audit.

PubMed

Verhoeven, Hannah; Van Hecke, Linde; Van Dyck, Delfien; Baert, Tim; Van de Weghe, Nico; Clarys, Peter; Deforche, Benedicte; Van Cauwenberg, Jelle

2018-05-29

The objective evaluation of the physical environmental characteristics (e.g. speed limit, cycling infrastructure) along adolescents' actual cycling routes remains understudied, although it may provide important insights into why adolescents prefer one cycling route over another. The present study aims to gain insight into the physical environmental characteristics determining the route choice of adolescent cyclists by comparing differences in physical environmental characteristics between their actual cycling routes and the shortest possible cycling routes. Adolescents (n = 204; 46.5% boys; 14.4 ± 1.2 years) recruited at secondary schools in and around Ghent (city in Flanders, northern part of Belgium) were instructed to wear a Global Positioning System device in order to identify cycling trips. For all identified cycling trips, the shortest possible route that could have been taken was calculated. Actual cycling routes that were not the shortest possible cycling routes were divided into street segments. Segments were audited with a Google Street View-based tool to assess physical environmental characteristics along actual and shortest cycling routes. Out of 160 actual cycling trips, 73.1% did not differ from the shortest possible cycling route. For actual cycling routes that were not the shortest cycling route, a speed limit of 30 km/h, roads having few buildings with windows on the street side and roads without cycle lane were more frequently present compared to the shortest possible cycling routes. A mixed land use, roads with commercial destinations, arterial roads, cycle lanes separated from traffic by white lines, small cycle lanes and cycle lanes covered by lighting were less frequently present along actual cycling routes compared to the shortest possible cycling routes. Results showed that distance mainly determines the route along which adolescents cycle. In addition, adolescents cycled more along residential streets (even if no cycle lane was present) and less along busy, arterial roads. Local authorities should provide shortcuts free from motorised traffic to meet adolescents' preference to cycle along the shortest route and to avoid cycling along arterial roads.

Siblings versus parents and friends: longitudinal linkages to adolescent externalizing problems.

PubMed

Defoe, Ivy N; Keijsers, Loes; Hawk, Skyler T; Branje, Susan; Dubas, Judith Semon; Buist, Kirsten; Frijns, Tom; van Aken, Marcel A G; Koot, Hans M; van Lier, Pol A C; Meeus, Wim

2013-08-01

It is well documented that friends' externalizing problems and negative parent-child interactions predict externalizing problems in adolescence, but relatively little is known about the role of siblings. This four-wave, multi-informant study investigated linkages of siblings' externalizing problems and sibling-adolescent negative interactions on adolescents' externalizing problems, while examining and controlling for similar linkages with friends and parents. Questionnaire data on externalizing problems and negative interactions were annually collected from 497 Dutch adolescents (M = 13.03 years, SD = 0.52, at baseline), as well as their siblings, mothers, fathers, and friends. Cross-lagged panel analyses revealed modest unique longitudinal paths from sibling externalizing problems to adolescent externalizing problems, for male and female adolescents, and for same-sex and mixed-sex sibling dyads, but only from older to younger siblings. Moreover, these paths were above and beyond significant paths from mother-adolescent negative interaction and friend externalizing problems to adolescent externalizing problems, 1 year later. No cross-lagged paths existed between sibling-adolescent negative interaction and adolescent externalizing problems. Taken together, it appears that especially older sibling externalizing problems may be a unique social risk factor for adolescent externalizing problems, equal in strength to significant parents' and friends' risk factors. © 2013 The Authors. Journal of Child Psychology and Psychiatry © 2013 Association for Child and Adolescent Mental Health.

Siblings versus parents and friends: longitudinal linkages to adolescent externalizing problems

PubMed Central

Defoe, Ivy N; Keijsers, Loes; Hawk, Skyler T; Branje, Susan; Dubas, Judith Semon; Buist, Kirsten; Frijns, Tom; van Aken, Marcel AG; Koot, Hans M; van Lier, Pol AC; Meeus, Wim

2013-01-01

Background: It is well documented that friends’ externalizing problems and negative parent–child interactions predict externalizing problems in adolescence, but relatively little is known about the role of siblings. This four-wave, multi-informant study investigated linkages of siblings’ externalizing problems and sibling–adolescent negative interactions on adolescents’ externalizing problems, while examining and controlling for similar linkages with friends and parents. Methods: Questionnaire data on externalizing problems and negative interactions were annually collected from 497 Dutch adolescents (M = 13.03 years, SD = 0.52, at baseline), as well as their siblings, mothers, fathers, and friends. Results: Cross-lagged panel analyses revealed modest unique longitudinal paths from sibling externalizing problems to adolescent externalizing problems, for male and female adolescents, and for same-sex and mixed-sex sibling dyads, but only from older to younger siblings. Moreover, these paths were above and beyond significant paths from mother–adolescent negative interaction and friend externalizing problems to adolescent externalizing problems, 1 year later. No cross-lagged paths existed between sibling–adolescent negative interaction and adolescent externalizing problems. Conclusions: Taken together, it appears that especially older sibling externalizing problems may be a unique social risk factor for adolescent externalizing problems, equal in strength to significant parents’ and friends’ risk factors. PMID:23398022

Petri net-based prediction of therapeutic targets that recover abnormally phosphorylated proteins in muscle atrophy.

PubMed

Jung, Jinmyung; Kwon, Mijin; Bae, Sunghwa; Yim, Soorin; Lee, Doheon

2018-03-05

Muscle atrophy, an involuntary loss of muscle mass, is involved in various diseases and sometimes leads to mortality. However, therapeutics for muscle atrophy thus far have had limited effects. Here, we present a new approach for therapeutic target prediction using Petri net simulation of the status of phosphorylation, with a reasonable assumption that the recovery of abnormally phosphorylated proteins can be a treatment for muscle atrophy. The Petri net model was employed to simulate phosphorylation status in three states, i.e. reference, atrophic and each gene-inhibited state based on the myocyte-specific phosphorylation network. Here, we newly devised a phosphorylation specific Petri net that involves two types of transitions (phosphorylation or de-phosphorylation) and two types of places (activation with or without phosphorylation). Before predicting therapeutic targets, the simulation results in reference and atrophic states were validated by Western blotting experiments detecting five marker proteins, i.e. RELA, SMAD2, SMAD3, FOXO1 and FOXO3. Finally, we determined 37 potential therapeutic targets whose inhibition recovers the phosphorylation status from an atrophic state as indicated by the five validated marker proteins. In the evaluation, we confirmed that the 37 potential targets were enriched for muscle atrophy-related terms such as actin and muscle contraction processes, and they were also significantly overlapping with the genes associated with muscle atrophy reported in the Comparative Toxicogenomics Database (p-value < 0.05). Furthermore, we noticed that they included several proteins that could not be characterized by the shortest path analysis. The three potential targets, i.e. BMPR1B, ROCK, and LEPR, were manually validated with the literature. In this study, we suggest a new approach to predict potential therapeutic targets of muscle atrophy with an analysis of phosphorylation status simulated by Petri net. We generated a list of the potential therapeutic targets whose inhibition recovers abnormally phosphorylated proteins in an atrophic state. They were evaluated by various approaches, such as Western blotting, GO terms, literature, known muscle atrophy-related genes and shortest path analysis. We expect the new proposed strategy to provide an understanding of phosphorylation status in muscle atrophy and to provide assistance towards identifying new therapies.

Boundary singularities produced by the motion of soap films.

PubMed

Goldstein, Raymond E; McTavish, James; Moffatt, H Keith; Pesci, Adriana I

2014-06-10

Recent work has shown that a Möbius strip soap film rendered unstable by deforming its frame changes topology to that of a disk through a "neck-pinching" boundary singularity. This behavior is unlike that of the catenoid, which transitions to two disks through a bulk singularity. It is not yet understood whether the type of singularity is generally a consequence of the surface topology, nor how this dependence could arise from an equation of motion for the surface. To address these questions we investigate experimentally, computationally, and theoretically the route to singularities of soap films with different topologies, including a family of punctured Klein bottles. We show that the location of singularities (bulk or boundary) may depend on the path of the boundary deformation. In the unstable regime the driving force for soap-film motion is the mean curvature. Thus, the narrowest part of the neck, associated with the shortest nontrivial closed geodesic of the surface, has the highest curvature and is the fastest moving. Just before onset of the instability there exists on the stable surface the shortest closed geodesic, which is the initial condition for evolution of the neck's geodesics, all of which have the same topological relationship to the frame. We make the plausible conjectures that if the initial geodesic is linked to the boundary, then the singularity will occur at the boundary, whereas if the two are unlinked initially, then the singularity will occur in the bulk. Numerical study of mean curvature flows and experiments support these conjectures.

The effect of hospital unit layout on nurse walking behavior.

PubMed

Yi, Lu; Seo, Hyun-Bo

2012-01-01

To confirm a new method for the research question, "How do different hospital unit layouts affect nurses' walking behavior and distance?" Concern is renewed regarding nurses' long walking distances because of the trend toward larger patient rooms with family areas inside, resulting in a larger overall unit size. Studies have found unit design characteristics that support nurses' efficient walking, but few have done it in units designed for patient- and family-centered care. To examine the effect of unit design on nurses' walking behavior, the authors propose a new method of observing a specific task. The authors observed nurses during the task of medication administration. Contrary to their hypotheses, results showed: (1) Experienced nurses had more unnecessary stops and longer walking distances than new nurses because of interactions; and (2) nurses in the smaller wing of the unit walked more than those in the larger wing of the same unit. The authors posit that the closeness between the nurses' path to the medication supply room and the central nurses' station affected the frequency of interactions and prompted a deviation from the shortest and most efficient path during medication administration. Observing a specific task to identify the effect of unit layout was effective, determining that overall unit shape or unit layout type might not be a good predictor of nurses' walking behavior; instead the characteristics of the path that connects functional spaces such as patient room and medication area might better predict nurses' walking behavior.

Solving the Curriculum Sequencing Problem with DNA Computing Approach

ERIC Educational Resources Information Center

Debbah, Amina; Ben Ali, Yamina Mohamed

2014-01-01

In the e-learning systems, a learning path is known as a sequence of learning materials linked to each others to help learners achieving their learning goals. As it is impossible to have the same learning path that suits different learners, the Curriculum Sequencing problem (CS) consists of the generation of a personalized learning path for each…

Open shop scheduling problem to minimize total weighted completion time

NASA Astrophysics Data System (ADS)

Bai, Danyu; Zhang, Zhihai; Zhang, Qiang; Tang, Mengqian

2017-01-01

A given number of jobs in an open shop scheduling environment must each be processed for given amounts of time on each of a given set of machines in an arbitrary sequence. This study aims to achieve a schedule that minimizes total weighted completion time. Owing to the strong NP-hardness of the problem, the weighted shortest processing time block (WSPTB) heuristic is presented to obtain approximate solutions for large-scale problems. Performance analysis proves the asymptotic optimality of the WSPTB heuristic in the sense of probability limits. The largest weight block rule is provided to seek optimal schedules in polynomial time for a special case. A hybrid discrete differential evolution algorithm is designed to obtain high-quality solutions for moderate-scale problems. Simulation experiments demonstrate the effectiveness of the proposed algorithms.

Optimal Propellant Maneuver Flight Demonstrations on ISS

NASA Technical Reports Server (NTRS)

Bhatt, Sagar; Bedrossian, Nazareth; Longacre, Kenneth; Nguyen, Louis

2013-01-01

In this paper, first ever flight demonstrations of Optimal Propellant Maneuver (OPM), a method of propulsive rotational state transition for spacecraft controlled using thrusters, is presented for the International Space Station (ISS). On August 1, 2012, two ISS reorientations of about 180deg each were performed using OPMs. These maneuvers were in preparation for the same-day launch and rendezvous of a Progress vehicle, also a first for ISS visiting vehicles. The first maneuver used 9.7 kg of propellant, whereas the second used 10.2 kg. Identical maneuvers performed without using OPMs would have used approximately 151.1kg and 150.9kg respectively. The OPM method is to use a pre-planned attitude command trajectory to accomplish a rotational state transition. The trajectory is designed to take advantage of the complete nonlinear system dynamics. The trajectory choice directly influences the cost of the maneuver, in this case, propellant. For example, while an eigenaxis maneuver is kinematically the shortest path between two orientations, following that path requires overcoming the nonlinear system dynamics, thereby increasing the cost of the maneuver. The eigenaxis path is used for ISS maneuvers using thrusters. By considering a longer angular path, the path dependence of the system dynamics can be exploited to reduce the cost. The benefits of OPM for the ISS include not only reduced lifetime propellant use, but also reduced loads, erosion, and contamination from thrusters due to fewer firings. Another advantage of the OPM is that it does not require ISS flight software modifications since it is a set of commands tailored to the specific attitude control architecture. The OPM takes advantage of the existing ISS control system architecture for propulsive rotation called USTO control mode1. USTO was originally developed to provide ISS Orbiter stack attitude control capability for a contingency tile-repair scenario, where the Orbiter is maneuvered using its robotic manipulator relative to the ISS. Since 2005 USTO has been used for nominal ISS operations.

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.

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.

The Shortest QRS Duration of an Electrocardiogram Might Be an Optimal Electrocardiographic Predictor for Response to Cardiac Resynchronization Therapy.

PubMed

Chen, Jan-Yow; Lin, Kuo-Hung; Chang, Kuan-Cheng; Chou, Che-Yi

2017-08-03

QRS duration has been associated with the response to cardiac resynchronization therapy (CRT). However, the methods for defining QRS duration to predict the outcome of CRT have discrepancies in previous reports. The aim of this study was to determine an optimal measurement of QRS duration to predict the response to CRT.Sixty-one patients who received CRT were analyzed. All patients had class III-IV heart failure, left ventricular ejection fraction not more than 35%, and complete left bundle branch block. The shortest, longest, and average QRS durations from the 12 leads of each electrocardiogram (ECG) were measured. The responses to CRT were determined using the changes in echocardiography after 6 months. Thirty-five (57.4%) patients were responders and 26 (42.6%) patients were non-responders. The pre-procedure shortest, average, and longest QRS durations and the QRS shortening (ΔQRS) of the shortest QRS duration were significantly associated with the response to CRT in a univariate logistic regression analysis (P = 0.002, P = 0.03, P = 0.04 and P = 0.04, respectively). Based on the measurement of the area under curve of the receiver operating characteristic curve, only the pre-procedure shortest QRS duration and the ΔQRS of the shortest QRS duration showed significant discrimination for the response to CRT (P = 0.002 and P = 0.038, respectively). Multivariable logistic regression showed the pre-procedure shortest QRS duration is an independent predictor for the response to CRT.The shortest QRS duration from the 12 leads of the electrocardiogram might be an optimal measurement to predict the response to CRT.

Comprehensive Materials and Morphologies Study of Ion Traps (COMMIT) for Scalable Quantum Computation

DTIC Science & Technology

2012-04-21

the photoelectric effect. The typical shortest wavelengths needed for ion traps range from 194 nm for Hg+ to 493 nm for Ba +, corresponding to 6.4-2.5...REPORT Comprehensive Materials and Morphologies Study of Ion Traps (COMMIT) for scalable Quantum Computation - Final Report 14. ABSTRACT 16. SECURITY...CLASSIFICATION OF: Trapped ion systems, are extremely promising for large-scale quantum computation, but face a vexing problem, with motional quantum

Train repathing in emergencies based on fuzzy linear programming.

PubMed

Meng, Xuelei; Cui, Bingmou

2014-01-01

Train pathing is a typical problem which is to assign the train trips on the sets of rail segments, such as rail tracks and links. This paper focuses on the train pathing problem, determining the paths of the train trips in emergencies. We analyze the influencing factors of train pathing, such as transferring cost, running cost, and social adverse effect cost. With the overall consideration of the segment and station capability constraints, we build the fuzzy linear programming model to solve the train pathing problem. We design the fuzzy membership function to describe the fuzzy coefficients. Furthermore, the contraction-expansion factors are introduced to contract or expand the value ranges of the fuzzy coefficients, coping with the uncertainty of the value range of the fuzzy coefficients. We propose a method based on triangular fuzzy coefficient and transfer the train pathing (fuzzy linear programming model) to a determinate linear model to solve the fuzzy linear programming problem. An emergency is supposed based on the real data of the Beijing-Shanghai Railway. The model in this paper was solved and the computation results prove the availability of the model and efficiency of the algorithm.

Topology Property and Dynamic Behavior of a Growing Spatial Network

NASA Astrophysics Data System (ADS)

Cao, Xian-Bin; Du, Wen-Bo; Hu, Mao-Bin; Rong, Zhi-Hai; Sun, Peng; Chen, Cai-Long

In this paper, we propose a growing spatial network (GSN) model and investigate its topology properties and dynamical behaviors. The model is generated by adding one node i with m links into a square lattice at each time step and the new node i is connected to the existing nodes with probabilities proportional to: ({kj})α /dij2, where kj is the degree of node j, α is the tunable parameter and dij is the Euclidean distance between i and j. It is found that both the degree heterogeneity and the clustering coefficient monotonously increase with the increment of α, while the average shortest path length monotonously decreases. Moreover, the evolutionary game dynamics and network traffic dynamics are investigated. Simulation results show that the value of α can also greatly influence the dynamic behaviors.

Complex networks in the Euclidean space of communicability distances

NASA Astrophysics Data System (ADS)

Estrada, Ernesto

2012-06-01

We study the properties of complex networks embedded in a Euclidean space of communicability distances. The communicability distance between two nodes is defined as the difference between the weighted sum of walks self-returning to the nodes and the weighted sum of walks going from one node to the other. We give some indications that the communicability distance identifies the least crowded routes in networks where simultaneous submission of packages is taking place. We define an index Q based on communicability and shortest path distances, which allows reinterpreting the “small-world” phenomenon as the region of minimum Q in the Watts-Strogatz model. It also allows the classification and analysis of networks with different efficiency of spatial uses. Consequently, the communicability distance displays unique features for the analysis of complex networks in different scenarios.

A dynamic network model for interbank market

NASA Astrophysics Data System (ADS)

Xu, Tao; He, Jianmin; Li, Shouwei

2016-12-01

In this paper, a dynamic network model based on agent behavior is introduced to explain the formation mechanism of interbank market network. We investigate the impact of credit lending preference on interbank market network topology, the evolution of interbank market network and stability of interbank market. Experimental results demonstrate that interbank market network is a small-world network and cumulative degree follows the power-law distribution. We find that the interbank network structure keeps dynamic stability in the network evolution process. With the increase of bank credit lending preference, network clustering coefficient increases and average shortest path length decreases monotonously, which improves the stability of the network structure. External shocks are main threats for the interbank market and the reduction of bank external investment yield rate and deposits fluctuations contribute to improve the resilience of the banking system.

Identifying influential spreaders in complex networks based on gravity formula

NASA Astrophysics Data System (ADS)

Ma, Ling-ling; Ma, Chuang; Zhang, Hai-Feng; Wang, Bing-Hong

2016-06-01

How to identify the influential spreaders in social networks is crucial for accelerating/hindering information diffusion, increasing product exposure, controlling diseases and rumors, and so on. In this paper, by viewing the k-shell value of each node as its mass and the shortest path distance between two nodes as their distance, then inspired by the idea of the gravity formula, we propose a gravity centrality index to identify the influential spreaders in complex networks. The comparison between the gravity centrality index and some well-known centralities, such as degree centrality, betweenness centrality, closeness centrality, and k-shell centrality, and so forth, indicates that our method can effectively identify the influential spreaders in real networks as well as synthetic networks. We also use the classical Susceptible-Infected-Recovered (SIR) epidemic model to verify the good performance of our method.

Epidemic spreading by objective traveling

NASA Astrophysics Data System (ADS)

Tang, Ming; Liu, Zonghua; Li, Baowen

2009-07-01

A fundamental feature of agent traveling in social networks is that traveling is usually not a random walk but with a specific destination and goes through the shortest path from starting to destination. A serious consequence of the objective traveling is that it may result in a fast epidemic spreading, such as SARS etc. In this letter we present a reaction-traveling model to study how the objective traveling influences the epidemic spreading. We consider a random scale-free meta-population network with sub-population at each node. Through a SIS model we theoretically prove that near the threshold of epidemic outbreak, the objective traveling can significantly enhance the final infected population and the infected fraction at a node is proportional to its betweenness for the traveling agents and approximately proportional to its degree for the non-traveling agents. Numerical simulations have confirmed the theoretical predictions.

Optimizing Mars Airplane Trajectory with the Application Navigation System

NASA Technical Reports Server (NTRS)

Frumkin, Michael; Riley, Derek

2004-01-01

Planning complex missions requires a number of programs to be executed in concert. The Application Navigation System (ANS), developed in the NAS Division, can execute many interdependent programs in a distributed environment. We show that the ANS simplifies user effort and reduces time in optimization of the trajectory of a martian airplane. We use a software package, Cart3D, to evaluate trajectories and a shortest path algorithm to determine the optimal trajectory. ANS employs the GridScape to represent the dynamic state of the available computer resources. Then, ANS uses a scheduler to dynamically assign ready task to machine resources and the GridScape for tracking available resources and forecasting completion time of running tasks. We demonstrate system capability to schedule and run the trajectory optimization application with efficiency exceeding 60% on 64 processors.

Long-term variability of global statistical properties of epileptic brain networks

NASA Astrophysics Data System (ADS)

Kuhnert, Marie-Therese; Elger, Christian E.; Lehnertz, Klaus

2010-12-01

We investigate the influence of various pathophysiologic and physiologic processes on global statistical properties of epileptic brain networks. We construct binary functional networks from long-term, multichannel electroencephalographic data recorded from 13 epilepsy patients, and the average shortest path length and the clustering coefficient serve as global statistical network characteristics. For time-resolved estimates of these characteristics we observe large fluctuations over time, however, with some periodic temporal structure. These fluctuations can—to a large extent—be attributed to daily rhythms while relevant aspects of the epileptic process contribute only marginally. Particularly, we could not observe clear cut changes in network states that can be regarded as predictive of an impending seizure. Our findings are of particular relevance for studies aiming at an improved understanding of the epileptic process with graph-theoretical approaches.

On the Hardness of Subset Sum Problem from Different Intervals

NASA Astrophysics Data System (ADS)

Kogure, Jun; Kunihiro, Noboru; Yamamoto, Hirosuke

The subset sum problem, which is often called as the knapsack problem, is known as an NP-hard problem, and there are several cryptosystems based on the problem. Assuming an oracle for shortest vector problem of lattice, the low-density attack algorithm by Lagarias and Odlyzko and its variants solve the subset sum problem efficiently, when the “density” of the given problem is smaller than some threshold. When we define the density in the context of knapsack-type cryptosystems, weights are usually assumed to be chosen uniformly at random from the same interval. In this paper, we focus on general subset sum problems, where this assumption may not hold. We assume that weights are chosen from different intervals, and make analysis of the effect on the success probability of above algorithms both theoretically and experimentally. Possible application of our result in the context of knapsack cryptosystems is the security analysis when we reduce the data size of public keys.

A global approach to kinematic path planning to robots with holonomic and nonholonomic constraints

NASA Technical Reports Server (NTRS)

Divelbiss, Adam; Seereeram, Sanjeev; Wen, John T.

1993-01-01

Robots in applications may be subject to holonomic or nonholonomic constraints. Examples of holonomic constraints include a manipulator constrained through the contact with the environment, e.g., inserting a part, turning a crank, etc., and multiple manipulators constrained through a common payload. Examples of nonholonomic constraints include no-slip constraints on mobile robot wheels, local normal rotation constraints for soft finger and rolling contacts in grasping, and conservation of angular momentum of in-orbit space robots. The above examples all involve equality constraints; in applications, there are usually additional inequality constraints such as robot joint limits, self collision and environment collision avoidance constraints, steering angle constraints in mobile robots, etc. The problem of finding a kinematically feasible path that satisfies a given set of holonomic and nonholonomic constraints, of both equality and inequality types is addressed. The path planning problem is first posed as a finite time nonlinear control problem. This problem is subsequently transformed to a static root finding problem in an augmented space which can then be iteratively solved. The algorithm has shown promising results in planning feasible paths for redundant arms satisfying Cartesian path following and goal endpoint specifications, and mobile vehicles with multiple trailers. In contrast to local approaches, this algorithm is less prone to problems such as singularities and local minima.

Kleinberg Complex Networks

DTIC Science & Technology

2014-10-21

linear combinations of paths. This project featured research on two classes of routing problems , namely traveling salesman problems and multicommodity...flows. One highlight of this research was our discovery of a polynomial-time algorithm for the metric traveling salesman s-t path problem whose...metric TSP would resolve one of the most venerable open problems in the theory of approximation algorithms. Our research on traveling salesman

Task Assignment and Path Planning for Multiple Autonomous Underwater Vehicles Using 3D Dubins Curves †

PubMed Central

Zhang, Meiyan; Zheng, Yahong Rosa

2017-01-01

This paper investigates the task assignment and path planning problem for multiple AUVs in three dimensional (3D) underwater wireless sensor networks where nonholonomic motion constraints of underwater AUVs in 3D space are considered. The multi-target task assignment and path planning problem is modeled by the Multiple Traveling Sales Person (MTSP) problem and the Genetic Algorithm (GA) is used to solve the MTSP problem with Euclidean distance as the cost function and the Tour Hop Balance (THB) or Tour Length Balance (TLB) constraints as the stop criterion. The resulting tour sequences are mapped to 2D Dubins curves in the X−Y plane, and then interpolated linearly to obtain the Z coordinates. We demonstrate that the linear interpolation fails to achieve G1 continuity in the 3D Dubins path for multiple targets. Therefore, the interpolated 3D Dubins curves are checked against the AUV dynamics constraint and the ones satisfying the constraint are accepted to finalize the 3D Dubins curve selection. Simulation results demonstrate that the integration of the 3D Dubins curve with the MTSP model is successful and effective for solving the 3D target assignment and path planning problem. PMID:28696377

Task Assignment and Path Planning for Multiple Autonomous Underwater Vehicles Using 3D Dubins Curves †.

PubMed

Cai, Wenyu; Zhang, Meiyan; Zheng, Yahong Rosa

2017-07-11

This paper investigates the task assignment and path planning problem for multiple AUVs in three dimensional (3D) underwater wireless sensor networks where nonholonomic motion constraints of underwater AUVs in 3D space are considered. The multi-target task assignment and path planning problem is modeled by the Multiple Traveling Sales Person (MTSP) problem and the Genetic Algorithm (GA) is used to solve the MTSP problem with Euclidean distance as the cost function and the Tour Hop Balance (THB) or Tour Length Balance (TLB) constraints as the stop criterion. The resulting tour sequences are mapped to 2D Dubins curves in the X - Y plane, and then interpolated linearly to obtain the Z coordinates. We demonstrate that the linear interpolation fails to achieve G 1 continuity in the 3D Dubins path for multiple targets. Therefore, the interpolated 3D Dubins curves are checked against the AUV dynamics constraint and the ones satisfying the constraint are accepted to finalize the 3D Dubins curve selection. Simulation results demonstrate that the integration of the 3D Dubins curve with the MTSP model is successful and effective for solving the 3D target assignment and path planning problem.

A Dynamic Bioinspired Neural Network Based Real-Time Path Planning Method for Autonomous Underwater Vehicles

PubMed Central

2017-01-01

Real-time path planning for autonomous underwater vehicle (AUV) is a very difficult and challenging task. Bioinspired neural network (BINN) has been used to deal with this problem for its many distinct advantages: that is, no learning process is needed and realization is also easy. However, there are some shortcomings when BINN is applied to AUV path planning in a three-dimensional (3D) unknown environment, including complex computing problem when the environment is very large and repeated path problem when the size of obstacles is bigger than the detection range of sensors. To deal with these problems, an improved dynamic BINN is proposed in this paper. In this proposed method, the AUV is regarded as the core of the BINN and the size of the BINN is based on the detection range of sensors. Then the BINN will move with the AUV and the computing could be reduced. A virtual target is proposed in the path planning method to ensure that the AUV can move to the real target effectively and avoid big-size obstacles automatically. Furthermore, a target attractor concept is introduced to improve the computing efficiency of neural activities. Finally, some experiments are conducted under various 3D underwater environments. The experimental results show that the proposed BINN based method can deal with the real-time path planning problem for AUV efficiently. PMID:28255297

A Dynamic Bioinspired Neural Network Based Real-Time Path Planning Method for Autonomous Underwater Vehicles.

PubMed

Ni, Jianjun; Wu, Liuying; Shi, Pengfei; Yang, Simon X

2017-01-01

Real-time path planning for autonomous underwater vehicle (AUV) is a very difficult and challenging task. Bioinspired neural network (BINN) has been used to deal with this problem for its many distinct advantages: that is, no learning process is needed and realization is also easy. However, there are some shortcomings when BINN is applied to AUV path planning in a three-dimensional (3D) unknown environment, including complex computing problem when the environment is very large and repeated path problem when the size of obstacles is bigger than the detection range of sensors. To deal with these problems, an improved dynamic BINN is proposed in this paper. In this proposed method, the AUV is regarded as the core of the BINN and the size of the BINN is based on the detection range of sensors. Then the BINN will move with the AUV and the computing could be reduced. A virtual target is proposed in the path planning method to ensure that the AUV can move to the real target effectively and avoid big-size obstacles automatically. Furthermore, a target attractor concept is introduced to improve the computing efficiency of neural activities. Finally, some experiments are conducted under various 3D underwater environments. The experimental results show that the proposed BINN based method can deal with the real-time path planning problem for AUV efficiently.

Sequential quadratic programming-based fast path planning algorithm subject to no-fly zone constraints

NASA Astrophysics Data System (ADS)

Liu, Wei; Ma, Shunjian; Sun, Mingwei; Yi, Haidong; Wang, Zenghui; Chen, Zengqiang

2016-08-01

Path planning plays an important role in aircraft guided systems. Multiple no-fly zones in the flight area make path planning a constrained nonlinear optimization problem. It is necessary to obtain a feasible optimal solution in real time. In this article, the flight path is specified to be composed of alternate line segments and circular arcs, in order to reformulate the problem into a static optimization one in terms of the waypoints. For the commonly used circular and polygonal no-fly zones, geometric conditions are established to determine whether or not the path intersects with them, and these can be readily programmed. Then, the original problem is transformed into a form that can be solved by the sequential quadratic programming method. The solution can be obtained quickly using the Sparse Nonlinear OPTimizer (SNOPT) package. Mathematical simulations are used to verify the effectiveness and rapidity of the proposed algorithm.

The path integral on the Poincaré upper half-plane with a magnetic field and for the Morse potential

NASA Astrophysics Data System (ADS)

Grosche, Christian

1988-10-01

Rigorous path integral treatments on the Poincaré upper half-plane with a magnetic field and for the Morse potential are presented. The calculation starts with the path integral on the Poincaré upper half-plane with a magnetic field. By a Fourier expansion and a non-linear transformation this problem is reformulated in terms of the path integral for the Morse potential. This latter problem can be reduced by an appropriate space-time transformation to the path integral for the harmonic oscillator with generalised angular momentum, a technique which has been developed in recent years. The well-known solution for the last problem enables one to give explicit expressions for the Feynman kernels for the Morse potential and for the Poincaré upper half-plane with magnetic field, respectively. The wavefunctions and the energy spectrum for the bound and scattering states are given, respectively.

Communication networks, soap films and vectors

NASA Astrophysics Data System (ADS)

Clark, R. C.

1981-01-01

The problem of constructing the least-cost network of connections between arbitrarily placed points is one that is common and which can be very important financially. The network may consist of motorways between towns, a grid of electric power lines, buried gas or oil pipe lines or telephone cables. Soap films trapped between parallel planes with vertical pins between them provide a 'shortest path' network and Isenberg (1975) has suggested that soap films of this sort be used to model communication networks. However soap films are unable to simulate the different costs of laying, say, a three-lane motorway instead of a two-lane one or of using a larger pipeline to take the flow from two smaller ones. Soap films, however, have considerable intrinsic interest. In the article the emphasis is on the use of soap films and communication networks as a practical means of illustrating the importance of vector and matrix methods in geometry. The power of vector methods is illustrated by the fact that given any soap film network the total length of the film can be written down by inspection if the vector positions of the pins are known. It is also possible to predict the boundaries at which 'catastrophes' occur and to decide which network has the least total length. In the field of communication networks a method is given of designing the minimum cost network linking, say, a number of oilwells, which produce at different rates to an outlet terminal.

Multi-phase arrival tracking using tetrahedral cells within a 3D layered titled transversely isotropic anisotropic model involving undulating topography and irregular interfaces

NASA Astrophysics Data System (ADS)

Li, Xing-Wang; Bai, Chao-Ying; Yue, Xiao-Peng; Greenhalgh, Stewart

2018-02-01

To overcome a major problem in current ray tracing methods, which are only capable of tracing first arrivals, and occasionally primary reflections (or mode conversions) in regular cell models, we extend in this paper the multistage triangular shortest-path method (SPM) into 3D titled transversely isotropic (TTI) anisotropic media. The proposed method is capable of tracking multi-phase arrivals composed of any kind of combinations of transmissions, mode conversions and reflections. In model parameterization, five elastic parameters, plus two angles defining the titled axis of symmetry of TTI media are sampled at the primary nodes of the tetrahedral cell, and velocity value at secondary node positions are linked by a tri-linear velocity interpolation function to the primary node velocity value of that of a tetrahedral cell, from which the group velocities of the three wave modes (qP, qSV and qSH) are computed. The multistage triangular SPM is used to track multi-phase arrivals. The uniform anisotropic test indicates that the numerical solution agrees well with the analytic solution, thus verifying the accuracy of the methodology. Several simulations and comparison results for heterogeneous models show that the proposed algorithm is able to efficiently and accurately approximate undulating surface topography and irregular subsurface velocity discontinuities. It is suitable for any combination of multi-phase arrival tracking in arbitrary tilt angle TTI media and can accommodate any magnitude of anisotropy.

Solving a Hamiltonian Path Problem with a bacterial computer

PubMed Central

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-of-concept experiment demonstrates that bacterial computing is a new way to address NP-complete problems using the inherent advantages of genetic systems. The results of our experiments also validate synthetic biology as a valuable approach to biological engineering. We designed and constructed basic parts, devices, and systems using synthetic biology principles of standardization and abstraction. PMID:19630940

On-Line Path Generation and Tracking for High-Speed Wheeled Autonomous Vehicles

DTIC Science & Technology

2006-02-17

On-Line Path Generation and Tracking for High-Speed Wheeled Autonomous Vehicles Report Title ABSTRACT In this work we proposed two semi-analytic...298-102 Enclosure 1 On-Line Path Generation and Tracking for High-Speed Wheeled Autonomous Vehicles by...Specifically, the following problems will be addressed during this project: 2.1 Challenges The problem of trajectory planning for high-speed autonomous vehicles is

Research on NC laser combined cutting optimization model of sheet metal parts

NASA Astrophysics Data System (ADS)

Wu, Z. Y.; Zhang, Y. L.; Li, L.; Wu, L. H.; Liu, N. B.

2017-09-01

The optimization problem for NC laser combined cutting of sheet metal parts was taken as the research object in this paper. The problem included two contents: combined packing optimization and combined cutting path optimization. In the problem of combined packing optimization, the method of “genetic algorithm + gravity center NFP + geometric transformation” was used to optimize the packing of sheet metal parts. In the problem of combined cutting path optimization, the mathematical model of cutting path optimization was established based on the parts cutting constraint rules of internal contour priority and cross cutting. The model played an important role in the optimization calculation of NC laser combined cutting.

A bat algorithm with mutation for UCAV path planning.

PubMed

Wang, Gaige; Guo, Lihong; Duan, Hong; Liu, Luo; Wang, Heqi

2012-01-01

Path planning for uninhabited combat air vehicle (UCAV) is a complicated high dimension optimization problem, which mainly centralizes on optimizing the flight route considering the different kinds of constrains under complicated battle field environments. Original bat algorithm (BA) is used to solve the UCAV path planning problem. Furthermore, a new bat algorithm with mutation (BAM) is proposed to solve the UCAV path planning problem, and a modification is applied to mutate between bats during the process of the new solutions updating. Then, the UCAV can find the safe path by connecting the chosen nodes of the coordinates while avoiding the threat areas and costing minimum fuel. This new approach can accelerate the global convergence speed while preserving the strong robustness of the basic BA. The realization procedure for original BA and this improved metaheuristic approach BAM is also presented. To prove the performance of this proposed metaheuristic method, BAM is compared with BA and other population-based optimization methods, such as ACO, BBO, DE, ES, GA, PBIL, PSO, and SGA. The experiment shows that the proposed approach is more effective and feasible in UCAV path planning than the other models.

Study on Earthquake Emergency Evacuation Drill Trainer Development

NASA Astrophysics Data System (ADS)

ChangJiang, L.

2016-12-01

With the improvement of China's urbanization, to ensure people survive the earthquake needs scientific routine emergency evacuation drills. Drawing on cellular automaton, shortest path algorithm and collision avoidance, we designed a model of earthquake emergency evacuation drill for school scenes. Based on this model, we made simulation software for earthquake emergency evacuation drill. The software is able to perform the simulation of earthquake emergency evacuation drill by building spatial structural model and selecting the information of people's location grounds on actual conditions of constructions. Based on the data of simulation, we can operate drilling in the same building. RFID technology could be used here for drill data collection which read personal information and send it to the evacuation simulation software via WIFI. Then the simulation software would contrast simulative data with the information of actual evacuation process, such as evacuation time, evacuation path, congestion nodes and so on. In the end, it would provide a contrastive analysis report to report assessment result and optimum proposal. We hope the earthquake emergency evacuation drill software and trainer can provide overall process disposal concept for earthquake emergency evacuation drill in assembly occupancies. The trainer can make the earthquake emergency evacuation more orderly, efficient, reasonable and scientific to fulfill the increase in coping capacity of urban hazard.

Optimal Path to a Laser Fusion Energy Power Plant

NASA Astrophysics Data System (ADS)

Bodner, Stephen

2013-10-01

There was a decision in the mid 1990s to attempt ignition using indirect-drive targets. It is now obvious that this decision was unjustified. The target design was too geometrically complex, too inefficient, and too far above plasma instability thresholds. By that same time, the mid 1990s, there had also been major advances in the direct-drive target concept. It also was not yet ready for a major test. Now, finally, because of significant advances in target designs, laser-target experiments, and laser development, the direct-drive fusion concept is ready for significant enhancements in funding, on the path to commercial fusion energy. There are two laser contenders. A KrF laser is attractive because of its shortest wavelength, broad bandwidth, and superb beam uniformity. A frequency-converted DPSSL has the disadvantage of inherently narrow bandwidth and longer wavelength, but by combining many beams in parallel one might be able to produce at the target the equivalent of an ultra-broad bandwidth. One or both of these lasers may also meet all of the engineering and economic requirements for a reactor. It is time to further develop and evaluate these two lasers as rep-rate systems, in preparation for a future high-gain fusion test.

Sink-oriented Dynamic Location Service Protocol for Mobile Sinks with an Energy Efficient Grid-Based Approach.

PubMed

Jeon, Hyeonjae; Park, Kwangjin; Hwang, Dae-Joon; Choo, Hyunseung

2009-01-01

Sensor nodes transmit the sensed information to the sink through wireless sensor networks (WSNs). They have limited power, computational capacities and memory. Portable wireless devices are increasing in popularity. Mechanisms that allow information to be efficiently obtained through mobile WSNs are of significant interest. However, a mobile sink introduces many challenges to data dissemination in large WSNs. For example, it is important to efficiently identify the locations of mobile sinks and disseminate information from multi-source nodes to the multi-mobile sinks. In particular, a stationary dissemination path may no longer be effective in mobile sink applications, due to sink mobility. In this paper, we propose a Sink-oriented Dynamic Location Service (SDLS) approach to handle sink mobility. In SDLS, we propose an Eight-Direction Anchor (EDA) system that acts as a location service server. EDA prevents intensive energy consumption at the border sensor nodes and thus provides energy balancing to all the sensor nodes. Then we propose a Location-based Shortest Relay (LSR) that efficiently forwards (or relays) data from a source node to a sink with minimal delay path. Our results demonstrate that SDLS not only provides an efficient and scalable location service, but also reduces the average data communication overhead in scenarios with multiple and moving sinks and sources.

Right-side-stretched multifractal spectra indicate small-worldness in networks

NASA Astrophysics Data System (ADS)

Oświȩcimka, Paweł; Livi, Lorenzo; Drożdż, Stanisław

2018-04-01

Complex network formalism allows to explain the behavior of systems composed by interacting units. Several prototypical network models have been proposed thus far. The small-world model has been introduced to mimic two important features observed in real-world systems: i) local clustering and ii) the possibility to move across a network by means of long-range links that significantly reduce the characteristic path length. A natural question would be whether there exist several ;types; of small-world architectures, giving rise to a continuum of models with properties (partially) shared with other models belonging to different network families. Here, we take advantage of the interplay between network theory and time series analysis and propose to investigate small-world signatures in complex networks by analyzing multifractal characteristics of time series generated from such networks. In particular, we suggest that the degree of right-sided asymmetry of multifractal spectra is linked with the degree of small-worldness present in networks. This claim is supported by numerical simulations performed on several parametric models, including prototypical small-world networks, scale-free, fractal and also real-world networks describing protein molecules. Our results also indicate that right-sided asymmetry emerges with the presence of the following topological properties: low edge density, low average shortest path, and high clustering coefficient.

Boundary singularities produced by the motion of soap films

PubMed Central

Goldstein, Raymond E.; McTavish, James; Moffatt, H. Keith; Pesci, Adriana I.

2014-01-01

Recent work has shown that a Möbius strip soap film rendered unstable by deforming its frame changes topology to that of a disk through a “neck-pinching” boundary singularity. This behavior is unlike that of the catenoid, which transitions to two disks through a bulk singularity. It is not yet understood whether the type of singularity is generally a consequence of the surface topology, nor how this dependence could arise from an equation of motion for the surface. To address these questions we investigate experimentally, computationally, and theoretically the route to singularities of soap films with different topologies, including a family of punctured Klein bottles. We show that the location of singularities (bulk or boundary) may depend on the path of the boundary deformation. In the unstable regime the driving force for soap-film motion is the mean curvature. Thus, the narrowest part of the neck, associated with the shortest nontrivial closed geodesic of the surface, has the highest curvature and is the fastest moving. Just before onset of the instability there exists on the stable surface the shortest closed geodesic, which is the initial condition for evolution of the neck’s geodesics, all of which have the same topological relationship to the frame. We make the plausible conjectures that if the initial geodesic is linked to the boundary, then the singularity will occur at the boundary, whereas if the two are unlinked initially, then the singularity will occur in the bulk. Numerical study of mean curvature flows and experiments support these conjectures. PMID:24843162

Roads at risk - traffic detours from debris flows in southern Norway

NASA Astrophysics Data System (ADS)

Meyer, N. K.; Schwanghart, W.; Korup, O.; Nadim, F.

2014-10-01

Globalization and interregional exchange of people, goods, and services has boosted the importance of and reliance on all kinds of transport networks. The linear structure of road networks is especially sensitive to natural hazards. In southern Norway, steep topography and extreme weather events promote frequent traffic disruption caused by debris flows. Topographic susceptibility and trigger frequency maps serve as input into a hazard appraisal at the scale of first-order catchments to quantify the impact of debris flows on the road network in terms of a failure likelihood of each link connecting two network vertices, e.g., road junctions. We compute total additional traffic loads as a function of traffic volume and excess distance, i.e. the extra length of an alternative path connecting two previously disrupted network vertices using a shortest-path algorithm. Our risk metric of link failure is the total additional annual traffic load expressed as vehicle kilometers because of debris-flow related road closures. We present two scenarios demonstrating the impact of debris flows on the road network, and quantify the associated path failure likelihood between major cities in southern Norway. The scenarios indicate that major routes crossing the central and northwestern part of the study area are associated with high link failure risk. Yet options for detours on major routes are manifold, and incur only little additional costs provided that drivers are sufficiently well informed about road closures. Our risk estimates may be of importance to road network managers and transport companies relying of speedy delivery of services and goods.

Roads at risk: traffic detours from debris flows in southern Norway

NASA Astrophysics Data System (ADS)

Meyer, N. K.; Schwanghart, W.; Korup, O.; Nadim, F.

2015-05-01

Globalisation and interregional exchange of people, goods, and services has boosted the importance of and reliance on all kinds of transport networks. The linear structure of road networks is especially sensitive to natural hazards. In southern Norway, steep topography and extreme weather events promote frequent traffic disruption caused by debris flows. Topographic susceptibility and trigger frequency maps serve as input into a hazard appraisal at the scale of first-order catchments to quantify the impact of debris flows on the road network in terms of a failure likelihood of each link connecting two network vertices, e.g. road junctions. We compute total additional traffic loads as a function of traffic volume and excess distance, i.e. the extra length of an alternative path connecting two previously disrupted network vertices using a shortest-path algorithm. Our risk metric of link failure is the total additional annual traffic load, expressed as vehicle kilometres, because of debris-flow-related road closures. We present two scenarios demonstrating the impact of debris flows on the road network and quantify the associated path-failure likelihood between major cities in southern Norway. The scenarios indicate that major routes crossing the central and north-western part of the study area are associated with high link-failure risk. Yet options for detours on major routes are manifold and incur only little additional costs provided that drivers are sufficiently well informed about road closures. Our risk estimates may be of importance to road network managers and transport companies relying on speedy delivery of services and goods.

Cortical brain connectivity evaluated by graph theory in dementia: a correlation study between functional and structural data.

PubMed

Vecchio, Fabrizio; Miraglia, Francesca; Curcio, Giuseppe; Altavilla, Riccardo; Scrascia, Federica; Giambattistelli, Federica; Quattrocchi, Carlo Cosimo; Bramanti, Placido; Vernieri, Fabrizio; Rossini, Paolo Maria

2015-01-01

A relatively new approach to brain function in neuroscience is the "functional connectivity", namely the synchrony in time of activity in anatomically-distinct but functionally-collaborating brain regions. On the other hand, diffusion tensor imaging (DTI) is a recently developed magnetic resonance imaging (MRI)-based technique with the capability to detect brain structural connection with fractional anisotropy (FA) identification. FA decrease has been observed in the corpus callosum of subjects with Alzheimer's disease (AD) and mild cognitive impairment (MCI, an AD prodromal stage). Corpus callosum splenium DTI abnormalities are thought to be associated with functional disconnections among cortical areas. This study aimed to investigate possible correlations between structural damage, measured by MRI-DTI, and functional abnormalities of brain integration, measured by characteristic path length detected in resting state EEG source activity (40 participants: 9 healthy controls, 10 MCI, 10 mild AD, 11 moderate AD). For each subject, undirected and weighted brain network was built to evaluate graph core measures. eLORETA lagged linear connectivity values were used as weight of the edges of the network. Results showed that callosal FA reduction is associated to a loss of brain interhemispheric functional connectivity characterized by increased delta and decreased alpha path length. These findings suggest that "global" (average network shortest path length representing an index of how efficient is the information transfer between two parts of the network) functional measure can reflect the reduction of fiber connecting the two hemispheres as revealed by DTI analysis and also anticipate in time this structural loss.

UCAV path planning in the presence of radar-guided surface-to-air missile threats

NASA Astrophysics Data System (ADS)

Zeitz, Frederick H., III

This dissertation addresses the problem of path planning for unmanned combat aerial vehicles (UCAVs) in the presence of radar-guided surface-to-air missiles (SAMs). The radars, collocated with SAM launch sites, operate within the structure of an Integrated Air Defense System (IADS) that permits communication and cooperation between individual radars. The problem is formulated in the framework of the interaction between three sub-systems: the aircraft, the IADS, and the missile. The main features of this integrated model are: The aircraft radar cross section (RCS) depends explicitly on both the aspect and bank angles; hence, the RCS and aircraft dynamics are coupled. The probabilistic nature of IADS tracking is accounted for; namely, the probability that the aircraft has been continuously tracked by the IADS depends on the aircraft RCS and range from the perspective of each radar within the IADS. Finally, the requirement to maintain tracking prior to missile launch and during missile flyout are also modeled. Based on this model, the problem of UCAV path planning is formulated as a minimax optimal control problem, with the aircraft bank angle serving as control. Necessary conditions of optimality for this minimax problem are derived. Based on these necessary conditions, properties of the optimal paths are derived. These properties are used to discretize the dynamic optimization problem into a finite-dimensional, nonlinear programming problem that can be solved numerically. Properties of the optimal paths are also used to initialize the numerical procedure. A homotopy method is proposed to solve the finite-dimensional, nonlinear programming problem, and a heuristic method is proposed to improve the discretization during the homotopy process. Based upon the properties of numerical solutions, a method is proposed for parameterizing and storing information for later recall in flight to permit rapid replanning in response to changing threats. Illustrative examples are presented that confirm the standard flying tactics of "denying range, aspect, and aim," by yielding flight paths that "weave" to avoid long exposures of aspects with large RCS.

jCompoundMapper: An open source Java library and command-line tool for chemical fingerprints

PubMed Central

2011-01-01

Background The decomposition of a chemical graph is a convenient approach to encode information of the corresponding organic compound. While several commercial toolkits exist to encode molecules as so-called fingerprints, only a few open source implementations are available. The aim of this work is to introduce a library for exactly defined molecular decompositions, with a strong focus on the application of these features in machine learning and data mining. It provides several options such as search depth, distance cut-offs, atom- and pharmacophore typing. Furthermore, it provides the functionality to combine, to compare, or to export the fingerprints into several formats. Results We provide a Java 1.6 library for the decomposition of chemical graphs based on the open source Chemistry Development Kit toolkit. We reimplemented popular fingerprinting algorithms such as depth-first search fingerprints, extended connectivity fingerprints, autocorrelation fingerprints (e.g. CATS2D), radial fingerprints (e.g. Molprint2D), geometrical Molprint, atom pairs, and pharmacophore fingerprints. We also implemented custom fingerprints such as the all-shortest path fingerprint that only includes the subset of shortest paths from the full set of paths of the depth-first search fingerprint. As an application of jCompoundMapper, we provide a command-line executable binary. We measured the conversion speed and number of features for each encoding and described the composition of the features in detail. The quality of the encodings was tested using the default parametrizations in combination with a support vector machine on the Sutherland QSAR data sets. Additionally, we benchmarked the fingerprint encodings on the large-scale Ames toxicity benchmark using a large-scale linear support vector machine. The results were promising and could often compete with literature results. On the large Ames benchmark, for example, we obtained an AUC ROC performance of 0.87 with a reimplementation of the extended connectivity fingerprint. This result is comparable to the performance achieved by a non-linear support vector machine using state-of-the-art descriptors. On the Sutherland QSAR data set, the best fingerprint encodings showed a comparable or better performance on 5 of the 8 benchmarks when compared against the results of the best descriptors published in the paper of Sutherland et al. Conclusions jCompoundMapper is a library for chemical graph fingerprints with several tweaking possibilities and exporting options for open source data mining toolkits. The quality of the data mining results, the conversion speed, the LPGL software license, the command-line interface, and the exporters should be useful for many applications in cheminformatics like benchmarks against literature methods, comparison of data mining algorithms, similarity searching, and similarity-based data mining. PMID:21219648

Robustness of cluster synchronous patterns in small-world networks with inter-cluster co-competition balance

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Jianbao; Ma, Zhongjun, E-mail: mzj1234402@163.com; Chen, Guanrong

All edges in the classical Watts and Strogatz's small-world network model are unweighted and cooperative (positive). By introducing competitive (negative) inter-cluster edges and assigning edge weights to mimic more realistic networks, this paper develops a modified model which possesses co-competitive weighted couplings and cluster structures while maintaining the common small-world network properties of small average shortest path lengths and large clustering coefficients. Based on theoretical analysis, it is proved that the new model with inter-cluster co-competition balance has an important dynamical property of robust cluster synchronous pattern formation. More precisely, clusters will neither merge nor split regardless of adding ormore » deleting nodes and edges, under the condition of inter-cluster co-competition balance. Numerical simulations demonstrate the robustness of the model against the increase of the coupling strength and several topological variations.« less

General formulation of long-range degree correlations in complex networks

NASA Astrophysics Data System (ADS)

Fujiki, Yuka; Takaguchi, Taro; Yakubo, Kousuke

2018-06-01

We provide a general framework for analyzing degree correlations between nodes separated by more than one step (i.e., beyond nearest neighbors) in complex networks. One joint and four conditional probability distributions are introduced to fully describe long-range degree correlations with respect to degrees k and k' of two nodes and shortest path length l between them. We present general relations among these probability distributions and clarify the relevance to nearest-neighbor degree correlations. Unlike nearest-neighbor correlations, some of these probability distributions are meaningful only in finite-size networks. Furthermore, as a baseline to determine the existence of intrinsic long-range degree correlations in a network other than inevitable correlations caused by the finite-size effect, the functional forms of these probability distributions for random networks are analytically evaluated within a mean-field approximation. The utility of our argument is demonstrated by applying it to real-world networks.

Time-resolved imaging of electrical discharge development in underwater bubbles

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tu, Yalong; Xia, Hualei; Yang, Yong, E-mail: yangyong@hust.edu.cn, E-mail: luxinpei@hust.edu.cn

2016-01-15

The formation and development of plasma in single air bubbles submerged in water were investigated. The difference in the discharge dynamics and the after-effects on the bubble were investigated using a 900 000 frame per second high-speed charge-coupled device camera. It was observed that depending on the position of the electrodes, the breakdown could be categorized into two modes: (1) direct discharge mode, where the high voltage and ground electrodes were in contact with the bubble, and the streamer would follow the shortest path and propagate along the axis of the bubble and (2) dielectric barrier mode, where the groundmore » electrode was not in touch with the bubble surface, and the streamer would form along the inner surface of the bubble. The oscillation of the bubble and the development of instabilities on the bubble surface were also discussed.« less

Robustness of cluster synchronous patterns in small-world networks with inter-cluster co-competition balance

NASA Astrophysics Data System (ADS)

Zhang, Jianbao; Ma, Zhongjun; Chen, Guanrong

2014-06-01

All edges in the classical Watts and Strogatz's small-world network model are unweighted and cooperative (positive). By introducing competitive (negative) inter-cluster edges and assigning edge weights to mimic more realistic networks, this paper develops a modified model which possesses co-competitive weighted couplings and cluster structures while maintaining the common small-world network properties of small average shortest path lengths and large clustering coefficients. Based on theoretical analysis, it is proved that the new model with inter-cluster co-competition balance has an important dynamical property of robust cluster synchronous pattern formation. More precisely, clusters will neither merge nor split regardless of adding or deleting nodes and edges, under the condition of inter-cluster co-competition balance. Numerical simulations demonstrate the robustness of the model against the increase of the coupling strength and several topological variations.

Analysis of the Chinese air route network as a complex network

NASA Astrophysics Data System (ADS)

Cai, Kai-Quan; Zhang, Jun; Du, Wen-Bo; Cao, Xian-Bin

2012-02-01

The air route network, which supports all the flight activities of the civil aviation, is the most fundamental infrastructure of air traffic management system. In this paper, we study the Chinese air route network (CARN) within the framework of complex networks. We find that CARN is a geographical network possessing exponential degree distribution, low clustering coefficient, large shortest path length and exponential spatial distance distribution that is obviously different from that of the Chinese airport network (CAN). Besides, via investigating the flight data from 2002 to 2010, we demonstrate that the topology structure of CARN is homogeneous, howbeit the distribution of flight flow on CARN is rather heterogeneous. In addition, the traffic on CARN keeps growing in an exponential form and the increasing speed of west China is remarkably larger than that of east China. Our work will be helpful to better understand Chinese air traffic systems.

Scalable software-defined optical networking with high-performance routing and wavelength assignment algorithms.

PubMed

Lee, Chankyun; Cao, Xiaoyuan; Yoshikane, Noboru; Tsuritani, Takehiro; Rhee, June-Koo Kevin

2015-10-19

The feasibility of software-defined optical networking (SDON) for a practical application critically depends on scalability of centralized control performance. The paper, highly scalable routing and wavelength assignment (RWA) algorithms are investigated on an OpenFlow-based SDON testbed for proof-of-concept demonstration. Efficient RWA algorithms are proposed to achieve high performance in achieving network capacity with reduced computation cost, which is a significant attribute in a scalable centralized-control SDON. The proposed heuristic RWA algorithms differ in the orders of request processes and in the procedures of routing table updates. Combined in a shortest-path-based routing algorithm, a hottest-request-first processing policy that considers demand intensity and end-to-end distance information offers both the highest throughput of networks and acceptable computation scalability. We further investigate trade-off relationship between network throughput and computation complexity in routing table update procedure by a simulation study.

Homeostatic reinforcement learning for integrating reward collection and physiological stability.

PubMed

Keramati, Mehdi; Gutkin, Boris

2014-12-02

Efficient regulation of internal homeostasis and defending it against perturbations requires adaptive behavioral strategies. However, the computational principles mediating the interaction between homeostatic and associative learning processes remain undefined. Here we use a definition of primary rewards, as outcomes fulfilling physiological needs, to build a normative theory showing how learning motivated behaviors may be modulated by internal states. Within this framework, we mathematically prove that seeking rewards is equivalent to the fundamental objective of physiological stability, defining the notion of physiological rationality of behavior. We further suggest a formal basis for temporal discounting of rewards by showing that discounting motivates animals to follow the shortest path in the space of physiological variables toward the desired setpoint. We also explain how animals learn to act predictively to preclude prospective homeostatic challenges, and several other behavioral patterns. Finally, we suggest a computational role for interaction between hypothalamus and the brain reward system.

[Research on brain white matter network in cerebral palsy infant].

PubMed

Li, Jun; Yang, Cheng; Wang, Yuanjun; Nie, Shengdong

2017-10-01

Present study used diffusion tensor image and tractography to construct brain white matter networks of 15 cerebral palsy infants and 30 healthy infants that matched for age and gender. After white matter network analysis, we found that both cerebral palsy and healthy infants had a small-world topology in white matter network, but cerebral palsy infants exhibited abnormal topological organization: increased shortest path length but decreased normalize clustering coefficient, global efficiency and local efficiency. Furthermore, we also found that white matter network hub regions were located in the left cuneus, precuneus, and left posterior cingulate gyrus. However, some abnormal nodes existed in the frontal, temporal, occipital and parietal lobes of cerebral palsy infants. These results indicated that the white matter networks for cerebral palsy infants were disrupted, which was consistent with previous studies about the abnormal brain white matter areas. This work could help us further study the pathogenesis of cerebral palsy infants.

Interplay between geo-population factors and hierarchy of cities in multilayer urban networks.

PubMed

Makarov, Vladimir V; Hramov, Alexander E; Kirsanov, Daniil V; Maksimenko, Vladimir A; Goremyko, Mikhail V; Ivanov, Alexey V; Yashkov, Ivan A; Boccaletti, Stefano

2017-12-08

Only taking into consideration the interplay between processes occurring at different levels of a country can provide the complete social and geopolitical plot of its urban system. We study the interaction of the administrative structure and the geographical connectivity between cities with the help of a multiplex network approach. We found that a spatially-distributed geo-network imposes its own ranking to the hierarchical administrative network, while the latter redistributes the shortest paths between nodes in the geographical layer. Using both real demographic data of population censuses of the Republic of Kazakhstan and theoretical models, we show that in a country-scale urban network and for each specific city, the geographical neighbouring with highly populated areas is more important than its political setting. Furthermore, the structure of political subordination is instead crucial for the wealth of transportation network and communication between populated regions of the country.

A Decision Processing Algorithm for CDC Location Under Minimum Cost SCM Network

NASA Astrophysics Data System (ADS)

Park, N. K.; Kim, J. Y.; Choi, W. Y.; Tian, Z. M.; Kim, D. J.

Location of CDC in the matter of network on Supply Chain is becoming on the high concern these days. Present status of methods on CDC has been mainly based on the calculation manually by the spread sheet to achieve the goal of minimum logistics cost. This study is focused on the development of new processing algorithm to overcome the limit of present methods, and examination of the propriety of this algorithm by case study. The algorithm suggested by this study is based on the principle of optimization on the directive GRAPH of SCM model and suggest the algorithm utilizing the traditionally introduced MST, shortest paths finding methods, etc. By the aftermath of this study, it helps to assess suitability of the present on-going SCM network and could be the criterion on the decision-making process for the optimal SCM network building-up for the demand prospect in the future.

Modeling Physarum space exploration using memristors

NASA Astrophysics Data System (ADS)

Ntinas, V.; Vourkas, I.; Sirakoulis, G. Ch; Adamatzky, A. I.

2017-05-01

Slime mold Physarum polycephalum optimizes its foraging behaviour by minimizing the distances between the sources of nutrients it spans. When two sources of nutrients are present, the slime mold connects the sources, with its protoplasmic tubes, along the shortest path. We present a two-dimensional mesh grid memristor based model as an approach to emulate Physarum’s foraging strategy, which includes space exploration and reinforcement of the optimally formed interconnection network in the presence of multiple aliment sources. The proposed algorithmic approach utilizes memristors and LC contours and is tested in two of the most popular computational challenges for Physarum, namely maze and transportation networks. Furthermore, the presented model is enriched with the notion of noise presence, which positively contributes to a collective behavior and enables us to move from deterministic to robust results. Consequently, the corresponding simulation results manage to reproduce, in a much better qualitative way, the expected transportation networks.

Brain white matter fiber estimation and tractography using Q-ball imaging and Bayesian MODEL.

PubMed

Lu, Meng

2015-01-01

Diffusion tensor imaging allows for the non-invasive in vivo mapping of the brain tractography. However, fiber bundles have complex structures such as fiber crossings, fiber branchings and fibers with large curvatures that tensor imaging (DTI) cannot accurately handle. This study presents a novel brain white matter tractography method using Q-ball imaging as the data source instead of DTI, because QBI can provide accurate information about multiple fiber crossings and branchings in a single voxel using an orientation distribution function (ODF). The presented method also uses graph theory to construct the Bayesian model-based graph, so that the fiber tracking between two voxels can be represented as the shortest path in a graph. Our experiment showed that our new method can accurately handle brain white matter fiber crossings and branchings, and reconstruct brain tractograhpy both in phantom data and real brain data.

Cascade defense via routing in complex networks

NASA Astrophysics Data System (ADS)

Xu, Xiao-Lan; Du, Wen-Bo; Hong, Chen

2015-05-01

As the cascading failures in networked traffic systems are becoming more and more serious, research on cascade defense in complex networks has become a hotspot in recent years. In this paper, we propose a traffic-based cascading failure model, in which each packet in the network has its own source and destination. When cascade is triggered, packets will be redistributed according to a given routing strategy. Here, a global hybrid (GH) routing strategy, which uses the dynamic information of the queue length and the static information of nodes' degree, is proposed to defense the network cascade. Comparing GH strategy with the shortest path (SP) routing, efficient routing (ER) and global dynamic (GD) routing strategies, we found that GH strategy is more effective than other routing strategies in improving the network robustness against cascading failures. Our work provides insight into the robustness of networked traffic systems.

Goal-oriented robot navigation learning using a multi-scale space representation.

PubMed

Llofriu, M; Tejera, G; Contreras, M; Pelc, T; Fellous, J M; Weitzenfeld, A

2015-12-01

There has been extensive research in recent years on the multi-scale nature of hippocampal place cells and entorhinal grid cells encoding which led to many speculations on their role in spatial cognition. In this paper we focus on the multi-scale nature of place cells and how they contribute to faster learning during goal-oriented navigation when compared to a spatial cognition system composed of single scale place cells. The task consists of a circular arena with a fixed goal location, in which a robot is trained to find the shortest path to the goal after a number of learning trials. Synaptic connections are modified using a reinforcement learning paradigm adapted to the place cells multi-scale architecture. The model is evaluated in both simulation and physical robots. We find that larger scale and combined multi-scale representations favor goal-oriented navigation task learning. Copyright © 2015 Elsevier Ltd. All rights reserved.

Surname complex network for Brazil and Portugal

NASA Astrophysics Data System (ADS)

Ferreira, G. D.; Viswanathan, G. M.; da Silva, L. R.; Herrmann, H. J.

2018-06-01

We present a study of social networks based on the analysis of Brazilian and Portuguese family names (surnames). We construct networks whose nodes are names of families and whose edges represent parental relations between two families. From these networks we extract the connectivity distribution, clustering coefficient, shortest path and centrality. We find that the connectivity distribution follows an approximate power law. We associate the number of hubs, centrality and entropy to the degree of miscegenation in the societies in both countries. Our results show that Portuguese society has a higher miscegenation degree than Brazilian society. All networks analyzed lead to approximate inverse square power laws in the degree distribution. We conclude that the thermodynamic limit is reached for small networks (3 or 4 thousand nodes). The assortative mixing of all networks is negative, showing that the more connected vertices are connected to vertices with lower connectivity. Finally, the network of surnames presents some small world characteristics.

Principal curve detection in complicated graph images

NASA Astrophysics Data System (ADS)

Liu, Yuncai; Huang, Thomas S.

2001-09-01

Finding principal curves in an image is an important low level processing in computer vision and pattern recognition. Principal curves are those curves in an image that represent boundaries or contours of objects of interest. In general, a principal curve should be smooth with certain length constraint and allow either smooth or sharp turning. In this paper, we present a method that can efficiently detect principal curves in complicated map images. For a given feature image, obtained from edge detection of an intensity image or thinning operation of a pictorial map image, the feature image is first converted to a graph representation. In graph image domain, the operation of principal curve detection is performed to identify useful image features. The shortest path and directional deviation schemes are used in our algorithm os principal verve detection, which is proven to be very efficient working with real graph images.

Comparison of some evolutionary algorithms for optimization of the path synthesis problem

NASA Astrophysics Data System (ADS)

Grabski, Jakub Krzysztof; Walczak, Tomasz; Buśkiewicz, Jacek; Michałowska, Martyna

2018-01-01

The paper presents comparison of the results obtained in a mechanism synthesis by means of some selected evolutionary algorithms. The optimization problem considered in the paper as an example is the dimensional synthesis of the path generating four-bar mechanism. In order to solve this problem, three different artificial intelligence algorithms are employed in this study.

Three-Dimensional Path Planning for Uninhabited Combat Aerial Vehicle Based on Predator-Prey Pigeon-Inspired Optimization in Dynamic Environment.

PubMed

Zhang, Bo; Duan, Haibin

2017-01-01

Three-dimension path planning of uninhabited combat aerial vehicle (UCAV) is a complicated optimal problem, which mainly focused on optimizing the flight route considering the different types of constrains under complex combating environment. A novel predator-prey pigeon-inspired optimization (PPPIO) is proposed to solve the UCAV three-dimension path planning problem in dynamic environment. Pigeon-inspired optimization (PIO) is a new bio-inspired optimization algorithm. In this algorithm, map and compass operator model and landmark operator model are used to search the best result of a function. The prey-predator concept is adopted to improve global best properties and enhance the convergence speed. The characteristics of the optimal path are presented in the form of a cost function. The comparative simulation results show that our proposed PPPIO algorithm is more efficient than the basic PIO, particle swarm optimization (PSO), and different evolution (DE) in solving UCAV three-dimensional path planning problems.

Rotational-path decomposition based recursive planning for spacecraft attitude reorientation

NASA Astrophysics Data System (ADS)

Xu, Rui; Wang, Hui; Xu, Wenming; Cui, Pingyuan; Zhu, Shengying

2018-02-01

The spacecraft reorientation is a common task in many space missions. With multiple pointing constraints, it is greatly difficult to solve the constrained spacecraft reorientation planning problem. To deal with this problem, an efficient rotational-path decomposition based recursive planning (RDRP) method is proposed in this paper. The uniform pointing-constraint-ignored attitude rotation planning process is designed to solve all rotations without considering pointing constraints. Then the whole path is checked node by node. If any pointing constraint is violated, the nearest critical increment approach will be used to generate feasible alternative nodes in the process of rotational-path decomposition. As the planning path of each subdivision may still violate pointing constraints, multiple decomposition is needed and the reorientation planning is designed as a recursive manner. Simulation results demonstrate the effectiveness of the proposed method. The proposed method has been successfully applied in two SPARK microsatellites to solve onboard constrained attitude reorientation planning problem, which were developed by the Shanghai Engineering Center for Microsatellites and launched on 22 December 2016.

Planning minimum-energy paths in an off-road environment with anisotropic traversal costs and motion constraints. Doctoral thesis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ross, R.S.

1989-06-01

For a vehicle operating across arbitrarily-contoured terrain, finding the most fuel-efficient route between two points can be viewed as a high-level global path-planning problem with traversal costs and stability dependent on the direction of travel (anisotropic). The problem assumes a two-dimensional polygonal map of homogeneous cost regions for terrain representation constructed from elevation information. The anisotropic energy cost of vehicle motion has a non-braking component dependent on horizontal distance, a braking component dependent on vertical distance, and a constant path-independent component. The behavior of minimum-energy paths is then proved to be restricted to a small, but optimal set of traversalmore » types. An optimal-path-planning algorithm, using a heuristic search technique, reduces the infinite number of paths between the start and goal points to a finite number by generating sequences of goal-feasible window lists from analyzing the polygonal map and applying pruning criteria. The pruning criteria consist of visibility analysis, heading analysis, and region-boundary constraints. Each goal-feasible window lists specifies an associated convex optimization problem, and the best of all locally-optimal paths through the goal-feasible window lists is the globally-optimal path. These ideas have been implemented in a computer program, with results showing considerably better performance than the exponential average-case behavior predicted.« less

Negative emotionality moderates associations among attachment, toddler sleep, and later problem behaviors.

PubMed

Troxel, Wendy M; Trentacosta, Christopher J; Forbes, Erika E; Campbell, Susan B

2013-02-01

Secure parent-child relationships are implicated in children's self-regulation, including the ability to self-soothe at bedtime. Sleep, in turn, may serve as a pathway linking attachment security with subsequent emotional and behavioral problems in children. We used path analysis to examine the direct relationship between attachment security and maternal reports of sleep problems during toddlerhood and the degree to which sleep serves as a pathway linking attachment with subsequent teacher-reported emotional and behavioral problems. We also examined infant negative emotionality as a vulnerability factor that may potentiate attachment-sleep-adjustment outcomes. Data were drawn from 776 mother-infant dyads participating in the National Institute of Child and Human Development Study of Early Child Care. After statistically adjusting for mother and child characteristics, including child sleep and emotional and behavioral problems at 24 months, we found no evidence for a statistically significant direct path between attachment security and sleep problems at 36 months; however, there was a direct relationship between sleep problems at 36 months and internalizing problems at 54 months. Path models that examined the moderating influence of infant negative emotionality demonstrated significant direct relationships between attachment security and toddler sleep problems and between sleep problems and subsequent emotional and behavioral problems, but only among children characterized by high negative emotionality at 6 months. In addition, among this subset, there was a significant indirect path between attachment and internalizing problems through sleep problems. These longitudinal findings implicate sleep as one critical pathway linking attachment security with adjustment difficulties, particularly among temperamentally vulnerable children. PsycINFO Database Record (c) 2013 APA, all rights reserved.

Negative Emotionality Moderates Associations among Attachment, Toddler Sleep, and Later Problem Behaviors

PubMed Central

Troxel, Wendy M.; Trentacosta, Christopher J.; Forbes, Erika E.; Campbell, Susan B.

2013-01-01

Secure parent-child relationships are implicated in children’s self-regulation, including the ability to self-soothe at bedtime. Sleep, in turn, may serve as a pathway linking attachment security with subsequent emotional and behavioral problems in children. We used path analysis to examine the direct relationship between attachment security and maternal-reports of sleep problems during toddlerhood, and the degree to which sleep serves as a pathway linking attachment with subsequent teacher-reported emotional and behavioral problems. We also examined infant negative emotionality as a vulnerability factor that may potentiate attachment-sleep-adjustment outcomes. Data were drawn from 776 mother-infant dyads participating in the NICHD Study of Early Child Care (SECC). In the full sample, after statistically adjusting for mother and child characteristics, including child sleep and emotional and behavioral problems at 24 months, we did not find evidence for a statistically significant direct path between attachment security and sleep problems at 36 months; however, there was a direct relationship between sleep problems at 36 months and internalizing problems at 54 months. Path models that examined the moderating influence of infant negative emotionality demonstrated significant direct relationships between attachment security and toddler sleep problems, and sleep problems and subsequent emotional and behavioral problems, but only among children characterized by high negative emotionality at 6 months of age. In addition, among this subset, there was a significant indirect path between attachment and internalizing problems through sleep problems. These longitudinal findings implicate sleep as one critical pathway linking attachment security with adjustment difficulties, particularly among temperamentally vulnerable children. PMID:23421840

Optimal Path Planning and Control of Quadrotor Unmanned Aerial Vehicle for Area Coverage

NASA Astrophysics Data System (ADS)

Fan, Jiankun

An Unmanned Aerial Vehicle (UAV) is an aircraft without a human pilot on board. Its flight is controlled either autonomously by computers onboard the vehicle, or remotely by a pilot on the ground, or by another vehicle. In recent years, UAVs have been used more commonly than prior years. The example includes areo-camera where a high speed camera was attached to a UAV which can be used as an airborne camera to obtain aerial video. It also could be used for detecting events on ground for tasks such as surveillance and monitoring which is a common task during wars. Similarly UAVs can be used for relaying communication signal during scenarios when regular communication infrastructure is destroyed. The objective of this thesis is motivated from such civilian operations such as search and rescue or wildfire detection and monitoring. One scenario is that of search and rescue where UAV's objective is to geo-locate a person in a given area. The task is carried out with the help of a camera whose live feed is provided to search and rescue personnel. For this objective, the UAV needs to carry out scanning of the entire area in the shortest time. The aim of this thesis to develop algorithms to enable a UAV to scan an area in optimal time, a problem referred to as "Coverage Control" in literature. The thesis focuses on a special kind of UAVs called "quadrotor" that is propelled with the help of four rotors. The overall objective of this thesis is achieved via solving two problems. The first problem is to develop a dynamic control model of quadrtor. In this thesis, a proportional-integral-derivative controller (PID) based feedback control system is developed and implemented on MATLAB's Simulink. The PID controller helps track any given trajectory. The second problem is to design a trajectory that will fulfill the mission. The planed trajectory should make sure the quadrotor will scan the whole area without missing any part to make sure that the quadrotor will find the lost person in the area. The generated trajectory should also be optimal. This is achieved via making some assumptions on the form of the trajectory and solving the optimization problem to obtain optimal parameters of the trajectory. The proposed techniques are validated with the help of numerous simulations.

Assessment of Oropharyngeal Dysphagia in Patients With Parkinson Disease: Use of Ultrasonography.

PubMed

Oh, Eun Hyun; Seo, Jin Seok; Kang, Hyo Jung

2016-04-01

To compare tongue thickness, the shortest hyoid-thyroid approximation (distance between the hyoid bone and thyroid cartilage), and the time interval between the initiation of tongue movement and the time of the shortest hyoid-thyroid approximation, by using ultrasonography in healthy controls and patients with Parkinson disease (PD). Healthy controls and PD patients with dysphagia were compared. Ultrasonography was performed 3 times for the evaluation of tongue thickness, the shortest hyoid-thyroid approximation, and the time between the initiation of tongue movement and the shortest hyoid-thyroid approximation. A total of 24 healthy controls and 24 PD patients with dysphagia were enrolled. No significant differences were demonstrated between the two groups for the shortest hyoid-thyroid approximation (controls, 1.19±0.34 cm; PD patients, 1.37±0.5 cm; p=0.15) and tongue thickness (controls, 4.42±0.46 cm; PD patients, 4.27±0.51 cm; p=0.3). In contrast, the time to the shortest hyoid-thyroid approximation was significantly different between the two groups (controls, 1.53±0.87 ms; PD patients, 2.4±1.4 ms, p=0.048). Ultrasonography can be useful in evaluating dysphagia in patients with PD by direct visualization and measurement of the hyoid bone. Moreover, ultrasonography might contribute to a greater understanding of the pathophysiology of dysphagia in PD.

Distributed Method to Optimal Profile Descent

NASA Astrophysics Data System (ADS)

Kim, Geun I.

Current ground automation tools for Optimal Profile Descent (OPD) procedures utilize path stretching and speed profile change to maintain proper merging and spacing requirements at high traffic terminal area. However, low predictability of aircraft's vertical profile and path deviation during decent add uncertainty to computing estimated time of arrival, a key information that enables the ground control center to manage airspace traffic effectively. This paper uses an OPD procedure that is based on a constant flight path angle to increase the predictability of the vertical profile and defines an OPD optimization problem that uses both path stretching and speed profile change while largely maintaining the original OPD procedure. This problem minimizes the cumulative cost of performing OPD procedures for a group of aircraft by assigning a time cost function to each aircraft and a separation cost function to a pair of aircraft. The OPD optimization problem is then solved in a decentralized manner using dual decomposition techniques under inter-aircraft ADS-B mechanism. This method divides the optimization problem into more manageable sub-problems which are then distributed to the group of aircraft. Each aircraft solves its assigned sub-problem and communicate the solutions to other aircraft in an iterative process until an optimal solution is achieved thus decentralizing the computation of the optimization problem.

The Time Window Vehicle Routing Problem Considering Closed Route

NASA Astrophysics Data System (ADS)

Irsa Syahputri, Nenna; Mawengkang, Herman

2017-12-01

The Vehicle Routing Problem (VRP) determines the optimal set of routes used by a fleet of vehicles to serve a given set of customers on a predefined graph; the objective is to minimize the total travel cost (related to the travel times or distances) and operational cost (related to the number of vehicles used). In this paper we study a variant of the predefined graph: given a weighted graph G and vertices a and b, and given a set X of closed paths in G, find the minimum total travel cost of a-b path P such that no path in X is a subpath of P. Path P is allowed to repeat vertices and edges. We use integer programming model to describe the problem. A feasible neighbourhood approach is proposed to solve the model

47 CFR 22.971 - Obligation to abate unacceptable interference.

Code of Federal Regulations, 2010 CFR

2010-10-01

... interference, with full cooperation and utmost diligence, in the shortest time practicable. Interfering... severally responsible for abating interference, with full cooperation and utmost diligence, in the shortest...

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.

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.

A Bat Algorithm with Mutation for UCAV Path Planning

PubMed Central

Wang, Gaige; Guo, Lihong; Duan, Hong; Liu, Luo; Wang, Heqi

2012-01-01

Path planning for uninhabited combat air vehicle (UCAV) is a complicated high dimension optimization problem, which mainly centralizes on optimizing the flight route considering the different kinds of constrains under complicated battle field environments. Original bat algorithm (BA) is used to solve the UCAV path planning problem. Furthermore, a new bat algorithm with mutation (BAM) is proposed to solve the UCAV path planning problem, and a modification is applied to mutate between bats during the process of the new solutions updating. Then, the UCAV can find the safe path by connecting the chosen nodes of the coordinates while avoiding the threat areas and costing minimum fuel. This new approach can accelerate the global convergence speed while preserving the strong robustness of the basic BA. The realization procedure for original BA and this improved metaheuristic approach BAM is also presented. To prove the performance of this proposed metaheuristic method, BAM is compared with BA and other population-based optimization methods, such as ACO, BBO, DE, ES, GA, PBIL, PSO, and SGA. The experiment shows that the proposed approach is more effective and feasible in UCAV path planning than the other models. PMID:23365518

Behavior problems and placement change in a national child welfare sample: a prospective study.

PubMed

Aarons, Gregory A; James, Sigrid; Monn, Amy R; Raghavan, Ramesh; Wells, Rebecca S; Leslie, Laurel K

2010-01-01

There is ongoing debate regarding the impact of youth behavior problems on placement change in child welfare compared to the impact of placement change on behavior problems. Existing studies provide support for both perspectives. The purpose of this study was to prospectively examine the relations of behavior problems and placement change in a nationally representative sample of youths in the National Survey of Child and Adolescent Well-Being. The sample consisted of 500 youths in the child welfare system with out-of-home placements over the course of the National Survey of Child and Adolescent Well-Being study. We used a prospective cross-lag design and path analysis to examine reciprocal effects of behavior problems and placement change, testing an overall model and models examining effects of age and gender. In the overall model, out of a total of eight path coefficients, behavior problems significantly predicted placement changes for three paths and placement change predicted behavior problems for one path. Internalizing and externalizing behavior problems at baseline predicted placement change between baseline and 18 months. Behavior problems at an older age and externalizing behavior at 18 months appear to confer an increased risk of placement change. Of note, among female subjects, placement changes later in the study predicted subsequent internalizing and externalizing behavior problems. In keeping with recommendations from a number of professional bodies, we suggest that initial and ongoing screening for internalizing and externalizing behavior problems be instituted as part of standard practice for youths entering or transitioning in the child welfare system.

Research and application of genetic algorithm in path planning of logistics distribution vehicle

NASA Astrophysics Data System (ADS)

Wang, Yong; Zhou, Heng; Wang, Ying

2017-08-01

The core of the logistics distribution system is the vehicle routing planning, research path planning problem, provide a better solution has become an important issue. In order to provide the decision support for logistics and distribution operations, this paper studies the problem of vehicle routing with capacity constraints (CVRP). By establishing a mathematical model, the genetic algorithm is used to plan the path of the logistics vehicle to meet the minimum logistics and transportation costs.

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…

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.

Thread Graphs, Linear Rank-Width and Their Algorithmic Applications

NASA Astrophysics Data System (ADS)

Ganian, Robert

The introduction of tree-width by Robertson and Seymour [7] was a breakthrough in the design of graph algorithms. A lot of research since then has focused on obtaining a width measure which would be more general and still allowed efficient algorithms for a wide range of NP-hard problems on graphs of bounded width. To this end, Oum and Seymour have proposed rank-width, which allows the solution of many such hard problems on a less restricted graph classes (see e.g. [3,4]). But what about problems which are NP-hard even on graphs of bounded tree-width or even on trees? The parameter used most often for these exceptionally hard problems is path-width, however it is extremely restrictive - for example the graphs of path-width 1 are exactly paths.

AG Channel Measurement and Modeling Results for Over-Sea Conditions

NASA Technical Reports Server (NTRS)

Matolak, David; Sun, Rouyu

2014-01-01

This report describes results from flight tests conducted in an over-sea environment, for the purpose of characterizing the air-to-ground (AG) channel, for future unmanned aircraft system (UAS) communication system analysis and design. These results are for the first of a set of several flight tests conducted in different ground site (GS) environments. An ultimate aim of all these tests is the development of models for the AG channel that can be used in communication system evaluation. In this report we provide measured results for propagation path loss, root-mean square delay spread (RMS-DS), and the correlation coefficient of the primary received signal components on the four antennas (two antennas for C-band, two for L-band). For path loss, the curved-earth two-ray model provides a reasonable fit to the measured data, altered by several dB at the shortest link distances by aircraft antenna pattern effects. This two-ray model also accounts for the majority of measured RMS-DS results of a few tens of nanoseconds, except for the occasional intermittent reflections from surface objects. These intermittent reflections yield RMS-DS values up to several hundred nanoseconds. For portions of the flight path that were over a harbor area highly populated with boats, the channel was found to be more "continuously dispersive," with RMS-DS reaching approximately 250 ns. A separate model will be developed for this over-harbor setting. The correlation coefficient results are still undergoing analysis; preliminary observations are that correlation between signals on the same-band antennas is generally large (>0.6) for the C-band straight flight paths, whereas for the L-band signals and for the oval-shaped flight paths the correlation is generally small (below 0.4). Inter-band correlations are typically very small, and are well modeled as zero-mean Gaussian in distribution, with a standard deviation less than 0.2. Hence the over-sea channel effects in the two bands can be considered uncorrelated, which will allow for good diversity gains in dual-band systems. We describe initial modeling approaches for the over-sea channel; complete models for this and the over-harbor setting will appear in a subsequent report.

Transition paths of Met-enkephalin from Markov state modeling of a molecular dynamics trajectory.

PubMed

Banerjee, Rahul; Cukier, Robert I

2014-03-20

Conformational states and their interconversion pathways of the zwitterionic form of the pentapeptide Met-enkephalin (MetEnk) are identified. An explicit solvent molecular dynamics (MD) trajectory is used to construct a Markov state model (MSM) based on dihedral space clustering of the trajectory, and transition path theory (TPT) is applied to identify pathways between open and closed conformers. In the MD trajectory, only four of the eight backbone dihedrals exhibit bistable behavior. Defining a conformer as the string XXXX with X = "+" or "-" denoting, respectively, positive or negative values of a given dihedral angle and obtaining the populations of these conformers shows that only four conformers are highly populated, implying a strong correlation among these dihedrals. Clustering in dihedral space to construct the MSM finds the same four bistable dihedral angles. These state populations are very similar to those found directly from the MD trajectory. TPT is used to obtain pathways, parametrized by committor values, in dihedral state space that are followed in transitioning from closed to open states. Pathway costs are estimated by introducing a kinetics-based procedure that orders pathways from least (shortest) to greater cost paths. The least costly pathways in dihedral space are found to only involve the same XXXX set of dihedral angles, and the conformers accessed in the closed to open transition pathways are identified. For these major pathways, a correlation between reaction path progress (committors) and the end-to-end distance is identified. A dihedral space principal component analysis of the MD trajectory shows that the first three modes capture most of the overall fluctuation, and pick out the same four dihedrals having essentially all the weight in those modes. A MSM based on root-mean-square backbone clustering was also carried out, with good agreement found with dihedral clustering for the static information, but with results that differ significantly for the pathway analysis.

Analysis of crossing path crashes

DOT National Transportation Integrated Search

2001-07-01

This report defines the problem of crossing path crashes in the United States. This crash type involves one moving vehicle that cuts across the path of another when their initial approach comes from either lateral or opposite directions and they typi...

Genetic Algorithm for Traveling Salesman Problem with Modified Cycle Crossover Operator

PubMed Central

Mohamd Shoukry, Alaa; Gani, Showkat

2017-01-01

Genetic algorithms are evolutionary techniques used for optimization purposes according to survival of the fittest idea. These methods do not ensure optimal solutions; however, they give good approximation usually in time. The genetic algorithms are useful for NP-hard problems, especially the traveling salesman problem. The genetic algorithm depends on selection criteria, crossover, and mutation operators. To tackle the traveling salesman problem using genetic algorithms, there are various representations such as binary, path, adjacency, ordinal, and matrix representations. In this article, we propose a new crossover operator for traveling salesman problem to minimize the total distance. This approach has been linked with path representation, which is the most natural way to represent a legal tour. Computational results are also reported with some traditional path representation methods like partially mapped and order crossovers along with new cycle crossover operator for some benchmark TSPLIB instances and found improvements. PMID:29209364

Genetic Algorithm for Traveling Salesman Problem with Modified Cycle Crossover Operator.

PubMed

Hussain, Abid; Muhammad, Yousaf Shad; Nauman Sajid, M; Hussain, Ijaz; Mohamd Shoukry, Alaa; Gani, Showkat

2017-01-01

Genetic algorithms are evolutionary techniques used for optimization purposes according to survival of the fittest idea. These methods do not ensure optimal solutions; however, they give good approximation usually in time. The genetic algorithms are useful for NP-hard problems, especially the traveling salesman problem. The genetic algorithm depends on selection criteria, crossover, and mutation operators. To tackle the traveling salesman problem using genetic algorithms, there are various representations such as binary, path, adjacency, ordinal, and matrix representations. In this article, we propose a new crossover operator for traveling salesman problem to minimize the total distance. This approach has been linked with path representation, which is the most natural way to represent a legal tour. Computational results are also reported with some traditional path representation methods like partially mapped and order crossovers along with new cycle crossover operator for some benchmark TSPLIB instances and found improvements.

Optimal Paths in Gliding Flight

NASA Astrophysics Data System (ADS)

Wolek, Artur

Underwater gliders are robust and long endurance ocean sampling platforms that are increasingly being deployed in coastal regions. This new environment is characterized by shallow waters and significant currents that can challenge the mobility of these efficient (but traditionally slow moving) vehicles. This dissertation aims to improve the performance of shallow water underwater gliders through path planning. The path planning problem is formulated for a dynamic particle (or "kinematic car") model. The objective is to identify the path which satisfies specified boundary conditions and minimizes a particular cost. Several cost functions are considered. The problem is addressed using optimal control theory. The length scales of interest for path planning are within a few turn radii. First, an approach is developed for planning minimum-time paths, for a fixed speed glider, that are sub-optimal but are guaranteed to be feasible in the presence of unknown time-varying currents. Next the minimum-time problem for a glider with speed controls, that may vary between the stall speed and the maximum speed, is solved. Last, optimal paths that minimize change in depth (equivalently, maximize range) are investigated. Recognizing that path planning alone cannot overcome all of the challenges associated with significant currents and shallow waters, the design of a novel underwater glider with improved capabilities is explored. A glider with a pneumatic buoyancy engine (allowing large, rapid buoyancy changes) and a cylindrical moving mass mechanism (generating large pitch and roll moments) is designed, manufactured, and tested to demonstrate potential improvements in speed and maneuverability.

Prevention of adolescent problem behavior: longitudinal impact of the Project P.A.T.H.S. in Hong Kong.

PubMed

Shek, Daniel T L; Yu, Lu

2011-03-07

The present study attempts to examine the longitudinal impact of a curriculum-based positive youth development program, entitled the Project P.A.T.H.S. (Positive Adolescent Training through Holistic Social Programmes), on adolescent problem behavior in Hong Kong. Using a longitudinal randomized group design, six waves of data were collected from 19 experimental schools (n = 3,797 at Wave 1) in which students participated in the Project P.A.T.H.S. and 24 control schools (n = 4,049 at Wave 1). At each wave, students responded to questions asking about their current problem behaviors, including delinquency and use of different types of drugs, and their intentions of engaging in such behaviors in the future. Results based on individual growth curve modeling generally showed that the participants displayed lower levels of substance abuse and delinquent behavior than did the control students. Participants who regarded the program to be helpful also showed lower levels of problem behavior than did the control students. The present findings suggest that the Project P.A.T.H.S. is effective in preventing adolescent problem behavior in the junior secondary school years.