Sample records for steiner tree algorithm

  1. Performance Analysis of Evolutionary Algorithms for Steiner Tree Problems.

    PubMed

    Lai, Xinsheng; Zhou, Yuren; Xia, Xiaoyun; Zhang, Qingfu

    2017-01-01

    The Steiner tree problem (STP) aims to determine some Steiner nodes such that the minimum spanning tree over these Steiner nodes and a given set of special nodes has the minimum weight, which is NP-hard. STP includes several important cases. The Steiner tree problem in graphs (GSTP) is one of them. Many heuristics have been proposed for STP, and some of them have proved to be performance guarantee approximation algorithms for this problem. Since evolutionary algorithms (EAs) are general and popular randomized heuristics, it is significant to investigate the performance of EAs for STP. Several empirical investigations have shown that EAs are efficient for STP. However, up to now, there is no theoretical work on the performance of EAs for STP. In this article, we reveal that the (1+1) EA achieves 3/2-approximation ratio for STP in a special class of quasi-bipartite graphs in expected runtime [Formula: see text], where [Formula: see text], [Formula: see text], and [Formula: see text] are, respectively, the number of Steiner nodes, the number of special nodes, and the largest weight among all edges in the input graph. We also show that the (1+1) EA is better than two other heuristics on two GSTP instances, and the (1+1) EA may be inefficient on a constructed GSTP instance.

  2. Multi-terminal pipe routing by Steiner minimal tree and particle swarm optimisation

    NASA Astrophysics Data System (ADS)

    Liu, Qiang; Wang, Chengen

    2012-08-01

    Computer-aided design of pipe routing is of fundamental importance for complex equipments' developments. In this article, non-rectilinear branch pipe routing with multiple terminals that can be formulated as a Euclidean Steiner Minimal Tree with Obstacles (ESMTO) problem is studied in the context of an aeroengine-integrated design engineering. Unlike the traditional methods that connect pipe terminals sequentially, this article presents a new branch pipe routing algorithm based on the Steiner tree theory. The article begins with a new algorithm for solving the ESMTO problem by using particle swarm optimisation (PSO), and then extends the method to the surface cases by using geodesics to meet the requirements of routing non-rectilinear pipes on the surfaces of aeroengines. Subsequently, the adaptive region strategy and the basic visibility graph method are adopted to increase the computation efficiency. Numeral computations show that the proposed routing algorithm can find satisfactory routing layouts while running in polynomial time.

  3. A physarum-inspired prize-collecting steiner tree approach to identify subnetworks for drug repositioning.

    PubMed

    Sun, Yahui; Hameed, Pathima Nusrath; Verspoor, Karin; Halgamuge, Saman

    2016-12-05

    Drug repositioning can reduce the time, costs and risks of drug development by identifying new therapeutic effects for known drugs. It is challenging to reposition drugs as pharmacological data is large and complex. Subnetwork identification has already been used to simplify the visualization and interpretation of biological data, but it has not been applied to drug repositioning so far. In this paper, we fill this gap by proposing a new Physarum-inspired Prize-Collecting Steiner Tree algorithm to identify subnetworks for drug repositioning. Drug Similarity Networks (DSN) are generated using the chemical, therapeutic, protein, and phenotype features of drugs. In DSNs, vertex prizes and edge costs represent the similarities and dissimilarities between drugs respectively, and terminals represent drugs in the cardiovascular class, as defined in the Anatomical Therapeutic Chemical classification system. A new Physarum-inspired Prize-Collecting Steiner Tree algorithm is proposed in this paper to identify subnetworks. We apply both the proposed algorithm and the widely-used GW algorithm to identify subnetworks in our 18 generated DSNs. In these DSNs, our proposed algorithm identifies subnetworks with an average Rand Index of 81.1%, while the GW algorithm can only identify subnetworks with an average Rand Index of 64.1%. We select 9 subnetworks with high Rand Index to find drug repositioning opportunities. 10 frequently occurring drugs in these subnetworks are identified as candidates to be repositioned for cardiovascular diseases. We find evidence to support previous discoveries that nitroglycerin, theophylline and acarbose may be able to be repositioned for cardiovascular diseases. Moreover, we identify seven previously unknown drug candidates that also may interact with the biological cardiovascular system. These discoveries show our proposed Prize-Collecting Steiner Tree approach as a promising strategy for drug repositioning.

  4. Steiner trees and spanning trees in six-pin soap films

    NASA Astrophysics Data System (ADS)

    Dutta, Prasun; Khastgir, S. Pratik; Roy, Anushree

    2010-02-01

    The problem of finding minimum (local as well as absolute) path lengths joining given points (or terminals) on a plane is known as the Steiner problem. The Steiner problem arises in finding the minimum total road length joining several towns and cities. We study the Steiner tree problem using six-pin soap films. Experimentally, we observe spanning trees as well as Steiner trees partly by varying the pin diameter. We propose a possibly exact expression for the length of a spanning tree or a Steiner tree, which fails mysteriously in certain cases.

  5. Performance of a cavity-method-based algorithm for the prize-collecting Steiner tree problem on graphs

    NASA Astrophysics Data System (ADS)

    Biazzo, Indaco; Braunstein, Alfredo; Zecchina, Riccardo

    2012-08-01

    We study the behavior of an algorithm derived from the cavity method for the prize-collecting steiner tree (PCST) problem on graphs. The algorithm is based on the zero temperature limit of the cavity equations and as such is formally simple (a fixed point equation resolved by iteration) and distributed (parallelizable). We provide a detailed comparison with state-of-the-art algorithms on a wide range of existing benchmarks, networks, and random graphs. Specifically, we consider an enhanced derivative of the Goemans-Williamson heuristics and the dhea solver, a branch and cut integer linear programming based approach. The comparison shows that the cavity algorithm outperforms the two algorithms in most large instances both in running time and quality of the solution. Finally we prove a few optimality properties of the solutions provided by our algorithm, including optimality under the two postprocessing procedures defined in the Goemans-Williamson derivative and global optimality in some limit cases.

  6. MIP models for connected facility location: A theoretical and computational study☆

    PubMed Central

    Gollowitzer, Stefan; Ljubić, Ivana

    2011-01-01

    This article comprises the first theoretical and computational study on mixed integer programming (MIP) models for the connected facility location problem (ConFL). ConFL combines facility location and Steiner trees: given a set of customers, a set of potential facility locations and some inter-connection nodes, ConFL searches for the minimum-cost way of assigning each customer to exactly one open facility, and connecting the open facilities via a Steiner tree. The costs needed for building the Steiner tree, facility opening costs and the assignment costs need to be minimized. We model ConFL using seven compact and three mixed integer programming formulations of exponential size. We also show how to transform ConFL into the Steiner arborescence problem. A full hierarchy between the models is provided. For two exponential size models we develop a branch-and-cut algorithm. An extensive computational study is based on two benchmark sets of randomly generated instances with up to 1300 nodes and 115,000 edges. We empirically compare the presented models with respect to the quality of obtained bounds and the corresponding running time. We report optimal values for all but 16 instances for which the obtained gaps are below 0.6%. PMID:25009366

  7. A restricted Steiner tree problem is solved by Geometric Method II

    NASA Astrophysics Data System (ADS)

    Lin, Dazhi; Zhang, Youlin; Lu, Xiaoxu

    2013-03-01

    The minimum Steiner tree problem has wide application background, such as transportation system, communication network, pipeline design and VISL, etc. It is unfortunately that the computational complexity of the problem is NP-hard. People are common to find some special problems to consider. In this paper, we first put forward a restricted Steiner tree problem, which the fixed vertices are in the same side of one line L and we find a vertex on L such the length of the tree is minimal. By the definition and the complexity of the Steiner tree problem, we know that the complexity of this problem is also Np-complete. In the part one, we have considered there are two fixed vertices to find the restricted Steiner tree problem. Naturally, we consider there are three fixed vertices to find the restricted Steiner tree problem. And we also use the geometric method to solve such the problem.

  8. Steiner minimal trees in small neighbourhoods of points in Riemannian manifolds

    NASA Astrophysics Data System (ADS)

    Chikin, V. M.

    2017-07-01

    In contrast to the Euclidean case, almost no Steiner minimal trees with concrete boundaries on Riemannian manifolds are known. A result describing the types of Steiner minimal trees on a Riemannian manifold for arbitrary small boundaries is obtained. As a consequence, it is shown that for sufficiently small regular n-gons with n≥ 7 their boundaries without a longest side are Steiner minimal trees. Bibliography: 22 titles.

  9. Diameter-Constrained Steiner Tree

    NASA Astrophysics Data System (ADS)

    Ding, Wei; Lin, Guohui; Xue, Guoliang

    Given an edge-weighted undirected graph G = (V,E,c,w), where each edge e ∈ E has a cost c(e) and a weight w(e), a set S ⊆ V of terminals and a positive constant D 0, we seek a minimum cost Steiner tree where all terminals appear as leaves and its diameter is bounded by D 0. Note that the diameter of a tree represents the maximum weight of path connecting two different leaves in the tree. Such problem is called the minimum cost diameter-constrained Steiner tree problem. This problem is NP-hard even when the topology of Steiner tree is fixed. In present paper we focus on this restricted version and present a fully polynomial time approximation scheme (FPTAS) for computing a minimum cost diameter-constrained Steiner tree under a fixed topology.

  10. A Sharp methodology for VLSI layout

    NASA Astrophysics Data System (ADS)

    Bapat, Shekhar

    1993-01-01

    The layout problem for VLSI circuits is recognized as a very difficult problem and has been traditionally decomposed into the several seemingly independent sub-problems of placement, global routing, and detailed routing. Although this structure achieves a reduction in programming complexity, it is also typically accompanied by a reduction in solution quality. Most current placement research recognizes that the separation is artificial, and that the placement and routing problems should be solved ideally in tandem. We propose a new interconnection model, Sharp and an associated partitioning algorithm. The Sharp interconnection model uses a partitioning shape that roughly resembles the musical sharp 'number sign' and makes extensive use of pre-computed rectilinear Steiner trees. The model is designed to generate strategic routing information along with the partitioning results. Additionally, the Sharp model also generates estimates of the routing congestion. We also propose the Sharp layout heuristic that solves the layout problem in its entirety. The Sharp layout heuristic makes extensive use of the Sharp partitioning model. The use of precomputed Steiner tree forms enables the method to model accurately net characteristics. For example, the Steiner tree forms can model both the length of the net and more importantly its route. In fact, the tree forms are also appropriate for modeling the timing delays of nets. The Sharp heuristic works to minimize both the total layout area by minimizing total net length (thus reducing the total wiring area), and the congestion imbalances in the various channels (thus reducing the unused or wasted channel area). Our heuristic uses circuit element movements amongst the different partitioning blocks and selection of alternate minimal Steiner tree forms to achieve this goal. The objective function for the algorithm can be modified readily to include other important circuit constraints like propagation delays. The layout technique first computes a very high-level approximation of the layout solution (i.e., the positions of the circuit elements and the associated net routes). The approximate solution is alternately refined, objective function. The technique creates well defined sub-problems and offers intermediary steps that can be solved in parallel, as well as a parallel mechanism to merge the sub-problem solutions.

  11. The node-weighted Steiner tree approach to identify elements of cancer-related signaling pathways.

    PubMed

    Sun, Yahui; Ma, Chenkai; Halgamuge, Saman

    2017-12-28

    Cancer constitutes a momentous health burden in our society. Critical information on cancer may be hidden in its signaling pathways. However, even though a large amount of money has been spent on cancer research, some critical information on cancer-related signaling pathways still remains elusive. Hence, new works towards a complete understanding of cancer-related signaling pathways will greatly benefit the prevention, diagnosis, and treatment of cancer. We propose the node-weighted Steiner tree approach to identify important elements of cancer-related signaling pathways at the level of proteins. This new approach has advantages over previous approaches since it is fast in processing large protein-protein interaction networks. We apply this new approach to identify important elements of two well-known cancer-related signaling pathways: PI3K/Akt and MAPK. First, we generate a node-weighted protein-protein interaction network using protein and signaling pathway data. Second, we modify and use two preprocessing techniques and a state-of-the-art Steiner tree algorithm to identify a subnetwork in the generated network. Third, we propose two new metrics to select important elements from this subnetwork. On a commonly used personal computer, this new approach takes less than 2 s to identify the important elements of PI3K/Akt and MAPK signaling pathways in a large node-weighted protein-protein interaction network with 16,843 vertices and 1,736,922 edges. We further analyze and demonstrate the significance of these identified elements to cancer signal transduction by exploring previously reported experimental evidences. Our node-weighted Steiner tree approach is shown to be both fast and effective to identify important elements of cancer-related signaling pathways. Furthermore, it may provide new perspectives into the identification of signaling pathways for other human diseases.

  12. Degree-constrained multicast routing for multimedia communications

    NASA Astrophysics Data System (ADS)

    Wang, Yanlin; Sun, Yugeng; Li, Guidan

    2005-02-01

    Multicast services have been increasingly used by many multimedia applications. As one of the key techniques to support multimedia applications, the rational and effective multicast routing algorithms are very important to networks performance. When switch nodes in networks have different multicast capability, multicast routing problem is modeled as the degree-constrained Steiner problem. We presented two heuristic algorithms, named BMSTA and BSPTA, for the degree-constrained case in multimedia communications. Both algorithms are used to generate degree-constrained multicast trees with bandwidth and end to end delay bound. Simulations over random networks were carried out to compare the performance of the two proposed algorithms. Experimental results show that the proposed algorithms have advantages in traffic load balancing, which can avoid link blocking and enhance networks performance efficiently. BMSTA has better ability in finding unsaturated links and (or) unsaturated nodes to generate multicast trees than BSPTA. The performance of BMSTA is affected by the variation of degree constraints.

  13. Practical optimization of Steiner trees via the cavity method

    NASA Astrophysics Data System (ADS)

    Braunstein, Alfredo; Muntoni, Anna

    2016-07-01

    The optimization version of the cavity method for single instances, called Max-Sum, has been applied in the past to the minimum Steiner tree problem on graphs and variants. Max-Sum has been shown experimentally to give asymptotically optimal results on certain types of weighted random graphs, and to give good solutions in short computation times for some types of real networks. However, the hypotheses behind the formulation and the cavity method itself limit substantially the class of instances on which the approach gives good results (or even converges). Moreover, in the standard model formulation, the diameter of the tree solution is limited by a predefined bound, that affects both computation time and convergence properties. In this work we describe two main enhancements to the Max-Sum equations to be able to cope with optimization of real-world instances. First, we develop an alternative ‘flat’ model formulation that allows the relevant configuration space to be reduced substantially, making the approach feasible on instances with large solution diameter, in particular when the number of terminal nodes is small. Second, we propose an integration between Max-Sum and three greedy heuristics. This integration allows Max-Sum to be transformed into a highly competitive self-contained algorithm, in which a feasible solution is given at each step of the iterative procedure. Part of this development participated in the 2014 DIMACS Challenge on Steiner problems, and we report the results here. The performance on the challenge of the proposed approach was highly satisfactory: it maintained a small gap to the best bound in most cases, and obtained the best results on several instances in two different categories. We also present several improvements with respect to the version of the algorithm that participated in the competition, including new best solutions for some of the instances of the challenge.

  14. An interactive programme for weighted Steiner trees

    NASA Astrophysics Data System (ADS)

    Zanchetta do Nascimento, Marcelo; Ramos Batista, Valério; Raffa Coimbra, Wendhel

    2015-01-01

    We introduce a fully written programmed code with a supervised method for generating weighted Steiner trees. Our choice of the programming language, and the use of well- known theorems from Geometry and Complex Analysis, allowed this method to be implemented with only 764 lines of effective source code. This eases the understanding and the handling of this beta version for future developments.

  15. A Prize-Collecting Steiner Tree Approach for Transduction Network Inference

    NASA Astrophysics Data System (ADS)

    Bailly-Bechet, Marc; Braunstein, Alfredo; Zecchina, Riccardo

    Into the cell, information from the environment is mainly propagated via signaling pathways which form a transduction network. Here we propose a new algorithm to infer transduction networks from heterogeneous data, using both the protein interaction network and expression datasets. We formulate the inference problem as an optimization task, and develop a message-passing, probabilistic and distributed formalism to solve it. We apply our algorithm to the pheromone response in the baker’s yeast S. cerevisiae. We are able to find the backbone of the known structure of the MAPK cascade of pheromone response, validating our algorithm. More importantly, we make biological predictions about some proteins whose role could be at the interface between pheromone response and other cellular functions.

  16. Many-to-Many Multicast Routing Schemes under a Fixed Topology

    PubMed Central

    Ding, Wei; Wang, Hongfa; Wei, Xuerui

    2013-01-01

    Many-to-many multicast routing can be extensively applied in computer or communication networks supporting various continuous multimedia applications. The paper focuses on the case where all users share a common communication channel while each user is both a sender and a receiver of messages in multicasting as well as an end user. In this case, the multicast tree appears as a terminal Steiner tree (TeST). The problem of finding a TeST with a quality-of-service (QoS) optimization is frequently NP-hard. However, we discover that it is a good idea to find a many-to-many multicast tree with QoS optimization under a fixed topology. In this paper, we are concerned with three kinds of QoS optimization objectives of multicast tree, that is, the minimum cost, minimum diameter, and maximum reliability. All of three optimization problems are distributed into two types, the centralized and decentralized version. This paper uses the dynamic programming method to devise an exact algorithm, respectively, for the centralized and decentralized versions of each optimization problem. PMID:23589706

  17. SteinerNet: a web server for integrating ‘omic’ data to discover hidden components of response pathways

    PubMed Central

    Tuncbag, Nurcan; McCallum, Scott; Huang, Shao-shan Carol; Fraenkel, Ernest

    2012-01-01

    High-throughput technologies including transcriptional profiling, proteomics and reverse genetics screens provide detailed molecular descriptions of cellular responses to perturbations. However, it is difficult to integrate these diverse data to reconstruct biologically meaningful signaling networks. Previously, we have established a framework for integrating transcriptional, proteomic and interactome data by searching for the solution to the prize-collecting Steiner tree problem. Here, we present a web server, SteinerNet, to make this method available in a user-friendly format for a broad range of users with data from any species. At a minimum, a user only needs to provide a set of experimentally detected proteins and/or genes and the server will search for connections among these data from the provided interactomes for yeast, human, mouse, Drosophila melanogaster and Caenorhabditis elegans. More advanced users can upload their own interactome data as well. The server provides interactive visualization of the resulting optimal network and downloadable files detailing the analysis and results. We believe that SteinerNet will be useful for researchers who would like to integrate their high-throughput data for a specific condition or cellular response and to find biologically meaningful pathways. SteinerNet is accessible at http://fraenkel.mit.edu/steinernet. PMID:22638579

  18. Exact and heuristic algorithms for Space Information Flow.

    PubMed

    Uwitonze, Alfred; Huang, Jiaqing; Ye, Yuanqing; Cheng, Wenqing; Li, Zongpeng

    2018-01-01

    Space Information Flow (SIF) is a new promising research area that studies network coding in geometric space, such as Euclidean space. The design of algorithms that compute the optimal SIF solutions remains one of the key open problems in SIF. This work proposes the first exact SIF algorithm and a heuristic SIF algorithm that compute min-cost multicast network coding for N (N ≥ 3) given terminal nodes in 2-D Euclidean space. Furthermore, we find that the Butterfly network in Euclidean space is the second example besides the Pentagram network where SIF is strictly better than Euclidean Steiner minimal tree. The exact algorithm design is based on two key techniques: Delaunay triangulation and linear programming. Delaunay triangulation technique helps to find practically good candidate relay nodes, after which a min-cost multicast linear programming model is solved over the terminal nodes and the candidate relay nodes, to compute the optimal multicast network topology, including the optimal relay nodes selected by linear programming from all the candidate relay nodes and the flow rates on the connection links. The heuristic algorithm design is also based on Delaunay triangulation and linear programming techniques. The exact algorithm can achieve the optimal SIF solution with an exponential computational complexity, while the heuristic algorithm can achieve the sub-optimal SIF solution with a polynomial computational complexity. We prove the correctness of the exact SIF algorithm. The simulation results show the effectiveness of the heuristic SIF algorithm.

  19. Reconstructing targetable pathways in lung cancer by integrating diverse omics data

    PubMed Central

    Balbin, O. Alejandro; Prensner, John R.; Sahu, Anirban; Yocum, Anastasia; Shankar, Sunita; Malik, Rohit; Fermin, Damian; Dhanasekaran, Saravana M.; Chandler, Benjamin; Thomas, Dafydd; Beer, David G.; Cao, Xuhong; Nesvizhskii, Alexey I.; Chinnaiyan, Arul M.

    2014-01-01

    Global ‘multi-omics’ profiling of cancer cells harbours the potential for characterizing the signaling networks associated with specific oncogenes. Here we profile the transcriptome, proteome and phosphoproteome in a panel of non-small cell lung cancer (NSCLC) cell lines in order to reconstruct targetable networks associated with KRAS dependency. We develop a two-step bioinformatics strategy addressing the challenge of integrating these disparate data sets. We first define an ‘abundance-score’ combining transcript, protein and phospho-protein abundances to nominate differentially abundant proteins and then use the Prize Collecting Steiner Tree algorithm to identify functional sub-networks. We identify three modules centered on KRAS and MET, LCK and PAK1 and b-Catenin. We validate activation of these proteins in KRAS-dependent (KRAS-Dep) cells and perform functional studies defining LCK as a critical gene for cell proliferation in KRAS-Dep but not KRAS-independent NSCLCs. These results suggest that LCK is a potential druggable target protein in KRAS-Dep lung cancers. PMID:24135919

  20. Implementation of Steiner point of fuzzy set.

    PubMed

    Liang, Jiuzhen; Wang, Dejiang

    2014-01-01

    This paper deals with the implementation of Steiner point of fuzzy set. Some definitions and properties of Steiner point are investigated and extended to fuzzy set. This paper focuses on establishing efficient methods to compute Steiner point of fuzzy set. Two strategies of computing Steiner point of fuzzy set are proposed. One is called linear combination of Steiner points computed by a series of crisp α-cut sets of the fuzzy set. The other is an approximate method, which is trying to find the optimal α-cut set approaching the fuzzy set. Stability analysis of Steiner point of fuzzy set is also studied. Some experiments on image processing are given, in which the two methods are applied for implementing Steiner point of fuzzy image, and both strategies show their own advantages in computing Steiner point of fuzzy set.

  1. In Harmony with the Child: The Steiner Teacher as Co-Leader in a Pedagogical Community

    ERIC Educational Resources Information Center

    Woods, Philip A.; Woods, Glenys J.

    2006-01-01

    This article provides a glimpse into what it means to be a Steiner teacher, drawing on research we have undertaken into Steiner schools in England. The distinctiveness of the philosophical context of Steiner teaching is highlighted, as well as aspects of curriculum, pedagogy and the collegial leadership of Steiner schools. Whilst not without its…

  2. Validating a Steiner-Waldorf Teacher Education Programme

    ERIC Educational Resources Information Center

    Oberski, Iddo; Pugh, Alistair; MacLean, Astrid; Cope, Peter

    2007-01-01

    Steiner-Waldorf (SW) education, based on the work of Rudolf Steiner (1861-1925), provides a distinctive form of education. There are approximately 900 SW schools worldwide. The only teacher training course for SW education in Scotland is currently offered at the Edinburgh Rudolf Steiner School (ERSS). Although students are continuously assessed on…

  3. Why a Steiner Academy?

    ERIC Educational Resources Information Center

    Avison, Kevin

    2008-01-01

    This article examines the curious position of the Academy model in the English school system and how a potential Hereford Steiner Waldorf Academy might figure in this. It sketches the background to the Steiner movement in the UK and goes on to set out the key aspirations and concerns of Steiner educators regarding an Academy. The article provides…

  4. 76 FR 9278 - Safety Zone; Fourth Annual Offshore Challenge, Sunny Isles Beach, FL

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-02-17

    ... Lieutenant Paul A. Steiner, Sector Miami Prevention Department, Coast Guard; telephone 305-535-8724, e-mail Paul.A.Steiner@uscg.mil . If you have questions on viewing or submitting material to the docket, call.... Steiner, Sector Miami Prevention Department, Coast Guard; telephone 305-535- 8724, e-mail Paul.A.Steiner...

  5. Connectivity Restoration in Wireless Sensor Networks via Space Network Coding.

    PubMed

    Uwitonze, Alfred; Huang, Jiaqing; Ye, Yuanqing; Cheng, Wenqing

    2017-04-20

    The problem of finding the number and optimal positions of relay nodes for restoring the network connectivity in partitioned Wireless Sensor Networks (WSNs) is Non-deterministic Polynomial-time hard (NP-hard) and thus heuristic methods are preferred to solve it. This paper proposes a novel polynomial time heuristic algorithm, namely, Relay Placement using Space Network Coding (RPSNC), to solve this problem, where Space Network Coding, also called Space Information Flow (SIF), is a new research paradigm that studies network coding in Euclidean space, in which extra relay nodes can be introduced to reduce the cost of communication. Unlike contemporary schemes that are often based on Minimum Spanning Tree (MST), Euclidean Steiner Minimal Tree (ESMT) or a combination of MST with ESMT, RPSNC is a new min-cost multicast space network coding approach that combines Delaunay triangulation and non-uniform partitioning techniques for generating a number of candidate relay nodes, and then linear programming is applied for choosing the optimal relay nodes and computing their connection links with terminals. Subsequently, an equilibrium method is used to refine the locations of the optimal relay nodes, by moving them to balanced positions. RPSNC can adapt to any density distribution of relay nodes and terminals, as well as any density distribution of terminals. The performance and complexity of RPSNC are analyzed and its performance is validated through simulation experiments.

  6. Understanding the Steiner Waldorf Approach: Early Years Education in Practice. Understanding the... Approach

    ERIC Educational Resources Information Center

    Nicol, Janni; Taplin, Jill

    2012-01-01

    Understanding the Steiner Waldorf Approach is a much needed source of information for those wishing to extend and consolidate their understanding of the Steiner Waldorf High Scope Approach. It will enable the reader to analyse the essential elements of the Steiner Waldorf Approach to early childhood and its relationship to quality early years…

  7. Ladislau Steiner, 1920-2013.

    PubMed

    Leksell, Dan; Lindquist, Christer E H

    2013-09-01

    The authors commemorate the life and career of Dr. Ladislau Steiner, one of the world's most highly regarded neurosurgeons, from Stockholm and Charlottesville, Virginia, who has died at age 92. They review the events of Dr. Steiner's early life, including his early training in his native Romania, his escape with his family from East Berlin, and his postgraduate training in neurosurgery at the Karolinska Institute in Stockholm. Dr. Steiner's work in the development of microsurgery and his collaboration with Lars Leksell in the development of Gamma Knife radiosurgery are described. After his retirement from Karolinska, Dr. Steiner had a second career as head of the Lars Leksell Gamma Knife Center at the University of Virginia in Charlottesville. The authors recall their own long association with Dr. Steiner and celebrate his contributions to the field of neurosurgery.

  8. Primal-dual techniques for online algorithms and mechanisms

    NASA Astrophysics Data System (ADS)

    Liaghat, Vahid

    An offline algorithm is one that knows the entire input in advance. An online algorithm, however, processes its input in a serial fashion. In contrast to offline algorithms, an online algorithm works in a local fashion and has to make irrevocable decisions without having the entire input. Online algorithms are often not optimal since their irrevocable decisions may turn out to be inefficient after receiving the rest of the input. For a given online problem, the goal is to design algorithms which are competitive against the offline optimal solutions. In a classical offline scenario, it is often common to see a dual analysis of problems that can be formulated as a linear or convex program. Primal-dual and dual-fitting techniques have been successfully applied to many such problems. Unfortunately, the usual tricks come short in an online setting since an online algorithm should make decisions without knowing even the whole program. In this thesis, we study the competitive analysis of fundamental problems in the literature such as different variants of online matching and online Steiner connectivity, via online dual techniques. Although there are many generic tools for solving an optimization problem in the offline paradigm, in comparison, much less is known for tackling online problems. The main focus of this work is to design generic techniques for solving integral linear optimization problems where the solution space is restricted via a set of linear constraints. A general family of these problems are online packing/covering problems. Our work shows that for several seemingly unrelated problems, primal-dual techniques can be successfully applied as a unifying approach for analyzing these problems. We believe this leads to generic algorithmic frameworks for solving online problems. In the first part of the thesis, we show the effectiveness of our techniques in the stochastic settings and their applications in Bayesian mechanism design. In particular, we introduce new techniques for solving a fundamental linear optimization problem, namely, the stochastic generalized assignment problem (GAP). This packing problem generalizes various problems such as online matching, ad allocation, bin packing, etc. We furthermore show applications of such results in the mechanism design by introducing Prophet Secretary, a novel Bayesian model for online auctions. In the second part of the thesis, we focus on the covering problems. We develop the framework of "Disk Painting" for a general class of network design problems that can be characterized by proper functions. This class generalizes the node-weighted and edge-weighted variants of several well-known Steiner connectivity problems. We furthermore design a generic technique for solving the prize-collecting variants of these problems when there exists a dual analysis for the non-prize-collecting counterparts. Hence, we solve the online prize-collecting variants of several network design problems for the first time. Finally we focus on designing techniques for online problems with mixed packing/covering constraints. We initiate the study of degree-bounded graph optimization problems in the online setting by designing an online algorithm with a tight competitive ratio for the degree-bounded Steiner forest problem. We hope these techniques establishes a starting point for the analysis of the important class of online degree-bounded optimization on graphs.

  9. Mathematical analysis of dynamic spread of Pine Wilt disease.

    PubMed

    Dimitrijevic, D D; Bacic, J

    2013-01-01

    Since its detection in Portugal in 1999, the pinewood nematode Bursaphelenchus xylophilus (Steiner and Buhrer), a causal agent of Pine Wilt Disease, represents a threat to European forestry. Significant amount of money has been spent on its monitoring and eradication. This paper presents mathematical analysis of spread of pine wilt disease using a set of partial differential equations with space (longitude and latitude) and time as parameters of estimated spread of disease. This methodology can be used to evaluate risk of various assumed entry points of disease and make defense plans in advance. In case of an already existing outbreak, it can be used to draw optimal line of defense and plan removal of trees. Optimization constraints are economic loss of removal of susceptible trees as well as budgetary constraints of workforce cost.

  10. Jean Piaget and Rudolf Steiner: Stages of Child Development and Implications for Pedagogy.

    ERIC Educational Resources Information Center

    Ginsburg, Iona H.

    1982-01-01

    The views of Jean Piaget and Rudolf Steiner concerning children's stages of development are compared and related to present-day instructional practices used in the Waldorf schools, which employ Steiner's ideas. Educational principles and practices used at the elementary school level are discussed. (PP)

  11. Renewing Education: Selected Writings on Steiner Education.

    ERIC Educational Resources Information Center

    Edmunds, Francis

    Having taught for nearly 30 years in Britain's first Rudolf Steiner school, Francis Edmunds founded Emerson College, an adult education and teacher training center where he was active until his death in 1989. This book contains a collection of Edmunds' writings on Steiner education mostly excerpted from "Child and Man,""The Michael…

  12. School Readiness and Rudolf Steiner's Theory of Learning.

    ERIC Educational Resources Information Center

    Ogletree, Earl J.; Ujlaki, Vilma

    This paper presents Rudolf Steiner's maturational readiness theory of human physiopsychology and comments on education in the Waldorf Schools. Discussion asserts that Steiner's concept of human development is complex and that intensive study is required for even a superficial understanding of "the four members of man": the physical,…

  13. The effect of three different educational approaches on children's drawing ability: Steiner, Montessori and traditional.

    PubMed

    Cox, M V; Rowlands, A

    2000-12-01

    Although there is a national curriculum for art education in the UK there are also alternative approaches in the private sector. This paper addresses the issue of the effect of these approaches on children's drawing ability. To compare the drawing ability in three drawing tasks of children in Steiner, Montessori and traditional schools. The participants were 60 school children between the ages of 5;11 and 7;2. Twenty children were tested in each type of school. Each child completed three drawings: a free drawing, a scene and an observational drawing. As predicted, the free and scene drawings of children in the Steiner school were rated more highly than those of children in Montessori and traditional schools. Steiner children's use of colour was also rated more highly, although they did not use more colours than the other children. Steiner children used significantly more fantasy topics in their free drawings. Further observation indicated that the Steiner children were better at using the whole page and organising their drawings into a scene; their drawings were also more detailed. Contrary to previous research Montessori children did not draw more inanimate objects and geometrical shapes or fewer people than other children. Also, contrary to the prediction, Steiner children were significantly better rather than worse than other children at observational drawing. The results suggest that the approach to art education in Steiner schools is conducive not only to more highly rated imaginative drawings in terms of general drawing ability and use of colour but also to more accurate and detailed observational drawings.

  14. Authentic Assessment in the First Steiner Academy

    ERIC Educational Resources Information Center

    Burnett, John

    2009-01-01

    In August 2008, the then Schools Minister, Andrew Adonis, gave the go-ahead for the privately funded Hereford Waldorf School to reopen as a tax-payer-funded Academy, sponsored by the Steiner Waldorf Schools Fellowship of Great Britain. Accordingly, the Steiner Academy Hereford opened in September 2008. In common with the 132 other Academies opened…

  15. Humanizing the Humanities: Some Reflections on George Steiner's "Brutal Paradox."

    ERIC Educational Resources Information Center

    Karier, Clarence J.

    1990-01-01

    Considers how literary critic, George Steiner, explores the failure of Western Civilization to humanize humanity. Analyzes Steiner's ultimately elitist model of culture to shed light on implications of his brutal paradox in which Nazism's death camps are juxtaposed to high culture. Theorizes about the possibilities of a culture inclusive of all…

  16. Rudolf Steiner Farm School, Hawthorne Valley.

    ERIC Educational Resources Information Center

    Rudolf Steiner Farm School, Harlemville, Ghent, NY.

    The goal of the Rudolf Steiner Farm School (which employs the spiritual/scientific path of knowledge described by Rudolf Steiner in the early 1900's) is to awaken and cultivate the capacities of the full human being through education, the arts, and agriculture, in direct relationship with nature, the spiritual universe, and current times. The…

  17. Educational Imperatives of the Evolution of Consciousness: The Integral Visions of Rudolf Steiner and Ken Wilber

    ERIC Educational Resources Information Center

    Gidley, Jennifer M.

    2007-01-01

    Rudolf Steiner and Ken Wilber claim that human consciousness is evolving beyond the "formal", abstract, intellectual mode toward a "post-formal", integral mode. Wilber calls this "vision-logic" and Steiner calls it "consciousness/spiritual soul". Both point to the emergence of more complex, dialectical,…

  18. Psychological Processes and "The Staircase to Terrorism"

    ERIC Educational Resources Information Center

    Moghaddam, Fathali M.

    2005-01-01

    This paper presents replies to the comments of Paniagua and Steiner on his original article on terrorism. The author notes that several points raised by Paniagua and Steiner are insightful and help to broaden the range of factors to be considered on the staircase to terrorism. Steiner highlights the role of incitement, and this points to the…

  19. 76 FR 24840 - Safety Zone; 2011 Rohto Ironman 70.3 Miami, Biscayne Bay, Miami, FL

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-05-03

    ... Lieutenant Paul A. Steiner, Sector Miami Prevention Department, Coast Guard; telephone 305-535-8724, e-mail Paul.A.Steiner@uscg.mil . If you have questions on viewing or submitting material to the docket, call... Lieutenant Paul A. Steiner, Sector Miami Prevention Department, Coast Guard; telephone 305-535-8724, e-mail...

  20. Tolerance of image enhancement brightness and contrast in lateral cephalometric digital radiography for Steiner analysis

    NASA Astrophysics Data System (ADS)

    Rianti, R. A.; Priaminiarti, M.; Syahraini, S. I.

    2017-08-01

    Image enhancement brightness and contrast can be adjusted on lateral cephalometric digital radiographs to improve image quality and anatomic landmarks for measurement by Steiner analysis. To determine the limit value for adjustments of image enhancement brightness and contrast in lateral cephalometric digital radiography for Steiner analysis. Image enhancement brightness and contrast were adjusted on 100 lateral cephalometric radiography in 10-point increments (-30, -20, -10, 0, +10, +20, +30). Steiner analysis measurements were then performed by two observers. Reliabilities were tested by the Interclass Correlation Coefficient (ICC) and significance tested by ANOVA or the Kruskal Wallis test. No significant differences were detected in lateral cephalometric analysis measurements following adjustment of the image enhancement brightness and contrast. The limit value of adjustments of the image enhancement brightness and contrast associated with incremental 10-point changes (-30, -20, -10, 0, +10, +20, +30) does not affect the results of Steiner analysis.

  1. 76 FR 43958 - Safety Zone; Rotary Club of Fort Lauderdale New River Raft Race, New River, Fort Lauderdale, FL

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-07-22

    ... have questions on this proposed rule, call or e-mail Lieutenant Paul A. Steiner, Sector Miami Prevention Department, Coast Guard; telephone 305-535-8724, e-mail Paul.A.Steiner@uscg.mil . If you have... Paul A. Steiner, Sector Miami Prevention Department, Coast Guard; telephone 305-535-8724, e-mail Paul.A...

  2. U.S. Democratization Strategy: Origins and Obstacles

    DTIC Science & Technology

    2008-09-01

    war was destroying Europe and Wilson’s non-intervention had won favor with the U.S. electorate, unwilling to partake in what Zara Steiner has aptly...33 Stanley Weintraub, Silent Night (New York: Simon and Schuster, 2001), p. 167. 34 Zara Steiner, The...Platter (Baltimore and London: The Johns Hopkins University Press, 2001). Steiner, Zara , The Lights that Failed: European International History

  3. Edmondson-Steiner grade: A crucial predictor of recurrence and survival in hepatocellular carcinoma without microvascular invasio.

    PubMed

    Zhou, Li; Rui, Jing-An; Zhou, Wei-Xun; Wang, Shao-Bin; Chen, Shu-Guang; Qu, Qiang

    2017-07-01

    Microvascular invasion (MVI), an important pathologic parameter, has been proven to be a powerful predictor of long-term prognosis in hepatocellular carcinoma (HCC). However, prognostic factors in HCC without MVI remain unknown. The present study aimed to identify the risk factors of recurrence and poor post-resectional survival in this type of HCC. A total of 109 patients with MVI-absent HCC underwent radical hepatectomy were enrolled. The influence of clinicopathologic variables on recurrence and patient survival was assessed using univariate and multivariate analyses. Chi-square test found that Edmondson-Steiner grade and satellite nodule were significantly associated with recurrence, while the former was the single marker for early recurrence. Stepwise logistic regression analysis demonstrated the independent predictive role of Edmondson-Steiner grade for recurrence. On the other hand, Edmondson-Steiner grade, serum AFP level and satellite nodule were significant for overall and disease-free survival in univariate analysis, whereas tumor size was linked to disease-free survival. Of the variables, Edmondson-Steiner grade, serum AFP level and satellite nodule were independent indicators. Edmondson-Steiner grade, a histological classification, carries robust prognostic implications for all the endpoints for prognosis, thus being potential to be a crucial prognosticator in HCC without MVI. Copyright © 2017 Elsevier GmbH. All rights reserved.

  4. The effect of attending steiner schools during childhood on health in adulthood: a multicentre cross-sectional study.

    PubMed

    Fischer, H Felix; Binting, Sylvia; Bockelbrink, Angelina; Heusser, Peter; Hueck, Christoph; Keil, Thomas; Roll, Stephanie; Witt, Claudia

    2013-01-01

    It is speculated that attending Steiner schools, whose pedagogical principles include an account for healthy psycho-physical development, may have long-term beneficial health effects. We examined whether the current health status differed between former attendees of German Steiner schools and adults from the general population. Furthermore, we examined factors that might explain those differences. We included former Steiner school attendees from 4 schools in Berlin, Hanover, Nuremberg and Stuttgart and randomly selected population controls. Using a self-report questionnaire we assessed sociodemographics, current and childhood lifestyle and health status. Outcomes were self-reports on 16 diseases: atopic dermatitis, allergic rhinitis, bronchial asthma, chronic obstructive pulmonary disease (COPD), cardiac arrhythmia, cardiac insufficiency, angina pectoris, arteriosclerosis, hypertension, hypercholesterolemia, osteoarthritis, rheumatism, cancer, diabetes, depression and multiple sclerosis. Furthermore, participants rated the symptom burden resulting from back pain, cold symptoms, headache, insomnia, joint pain, gastrointestinal symptoms and imbalance. Unadjusted and adjusted odds ratios were calculated for each outcome. 1136 Steiner school attendees and 1746 controls were eligible for analysis. Both groups were comparable regarding sex, age and region, but differed in nationality and educational status. After adjusting for possible confounders, we found statistically significant effects of Steiner school attendance for osteoarthritis (OR 0.69 [0.49-0.97]) and allergic rhinitis (OR 0.77, [0.59-1.00]) as well as for symptom burden from back pain (OR 0.80, [0.64-1.00]), insomnia (OR 0.65, [0.50-0.84]), joint pain (OR 0.62, [0.48-0.82]), gastrointestinal symptoms (OR 0.76, [0.58-1.00]) and imbalance (OR 0.60, [0.38-0.93]). The risk of most examined diseases did not differ between former Steiner school attendees and the general population after adjustment for sociodemographics, current and childhood lifestyle features, but symptom burden from some current health complaints was reported less by former Steiner school attendees. Results must be interpreted with caution since the analysis was exploratory.

  5. 8TH International Laser Physics Workshop Lphys󈨧 Budapest, July 2-6, 1999, Program

    DTIC Science & Technology

    1999-07-05

    Gerhard J. MUller (Germany) Rudolf Steiner (Germany) Symposium Status and Future Directions of High-Power Laser Installations Co-Chairs: See Leang...Sciences, Kazan. Russia I.A. Shcherbakov General Physics Institute. Russian Academy of Sciences. Moscow, Russia R. Steiner Institute of Laser Technologies...14.50-15.15 R. Steiner , A. Pohl, A. Bentele, T. Meier (Ulm, Germany) Laser Doppler sensor for laser assisted injection 30 SEMINAR 5 --- LASER METHODS IN

  6. Wiedemann-Steiner Syndrome With 2 Novel KMT2A Mutations.

    PubMed

    Min Ko, Jung; Cho, Jae So; Yoo, Yongjin; Seo, Jieun; Choi, Murim; Chae, Jong-Hee; Lee, Hye-Ran; Cho, Tae-Joon

    2017-02-01

    Wiedemann-Steiner syndrome is a rare genetic disorder characterized by short stature, hairy elbows, facial dysmorphism, and developmental delay. It can also be accompanied by musculoskeletal anomalies such as muscular hypotonia and small hands and feet. Mutations in the KMT2A gene have only recently been identified as the cause of Wiedemann-Steiner syndrome; therefore, only 16 patients from 15 families have been described, and new phenotypic features continue to be added. In this report, we describe 2 newly identified patients with Wiedemann-Steiner syndrome who presented with variable severity. One girl exhibited developmental dysplasia of the hip and fibromatosis colli accompanied by other clinical features, including facial dysmorphism, hypertrichosis, patent ductus arteriosus, growth retardation, and borderline intellectual disability. The other patient, a boy, showed severe developmental retardation with automatic self-mutilation, facial dysmorphism, and hypertrichosis at a later age. Exome sequencing analysis of these patients and their parents revealed a de novo nonsense mutation, p.Gln1978*, of KMT2A in the former, and a missense mutation, p.Gly1168Asp, in the latter, which molecularly confirmed the diagnosis of Wiedemann-Steiner syndrome.

  7. Steiner's Amazing Porism

    ERIC Educational Resources Information Center

    Fletcher, Trevor

    2007-01-01

    In this article, the author describes his experiments with Steiner's Porism using the drawing/animation program "Cinderella" and discusses insights into this theorem gleaned from the manipulation of his animation. (Contains 2 notes.)

  8. 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.

  9. The Effect of Attending Steiner Schools during Childhood on Health in Adulthood: A Multicentre Cross-Sectional Study

    PubMed Central

    Fischer, H. Felix; Binting, Sylvia; Bockelbrink, Angelina; Heusser, Peter; Hueck, Christoph; Keil, Thomas; Roll, Stephanie; Witt, Claudia

    2013-01-01

    Background It is speculated that attending Steiner schools, whose pedagogical principles include an account for healthy psycho-physical development, may have long-term beneficial health effects. We examined whether the current health status differed between former attendees of German Steiner schools and adults from the general population. Furthermore, we examined factors that might explain those differences. Methods We included former Steiner school attendees from 4 schools in Berlin, Hanover, Nuremberg and Stuttgart and randomly selected population controls. Using a self-report questionnaire we assessed sociodemographics, current and childhood lifestyle and health status. Outcomes were self-reports on 16 diseases: atopic dermatitis, allergic rhinitis, bronchial asthma, chronic obstructive pulmonary disease (COPD), cardiac arrhythmia, cardiac insufficiency, angina pectoris, arteriosclerosis, hypertension, hypercholesterolemia, osteoarthritis, rheumatism, cancer, diabetes, depression and multiple sclerosis. Furthermore, participants rated the symptom burden resulting from back pain, cold symptoms, headache, insomnia, joint pain, gastrointestinal symptoms and imbalance. Unadjusted and adjusted odds ratios were calculated for each outcome. Results 1136 Steiner school attendees and 1746 controls were eligible for analysis. Both groups were comparable regarding sex, age and region, but differed in nationality and educational status. After adjusting for possible confounders, we found statistically significant effects of Steiner school attendance for osteoarthritis (OR 0.69 [0.49–0.97]) and allergic rhinitis (OR 0.77, [0.59–1.00]) as well as for symptom burden from back pain (OR 0.80, [0.64–1.00]), insomnia (OR 0.65, [0.50–0.84]), joint pain (OR 0.62, [0.48–0.82]), gastrointestinal symptoms (OR 0.76, [0.58–1.00]) and imbalance (OR 0.60, [0.38–0.93]). Conclusions The risk of most examined diseases did not differ between former Steiner school attendees and the general population after adjustment for sociodemographics, current and childhood lifestyle features, but symptom burden from some current health complaints was reported less by former Steiner school attendees. Results must be interpreted with caution since the analysis was exploratory. PMID:24069175

  10. Dental Health and Orthodontic Problems

    MedlinePlus

    ... of yesteryear. Dr. Jim Steiner, director of pediatric dentistry at Children’s Hospital in Cincinnati, Ohio, attributes the ... ago,” says Dr. Jim Steiner, director of pediatric dentistry at Children's Hospital in cincinnati, Ohio, “the silver ...

  11. Roy-Steiner equations for πN scattering

    NASA Astrophysics Data System (ADS)

    Ruiz de Elvira, J.; Ditsche, C.; Hoferichter, M.; Kubis, B.; Meißner, U.-G.

    2014-06-01

    In this talk, we present a coupled system of integral equations for the πN → πN (s-channel) and ππ → N̅N (t-channel) lowest partial waves, derived from Roy-Steiner equations for pion-nucleon scattering. After giving a brief overview of this system of equations, we present the solution of the t-channel sub-problem by means of Muskhelishvili-Omnès techniques, and solve the s-channel sub-problem after finding a set of phase shifts and subthreshold parameters which satisfy the Roy-Steiner equations.

  12. 76 FR 8656 - Safety Zone; Miami International Triathlon, Bayfront Park, Miami, FL

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-02-15

    ...-mail Lieutenant Paul A. Steiner, Sector Miami Prevention Department, Coast Guard; telephone 305-535-8724, e-mail Paul.A.Steiner@uscg.mil . If you have questions on viewing the docket, call Renee V...

  13. Geometric Form Drawing: A Perceptual-Motor Approach to Preventive Remediation (The Steiner Approach)

    ERIC Educational Resources Information Center

    Ogletree, Earl J.

    1975-01-01

    Provided is a rationale for geometric form drawing developed by Rudolf Steiner as a tool to develop motor coordination, perceptual skills, and cognition for mentally retarded and perceptually handicapped children. (Author/CL)

  14. A comparison of the Cook single lumen immature ovum IVM needle to the Steiner-Tan pseudo double lumen flushing needle for oocyte retrieval for IVM.

    PubMed

    Rose, B I; Laky, D

    2013-06-01

    This study compared the impact of using the Steiner-Tan pseudo double lumen needle for antral follicle oocyte retrieval to using a conventional non-flushing needle. The Steiner-Tan needle has a much smaller dead space than the needles commonly used for IVM oocyte retrievals. This was a retrospective cohort study. The patient population was determined by the time period in which a patient underwent IVM in a single physician's IVF practice. The following data was abstracted from clinical and embryology records: oocytes retrieved, oocytes matured, early maturing oocytes, oocytes fertilized, embryo quality measures, retrieval time, needle punctures, clot formation, and clinical pregnancy rate. The Steiner-Tan needle did not increase the number of oocytes retrieved. It also did not increase the time required for retrieval. However, flushing of antral follicles significantly decreased clot formation in fluid aspirates. Use of the Steiner-Tan needle also significantly decreased the number of vaginal needle punctures during each case. There was a trend toward improved embryo quality, but statistical power was inadequate to show a difference. The primary benefit of the Steiner-Tan needle was on the embryological aspects of IVM. Decreased blood and blood clots in the aspirates made an IVM retrieval more like conventional IVF for the embryologist. The patient also experienced less tissue trauma without increasing anesthesia or surgical time. There was no improvement in the number of oocytes retrieved, but based on the results, we hypothesized that oocytes were more commonly retrieved from slightly large follicles than when using a routine needle.

  15. Individual Differences in Learning from Verbal and Figural Materials.

    DTIC Science & Technology

    1980-09-01

    price floors and ceilings, taxation, and agricultural problems. Materials were adapted from introductory college economics textbooks (Lipsey and Steiner...introductory college economics textbooks (Lipsey and Steiner, 1969; Samuelson, 1976; Spencer, 1977; Sutton, 1976), but presented at a level appropriate

  16. 76 FR 29642 - Special Local Regulations; Miami Super Boat Grand Prix, Miami Beach, FL

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-05-23

    ... INFORMATION CONTACT: If you have questions on this rule, call or e-mail Lieutenant Paul A. Steiner, Sector Miami Prevention Department, Coast Guard; telephone 305-535-8724, e-mail Paul.A.Steiner@uscg.mil . If...

  17. Discovering Steiner Triple Systems through Problem Solving

    ERIC Educational Resources Information Center

    Sriraman, Bharath

    2004-01-01

    An attempt to implement problem solving as a teacher of ninth grade algebra is described. The problems selected were not general ones, they involved combinations and represented various situations and were more complex which lead to the discovery of Steiner triple systems.

  18. Practising Empathy: Enacting Alternative Perspectives through Imaginative Play

    ERIC Educational Resources Information Center

    Waite, Sue; Rees, Sarah

    2014-01-01

    This article reports on a collaborative study using an innovative methodology, based on "insiders" who are Steiner practitioners knowledgeable and practised in Steiner philosophy and "outsiders" from UK mainstream early years and primary perspectives. Although the study as a whole focused on assessment and observation used in…

  19. Waldorf Education: Theory of Child Development and Teaching Methods.

    ERIC Educational Resources Information Center

    Ogletree, Earl J.

    This paper examines the educational philosophy underlying Waldorf Education, focusing on Rudolf Steiner's concept of "vital" or etheric energy and comparing Piaget's and Steiner's stages of cognition. The paper begins with a discussion of school readiness and the trend toward lowering the school entry age, and maintains that this trend…

  20. Montessori and Steiner: A Pattern of Reverse Symmetries.

    ERIC Educational Resources Information Center

    Coulter, Dee Joy

    2003-01-01

    Explains the educational movements precipitated by Maria Montessori and Rudolf Steiner as comprising a pattern of reverse symmetries. Notes the influence of war on their philosophies. Discusses reverse symmetries in curriculum related to mathematics, geography, and history. Maintains that each of these two movements holds the other at its core,…

  1. Creative Grammar and Art Education

    ERIC Educational Resources Information Center

    Cunliffe, Leslie

    2011-01-01

    The grammar of creative practices is described by George Steiner as the "articulate organisation of perception, reflection and experience, the nerve structure of consciousness when it communicates with itself and with others." Steiner's description of creative grammar is consistent with Lev Vygotsky's comment that "art is the social within us, and…

  2. Exact Algorithms for Duplication-Transfer-Loss Reconciliation with Non-Binary Gene Trees.

    PubMed

    Kordi, Misagh; Bansal, Mukul S

    2017-06-01

    Duplication-Transfer-Loss (DTL) reconciliation is a powerful method for studying gene family evolution in the presence of horizontal gene transfer. DTL reconciliation seeks to reconcile gene trees with species trees by postulating speciation, duplication, transfer, and loss events. Efficient algorithms exist for finding optimal DTL reconciliations when the gene tree is binary. In practice, however, gene trees are often non-binary due to uncertainty in the gene tree topologies, and DTL reconciliation with non-binary gene trees is known to be NP-hard. In this paper, we present the first exact algorithms for DTL reconciliation with non-binary gene trees. Specifically, we (i) show that the DTL reconciliation problem for non-binary gene trees is fixed-parameter tractable in the maximum degree of the gene tree, (ii) present an exponential-time, but in-practice efficient, algorithm to track and enumerate all optimal binary resolutions of a non-binary input gene tree, and (iii) apply our algorithms to a large empirical data set of over 4700 gene trees from 100 species to study the impact of gene tree uncertainty on DTL-reconciliation and to demonstrate the applicability and utility of our algorithms. The new techniques and algorithms introduced in this paper will help biologists avoid incorrect evolutionary inferences caused by gene tree uncertainty.

  3. Recursive algorithms for phylogenetic tree counting.

    PubMed

    Gavryushkina, Alexandra; Welch, David; Drummond, Alexei J

    2013-10-28

    In Bayesian phylogenetic inference we are interested in distributions over a space of trees. The number of trees in a tree space is an important characteristic of the space and is useful for specifying prior distributions. When all samples come from the same time point and no prior information available on divergence times, the tree counting problem is easy. However, when fossil evidence is used in the inference to constrain the tree or data are sampled serially, new tree spaces arise and counting the number of trees is more difficult. We describe an algorithm that is polynomial in the number of sampled individuals for counting of resolutions of a constraint tree assuming that the number of constraints is fixed. We generalise this algorithm to counting resolutions of a fully ranked constraint tree. We describe a quadratic algorithm for counting the number of possible fully ranked trees on n sampled individuals. We introduce a new type of tree, called a fully ranked tree with sampled ancestors, and describe a cubic time algorithm for counting the number of such trees on n sampled individuals. These algorithms should be employed for Bayesian Markov chain Monte Carlo inference when fossil data are included or data are serially sampled.

  4. Soap films and GeoGebra in the study of Fermat and Steiner points

    NASA Astrophysics Data System (ADS)

    Flores, Alfinio; Park, Jungeun

    2018-05-01

    We discuss how mathematics and secondary mathematics education majors developed an understanding of Fermat points for the triangle as well as Steiner points for the square and regular pentagon, and also of soap film configurations between parallel plates where forces are in equilibrium. The activities included the use of soap films and the interactive geometry program GeoGebra. Students worked in small groups using these tools to investigate the properties of Fermat and Steiner points and then justified the results of their investigations using geometrical arguments. These activities are specific approaches of how to encourage prospective teachers to use physical experiments to support students' development of mathematical curiosity and mathematical justifications.

  5. SDIA: A dynamic situation driven information fusion algorithm for cloud environment

    NASA Astrophysics Data System (ADS)

    Guo, Shuhang; Wang, Tong; Wang, Jian

    2017-09-01

    Information fusion is an important issue in information integration domain. In order to form an extensive information fusion technology under the complex and diverse situations, a new information fusion algorithm is proposed. Firstly, a fuzzy evaluation model of tag utility was proposed that can be used to count the tag entropy. Secondly, a ubiquitous situation tag tree model is proposed to define multidimensional structure of information situation. Thirdly, the similarity matching between the situation models is classified into three types: the tree inclusion, the tree embedding, and the tree compatibility. Next, in order to reduce the time complexity of the tree compatible matching algorithm, a fast and ordered tree matching algorithm is proposed based on the node entropy, which is used to support the information fusion by ubiquitous situation. Since the algorithm revolve from the graph theory of disordered tree matching algorithm, it can improve the information fusion present recall rate and precision rate in the situation. The information fusion algorithm is compared with the star and the random tree matching algorithm, and the difference between the three algorithms is analyzed in the view of isomorphism, which proves the innovation and applicability of the algorithm.

  6. Myles A. Steiner | NREL

    Science.gov Websites

    ; Emmett E. Perl, John Simon, Daniel J. Friedman, Nikhil Jain, Paul Sharps, Claiborne McPheeters, Yukun Sun , Kevin L. Schulte, Ryan M. France, William E. McMahon, Emmett E. Perl, Daniel J. Friedman, Journal of ; E.E. Perl, D. Kuciauskas, J. Simon, D.J. Friedman, M.A. Steiner, Journal of Applied Physics, 122

  7. An Experiment on a Physical Pendulum and Steiner's Theorem

    ERIC Educational Resources Information Center

    Russeva, G. B.; Tsutsumanova, G. G.; Russev, S. C.

    2010-01-01

    Introductory physics laboratory curricula usually include experiments on the moment of inertia, the centre of gravity, the harmonic motion of a physical pendulum, and Steiner's theorem. We present a simple experiment using very low cost equipment for investigating these subjects in the general case of an asymmetrical test body. (Contains 3 figures…

  8. The Steiner Multigraph Problem: Wildlife corridor design for multiple species

    Treesearch

    Katherine J. Lai; Carla P. Gomes; Michael K. Schwartz; Kevin S. McKelvey; David E. Calkin; Claire A. Montgomery

    2011-01-01

    The conservation of wildlife corridors between existing habitat preserves is important for combating the effects of habitat loss and fragmentation facing species of concern. We introduce the Steiner Multigraph Problem to model the problem of minimum-cost wildlife corridor design for multiple species with different landscape requirements. This problem can also model...

  9. An Education Lived

    ERIC Educational Resources Information Center

    Steiner, David

    2009-01-01

    This article is an autobiographical account of a remarkable childhood. In this essay, David Steiner, the Klara & Larry Silverstein Dean of the School of Education at Hunter College in New York, chronicles his early years and his road to Oxford. David is the son of George Steiner, the polymath who has scathingly denounced Western societies for the…

  10. Holism in Teacher Development: A Goethean Perspective

    ERIC Educational Resources Information Center

    Oberski, Iddo; McNally, Jim

    2007-01-01

    Teaching has moved gradually from being seen as an art or craft to an evidence-based techno-rational profession. However, within Steiner-Waldorf schools, teachers are largely autonomous and seen, like their pupils, as always "coming into being", through the development of an objective imaginative faculty. This perspective is derived from Steiner's…

  11. A Fascinating Application of Steiner's Theorem for Trapezium: Geometric Constructions Using Straightedge Alone

    ERIC Educational Resources Information Center

    Stupel, Moshe; Ben-Chaim, David

    2013-01-01

    Based on Steiner's fascinating theorem for trapezium, seven geometrical constructions using straight-edge alone are described. These constructions provide an excellent base for teaching theorems and the properties of geometrical shapes, as well as challenging thought and inspiring deeper insight into the world of geometry. In particular, this…

  12. Fear and Attraction in Statecraft: Western Multilateralism’s Double-Edged Swords

    DTIC Science & Technology

    2013-06-01

    Zara Steiner, The Lights that Failed: European International History 1919–1933 (Oxford: Oxford University Press, 2005) 1–5. 111 Gray, War, Peace and...Steven E. Miller, 104– 140. Cambridge, MA: The MIT Press, 2001. Steiner, Zara . The Lights that Failed: European International History 1919–1933. Oxford

  13. Waldorf Schools: A Child-Centered System.

    ERIC Educational Resources Information Center

    Ogletree, Earl J.

    This paper presents an overview of the philosophy, psychology of learning, teaching methods, and curriculum of the Waldorf Schools. Most Waldorf teachers are influenced by the esoteric form of critical idealism propounded by Rudolf Steiner. The child is considered by Steiner to be a spiritual being who has reincarnated on to earth in a physical…

  14. Drawing and Painting in Rudolf Steiner Schools.

    ERIC Educational Resources Information Center

    Junemann, Margit; Weitmann, Fritz

    This book gives an overview of the Waldorf School teaching plan and art curriculum. The book thoroughly investigates many aspects of art that Rudolf Steiner spoke of in lectures, notes, and demonstrations. Particular emphasis is placed upon his work on color. Specific lessons are given for the elementary classes, and discussions of principles and…

  15. Coalescent-based species tree inference from gene tree topologies under incomplete lineage sorting by maximum likelihood.

    PubMed

    Wu, Yufeng

    2012-03-01

    Incomplete lineage sorting can cause incongruence between the phylogenetic history of genes (the gene tree) and that of the species (the species tree), which can complicate the inference of phylogenies. In this article, I present a new coalescent-based algorithm for species tree inference with maximum likelihood. I first describe an improved method for computing the probability of a gene tree topology given a species tree, which is much faster than an existing algorithm by Degnan and Salter (2005). Based on this method, I develop a practical algorithm that takes a set of gene tree topologies and infers species trees with maximum likelihood. This algorithm searches for the best species tree by starting from initial species trees and performing heuristic search to obtain better trees with higher likelihood. This algorithm, called STELLS (which stands for Species Tree InfErence with Likelihood for Lineage Sorting), has been implemented in a program that is downloadable from the author's web page. The simulation results show that the STELLS algorithm is more accurate than an existing maximum likelihood method for many datasets, especially when there is noise in gene trees. I also show that the STELLS algorithm is efficient and can be applied to real biological datasets. © 2011 The Author. Evolution© 2011 The Society for the Study of Evolution.

  16. Finding Frequent Closed Itemsets in Sliding Window in Linear Time

    NASA Astrophysics Data System (ADS)

    Chen, Junbo; Zhou, Bo; Chen, Lu; Wang, Xinyu; Ding, Yiqun

    One of the most well-studied problems in data mining is computing the collection of frequent itemsets in large transactional databases. Since the introduction of the famous Apriori algorithm [14], many others have been proposed to find the frequent itemsets. Among such algorithms, the approach of mining closed itemsets has raised much interest in data mining community. The algorithms taking this approach include TITANIC [8], CLOSET+[6], DCI-Closed [4], FCI-Stream [3], GC-Tree [15], TGC-Tree [16] etc. Among these algorithms, FCI-Stream, GC-Tree and TGC-Tree are online algorithms work under sliding window environments. By the performance evaluation in [16], GC-Tree [15] is the fastest one. In this paper, an improved algorithm based on GC-Tree is proposed, the computational complexity of which is proved to be a linear combination of the average transaction size and the average closed itemset size. The algorithm is based on the essential theorem presented in Sect. 4.2. Empirically, the new algorithm is several orders of magnitude faster than the state of art algorithm, GC-Tree.

  17. The Impact of the Self-Awareness Process on Learning and Leading

    ERIC Educational Resources Information Center

    Steiner, Patricia

    2014-01-01

    In this article, Patricia Steiner describes a research problem that took considerable time and energy to investigate: the study of the "self-awareness" process. Steiner states that, if we believe in the concept of lifelong learning and development, then we must acknowledge the value of self-awareness as an important precursor to learning…

  18. A Scheme for Understanding Group Processes in Problem-Based Learning

    ERIC Educational Resources Information Center

    Hammar Chiriac, Eva

    2008-01-01

    The purpose of this study was to identify, describe and interpret group processes occurring in tutorials in problem-based learning. Another aim was to investigate if a combination of Steiner's (Steiner, I. D. (1972). "Group process and productivity". New York: Academic Press.) theory of group work and Bion's (Bion, W. R. (1961). "Experiences in…

  19. Assessing New York's Commissioner of Education

    ERIC Educational Resources Information Center

    Meyer, Peter

    2011-01-01

    In this article, the author talks about the resignation of New York State's commissioner of education David Steiner, and how it will affect the state's Race to the Top. He contends that Steiner was savvy enough to understand the importance of Race to the Top and able enough to turn the state's education energies toward it. The "Washington…

  20. Soap Films and GeoGebra in the Study of Fermat and Steiner Points

    ERIC Educational Resources Information Center

    Flores, Alfinio; Park, Jungeun

    2018-01-01

    We discuss how mathematics and secondary mathematics education majors developed an understanding of Fermat points for the triangle as well as Steiner points for the square and regular pentagon, and also of soap film configurations between parallel plates where forces are in equilibrium. The activities included the use of soap films and the…

  1. On the Path towards Thinking: Learning from Martin Heidegger and Rudolf Steiner

    ERIC Educational Resources Information Center

    Dahlin, Bo

    2009-01-01

    This paper is a philosophical study of the nature of thinking based on the philosophies of Martin Heidegger and Rudolf Steiner. For Heidegger, the pre-Socratic Greek philosophers exemplified genuine thinking, appreciating the meaning of Being. But this kind of philosophy was soon replaced by the onto-theological approach, in which Being was…

  2. The Effect of Steiner, Montessori, and National Curriculum Education upon Children's Pretence and Creativity

    ERIC Educational Resources Information Center

    Kirkham, Julie Ann; Kidd, Evan

    2017-01-01

    Pretence and creativity are often regarded as ubiquitous characteristics of childhood, yet not all education systems value or promote these attributes to the same extent. Different pedagogies and practices are evident within the UK National Curriculum, Steiner and Montessori schools. In this study, 20 children participated from each of these…

  3. Closed Circular Chains

    ERIC Educational Resources Information Center

    Caglayan, Günhan

    2016-01-01

    A Steiner chain is defined as the sequence of n circles that are all tangent to two given non-intersecting circles. A closed chain, in particular, is one in which every circle in the sequence is tangent to the previous and next circles of the chain. In a closed Steiner chain the first and the "n"th circles of the chain are also tangent…

  4. A Day in the Life of the Rudolf Steiner School.

    ERIC Educational Resources Information Center

    Prescott, Jennifer O.

    1999-01-01

    Describes a typical day at the Rudolf Steiner School, an arts-based Waldorf school that encourages students to be anything they want to be and integrates the arts into everything. Natural developmental stages is an intrinsic part of the curriculum. Students remain with the same teacher for 8 years. A sidebar notes what opponents say about Waldorf…

  5. An algorithm for computing the gene tree probability under the multispecies coalescent and its application in the inference of population tree

    PubMed Central

    2016-01-01

    Motivation: Gene tree represents the evolutionary history of gene lineages that originate from multiple related populations. Under the multispecies coalescent model, lineages may coalesce outside the species (population) boundary. Given a species tree (with branch lengths), the gene tree probability is the probability of observing a specific gene tree topology under the multispecies coalescent model. There are two existing algorithms for computing the exact gene tree probability. The first algorithm is due to Degnan and Salter, where they enumerate all the so-called coalescent histories for the given species tree and the gene tree topology. Their algorithm runs in exponential time in the number of gene lineages in general. The second algorithm is the STELLS algorithm (2012), which is usually faster but also runs in exponential time in almost all the cases. Results: In this article, we present a new algorithm, called CompactCH, for computing the exact gene tree probability. This new algorithm is based on the notion of compact coalescent histories: multiple coalescent histories are represented by a single compact coalescent history. The key advantage of our new algorithm is that it runs in polynomial time in the number of gene lineages if the number of populations is fixed to be a constant. The new algorithm is more efficient than the STELLS algorithm both in theory and in practice when the number of populations is small and there are multiple gene lineages from each population. As an application, we show that CompactCH can be applied in the inference of population tree (i.e. the population divergence history) from population haplotypes. Simulation results show that the CompactCH algorithm enables efficient and accurate inference of population trees with much more haplotypes than a previous approach. Availability: The CompactCH algorithm is implemented in the STELLS software package, which is available for download at http://www.engr.uconn.edu/ywu/STELLS.html. Contact: ywu@engr.uconn.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27307621

  6. Minimal model of a cell connecting amoebic motion and adaptive transport networks.

    PubMed

    Gunji, Yukio-Pegio; Shirakawa, Tomohiro; Niizato, Takayuki; Haruna, Taichi

    2008-08-21

    A cell is a minimal self-sustaining system that can move and compute. Previous work has shown that a unicellular slime mold, Physarum, can be utilized as a biological computer based on cytoplasmic flow encapsulated by a membrane. Although the interplay between the modification of the boundary of a cell and the cytoplasmic flow surrounded by the boundary plays a key role in Physarum computing, no model of a cell has been developed to describe this interplay. Here we propose a toy model of a cell that shows amoebic motion and can solve a maze, Steiner minimum tree problem and a spanning tree problem. Only by assuming that cytoplasm is hardened after passing external matter (or softened part) through a cell, the shape of the cell and the cytoplasmic flow can be changed. Without cytoplasm hardening, a cell is easily destroyed. This suggests that cytoplasmic hardening and/or sol-gel transformation caused by external perturbation can keep a cell in a critical state leading to a wide variety of shapes and motion.

  7. "Give Them Time" -- An Analysis of School Readiness in Ireland's Early Education System: A Steiner Waldorf Perspective

    ERIC Educational Resources Information Center

    O'Connor, Doireann; Angus, Jonathan

    2014-01-01

    This paper examines a Steiner Waldorf Perspective to School Readiness and applies that international ideology to educational practice and curriculum policy in modern Ireland. The case for a later school start is championed with strong arguments underpinning the reasons why a later start is better in the long run for children's formal learning…

  8. Foreign Language Teaching in Rudolf Steiner Schools. Guidelines for Class-Teachers and Language Teachers. First Edition.

    ERIC Educational Resources Information Center

    Stott, Michael

    This book is intended for foreign language teachers interested in the approaches used in Rudolf Steiner schools, and also classroom teachers who teach foreign languages. Chapters address these issues: what the language lesson is to achieve; how the language lesson differs from other lessons; lesson design; examples of actual lessons; avoiding the…

  9. Finding Minimum-Power Broadcast Trees for Wireless Networks

    NASA Technical Reports Server (NTRS)

    Arabshahi, Payman; Gray, Andrew; Das, Arindam; El-Sharkawi, Mohamed; Marks, Robert, II

    2004-01-01

    Some algorithms have been devised for use in a method of constructing tree graphs that represent connections among the nodes of a wireless communication network. These algorithms provide for determining the viability of any given candidate connection tree and for generating an initial set of viable trees that can be used in any of a variety of search algorithms (e.g., a genetic algorithm) to find a tree that enables the network to broadcast from a source node to all other nodes while consuming the minimum amount of total power. The method yields solutions better than those of a prior algorithm known as the broadcast incremental power algorithm, albeit at a slightly greater computational cost.

  10. In memoriam Ladislau Steiner, neurosurgeon: some people from transylvania do live forever.

    PubMed

    Dinca, Eduard B; Ciurea, Alexandru V; Valéry, Charles-Ambroise

    2014-01-01

    We review the extraordinary professional trajectory of Ladislau Steiner, a prolific neurosurgeon and radiosurgeon, who died earlier this year. Dr. Steiner trained and practiced as a neurosurgeon in his native Romania until he was 42, before moving to Stockholm. After 25 years at the Karolinska Institute, when most people consider retirement, he spent the following 25 years of his life as director of the Lars Leksell Center for Gamma Knife Radiosurgery at the University of Virginia, Charlottesville, Virginia. At 90, nostalgia for Europe made him accept the position of director of the Gamma Knife Center at the International Neuroscience Institute in Hannover, Germany. His life was dedicated to the 15,000 patients whose lives he saved in his lengthy career. Copyright © 2014 Elsevier Inc. All rights reserved.

  11. Polynomial-Time Algorithms for Building a Consensus MUL-Tree

    PubMed Central

    Cui, Yun; Jansson, Jesper

    2012-01-01

    Abstract A multi-labeled phylogenetic tree, or MUL-tree, is a generalization of a phylogenetic tree that allows each leaf label to be used many times. MUL-trees have applications in biogeography, the study of host–parasite cospeciation, gene evolution studies, and computer science. Here, we consider the problem of inferring a consensus MUL-tree that summarizes a given set of conflicting MUL-trees, and present the first polynomial-time algorithms for solving it. In particular, we give a straightforward, fast algorithm for building a strict consensus MUL-tree for any input set of MUL-trees with identical leaf label multisets, as well as a polynomial-time algorithm for building a majority rule consensus MUL-tree for the special case where every leaf label occurs at most twice. We also show that, although it is NP-hard to find a majority rule consensus MUL-tree in general, the variant that we call the singular majority rule consensus MUL-tree can be constructed efficiently whenever it exists. PMID:22963134

  12. Polynomial-time algorithms for building a consensus MUL-tree.

    PubMed

    Cui, Yun; Jansson, Jesper; Sung, Wing-Kin

    2012-09-01

    A multi-labeled phylogenetic tree, or MUL-tree, is a generalization of a phylogenetic tree that allows each leaf label to be used many times. MUL-trees have applications in biogeography, the study of host-parasite cospeciation, gene evolution studies, and computer science. Here, we consider the problem of inferring a consensus MUL-tree that summarizes a given set of conflicting MUL-trees, and present the first polynomial-time algorithms for solving it. In particular, we give a straightforward, fast algorithm for building a strict consensus MUL-tree for any input set of MUL-trees with identical leaf label multisets, as well as a polynomial-time algorithm for building a majority rule consensus MUL-tree for the special case where every leaf label occurs at most twice. We also show that, although it is NP-hard to find a majority rule consensus MUL-tree in general, the variant that we call the singular majority rule consensus MUL-tree can be constructed efficiently whenever it exists.

  13. The Development of Early Literacy in Steiner- and Standard-Educated Children

    ERIC Educational Resources Information Center

    Cunningham, Anna J.; Carroll, Julia M.

    2011-01-01

    Background: There is evidence that children who are taught to read later in childhood (age 6-7) make faster progress in early literacy than those who are taught at a younger age (4-5 years), as is current practice in the UK. Aims: Steiner-educated children begin learning how to read at age 7, and have better reading-related skills at the onset of…

  14. Autumn Algorithm-Computation of Hybridization Networks for Realistic Phylogenetic Trees.

    PubMed

    Huson, Daniel H; Linz, Simone

    2018-01-01

    A minimum hybridization network is a rooted phylogenetic network that displays two given rooted phylogenetic trees using a minimum number of reticulations. Previous mathematical work on their calculation has usually assumed the input trees to be bifurcating, correctly rooted, or that they both contain the same taxa. These assumptions do not hold in biological studies and "realistic" trees have multifurcations, are difficult to root, and rarely contain the same taxa. We present a new algorithm for computing minimum hybridization networks for a given pair of "realistic" rooted phylogenetic trees. We also describe how the algorithm might be used to improve the rooting of the input trees. We introduce the concept of "autumn trees", a nice framework for the formulation of algorithms based on the mathematics of "maximum acyclic agreement forests". While the main computational problem is hard, the run-time depends mainly on how different the given input trees are. In biological studies, where the trees are reasonably similar, our parallel implementation performs well in practice. The algorithm is available in our open source program Dendroscope 3, providing a platform for biologists to explore rooted phylogenetic networks. We demonstrate the utility of the algorithm using several previously studied data sets.

  15. Bacterial and fungal components in house dust of farm children, Rudolf Steiner school children and reference children--the PARSIFAL Study.

    PubMed

    Schram, D; Doekes, G; Boeve, M; Douwes, J; Riedler, J; Ublagger, E; von Mutius, E; Budde, J; Pershagen, G; Nyberg, F; Alm, J; Braun-Fahrländer, C; Waser, M; Brunekreef, B

    2005-05-01

    Growing up on a farm and an anthroposophic lifestyle are associated with a lower prevalence of allergic diseases in childhood. It has been suggested that the enhanced exposure to endotoxin is an important protective factor of farm environments. Little is known about exposure to other microbial components on farms and exposure in anthroposophic families. To assess the levels and determinants of bacterial endotoxin, mould beta(1,3)-glucans and fungal extracellular polysaccharides (EPS) in house dust of farm children, Steiner school children and reference children. Mattress and living room dust was collected in the homes of 229 farm children, 122 Steiner children and 60 and 67 of their respective reference children in five European countries. Stable dust was collected as well. All samples were analysed in one central laboratory. Determinants were assessed by questionnaire. Levels of endotoxin, EPS and glucans per gram of house dust in farm homes were 1.2- to 3.2-fold higher than levels in reference homes. For Steiner children, 1.1- to 1.6-fold higher levels were observed compared with their reference children. These differences were consistently found across countries, although mean levels varied considerably. Differences between groups and between countries were also significant after adjustment for home and family characteristics. Farm children are not only consistently exposed to higher levels of endotoxin, but also to higher levels of mould components. Steiner school children may also be exposed to higher levels of microbial agents, but differences with reference children are much less pronounced than for farm children. Further analyses are, however, required to assess the association between exposure to these various microbial agents and allergic and airway diseases in the PARSIFAL population.

  16. Direct evaluation of fault trees using object-oriented programming techniques

    NASA Technical Reports Server (NTRS)

    Patterson-Hine, F. A.; Koen, B. V.

    1989-01-01

    Object-oriented programming techniques are used in an algorithm for the direct evaluation of fault trees. The algorithm combines a simple bottom-up procedure for trees without repeated events with a top-down recursive procedure for trees with repeated events. The object-oriented approach results in a dynamic modularization of the tree at each step in the reduction process. The algorithm reduces the number of recursive calls required to solve trees with repeated events and calculates intermediate results as well as the solution of the top event. The intermediate results can be reused if part of the tree is modified. An example is presented in which the results of the algorithm implemented with conventional techniques are compared to those of the object-oriented approach.

  17. Teaching Mathematics in Rudolf Steiner Schools for Classes I-VIII. How To Become Imaginative and Holistic. Volume 1, Up to Age 14.

    ERIC Educational Resources Information Center

    Jarman, Ron

    This book aims to present helpful, practical ideas and suggestions for mathematics teaching. Focus is on how teaching can be developed in a Rudolf Steiner (Waldorf) School and includes treatment of mathematical topics applicable to the 7-14 age group. Suggestions for curriculum and examples for children to work on are presented with a very wide…

  18. The Pacification Campaign of Madagascar: 1896-1905

    DTIC Science & Technology

    2002-01-01

    and 1940s. This was no improvised brutality. My German colleague, Rudolf Scharping revealed on 9 April details of a covert Serbian plan, code-named...administrator arrived to begin attempts to transfer authority to local institutions and to work to improve security and boost the economy. Steiner , a...Yugoslav President Slobodan Milosevic’s crackdown on ethnic Albanians in the province. Steiner also said he would focus on creating jobs in the province

  19. A Fast Exact k-Nearest Neighbors Algorithm for High Dimensional Search Using k-Means Clustering and Triangle Inequality.

    PubMed

    Wang, Xueyi

    2012-02-08

    The k-nearest neighbors (k-NN) algorithm is a widely used machine learning method that finds nearest neighbors of a test object in a feature space. We present a new exact k-NN algorithm called kMkNN (k-Means for k-Nearest Neighbors) that uses the k-means clustering and the triangle inequality to accelerate the searching for nearest neighbors in a high dimensional space. The kMkNN algorithm has two stages. In the buildup stage, instead of using complex tree structures such as metric trees, kd-trees, or ball-tree, kMkNN uses a simple k-means clustering method to preprocess the training dataset. In the searching stage, given a query object, kMkNN finds nearest training objects starting from the nearest cluster to the query object and uses the triangle inequality to reduce the distance calculations. Experiments show that the performance of kMkNN is surprisingly good compared to the traditional k-NN algorithm and tree-based k-NN algorithms such as kd-trees and ball-trees. On a collection of 20 datasets with up to 10(6) records and 10(4) dimensions, kMkNN shows a 2-to 80-fold reduction of distance calculations and a 2- to 60-fold speedup over the traditional k-NN algorithm for 16 datasets. Furthermore, kMkNN performs significant better than a kd-tree based k-NN algorithm for all datasets and performs better than a ball-tree based k-NN algorithm for most datasets. The results show that kMkNN is effective for searching nearest neighbors in high dimensional spaces.

  20. Decision tree and ensemble learning algorithms with their applications in bioinformatics.

    PubMed

    Che, Dongsheng; Liu, Qi; Rasheed, Khaled; Tao, Xiuping

    2011-01-01

    Machine learning approaches have wide applications in bioinformatics, and decision tree is one of the successful approaches applied in this field. In this chapter, we briefly review decision tree and related ensemble algorithms and show the successful applications of such approaches on solving biological problems. We hope that by learning the algorithms of decision trees and ensemble classifiers, biologists can get the basic ideas of how machine learning algorithms work. On the other hand, by being exposed to the applications of decision trees and ensemble algorithms in bioinformatics, computer scientists can get better ideas of which bioinformatics topics they may work on in their future research directions. We aim to provide a platform to bridge the gap between biologists and computer scientists.

  1. A Hybrid Shared-Memory Parallel Max-Tree Algorithm for Extreme Dynamic-Range Images.

    PubMed

    Moschini, Ugo; Meijster, Arnold; Wilkinson, Michael H F

    2018-03-01

    Max-trees, or component trees, are graph structures that represent the connected components of an image in a hierarchical way. Nowadays, many application fields rely on images with high-dynamic range or floating point values. Efficient sequential algorithms exist to build trees and compute attributes for images of any bit depth. However, we show that the current parallel algorithms perform poorly already with integers at bit depths higher than 16 bits per pixel. We propose a parallel method combining the two worlds of flooding and merging max-tree algorithms. First, a pilot max-tree of a quantized version of the image is built in parallel using a flooding method. Later, this structure is used in a parallel leaf-to-root approach to compute efficiently the final max-tree and to drive the merging of the sub-trees computed by the threads. We present an analysis of the performance both on simulated and actual 2D images and 3D volumes. Execution times are about better than the fastest sequential algorithm and speed-up goes up to on 64 threads.

  2. Roy-Steiner equations for πN scattering

    NASA Astrophysics Data System (ADS)

    de Elvira, J. Ruiz; Ditsche, C.; Hoferichter, M.; Kubis, B.; Meißner, U.-G.

    2015-10-01

    In this talk, we briefly review our ongoing collaboration to precisely determine the low-energy πN scattering amplitude by means of Roy-Steiner equations. After giving a brief overview of this system of dispersive equations and their application to πN scattering, we proceed to solve for the lower partial waves of the s-channel (πN → πN) and the t-channel l( {π π to bar NN} right) sub-problems.

  3. Effects of Anti-G Measures on Gas Exchange.

    DTIC Science & Technology

    1981-05-01

    position (+lGz), and the endotracheal tube was connected to a Rudolf valve arranged so that expired gas passed through a heated pneumotachograph and a... Steiner , 1960; Peterson, Bishop and Erickson, 1977). Data presented in Table 111-I suggest that application of the G-sult abdominal bladder tended to...accelerations. Aerospace Med. 31: 213-219, 1960. 18. Hershgold, E.J. and S.H. Steiner . Cardiovascular changes during acceleration stress in dogs. J

  4. Existence of Lipschitz selections of the Steiner map

    NASA Astrophysics Data System (ADS)

    Bednov, B. B.; Borodin, P. A.; Chesnokova, K. V.

    2018-02-01

    This paper is concerned with the problem of the existence of Lipschitz selections of the Steiner map {St}_n, which associates with n points of a Banach space X the set of their Steiner points. The answer to this problem depends on the geometric properties of the unit sphere S(X) of X, its dimension, and the number n. For n≥slant 4 general conditions are obtained on the space X under which {St}_n admits no Lipschitz selection. When X is finite dimensional it is shown that, if n≥slant 4 is even, the map {St}_n has a Lipschitz selection if and only if S(X) is a finite polytope; this is not true if n≥slant 3 is odd. For n=3 the (single-valued) map {St}_3 is shown to be Lipschitz continuous in any smooth strictly-convex two-dimensional space; this ceases to be true in three-dimensional spaces. Bibliography: 21 titles.

  5. Incremental triangulation by way of edge swapping and local optimization

    NASA Technical Reports Server (NTRS)

    Wiltberger, N. Lyn

    1994-01-01

    This document is intended to serve as an installation, usage, and basic theory guide for the two dimensional triangulation software 'HARLEY' written for the Silicon Graphics IRIS workstation. This code consists of an incremental triangulation algorithm based on point insertion and local edge swapping. Using this basic strategy, several types of triangulations can be produced depending on user selected options. For example, local edge swapping criteria can be chosen which minimizes the maximum interior angle (a MinMax triangulation) or which maximizes the minimum interior angle (a MaxMin or Delaunay triangulation). It should be noted that the MinMax triangulation is generally only locally optical (not globally optimal) in this measure. The MaxMin triangulation, however, is both locally and globally optical. In addition, Steiner triangulations can be constructed by inserting new sites at triangle circumcenters followed by edge swapping based on the MaxMin criteria. Incremental insertion of sites also provides flexibility in choosing cell refinement criteria. A dynamic heap structure has been implemented in the code so that once a refinement measure is specified (i.e., maximum aspect ratio or some measure of a solution gradient for the solution adaptive grid generation) the cell with the largest value of this measure is continually removed from the top of the heap and refined. The heap refinement strategy allows the user to specify either the number of cells desired or refine the mesh until all cell refinement measures satisfy a user specified tolerance level. Since the dynamic heap structure is constantly updated, the algorithm always refines the particular cell in the mesh with the largest refinement criteria value. The code allows the user to: triangulate a cloud of prespecified points (sites), triangulate a set of prespecified interior points constrained by prespecified boundary curve(s), Steiner triangulate the interior/exterior of prespecified boundary curve(s), refine existing triangulations based on solution error measures, and partition meshes based on the Cuthill-McKee, spectral, and coordinate bisection strategies.

  6. Bayes Forest: a data-intensive generator of morphological tree clones

    PubMed Central

    Järvenpää, Marko; Åkerblom, Markku; Raumonen, Pasi; Kaasalainen, Mikko

    2017-01-01

    Abstract Detailed and realistic tree form generators have numerous applications in ecology and forestry. For example, the varying morphology of trees contributes differently to formation of landscapes, natural habitats of species, and eco-physiological characteristics of the biosphere. Here, we present an algorithm for generating morphological tree “clones” based on the detailed reconstruction of the laser scanning data, statistical measure of similarity, and a plant growth model with simple stochastic rules. The algorithm is designed to produce tree forms, i.e., morphological clones, similar (and not identical) in respect to tree-level structure, but varying in fine-scale structural detail. Although we opted for certain choices in our algorithm, individual parts may vary depending on the application, making it a general adaptable pipeline. Namely, we showed that a specific multipurpose procedural stochastic growth model can be algorithmically adjusted to produce the morphological clones replicated from the target experimentally measured tree. For this, we developed a statistical measure of similarity (structural distance) between any given pair of trees, which allows for the comprehensive comparing of the tree morphologies by means of empirical distributions describing the geometrical and topological features of a tree. Finally, we developed a programmable interface to manipulate data required by the algorithm. Our algorithm can be used in a variety of applications for exploration of the morphological potential of the growth models (both theoretical and experimental), arising in all sectors of plant science research. PMID:29020742

  7. Detection and Counting of Orchard Trees from Vhr Images Using a Geometrical-Optical Model and Marked Template Matching

    NASA Astrophysics Data System (ADS)

    Maillard, Philippe; Gomes, Marília F.

    2016-06-01

    This article presents an original algorithm created to detect and count trees in orchards using very high resolution images. The algorithm is based on an adaptation of the "template matching" image processing approach, in which the template is based on a "geometricaloptical" model created from a series of parameters, such as illumination angles, maximum and ambient radiance, and tree size specifications. The algorithm is tested on four images from different regions of the world and different crop types. These images all have < 1 meter spatial resolution and were downloaded from the GoogleEarth application. Results show that the algorithm is very efficient at detecting and counting trees as long as their spectral and spatial characteristics are relatively constant. For walnut, mango and orange trees, the overall accuracy was clearly above 90%. However, the overall success rate for apple trees fell under 75%. It appears that the openness of the apple tree crown is most probably responsible for this poorer result. The algorithm is fully explained with a step-by-step description. At this stage, the algorithm still requires quite a bit of user interaction. The automatic determination of most of the required parameters is under development.

  8. A Modified Decision Tree Algorithm Based on Genetic Algorithm for Mobile User Classification Problem

    PubMed Central

    Liu, Dong-sheng; Fan, Shu-jiang

    2014-01-01

    In order to offer mobile customers better service, we should classify the mobile user firstly. Aimed at the limitations of previous classification methods, this paper puts forward a modified decision tree algorithm for mobile user classification, which introduced genetic algorithm to optimize the results of the decision tree algorithm. We also take the context information as a classification attributes for the mobile user and we classify the context into public context and private context classes. Then we analyze the processes and operators of the algorithm. At last, we make an experiment on the mobile user with the algorithm, we can classify the mobile user into Basic service user, E-service user, Plus service user, and Total service user classes and we can also get some rules about the mobile user. Compared to C4.5 decision tree algorithm and SVM algorithm, the algorithm we proposed in this paper has higher accuracy and more simplicity. PMID:24688389

  9. Multicasting for all-optical multifiber networks

    NASA Astrophysics Data System (ADS)

    Kã¶Ksal, Fatih; Ersoy, Cem

    2007-02-01

    All-optical wavelength-routed WDM WANs can support the high bandwidth and the long session duration requirements of the application scenarios such as interactive distance learning or on-line diagnosis of patients simultaneously in different hospitals. However, multifiber and limited sparse light splitting and wavelength conversion capabilities of switches result in a difficult optimization problem. We attack this problem using a layered graph model. The problem is defined as a k-edge-disjoint degree-constrained Steiner tree problem for routing and fiber and wavelength assignment of k multicasts. A mixed integer linear programming formulation for the problem is given, and a solution using CPLEX is provided. However, the complexity of the problem grows quickly with respect to the number of edges in the layered graph, which depends on the number of nodes, fibers, wavelengths, and multicast sessions. Hence, we propose two heuristics layered all-optical multicast algorithm [(LAMA) and conservative fiber and wavelength assignment (C-FWA)] to compare with CPLEX, existing work, and unicasting. Extensive computational experiments show that LAMA's performance is very close to CPLEX, and it is significantly better than existing work and C-FWA for nearly all metrics, since LAMA jointly optimizes routing and fiber-wavelength assignment phases compared with the other candidates, which attack the problem by decomposing two phases. Experiments also show that important metrics (e.g., session and group blocking probability, transmitter wavelength, and fiber conversion resources) are adversely affected by the separation of two phases. Finally, the fiber-wavelength assignment strategy of C-FWA (Ex-Fit) uses wavelength and fiber conversion resources more effectively than the First Fit.

  10. Pruning Rogue Taxa Improves Phylogenetic Accuracy: An Efficient Algorithm and Webservice

    PubMed Central

    Aberer, Andre J.; Krompass, Denis; Stamatakis, Alexandros

    2013-01-01

    Abstract The presence of rogue taxa (rogues) in a set of trees can frequently have a negative impact on the results of a bootstrap analysis (e.g., the overall support in consensus trees). We introduce an efficient graph-based algorithm for rogue taxon identification as well as an interactive webservice implementing this algorithm. Compared with our previous method, the new algorithm is up to 4 orders of magnitude faster, while returning qualitatively identical results. Because of this significant improvement in scalability, the new algorithm can now identify substantially more complex and compute-intensive rogue taxon constellations. On a large and diverse collection of real-world data sets, we show that our method yields better supported reduced/pruned consensus trees than any competing rogue taxon identification method. Using the parallel version of our open-source code, we successfully identified rogue taxa in a set of 100 trees with 116 334 taxa each. For simulated data sets, we show that when removing/pruning rogue taxa with our method from a tree set, we consistently obtain bootstrap consensus trees as well as maximum-likelihood trees that are topologically closer to the respective true trees. PMID:22962004

  11. Pruning rogue taxa improves phylogenetic accuracy: an efficient algorithm and webservice.

    PubMed

    Aberer, Andre J; Krompass, Denis; Stamatakis, Alexandros

    2013-01-01

    The presence of rogue taxa (rogues) in a set of trees can frequently have a negative impact on the results of a bootstrap analysis (e.g., the overall support in consensus trees). We introduce an efficient graph-based algorithm for rogue taxon identification as well as an interactive webservice implementing this algorithm. Compared with our previous method, the new algorithm is up to 4 orders of magnitude faster, while returning qualitatively identical results. Because of this significant improvement in scalability, the new algorithm can now identify substantially more complex and compute-intensive rogue taxon constellations. On a large and diverse collection of real-world data sets, we show that our method yields better supported reduced/pruned consensus trees than any competing rogue taxon identification method. Using the parallel version of our open-source code, we successfully identified rogue taxa in a set of 100 trees with 116 334 taxa each. For simulated data sets, we show that when removing/pruning rogue taxa with our method from a tree set, we consistently obtain bootstrap consensus trees as well as maximum-likelihood trees that are topologically closer to the respective true trees.

  12. Concurrent computation of attribute filters on shared memory parallel machines.

    PubMed

    Wilkinson, Michael H F; Gao, Hui; Hesselink, Wim H; Jonker, Jan-Eppo; Meijster, Arnold

    2008-10-01

    Morphological attribute filters have not previously been parallelized, mainly because they are both global and non-separable. We propose a parallel algorithm that achieves efficient parallelism for a large class of attribute filters, including attribute openings, closings, thinnings and thickenings, based on Salembier's Max-Trees and Min-trees. The image or volume is first partitioned in multiple slices. We then compute the Max-trees of each slice using any sequential Max-Tree algorithm. Subsequently, the Max-trees of the slices can be merged to obtain the Max-tree of the image. A C-implementation yielded good speed-ups on both a 16-processor MIPS 14000 parallel machine, and a dual-core Opteron-based machine. It is shown that the speed-up of the parallel algorithm is a direct measure of the gain with respect to the sequential algorithm used. Furthermore, the concurrent algorithm shows a speed gain of up to 72 percent on a single-core processor, due to reduced cache thrashing.

  13. Phylogenetic search through partial tree mixing

    PubMed Central

    2012-01-01

    Background Recent advances in sequencing technology have created large data sets upon which phylogenetic inference can be performed. Current research is limited by the prohibitive time necessary to perform tree search on a reasonable number of individuals. This research develops new phylogenetic algorithms that can operate on tens of thousands of species in a reasonable amount of time through several innovative search techniques. Results When compared to popular phylogenetic search algorithms, better trees are found much more quickly for large data sets. These algorithms are incorporated in the PSODA application available at http://dna.cs.byu.edu/psoda Conclusions The use of Partial Tree Mixing in a partition based tree space allows the algorithm to quickly converge on near optimal tree regions. These regions can then be searched in a methodical way to determine the overall optimal phylogenetic solution. PMID:23320449

  14. Fuzzy α-minimum spanning tree problem: definition and solutions

    NASA Astrophysics Data System (ADS)

    Zhou, Jian; Chen, Lu; Wang, Ke; Yang, Fan

    2016-04-01

    In this paper, the minimum spanning tree problem is investigated on the graph with fuzzy edge weights. The notion of fuzzy ? -minimum spanning tree is presented based on the credibility measure, and then the solutions of the fuzzy ? -minimum spanning tree problem are discussed under different assumptions. First, we respectively, assume that all the edge weights are triangular fuzzy numbers and trapezoidal fuzzy numbers and prove that the fuzzy ? -minimum spanning tree problem can be transformed to a classical problem on a crisp graph in these two cases, which can be solved by classical algorithms such as the Kruskal algorithm and the Prim algorithm in polynomial time. Subsequently, as for the case that the edge weights are general fuzzy numbers, a fuzzy simulation-based genetic algorithm using Prüfer number representation is designed for solving the fuzzy ? -minimum spanning tree problem. Some numerical examples are also provided for illustrating the effectiveness of the proposed solutions.

  15. Reduced-rank technique for joint channel estimation in TD-SCDMA systems

    NASA Astrophysics Data System (ADS)

    Kamil Marzook, Ali; Ismail, Alyani; Mohd Ali, Borhanuddin; Sali, Adawati; Khatun, Sabira

    2013-02-01

    In time division-synchronous code division multiple access systems, increasing the system capacity by exploiting the inserting of the largest number of users in one time slot (TS) requires adding more estimation processes to estimate the joint channel matrix for the whole system. The increase in the number of channel parameters due the increase in the number of users in one TS directly affects the precision of the estimator's performance. This article presents a novel channel estimation with low complexity, which relies on reducing the rank order of the total channel matrix H. The proposed method exploits the rank deficiency of H to reduce the number of parameters that characterise this matrix. The adopted reduced-rank technique is based on truncated singular value decomposition algorithm. The algorithms for reduced-rank joint channel estimation (JCE) are derived and compared against traditional full-rank JCEs: least squares (LS) or Steiner and enhanced (LS or MMSE) algorithms. Simulation results of the normalised mean square error showed the superiority of reduced-rank estimators. In addition, the channel impulse responses founded by reduced-rank estimator for all active users offers considerable performance improvement over the conventional estimator along the channel window length.

  16. Inferring duplications, losses, transfers and incomplete lineage sorting with nonbinary species trees.

    PubMed

    Stolzer, Maureen; Lai, Han; Xu, Minli; Sathaye, Deepa; Vernot, Benjamin; Durand, Dannie

    2012-09-15

    Gene duplication (D), transfer (T), loss (L) and incomplete lineage sorting (I) are crucial to the evolution of gene families and the emergence of novel functions. The history of these events can be inferred via comparison of gene and species trees, a process called reconciliation, yet current reconciliation algorithms model only a subset of these evolutionary processes. We present an algorithm to reconcile a binary gene tree with a nonbinary species tree under a DTLI parsimony criterion. This is the first reconciliation algorithm to capture all four evolutionary processes driving tree incongruence and the first to reconcile non-binary species trees with a transfer model. Our algorithm infers all optimal solutions and reports complete, temporally feasible event histories, giving the gene and species lineages in which each event occurred. It is fixed-parameter tractable, with polytime complexity when the maximum species outdegree is fixed. Application of our algorithms to prokaryotic and eukaryotic data show that use of an incomplete event model has substantial impact on the events inferred and resulting biological conclusions. Our algorithms have been implemented in Notung, a freely available phylogenetic reconciliation software package, available at http://www.cs.cmu.edu/~durand/Notung. mstolzer@andrew.cmu.edu.

  17. A stochastic multiple imputation algorithm for missing covariate data in tree-structured survival analysis.

    PubMed

    Wallace, Meredith L; Anderson, Stewart J; Mazumdar, Sati

    2010-12-20

    Missing covariate data present a challenge to tree-structured methodology due to the fact that a single tree model, as opposed to an estimated parameter value, may be desired for use in a clinical setting. To address this problem, we suggest a multiple imputation algorithm that adds draws of stochastic error to a tree-based single imputation method presented by Conversano and Siciliano (Technical Report, University of Naples, 2003). Unlike previously proposed techniques for accommodating missing covariate data in tree-structured analyses, our methodology allows the modeling of complex and nonlinear covariate structures while still resulting in a single tree model. We perform a simulation study to evaluate our stochastic multiple imputation algorithm when covariate data are missing at random and compare it to other currently used methods. Our algorithm is advantageous for identifying the true underlying covariate structure when complex data and larger percentages of missing covariate observations are present. It is competitive with other current methods with respect to prediction accuracy. To illustrate our algorithm, we create a tree-structured survival model for predicting time to treatment response in older, depressed adults. Copyright © 2010 John Wiley & Sons, Ltd.

  18. Routing Algorithm based on Minimum Spanning Tree and Minimum Cost Flow for Hybrid Wireless-optical Broadband Access Network

    NASA Astrophysics Data System (ADS)

    Le, Zichun; Suo, Kaihua; Fu, Minglei; Jiang, Ling; Dong, Wen

    2012-03-01

    In order to minimize the average end to end delay for data transporting in hybrid wireless optical broadband access network, a novel routing algorithm named MSTMCF (minimum spanning tree and minimum cost flow) is devised. The routing problem is described as a minimum spanning tree and minimum cost flow model and corresponding algorithm procedures are given. To verify the effectiveness of MSTMCF algorithm, extensively simulations based on OWNS have been done under different types of traffic source.

  19. Exact solutions for species tree inference from discordant gene trees.

    PubMed

    Chang, Wen-Chieh; Górecki, Paweł; Eulenstein, Oliver

    2013-10-01

    Phylogenetic analysis has to overcome the grant challenge of inferring accurate species trees from evolutionary histories of gene families (gene trees) that are discordant with the species tree along whose branches they have evolved. Two well studied approaches to cope with this challenge are to solve either biologically informed gene tree parsimony (GTP) problems under gene duplication, gene loss, and deep coalescence, or the classic RF supertree problem that does not rely on any biological model. Despite the potential of these problems to infer credible species trees, they are NP-hard. Therefore, these problems are addressed by heuristics that typically lack any provable accuracy and precision. We describe fast dynamic programming algorithms that solve the GTP problems and the RF supertree problem exactly, and demonstrate that our algorithms can solve instances with data sets consisting of as many as 22 taxa. Extensions of our algorithms can also report the number of all optimal species trees, as well as the trees themselves. To better asses the quality of the resulting species trees that best fit the given gene trees, we also compute the worst case species trees, their numbers, and optimization score for each of the computational problems. Finally, we demonstrate the performance of our exact algorithms using empirical and simulated data sets, and analyze the quality of heuristic solutions for the studied problems by contrasting them with our exact solutions.

  20. Algorithm for protecting light-trees in survivable mesh wavelength-division-multiplexing networks

    NASA Astrophysics Data System (ADS)

    Luo, Hongbin; Li, Lemin; Yu, Hongfang

    2006-12-01

    Wavelength-division-multiplexing (WDM) technology is expected to facilitate bandwidth-intensive multicast applications such as high-definition television. A single fiber cut in a WDM mesh network, however, can disrupt the dissemination of information to several destinations on a light-tree based multicast session. Thus it is imperative to protect multicast sessions by reserving redundant resources. We propose a novel and efficient algorithm for protecting light-trees in survivable WDM mesh networks. The algorithm is called segment-based protection with sister node first (SSNF), whose basic idea is to protect a light-tree using a set of backup segments with a higher priority to protect the segments from a branch point to its children (sister nodes). The SSNF algorithm differs from the segment protection scheme proposed in the literature in how the segments are identified and protected. Our objective is to minimize the network resources used for protecting each primary light-tree such that the blocking probability can be minimized. To verify the effectiveness of the SSNF algorithm, we conduct extensive simulation experiments. The simulation results demonstrate that the SSNF algorithm outperforms existing algorithms for the same problem.

  1. Automatic design of decision-tree induction algorithms tailored to flexible-receptor docking data.

    PubMed

    Barros, Rodrigo C; Winck, Ana T; Machado, Karina S; Basgalupp, Márcio P; de Carvalho, André C P L F; Ruiz, Duncan D; de Souza, Osmar Norberto

    2012-11-21

    This paper addresses the prediction of the free energy of binding of a drug candidate with enzyme InhA associated with Mycobacterium tuberculosis. This problem is found within rational drug design, where interactions between drug candidates and target proteins are verified through molecular docking simulations. In this application, it is important not only to correctly predict the free energy of binding, but also to provide a comprehensible model that could be validated by a domain specialist. Decision-tree induction algorithms have been successfully used in drug-design related applications, specially considering that decision trees are simple to understand, interpret, and validate. There are several decision-tree induction algorithms available for general-use, but each one has a bias that makes it more suitable for a particular data distribution. In this article, we propose and investigate the automatic design of decision-tree induction algorithms tailored to particular drug-enzyme binding data sets. We investigate the performance of our new method for evaluating binding conformations of different drug candidates to InhA, and we analyze our findings with respect to decision tree accuracy, comprehensibility, and biological relevance. The empirical analysis indicates that our method is capable of automatically generating decision-tree induction algorithms that significantly outperform the traditional C4.5 algorithm with respect to both accuracy and comprehensibility. In addition, we provide the biological interpretation of the rules generated by our approach, reinforcing the importance of comprehensible predictive models in this particular bioinformatics application. We conclude that automatically designing a decision-tree algorithm tailored to molecular docking data is a promising alternative for the prediction of the free energy from the binding of a drug candidate with a flexible-receptor.

  2. Automatic design of decision-tree induction algorithms tailored to flexible-receptor docking data

    PubMed Central

    2012-01-01

    Background This paper addresses the prediction of the free energy of binding of a drug candidate with enzyme InhA associated with Mycobacterium tuberculosis. This problem is found within rational drug design, where interactions between drug candidates and target proteins are verified through molecular docking simulations. In this application, it is important not only to correctly predict the free energy of binding, but also to provide a comprehensible model that could be validated by a domain specialist. Decision-tree induction algorithms have been successfully used in drug-design related applications, specially considering that decision trees are simple to understand, interpret, and validate. There are several decision-tree induction algorithms available for general-use, but each one has a bias that makes it more suitable for a particular data distribution. In this article, we propose and investigate the automatic design of decision-tree induction algorithms tailored to particular drug-enzyme binding data sets. We investigate the performance of our new method for evaluating binding conformations of different drug candidates to InhA, and we analyze our findings with respect to decision tree accuracy, comprehensibility, and biological relevance. Results The empirical analysis indicates that our method is capable of automatically generating decision-tree induction algorithms that significantly outperform the traditional C4.5 algorithm with respect to both accuracy and comprehensibility. In addition, we provide the biological interpretation of the rules generated by our approach, reinforcing the importance of comprehensible predictive models in this particular bioinformatics application. Conclusions We conclude that automatically designing a decision-tree algorithm tailored to molecular docking data is a promising alternative for the prediction of the free energy from the binding of a drug candidate with a flexible-receptor. PMID:23171000

  3. Learning classification trees

    NASA Technical Reports Server (NTRS)

    Buntine, Wray

    1991-01-01

    Algorithms for learning classification trees have had successes in artificial intelligence and statistics over many years. How a tree learning algorithm can be derived from Bayesian decision theory is outlined. This introduces Bayesian techniques for splitting, smoothing, and tree averaging. The splitting rule turns out to be similar to Quinlan's information gain splitting rule, while smoothing and averaging replace pruning. Comparative experiments with reimplementations of a minimum encoding approach, Quinlan's C4 and Breiman et al. Cart show the full Bayesian algorithm is consistently as good, or more accurate than these other approaches though at a computational price.

  4. Water-quality assessment of Steiner Branch basin, Lafayette County, Wisconsin

    USGS Publications Warehouse

    Field, Stephen J.; Lidwin, R.A.

    1982-01-01

    Most of the nutrient load of the stream was transported during runoff: total organic nitrogen, 80 percent; ammonia nitrogen, 80 percent; total phosphorus, 84 percent; and total orthophosphorus, 77 percent. Transport of nitrite plus nitrate nitrogen and total nitrogen occurred primarily during baseflow conditions, with 75 and 56 percent, respectively, of the total load for the study period being transported during these conditions. The time distribution of total phosphorus, total orthophosphorus, ammonia nitrogen, and total organic nitrogen transport was very similar to suspended-sediment transport in Steiner Branch.

  5. A new approach to enhance the performance of decision tree for classifying gene expression data.

    PubMed

    Hassan, Md; Kotagiri, Ramamohanarao

    2013-12-20

    Gene expression data classification is a challenging task due to the large dimensionality and very small number of samples. Decision tree is one of the popular machine learning approaches to address such classification problems. However, the existing decision tree algorithms use a single gene feature at each node to split the data into its child nodes and hence might suffer from poor performance specially when classifying gene expression dataset. By using a new decision tree algorithm where, each node of the tree consists of more than one gene, we enhance the classification performance of traditional decision tree classifiers. Our method selects suitable genes that are combined using a linear function to form a derived composite feature. To determine the structure of the tree we use the area under the Receiver Operating Characteristics curve (AUC). Experimental analysis demonstrates higher classification accuracy using the new decision tree compared to the other existing decision trees in literature. We experimentally compare the effect of our scheme against other well known decision tree techniques. Experiments show that our algorithm can substantially boost the classification performance of the decision tree.

  6. Enumerating Substituted Benzene Isomers of Tree-Like Chemical Graphs.

    PubMed

    Li, Jinghui; Nagamochi, Hiroshi; Akutsu, Tatsuya

    2018-01-01

    Enumeration of chemical structures is useful for drug design, which is one of the main targets of computational biology and bioinformatics. A chemical graph with no other cycles than benzene rings is called tree-like, and becomes a tree possibly with multiple edges if we contract each benzene ring into a single virtual atom of valence 6. All tree-like chemical graphs with a given tree representation are called the substituted benzene isomers of . When we replace each virtual atom in with a benzene ring to obtain a substituted benzene isomer, distinct isomers of are caused by the difference in arrangements of atom groups around a benzene ring. In this paper, we propose an efficient algorithm that enumerates all substituted benzene isomers of a given tree representation . Our algorithm first counts the number of all the isomers of the tree representation by a dynamic programming method. To enumerate all the isomers, for each , our algorithm then generates the th isomer by backtracking the counting phase of the dynamic programming. We also implemented our algorithm for computational experiments.

  7. Efficient tree tensor network states (TTNS) for quantum chemistry: Generalizations of the density matrix renormalization group algorithm

    NASA Astrophysics Data System (ADS)

    Nakatani, Naoki; Chan, Garnet Kin-Lic

    2013-04-01

    We investigate tree tensor network states for quantum chemistry. Tree tensor network states represent one of the simplest generalizations of matrix product states and the density matrix renormalization group. While matrix product states encode a one-dimensional entanglement structure, tree tensor network states encode a tree entanglement structure, allowing for a more flexible description of general molecules. We describe an optimal tree tensor network state algorithm for quantum chemistry. We introduce the concept of half-renormalization which greatly improves the efficiency of the calculations. Using our efficient formulation we demonstrate the strengths and weaknesses of tree tensor network states versus matrix product states. We carry out benchmark calculations both on tree systems (hydrogen trees and π-conjugated dendrimers) as well as non-tree molecules (hydrogen chains, nitrogen dimer, and chromium dimer). In general, tree tensor network states require much fewer renormalized states to achieve the same accuracy as matrix product states. In non-tree molecules, whether this translates into a computational savings is system dependent, due to the higher prefactor and computational scaling associated with tree algorithms. In tree like molecules, tree network states are easily superior to matrix product states. As an illustration, our largest dendrimer calculation with tree tensor network states correlates 110 electrons in 110 active orbitals.

  8. The influence of conifer forest canopy cover on the accuracy of two individual tree measurement algorithms using lidar data

    Treesearch

    Michael J. Falkowski; Alistair M.S. Smith; Paul E. Gessler; Andrew T. Hudak; Lee A. Vierling; Jeffrey S. Evans

    2008-01-01

    Individual tree detection algorithms can provide accurate measurements of individual tree locations, crown diameters (from aerial photography and light detection and ranging (lidar) data), and tree heights (from lidar data). However, to be useful for forest management goals relating to timber harvest, carbon accounting, and ecological processes, there is a need to...

  9. Distance-Based Phylogenetic Methods Around a Polytomy.

    PubMed

    Davidson, Ruth; Sullivant, Seth

    2014-01-01

    Distance-based phylogenetic algorithms attempt to solve the NP-hard least-squares phylogeny problem by mapping an arbitrary dissimilarity map representing biological data to a tree metric. The set of all dissimilarity maps is a Euclidean space properly containing the space of all tree metrics as a polyhedral fan. Outputs of distance-based tree reconstruction algorithms such as UPGMA and neighbor-joining are points in the maximal cones in the fan. Tree metrics with polytomies lie at the intersections of maximal cones. A phylogenetic algorithm divides the space of all dissimilarity maps into regions based upon which combinatorial tree is reconstructed by the algorithm. Comparison of phylogenetic methods can be done by comparing the geometry of these regions. We use polyhedral geometry to compare the local nature of the subdivisions induced by least-squares phylogeny, UPGMA, and neighbor-joining when the true tree has a single polytomy with exactly four neighbors. Our results suggest that in some circumstances, UPGMA and neighbor-joining poorly match least-squares phylogeny.

  10. Detecting treatment-subgroup interactions in clustered data with generalized linear mixed-effects model trees.

    PubMed

    Fokkema, M; Smits, N; Zeileis, A; Hothorn, T; Kelderman, H

    2017-10-25

    Identification of subgroups of patients for whom treatment A is more effective than treatment B, and vice versa, is of key importance to the development of personalized medicine. Tree-based algorithms are helpful tools for the detection of such interactions, but none of the available algorithms allow for taking into account clustered or nested dataset structures, which are particularly common in psychological research. Therefore, we propose the generalized linear mixed-effects model tree (GLMM tree) algorithm, which allows for the detection of treatment-subgroup interactions, while accounting for the clustered structure of a dataset. The algorithm uses model-based recursive partitioning to detect treatment-subgroup interactions, and a GLMM to estimate the random-effects parameters. In a simulation study, GLMM trees show higher accuracy in recovering treatment-subgroup interactions, higher predictive accuracy, and lower type II error rates than linear-model-based recursive partitioning and mixed-effects regression trees. Also, GLMM trees show somewhat higher predictive accuracy than linear mixed-effects models with pre-specified interaction effects, on average. We illustrate the application of GLMM trees on an individual patient-level data meta-analysis on treatments for depression. We conclude that GLMM trees are a promising exploratory tool for the detection of treatment-subgroup interactions in clustered datasets.

  11. Image compression using quad-tree coding with morphological dilation

    NASA Astrophysics Data System (ADS)

    Wu, Jiaji; Jiang, Weiwei; Jiao, Licheng; Wang, Lei

    2007-11-01

    In this paper, we propose a new algorithm which integrates morphological dilation operation to quad-tree coding, the purpose of doing this is to compensate each other's drawback by using quad-tree coding and morphological dilation operation respectively. New algorithm can not only quickly find the seed significant coefficient of dilation but also break the limit of block boundary of quad-tree coding. We also make a full use of both within-subband and cross-subband correlation to avoid the expensive cost of representing insignificant coefficients. Experimental results show that our algorithm outperforms SPECK and SPIHT. Without using any arithmetic coding, our algorithm can achieve good performance with low computational cost and it's more suitable to mobile devices or scenarios with a strict real-time requirement.

  12. Decision tree methods: applications for classification and prediction.

    PubMed

    Song, Yan-Yan; Lu, Ying

    2015-04-25

    Decision tree methodology is a commonly used data mining method for establishing classification systems based on multiple covariates or for developing prediction algorithms for a target variable. This method classifies a population into branch-like segments that construct an inverted tree with a root node, internal nodes, and leaf nodes. The algorithm is non-parametric and can efficiently deal with large, complicated datasets without imposing a complicated parametric structure. When the sample size is large enough, study data can be divided into training and validation datasets. Using the training dataset to build a decision tree model and a validation dataset to decide on the appropriate tree size needed to achieve the optimal final model. This paper introduces frequently used algorithms used to develop decision trees (including CART, C4.5, CHAID, and QUEST) and describes the SPSS and SAS programs that can be used to visualize tree structure.

  13. Greedy algorithms in disordered systems

    NASA Astrophysics Data System (ADS)

    Duxbury, P. M.; Dobrin, R.

    1999-08-01

    We discuss search, minimal path and minimal spanning tree algorithms and their applications to disordered systems. Greedy algorithms solve these problems exactly, and are related to extremal dynamics in physics. Minimal cost path (Dijkstra) and minimal cost spanning tree (Prim) algorithms provide extremal dynamics for a polymer in a random medium (the KPZ universality class) and invasion percolation (without trapping) respectively.

  14. A data driven approach for condition monitoring of wind turbine blade using vibration signals through best-first tree algorithm and functional trees algorithm: A comparative study.

    PubMed

    Joshuva, A; Sugumaran, V

    2017-03-01

    Wind energy is one of the important renewable energy resources available in nature. It is one of the major resources for production of energy because of its dependability due to the development of the technology and relatively low cost. Wind energy is converted into electrical energy using rotating blades. Due to environmental conditions and large structure, the blades are subjected to various vibration forces that may cause damage to the blades. This leads to a liability in energy production and turbine shutdown. The downtime can be reduced when the blades are diagnosed continuously using structural health condition monitoring. These are considered as a pattern recognition problem which consists of three phases namely, feature extraction, feature selection, and feature classification. In this study, statistical features were extracted from vibration signals, feature selection was carried out using a J48 decision tree algorithm and feature classification was performed using best-first tree algorithm and functional trees algorithm. The better algorithm is suggested for fault diagnosis of wind turbine blade. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  15. Object-Oriented Algorithm For Evaluation Of Fault Trees

    NASA Technical Reports Server (NTRS)

    Patterson-Hine, F. A.; Koen, B. V.

    1992-01-01

    Algorithm for direct evaluation of fault trees incorporates techniques of object-oriented programming. Reduces number of calls needed to solve trees with repeated events. Provides significantly improved software environment for such computations as quantitative analyses of safety and reliability of complicated systems of equipment (e.g., spacecraft or factories).

  16. Applications and Benefits for Big Data Sets Using Tree Distances and The T-SNE Algorithm

    DTIC Science & Technology

    2016-03-01

    BENEFITS FOR BIG DATA SETS USING TREE DISTANCES AND THE T-SNE ALGORITHM by Suyoung Lee March 2016 Thesis Advisor: Samuel E. Buttrey...REPORT TYPE AND DATES COVERED Master’s thesis 4. TITLE AND SUBTITLE APPLICATIONS AND BENEFITS FOR BIG DATA SETS USING TREE DISTANCES AND THE T-SNE...this work we use tree distance computed using Buttrey’s treeClust package in R, as discussed by Buttrey and Whitaker in 2015, to process mixed data

  17. Wavelet compression of multichannel ECG data by enhanced set partitioning in hierarchical trees algorithm.

    PubMed

    Sharifahmadian, Ershad

    2006-01-01

    The set partitioning in hierarchical trees (SPIHT) algorithm is very effective and computationally simple technique for image and signal compression. Here the author modified the algorithm which provides even better performance than the SPIHT algorithm. The enhanced set partitioning in hierarchical trees (ESPIHT) algorithm has performance faster than the SPIHT algorithm. In addition, the proposed algorithm reduces the number of bits in a bit stream which is stored or transmitted. I applied it to compression of multichannel ECG data. Also, I presented a specific procedure based on the modified algorithm for more efficient compression of multichannel ECG data. This method employed on selected records from the MIT-BIH arrhythmia database. According to experiments, the proposed method attained the significant results regarding compression of multichannel ECG data. Furthermore, in order to compress one signal which is stored for a long time, the proposed multichannel compression method can be utilized efficiently.

  18. A construction of unimodular equiangular tight frames from resolvable Steiner systems

    NASA Astrophysics Data System (ADS)

    Jasper, John

    2013-09-01

    An equiangular tight frame (ETF) is an M x N matrix which has orthogonal equal norm rows, equal norm columns, and the inner products of all pairs of columns have the same modulus. In this paper we study ETFs in which all of the entries are unimodular, and in particular pth roots of unity. A new construction of unimodular ETFs based on resolvable Steiner systems is presented. This construction gives many new examples of unimodular ETFs. In particular, an new infinite class of ETFs with entries in f1;-1g is presented.

  19. On the Complexity of Duplication-Transfer-Loss Reconciliation with Non-Binary Gene Trees.

    PubMed

    Kordi, Misagh; Bansal, Mukul S

    2017-01-01

    Duplication-Transfer-Loss (DTL) reconciliation has emerged as a powerful technique for studying gene family evolution in the presence of horizontal gene transfer. DTL reconciliation takes as input a gene family phylogeny and the corresponding species phylogeny, and reconciles the two by postulating speciation, gene duplication, horizontal gene transfer, and gene loss events. Efficient algorithms exist for finding optimal DTL reconciliations when the gene tree is binary. However, gene trees are frequently non-binary. With such non-binary gene trees, the reconciliation problem seeks to find a binary resolution of the gene tree that minimizes the reconciliation cost. Given the prevalence of non-binary gene trees, many efficient algorithms have been developed for this problem in the context of the simpler Duplication-Loss (DL) reconciliation model. Yet, no efficient algorithms exist for DTL reconciliation with non-binary gene trees and the complexity of the problem remains unknown. In this work, we resolve this open question by showing that the problem is, in fact, NP-hard. Our reduction applies to both the dated and undated formulations of DTL reconciliation. By resolving this long-standing open problem, this work will spur the development of both exact and heuristic algorithms for this important problem.

  20. Rare itemsets mining algorithm based on RP-Tree and spark framework

    NASA Astrophysics Data System (ADS)

    Liu, Sainan; Pan, Haoan

    2018-05-01

    For the issues of the rare itemsets mining in big data, this paper proposed a rare itemsets mining algorithm based on RP-Tree and Spark framework. Firstly, it arranged the data vertically according to the transaction identifier, in order to solve the defects of scan the entire data set, the vertical datasets are divided into frequent vertical datasets and rare vertical datasets. Then, it adopted the RP-Tree algorithm to construct the frequent pattern tree that contains rare items and generate rare 1-itemsets. After that, it calculated the support of the itemsets by scanning the two vertical data sets, finally, it used the iterative process to generate rare itemsets. The experimental show that the algorithm can effectively excavate rare itemsets and have great superiority in execution time.

  1. Automated Mobile System for Accurate Outdoor Tree Crop Enumeration Using an Uncalibrated Camera.

    PubMed

    Nguyen, Thuy Tuong; Slaughter, David C; Hanson, Bradley D; Barber, Andrew; Freitas, Amy; Robles, Daniel; Whelan, Erin

    2015-07-28

    This paper demonstrates an automated computer vision system for outdoor tree crop enumeration in a seedling nursery. The complete system incorporates both hardware components (including an embedded microcontroller, an odometry encoder, and an uncalibrated digital color camera) and software algorithms (including microcontroller algorithms and the proposed algorithm for tree crop enumeration) required to obtain robust performance in a natural outdoor environment. The enumeration system uses a three-step image analysis process based upon: (1) an orthographic plant projection method integrating a perspective transform with automatic parameter estimation; (2) a plant counting method based on projection histograms; and (3) a double-counting avoidance method based on a homography transform. Experimental results demonstrate the ability to count large numbers of plants automatically with no human effort. Results show that, for tree seedlings having a height up to 40 cm and a within-row tree spacing of approximately 10 cm, the algorithms successfully estimated the number of plants with an average accuracy of 95.2% for trees within a single image and 98% for counting of the whole plant population in a large sequence of images.

  2. Automated Mobile System for Accurate Outdoor Tree Crop Enumeration Using an Uncalibrated Camera

    PubMed Central

    Nguyen, Thuy Tuong; Slaughter, David C.; Hanson, Bradley D.; Barber, Andrew; Freitas, Amy; Robles, Daniel; Whelan, Erin

    2015-01-01

    This paper demonstrates an automated computer vision system for outdoor tree crop enumeration in a seedling nursery. The complete system incorporates both hardware components (including an embedded microcontroller, an odometry encoder, and an uncalibrated digital color camera) and software algorithms (including microcontroller algorithms and the proposed algorithm for tree crop enumeration) required to obtain robust performance in a natural outdoor environment. The enumeration system uses a three-step image analysis process based upon: (1) an orthographic plant projection method integrating a perspective transform with automatic parameter estimation; (2) a plant counting method based on projection histograms; and (3) a double-counting avoidance method based on a homography transform. Experimental results demonstrate the ability to count large numbers of plants automatically with no human effort. Results show that, for tree seedlings having a height up to 40 cm and a within-row tree spacing of approximately 10 cm, the algorithms successfully estimated the number of plants with an average accuracy of 95.2% for trees within a single image and 98% for counting of the whole plant population in a large sequence of images. PMID:26225982

  3. Co-expression network with protein-protein interaction and transcription regulation in malaria parasite Plasmodium falciparum.

    PubMed

    Yu, Fu-Dong; Yang, Shao-You; Li, Yuan-Yuan; Hu, Wei

    2013-04-10

    Malaria continues to be one of the most severe global infectious diseases, as a major threat to human health and economic development. Network-based biological analysis is a promising approach to uncover key genes and biological processes from a network viewpoint, which could not be recognized from individual gene-based signatures. We integrated gene co-expression profile with protein-protein interaction and transcriptional regulation information to construct a comprehensive gene co-expression network of Plasmodium falciparum. Based on this network, we identified 10 core modules by using ICE (Iterative Clique Enumeration) algorithm, which were essential for malaria parasite development in intraerythrocytic developmental cycle (IDC) stages. In each module, all genes were highly correlated probably due to co-regulation or formation of a protein complex. Some of these genes were recognized to be differentially coexpressed among three close-by IDC stages. The gene of prpf8 (PFD0265w) encoding pre-mRNA processing splicing factor 8 product was identified as DCGs (differentially co-expressed genes) among IDC stages, although this gene function was seldom reported in previous researches. Integrating the species-specific gene prediction and differential co-expression gene detection, we found some modules could perform species-specific functions according to some of genes in these modules were species-specific genes, like the module 10. Furthermore, in order to reveal the underlying mechanisms of the erythrocyte invasion by P. falciparum, Steiner Tree algorithm was employed to identify the invasion subnetwork from our gene co-expression network. The subnetwork-based analysis indicated that some important Plasmodium parasite specific genes could corporate with each other and be co-regulated during the parasite invasion process, which including a head-to-head gene pair of PfRH2a (PF13_0198) and PfRH2b (MAL13P1.176). This study based on gene co-expression network could shed new insights on the mechanisms of pathogenesis, even virulence and P. falciparum development. Crown Copyright © 2012. Published by Elsevier B.V. All rights reserved.

  4. Block-Based Connected-Component Labeling Algorithm Using Binary Decision Trees

    PubMed Central

    Chang, Wan-Yu; Chiu, Chung-Cheng; Yang, Jia-Horng

    2015-01-01

    In this paper, we propose a fast labeling algorithm based on block-based concepts. Because the number of memory access points directly affects the time consumption of the labeling algorithms, the aim of the proposed algorithm is to minimize neighborhood operations. Our algorithm utilizes a block-based view and correlates a raster scan to select the necessary pixels generated by a block-based scan mask. We analyze the advantages of a sequential raster scan for the block-based scan mask, and integrate the block-connected relationships using two different procedures with binary decision trees to reduce unnecessary memory access. This greatly simplifies the pixel locations of the block-based scan mask. Furthermore, our algorithm significantly reduces the number of leaf nodes and depth levels required in the binary decision tree. We analyze the labeling performance of the proposed algorithm alongside that of other labeling algorithms using high-resolution images and foreground images. The experimental results from synthetic and real image datasets demonstrate that the proposed algorithm is faster than other methods. PMID:26393597

  5. Faster Bit-Parallel Algorithms for Unordered Pseudo-tree Matching and Tree Homeomorphism

    NASA Astrophysics Data System (ADS)

    Kaneta, Yusaku; Arimura, Hiroki

    In this paper, we consider the unordered pseudo-tree matching problem, which is a problem of, given two unordered labeled trees P and T, finding all occurrences of P in T via such many-one embeddings that preserve node labels and parent-child relationship. This problem is closely related to tree pattern matching problem for XPath queries with child axis only. If m > w , we present an efficient algorithm that solves the problem in O(nm log(w)/w) time using O(hm/w + mlog(w)/w) space and O(m log(w)) preprocessing on a unit-cost arithmetic RAM model with addition, where m is the number of nodes in P, n is the number of nodes in T, h is the height of T, and w is the word length. We also discuss a modification of our algorithm for the unordered tree homeomorphism problem, which corresponds to a tree pattern matching problem for XPath queries with descendant axis only.

  6. Computing Maximum Cardinality Matchings in Parallel on Bipartite Graphs via Tree-Grafting

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

    Azad, Ariful; Buluc, Aydn; Pothen, Alex

    It is difficult to obtain high performance when computing matchings on parallel processors because matching algorithms explicitly or implicitly search for paths in the graph, and when these paths become long, there is little concurrency. In spite of this limitation, we present a new algorithm and its shared-memory parallelization that achieves good performance and scalability in computing maximum cardinality matchings in bipartite graphs. This algorithm searches for augmenting paths via specialized breadth-first searches (BFS) from multiple source vertices, hence creating more parallelism than single source algorithms. Algorithms that employ multiple-source searches cannot discard a search tree once no augmenting pathmore » is discovered from the tree, unlike algorithms that rely on single-source searches. We describe a novel tree-grafting method that eliminates most of the redundant edge traversals resulting from this property of multiple-source searches. We also employ the recent direction-optimizing BFS algorithm as a subroutine to discover augmenting paths faster. Our algorithm compares favorably with the current best algorithms in terms of the number of edges traversed, the average augmenting path length, and the number of iterations. Here, we provide a proof of correctness for our algorithm. Our NUMA-aware implementation is scalable to 80 threads of an Intel multiprocessor and to 240 threads on an Intel Knights Corner coprocessor. On average, our parallel algorithm runs an order of magnitude faster than the fastest algorithms available. The performance improvement is more significant on graphs with small matching number.« less

  7. Computing Maximum Cardinality Matchings in Parallel on Bipartite Graphs via Tree-Grafting

    DOE PAGES

    Azad, Ariful; Buluc, Aydn; Pothen, Alex

    2016-03-24

    It is difficult to obtain high performance when computing matchings on parallel processors because matching algorithms explicitly or implicitly search for paths in the graph, and when these paths become long, there is little concurrency. In spite of this limitation, we present a new algorithm and its shared-memory parallelization that achieves good performance and scalability in computing maximum cardinality matchings in bipartite graphs. This algorithm searches for augmenting paths via specialized breadth-first searches (BFS) from multiple source vertices, hence creating more parallelism than single source algorithms. Algorithms that employ multiple-source searches cannot discard a search tree once no augmenting pathmore » is discovered from the tree, unlike algorithms that rely on single-source searches. We describe a novel tree-grafting method that eliminates most of the redundant edge traversals resulting from this property of multiple-source searches. We also employ the recent direction-optimizing BFS algorithm as a subroutine to discover augmenting paths faster. Our algorithm compares favorably with the current best algorithms in terms of the number of edges traversed, the average augmenting path length, and the number of iterations. Here, we provide a proof of correctness for our algorithm. Our NUMA-aware implementation is scalable to 80 threads of an Intel multiprocessor and to 240 threads on an Intel Knights Corner coprocessor. On average, our parallel algorithm runs an order of magnitude faster than the fastest algorithms available. The performance improvement is more significant on graphs with small matching number.« less

  8. A new algorithm to construct phylogenetic networks from trees.

    PubMed

    Wang, J

    2014-03-06

    Developing appropriate methods for constructing phylogenetic networks from tree sets is an important problem, and much research is currently being undertaken in this area. BIMLR is an algorithm that constructs phylogenetic networks from tree sets. The algorithm can construct a much simpler network than other available methods. Here, we introduce an improved version of the BIMLR algorithm, QuickCass. QuickCass changes the selection strategy of the labels of leaves below the reticulate nodes, i.e., the nodes with an indegree of at least 2 in BIMLR. We show that QuickCass can construct simpler phylogenetic networks than BIMLR. Furthermore, we show that QuickCass is a polynomial-time algorithm when the output network that is constructed by QuickCass is binary.

  9. Efficient algorithms for a class of partitioning problems

    NASA Technical Reports Server (NTRS)

    Iqbal, M. Ashraf; Bokhari, Shahid H.

    1990-01-01

    The problem of optimally partitioning the modules of chain- or tree-like tasks over chain-structured or host-satellite multiple computer systems is addressed. This important class of problems includes many signal processing and industrial control applications. Prior research has resulted in a succession of faster exact and approximate algorithms for these problems. Polynomial exact and approximate algorithms are described for this class that are better than any of the previously reported algorithms. The approach is based on a preprocessing step that condenses the given chain or tree structured task into a monotonic chain or tree. The partitioning of this monotonic take can then be carried out using fast search techniques.

  10. Reconciliation of Gene and Species Trees

    PubMed Central

    Rusin, L. Y.; Lyubetskaya, E. V.; Gorbunov, K. Y.; Lyubetsky, V. A.

    2014-01-01

    The first part of the paper briefly overviews the problem of gene and species trees reconciliation with the focus on defining and algorithmic construction of the evolutionary scenario. Basic ideas are discussed for the aspects of mapping definitions, costs of the mapping and evolutionary scenario, imposing time scales on a scenario, incorporating horizontal gene transfers, binarization and reconciliation of polytomous trees, and construction of species trees and scenarios. The review does not intend to cover the vast diversity of literature published on these subjects. Instead, the authors strived to overview the problem of the evolutionary scenario as a central concept in many areas of evolutionary research. The second part provides detailed mathematical proofs for the solutions of two problems: (i) inferring a gene evolution along a species tree accounting for various types of evolutionary events and (ii) trees reconciliation into a single species tree when only gene duplications and losses are allowed. All proposed algorithms have a cubic time complexity and are mathematically proved to find exact solutions. Solving algorithms for problem (ii) can be naturally extended to incorporate horizontal transfers, other evolutionary events, and time scales on the species tree. PMID:24800245

  11. GIGA: a simple, efficient algorithm for gene tree inference in the genomic age

    PubMed Central

    2010-01-01

    Background Phylogenetic relationships between genes are not only of theoretical interest: they enable us to learn about human genes through the experimental work on their relatives in numerous model organisms from bacteria to fruit flies and mice. Yet the most commonly used computational algorithms for reconstructing gene trees can be inaccurate for numerous reasons, both algorithmic and biological. Additional information beyond gene sequence data has been shown to improve the accuracy of reconstructions, though at great computational cost. Results We describe a simple, fast algorithm for inferring gene phylogenies, which makes use of information that was not available prior to the genomic age: namely, a reliable species tree spanning much of the tree of life, and knowledge of the complete complement of genes in a species' genome. The algorithm, called GIGA, constructs trees agglomeratively from a distance matrix representation of sequences, using simple rules to incorporate this genomic age information. GIGA makes use of a novel conceptualization of gene trees as being composed of orthologous subtrees (containing only speciation events), which are joined by other evolutionary events such as gene duplication or horizontal gene transfer. An important innovation in GIGA is that, at every step in the agglomeration process, the tree is interpreted/reinterpreted in terms of the evolutionary events that created it. Remarkably, GIGA performs well even when using a very simple distance metric (pairwise sequence differences) and no distance averaging over clades during the tree construction process. Conclusions GIGA is efficient, allowing phylogenetic reconstruction of very large gene families and determination of orthologs on a large scale. It is exceptionally robust to adding more gene sequences, opening up the possibility of creating stable identifiers for referring to not only extant genes, but also their common ancestors. We compared trees produced by GIGA to those in the TreeFam database, and they were very similar in general, with most differences likely due to poor alignment quality. However, some remaining differences are algorithmic, and can be explained by the fact that GIGA tends to put a larger emphasis on minimizing gene duplication and deletion events. PMID:20534164

  12. GIGA: a simple, efficient algorithm for gene tree inference in the genomic age.

    PubMed

    Thomas, Paul D

    2010-06-09

    Phylogenetic relationships between genes are not only of theoretical interest: they enable us to learn about human genes through the experimental work on their relatives in numerous model organisms from bacteria to fruit flies and mice. Yet the most commonly used computational algorithms for reconstructing gene trees can be inaccurate for numerous reasons, both algorithmic and biological. Additional information beyond gene sequence data has been shown to improve the accuracy of reconstructions, though at great computational cost. We describe a simple, fast algorithm for inferring gene phylogenies, which makes use of information that was not available prior to the genomic age: namely, a reliable species tree spanning much of the tree of life, and knowledge of the complete complement of genes in a species' genome. The algorithm, called GIGA, constructs trees agglomeratively from a distance matrix representation of sequences, using simple rules to incorporate this genomic age information. GIGA makes use of a novel conceptualization of gene trees as being composed of orthologous subtrees (containing only speciation events), which are joined by other evolutionary events such as gene duplication or horizontal gene transfer. An important innovation in GIGA is that, at every step in the agglomeration process, the tree is interpreted/reinterpreted in terms of the evolutionary events that created it. Remarkably, GIGA performs well even when using a very simple distance metric (pairwise sequence differences) and no distance averaging over clades during the tree construction process. GIGA is efficient, allowing phylogenetic reconstruction of very large gene families and determination of orthologs on a large scale. It is exceptionally robust to adding more gene sequences, opening up the possibility of creating stable identifiers for referring to not only extant genes, but also their common ancestors. We compared trees produced by GIGA to those in the TreeFam database, and they were very similar in general, with most differences likely due to poor alignment quality. However, some remaining differences are algorithmic, and can be explained by the fact that GIGA tends to put a larger emphasis on minimizing gene duplication and deletion events.

  13. Structure and formation of ant transportation networks

    PubMed Central

    Latty, Tanya; Ramsch, Kai; Ito, Kentaro; Nakagaki, Toshiyuki; Sumpter, David J. T.; Middendorf, Martin; Beekman, Madeleine

    2011-01-01

    Many biological systems use extensive networks for the transport of resources and information. Ants are no exception. How do biological systems achieve efficient transportation networks in the absence of centralized control and without global knowledge of the environment? Here, we address this question by studying the formation and properties of inter-nest transportation networks in the Argentine ant (Linepithema humile). We find that the formation of inter-nest networks depends on the number of ants involved in the construction process. When the number of ants is sufficient and networks do form, they tend to have short total length but a low level of robustness. These networks are topologically similar to either minimum spanning trees or Steiner networks. The process of network formation involves an initial construction of multiple links followed by a pruning process that reduces the number of trails. Our study thus illuminates the conditions under and the process by which minimal biological transport networks can be constructed. PMID:21288958

  14. Integration of Proteomic, Transcriptional, and Interactome Data Reveals Hidden Signaling Components

    PubMed Central

    Huang, Shao-shan Carol; Fraenkel, Ernest

    2009-01-01

    Cellular signaling and regulatory networks underlie fundamental biological processes such as growth, differentiation, and response to the environment. Although there are now various high-throughput methods for studying these processes, knowledge of them remains fragmentary. Typically, the vast majority of hits identified by transcriptional, proteomic, and genetic assays lie outside of the expected pathways. These unexpected components of the cellular response are often the most interesting, because they can provide new insights into biological processes and potentially reveal new therapeutic approaches. However, they are also the most difficult to interpret. We present a technique, based on the Steiner tree problem, that uses previously reported protein-protein and protein-DNA interactions to determine how these hits are organized into functionally coherent pathways, revealing many components of the cellular response that are not readily apparent in the original data. Applied simultaneously to phosphoproteomic and transcriptional data for the yeast pheromone response, it identifies changes in diverse cellular processes that extend far beyond the expected pathways. PMID:19638617

  15. Efficient Wide Baseline Structure from Motion

    NASA Astrophysics Data System (ADS)

    Michelini, Mario; Mayer, Helmut

    2016-06-01

    This paper presents a Structure from Motion approach for complex unorganized image sets. To achieve high accuracy and robustness, image triplets are employed and (an approximate) camera calibration is assumed to be known. The focus lies on a complete linking of images even in case of large image distortions, e.g., caused by wide baselines, as well as weak baselines. A method for embedding image descriptors into Hamming space is proposed for fast image similarity ranking. The later is employed to limit the number of pairs to be matched by a wide baseline method. An iterative graph-based approach is proposed formulating image linking as the search for a terminal Steiner minimum tree in a line graph. Finally, additional links are determined and employed to improve the accuracy of the pose estimation. By this means, loops in long image sequences are implicitly closed. The potential of the proposed approach is demonstrated by results for several complex image sets also in comparison with VisualSFM.

  16. iNJclust: Iterative Neighbor-Joining Tree Clustering Framework for Inferring Population Structure.

    PubMed

    Limpiti, Tulaya; Amornbunchornvej, Chainarong; Intarapanich, Apichart; Assawamakin, Anunchai; Tongsima, Sissades

    2014-01-01

    Understanding genetic differences among populations is one of the most important issues in population genetics. Genetic variations, e.g., single nucleotide polymorphisms, are used to characterize commonality and difference of individuals from various populations. This paper presents an efficient graph-based clustering framework which operates iteratively on the Neighbor-Joining (NJ) tree called the iNJclust algorithm. The framework uses well-known genetic measurements, namely the allele-sharing distance, the neighbor-joining tree, and the fixation index. The behavior of the fixation index is utilized in the algorithm's stopping criterion. The algorithm provides an estimated number of populations, individual assignments, and relationships between populations as outputs. The clustering result is reported in the form of a binary tree, whose terminal nodes represent the final inferred populations and the tree structure preserves the genetic relationships among them. The clustering performance and the robustness of the proposed algorithm are tested extensively using simulated and real data sets from bovine, sheep, and human populations. The result indicates that the number of populations within each data set is reasonably estimated, the individual assignment is robust, and the structure of the inferred population tree corresponds to the intrinsic relationships among populations within the data.

  17. Performance analysis of a dual-tree algorithm for computing spatial distance histograms

    PubMed Central

    Chen, Shaoping; Tu, Yi-Cheng; Xia, Yuni

    2011-01-01

    Many scientific and engineering fields produce large volume of spatiotemporal data. The storage, retrieval, and analysis of such data impose great challenges to database systems design. Analysis of scientific spatiotemporal data often involves computing functions of all point-to-point interactions. One such analytics, the Spatial Distance Histogram (SDH), is of vital importance to scientific discovery. Recently, algorithms for efficient SDH processing in large-scale scientific databases have been proposed. These algorithms adopt a recursive tree-traversing strategy to process point-to-point distances in the visited tree nodes in batches, thus require less time when compared to the brute-force approach where all pairwise distances have to be computed. Despite the promising experimental results, the complexity of such algorithms has not been thoroughly studied. In this paper, we present an analysis of such algorithms based on a geometric modeling approach. The main technique is to transform the analysis of point counts into a problem of quantifying the area of regions where pairwise distances can be processed in batches by the algorithm. From the analysis, we conclude that the number of pairwise distances that are left to be processed decreases exponentially with more levels of the tree visited. This leads to the proof of a time complexity lower than the quadratic time needed for a brute-force algorithm and builds the foundation for a constant-time approximate algorithm. Our model is also general in that it works for a wide range of point spatial distributions, histogram types, and space-partitioning options in building the tree. PMID:21804753

  18. Efficient FPT Algorithms for (Strict) Compatibility of Unrooted Phylogenetic Trees.

    PubMed

    Baste, Julien; Paul, Christophe; Sau, Ignasi; Scornavacca, Celine

    2017-04-01

    In phylogenetics, a central problem is to infer the evolutionary relationships between a set of species X; these relationships are often depicted via a phylogenetic tree-a tree having its leaves labeled bijectively by elements of X and without degree-2 nodes-called the "species tree." One common approach for reconstructing a species tree consists in first constructing several phylogenetic trees from primary data (e.g., DNA sequences originating from some species in X), and then constructing a single phylogenetic tree maximizing the "concordance" with the input trees. The obtained tree is our estimation of the species tree and, when the input trees are defined on overlapping-but not identical-sets of labels, is called "supertree." In this paper, we focus on two problems that are central when combining phylogenetic trees into a supertree: the compatibility and the strict compatibility problems for unrooted phylogenetic trees. These problems are strongly related, respectively, to the notions of "containing as a minor" and "containing as a topological minor" in the graph community. Both problems are known to be fixed parameter tractable in the number of input trees k, by using their expressibility in monadic second-order logic and a reduction to graphs of bounded treewidth. Motivated by the fact that the dependency on k of these algorithms is prohibitively large, we give the first explicit dynamic programming algorithms for solving these problems, both running in time [Formula: see text], where n is the total size of the input.

  19. An algorithm to count the number of repeated patient data entries with B tree.

    PubMed

    Okada, M; Okada, M

    1985-04-01

    An algorithm to obtain the number of different values that appear a specified number of times in a given data field of a given data file is presented. Basically, a well-known B-tree structure is employed in this study. Some modifications were made to the basic B-tree algorithm. The first step of the modifications is to allow a data item whose values are not necessary distinct from one record to another to be used as a primary key. When a key value is inserted, the number of previous appearances is counted. At the end of all the insertions, the number of key values which are unique in the tree, the number of key values which appear twice, three times, and so forth are obtained. This algorithm is especially powerful for a large size file in disk storage.

  20. Wavelet tree structure based speckle noise removal for optical coherence tomography

    NASA Astrophysics Data System (ADS)

    Yuan, Xin; Liu, Xuan; Liu, Yang

    2018-02-01

    We report a new speckle noise removal algorithm in optical coherence tomography (OCT). Though wavelet domain thresholding algorithms have demonstrated superior advantages in suppressing noise magnitude and preserving image sharpness in OCT, the wavelet tree structure has not been investigated in previous applications. In this work, we propose an adaptive wavelet thresholding algorithm via exploiting the tree structure in wavelet coefficients to remove the speckle noise in OCT images. The threshold for each wavelet band is adaptively selected following a special rule to retain the structure of the image across different wavelet layers. Our results demonstrate that the proposed algorithm outperforms conventional wavelet thresholding, with significant advantages in preserving image features.

  1. Using trees to compute approximate solutions to ordinary differential equations exactly

    NASA Technical Reports Server (NTRS)

    Grossman, Robert

    1991-01-01

    Some recent work is reviewed which relates families of trees to symbolic algorithms for the exact computation of series which approximate solutions of ordinary differential equations. It turns out that the vector space whose basis is the set of finite, rooted trees carries a natural multiplication related to the composition of differential operators, making the space of trees an algebra. This algebraic structure can be exploited to yield a variety of algorithms for manipulating vector fields and the series and algebras they generate.

  2. Functional grouping of similar genes using eigenanalysis on minimum spanning tree based neighborhood graph.

    PubMed

    Jothi, R; Mohanty, Sraban Kumar; Ojha, Aparajita

    2016-04-01

    Gene expression data clustering is an important biological process in DNA microarray analysis. Although there have been many clustering algorithms for gene expression analysis, finding a suitable and effective clustering algorithm is always a challenging problem due to the heterogeneous nature of gene profiles. Minimum Spanning Tree (MST) based clustering algorithms have been successfully employed to detect clusters of varying shapes and sizes. This paper proposes a novel clustering algorithm using Eigenanalysis on Minimum Spanning Tree based neighborhood graph (E-MST). As MST of a set of points reflects the similarity of the points with their neighborhood, the proposed algorithm employs a similarity graph obtained from k(') rounds of MST (k(')-MST neighborhood graph). By studying the spectral properties of the similarity matrix obtained from k(')-MST graph, the proposed algorithm achieves improved clustering results. We demonstrate the efficacy of the proposed algorithm on 12 gene expression datasets. Experimental results show that the proposed algorithm performs better than the standard clustering algorithms. Copyright © 2016 Elsevier Ltd. All rights reserved.

  3. Improved quantum backtracking algorithms using effective resistance estimates

    NASA Astrophysics Data System (ADS)

    Jarret, Michael; Wan, Kianna

    2018-02-01

    We investigate quantum backtracking algorithms of the type introduced by Montanaro (Montanaro, arXiv:1509.02374). These algorithms explore trees of unknown structure and in certain settings exponentially outperform their classical counterparts. Some of the previous work focused on obtaining a quantum advantage for trees in which a unique marked vertex is promised to exist. We remove this restriction by recharacterizing the problem in terms of the effective resistance of the search space. In this paper, we present a generalization of one of Montanaro's algorithms to trees containing k marked vertices, where k is not necessarily known a priori. Our approach involves using amplitude estimation to determine a near-optimal weighting of a diffusion operator, which can then be applied to prepare a superposition state with support only on marked vertices and ancestors thereof. By repeatedly sampling this state and updating the input vertex, a marked vertex is reached in a logarithmic number of steps. The algorithm thereby achieves the conjectured bound of O ˜(√{T Rmax }) for finding a single marked vertex and O ˜(k √{T Rmax }) for finding all k marked vertices, where T is an upper bound on the tree size and Rmax is the maximum effective resistance encountered by the algorithm. This constitutes a speedup over Montanaro's original procedure in both the case of finding one and the case of finding multiple marked vertices in an arbitrary tree.

  4. Uncertain decision tree inductive inference

    NASA Astrophysics Data System (ADS)

    Zarban, L.; Jafari, S.; Fakhrahmad, S. M.

    2011-10-01

    Induction is the process of reasoning in which general rules are formulated based on limited observations of recurring phenomenal patterns. Decision tree learning is one of the most widely used and practical inductive methods, which represents the results in a tree scheme. Various decision tree algorithms have already been proposed such as CLS, ID3, Assistant C4.5, REPTree and Random Tree. These algorithms suffer from some major shortcomings. In this article, after discussing the main limitations of the existing methods, we introduce a new decision tree induction algorithm, which overcomes all the problems existing in its counterparts. The new method uses bit strings and maintains important information on them. This use of bit strings and logical operation on them causes high speed during the induction process. Therefore, it has several important features: it deals with inconsistencies in data, avoids overfitting and handles uncertainty. We also illustrate more advantages and the new features of the proposed method. The experimental results show the effectiveness of the method in comparison with other methods existing in the literature.

  5. Hierarchical Learning of Tree Classifiers for Large-Scale Plant Species Identification.

    PubMed

    Fan, Jianping; Zhou, Ning; Peng, Jinye; Gao, Ling

    2015-11-01

    In this paper, a hierarchical multi-task structural learning algorithm is developed to support large-scale plant species identification, where a visual tree is constructed for organizing large numbers of plant species in a coarse-to-fine fashion and determining the inter-related learning tasks automatically. For a given parent node on the visual tree, it contains a set of sibling coarse-grained categories of plant species or sibling fine-grained plant species, and a multi-task structural learning algorithm is developed to train their inter-related classifiers jointly for enhancing their discrimination power. The inter-level relationship constraint, e.g., a plant image must first be assigned to a parent node (high-level non-leaf node) correctly if it can further be assigned to the most relevant child node (low-level non-leaf node or leaf node) on the visual tree, is formally defined and leveraged to learn more discriminative tree classifiers over the visual tree. Our experimental results have demonstrated the effectiveness of our hierarchical multi-task structural learning algorithm on training more discriminative tree classifiers for large-scale plant species identification.

  6. A fast bottom-up algorithm for computing the cut sets of noncoherent fault trees

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

    Corynen, G.C.

    1987-11-01

    An efficient procedure for finding the cut sets of large fault trees has been developed. Designed to address coherent or noncoherent systems, dependent events, shared or common-cause events, the method - called SHORTCUT - is based on a fast algorithm for transforming a noncoherent tree into a quasi-coherent tree (COHERE), and on a new algorithm for reducing cut sets (SUBSET). To assure sufficient clarity and precision, the procedure is discussed in the language of simple sets, which is also developed in this report. Although the new method has not yet been fully implemented on the computer, we report theoretical worst-casemore » estimates of its computational complexity. 12 refs., 10 figs.« less

  7. Learning Extended Finite State Machines

    NASA Technical Reports Server (NTRS)

    Cassel, Sofia; Howar, Falk; Jonsson, Bengt; Steffen, Bernhard

    2014-01-01

    We present an active learning algorithm for inferring extended finite state machines (EFSM)s, combining data flow and control behavior. Key to our learning technique is a novel learning model based on so-called tree queries. The learning algorithm uses the tree queries to infer symbolic data constraints on parameters, e.g., sequence numbers, time stamps, identifiers, or even simple arithmetic. We describe sufficient conditions for the properties that the symbolic constraints provided by a tree query in general must have to be usable in our learning model. We have evaluated our algorithm in a black-box scenario, where tree queries are realized through (black-box) testing. Our case studies include connection establishment in TCP and a priority queue from the Java Class Library.

  8. RS-Forest: A Rapid Density Estimator for Streaming Anomaly Detection.

    PubMed

    Wu, Ke; Zhang, Kun; Fan, Wei; Edwards, Andrea; Yu, Philip S

    Anomaly detection in streaming data is of high interest in numerous application domains. In this paper, we propose a novel one-class semi-supervised algorithm to detect anomalies in streaming data. Underlying the algorithm is a fast and accurate density estimator implemented by multiple fully randomized space trees (RS-Trees), named RS-Forest. The piecewise constant density estimate of each RS-tree is defined on the tree node into which an instance falls. Each incoming instance in a data stream is scored by the density estimates averaged over all trees in the forest. Two strategies, statistical attribute range estimation of high probability guarantee and dual node profiles for rapid model update, are seamlessly integrated into RS-Forest to systematically address the ever-evolving nature of data streams. We derive the theoretical upper bound for the proposed algorithm and analyze its asymptotic properties via bias-variance decomposition. Empirical comparisons to the state-of-the-art methods on multiple benchmark datasets demonstrate that the proposed method features high detection rate, fast response, and insensitivity to most of the parameter settings. Algorithm implementations and datasets are available upon request.

  9. RS-Forest: A Rapid Density Estimator for Streaming Anomaly Detection

    PubMed Central

    Wu, Ke; Zhang, Kun; Fan, Wei; Edwards, Andrea; Yu, Philip S.

    2015-01-01

    Anomaly detection in streaming data is of high interest in numerous application domains. In this paper, we propose a novel one-class semi-supervised algorithm to detect anomalies in streaming data. Underlying the algorithm is a fast and accurate density estimator implemented by multiple fully randomized space trees (RS-Trees), named RS-Forest. The piecewise constant density estimate of each RS-tree is defined on the tree node into which an instance falls. Each incoming instance in a data stream is scored by the density estimates averaged over all trees in the forest. Two strategies, statistical attribute range estimation of high probability guarantee and dual node profiles for rapid model update, are seamlessly integrated into RS-Forest to systematically address the ever-evolving nature of data streams. We derive the theoretical upper bound for the proposed algorithm and analyze its asymptotic properties via bias-variance decomposition. Empirical comparisons to the state-of-the-art methods on multiple benchmark datasets demonstrate that the proposed method features high detection rate, fast response, and insensitivity to most of the parameter settings. Algorithm implementations and datasets are available upon request. PMID:25685112

  10. GRAPE-6A: A Single-Card GRAPE-6 for Parallel PC-GRAPE Cluster Systems

    NASA Astrophysics Data System (ADS)

    Fukushige, Toshiyuki; Makino, Junichiro; Kawai, Atsushi

    2005-12-01

    In this paper, we describe the design and performance of GRAPE-6A, a special-purpose computer for gravitational many-body simulations. It was designed to be used with a PC cluster, in which each node has one GRAPE-6A. Such a configuration is particularly cost-effective in running parallel tree algorithms. Though the use of parallel tree algorithms was possible with the original GRAPE-6 hardware, it was not very cost-effective since a single GRAPE-6 board was still too fast and too expensive. Therefore, we designed GRAPE-6A as a single PCI card to minimize the reproduction cost and to optimize the computing speed. The peak performance is 130 Gflops for one GRAPE-6A board and 3.1 Tflops for our 24 node cluster. We describe the implementation of the tree, TreePM and individual timestep algorithms on both a single GRAPE-6A system and GRAPE-6A cluster. Using the tree algorithm on our 16-node GRAPE-6A system, we can complete a collisionless simulation with 100 million particles (8000 steps) within 10 days.

  11. An Extension of CART's Pruning Algorithm. Program Statistics Research Technical Report No. 91-11.

    ERIC Educational Resources Information Center

    Kim, Sung-Ho

    Among the computer-based methods used for the construction of trees such as AID, THAID, CART, and FACT, the only one that uses an algorithm that first grows a tree and then prunes the tree is CART. The pruning component of CART is analogous in spirit to the backward elimination approach in regression analysis. This idea provides a tool in…

  12. Automatic creation of object hierarchies for ray tracing

    NASA Technical Reports Server (NTRS)

    Goldsmith, Jeffrey; Salmon, John

    1987-01-01

    Various methods for evaluating generated trees are proposed. The use of the hierarchical extent method of Rubin and Whitted (1980) to find the objects that will be hit by a ray is examined. This method employs tree searching; the construction of a tree of bounding volumes in order to determine the number of objects that will be hit by a ray is discussed. A tree generation algorithm, which uses a heuristic tree search strategy, is described. The effects of shuffling and sorting on the input data are investigated. The cost of inserting an object into the hierarchy during the construction of a tree algorithm is estimated. The steps involved in estimating the number of intersection calculations are presented.

  13. Integrated Network Decompositions and Dynamic Programming for Graph Optimization (INDDGO)

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

    The INDDGO software package offers a set of tools for finding exact solutions to graph optimization problems via tree decompositions and dynamic programming algorithms. Currently the framework offers serial and parallel (distributed memory) algorithms for finding tree decompositions and solving the maximum weighted independent set problem. The parallel dynamic programming algorithm is implemented on top of the MADNESS task-based runtime.

  14. Learning accurate very fast decision trees from uncertain data streams

    NASA Astrophysics Data System (ADS)

    Liang, Chunquan; Zhang, Yang; Shi, Peng; Hu, Zhengguo

    2015-12-01

    Most existing works on data stream classification assume the streaming data is precise and definite. Such assumption, however, does not always hold in practice, since data uncertainty is ubiquitous in data stream applications due to imprecise measurement, missing values, privacy protection, etc. The goal of this paper is to learn accurate decision tree models from uncertain data streams for classification analysis. On the basis of very fast decision tree (VFDT) algorithms, we proposed an algorithm for constructing an uncertain VFDT tree with classifiers at tree leaves (uVFDTc). The uVFDTc algorithm can exploit uncertain information effectively and efficiently in both the learning and the classification phases. In the learning phase, it uses Hoeffding bound theory to learn from uncertain data streams and yield fast and reasonable decision trees. In the classification phase, at tree leaves it uses uncertain naive Bayes (UNB) classifiers to improve the classification performance. Experimental results on both synthetic and real-life datasets demonstrate the strong ability of uVFDTc to classify uncertain data streams. The use of UNB at tree leaves has improved the performance of uVFDTc, especially the any-time property, the benefit of exploiting uncertain information, and the robustness against uncertainty.

  15. An Improved Binary Differential Evolution Algorithm to Infer Tumor Phylogenetic Trees.

    PubMed

    Liang, Ying; Liao, Bo; Zhu, Wen

    2017-01-01

    Tumourigenesis is a mutation accumulation process, which is likely to start with a mutated founder cell. The evolutionary nature of tumor development makes phylogenetic models suitable for inferring tumor evolution through genetic variation data. Copy number variation (CNV) is the major genetic marker of the genome with more genes, disease loci, and functional elements involved. Fluorescence in situ hybridization (FISH) accurately measures multiple gene copy number of hundreds of single cells. We propose an improved binary differential evolution algorithm, BDEP, to infer tumor phylogenetic tree based on FISH platform. The topology analysis of tumor progression tree shows that the pathway of tumor subcell expansion varies greatly during different stages of tumor formation. And the classification experiment shows that tree-based features are better than data-based features in distinguishing tumor. The constructed phylogenetic trees have great performance in characterizing tumor development process, which outperforms other similar algorithms.

  16. Enumeration of spanning trees in planar unclustered networks

    NASA Astrophysics Data System (ADS)

    Xiao, Yuzhi; Zhao, Haixing; Hu, Guona; Ma, Xiujuan

    2014-07-01

    Among a variety of subgraphs, spanning trees are one of the most important and fundamental categories. They are relevant to diverse aspects of networks, including reliability, transport, self-organized criticality, loop-erased random walks and so on. In this paper, we introduce a family of modular, self-similar planar networks with zero clustering. Relevant properties of this family are comparable to those networks associated with technological systems having low clustering, like power grids, some electronic circuits, the Internet and some biological systems. So, it is very significant to research on spanning trees of planar networks. However, for a large network, evaluating the relevant determinant is intractable. In this paper, we propose a fairly generic linear algorithm for counting the number of spanning trees of a planar network. Using the algorithm, we derive analytically the exact numbers of spanning trees in planar networks. Our result shows that the computational complexity is O(t) , which is better than that of the matrix tree theorem with O(m2t2) , where t is the number of steps and m is the girth of the planar network. We also obtain the entropy for the spanning trees of a given planar network. We find that the entropy of spanning trees in the studied network is small, which is in sharp contrast to the previous result for planar networks with the same average degree. We also determine an upper bound and a lower bound for the numbers of spanning trees in the family of planar networks by the algorithm. As another application of the algorithm, we give a formula for the number of spanning trees in an outerplanar network with small-world features.

  17. Implementation of Data Mining to Analyze Drug Cases Using C4.5 Decision Tree

    NASA Astrophysics Data System (ADS)

    Wahyuni, Sri

    2018-03-01

    Data mining was the process of finding useful information from a large set of databases. One of the existing techniques in data mining was classification. The method used was decision tree method and algorithm used was C4.5 algorithm. The decision tree method was a method that transformed a very large fact into a decision tree which was presenting the rules. Decision tree method was useful for exploring data, as well as finding a hidden relationship between a number of potential input variables with a target variable. The decision tree of the C4.5 algorithm was constructed with several stages including the selection of attributes as roots, created a branch for each value and divided the case into the branch. These stages would be repeated for each branch until all the cases on the branch had the same class. From the solution of the decision tree there would be some rules of a case. In this case the researcher classified the data of prisoners at Labuhan Deli prison to know the factors of detainees committing criminal acts of drugs. By applying this C4.5 algorithm, then the knowledge was obtained as information to minimize the criminal acts of drugs. From the findings of the research, it was found that the most influential factor of the detainee committed the criminal act of drugs was from the address variable.

  18. Live phylogeny with polytomies: Finding the most compact parsimonious trees.

    PubMed

    Papamichail, D; Huang, A; Kennedy, E; Ott, J-L; Miller, A; Papamichail, G

    2017-08-01

    Construction of phylogenetic trees has traditionally focused on binary trees where all species appear on leaves, a problem for which numerous efficient solutions have been developed. Certain application domains though, such as viral evolution and transmission, paleontology, linguistics, and phylogenetic stemmatics, often require phylogeny inference that involves placing input species on ancestral tree nodes (live phylogeny), and polytomies. These requirements, despite their prevalence, lead to computationally harder algorithmic solutions and have been sparsely examined in the literature to date. In this article we prove some unique properties of most parsimonious live phylogenetic trees with polytomies, and their mapping to traditional binary phylogenetic trees. We show that our problem reduces to finding the most compact parsimonious tree for n species, and describe a novel efficient algorithm to find such trees without resorting to exhaustive enumeration of all possible tree topologies. Copyright © 2017 Elsevier Ltd. All rights reserved.

  19. Blooming Trees: Substructures and Surrounding Groups of Galaxy Clusters

    NASA Astrophysics Data System (ADS)

    Yu, Heng; Diaferio, Antonaldo; Serra, Ana Laura; Baldi, Marco

    2018-06-01

    We develop the Blooming Tree Algorithm, a new technique that uses spectroscopic redshift data alone to identify the substructures and the surrounding groups of galaxy clusters, along with their member galaxies. Based on the estimated binding energy of galaxy pairs, the algorithm builds a binary tree that hierarchically arranges all of the galaxies in the field of view. The algorithm searches for buds, corresponding to gravitational potential minima on the binary tree branches; for each bud, the algorithm combines the number of galaxies, their velocity dispersion, and their average pairwise distance into a parameter that discriminates between the buds that do not correspond to any substructure or group, and thus eventually die, and the buds that correspond to substructures and groups, and thus bloom into the identified structures. We test our new algorithm with a sample of 300 mock redshift surveys of clusters in different dynamical states; the clusters are extracted from a large cosmological N-body simulation of a ΛCDM model. We limit our analysis to substructures and surrounding groups identified in the simulation with mass larger than 1013 h ‑1 M ⊙. With mock redshift surveys with 200 galaxies within 6 h ‑1 Mpc from the cluster center, the technique recovers 80% of the real substructures and 60% of the surrounding groups; in 57% of the identified structures, at least 60% of the member galaxies of the substructures and groups belong to the same real structure. These results improve by roughly a factor of two the performance of the best substructure identification algorithm currently available, the σ plateau algorithm, and suggest that our Blooming Tree Algorithm can be an invaluable tool for detecting substructures of galaxy clusters and investigating their complex dynamics.

  20. Adversarial search by evolutionary computation.

    PubMed

    Hong, T P; Huang, K Y; Lin, W Y

    2001-01-01

    In this paper, we consider the problem of finding good next moves in two-player games. Traditional search algorithms, such as minimax and alpha-beta pruning, suffer great temporal and spatial expansion when exploring deeply into search trees to find better next moves. The evolution of genetic algorithms with the ability to find global or near global optima in limited time seems promising, but they are inept at finding compound optima, such as the minimax in a game-search tree. We thus propose a new genetic algorithm-based approach that can find a good next move by reserving the board evaluation values of new offspring in a partial game-search tree. Experiments show that solution accuracy and search speed are greatly improved by our algorithm.

  1. Using laser altimetry-based segmentation to refine automated tree identification in managed forests of the Black Hills, South Dakota

    Treesearch

    Eric Rowell; Carl Selelstad; Lee Vierling; Lloyd Queen; Wayne Sheppard

    2006-01-01

    The success of a local maximum (LM) tree detection algorithm for detecting individual trees from lidar data depends on stand conditions that are often highly variable. A laser height variance and percent canopy cover (PCC) classification is used to segment the landscape by stand condition prior to stem detection. We test the performance of the LM algorithm using canopy...

  2. 3D Forest: An application for descriptions of three-dimensional forest structures using terrestrial LiDAR

    PubMed Central

    Krůček, Martin; Vrška, Tomáš; Král, Kamil

    2017-01-01

    Terrestrial laser scanning is a powerful technology for capturing the three-dimensional structure of forests with a high level of detail and accuracy. Over the last decade, many algorithms have been developed to extract various tree parameters from terrestrial laser scanning data. Here we present 3D Forest, an open-source non-platform-specific software application with an easy-to-use graphical user interface with the compilation of algorithms focused on the forest environment and extraction of tree parameters. The current version (0.42) extracts important parameters of forest structure from the terrestrial laser scanning data, such as stem positions (X, Y, Z), tree heights, diameters at breast height (DBH), as well as more advanced parameters such as tree planar projections, stem profiles or detailed crown parameters including convex and concave crown surface and volume. Moreover, 3D Forest provides quantitative measures of between-crown interactions and their real arrangement in 3D space. 3D Forest also includes an original algorithm of automatic tree segmentation and crown segmentation. Comparison with field data measurements showed no significant difference in measuring DBH or tree height using 3D Forest, although for DBH only the Randomized Hough Transform algorithm proved to be sufficiently resistant to noise and provided results comparable to traditional field measurements. PMID:28472167

  3. EDNA: Expert fault digraph analysis using CLIPS

    NASA Technical Reports Server (NTRS)

    Dixit, Vishweshwar V.

    1990-01-01

    Traditionally fault models are represented by trees. Recently, digraph models have been proposed (Sack). Digraph models closely imitate the real system dependencies and hence are easy to develop, validate and maintain. However, they can also contain directed cycles and analysis algorithms are hard to find. Available algorithms tend to be complicated and slow. On the other hand, the tree analysis (VGRH, Tayl) is well understood and rooted in vast research effort and analytical techniques. The tree analysis algorithms are sophisticated and orders of magnitude faster. Transformation of a digraph (cyclic) into trees (CLP, LP) is a viable approach to blend the advantages of the representations. Neither the digraphs nor the trees provide the ability to handle heuristic knowledge. An expert system, to capture the engineering knowledge, is essential. We propose an approach here, namely, expert network analysis. We combine the digraph representation and tree algorithms. The models are augmented by probabilistic and heuristic knowledge. CLIPS, an expert system shell from NASA-JSC will be used to develop a tool. The technique provides the ability to handle probabilities and heuristic knowledge. Mixed analysis, some nodes with probabilities, is possible. The tool provides graphics interface for input, query, and update. With the combined approach it is expected to be a valuable tool in the design process as well in the capture of final design knowledge.

  4. Applying Data Mining Techniques to Extract Hidden Patterns about Breast Cancer Survival in an Iranian Cohort Study.

    PubMed

    Khalkhali, Hamid Reza; Lotfnezhad Afshar, Hadi; Esnaashari, Omid; Jabbari, Nasrollah

    2016-01-01

    Breast cancer survival has been analyzed by many standard data mining algorithms. A group of these algorithms belonged to the decision tree category. Ability of the decision tree algorithms in terms of visualizing and formulating of hidden patterns among study variables were main reasons to apply an algorithm from the decision tree category in the current study that has not studied already. The classification and regression trees (CART) was applied to a breast cancer database contained information on 569 patients in 2007-2010. The measurement of Gini impurity used for categorical target variables was utilized. The classification error that is a function of tree size was measured by 10-fold cross-validation experiments. The performance of created model was evaluated by the criteria as accuracy, sensitivity and specificity. The CART model produced a decision tree with 17 nodes, 9 of which were associated with a set of rules. The rules were meaningful clinically. They showed in the if-then format that Stage was the most important variable for predicting breast cancer survival. The scores of accuracy, sensitivity and specificity were: 80.3%, 93.5% and 53%, respectively. The current study model as the first one created by the CART was able to extract useful hidden rules from a relatively small size dataset.

  5. Creating ensembles of oblique decision trees with evolutionary algorithms and sampling

    DOEpatents

    Cantu-Paz, Erick [Oakland, CA; Kamath, Chandrika [Tracy, CA

    2006-06-13

    A decision tree system that is part of a parallel object-oriented pattern recognition system, which in turn is part of an object oriented data mining system. A decision tree process includes the step of reading the data. If necessary, the data is sorted. A potential split of the data is evaluated according to some criterion. An initial split of the data is determined. The final split of the data is determined using evolutionary algorithms and statistical sampling techniques. The data is split. Multiple decision trees are combined in ensembles.

  6. Traveling front solutions to directed diffusion-limited aggregation, digital search trees, and the Lempel-Ziv data compression algorithm.

    PubMed

    Majumdar, Satya N

    2003-08-01

    We use the traveling front approach to derive exact asymptotic results for the statistics of the number of particles in a class of directed diffusion-limited aggregation models on a Cayley tree. We point out that some aspects of these models are closely connected to two different problems in computer science, namely, the digital search tree problem in data structures and the Lempel-Ziv algorithm for data compression. The statistics of the number of particles studied here is related to the statistics of height in digital search trees which, in turn, is related to the statistics of the length of the longest word formed by the Lempel-Ziv algorithm. Implications of our results to these computer science problems are pointed out.

  7. Traveling front solutions to directed diffusion-limited aggregation, digital search trees, and the Lempel-Ziv data compression algorithm

    NASA Astrophysics Data System (ADS)

    Majumdar, Satya N.

    2003-08-01

    We use the traveling front approach to derive exact asymptotic results for the statistics of the number of particles in a class of directed diffusion-limited aggregation models on a Cayley tree. We point out that some aspects of these models are closely connected to two different problems in computer science, namely, the digital search tree problem in data structures and the Lempel-Ziv algorithm for data compression. The statistics of the number of particles studied here is related to the statistics of height in digital search trees which, in turn, is related to the statistics of the length of the longest word formed by the Lempel-Ziv algorithm. Implications of our results to these computer science problems are pointed out.

  8. A Semi-Automated Machine Learning Algorithm for Tree Cover Delineation from 1-m Naip Imagery Using a High Performance Computing Architecture

    NASA Astrophysics Data System (ADS)

    Basu, S.; Ganguly, S.; Nemani, R. R.; Mukhopadhyay, S.; Milesi, C.; Votava, P.; Michaelis, A.; Zhang, G.; Cook, B. D.; Saatchi, S. S.; Boyda, E.

    2014-12-01

    Accurate tree cover delineation is a useful instrument in the derivation of Above Ground Biomass (AGB) density estimates from Very High Resolution (VHR) satellite imagery data. Numerous algorithms have been designed to perform tree cover delineation in high to coarse resolution satellite imagery, but most of them do not scale to terabytes of data, typical in these VHR datasets. In this paper, we present an automated probabilistic framework for the segmentation and classification of 1-m VHR data as obtained from the National Agriculture Imagery Program (NAIP) for deriving tree cover estimates for the whole of Continental United States, using a High Performance Computing Architecture. The results from the classification and segmentation algorithms are then consolidated into a structured prediction framework using a discriminative undirected probabilistic graphical model based on Conditional Random Field (CRF), which helps in capturing the higher order contextual dependencies between neighboring pixels. Once the final probability maps are generated, the framework is updated and re-trained by incorporating expert knowledge through the relabeling of misclassified image patches. This leads to a significant improvement in the true positive rates and reduction in false positive rates. The tree cover maps were generated for the state of California, which covers a total of 11,095 NAIP tiles and spans a total geographical area of 163,696 sq. miles. Our framework produced correct detection rates of around 85% for fragmented forests and 70% for urban tree cover areas, with false positive rates lower than 3% for both regions. Comparative studies with the National Land Cover Data (NLCD) algorithm and the LiDAR high-resolution canopy height model shows the effectiveness of our algorithm in generating accurate high-resolution tree cover maps.

  9. A New Algorithm Using the Non-Dominated Tree to Improve Non-Dominated Sorting.

    PubMed

    Gustavsson, Patrik; Syberfeldt, Anna

    2018-01-01

    Non-dominated sorting is a technique often used in evolutionary algorithms to determine the quality of solutions in a population. The most common algorithm is the Fast Non-dominated Sort (FNS). This algorithm, however, has the drawback that its performance deteriorates when the population size grows. The same drawback applies also to other non-dominating sorting algorithms such as the Efficient Non-dominated Sort with Binary Strategy (ENS-BS). An algorithm suggested to overcome this drawback is the Divide-and-Conquer Non-dominated Sort (DCNS) which works well on a limited number of objectives but deteriorates when the number of objectives grows. This article presents a new, more efficient algorithm called the Efficient Non-dominated Sort with Non-Dominated Tree (ENS-NDT). ENS-NDT is an extension of the ENS-BS algorithm and uses a novel Non-Dominated Tree (NDTree) to speed up the non-dominated sorting. ENS-NDT is able to handle large population sizes and a large number of objectives more efficiently than existing algorithms for non-dominated sorting. In the article, it is shown that with ENS-NDT the runtime of multi-objective optimization algorithms such as the Non-Dominated Sorting Genetic Algorithm II (NSGA-II) can be substantially reduced.

  10. New Hybrid Algorithms for Estimating Tree Stem Diameters at Breast Height Using a Two Dimensional Terrestrial Laser Scanner

    PubMed Central

    Kong, Jianlei; Ding, Xiaokang; Liu, Jinhao; Yan, Lei; Wang, Jianli

    2015-01-01

    In this paper, a new algorithm to improve the accuracy of estimating diameter at breast height (DBH) for tree trunks in forest areas is proposed. First, the information is collected by a two-dimensional terrestrial laser scanner (2DTLS), which emits laser pulses to generate a point cloud. After extraction and filtration, the laser point clusters of the trunks are obtained, which are optimized by an arithmetic means method. Then, an algebraic circle fitting algorithm in polar form is non-linearly optimized by the Levenberg-Marquardt method to form a new hybrid algorithm, which is used to acquire the diameters and positions of the trees. Compared with previous works, this proposed method improves the accuracy of diameter estimation of trees significantly and effectively reduces the calculation time. Moreover, the experimental results indicate that this method is stable and suitable for the most challenging conditions, which has practical significance in improving the operating efficiency of forest harvester and reducing the risk of causing accidents. PMID:26147726

  11. Efficient Delaunay Tessellation through K-D Tree Decomposition

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

    Morozov, Dmitriy; Peterka, Tom

    Delaunay tessellations are fundamental data structures in computational geometry. They are important in data analysis, where they can represent the geometry of a point set or approximate its density. The algorithms for computing these tessellations at scale perform poorly when the input data is unbalanced. We investigate the use of k-d trees to evenly distribute points among processes and compare two strategies for picking split points between domain regions. Because resulting point distributions no longer satisfy the assumptions of existing parallel Delaunay algorithms, we develop a new parallel algorithm that adapts to its input and prove its correctness. We evaluatemore » the new algorithm using two late-stage cosmology datasets. The new running times are up to 50 times faster using k-d tree compared with regular grid decomposition. Moreover, in the unbalanced data sets, decomposing the domain into a k-d tree is up to five times faster than decomposing it into a regular grid.« less

  12. Recursive optimal pruning with applications to tree structured vector quantizers

    NASA Technical Reports Server (NTRS)

    Kiang, Shei-Zein; Baker, Richard L.; Sullivan, Gary J.; Chiu, Chung-Yen

    1992-01-01

    A pruning algorithm of Chou et al. (1989) for designing optimal tree structures identifies only those codebooks which lie on the convex hull of the original codebook's operational distortion rate function. The authors introduce a modified version of the original algorithm, which identifies a large number of codebooks having minimum average distortion, under the constraint that, in each step, only modes having no descendents are removed from the tree. All codebooks generated by the original algorithm are also generated by this algorithm. The new algorithm generates a much larger number of codebooks in the middle- and low-rate regions. The additional codebooks permit operation near the codebook's operational distortion rate function without time sharing by choosing from the increased number of available bit rates. Despite the statistical mismatch which occurs when coding data outside the training sequence, these pruned codebooks retain their performance advantage over full search vector quantizers (VQs) for a large range of rates.

  13. A faster 1.375-approximation algorithm for sorting by transpositions.

    PubMed

    Cunha, Luís Felipe I; Kowada, Luis Antonio B; Hausen, Rodrigo de A; de Figueiredo, Celina M H

    2015-11-01

    Sorting by Transpositions is an NP-hard problem for which several polynomial-time approximation algorithms have been developed. Hartman and Shamir (2006) developed a 1.5-approximation [Formula: see text] algorithm, whose running time was improved to O(nlogn) by Feng and Zhu (2007) with a data structure they defined, the permutation tree. Elias and Hartman (2006) developed a 1.375-approximation O(n(2)) algorithm, and Firoz et al. (2011) claimed an improvement to the running time, from O(n(2)) to O(nlogn), by using the permutation tree. We provide counter-examples to the correctness of Firoz et al.'s strategy, showing that it is not possible to reach a component by sufficient extensions using the method proposed by them. In addition, we propose a 1.375-approximation algorithm, modifying Elias and Hartman's approach with the use of permutation trees and achieving O(nlogn) time.

  14. A de novo Mutation in KMT2A (MLL) in monozygotic twins with Wiedemann-Steiner syndrome.

    PubMed

    Dunkerton, Sophie; Field, Matthew; Cho, Vicki; Bertram, Edward; Whittle, Belinda; Groves, Alexandra; Goel, Himanshu

    2015-09-01

    Growth deficiency, psychomotor delay, and facial dysmorphism was originally described in a male patient in 1989 by Wiedemann et al. and later in 2000 by Steiner et al. Wiedemann-Steiner syndrome (WSS) has since been described only a few times in the literature, with the phenotypic spectrum both expanding and becoming more delineated with each patient reported. We report on the clinical and molecular features of monozygotic twins with a de novo mutation in KMT2A. Single nucleotide polymorphism (SNP) microarray was done on both twins and whole-exome sequencing was done using both parents and one of the affected twins. SNP microarray confirmed that they were monozygotic twins. A de novo heterozygous variant (p. Arg1083*) in the KMT2A gene was identified through whole-exome sequencing, confirming the diagnosis of WSS. In this study, we have identified a de novo mutation in KMT2A associated with psychomotor developmental delay, facial dysmorphism, short stature, hypertrichosis cubiti, and small kidneys. This finding in monozygotic twins gives specificity to the WSS. The description of more cases of WSS is needed for further delineation of this condition. Small kidneys with normal function have not been described in this condition in the medical literature before. © 2015 Wiley Periodicals, Inc.

  15. Application of the pessimistic pruning to increase the accuracy of C4.5 algorithm in diagnosing chronic kidney disease

    NASA Astrophysics Data System (ADS)

    Muslim, M. A.; Herowati, A. J.; Sugiharti, E.; Prasetiyo, B.

    2018-03-01

    A technique to dig valuable information buried or hidden in data collection which is so big to be found an interesting patterns that was previously unknown is called data mining. Data mining has been applied in the healthcare industry. One technique used data mining is classification. The decision tree included in the classification of data mining and algorithm developed by decision tree is C4.5 algorithm. A classifier is designed using applying pessimistic pruning in C4.5 algorithm in diagnosing chronic kidney disease. Pessimistic pruning use to identify and remove branches that are not needed, this is done to avoid overfitting the decision tree generated by the C4.5 algorithm. In this paper, the result obtained using these classifiers are presented and discussed. Using pessimistic pruning shows increase accuracy of C4.5 algorithm of 1.5% from 95% to 96.5% in diagnosing of chronic kidney disease.

  16. C-semiring Frameworks for Minimum Spanning Tree Problems

    NASA Astrophysics Data System (ADS)

    Bistarelli, Stefano; Santini, Francesco

    In this paper we define general algebraic frameworks for the Minimum Spanning Tree problem based on the structure of c-semirings. We propose general algorithms that can compute such trees by following different cost criteria, which must be all specific instantiation of c-semirings. Our algorithms are extensions of well-known procedures, as Prim or Kruskal, and show the expressivity of these algebraic structures. They can deal also with partially-ordered costs on the edges.

  17. Parallel peak pruning for scalable SMP contour tree computation

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

    Carr, Hamish A.; Weber, Gunther H.; Sewell, Christopher M.

    As data sets grow to exascale, automated data analysis and visualisation are increasingly important, to intermediate human understanding and to reduce demands on disk storage via in situ analysis. Trends in architecture of high performance computing systems necessitate analysis algorithms to make effective use of combinations of massively multicore and distributed systems. One of the principal analytic tools is the contour tree, which analyses relationships between contours to identify features of more than local importance. Unfortunately, the predominant algorithms for computing the contour tree are explicitly serial, and founded on serial metaphors, which has limited the scalability of this formmore » of analysis. While there is some work on distributed contour tree computation, and separately on hybrid GPU-CPU computation, there is no efficient algorithm with strong formal guarantees on performance allied with fast practical performance. Here in this paper, we report the first shared SMP algorithm for fully parallel contour tree computation, withfor-mal guarantees of O(lgnlgt) parallel steps and O(n lgn) work, and implementations with up to 10x parallel speed up in OpenMP and up to 50x speed up in NVIDIA Thrust.« less

  18. [Prediction of regional soil quality based on mutual information theory integrated with decision tree algorithm].

    PubMed

    Lin, Fen-Fang; Wang, Ke; Yang, Ning; Yan, Shi-Guang; Zheng, Xin-Yu

    2012-02-01

    In this paper, some main factors such as soil type, land use pattern, lithology type, topography, road, and industry type that affect soil quality were used to precisely obtain the spatial distribution characteristics of regional soil quality, mutual information theory was adopted to select the main environmental factors, and decision tree algorithm See 5.0 was applied to predict the grade of regional soil quality. The main factors affecting regional soil quality were soil type, land use, lithology type, distance to town, distance to water area, altitude, distance to road, and distance to industrial land. The prediction accuracy of the decision tree model with the variables selected by mutual information was obviously higher than that of the model with all variables, and, for the former model, whether of decision tree or of decision rule, its prediction accuracy was all higher than 80%. Based on the continuous and categorical data, the method of mutual information theory integrated with decision tree could not only reduce the number of input parameters for decision tree algorithm, but also predict and assess regional soil quality effectively.

  19. Heterogeneous Compression of Large Collections of Evolutionary Trees.

    PubMed

    Matthews, Suzanne J

    2015-01-01

    Compressing heterogeneous collections of trees is an open problem in computational phylogenetics. In a heterogeneous tree collection, each tree can contain a unique set of taxa. An ideal compression method would allow for the efficient archival of large tree collections and enable scientists to identify common evolutionary relationships over disparate analyses. In this paper, we extend TreeZip to compress heterogeneous collections of trees. TreeZip is the most efficient algorithm for compressing homogeneous tree collections. To the best of our knowledge, no other domain-based compression algorithm exists for large heterogeneous tree collections or enable their rapid analysis. Our experimental results indicate that TreeZip averages 89.03 percent (72.69 percent) space savings on unweighted (weighted) collections of trees when the level of heterogeneity in a collection is moderate. The organization of the TRZ file allows for efficient computations over heterogeneous data. For example, consensus trees can be computed in mere seconds. Lastly, combining the TreeZip compressed (TRZ) file with general-purpose compression yields average space savings of 97.34 percent (81.43 percent) on unweighted (weighted) collections of trees. Our results lead us to believe that TreeZip will prove invaluable in the efficient archival of tree collections, and enables scientists to develop novel methods for relating heterogeneous collections of trees.

  20. Exploiting the wavelet structure in compressed sensing MRI.

    PubMed

    Chen, Chen; Huang, Junzhou

    2014-12-01

    Sparsity has been widely utilized in magnetic resonance imaging (MRI) to reduce k-space sampling. According to structured sparsity theories, fewer measurements are required for tree sparse data than the data only with standard sparsity. Intuitively, more accurate image reconstruction can be achieved with the same number of measurements by exploiting the wavelet tree structure in MRI. A novel algorithm is proposed in this article to reconstruct MR images from undersampled k-space data. In contrast to conventional compressed sensing MRI (CS-MRI) that only relies on the sparsity of MR images in wavelet or gradient domain, we exploit the wavelet tree structure to improve CS-MRI. This tree-based CS-MRI problem is decomposed into three simpler subproblems then each of the subproblems can be efficiently solved by an iterative scheme. Simulations and in vivo experiments demonstrate the significant improvement of the proposed method compared to conventional CS-MRI algorithms, and the feasibleness on MR data compared to existing tree-based imaging algorithms. Copyright © 2014 Elsevier Inc. All rights reserved.

  1. Data mining for multiagent rules, strategies, and fuzzy decision tree structure

    NASA Astrophysics Data System (ADS)

    Smith, James F., III; Rhyne, Robert D., II; Fisher, Kristin

    2002-03-01

    A fuzzy logic based resource manager (RM) has been developed that automatically allocates electronic attack resources in real-time over many dissimilar platforms. Two different data mining algorithms have been developed to determine rules, strategies, and fuzzy decision tree structure. The first data mining algorithm uses a genetic algorithm as a data mining function and is called from an electronic game. The game allows a human expert to play against the resource manager in a simulated battlespace with each of the defending platforms being exclusively directed by the fuzzy resource manager and the attacking platforms being controlled by the human expert or operating autonomously under their own logic. This approach automates the data mining problem. The game automatically creates a database reflecting the domain expert's knowledge. It calls a data mining function, a genetic algorithm, for data mining of the database as required and allows easy evaluation of the information mined in the second step. The criterion for re- optimization is discussed as well as experimental results. Then a second data mining algorithm that uses a genetic program as a data mining function is introduced to automatically discover fuzzy decision tree structures. Finally, a fuzzy decision tree generated through this process is discussed.

  2. Determining Geometric Parameters of Agricultural Trees from Laser Scanning Data Obtained with Unmanned Aerial Vehicle

    NASA Astrophysics Data System (ADS)

    Hadas, E.; Jozkow, G.; Walicka, A.; Borkowski, A.

    2018-05-01

    The estimation of dendrometric parameters has become an important issue for agriculture planning and for the efficient management of orchards. Airborne Laser Scanning (ALS) data is widely used in forestry and many algorithms for automatic estimation of dendrometric parameters of individual forest trees were developed. Unfortunately, due to significant differences between forest and fruit trees, some contradictions exist against adopting the achievements of forestry science to agricultural studies indiscriminately. In this study we present the methodology to identify individual trees in apple orchard and estimate heights of individual trees, using high-density LiDAR data (3200 points/m2) obtained with Unmanned Aerial Vehicle (UAV) equipped with Velodyne HDL32-E sensor. The processing strategy combines the alpha-shape algorithm, principal component analysis (PCA) and detection of local minima. The alpha-shape algorithm is used to separate tree rows. In order to separate trees in a single row, we detect local minima on the canopy profile and slice polygons from alpha-shape results. We successfully separated 92 % of trees in the test area. 6 % of trees in orchard were not separated from each other and 2 % were sliced into two polygons. The RMSE of tree heights determined from the point clouds compared to field measurements was equal to 0.09 m, and the correlation coefficient was equal to 0.96. The results confirm the usefulness of LiDAR data from UAV platform in orchard inventory.

  3. The just provision of health care: a reply to Elizabeth Telfer.

    PubMed Central

    Steiner, H

    1976-01-01

    Dr Hillel Steiner in this reply to Elizabeth Telfer takes each of her arguments for different arrangements of a health service and examines them--'four positions which can be located on a linear ideological spectrum'--and adds a fifth which could have the effect of 'turning the alleged linear spectrum into a circle'. Underlying both Elizabeth Telfer's article and Dr Steiner's reply, the base is inescapably a 'political' one, but cannot be abandoned in favour of purely philosophical concepts. Whatever the attitude of mind of the reader of these two papers to the provision of a health service, the stimulus to more careful assessments of our own National Health Service and its problems can only be good. PMID:1003436

  4. Roy-Steiner-equation analysis of pion-nucleon scattering

    NASA Astrophysics Data System (ADS)

    Meißner, U.-G.; Ruiz de Elvira, J.; Hoferichter, M.; Kubis, B.

    2017-03-01

    Low-energy pion-nucleon scattering is relevant for many areas in nuclear and hadronic physics, ranging from the scalar couplings of the nucleon to the long-range part of two-pion-exchange potentials and three-nucleon forces in Chiral Effective Field Theory. In this talk, we show how the fruitful combination of dispersion-theoretical methods, in particular in the form of Roy-Steiner equations, with modern high-precision data on hadronic atoms allows one to determine the pion-nucleon scattering amplitudes at low energies with unprecedented accuracy. Special attention will be paid to the extraction of the pion-nucleon σ-term, and we discuss in detail the current tension with recent lattice results, as well as the determination of the low-energy constants of chiral perturbation theory.

  5. Pion-nucleon scattering: from chiral perturbation theory to Roy-Steiner equations

    NASA Astrophysics Data System (ADS)

    Kubis, Bastian; Hoferichter, Martin; de Elvira, Jacobo Ruiz; Meißner, Ulf-G.

    2016-11-01

    Ever since Weinberg's seminal predictions of the pion-nucleon scattering amplitudes at threshold, this process has been of central interest for the study of chiral dynamics involving nucleons. The scattering lengths or the pion-nucleon σ-term are fundamental quantities characterizing the explicit breaking of chiral symmetry by means of the light quark masses. On the other hand, pion-nucleon dynamics also strongly affects the long-range part of nucleon-nucleon potentials, and hence has a far-reaching impact on nuclear physics. We discuss the fruitful combination of dispersion-theoretical methods, in the form of Roy-Steiner equations, with chiral dynamics to determine pion-nucleon scattering amplitudes at low energies with high precision.*

  6. Method for estimating potential tree-grade distributions for northeastern forest species

    Treesearch

    Daniel A. Yaussy; Daniel A. Yaussy

    1993-01-01

    Generalized logistic regression was used to distribute trees into four potential tree grades for 20 northeastern species groups. The potential tree grade is defined as the tree grade based on the length and amount of clear cuttings and defects only, disregarding minimum grading diameter. The algorithms described use site index and tree diameter as the predictive...

  7. Integrated Approach To Design And Analysis Of Systems

    NASA Technical Reports Server (NTRS)

    Patterson-Hine, F. A.; Iverson, David L.

    1993-01-01

    Object-oriented fault-tree representation unifies evaluation of reliability and diagnosis of faults. Programming/fault tree described more fully in "Object-Oriented Algorithm For Evaluation Of Fault Trees" (ARC-12731). Augmented fault tree object contains more information than fault tree object used in quantitative analysis of reliability. Additional information needed to diagnose faults in system represented by fault tree.

  8. MDTS: automatic complex materials design using Monte Carlo tree search.

    PubMed

    M Dieb, Thaer; Ju, Shenghong; Yoshizoe, Kazuki; Hou, Zhufeng; Shiomi, Junichiro; Tsuda, Koji

    2017-01-01

    Complex materials design is often represented as a black-box combinatorial optimization problem. In this paper, we present a novel python library called MDTS (Materials Design using Tree Search). Our algorithm employs a Monte Carlo tree search approach, which has shown exceptional performance in computer Go game. Unlike evolutionary algorithms that require user intervention to set parameters appropriately, MDTS has no tuning parameters and works autonomously in various problems. In comparison to a Bayesian optimization package, our algorithm showed competitive search efficiency and superior scalability. We succeeded in designing large Silicon-Germanium (Si-Ge) alloy structures that Bayesian optimization could not deal with due to excessive computational cost. MDTS is available at https://github.com/tsudalab/MDTS.

  9. MDTS: automatic complex materials design using Monte Carlo tree search

    NASA Astrophysics Data System (ADS)

    Dieb, Thaer M.; Ju, Shenghong; Yoshizoe, Kazuki; Hou, Zhufeng; Shiomi, Junichiro; Tsuda, Koji

    2017-12-01

    Complex materials design is often represented as a black-box combinatorial optimization problem. In this paper, we present a novel python library called MDTS (Materials Design using Tree Search). Our algorithm employs a Monte Carlo tree search approach, which has shown exceptional performance in computer Go game. Unlike evolutionary algorithms that require user intervention to set parameters appropriately, MDTS has no tuning parameters and works autonomously in various problems. In comparison to a Bayesian optimization package, our algorithm showed competitive search efficiency and superior scalability. We succeeded in designing large Silicon-Germanium (Si-Ge) alloy structures that Bayesian optimization could not deal with due to excessive computational cost. MDTS is available at https://github.com/tsudalab/MDTS.

  10. Comment on 'Modeling of Convective-Stratiform Precipitation Processes: Sensitivity to Partitioning Methods' by Matthias Steiner

    NASA Technical Reports Server (NTRS)

    Lang, Steve; Tao, W.-K.; Simpson, J.; Ferrier, B.

    2003-01-01

    Despite the obvious notion that the presence of hail or graupel is a good indication of convection, the model results show this does not provide an objective benchmark partly due to the unrealistic presence of small amounts of hail or graupel throughout the anvil in the model but mainly because of the significant amounts of hail or graupel, especially in the tropical TOGA COARE simulation, in the transition zone. Without use of a "transition" category, it is open to debate as how this region should best be defined, as stratiform or as convective. So, the presence of significant hail or graupel contents in this zone significantly degrades its use an objective benchmark for convection. The separation algorithm comparison was done in the context of a cloud-resolving model. These models are widely used and serve a variety of purposes especially with regard to retrieving information that cannot be directly measured by providing synthetic data sets that are consistent and complete. Separation algorithms are regularly applied in these models. However, as with any modeling system, these types 'of models are constantly being improved to overcome any known deficiencies and make them more accurate representations of observed systems. The presence of hail and graupel in the anvil and the bias towards heavy rainfall rates are two such examples of areas that need improvement. Since, both of these can effect the perceived performance of the separation algorithms, the Lang et al. (2003) study did not want to overstate the relative performance of any specific algorithms.

  11. A fast algorithm for identifying friends-of-friends halos

    NASA Astrophysics Data System (ADS)

    Feng, Y.; Modi, C.

    2017-07-01

    We describe a simple and fast algorithm for identifying friends-of-friends features and prove its correctness. The algorithm avoids unnecessary expensive neighbor queries, uses minimal memory overhead, and rejects slowdown in high over-density regions. We define our algorithm formally based on pair enumeration, a problem that has been heavily studied in fast 2-point correlation codes and our reference implementation employs a dual KD-tree correlation function code. We construct features in a hierarchical tree structure, and use a splay operation to reduce the average cost of identifying the root of a feature from O [ log L ] to O [ 1 ] (L is the size of a feature) without additional memory costs. This reduces the overall time complexity of merging trees from O [ L log L ] to O [ L ] , reducing the number of operations per splay by orders of magnitude. We next introduce a pruning operation that skips merge operations between two fully self-connected KD-tree nodes. This improves the robustness of the algorithm, reducing the number of merge operations in high density peaks from O [δ2 ] to O [ δ ] . We show that for cosmological data set the algorithm eliminates more than half of merge operations for typically used linking lengths b ∼ 0 . 2 (relative to mean separation). Furthermore, our algorithm is extremely simple and easy to implement on top of an existing pair enumeration code, reusing the optimization effort that has been invested in fast correlation function codes.

  12. Tree-based solvers for adaptive mesh refinement code FLASH - I: gravity and optical depths

    NASA Astrophysics Data System (ADS)

    Wünsch, R.; Walch, S.; Dinnbier, F.; Whitworth, A.

    2018-04-01

    We describe an OctTree algorithm for the MPI parallel, adaptive mesh refinement code FLASH, which can be used to calculate the gas self-gravity, and also the angle-averaged local optical depth, for treating ambient diffuse radiation. The algorithm communicates to the different processors only those parts of the tree that are needed to perform the tree-walk locally. The advantage of this approach is a relatively low memory requirement, important in particular for the optical depth calculation, which needs to process information from many different directions. This feature also enables a general tree-based radiation transport algorithm that will be described in a subsequent paper, and delivers excellent scaling up to at least 1500 cores. Boundary conditions for gravity can be either isolated or periodic, and they can be specified in each direction independently, using a newly developed generalization of the Ewald method. The gravity calculation can be accelerated with the adaptive block update technique by partially re-using the solution from the previous time-step. Comparison with the FLASH internal multigrid gravity solver shows that tree-based methods provide a competitive alternative, particularly for problems with isolated or mixed boundary conditions. We evaluate several multipole acceptance criteria (MACs) and identify a relatively simple approximate partial error MAC which provides high accuracy at low computational cost. The optical depth estimates are found to agree very well with those of the RADMC-3D radiation transport code, with the tree-solver being much faster. Our algorithm is available in the standard release of the FLASH code in version 4.0 and later.

  13. Polynomial algorithms for the Maximal Pairing Problem: efficient phylogenetic targeting on arbitrary trees

    PubMed Central

    2010-01-01

    Background The Maximal Pairing Problem (MPP) is the prototype of a class of combinatorial optimization problems that are of considerable interest in bioinformatics: Given an arbitrary phylogenetic tree T and weights ωxy for the paths between any two pairs of leaves (x, y), what is the collection of edge-disjoint paths between pairs of leaves that maximizes the total weight? Special cases of the MPP for binary trees and equal weights have been described previously; algorithms to solve the general MPP are still missing, however. Results We describe a relatively simple dynamic programming algorithm for the special case of binary trees. We then show that the general case of multifurcating trees can be treated by interleaving solutions to certain auxiliary Maximum Weighted Matching problems with an extension of this dynamic programming approach, resulting in an overall polynomial-time solution of complexity (n4 log n) w.r.t. the number n of leaves. The source code of a C implementation can be obtained under the GNU Public License from http://www.bioinf.uni-leipzig.de/Software/Targeting. For binary trees, we furthermore discuss several constrained variants of the MPP as well as a partition function approach to the probabilistic version of the MPP. Conclusions The algorithms introduced here make it possible to solve the MPP also for large trees with high-degree vertices. This has practical relevance in the field of comparative phylogenetics and, for example, in the context of phylogenetic targeting, i.e., data collection with resource limitations. PMID:20525185

  14. OCTGRAV: Sparse Octree Gravitational N-body Code on Graphics Processing Units

    NASA Astrophysics Data System (ADS)

    Gaburov, Evghenii; Bédorf, Jeroen; Portegies Zwart, Simon

    2010-10-01

    Octgrav is a very fast tree-code which runs on massively parallel Graphical Processing Units (GPU) with NVIDIA CUDA architecture. The algorithms are based on parallel-scan and sort methods. The tree-construction and calculation of multipole moments is carried out on the host CPU, while the force calculation which consists of tree walks and evaluation of interaction list is carried out on the GPU. In this way, a sustained performance of about 100GFLOP/s and data transfer rates of about 50GB/s is achieved. It takes about a second to compute forces on a million particles with an opening angle of heta approx 0.5. To test the performance and feasibility, we implemented the algorithms in CUDA in the form of a gravitational tree-code which completely runs on the GPU. The tree construction and traverse algorithms are portable to many-core devices which have support for CUDA or OpenCL programming languages. The gravitational tree-code outperforms tuned CPU code during the tree-construction and shows a performance improvement of more than a factor 20 overall, resulting in a processing rate of more than 2.8 million particles per second. The code has a convenient user interface and is freely available for use.

  15. Phylogenetic Copy-Number Factorization of Multiple Tumor Samples.

    PubMed

    Zaccaria, Simone; El-Kebir, Mohammed; Klau, Gunnar W; Raphael, Benjamin J

    2018-04-16

    Cancer is an evolutionary process driven by somatic mutations. This process can be represented as a phylogenetic tree. Constructing such a phylogenetic tree from genome sequencing data is a challenging task due to the many types of mutations in cancer and the fact that nearly all cancer sequencing is of a bulk tumor, measuring a superposition of somatic mutations present in different cells. We study the problem of reconstructing tumor phylogenies from copy-number aberrations (CNAs) measured in bulk-sequencing data. We introduce the Copy-Number Tree Mixture Deconvolution (CNTMD) problem, which aims to find the phylogenetic tree with the fewest number of CNAs that explain the copy-number data from multiple samples of a tumor. We design an algorithm for solving the CNTMD problem and apply the algorithm to both simulated and real data. On simulated data, we find that our algorithm outperforms existing approaches that either perform deconvolution/factorization of mixed tumor samples or build phylogenetic trees assuming homogeneous tumor samples. On real data, we analyze multiple samples from a prostate cancer patient, identifying clones within these samples and a phylogenetic tree that relates these clones and their differing proportions across samples. This phylogenetic tree provides a higher resolution view of copy-number evolution of this cancer than published analyses.

  16. Multi-hop path tracing of mobile robot with multi-range image

    NASA Astrophysics Data System (ADS)

    Choudhury, Ramakanta; Samal, Chandrakanta; Choudhury, Umakanta

    2010-02-01

    It is well known that image processing depends heavily upon image representation technique . This paper intends to find out the optimal path of mobile robots for a specified area where obstacles are predefined as well as modified. Here the optimal path is represented by using the Quad tree method. Since there has been rising interest in the use of quad tree, we have tried to use the successive subdivision of images into quadrants from which the quad tree is developed. In the quad tree, obstacles-free area and the partial filled area are represented with different notations. After development of quad tree the algorithm is used to find the optimal path by employing neighbor finding technique, with a view to move the robot from the source to destination. The algorithm, here , permeates through the entire tree, and tries to locate the common ancestor for computation. The computation and the algorithm, aim at easing the ability of the robot to trace the optimal path with the help of adjacencies between the neighboring nodes as well as determining such adjacencies in the horizontal, vertical and diagonal directions. In this paper efforts have been made to determine the movement of the adjacent block in the quad tree and to detect the transition between the blocks equal size and finally generate the result.

  17. A hybrid 3D spatial access method based on quadtrees and R-trees for globe data

    NASA Astrophysics Data System (ADS)

    Gong, Jun; Ke, Shengnan; Li, Xiaomin; Qi, Shuhua

    2009-10-01

    3D spatial access method for globe data is very crucial technique for virtual earth. This paper presents a brand-new maintenance method to index 3d objects distributed on the whole surface of the earth, which integrates the 1:1,000,000- scale topographic map tiles, Quad-tree and R-tree. Furthermore, when traditional methods are extended into 3d space, the performance of spatial index deteriorates badly, for example 3D R-tree. In order to effectively solve this difficult problem, a new algorithm of dynamic R-tree is put forward, which includes two sub-procedures, namely node-choosing and node-split. In the node-choosing algorithm, a new strategy is adopted, not like the traditional mode which is from top to bottom, but firstly from bottom to top then from top to bottom. This strategy can effectively solve the negative influence of node overlap. In the node-split algorithm, 2-to-3 split mode substitutes the traditional 1-to-2 mode, which can better concern the shape and size of nodes. Because of the rational tree shape, this R-tree method can easily integrate the concept of LOD. Therefore, it will be later implemented in commercial DBMS and adopted in time-crucial 3d GIS system.

  18. TreeNetViz: revealing patterns of networks over tree structures.

    PubMed

    Gou, Liang; Zhang, Xiaolong Luke

    2011-12-01

    Network data often contain important attributes from various dimensions such as social affiliations and areas of expertise in a social network. If such attributes exhibit a tree structure, visualizing a compound graph consisting of tree and network structures becomes complicated. How to visually reveal patterns of a network over a tree has not been fully studied. In this paper, we propose a compound graph model, TreeNet, to support visualization and analysis of a network at multiple levels of aggregation over a tree. We also present a visualization design, TreeNetViz, to offer the multiscale and cross-scale exploration and interaction of a TreeNet graph. TreeNetViz uses a Radial, Space-Filling (RSF) visualization to represent the tree structure, a circle layout with novel optimization to show aggregated networks derived from TreeNet, and an edge bundling technique to reduce visual complexity. Our circular layout algorithm reduces both total edge-crossings and edge length and also considers hierarchical structure constraints and edge weight in a TreeNet graph. These experiments illustrate that the algorithm can reduce visual cluttering in TreeNet graphs. Our case study also shows that TreeNetViz has the potential to support the analysis of a compound graph by revealing multiscale and cross-scale network patterns. © 2011 IEEE

  19. Reconciliation of Decision-Making Heuristics Based on Decision Trees Topologies and Incomplete Fuzzy Probabilities Sets

    PubMed Central

    Doubravsky, Karel; Dohnal, Mirko

    2015-01-01

    Complex decision making tasks of different natures, e.g. economics, safety engineering, ecology and biology, are based on vague, sparse, partially inconsistent and subjective knowledge. Moreover, decision making economists / engineers are usually not willing to invest too much time into study of complex formal theories. They require such decisions which can be (re)checked by human like common sense reasoning. One important problem related to realistic decision making tasks are incomplete data sets required by the chosen decision making algorithm. This paper presents a relatively simple algorithm how some missing III (input information items) can be generated using mainly decision tree topologies and integrated into incomplete data sets. The algorithm is based on an easy to understand heuristics, e.g. a longer decision tree sub-path is less probable. This heuristic can solve decision problems under total ignorance, i.e. the decision tree topology is the only information available. But in a practice, isolated information items e.g. some vaguely known probabilities (e.g. fuzzy probabilities) are usually available. It means that a realistic problem is analysed under partial ignorance. The proposed algorithm reconciles topology related heuristics and additional fuzzy sets using fuzzy linear programming. The case study, represented by a tree with six lotteries and one fuzzy probability, is presented in details. PMID:26158662

  20. Reconciliation of Decision-Making Heuristics Based on Decision Trees Topologies and Incomplete Fuzzy Probabilities Sets.

    PubMed

    Doubravsky, Karel; Dohnal, Mirko

    2015-01-01

    Complex decision making tasks of different natures, e.g. economics, safety engineering, ecology and biology, are based on vague, sparse, partially inconsistent and subjective knowledge. Moreover, decision making economists / engineers are usually not willing to invest too much time into study of complex formal theories. They require such decisions which can be (re)checked by human like common sense reasoning. One important problem related to realistic decision making tasks are incomplete data sets required by the chosen decision making algorithm. This paper presents a relatively simple algorithm how some missing III (input information items) can be generated using mainly decision tree topologies and integrated into incomplete data sets. The algorithm is based on an easy to understand heuristics, e.g. a longer decision tree sub-path is less probable. This heuristic can solve decision problems under total ignorance, i.e. the decision tree topology is the only information available. But in a practice, isolated information items e.g. some vaguely known probabilities (e.g. fuzzy probabilities) are usually available. It means that a realistic problem is analysed under partial ignorance. The proposed algorithm reconciles topology related heuristics and additional fuzzy sets using fuzzy linear programming. The case study, represented by a tree with six lotteries and one fuzzy probability, is presented in details.

  1. Computing all hybridization networks for multiple binary phylogenetic input trees.

    PubMed

    Albrecht, Benjamin

    2015-07-30

    The computation of phylogenetic trees on the same set of species that are based on different orthologous genes can lead to incongruent trees. One possible explanation for this behavior are interspecific hybridization events recombining genes of different species. An important approach to analyze such events is the computation of hybridization networks. This work presents the first algorithm computing the hybridization number as well as a set of representative hybridization networks for multiple binary phylogenetic input trees on the same set of taxa. To improve its practical runtime, we show how this algorithm can be parallelized. Moreover, we demonstrate the efficiency of the software Hybroscale, containing an implementation of our algorithm, by comparing it to PIRNv2.0, which is so far the best available software computing the exact hybridization number for multiple binary phylogenetic trees on the same set of taxa. The algorithm is part of the software Hybroscale, which was developed specifically for the investigation of hybridization networks including their computation and visualization. Hybroscale is freely available(1) and runs on all three major operating systems. Our simulation study indicates that our approach is on average 100 times faster than PIRNv2.0. Moreover, we show how Hybroscale improves the interpretation of the reported hybridization networks by adding certain features to its graphical representation.

  2. Continuous-time quantum search on balanced trees

    NASA Astrophysics Data System (ADS)

    Philipp, Pascal; Tarrataca, Luís; Boettcher, Stefan

    2016-03-01

    We examine the effect of network heterogeneity on the performance of quantum search algorithms. To this end, we study quantum search on a tree for the oracle Hamiltonian formulation employed by continuous-time quantum walks. We use analytical and numerical arguments to show that the exponent of the asymptotic running time ˜Nβ changes uniformly from β =0.5 to β =1 as the searched-for site is moved from the root of the tree towards the leaves. These results imply that the time complexity of the quantum search algorithm on a balanced tree is closely correlated with certain path-based centrality measures of the searched-for site.

  3. Application of a fast skyline computation algorithm for serendipitous searching problems

    NASA Astrophysics Data System (ADS)

    Koizumi, Kenichi; Hiraki, Kei; Inaba, Mary

    2018-02-01

    Skyline computation is a method of extracting interesting entries from a large population with multiple attributes. These entries, called skyline or Pareto optimal entries, are known to have extreme characteristics that cannot be found by outlier detection methods. Skyline computation is an important task for characterizing large amounts of data and selecting interesting entries with extreme features. When the population changes dynamically, the task of calculating a sequence of skyline sets is called continuous skyline computation. This task is known to be difficult to perform for the following reasons: (1) information of non-skyline entries must be stored since they may join the skyline in the future; (2) the appearance or disappearance of even a single entry can change the skyline drastically; (3) it is difficult to adopt a geometric acceleration algorithm for skyline computation tasks with high-dimensional datasets. Our new algorithm called jointed rooted-tree (JR-tree) manages entries using a rooted tree structure. JR-tree delays extend the tree to deep levels to accelerate tree construction and traversal. In this study, we presented the difficulties in extracting entries tagged with a rare label in high-dimensional space and the potential of fast skyline computation in low-latency cell identification technology.

  4. Implementation of Tree and Butterfly Barriers with Optimistic Time Management Algorithms for Discrete Event Simulation

    NASA Astrophysics Data System (ADS)

    Rizvi, Syed S.; Shah, Dipali; Riasat, Aasia

    The Time Wrap algorithm [3] offers a run time recovery mechanism that deals with the causality errors. These run time recovery mechanisms consists of rollback, anti-message, and Global Virtual Time (GVT) techniques. For rollback, there is a need to compute GVT which is used in discrete-event simulation to reclaim the memory, commit the output, detect the termination, and handle the errors. However, the computation of GVT requires dealing with transient message problem and the simultaneous reporting problem. These problems can be dealt in an efficient manner by the Samadi's algorithm [8] which works fine in the presence of causality errors. However, the performance of both Time Wrap and Samadi's algorithms depends on the latency involve in GVT computation. Both algorithms give poor latency for large simulation systems especially in the presence of causality errors. To improve the latency and reduce the processor ideal time, we implement tree and butterflies barriers with the optimistic algorithm. Our analysis shows that the use of synchronous barriers such as tree and butterfly with the optimistic algorithm not only minimizes the GVT latency but also minimizes the processor idle time.

  5. Fish to meat intake ratio and cooking oils are associated with hepatitis C virus carriers with persistently normal alanine aminotransferase levels.

    PubMed

    Otsuka, Momoka; Uchida, Yuki; Kawaguchi, Takumi; Taniguchi, Eitaro; Kawaguchi, Atsushi; Kitani, Shingo; Itou, Minoru; Oriishi, Tetsuharu; Kakuma, Tatsuyuki; Tanaka, Suiko; Yagi, Minoru; Sata, Michio

    2012-10-01

      Dietary habits are involved in the development of chronic inflammation; however, the impact of dietary profiles of hepatitis C virus carriers with persistently normal alanine transaminase levels (HCV-PNALT) remains unclear. The decision-tree algorithm is a data-mining statistical technique, which uncovers meaningful profiles of factors from a data collection. We aimed to investigate dietary profiles associated with HCV-PNALT using a decision-tree algorithm.   Twenty-seven HCV-PNALT and 41 patients with chronic hepatitis C were enrolled in this study. Dietary habit was assessed using a validated semiquantitative food frequency questionnaire. A decision-tree algorithm was created by dietary variables, and was evaluated by area under the receiver operating characteristic curve analysis (AUROC).   In multivariate analysis, fish to meat ratio, dairy product and cooking oils were identified as independent variables associated with HCV-PNALT. The decision-tree algorithm was created with two variables: a fish to meat ratio and cooking oils/ideal bodyweight. When subjects showed a fish to meat ratio of 1.24 or more, 68.8% of the subjects were HCV-PNALT. On the other hand, 11.5% of the subjects were HCV-PNALT when subjects showed a fish to meat ratio of less than 1.24 and cooking oil/ideal bodyweight of less than 0.23 g/kg. The difference in the proportion of HCV-PNALT between these groups are significant (odds ratio 16.87, 95% CI 3.40-83.67, P = 0.0005). Fivefold cross-validation of the decision-tree algorithm showed an AUROC of 0.6947 (95% CI 0.5656-0.8238, P = 0.0067).   The decision-tree algorithm disclosed that fish to meat ratio and cooking oil/ideal bodyweight were associated with HCV-PNALT. © 2012 The Japan Society of Hepatology.

  6. Finding minimum spanning trees more efficiently for tile-based phase unwrapping

    NASA Astrophysics Data System (ADS)

    Sawaf, Firas; Tatam, Ralph P.

    2006-06-01

    The tile-based phase unwrapping method employs an algorithm for finding the minimum spanning tree (MST) in each tile. We first examine the properties of a tile's representation from a graph theory viewpoint, observing that it is possible to make use of a more efficient class of MST algorithms. We then describe a novel linear time algorithm which reduces the size of the MST problem by half at the least, and solves it completely at best. We also show how this algorithm can be applied to a tile using a sliding window technique. Finally, we show how the reduction algorithm can be combined with any other standard MST algorithm to achieve a more efficient hybrid, using Prim's algorithm for empirical comparison and noting that the reduction algorithm takes only 0.1% of the time taken by the overall hybrid.

  7. Distribution and persistence of emamectin benzoate at efficacious concentrations in pine tissues after injection of a liquid formulation.

    PubMed

    Takai, Kazuya; Suzuki, Toshio; Kawazu, Kazuyoshi

    2004-01-01

    In an earlier paper the authors reported the creation of a novel emamectin benzoate 40 g litre(-1) liquid formulation (Shot Wan Liquid Formulation). The injection of this formulation exerted a preventative effect against the pine wilt disease caused by the pine wood nematode, Bursaphelenchus xylophilus (Steiner & Buhrer) Nickle, and this effect lasted for at least 3 years. The present study was carried out to show experimentally that the marked effect of this formulation was due to the presence and persistence in pine tissues of sufficient amounts of emamectin benzoate to inhibit nematode propagation. A cleanup procedure prior to quantitative analysis of emamectin benzoate by fluorescence HPLC was devised. The presence of the compound in concentrations sufficient to inhibit nematode propagation in the shoots of current growth and its persistence for 3 years explained the marked preventative effect. Non-distribution of emamectin benzoate in some parts of the lower trunk suggested that the formulation should be injected at several points for large trees in order to distribute the compound uniformly to lower branches.

  8. Association between split selection instability and predictive error in survival trees.

    PubMed

    Radespiel-Tröger, M; Gefeller, O; Rabenstein, T; Hothorn, T

    2006-01-01

    To evaluate split selection instability in six survival tree algorithms and its relationship with predictive error by means of a bootstrap study. We study the following algorithms: logrank statistic with multivariate p-value adjustment without pruning (LR), Kaplan-Meier distance of survival curves (KM), martingale residuals (MR), Poisson regression for censored data (PR), within-node impurity (WI), and exponential log-likelihood loss (XL). With the exception of LR, initial trees are pruned by using split-complexity, and final trees are selected by means of cross-validation. We employ a real dataset from a clinical study of patients with gallbladder stones. The predictive error is evaluated using the integrated Brier score for censored data. The relationship between split selection instability and predictive error is evaluated by means of box-percentile plots, covariate and cutpoint selection entropy, and cutpoint selection coefficients of variation, respectively, in the root node. We found a positive association between covariate selection instability and predictive error in the root node. LR yields the lowest predictive error, while KM and MR yield the highest predictive error. The predictive error of survival trees is related to split selection instability. Based on the low predictive error of LR, we recommend the use of this algorithm for the construction of survival trees. Unpruned survival trees with multivariate p-value adjustment can perform equally well compared to pruned trees. The analysis of split selection instability can be used to communicate the results of tree-based analyses to clinicians and to support the application of survival trees.

  9. Transoral laser surgery for laryngeal carcinoma: has Steiner achieved a genuine paradigm shift in oncological surgery?

    PubMed

    Harris, A T; Tanyi, A; Hart, R D; Trites, J; Rigby, M H; Lancaster, J; Nicolaides, A; Taylor, S M

    2018-01-01

    Transoral laser microsurgery applies to the piecemeal removal of malignant tumours of the upper aerodigestive tract using the CO 2 laser under the operating microscope. This method of surgery is being increasingly popularised as a single modality treatment of choice in early laryngeal cancers (T1 and T2) and occasionally in the more advanced forms of the disease (T3 and T4), predominantly within the supraglottis. Thomas Kuhn, the American physicist turned philosopher and historian of science, coined the phrase 'paradigm shift' in his groundbreaking book The Structure of Scientific Revolutions. He argued that the arrival of the new and often incompatible idea forms the core of a new paradigm, the birth of an entirely new way of thinking. This article discusses whether Steiner and colleagues truly brought about a paradigm shift in oncological surgery. By rejecting the principle of en block resection and by replacing it with the belief that not only is it oncologically safe to cut through the substance of the tumour but in doing so one can actually achieve better results, Steiner was able to truly revolutionise the management of laryngeal cancer. Even though within this article the repercussions of his insight are limited to the upper aerodigestive tract oncological surgery, his willingness to question other peoples' dogma makes his contribution truly a genuine paradigm shift.

  10. Extensions and applications of ensemble-of-trees methods in machine learning

    NASA Astrophysics Data System (ADS)

    Bleich, Justin

    Ensemble-of-trees algorithms have emerged to the forefront of machine learning due to their ability to generate high forecasting accuracy for a wide array of regression and classification problems. Classic ensemble methodologies such as random forests (RF) and stochastic gradient boosting (SGB) rely on algorithmic procedures to generate fits to data. In contrast, more recent ensemble techniques such as Bayesian Additive Regression Trees (BART) and Dynamic Trees (DT) focus on an underlying Bayesian probability model to generate the fits. These new probability model-based approaches show much promise versus their algorithmic counterparts, but also offer substantial room for improvement. The first part of this thesis focuses on methodological advances for ensemble-of-trees techniques with an emphasis on the more recent Bayesian approaches. In particular, we focus on extensions of BART in four distinct ways. First, we develop a more robust implementation of BART for both research and application. We then develop a principled approach to variable selection for BART as well as the ability to naturally incorporate prior information on important covariates into the algorithm. Next, we propose a method for handling missing data that relies on the recursive structure of decision trees and does not require imputation. Last, we relax the assumption of homoskedasticity in the BART model to allow for parametric modeling of heteroskedasticity. The second part of this thesis returns to the classic algorithmic approaches in the context of classification problems with asymmetric costs of forecasting errors. First we consider the performance of RF and SGB more broadly and demonstrate its superiority to logistic regression for applications in criminology with asymmetric costs. Next, we use RF to forecast unplanned hospital readmissions upon patient discharge with asymmetric costs taken into account. Finally, we explore the construction of stable decision trees for forecasts of violence during probation hearings in court systems.

  11. ATLAAS: an automatic decision tree-based learning algorithm for advanced image segmentation in positron emission tomography.

    PubMed

    Berthon, Beatrice; Marshall, Christopher; Evans, Mererid; Spezi, Emiliano

    2016-07-07

    Accurate and reliable tumour delineation on positron emission tomography (PET) is crucial for radiotherapy treatment planning. PET automatic segmentation (PET-AS) eliminates intra- and interobserver variability, but there is currently no consensus on the optimal method to use, as different algorithms appear to perform better for different types of tumours. This work aimed to develop a predictive segmentation model, trained to automatically select and apply the best PET-AS method, according to the tumour characteristics. ATLAAS, the automatic decision tree-based learning algorithm for advanced segmentation is based on supervised machine learning using decision trees. The model includes nine PET-AS methods and was trained on a 100 PET scans with known true contour. A decision tree was built for each PET-AS algorithm to predict its accuracy, quantified using the Dice similarity coefficient (DSC), according to the tumour volume, tumour peak to background SUV ratio and a regional texture metric. The performance of ATLAAS was evaluated for 85 PET scans obtained from fillable and printed subresolution sandwich phantoms. ATLAAS showed excellent accuracy across a wide range of phantom data and predicted the best or near-best segmentation algorithm in 93% of cases. ATLAAS outperformed all single PET-AS methods on fillable phantom data with a DSC of 0.881, while the DSC for H&N phantom data was 0.819. DSCs higher than 0.650 were achieved in all cases. ATLAAS is an advanced automatic image segmentation algorithm based on decision tree predictive modelling, which can be trained on images with known true contour, to predict the best PET-AS method when the true contour is unknown. ATLAAS provides robust and accurate image segmentation with potential applications to radiation oncology.

  12. ATLAAS: an automatic decision tree-based learning algorithm for advanced image segmentation in positron emission tomography

    NASA Astrophysics Data System (ADS)

    Berthon, Beatrice; Marshall, Christopher; Evans, Mererid; Spezi, Emiliano

    2016-07-01

    Accurate and reliable tumour delineation on positron emission tomography (PET) is crucial for radiotherapy treatment planning. PET automatic segmentation (PET-AS) eliminates intra- and interobserver variability, but there is currently no consensus on the optimal method to use, as different algorithms appear to perform better for different types of tumours. This work aimed to develop a predictive segmentation model, trained to automatically select and apply the best PET-AS method, according to the tumour characteristics. ATLAAS, the automatic decision tree-based learning algorithm for advanced segmentation is based on supervised machine learning using decision trees. The model includes nine PET-AS methods and was trained on a 100 PET scans with known true contour. A decision tree was built for each PET-AS algorithm to predict its accuracy, quantified using the Dice similarity coefficient (DSC), according to the tumour volume, tumour peak to background SUV ratio and a regional texture metric. The performance of ATLAAS was evaluated for 85 PET scans obtained from fillable and printed subresolution sandwich phantoms. ATLAAS showed excellent accuracy across a wide range of phantom data and predicted the best or near-best segmentation algorithm in 93% of cases. ATLAAS outperformed all single PET-AS methods on fillable phantom data with a DSC of 0.881, while the DSC for H&N phantom data was 0.819. DSCs higher than 0.650 were achieved in all cases. ATLAAS is an advanced automatic image segmentation algorithm based on decision tree predictive modelling, which can be trained on images with known true contour, to predict the best PET-AS method when the true contour is unknown. ATLAAS provides robust and accurate image segmentation with potential applications to radiation oncology.

  13. The effect of different distance measures in detecting outliers using clustering-based algorithm for circular regression model

    NASA Astrophysics Data System (ADS)

    Di, Nur Faraidah Muhammad; Satari, Siti Zanariah

    2017-05-01

    Outlier detection in linear data sets has been done vigorously but only a small amount of work has been done for outlier detection in circular data. In this study, we proposed multiple outliers detection in circular regression models based on the clustering algorithm. Clustering technique basically utilizes distance measure to define distance between various data points. Here, we introduce the similarity distance based on Euclidean distance for circular model and obtain a cluster tree using the single linkage clustering algorithm. Then, a stopping rule for the cluster tree based on the mean direction and circular standard deviation of the tree height is proposed. We classify the cluster group that exceeds the stopping rule as potential outlier. Our aim is to demonstrate the effectiveness of proposed algorithms with the similarity distances in detecting the outliers. It is found that the proposed methods are performed well and applicable for circular regression model.

  14. Automatic Classification of Trees from Laser Scanning Point Clouds

    NASA Astrophysics Data System (ADS)

    Sirmacek, B.; Lindenbergh, R.

    2015-08-01

    Development of laser scanning technologies has promoted tree monitoring studies to a new level, as the laser scanning point clouds enable accurate 3D measurements in a fast and environmental friendly manner. In this paper, we introduce a probability matrix computation based algorithm for automatically classifying laser scanning point clouds into 'tree' and 'non-tree' classes. Our method uses the 3D coordinates of the laser scanning points as input and generates a new point cloud which holds a label for each point indicating if it belongs to the 'tree' or 'non-tree' class. To do so, a grid surface is assigned to the lowest height level of the point cloud. The grids are filled with probability values which are calculated by checking the point density above the grid. Since the tree trunk locations appear with very high values in the probability matrix, selecting the local maxima of the grid surface help to detect the tree trunks. Further points are assigned to tree trunks if they appear in the close proximity of trunks. Since heavy mathematical computations (such as point cloud organization, detailed shape 3D detection methods, graph network generation) are not required, the proposed algorithm works very fast compared to the existing methods. The tree classification results are found reliable even on point clouds of cities containing many different objects. As the most significant weakness, false detection of light poles, traffic signs and other objects close to trees cannot be prevented. Nevertheless, the experimental results on mobile and airborne laser scanning point clouds indicate the possible usage of the algorithm as an important step for tree growth observation, tree counting and similar applications. While the laser scanning point cloud is giving opportunity to classify even very small trees, accuracy of the results is reduced in the low point density areas further away than the scanning location. These advantages and disadvantages of two laser scanning point cloud sources are discussed in detail.

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

    Behroozi, Peter S.; Wechsler, Risa H.; Wu, Hao-Yi

    We present a new algorithm for generating merger trees and halo catalogs which explicitly ensures consistency of halo properties (mass, position, and velocity) across time steps. Our algorithm has demonstrated the ability to improve both the completeness (through detecting and inserting otherwise missing halos) and purity (through detecting and removing spurious objects) of both merger trees and halo catalogs. In addition, our method is able to robustly measure the self-consistency of halo finders; it is the first to directly measure the uncertainties in halo positions, halo velocities, and the halo mass function for a given halo finder based on consistencymore » between snapshots in cosmological simulations. We use this algorithm to generate merger trees for two large simulations (Bolshoi and Consuelo) and evaluate two halo finders (ROCKSTAR and BDM). We find that both the ROCKSTAR and BDM halo finders track halos extremely well; in both, the number of halos which do not have physically consistent progenitors is at the 1%-2% level across all halo masses. Our code is publicly available at http://code.google.com/p/consistent-trees. Our trees and catalogs are publicly available at http://hipacc.ucsc.edu/Bolshoi/.« less

  16. Effects of plot size on forest-type algorithm accuracy

    Treesearch

    James A. Westfall

    2009-01-01

    The Forest Inventory and Analysis (FIA) program utilizes an algorithm to consistently determine the forest type for forested conditions on sample plots. Forest type is determined from tree size and species information. Thus, the accuracy of results is often dependent on the number of trees present, which is highly correlated with plot area. This research examines the...

  17. Matching Pion-Nucleon Roy-Steiner Equations to Chiral Perturbation Theory.

    PubMed

    Hoferichter, Martin; Ruiz de Elvira, Jacobo; Kubis, Bastian; Meissner, Ulf-G

    2015-11-06

    We match the results for the subthreshold parameters of pion-nucleon scattering obtained from a solution of Roy-Steiner equations to chiral perturbation theory up to next-to-next-to-next-to-leading order, to extract the pertinent low-energy constants including a comprehensive analysis of systematic uncertainties and correlations. We study the convergence of the chiral series by investigating the chiral expansion of threshold parameters up to the same order and discuss the role of the Δ(1232) resonance in this context. Results for the low-energy constants are also presented in the counting scheme usually applied in chiral nuclear effective field theory, where they serve as crucial input to determine the long-range part of the nucleon-nucleon potential as well as three-nucleon forces.

  18. Matching Pion-Nucleon Roy-Steiner Equations to Chiral Perturbation Theory

    NASA Astrophysics Data System (ADS)

    Hoferichter, Martin; Ruiz de Elvira, Jacobo; Kubis, Bastian; Meißner, Ulf-G.

    2015-11-01

    We match the results for the subthreshold parameters of pion-nucleon scattering obtained from a solution of Roy-Steiner equations to chiral perturbation theory up to next-to-next-to-next-to-leading order, to extract the pertinent low-energy constants including a comprehensive analysis of systematic uncertainties and correlations. We study the convergence of the chiral series by investigating the chiral expansion of threshold parameters up to the same order and discuss the role of the Δ (1232 ) resonance in this context. Results for the low-energy constants are also presented in the counting scheme usually applied in chiral nuclear effective field theory, where they serve as crucial input to determine the long-range part of the nucleon-nucleon potential as well as three-nucleon forces.

  19. Correlation between the norm and the geometry of minimal networks

    NASA Astrophysics Data System (ADS)

    Laut, I. L.

    2017-05-01

    The paper is concerned with the inverse problem of the minimal Steiner network problem in a normed linear space. Namely, given a normed space in which all minimal networks are known for any finite point set, the problem is to describe all the norms on this space for which the minimal networks are the same as for the original norm. We survey the available results and prove that in the plane a rotund differentiable norm determines a distinctive set of minimal Steiner networks. In a two-dimensional space with rotund differentiable norm the coordinates of interior vertices of a nondegenerate minimal parametric network are shown to vary continuously under small deformations of the boundary set, and the turn direction of the network is determined. Bibliography: 15 titles.

  20. Fast Dating Using Least-Squares Criteria and Algorithms.

    PubMed

    To, Thu-Hien; Jung, Matthieu; Lycett, Samantha; Gascuel, Olivier

    2016-01-01

    Phylogenies provide a useful way to understand the evolutionary history of genetic samples, and data sets with more than a thousand taxa are becoming increasingly common, notably with viruses (e.g., human immunodeficiency virus (HIV)). Dating ancestral events is one of the first, essential goals with such data. However, current sophisticated probabilistic approaches struggle to handle data sets of this size. Here, we present very fast dating algorithms, based on a Gaussian model closely related to the Langley-Fitch molecular-clock model. We show that this model is robust to uncorrelated violations of the molecular clock. Our algorithms apply to serial data, where the tips of the tree have been sampled through times. They estimate the substitution rate and the dates of all ancestral nodes. When the input tree is unrooted, they can provide an estimate for the root position, thus representing a new, practical alternative to the standard rooting methods (e.g., midpoint). Our algorithms exploit the tree (recursive) structure of the problem at hand, and the close relationships between least-squares and linear algebra. We distinguish between an unconstrained setting and the case where the temporal precedence constraint (i.e., an ancestral node must be older that its daughter nodes) is accounted for. With rooted trees, the former is solved using linear algebra in linear computing time (i.e., proportional to the number of taxa), while the resolution of the latter, constrained setting, is based on an active-set method that runs in nearly linear time. With unrooted trees the computing time becomes (nearly) quadratic (i.e., proportional to the square of the number of taxa). In all cases, very large input trees (>10,000 taxa) can easily be processed and transformed into time-scaled trees. We compare these algorithms to standard methods (root-to-tip, r8s version of Langley-Fitch method, and BEAST). Using simulated data, we show that their estimation accuracy is similar to that of the most sophisticated methods, while their computing time is much faster. We apply these algorithms on a large data set comprising 1194 strains of Influenza virus from the pdm09 H1N1 Human pandemic. Again the results show that these algorithms provide a very fast alternative with results similar to those of other computer programs. These algorithms are implemented in the LSD software (least-squares dating), which can be downloaded from http://www.atgc-montpellier.fr/LSD/, along with all our data sets and detailed results. An Online Appendix, providing additional algorithm descriptions, tables, and figures can be found in the Supplementary Material available on Dryad at http://dx.doi.org/10.5061/dryad.968t3. © The Author(s) 2015. Published by Oxford University Press, on behalf of the Society of Systematic Biologists.

  1. Fast Dating Using Least-Squares Criteria and Algorithms

    PubMed Central

    To, Thu-Hien; Jung, Matthieu; Lycett, Samantha; Gascuel, Olivier

    2016-01-01

    Phylogenies provide a useful way to understand the evolutionary history of genetic samples, and data sets with more than a thousand taxa are becoming increasingly common, notably with viruses (e.g., human immunodeficiency virus (HIV)). Dating ancestral events is one of the first, essential goals with such data. However, current sophisticated probabilistic approaches struggle to handle data sets of this size. Here, we present very fast dating algorithms, based on a Gaussian model closely related to the Langley–Fitch molecular-clock model. We show that this model is robust to uncorrelated violations of the molecular clock. Our algorithms apply to serial data, where the tips of the tree have been sampled through times. They estimate the substitution rate and the dates of all ancestral nodes. When the input tree is unrooted, they can provide an estimate for the root position, thus representing a new, practical alternative to the standard rooting methods (e.g., midpoint). Our algorithms exploit the tree (recursive) structure of the problem at hand, and the close relationships between least-squares and linear algebra. We distinguish between an unconstrained setting and the case where the temporal precedence constraint (i.e., an ancestral node must be older that its daughter nodes) is accounted for. With rooted trees, the former is solved using linear algebra in linear computing time (i.e., proportional to the number of taxa), while the resolution of the latter, constrained setting, is based on an active-set method that runs in nearly linear time. With unrooted trees the computing time becomes (nearly) quadratic (i.e., proportional to the square of the number of taxa). In all cases, very large input trees (>10,000 taxa) can easily be processed and transformed into time-scaled trees. We compare these algorithms to standard methods (root-to-tip, r8s version of Langley–Fitch method, and BEAST). Using simulated data, we show that their estimation accuracy is similar to that of the most sophisticated methods, while their computing time is much faster. We apply these algorithms on a large data set comprising 1194 strains of Influenza virus from the pdm09 H1N1 Human pandemic. Again the results show that these algorithms provide a very fast alternative with results similar to those of other computer programs. These algorithms are implemented in the LSD software (least-squares dating), which can be downloaded from http://www.atgc-montpellier.fr/LSD/, along with all our data sets and detailed results. An Online Appendix, providing additional algorithm descriptions, tables, and figures can be found in the Supplementary Material available on Dryad at http://dx.doi.org/10.5061/dryad.968t3. PMID:26424727

  2. Labeled trees and the efficient computation of derivations

    NASA Technical Reports Server (NTRS)

    Grossman, Robert; Larson, Richard G.

    1989-01-01

    The effective parallel symbolic computation of operators under composition is discussed. Examples include differential operators under composition and vector fields under the Lie bracket. Data structures consisting of formal linear combinations of rooted labeled trees are discussed. A multiplication on rooted labeled trees is defined, thereby making the set of these data structures into an associative algebra. An algebra homomorphism is defined from the original algebra of operators into this algebra of trees. An algebra homomorphism from the algebra of trees into the algebra of differential operators is then described. The cancellation which occurs when noncommuting operators are expressed in terms of commuting ones occurs naturally when the operators are represented using this data structure. This leads to an algorithm which, for operators which are derivations, speeds up the computation exponentially in the degree of the operator. It is shown that the algebra of trees leads naturally to a parallel version of the algorithm.

  3. Computational path planner for product assembly in complex environments

    NASA Astrophysics Data System (ADS)

    Shang, Wei; Liu, Jianhua; Ning, Ruxin; Liu, Mi

    2013-03-01

    Assembly path planning is a crucial problem in assembly related design and manufacturing processes. Sampling based motion planning algorithms are used for computational assembly path planning. However, the performance of such algorithms may degrade much in environments with complex product structure, narrow passages or other challenging scenarios. A computational path planner for automatic assembly path planning in complex 3D environments is presented. The global planning process is divided into three phases based on the environment and specific algorithms are proposed and utilized in each phase to solve the challenging issues. A novel ray test based stochastic collision detection method is proposed to evaluate the intersection between two polyhedral objects. This method avoids fake collisions in conventional methods and degrades the geometric constraint when a part has to be removed with surface contact with other parts. A refined history based rapidly-exploring random tree (RRT) algorithm which bias the growth of the tree based on its planning history is proposed and employed in the planning phase where the path is simple but the space is highly constrained. A novel adaptive RRT algorithm is developed for the path planning problem with challenging scenarios and uncertain environment. With extending values assigned on each tree node and extending schemes applied, the tree can adapts its growth to explore complex environments more efficiently. Experiments on the key algorithms are carried out and comparisons are made between the conventional path planning algorithms and the presented ones. The comparing results show that based on the proposed algorithms, the path planner can compute assembly path in challenging complex environments more efficiently and with higher success. This research provides the references to the study of computational assembly path planning under complex environments.

  4. Analysis of data mining classification by comparison of C4.5 and ID algorithms

    NASA Astrophysics Data System (ADS)

    Sudrajat, R.; Irianingsih, I.; Krisnawan, D.

    2017-01-01

    The rapid development of information technology, triggered by the intensive use of information technology. For example, data mining widely used in investment. Many techniques that can be used assisting in investment, the method that used for classification is decision tree. Decision tree has a variety of algorithms, such as C4.5 and ID3. Both algorithms can generate different models for similar data sets and different accuracy. C4.5 and ID3 algorithms with discrete data provide accuracy are 87.16% and 99.83% and C4.5 algorithm with numerical data is 89.69%. C4.5 and ID3 algorithms with discrete data provides 520 and 598 customers and C4.5 algorithm with numerical data is 546 customers. From the analysis of the both algorithm it can classified quite well because error rate less than 15%.

  5. Multi-test decision tree and its application to microarray data classification.

    PubMed

    Czajkowski, Marcin; Grześ, Marek; Kretowski, Marek

    2014-05-01

    The desirable property of tools used to investigate biological data is easy to understand models and predictive decisions. Decision trees are particularly promising in this regard due to their comprehensible nature that resembles the hierarchical process of human decision making. However, existing algorithms for learning decision trees have tendency to underfit gene expression data. The main aim of this work is to improve the performance and stability of decision trees with only a small increase in their complexity. We propose a multi-test decision tree (MTDT); our main contribution is the application of several univariate tests in each non-terminal node of the decision tree. We also search for alternative, lower-ranked features in order to obtain more stable and reliable predictions. Experimental validation was performed on several real-life gene expression datasets. Comparison results with eight classifiers show that MTDT has a statistically significantly higher accuracy than popular decision tree classifiers, and it was highly competitive with ensemble learning algorithms. The proposed solution managed to outperform its baseline algorithm on 14 datasets by an average 6%. A study performed on one of the datasets showed that the discovered genes used in the MTDT classification model are supported by biological evidence in the literature. This paper introduces a new type of decision tree which is more suitable for solving biological problems. MTDTs are relatively easy to analyze and much more powerful in modeling high dimensional microarray data than their popular counterparts. Copyright © 2014 Elsevier B.V. All rights reserved.

  6. Accuracy Assessment of Crown Delineation Methods for the Individual Trees Using LIDAR Data

    NASA Astrophysics Data System (ADS)

    Chang, K. T.; Lin, C.; Lin, Y. C.; Liu, J. K.

    2016-06-01

    Forest canopy density and height are used as variables in a number of environmental applications, including the estimation of biomass, forest extent and condition, and biodiversity. The airborne Light Detection and Ranging (LiDAR) is very useful to estimate forest canopy parameters according to the generated canopy height models (CHMs). The purpose of this work is to introduce an algorithm to delineate crown parameters, e.g. tree height and crown radii based on the generated rasterized CHMs. And accuracy assessment for the extraction of volumetric parameters of a single tree is also performed via manual measurement using corresponding aerial photo pairs. A LiDAR dataset of a golf course acquired by Leica ALS70-HP is used in this study. Two algorithms, i.e. a traditional one with the subtraction of a digital elevation model (DEM) from a digital surface model (DSM), and a pit-free approach are conducted to generate the CHMs firstly. Then two algorithms, a multilevel morphological active-contour (MMAC) and a variable window filter (VWF), are implemented and used in this study for individual tree delineation. Finally, experimental results of two automatic estimation methods for individual trees can be evaluated with manually measured stand-level parameters, i.e. tree height and crown diameter. The resulting CHM generated by a simple subtraction is full of empty pixels (called "pits") that will give vital impact on subsequent analysis for individual tree delineation. The experimental results indicated that if more individual trees can be extracted, tree crown shape will became more completely in the CHM data after the pit-free process.

  7. Aneurysmal subarachnoid hemorrhage prognostic decision-making algorithm using classification and regression tree analysis.

    PubMed

    Lo, Benjamin W Y; Fukuda, Hitoshi; Angle, Mark; Teitelbaum, Jeanne; Macdonald, R Loch; Farrokhyar, Forough; Thabane, Lehana; Levine, Mitchell A H

    2016-01-01

    Classification and regression tree analysis involves the creation of a decision tree by recursive partitioning of a dataset into more homogeneous subgroups. Thus far, there is scarce literature on using this technique to create clinical prediction tools for aneurysmal subarachnoid hemorrhage (SAH). The classification and regression tree analysis technique was applied to the multicenter Tirilazad database (3551 patients) in order to create the decision-making algorithm. In order to elucidate prognostic subgroups in aneurysmal SAH, neurologic, systemic, and demographic factors were taken into account. The dependent variable used for analysis was the dichotomized Glasgow Outcome Score at 3 months. Classification and regression tree analysis revealed seven prognostic subgroups. Neurological grade, occurrence of post-admission stroke, occurrence of post-admission fever, and age represented the explanatory nodes of this decision tree. Split sample validation revealed classification accuracy of 79% for the training dataset and 77% for the testing dataset. In addition, the occurrence of fever at 1-week post-aneurysmal SAH is associated with increased odds of post-admission stroke (odds ratio: 1.83, 95% confidence interval: 1.56-2.45, P < 0.01). A clinically useful classification tree was generated, which serves as a prediction tool to guide bedside prognostication and clinical treatment decision making. This prognostic decision-making algorithm also shed light on the complex interactions between a number of risk factors in determining outcome after aneurysmal SAH.

  8. Individual tree detection in intact forest and degraded forest areas in the north region of Mato Grosso State, Brazilian Amazon

    NASA Astrophysics Data System (ADS)

    Santos, E. G.; Jorge, A.; Shimabukuro, Y. E.; Gasparini, K.

    2017-12-01

    The State of Mato Grosso - MT has the second largest area with degraded forest among the states of the Brazilian Legal Amazon. Land use and land cover change processes that occur in this region cause the loss of forest biomass, releasing greenhouse gases that contribute to the increase of temperature on earth. These degraded forest areas lose biomass according to the intensity and magnitude of the degradation type. The estimate of forest biomass, commonly performed by forest inventory through sample plots, shows high variance in degraded forest areas. Due to this variance and complexity of tropical forests, the aim of this work was to estimate forest biomass using LiDAR point clouds in three distinct forest areas: one degraded by fire, another by selective logging and one area of intact forest. The approach applied in these areas was the Individual Tree Detection (ITD). To isolate the trees, we generated Canopy Height Models (CHM) images, which are obtained by subtracting the Digital Elevation Model (MDE) and the Digital Terrain Model (MDT), created by the cloud of LiDAR points. The trees in the CHM images are isolated by an algorithm provided by the Quantitative Ecology research group at the School of Forestry at Northern Arizona University (SILVA, 2015). With these points, metrics were calculated for some areas, which were used in the model of biomass estimation. The methodology used in this work was expected to reduce the error in biomass estimate in the study area. The cloud points of the most representative trees were analyzed, and thus field data was correlated with the individual trees found by the proposed algorithm. In a pilot study, the proposed methodology was applied generating the individual tree metrics: total height and area of the crown. When correlating 339 isolated trees, an unsatisfactory R² was obtained, as heights found by the algorithm were lower than those obtained in the field, with an average difference of 2.43 m. This shows that the algorithm used to isolate trees in temperate areas did not obtained satisfactory results in the tropical forest of Mato Grosso State. Due to this, in future works two algorithms, one developed by Dalponte et al. (2015) and another by Li et al. (2012) will be used.

  9. The K tree score: quantification of differences in the relative branch length and topology of phylogenetic trees.

    PubMed

    Soria-Carrasco, Víctor; Talavera, Gerard; Igea, Javier; Castresana, Jose

    2007-11-01

    We introduce a new phylogenetic comparison method that measures overall differences in the relative branch length and topology of two phylogenetic trees. To do this, the algorithm first scales one of the trees to have a global divergence as similar as possible to the other tree. Then, the branch length distance, which takes differences in topology and branch lengths into account, is applied to the two trees. We thus obtain the minimum branch length distance or K tree score. Two trees with very different relative branch lengths get a high K score whereas two trees that follow a similar among-lineage rate variation get a low score, regardless of the overall rates in both trees. There are several applications of the K tree score, two of which are explained here in more detail. First, this score allows the evaluation of the performance of phylogenetic algorithms, not only with respect to their topological accuracy, but also with respect to the reproduction of a given branch length variation. In a second example, we show how the K score allows the selection of orthologous genes by choosing those that better follow the overall shape of a given reference tree. http://molevol.ibmb.csic.es/Ktreedist.html

  10. Triplet supertree heuristics for the tree of life

    PubMed Central

    Lin, Harris T; Burleigh, J Gordon; Eulenstein, Oliver

    2009-01-01

    Background There is much interest in developing fast and accurate supertree methods to infer the tree of life. Supertree methods combine smaller input trees with overlapping sets of taxa to make a comprehensive phylogenetic tree that contains all of the taxa in the input trees. The intrinsically hard triplet supertree problem takes a collection of input species trees and seeks a species tree (supertree) that maximizes the number of triplet subtrees that it shares with the input trees. However, the utility of this supertree problem has been limited by a lack of efficient and effective heuristics. Results We introduce fast hill-climbing heuristics for the triplet supertree problem that perform a step-wise search of the tree space, where each step is guided by an exact solution to an instance of a local search problem. To realize time efficient heuristics we designed the first nontrivial algorithms for two standard search problems, which greatly improve on the time complexity to the best known (naïve) solutions by a factor of n and n2 (the number of taxa in the supertree). These algorithms enable large-scale supertree analyses based on the triplet supertree problem that were previously not possible. We implemented hill-climbing heuristics that are based on our new algorithms, and in analyses of two published supertree data sets, we demonstrate that our new heuristics outperform other standard supertree methods in maximizing the number of triplets shared with the input trees. Conclusion With our new heuristics, the triplet supertree problem is now computationally more tractable for large-scale supertree analyses, and it provides a potentially more accurate alternative to existing supertree methods. PMID:19208181

  11. Simulating Urban Tree Effects on Air, Water, and Heat Pollution Mitigation: iTree-Hydro Model

    NASA Astrophysics Data System (ADS)

    Yang, Y.; Endreny, T. A.; Nowak, D.

    2011-12-01

    Urban and suburban development changes land surface thermal, radiative, porous, and roughness properties and pollutant loading rates, with the combined effect leading to increased air, water, and heat pollution (e.g., urban heat islands). In this research we present the USDA Forest Service urban forest ecosystem and hydrology model, iTree Eco and Hydro, used to analyze how tree cover can deliver valuable ecosystem services to mitigate air, water, and heat pollution. Air pollution mitigation is simulated by dry deposition processes based on detected pollutant levels for CO, NO2, SO2, O3 and atmospheric stability and leaf area indices. Water quality mitigation is simulated with event mean concentration loading algorithms for N, P, metals, and TSS, and by green infrastructure pollutant filtering algorithms that consider flow path dispersal areas. Urban cooling considers direct shading and indirect evapotranspiration. Spatially distributed estimates of hourly tree evapotranspiration during the growing season are used to estimate human thermal comfort. Two main factors regulating evapotranspiration are soil moisture and canopy radiation. Spatial variation of soil moisture is represented by a modified urban topographic index and radiation for each tree is modified by considering aspect, slope and shade from surrounding buildings or hills. We compare the urban cooling algorithms used in iTree-Hydro with the urban canopy and land surface physics schemes used in the Weather Research and Forecasting model. We conclude by identifying biophysical feedbacks between tree-modulated air and water quality environmental services and how these may respond to urban heating and cooling. Improvements to this iTree model are intended to assist managers identify valuable tree services for urban living.

  12. A combined NLP-differential evolution algorithm approach for the optimization of looped water distribution systems

    NASA Astrophysics Data System (ADS)

    Zheng, Feifei; Simpson, Angus R.; Zecchin, Aaron C.

    2011-08-01

    This paper proposes a novel optimization approach for the least cost design of looped water distribution systems (WDSs). Three distinct steps are involved in the proposed optimization approach. In the first step, the shortest-distance tree within the looped network is identified using the Dijkstra graph theory algorithm, for which an extension is proposed to find the shortest-distance tree for multisource WDSs. In the second step, a nonlinear programming (NLP) solver is employed to optimize the pipe diameters for the shortest-distance tree (chords of the shortest-distance tree are allocated the minimum allowable pipe sizes). Finally, in the third step, the original looped water network is optimized using a differential evolution (DE) algorithm seeded with diameters in the proximity of the continuous pipe sizes obtained in step two. As such, the proposed optimization approach combines the traditional deterministic optimization technique of NLP with the emerging evolutionary algorithm DE via the proposed network decomposition. The proposed methodology has been tested on four looped WDSs with the number of decision variables ranging from 21 to 454. Results obtained show the proposed approach is able to find optimal solutions with significantly less computational effort than other optimization techniques.

  13. Exploiting machine learning algorithms for tree species classification in a semiarid woodland using RapidEye image

    NASA Astrophysics Data System (ADS)

    Adelabu, Samuel; Mutanga, Onisimo; Adam, Elhadi; Cho, Moses Azong

    2013-01-01

    Classification of different tree species in semiarid areas can be challenging as a result of the change in leaf structure and orientation due to soil moisture constraints. Tree species mapping is, however, a key parameter for forest management in semiarid environments. In this study, we examined the suitability of 5-band RapidEye satellite data for the classification of five tree species in mopane woodland of Botswana using machine leaning algorithms with limited training samples.We performed classification using random forest (RF) and support vector machines (SVM) based on EnMap box. The overall accuracies for classifying the five tree species was 88.75 and 85% for both SVM and RF, respectively. We also demonstrated that the new red-edge band in the RapidEye sensor has the potential for classifying tree species in semiarid environments when integrated with other standard bands. Similarly, we observed that where there are limited training samples, SVM is preferred over RF. Finally, we demonstrated that the two accuracy measures of quantity and allocation disagreement are simpler and more helpful for the vast majority of remote sensing classification process than the kappa coefficient. Overall, high species classification can be achieved using strategically located RapidEye bands integrated with advanced processing algorithms.

  14. Binary tree eigen solver in finite element analysis

    NASA Technical Reports Server (NTRS)

    Akl, F. A.; Janetzke, D. C.; Kiraly, L. J.

    1993-01-01

    This paper presents a transputer-based binary tree eigensolver for the solution of the generalized eigenproblem in linear elastic finite element analysis. The algorithm is based on the method of recursive doubling, which parallel implementation of a number of associative operations on an arbitrary set having N elements is of the order of o(log2N), compared to (N-1) steps if implemented sequentially. The hardware used in the implementation of the binary tree consists of 32 transputers. The algorithm is written in OCCAM which is a high-level language developed with the transputers to address parallel programming constructs and to provide the communications between processors. The algorithm can be replicated to match the size of the binary tree transputer network. Parallel and sequential finite element analysis programs have been developed to solve for the set of the least-order eigenpairs using the modified subspace method. The speed-up obtained for a typical analysis problem indicates close agreement with the theoretical prediction given by the method of recursive doubling.

  15. Rapid Calculation of Max-Min Fair Rates for Multi-Commodity Flows in Fat-Tree Networks

    DOE PAGES

    Mollah, Md Atiqul; Yuan, Xin; Pakin, Scott; ...

    2017-08-29

    Max-min fairness is often used in the performance modeling of interconnection networks. Existing methods to compute max-min fair rates for multi-commodity flows have high complexity and are computationally infeasible for large networks. In this paper, we show that by considering topological features, this problem can be solved efficiently for the fat-tree topology that is widely used in data centers and high performance compute clusters. Several efficient new algorithms are developed for this problem, including a parallel algorithm that can take advantage of multi-core and shared-memory architectures. Using these algorithms, we demonstrate that it is possible to find the max-min fairmore » rate allocation for multi-commodity flows in fat-tree networks that support tens of thousands of nodes. We evaluate the run-time performance of the proposed algorithms and show improvement in orders of magnitude over the previously best known method. Finally, we further demonstrate a new application of max-min fair rate allocation that is only computationally feasible using our new algorithms.« less

  16. Rapid Calculation of Max-Min Fair Rates for Multi-Commodity Flows in Fat-Tree Networks

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

    Mollah, Md Atiqul; Yuan, Xin; Pakin, Scott

    Max-min fairness is often used in the performance modeling of interconnection networks. Existing methods to compute max-min fair rates for multi-commodity flows have high complexity and are computationally infeasible for large networks. In this paper, we show that by considering topological features, this problem can be solved efficiently for the fat-tree topology that is widely used in data centers and high performance compute clusters. Several efficient new algorithms are developed for this problem, including a parallel algorithm that can take advantage of multi-core and shared-memory architectures. Using these algorithms, we demonstrate that it is possible to find the max-min fairmore » rate allocation for multi-commodity flows in fat-tree networks that support tens of thousands of nodes. We evaluate the run-time performance of the proposed algorithms and show improvement in orders of magnitude over the previously best known method. Finally, we further demonstrate a new application of max-min fair rate allocation that is only computationally feasible using our new algorithms.« less

  17. A new method of optimal capacitor switching based on minimum spanning tree theory in distribution systems

    NASA Astrophysics Data System (ADS)

    Li, H. W.; Pan, Z. Y.; Ren, Y. B.; Wang, J.; Gan, Y. L.; Zheng, Z. Z.; Wang, W.

    2018-03-01

    According to the radial operation characteristics in distribution systems, this paper proposes a new method based on minimum spanning trees method for optimal capacitor switching. Firstly, taking the minimal active power loss as objective function and not considering the capacity constraints of capacitors and source, this paper uses Prim algorithm among minimum spanning trees algorithms to get the power supply ranges of capacitors and source. Then with the capacity constraints of capacitors considered, capacitors are ranked by the method of breadth-first search. In term of the order from high to low of capacitor ranking, capacitor compensation capacity based on their power supply range is calculated. Finally, IEEE 69 bus system is adopted to test the accuracy and practicality of the proposed algorithm.

  18. 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.

  19. The Proposal of a Evolutionary Strategy Generating the Data Structures Based on a Horizontal Tree for the Tests

    NASA Astrophysics Data System (ADS)

    Żukowicz, Marek; Markiewicz, Michał

    2016-09-01

    The aim of the article is to present a mathematical definition of the object model, that is known in computer science as TreeList and to show application of this model for design evolutionary algorithm, that purpose is to generate structures based on this object. The first chapter introduces the reader to the problem of presenting data using the TreeList object. The second chapter describes the problem of testing data structures based on TreeList. The third one shows a mathematical model of the object TreeList and the parameters, used in determining the utility of structures created through this model and in evolutionary strategy, that generates these structures for testing purposes. The last chapter provides a brief summary and plans for future research related to the algorithm presented in the article.

  20. Constraint Embedding Technique for Multibody System Dynamics

    NASA Technical Reports Server (NTRS)

    Woo, Simon S.; Cheng, Michael K.

    2011-01-01

    Multibody dynamics play a critical role in simulation testbeds for space missions. There has been a considerable interest in the development of efficient computational algorithms for solving the dynamics of multibody systems. Mass matrix factorization and inversion techniques and the O(N) class of forward dynamics algorithms developed using a spatial operator algebra stand out as important breakthrough on this front. Techniques such as these provide the efficient algorithms and methods for the application and implementation of such multibody dynamics models. However, these methods are limited only to tree-topology multibody systems. Closed-chain topology systems require different techniques that are not as efficient or as broad as those for tree-topology systems. The closed-chain forward dynamics approach consists of treating the closed-chain topology as a tree-topology system subject to additional closure constraints. The resulting forward dynamics solution consists of: (a) ignoring the closure constraints and using the O(N) algorithm to solve for the free unconstrained accelerations for the system; (b) using the tree-topology solution to compute a correction force to enforce the closure constraints; and (c) correcting the unconstrained accelerations with correction accelerations resulting from the correction forces. This constraint-embedding technique shows how to use direct embedding to eliminate local closure-loops in the system and effectively convert the system back to a tree-topology system. At this point, standard tree-topology techniques can be brought to bear on the problem. The approach uses a spatial operator algebra approach to formulating the equations of motion. The operators are block-partitioned around the local body subgroups to convert them into aggregate bodies. Mass matrix operator factorization and inversion techniques are applied to the reformulated tree-topology system. Thus in essence, the new technique allows conversion of a system with closure-constraints into an equivalent tree-topology system, and thus allows one to take advantage of the host of techniques available to the latter class of systems. This technology is highly suitable for the class of multibody systems where the closure-constraints are local, i.e., where they are confined to small groupings of bodies within the system. Important examples of such local closure-constraints are constraints associated with four-bar linkages, geared motors, differential suspensions, etc. One can eliminate these closure-constraints and convert the system into a tree-topology system by embedding the constraints directly into the system dynamics and effectively replacing the body groupings with virtual aggregate bodies. Once eliminated, one can apply the well-known results and algorithms for tree-topology systems to solve the dynamics of such closed-chain system.

  1. 76 FR 6500 - Self-Regulatory Organizations; Financial Industry Regulatory Authority, Inc.; Notice of Filing of...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-02-04

    ... Haigney comment, Sutherland comment, Black and Gross comment, Berg comment, PIABA comment; St. John's..., Steiner comment, Chalmers comment, Gladden comment, Estell comment, Sutherland comment, Furgison comment...

  2. Global interrupt and barrier networks

    DOEpatents

    Blumrich, Matthias A.; Chen, Dong; Coteus, Paul W.; Gara, Alan G.; Giampapa, Mark E; Heidelberger, Philip; Kopcsay, Gerard V.; Steinmacher-Burow, Burkhard D.; Takken, Todd E.

    2008-10-28

    A system and method for generating global asynchronous signals in a computing structure. Particularly, a global interrupt and barrier network is implemented that implements logic for generating global interrupt and barrier signals for controlling global asynchronous operations performed by processing elements at selected processing nodes of a computing structure in accordance with a processing algorithm; and includes the physical interconnecting of the processing nodes for communicating the global interrupt and barrier signals to the elements via low-latency paths. The global asynchronous signals respectively initiate interrupt and barrier operations at the processing nodes at times selected for optimizing performance of the processing algorithms. In one embodiment, the global interrupt and barrier network is implemented in a scalable, massively parallel supercomputing device structure comprising a plurality of processing nodes interconnected by multiple independent networks, with each node including one or more processing elements for performing computation or communication activity as required when performing parallel algorithm operations. One multiple independent network includes a global tree network for enabling high-speed global tree communications among global tree network nodes or sub-trees thereof. The global interrupt and barrier network may operate in parallel with the global tree network for providing global asynchronous sideband signals.

  3. Cost-effectiveness Analysis with Influence Diagrams.

    PubMed

    Arias, M; Díez, F J

    2015-01-01

    Cost-effectiveness analysis (CEA) is used increasingly in medicine to determine whether the health benefit of an intervention is worth the economic cost. Decision trees, the standard decision modeling technique for non-temporal domains, can only perform CEA for very small problems. To develop a method for CEA in problems involving several dozen variables. We explain how to build influence diagrams (IDs) that explicitly represent cost and effectiveness. We propose an algorithm for evaluating cost-effectiveness IDs directly, i.e., without expanding an equivalent decision tree. The evaluation of an ID returns a set of intervals for the willingness to pay - separated by cost-effectiveness thresholds - and, for each interval, the cost, the effectiveness, and the optimal intervention. The algorithm that evaluates the ID directly is in general much more efficient than the brute-force method, which is in turn more efficient than the expansion of an equivalent decision tree. Using OpenMarkov, an open-source software tool that implements this algorithm, we have been able to perform CEAs on several IDs whose equivalent decision trees contain millions of branches. IDs can perform CEA on large problems that cannot be analyzed with decision trees.

  4. Tanglegrams for rooted phylogenetic trees and networks

    PubMed Central

    Scornavacca, Celine; Zickmann, Franziska; Huson, Daniel H.

    2011-01-01

    Motivation: In systematic biology, one is often faced with the task of comparing different phylogenetic trees, in particular in multi-gene analysis or cospeciation studies. One approach is to use a tanglegram in which two rooted phylogenetic trees are drawn opposite each other, using auxiliary lines to connect matching taxa. There is an increasing interest in using rooted phylogenetic networks to represent evolutionary history, so as to explicitly represent reticulate events, such as horizontal gene transfer, hybridization or reassortment. Thus, the question arises how to define and compute a tanglegram for such networks. Results: In this article, we present the first formal definition of a tanglegram for rooted phylogenetic networks and present a heuristic approach for computing one, called the NN-tanglegram method. We compare the performance of our method with existing tree tanglegram algorithms and also show a typical application to real biological datasets. For maximum usability, the algorithm does not require that the trees or networks are bifurcating or bicombining, or that they are on identical taxon sets. Availability: The algorithm is implemented in our program Dendroscope 3, which is freely available from www.dendroscope.org. Contact: scornava@informatik.uni-tuebingen.de; huson@informatik.uni-tuebingen.de PMID:21685078

  5. Consensus properties and their large-scale applications for the gene duplication problem.

    PubMed

    Moon, Jucheol; Lin, Harris T; Eulenstein, Oliver

    2016-06-01

    Solving the gene duplication problem is a classical approach for species tree inference from gene trees that are confounded by gene duplications. This problem takes a collection of gene trees and seeks a species tree that implies the minimum number of gene duplications. Wilkinson et al. posed the conjecture that the gene duplication problem satisfies the desirable Pareto property for clusters. That is, for every instance of the problem, all clusters that are commonly present in the input gene trees of this instance, called strict consensus, will also be found in every solution to this instance. We prove that this conjecture does not generally hold. Despite this negative result we show that the gene duplication problem satisfies a weaker version of the Pareto property where the strict consensus is found in at least one solution (rather than all solutions). This weaker property contributes to our design of an efficient scalable algorithm for the gene duplication problem. We demonstrate the performance of our algorithm in analyzing large-scale empirical datasets. Finally, we utilize the algorithm to evaluate the accuracy of standard heuristics for the gene duplication problem using simulated datasets.

  6. Node Deployment Algorithm Based on Connected Tree for Underwater Sensor Networks

    PubMed Central

    Jiang, Peng; Wang, Xingmin; Jiang, Lurong

    2015-01-01

    Designing an efficient deployment method to guarantee optimal monitoring quality is one of the key topics in underwater sensor networks. At present, a realistic approach of deployment involves adjusting the depths of nodes in water. One of the typical algorithms used in such process is the self-deployment depth adjustment algorithm (SDDA). This algorithm mainly focuses on maximizing network coverage by constantly adjusting node depths to reduce coverage overlaps between two neighboring nodes, and thus, achieves good performance. However, the connectivity performance of SDDA is irresolute. In this paper, we propose a depth adjustment algorithm based on connected tree (CTDA). In CTDA, the sink node is used as the first root node to start building a connected tree. Finally, the network can be organized as a forest to maintain network connectivity. Coverage overlaps between the parent node and the child node are then reduced within each sub-tree to optimize coverage. The hierarchical strategy is used to adjust the distance between the parent node and the child node to reduce node movement. Furthermore, the silent mode is adopted to reduce communication cost. Simulations show that compared with SDDA, CTDA can achieve high connectivity with various communication ranges and different numbers of nodes. Moreover, it can realize coverage as high as that of SDDA with various sensing ranges and numbers of nodes but with less energy consumption. Simulations under sparse environments show that the connectivity and energy consumption performances of CTDA are considerably better than those of SDDA. Meanwhile, the connectivity and coverage performances of CTDA are close to those depth adjustment algorithms base on connected dominating set (CDA), which is an algorithm similar to CTDA. However, the energy consumption of CTDA is less than that of CDA, particularly in sparse underwater environments. PMID:26184209

  7. Amazon Forest Structure from IKONOS Satellite Data and the Automated Characterization of Forest Canopy Properties

    Treesearch

    Michael Palace; Michael Keller; Gregory P. Asner; Stephen Hagen; Bobby Braswell

    2008-01-01

    We developed an automated tree crown analysis algorithm using 1-m panchromatic IKONOS satellite images to examine forest canopy structure in the Brazilian Amazon. The algorithm was calibrated on the landscape level with tree geometry and forest stand data at the Fazenda Cauaxi (3.75◦ S, 48.37◦ W) in the eastern Amazon, and then compared with forest...

  8. Vlsi implementation of flexible architecture for decision tree classification in data mining

    NASA Astrophysics Data System (ADS)

    Sharma, K. Venkatesh; Shewandagn, Behailu; Bhukya, Shankar Nayak

    2017-07-01

    The Data mining algorithms have become vital to researchers in science, engineering, medicine, business, search and security domains. In recent years, there has been a terrific raise in the size of the data being collected and analyzed. Classification is the main difficulty faced in data mining. In a number of the solutions developed for this problem, most accepted one is Decision Tree Classification (DTC) that gives high precision while handling very large amount of data. This paper presents VLSI implementation of flexible architecture for Decision Tree classification in data mining using c4.5 algorithm.

  9. Logistic regression trees for initial selection of interesting loci in case-control studies

    PubMed Central

    Nickolov, Radoslav Z; Milanov, Valentin B

    2007-01-01

    Modern genetic epidemiology faces the challenge of dealing with hundreds of thousands of genetic markers. The selection of a small initial subset of interesting markers for further investigation can greatly facilitate genetic studies. In this contribution we suggest the use of a logistic regression tree algorithm known as logistic tree with unbiased selection. Using the simulated data provided for Genetic Analysis Workshop 15, we show how this algorithm, with incorporation of multifactor dimensionality reduction method, can reduce an initial large pool of markers to a small set that includes the interesting markers with high probability. PMID:18466557

  10. An IPv6 routing lookup algorithm using weight-balanced tree based on prefix value for virtual router

    NASA Astrophysics Data System (ADS)

    Chen, Lingjiang; Zhou, Shuguang; Zhang, Qiaoduo; Li, Fenghua

    2016-10-01

    Virtual router enables the coexistence of different networks on the same physical facility and has lately attracted a great deal of attention from researchers. As the number of IPv6 addresses is rapidly increasing in virtual routers, designing an efficient IPv6 routing lookup algorithm is of great importance. In this paper, we present an IPv6 lookup algorithm called weight-balanced tree (WBT). WBT merges Forwarding Information Bases (FIBs) of virtual routers into one spanning tree, and compresses the space cost. WBT's average time complexity and the worst case time complexity of lookup and update process are both O(logN) and space complexity is O(cN) where N is the size of routing table and c is a constant. Experiments show that WBT helps reduce more than 80% Static Random Access Memory (SRAM) cost in comparison to those separation schemes. WBT also achieves the least average search depth comparing with other homogeneous algorithms.

  11. Multipoint to multipoint routing and wavelength assignment in multi-domain optical networks

    NASA Astrophysics Data System (ADS)

    Qin, Panke; Wu, Jingru; Li, Xudong; Tang, Yongli

    2018-01-01

    In multi-point to multi-point (MP2MP) routing and wavelength assignment (RWA) problems, researchers usually assume the optical networks to be a single domain. However, the optical networks develop toward to multi-domain and larger scale in practice. In this context, multi-core shared tree (MST)-based MP2MP RWA are introduced problems including optimal multicast domain sequence selection, core nodes belonging in which domains and so on. In this letter, we focus on MST-based MP2MP RWA problems in multi-domain optical networks, mixed integer linear programming (MILP) formulations to optimally construct MP2MP multicast trees is presented. A heuristic algorithm base on network virtualization and weighted clustering algorithm (NV-WCA) is proposed. Simulation results show that, under different traffic patterns, the proposed algorithm achieves significant improvement on network resources occupation and multicast trees setup latency in contrast with the conventional algorithms which were proposed base on a single domain network environment.

  12. Combinatorics of least-squares trees.

    PubMed

    Mihaescu, Radu; Pachter, Lior

    2008-09-09

    A recurring theme in the least-squares approach to phylogenetics has been the discovery of elegant combinatorial formulas for the least-squares estimates of edge lengths. These formulas have proved useful for the development of efficient algorithms, and have also been important for understanding connections among popular phylogeny algorithms. For example, the selection criterion of the neighbor-joining algorithm is now understood in terms of the combinatorial formulas of Pauplin for estimating tree length. We highlight a phylogenetically desirable property that weighted least-squares methods should satisfy, and provide a complete characterization of methods that satisfy the property. The necessary and sufficient condition is a multiplicative four-point condition that the variance matrix needs to satisfy. The proof is based on the observation that the Lagrange multipliers in the proof of the Gauss-Markov theorem are tree-additive. Our results generalize and complete previous work on ordinary least squares, balanced minimum evolution, and the taxon-weighted variance model. They also provide a time-optimal algorithm for computation.

  13. Application of decision tree model for the ground subsidence hazard mapping near abandoned underground coal mines.

    PubMed

    Lee, Saro; Park, Inhye

    2013-09-30

    Subsidence of ground caused by underground mines poses hazards to human life and property. This study analyzed the hazard to ground subsidence using factors that can affect ground subsidence and a decision tree approach in a geographic information system (GIS). The study area was Taebaek, Gangwon-do, Korea, where many abandoned underground coal mines exist. Spatial data, topography, geology, and various ground-engineering data for the subsidence area were collected and compiled in a database for mapping ground-subsidence hazard (GSH). The subsidence area was randomly split 50/50 for training and validation of the models. A data-mining classification technique was applied to the GSH mapping, and decision trees were constructed using the chi-squared automatic interaction detector (CHAID) and the quick, unbiased, and efficient statistical tree (QUEST) algorithms. The frequency ratio model was also applied to the GSH mapping for comparing with probabilistic model. The resulting GSH maps were validated using area-under-the-curve (AUC) analysis with the subsidence area data that had not been used for training the model. The highest accuracy was achieved by the decision tree model using CHAID algorithm (94.01%) comparing with QUEST algorithms (90.37%) and frequency ratio model (86.70%). These accuracies are higher than previously reported results for decision tree. Decision tree methods can therefore be used efficiently for GSH analysis and might be widely used for prediction of various spatial events. Copyright © 2013. Published by Elsevier Ltd.

  14. An Isometric Mapping Based Co-Location Decision Tree Algorithm

    NASA Astrophysics Data System (ADS)

    Zhou, G.; Wei, J.; Zhou, X.; Zhang, R.; Huang, W.; Sha, H.; Chen, J.

    2018-05-01

    Decision tree (DT) induction has been widely used in different pattern classification. However, most traditional DTs have the disadvantage that they consider only non-spatial attributes (ie, spectral information) as a result of classifying pixels, which can result in objects being misclassified. Therefore, some researchers have proposed a co-location decision tree (Cl-DT) method, which combines co-location and decision tree to solve the above the above-mentioned traditional decision tree problems. Cl-DT overcomes the shortcomings of the existing DT algorithms, which create a node for each value of a given attribute, which has a higher accuracy than the existing decision tree approach. However, for non-linearly distributed data instances, the euclidean distance between instances does not reflect the true positional relationship between them. In order to overcome these shortcomings, this paper proposes an isometric mapping method based on Cl-DT (called, (Isomap-based Cl-DT), which is a method that combines heterogeneous and Cl-DT together. Because isometric mapping methods use geodetic distances instead of Euclidean distances between non-linearly distributed instances, the true distance between instances can be reflected. The experimental results and several comparative analyzes show that: (1) The extraction method of exposed carbonate rocks is of high accuracy. (2) The proposed method has many advantages, because the total number of nodes, the number of leaf nodes and the number of nodes are greatly reduced compared to Cl-DT. Therefore, the Isomap -based Cl-DT algorithm can construct a more accurate and faster decision tree.

  15. Automated Reconstruction of Neural Trees Using Front Re-initialization

    PubMed Central

    Mukherjee, Amit; Stepanyants, Armen

    2013-01-01

    This paper proposes a greedy algorithm for automated reconstruction of neural arbors from light microscopy stacks of images. The algorithm is based on the minimum cost path method. While the minimum cost path, obtained using the Fast Marching Method, results in a trace with the least cumulative cost between the start and the end points, it is not sufficient for the reconstruction of neural trees. This is because sections of the minimum cost path can erroneously travel through the image background with undetectable detriment to the cumulative cost. To circumvent this problem we propose an algorithm that grows a neural tree from a specified root by iteratively re-initializing the Fast Marching fronts. The speed image used in the Fast Marching Method is generated by computing the average outward flux of the gradient vector flow field. Each iteration of the algorithm produces a candidate extension by allowing the front to travel a specified distance and then tracking from the farthest point of the front back to the tree. Robust likelihood ratio test is used to evaluate the quality of the candidate extension by comparing voxel intensities along the extension to those in the foreground and the background. The qualified extensions are appended to the current tree, the front is re-initialized, and Fast Marching is continued until the stopping criterion is met. To evaluate the performance of the algorithm we reconstructed 6 stacks of two-photon microscopy images and compared the results to the ground truth reconstructions by using the DIADEM metric. The average comparison score was 0.82 out of 1.0, which is on par with the performance achieved by expert manual tracers. PMID:24386539

  16. Secure Multicast Tree Structure Generation Method for Directed Diffusion Using A* Algorithms

    NASA Astrophysics Data System (ADS)

    Kim, Jin Myoung; Lee, Hae Young; Cho, Tae Ho

    The application of wireless sensor networks to areas such as combat field surveillance, terrorist tracking, and highway traffic monitoring requires secure communication among the sensor nodes within the networks. Logical key hierarchy (LKH) is a tree based key management model which provides secure group communication. When a sensor node is added or evicted from the communication group, LKH updates the group key in order to ensure the security of the communications. In order to efficiently update the group key in directed diffusion, we propose a method for secure multicast tree structure generation, an extension to LKH that reduces the number of re-keying messages by considering the addition and eviction ratios of the history data. For the generation of the proposed key tree structure the A* algorithm is applied, in which the branching factor at each level can take on different value. The experiment results demonstrate the efficiency of the proposed key tree structure against the existing key tree structures of fixed branching factors.

  17. Owen Chamberlain, the Antiproton, and Polarized Targets

    Science.gov Websites

    allowed us to test the symmetry principles underlying the physics," [colleague Herbert Steiner] said . Symmetry principles state, for example, that some interactions look the same when reflected in a mirror or

  18. Genetics Home Reference: spondylocarpotarsal synostosis syndrome

    MedlinePlus

    ... active (expressed) in the cell membranes of cartilage-forming cells (chondrocytes). Cartilage is a tough, flexible tissue ... D, Shapiro SS, Takafuta T, Aftimos S, Kim CA, Firth H, Steiner CE, Cormier-Daire V, Superti-Furga A, ...

  19. The Austrian Approach: Entering the World of Children.

    ERIC Educational Resources Information Center

    Feistritzer, Patricia; Balcerack, Carl

    1979-01-01

    This photo-essay describes a Waldorf School. Developed by Austrian Rudolf Steiner, the Waldorf plan is dedicated to allowing the child a childlike environment. It emphasizes storytelling, creative dramatics, flexibility, improvisation, crafts, and movement. (SJL)

  20. Comparison of rule induction, decision trees and formal concept analysis approaches for classification

    NASA Astrophysics Data System (ADS)

    Kotelnikov, E. V.; Milov, V. R.

    2018-05-01

    Rule-based learning algorithms have higher transparency and easiness to interpret in comparison with neural networks and deep learning algorithms. These properties make it possible to effectively use such algorithms to solve descriptive tasks of data mining. The choice of an algorithm depends also on its ability to solve predictive tasks. The article compares the quality of the solution of the problems with binary and multiclass classification based on the experiments with six datasets from the UCI Machine Learning Repository. The authors investigate three algorithms: Ripper (rule induction), C4.5 (decision trees), In-Close (formal concept analysis). The results of the experiments show that In-Close demonstrates the best quality of classification in comparison with Ripper and C4.5, however the latter two generate more compact rule sets.

  1. A junction-tree based learning algorithm to optimize network wide traffic control: A coordinated multi-agent framework

    DOE PAGES

    Zhu, Feng; Aziz, H. M. Abdul; Qian, Xinwu; ...

    2015-01-31

    Our study develops a novel reinforcement learning algorithm for the challenging coordinated signal control problem. Traffic signals are modeled as intelligent agents interacting with the stochastic traffic environment. The model is built on the framework of coordinated reinforcement learning. The Junction Tree Algorithm (JTA) based reinforcement learning is proposed to obtain an exact inference of the best joint actions for all the coordinated intersections. Moreover, the algorithm is implemented and tested with a network containing 18 signalized intersections in VISSIM. Finally, our results show that the JTA based algorithm outperforms independent learning (Q-learning), real-time adaptive learning, and fixed timing plansmore » in terms of average delay, number of stops, and vehicular emissions at the network level.« less

  2. Applied Swarm-based medicine: collecting decision trees for patterns of algorithms analysis.

    PubMed

    Panje, Cédric M; Glatzer, Markus; von Rappard, Joscha; Rothermundt, Christian; Hundsberger, Thomas; Zumstein, Valentin; Plasswilm, Ludwig; Putora, Paul Martin

    2017-08-16

    The objective consensus methodology has recently been applied in consensus finding in several studies on medical decision-making among clinical experts or guidelines. The main advantages of this method are an automated analysis and comparison of treatment algorithms of the participating centers which can be performed anonymously. Based on the experience from completed consensus analyses, the main steps for the successful implementation of the objective consensus methodology were identified and discussed among the main investigators. The following steps for the successful collection and conversion of decision trees were identified and defined in detail: problem definition, population selection, draft input collection, tree conversion, criteria adaptation, problem re-evaluation, results distribution and refinement, tree finalisation, and analysis. This manuscript provides information on the main steps for successful collection of decision trees and summarizes important aspects at each point of the analysis.

  3. Prediction of Baseflow Index of Catchments using Machine Learning Algorithms

    NASA Astrophysics Data System (ADS)

    Yadav, B.; Hatfield, K.

    2017-12-01

    We present the results of eight machine learning techniques for predicting the baseflow index (BFI) of ungauged basins using a surrogate of catchment scale climate and physiographic data. The tested algorithms include ordinary least squares, ridge regression, least absolute shrinkage and selection operator (lasso), elasticnet, support vector machine, gradient boosted regression trees, random forests, and extremely randomized trees. Our work seeks to identify the dominant controls of BFI that can be readily obtained from ancillary geospatial databases and remote sensing measurements, such that the developed techniques can be extended to ungauged catchments. More than 800 gauged catchments spanning the continental United States were selected to develop the general methodology. The BFI calculation was based on the baseflow separated from daily streamflow hydrograph using HYSEP filter. The surrogate catchment attributes were compiled from multiple sources including digital elevation model, soil, landuse, climate data, other publicly available ancillary and geospatial data. 80% catchments were used to train the ML algorithms, and the remaining 20% of the catchments were used as an independent test set to measure the generalization performance of fitted models. A k-fold cross-validation using exhaustive grid search was used to fit the hyperparameters of each model. Initial model development was based on 19 independent variables, but after variable selection and feature ranking, we generated revised sparse models of BFI prediction that are based on only six catchment attributes. These key predictive variables selected after the careful evaluation of bias-variance tradeoff include average catchment elevation, slope, fraction of sand, permeability, temperature, and precipitation. The most promising algorithms exceeding an accuracy score (r-square) of 0.7 on test data include support vector machine, gradient boosted regression trees, random forests, and extremely randomized trees. Considering both the accuracy and the computational complexity of these algorithms, we identify the extremely randomized trees as the best performing algorithm for BFI prediction in ungauged basins.

  4. A decision tree algorithm for investigation of model biases related to dynamical cores and physical parameterizations: CESM/CAM EVALUATION BY DECISION TREES

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

    Soner Yorgun, M.; Rood, Richard B.

    An object-based evaluation method using a pattern recognition algorithm (i.e., classification trees) is applied to the simulated orographic precipitation for idealized experimental setups using the National Center of Atmospheric Research (NCAR) Community Atmosphere Model (CAM) with the finite volume (FV) and the Eulerian spectral transform dynamical cores with varying resolutions. Daily simulations were analyzed and three different types of precipitation features were identified by the classification tree algorithm. The statistical characteristics of these features (i.e., maximum value, mean value, and variance) were calculated to quantify the difference between the dynamical cores and changing resolutions. Even with the simple and smoothmore » topography in the idealized setups, complexity in the precipitation fields simulated by the models develops quickly. The classification tree algorithm using objective thresholding successfully detected different types of precipitation features even as the complexity of the precipitation field increased. The results show that the complexity and the bias introduced in small-scale phenomena due to the spectral transform method of CAM Eulerian spectral dynamical core is prominent, and is an important reason for its dissimilarity from the FV dynamical core. The resolvable scales, both in horizontal and vertical dimensions, have significant effect on the simulation of precipitation. The results of this study also suggest that an efficient and informative study about the biases produced by GCMs should involve daily (or even hourly) output (rather than monthly mean) analysis over local scales.« less

  5. A decision tree algorithm for investigation of model biases related to dynamical cores and physical parameterizations: CESM/CAM EVALUATION BY DECISION TREES

    DOE PAGES

    Soner Yorgun, M.; Rood, Richard B.

    2016-11-11

    An object-based evaluation method using a pattern recognition algorithm (i.e., classification trees) is applied to the simulated orographic precipitation for idealized experimental setups using the National Center of Atmospheric Research (NCAR) Community Atmosphere Model (CAM) with the finite volume (FV) and the Eulerian spectral transform dynamical cores with varying resolutions. Daily simulations were analyzed and three different types of precipitation features were identified by the classification tree algorithm. The statistical characteristics of these features (i.e., maximum value, mean value, and variance) were calculated to quantify the difference between the dynamical cores and changing resolutions. Even with the simple and smoothmore » topography in the idealized setups, complexity in the precipitation fields simulated by the models develops quickly. The classification tree algorithm using objective thresholding successfully detected different types of precipitation features even as the complexity of the precipitation field increased. The results show that the complexity and the bias introduced in small-scale phenomena due to the spectral transform method of CAM Eulerian spectral dynamical core is prominent, and is an important reason for its dissimilarity from the FV dynamical core. The resolvable scales, both in horizontal and vertical dimensions, have significant effect on the simulation of precipitation. The results of this study also suggest that an efficient and informative study about the biases produced by GCMs should involve daily (or even hourly) output (rather than monthly mean) analysis over local scales.« less

  6. 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.

  7. 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

  8. Resolution of the 1D regularized Burgers equation using a spatial wavelet approximation

    NASA Technical Reports Server (NTRS)

    Liandrat, J.; Tchamitchian, PH.

    1990-01-01

    The Burgers equation with a small viscosity term, initial and periodic boundary conditions is resolved using a spatial approximation constructed from an orthonormal basis of wavelets. The algorithm is directly derived from the notions of multiresolution analysis and tree algorithms. Before the numerical algorithm is described these notions are first recalled. The method uses extensively the localization properties of the wavelets in the physical and Fourier spaces. Moreover, the authors take advantage of the fact that the involved linear operators have constant coefficients. Finally, the algorithm can be considered as a time marching version of the tree algorithm. The most important point is that an adaptive version of the algorithm exists: it allows one to reduce in a significant way the number of degrees of freedom required for a good computation of the solution. Numerical results and description of the different elements of the algorithm are provided in combination with different mathematical comments on the method and some comparison with more classical numerical algorithms.

  9. A High Performance Computing Approach to Tree Cover Delineation in 1-m NAIP Imagery Using a Probabilistic Learning Framework

    NASA Technical Reports Server (NTRS)

    Basu, Saikat; Ganguly, Sangram; Michaelis, Andrew; Votava, Petr; Roy, Anshuman; Mukhopadhyay, Supratik; Nemani, Ramakrishna

    2015-01-01

    Tree cover delineation is a useful instrument in deriving Above Ground Biomass (AGB) density estimates from Very High Resolution (VHR) airborne imagery data. Numerous algorithms have been designed to address this problem, but most of them do not scale to these datasets, which are of the order of terabytes. In this paper, we present a semi-automated probabilistic framework for the segmentation and classification of 1-m National Agriculture Imagery Program (NAIP) for tree-cover delineation for the whole of Continental United States, using a High Performance Computing Architecture. Classification is performed using a multi-layer Feedforward Backpropagation Neural Network and segmentation is performed using a Statistical Region Merging algorithm. The results from the classification and segmentation algorithms are then consolidated into a structured prediction framework using a discriminative undirected probabilistic graphical model based on Conditional Random Field, which helps in capturing the higher order contextual dependencies between neighboring pixels. Once the final probability maps are generated, the framework is updated and re-trained by relabeling misclassified image patches. This leads to a significant improvement in the true positive rates and reduction in false positive rates. The tree cover maps were generated for the whole state of California, spanning a total of 11,095 NAIP tiles covering a total geographical area of 163,696 sq. miles. The framework produced true positive rates of around 88% for fragmented forests and 74% for urban tree cover areas, with false positive rates lower than 2% for both landscapes. Comparative studies with the National Land Cover Data (NLCD) algorithm and the LiDAR canopy height model (CHM) showed the effectiveness of our framework for generating accurate high-resolution tree-cover maps.

  10. A High Performance Computing Approach to Tree Cover Delineation in 1-m NAIP Imagery using a Probabilistic Learning Framework

    NASA Astrophysics Data System (ADS)

    Basu, S.; Ganguly, S.; Michaelis, A.; Votava, P.; Roy, A.; Mukhopadhyay, S.; Nemani, R. R.

    2015-12-01

    Tree cover delineation is a useful instrument in deriving Above Ground Biomass (AGB) density estimates from Very High Resolution (VHR) airborne imagery data. Numerous algorithms have been designed to address this problem, but most of them do not scale to these datasets which are of the order of terabytes. In this paper, we present a semi-automated probabilistic framework for the segmentation and classification of 1-m National Agriculture Imagery Program (NAIP) for tree-cover delineation for the whole of Continental United States, using a High Performance Computing Architecture. Classification is performed using a multi-layer Feedforward Backpropagation Neural Network and segmentation is performed using a Statistical Region Merging algorithm. The results from the classification and segmentation algorithms are then consolidated into a structured prediction framework using a discriminative undirected probabilistic graphical model based on Conditional Random Field, which helps in capturing the higher order contextual dependencies between neighboring pixels. Once the final probability maps are generated, the framework is updated and re-trained by relabeling misclassified image patches. This leads to a significant improvement in the true positive rates and reduction in false positive rates. The tree cover maps were generated for the whole state of California, spanning a total of 11,095 NAIP tiles covering a total geographical area of 163,696 sq. miles. The framework produced true positive rates of around 88% for fragmented forests and 74% for urban tree cover areas, with false positive rates lower than 2% for both landscapes. Comparative studies with the National Land Cover Data (NLCD) algorithm and the LiDAR canopy height model (CHM) showed the effectiveness of our framework for generating accurate high-resolution tree-cover maps.

  11. hs-CRP is strongly associated with coronary heart disease (CHD): A data mining approach using decision tree algorithm.

    PubMed

    Tayefi, Maryam; Tajfard, Mohammad; Saffar, Sara; Hanachi, Parichehr; Amirabadizadeh, Ali Reza; Esmaeily, Habibollah; Taghipour, Ali; Ferns, Gordon A; Moohebati, Mohsen; Ghayour-Mobarhan, Majid

    2017-04-01

    Coronary heart disease (CHD) is an important public health problem globally. Algorithms incorporating the assessment of clinical biomarkers together with several established traditional risk factors can help clinicians to predict CHD and support clinical decision making with respect to interventions. Decision tree (DT) is a data mining model for extracting hidden knowledge from large databases. We aimed to establish a predictive model for coronary heart disease using a decision tree algorithm. Here we used a dataset of 2346 individuals including 1159 healthy participants and 1187 participant who had undergone coronary angiography (405 participants with negative angiography and 782 participants with positive angiography). We entered 10 variables of a total 12 variables into the DT algorithm (including age, sex, FBG, TG, hs-CRP, TC, HDL, LDL, SBP and DBP). Our model could identify the associated risk factors of CHD with sensitivity, specificity, accuracy of 96%, 87%, 94% and respectively. Serum hs-CRP levels was at top of the tree in our model, following by FBG, gender and age. Our model appears to be an accurate, specific and sensitive model for identifying the presence of CHD, but will require validation in prospective studies. Copyright © 2017 Elsevier B.V. All rights reserved.

  12. A Depth-Adjustment Deployment Algorithm Based on Two-Dimensional Convex Hull and Spanning Tree for Underwater Wireless Sensor Networks.

    PubMed

    Jiang, Peng; Liu, Shuai; Liu, Jun; Wu, Feng; Zhang, Le

    2016-07-14

    Most of the existing node depth-adjustment deployment algorithms for underwater wireless sensor networks (UWSNs) just consider how to optimize network coverage and connectivity rate. However, these literatures don't discuss full network connectivity, while optimization of network energy efficiency and network reliability are vital topics for UWSN deployment. Therefore, in this study, a depth-adjustment deployment algorithm based on two-dimensional (2D) convex hull and spanning tree (NDACS) for UWSNs is proposed. First, the proposed algorithm uses the geometric characteristics of a 2D convex hull and empty circle to find the optimal location of a sleep node and activate it, minimizes the network coverage overlaps of the 2D plane, and then increases the coverage rate until the first layer coverage threshold is reached. Second, the sink node acts as a root node of all active nodes on the 2D convex hull and then forms a small spanning tree gradually. Finally, the depth-adjustment strategy based on time marker is used to achieve the three-dimensional overall network deployment. Compared with existing depth-adjustment deployment algorithms, the simulation results show that the NDACS algorithm can maintain full network connectivity with high network coverage rate, as well as improved network average node degree, thus increasing network reliability.

  13. A Depth-Adjustment Deployment Algorithm Based on Two-Dimensional Convex Hull and Spanning Tree for Underwater Wireless Sensor Networks

    PubMed Central

    Jiang, Peng; Liu, Shuai; Liu, Jun; Wu, Feng; Zhang, Le

    2016-01-01

    Most of the existing node depth-adjustment deployment algorithms for underwater wireless sensor networks (UWSNs) just consider how to optimize network coverage and connectivity rate. However, these literatures don’t discuss full network connectivity, while optimization of network energy efficiency and network reliability are vital topics for UWSN deployment. Therefore, in this study, a depth-adjustment deployment algorithm based on two-dimensional (2D) convex hull and spanning tree (NDACS) for UWSNs is proposed. First, the proposed algorithm uses the geometric characteristics of a 2D convex hull and empty circle to find the optimal location of a sleep node and activate it, minimizes the network coverage overlaps of the 2D plane, and then increases the coverage rate until the first layer coverage threshold is reached. Second, the sink node acts as a root node of all active nodes on the 2D convex hull and then forms a small spanning tree gradually. Finally, the depth-adjustment strategy based on time marker is used to achieve the three-dimensional overall network deployment. Compared with existing depth-adjustment deployment algorithms, the simulation results show that the NDACS algorithm can maintain full network connectivity with high network coverage rate, as well as improved network average node degree, thus increasing network reliability. PMID:27428970

  14. AntiClustal: Multiple Sequence Alignment by antipole clustering and linear approximate 1-median computation.

    PubMed

    Di Pietro, C; Di Pietro, V; Emmanuele, G; Ferro, A; Maugeri, T; Modica, E; Pigola, G; Pulvirenti, A; Purrello, M; Ragusa, M; Scalia, M; Shasha, D; Travali, S; Zimmitti, V

    2003-01-01

    In this paper we present a new Multiple Sequence Alignment (MSA) algorithm called AntiClusAl. The method makes use of the commonly use idea of aligning homologous sequences belonging to classes generated by some clustering algorithm, and then continue the alignment process ina bottom-up way along a suitable tree structure. The final result is then read at the root of the tree. Multiple sequence alignment in each cluster makes use of the progressive alignment with the 1-median (center) of the cluster. The 1-median of set S of sequences is the element of S which minimizes the average distance from any other sequence in S. Its exact computation requires quadratic time. The basic idea of our proposed algorithm is to make use of a simple and natural algorithmic technique based on randomized tournaments which has been successfully applied to large size search problems in general metric spaces. In particular a clustering algorithm called Antipole tree and an approximate linear 1-median computation are used. Our algorithm compared with Clustal W, a widely used tool to MSA, shows a better running time results with fully comparable alignment quality. A successful biological application showing high aminoacid conservation during evolution of Xenopus laevis SOD2 is also cited.

  15. How Hierarchical Topics Evolve in Large Text Corpora.

    PubMed

    Cui, Weiwei; Liu, Shixia; Wu, Zhuofeng; Wei, Hao

    2014-12-01

    Using a sequence of topic trees to organize documents is a popular way to represent hierarchical and evolving topics in text corpora. However, following evolving topics in the context of topic trees remains difficult for users. To address this issue, we present an interactive visual text analysis approach to allow users to progressively explore and analyze the complex evolutionary patterns of hierarchical topics. The key idea behind our approach is to exploit a tree cut to approximate each tree and allow users to interactively modify the tree cuts based on their interests. In particular, we propose an incremental evolutionary tree cut algorithm with the goal of balancing 1) the fitness of each tree cut and the smoothness between adjacent tree cuts; 2) the historical and new information related to user interests. A time-based visualization is designed to illustrate the evolving topics over time. To preserve the mental map, we develop a stable layout algorithm. As a result, our approach can quickly guide users to progressively gain profound insights into evolving hierarchical topics. We evaluate the effectiveness of the proposed method on Amazon's Mechanical Turk and real-world news data. The results show that users are able to successfully analyze evolving topics in text data.

  16. Detection of dead standing Eucalyptus camaldulensis without tree delineation for managing biodiversity in native Australian forest

    NASA Astrophysics Data System (ADS)

    Miltiadou, Milto; Campbell, Neil D. F.; Gonzalez Aracil, Susana; Brown, Tony; Grant, Michael G.

    2018-05-01

    In Australia, many birds and arboreal animals use hollows for shelters, but studies predict shortage of hollows in near future. Aged dead trees are more likely to contain hollows and therefore automated detection of them plays a substantial role in preserving biodiversity and consequently maintaining a resilient ecosystem. For this purpose full-waveform LiDAR data were acquired from a native Eucalypt forest in Southern Australia. The structure of the forest significantly varies in terms of tree density, age and height. Additionally, Eucalyptus camaldulensis have multiple trunk splits making tree delineation very challenging. For that reason, this paper investigates automated detection of dead standing Eucalyptus camaldulensis without tree delineation. It also presents the new feature of the open source software DASOS, which extracts features for 3D object detection in voxelised FW LiDAR. A random forest classifier, a weighted-distance KNN algorithm and a seed growth algorithm are used to create a 2D probabilistic field and to then predict potential positions of dead trees. It is shown that tree health assessment is possible without tree delineation but since it is a new research directions there are many improvements to be made.

  17. Logrank Test and Interval Overlap Test for Bactericera cockerelli (Hemiptera: Triozidae) Under Different Fertilization Treatments for 7705 Tomato Hybrid

    PubMed Central

    Vargas-Madríz, Haidel; Bautista-Martínez, Néstor; Vera-Graziano, Jorge; Sánchez-García, Prometeo; García-Gutiérrez, Cipriano; Sánchez-Soto, Saúl; de Jesús García-Avila, Clemente

    2014-01-01

    Abstract It is known that some nutrients can have both negative and positive effects on some populations of insects. To test this, the Logrank test and the Interval Overlap Test were evaluated for two crop cycles (February–May and May–August) of the 7705 tomato hybrid, and the effect on the psyllid, Bactericera cockerelli (Sulc.) (Hemiptera: Triozidae), was examined under greenhouse conditions. Tomato plants were in polythene bags and irrigated with the following solutions: T1—Steiner solution, T2—Steiner solution with nitrogen reduced to 25%, T3—Steiner solution with potassium reduced to 25%, and T4—Steiner solution with calcium reduced to 25%. In the Logrank test, a significant difference was found when comparing the survival parameters of B. cockerelli generated from the treatment cohorts: T1–T2; T1–T3; T1–T4; T2–T3; and T3–T4, while no significant differences were found in the T2–T4 comparison in the February–May cycle. In the May–August cycle, significant differences were found when comparing the survival parameters generated from the treatment cohorts: T1–T2; T1–T3; and T1–T4, while no significant differences were found in the T2–T3; T2–T4; and T3–T4 comparisons of survival parameters of B. cockerelli fed with the 7705 tomato hybrid. Also, the Interval Overlap Test was done on the treatment cohorts (T1, T2, T3, and T4) in the February–May and May–August cycles. T1 and T2 compare similarly in both cycles when feeding on the treatments up to 36 d. Similarly, in T1 and T3, the behavior of the insect is similar when feeding on the treatments up to 40 and 73 d, respectively. Comparisons T2–T3 and T2–T4 are similar when feeding on both treatments up to 42, 38 and 37, 63 d, respectively. Finally, the T3–T4 comparison was similar when feeding in both treatments up to 20 and 46 d, respectively. RESUMEN. Se sabe que algunos nutrientes pueden tener efectos tanto negativos como positivos en algunas poblaciones de insectos. Para probar esto se evaluó la prueba de rango logarítmico y la prueba de Overlap intervalo de dos ciclos de cultivo (febrero–mayo y mayo–agosto) del híbrido de tomate 7705 y el efecto sobre el psílido, Bactericera cockerelli (Sulc) (Hemiptera: Triozidae) fue examinado bajo condiciones de invernadero. Las plantas de tomate estaban en bolsas de polietileno y regadas con las siguientes soluciones: T1: Solución de Steiner, T2: solución de Steiner con Nitrógeno a 25%, T3: solución de Steiner con Potasio a 25% y T4: solución de Steiner con Calcio a 25%. En la prueba de Logrank se encontró diferencia significativa al comparar los parámetros de supervivencia que se generaron en las cohortes de los tratamientos, T1 – T2; T1 – T3; T1 – T4; T2 – T3 y T3 – T4. En la comparación de T2 – T4, no se encontraron diferencias significativas, entre los parámetros de supervivencia de B. cockerelli ; para el ciclo Mayo-Agosto, se encontró diferencia significativa al comparar los parámetros de supervivencia que se generaron en las cohortes de los tratamientos, T1 - T2; T1 – T3; T1 – T4; en las comparaciones de T2 – T3; T2 – T4; T3 – T4, no se encontraron diferencias significativas, entre los parámetros de supervivencia de B. cockerelli alimentados con el hibrido de tomate 7705. De igual manera se realizó la Prueba de Traslape de Intervalos para las cohortes de los tratamientos (T1, T2, T3 y T4) en los ciclos de Febrero-Mayo y de Mayo-Agosto, se puede observar que la comparación de T1 con T2, son similares cuando se alimenta en ambos tratamientos hasta los 36 días, respectivamente. De igual manera, en la comparación (T1 y T3), siendo similar cuando el insecto se alimenta en ambos tratamientos hasta los 40 y 37 días, respectivamente. Las comparaciones (T2 y T3) y (T2 y T4) es similar cuando se alimenta en ambos tratamientos hasta los (42, 38) y (37, 63) días, respectivamente. Finalmente, la comparación para (T3 y T4) fue similar cuando se alimenta en ambos tratamientos hasta los 20 y 46 días, respectivamente. PMID:25527579

  18. An efficient group multicast routing for multimedia communication

    NASA Astrophysics Data System (ADS)

    Wang, Yanlin; Sun, Yugen; Yan, Xinfang

    2004-04-01

    Group multicasting is a kind of communication mechanism whereby each member of a group sends messages to all the other members of the same group. Group multicast routing algorithms capable of satisfying quality of service (QoS) requirements of multimedia applications are essential for high-speed networks. We present a heuristic algorithm for group multicast routing with end to end delay constraint. Source-specific routing trees for each member are generated in our algorithm, which satisfy member"s bandwidth and end to end delay requirements. Simulations over random network were carried out to compare proposed algorithm performance with Low and Song"s. The experimental results show that our proposed algorithm performs better in terms of network cost and ability in constructing feasible multicast trees for group members. Moreover, our algorithm achieves good performance in balancing traffic, which can avoid link blocking and enhance the network behavior efficiently.

  19. Enhancement of Fast Face Detection Algorithm Based on a Cascade of Decision Trees

    NASA Astrophysics Data System (ADS)

    Khryashchev, V. V.; Lebedev, A. A.; Priorov, A. L.

    2017-05-01

    Face detection algorithm based on a cascade of ensembles of decision trees (CEDT) is presented. The new approach allows detecting faces other than the front position through the use of multiple classifiers. Each classifier is trained for a specific range of angles of the rotation head. The results showed a high rate of productivity for CEDT on images with standard size. The algorithm increases the area under the ROC-curve of 13% compared to a standard Viola-Jones face detection algorithm. Final realization of given algorithm consist of 5 different cascades for frontal/non-frontal faces. One more thing which we take from the simulation results is a low computational complexity of CEDT algorithm in comparison with standard Viola-Jones approach. This could prove important in the embedded system and mobile device industries because it can reduce the cost of hardware and make battery life longer.

  20. Using traveling salesman problem algorithms for evolutionary tree construction.

    PubMed

    Korostensky, C; Gonnet, G H

    2000-07-01

    The construction of evolutionary trees is one of the major problems in computational biology, mainly due to its complexity. We present a new tree construction method that constructs a tree with minimum score for a given set of sequences, where the score is the amount of evolution measured in PAM distances. To do this, the problem of tree construction is reduced to the Traveling Salesman Problem (TSP). The input for the TSP algorithm are the pairwise distances of the sequences and the output is a circular tour through the optimal, unknown tree plus the minimum score of the tree. The circular order and the score can be used to construct the topology of the optimal tree. Our method can be used for any scoring function that correlates to the amount of changes along the branches of an evolutionary tree, for instance it could also be used for parsimony scores, but it cannot be used for least squares fit of distances. A TSP solution reduces the space of all possible trees to 2n. Using this order, we can guarantee that we reconstruct a correct evolutionary tree if the absolute value of the error for each distance measurement is smaller than f2.gif" BORDER="0">, where f3.gif" BORDER="0">is the length of the shortest edge in the tree. For data sets with large errors, a dynamic programming approach is used to reconstruct the tree. Finally simulations and experiments with real data are shown.

  1. DupTree: a program for large-scale phylogenetic analyses using gene tree parsimony.

    PubMed

    Wehe, André; Bansal, Mukul S; Burleigh, J Gordon; Eulenstein, Oliver

    2008-07-01

    DupTree is a new software program for inferring rooted species trees from collections of gene trees using the gene tree parsimony approach. The program implements a novel algorithm that significantly improves upon the run time of standard search heuristics for gene tree parsimony, and enables the first truly genome-scale phylogenetic analyses. In addition, DupTree allows users to examine alternate rootings and to weight the reconciliation costs for gene trees. DupTree is an open source project written in C++. DupTree for Mac OS X, Windows, and Linux along with a sample dataset and an on-line manual are available at http://genome.cs.iastate.edu/CBL/DupTree

  2. Comparison of Naive Bayes and Decision Tree on Feature Selection Using Genetic Algorithm for Classification Problem

    NASA Astrophysics Data System (ADS)

    Rahmadani, S.; Dongoran, A.; Zarlis, M.; Zakarias

    2018-03-01

    This paper discusses the problem of feature selection using genetic algorithms on a dataset for classification problems. The classification model used is the decicion tree (DT), and Naive Bayes. In this paper we will discuss how the Naive Bayes and Decision Tree models to overcome the classification problem in the dataset, where the dataset feature is selectively selected using GA. Then both models compared their performance, whether there is an increase in accuracy or not. From the results obtained shows an increase in accuracy if the feature selection using GA. The proposed model is referred to as GADT (GA-Decision Tree) and GANB (GA-Naive Bayes). The data sets tested in this paper are taken from the UCI Machine Learning repository.

  3. A stepwise regression tree for nonlinear approximation: applications to estimating subpixel land cover

    USGS Publications Warehouse

    Huang, C.; Townshend, J.R.G.

    2003-01-01

    A stepwise regression tree (SRT) algorithm was developed for approximating complex nonlinear relationships. Based on the regression tree of Breiman et al . (BRT) and a stepwise linear regression (SLR) method, this algorithm represents an improvement over SLR in that it can approximate nonlinear relationships and over BRT in that it gives more realistic predictions. The applicability of this method to estimating subpixel forest was demonstrated using three test data sets, on all of which it gave more accurate predictions than SLR and BRT. SRT also generated more compact trees and performed better than or at least as well as BRT at all 10 equal forest proportion interval ranging from 0 to 100%. This method is appealing to estimating subpixel land cover over large areas.

  4. Improving generalized inverted index lock wait times

    NASA Astrophysics Data System (ADS)

    Borodin, A.; Mirvoda, S.; Porshnev, S.; Ponomareva, O.

    2018-01-01

    Concurrent operations on tree like data structures is a cornerstone of any database system. Concurrent operations intended for improving read\\write performance and usually implemented via some way of locking. Deadlock-free methods of concurrency control are known as tree locking protocols. These protocols provide basic operations(verbs) and algorithm (ways of operation invocations) for applying it to any tree-like data structure. These algorithms operate on data, managed by storage engine which are very different among RDBMS implementations. In this paper, we discuss tree locking protocol implementation for General inverted index (Gin) applied to multiversion concurrency control (MVCC) storage engine inside PostgreSQL RDBMS. After that we introduce improvements to locking protocol and provide usage statistics about evaluation of our improvement in very high load environment in one of the world’s largest IT company.

  5. Integrated pipeline for inferring the evolutionary history of a gene family embedded in the species tree: a case study on the STIMATE gene family.

    PubMed

    Song, Jia; Zheng, Sisi; Nguyen, Nhung; Wang, Youjun; Zhou, Yubin; Lin, Kui

    2017-10-03

    Because phylogenetic inference is an important basis for answering many evolutionary problems, a large number of algorithms have been developed. Some of these algorithms have been improved by integrating gene evolution models with the expectation of accommodating the hierarchy of evolutionary processes. To the best of our knowledge, however, there still is no single unifying model or algorithm that can take all evolutionary processes into account through a stepwise or simultaneous method. On the basis of three existing phylogenetic inference algorithms, we built an integrated pipeline for inferring the evolutionary history of a given gene family; this pipeline can model gene sequence evolution, gene duplication-loss, gene transfer and multispecies coalescent processes. As a case study, we applied this pipeline to the STIMATE (TMEM110) gene family, which has recently been reported to play an important role in store-operated Ca 2+ entry (SOCE) mediated by ORAI and STIM proteins. We inferred their phylogenetic trees in 69 sequenced chordate genomes. By integrating three tree reconstruction algorithms with diverse evolutionary models, a pipeline for inferring the evolutionary history of a gene family was developed, and its application was demonstrated.

  6. Isosurface Extraction in Time-Varying Fields Using a Temporal Hierarchical Index Tree

    NASA Technical Reports Server (NTRS)

    Shen, Han-Wei; Gerald-Yamasaki, Michael (Technical Monitor)

    1998-01-01

    Many high-performance isosurface extraction algorithms have been proposed in the past several years as a result of intensive research efforts. When applying these algorithms to large-scale time-varying fields, the storage overhead incurred from storing the search index often becomes overwhelming. this paper proposes an algorithm for locating isosurface cells in time-varying fields. We devise a new data structure, called Temporal Hierarchical Index Tree, which utilizes the temporal coherence that exists in a time-varying field and adoptively coalesces the cells' extreme values over time; the resulting extreme values are then used to create the isosurface cell search index. For a typical time-varying scalar data set, not only does this temporal hierarchical index tree require much less storage space, but also the amount of I/O required to access the indices from the disk at different time steps is substantially reduced. We illustrate the utility and speed of our algorithm with data from several large-scale time-varying CID simulations. Our algorithm can achieve more than 80% of disk-space savings when compared with the existing techniques, while the isosurface extraction time is nearly optimal.

  7. A practical approximation algorithm for solving massive instances of hybridization number for binary and nonbinary trees.

    PubMed

    van Iersel, Leo; Kelk, Steven; Lekić, Nela; Scornavacca, Celine

    2014-05-05

    Reticulate events play an important role in determining evolutionary relationships. The problem of computing the minimum number of such events to explain discordance between two phylogenetic trees is a hard computational problem. Even for binary trees, exact solvers struggle to solve instances with reticulation number larger than 40-50. Here we present CycleKiller and NonbinaryCycleKiller, the first methods to produce solutions verifiably close to optimality for instances with hundreds or even thousands of reticulations. Using simulations, we demonstrate that these algorithms run quickly for large and difficult instances, producing solutions that are very close to optimality. As a spin-off from our simulations we also present TerminusEst, which is the fastest exact method currently available that can handle nonbinary trees: this is used to measure the accuracy of the NonbinaryCycleKiller algorithm. All three methods are based on extensions of previous theoretical work (SIDMA 26(4):1635-1656, TCBB 10(1):18-25, SIDMA 28(1):49-66) and are publicly available. We also apply our methods to real data.

  8. High-Precision Determination of the Pion-Nucleon σ Term from Roy-Steiner Equations.

    PubMed

    Hoferichter, Martin; Ruiz de Elvira, Jacobo; Kubis, Bastian; Meißner, Ulf-G

    2015-08-28

    We present a determination of the pion-nucleon (πN) σ term σ_{πN} based on the Cheng-Dashen low-energy theorem (LET), taking advantage of the recent high-precision data from pionic atoms to pin down the πN scattering lengths as well as of constraints from analyticity, unitarity, and crossing symmetry in the form of Roy-Steiner equations to perform the extrapolation to the Cheng-Dashen point in a reliable manner. With isospin-violating corrections included both in the scattering lengths and the LET, we obtain σ_{πN}=(59.1±1.9±3.0)  MeV=(59.1±3.5)  MeV, where the first error refers to uncertainties in the πN amplitude and the second to the LET. Consequences for the scalar nucleon couplings relevant for the direct detection of dark matter are discussed.

  9. High-Precision Determination of the Pion-Nucleon σ Term from Roy-Steiner Equations

    NASA Astrophysics Data System (ADS)

    Hoferichter, Martin; Ruiz de Elvira, Jacobo; Kubis, Bastian; Meißner, Ulf-G.

    2015-08-01

    We present a determination of the pion-nucleon (π N ) σ term σπ N based on the Cheng-Dashen low-energy theorem (LET), taking advantage of the recent high-precision data from pionic atoms to pin down the π N scattering lengths as well as of constraints from analyticity, unitarity, and crossing symmetry in the form of Roy-Steiner equations to perform the extrapolation to the Cheng-Dashen point in a reliable manner. With isospin-violating corrections included both in the scattering lengths and the LET, we obtain σπ N=(59.1 ±1.9 ±3.0 ) MeV =(59.1 ±3.5 ) MeV , where the first error refers to uncertainties in the π N amplitude and the second to the LET. Consequences for the scalar nucleon couplings relevant for the direct detection of dark matter are discussed.

  10. Roy-Steiner equations for pion-nucleon scattering

    NASA Astrophysics Data System (ADS)

    Ditsche, C.; Hoferichter, M.; Kubis, B.; Meißner, U.-G.

    2012-06-01

    Starting from hyperbolic dispersion relations, we derive a closed system of Roy-Steiner equations for pion-nucleon scattering that respects analyticity, unitarity, and crossing symmetry. We work out analytically all kernel functions and unitarity relations required for the lowest partial waves. In order to suppress the dependence on the high energy regime we also consider once- and twice-subtracted versions of the equations, where we identify the subtraction constants with subthreshold parameters. Assuming Mandelstam analyticity we determine the maximal range of validity of these equations. As a first step towards the solution of the full system we cast the equations for the π π to overline N N partial waves into the form of a Muskhelishvili-Omnès problem with finite matching point, which we solve numerically in the single-channel approximation. We investigate in detail the role of individual contributions to our solutions and discuss some consequences for the spectral functions of the nucleon electromagnetic form factors.

  11. Characterizing the phylogenetic tree-search problem.

    PubMed

    Money, Daniel; Whelan, Simon

    2012-03-01

    Phylogenetic trees are important in many areas of biological research, ranging from systematic studies to the methods used for genome annotation. Finding the best scoring tree under any optimality criterion is an NP-hard problem, which necessitates the use of heuristics for tree-search. Although tree-search plays a major role in obtaining a tree estimate, there remains a limited understanding of its characteristics and how the elements of the statistical inferential procedure interact with the algorithms used. This study begins to answer some of these questions through a detailed examination of maximum likelihood tree-search on a wide range of real genome-scale data sets. We examine all 10,395 trees for each of the 106 genes of an eight-taxa yeast phylogenomic data set, then apply different tree-search algorithms to investigate their performance. We extend our findings by examining two larger genome-scale data sets and a large disparate data set that has been previously used to benchmark the performance of tree-search programs. We identify several broad trends occurring during tree-search that provide an insight into the performance of heuristics and may, in the future, aid their development. These trends include a tendency for the true maximum likelihood (best) tree to also be the shortest tree in terms of branch lengths, a weak tendency for tree-search to recover the best tree, and a tendency for tree-search to encounter fewer local optima in genes that have a high information content. When examining current heuristics for tree-search, we find that nearest-neighbor-interchange performs poorly, and frequently finds trees that are significantly different from the best tree. In contrast, subtree-pruning-and-regrafting tends to perform well, nearly always finding trees that are not significantly different to the best tree. Finally, we demonstrate that the precise implementation of a tree-search strategy, including when and where parameters are optimized, can change the character of tree-search, and that good strategies for tree-search may combine existing tree-search programs.

  12. An efficient and extensible approach for compressing phylogenetic trees

    PubMed Central

    2011-01-01

    Background Biologists require new algorithms to efficiently compress and store their large collections of phylogenetic trees. Our previous work showed that TreeZip is a promising approach for compressing phylogenetic trees. In this paper, we extend our TreeZip algorithm by handling trees with weighted branches. Furthermore, by using the compressed TreeZip file as input, we have designed an extensible decompressor that can extract subcollections of trees, compute majority and strict consensus trees, and merge tree collections using set operations such as union, intersection, and set difference. Results On unweighted phylogenetic trees, TreeZip is able to compress Newick files in excess of 98%. On weighted phylogenetic trees, TreeZip is able to compress a Newick file by at least 73%. TreeZip can be combined with 7zip with little overhead, allowing space savings in excess of 99% (unweighted) and 92%(weighted). Unlike TreeZip, 7zip is not immune to branch rotations, and performs worse as the level of variability in the Newick string representation increases. Finally, since the TreeZip compressed text (TRZ) file contains all the semantic information in a collection of trees, we can easily filter and decompress a subset of trees of interest (such as the set of unique trees), or build the resulting consensus tree in a matter of seconds. We also show the ease of which set operations can be performed on TRZ files, at speeds quicker than those performed on Newick or 7zip compressed Newick files, and without loss of space savings. Conclusions TreeZip is an efficient approach for compressing large collections of phylogenetic trees. The semantic and compact nature of the TRZ file allow it to be operated upon directly and quickly, without a need to decompress the original Newick file. We believe that TreeZip will be vital for compressing and archiving trees in the biological community. PMID:22165819

  13. An efficient and extensible approach for compressing phylogenetic trees.

    PubMed

    Matthews, Suzanne J; Williams, Tiffani L

    2011-10-18

    Biologists require new algorithms to efficiently compress and store their large collections of phylogenetic trees. Our previous work showed that TreeZip is a promising approach for compressing phylogenetic trees. In this paper, we extend our TreeZip algorithm by handling trees with weighted branches. Furthermore, by using the compressed TreeZip file as input, we have designed an extensible decompressor that can extract subcollections of trees, compute majority and strict consensus trees, and merge tree collections using set operations such as union, intersection, and set difference. On unweighted phylogenetic trees, TreeZip is able to compress Newick files in excess of 98%. On weighted phylogenetic trees, TreeZip is able to compress a Newick file by at least 73%. TreeZip can be combined with 7zip with little overhead, allowing space savings in excess of 99% (unweighted) and 92%(weighted). Unlike TreeZip, 7zip is not immune to branch rotations, and performs worse as the level of variability in the Newick string representation increases. Finally, since the TreeZip compressed text (TRZ) file contains all the semantic information in a collection of trees, we can easily filter and decompress a subset of trees of interest (such as the set of unique trees), or build the resulting consensus tree in a matter of seconds. We also show the ease of which set operations can be performed on TRZ files, at speeds quicker than those performed on Newick or 7zip compressed Newick files, and without loss of space savings. TreeZip is an efficient approach for compressing large collections of phylogenetic trees. The semantic and compact nature of the TRZ file allow it to be operated upon directly and quickly, without a need to decompress the original Newick file. We believe that TreeZip will be vital for compressing and archiving trees in the biological community.

  14. Using Decision Trees to Detect and Isolate Simulated Leaks in the J-2X Rocket Engine

    NASA Technical Reports Server (NTRS)

    Schwabacher, Mark A.; Aguilar, Robert; Figueroa, Fernando F.

    2009-01-01

    The goal of this work was to use data-driven methods to automatically detect and isolate faults in the J-2X rocket engine. It was decided to use decision trees, since they tend to be easier to interpret than other data-driven methods. The decision tree algorithm automatically "learns" a decision tree by performing a search through the space of possible decision trees to find one that fits the training data. The particular decision tree algorithm used is known as C4.5. Simulated J-2X data from a high-fidelity simulator developed at Pratt & Whitney Rocketdyne and known as the Detailed Real-Time Model (DRTM) was used to "train" and test the decision tree. Fifty-six DRTM simulations were performed for this purpose, with different leak sizes, different leak locations, and different times of leak onset. To make the simulations as realistic as possible, they included simulated sensor noise, and included a gradual degradation in both fuel and oxidizer turbine efficiency. A decision tree was trained using 11 of these simulations, and tested using the remaining 45 simulations. In the training phase, the C4.5 algorithm was provided with labeled examples of data from nominal operation and data including leaks in each leak location. From the data, it "learned" a decision tree that can classify unseen data as having no leak or having a leak in one of the five leak locations. In the test phase, the decision tree produced very low false alarm rates and low missed detection rates on the unseen data. It had very good fault isolation rates for three of the five simulated leak locations, but it tended to confuse the remaining two locations, perhaps because a large leak at one of these two locations can look very similar to a small leak at the other location.

  15. Molecular Infectious Disease Epidemiology: Survival Analysis and Algorithms Linking Phylogenies to Transmission Trees

    PubMed Central

    Kenah, Eben; Britton, Tom; Halloran, M. Elizabeth; Longini, Ira M.

    2016-01-01

    Recent work has attempted to use whole-genome sequence data from pathogens to reconstruct the transmission trees linking infectors and infectees in outbreaks. However, transmission trees from one outbreak do not generalize to future outbreaks. Reconstruction of transmission trees is most useful to public health if it leads to generalizable scientific insights about disease transmission. In a survival analysis framework, estimation of transmission parameters is based on sums or averages over the possible transmission trees. A phylogeny can increase the precision of these estimates by providing partial information about who infected whom. The leaves of the phylogeny represent sampled pathogens, which have known hosts. The interior nodes represent common ancestors of sampled pathogens, which have unknown hosts. Starting from assumptions about disease biology and epidemiologic study design, we prove that there is a one-to-one correspondence between the possible assignments of interior node hosts and the transmission trees simultaneously consistent with the phylogeny and the epidemiologic data on person, place, and time. We develop algorithms to enumerate these transmission trees and show these can be used to calculate likelihoods that incorporate both epidemiologic data and a phylogeny. A simulation study confirms that this leads to more efficient estimates of hazard ratios for infectiousness and baseline hazards of infectious contact, and we use these methods to analyze data from a foot-and-mouth disease virus outbreak in the United Kingdom in 2001. These results demonstrate the importance of data on individuals who escape infection, which is often overlooked. The combination of survival analysis and algorithms linking phylogenies to transmission trees is a rigorous but flexible statistical foundation for molecular infectious disease epidemiology. PMID:27070316

  16. Trees, bialgebras and intrinsic numerical algorithms

    NASA Technical Reports Server (NTRS)

    Crouch, Peter; Grossman, Robert; Larson, Richard

    1990-01-01

    Preliminary work about intrinsic numerical integrators evolving on groups is described. Fix a finite dimensional Lie group G; let g denote its Lie algebra, and let Y(sub 1),...,Y(sub N) denote a basis of g. A class of numerical algorithms is presented that approximate solutions to differential equations evolving on G of the form: dot-x(t) = F(x(t)), x(0) = p is an element of G. The algorithms depend upon constants c(sub i) and c(sub ij), for i = 1,...,k and j is less than i. The algorithms have the property that if the algorithm starts on the group, then it remains on the group. In addition, they also have the property that if G is the abelian group R(N), then the algorithm becomes the classical Runge-Kutta algorithm. The Cayley algebra generated by labeled, ordered trees is used to generate the equations that the coefficients c(sub i) and c(sub ij) must satisfy in order for the algorithm to yield an rth order numerical integrator and to analyze the resulting algorithms.

  17. Reducing process delays for real-time earthquake parameter estimation - An application of KD tree to large databases for Earthquake Early Warning

    NASA Astrophysics Data System (ADS)

    Yin, Lucy; Andrews, Jennifer; Heaton, Thomas

    2018-05-01

    Earthquake parameter estimations using nearest neighbor searching among a large database of observations can lead to reliable prediction results. However, in the real-time application of Earthquake Early Warning (EEW) systems, the accurate prediction using a large database is penalized by a significant delay in the processing time. We propose to use a multidimensional binary search tree (KD tree) data structure to organize large seismic databases to reduce the processing time in nearest neighbor search for predictions. We evaluated the performance of KD tree on the Gutenberg Algorithm, a database-searching algorithm for EEW. We constructed an offline test to predict peak ground motions using a database with feature sets of waveform filter-bank characteristics, and compare the results with the observed seismic parameters. We concluded that large database provides more accurate predictions of the ground motion information, such as peak ground acceleration, velocity, and displacement (PGA, PGV, PGD), than source parameters, such as hypocenter distance. Application of the KD tree search to organize the database reduced the average searching process by 85% time cost of the exhaustive method, allowing the method to be feasible for real-time implementation. The algorithm is straightforward and the results will reduce the overall time of warning delivery for EEW.

  18. Graphical models for optimal power flow

    DOE PAGES

    Dvijotham, Krishnamurthy; Chertkov, Michael; Van Hentenryck, Pascal; ...

    2016-09-13

    Optimal power flow (OPF) is the central optimization problem in electric power grids. Although solved routinely in the course of power grid operations, it is known to be strongly NP-hard in general, and weakly NP-hard over tree networks. In this paper, we formulate the optimal power flow problem over tree networks as an inference problem over a tree-structured graphical model where the nodal variables are low-dimensional vectors. We adapt the standard dynamic programming algorithm for inference over a tree-structured graphical model to the OPF problem. Combining this with an interval discretization of the nodal variables, we develop an approximation algorithmmore » for the OPF problem. Further, we use techniques from constraint programming (CP) to perform interval computations and adaptive bound propagation to obtain practically efficient algorithms. Compared to previous algorithms that solve OPF with optimality guarantees using convex relaxations, our approach is able to work for arbitrary tree-structured distribution networks and handle mixed-integer optimization problems. Further, it can be implemented in a distributed message-passing fashion that is scalable and is suitable for “smart grid” applications like control of distributed energy resources. In conclusion, numerical evaluations on several benchmark networks show that practical OPF problems can be solved effectively using this approach.« less

  19. The Refinement-Tree Partition for Parallel Solution of Partial Differential Equations

    PubMed Central

    Mitchell, William F.

    1998-01-01

    Dynamic load balancing is considered in the context of adaptive multilevel methods for partial differential equations on distributed memory multiprocessors. An approach that periodically repartitions the grid is taken. The important properties of a partitioning algorithm are presented and discussed in this context. A partitioning algorithm based on the refinement tree of the adaptive grid is presented and analyzed in terms of these properties. Theoretical and numerical results are given. PMID:28009355

  20. The Refinement-Tree Partition for Parallel Solution of Partial Differential Equations.

    PubMed

    Mitchell, William F

    1998-01-01

    Dynamic load balancing is considered in the context of adaptive multilevel methods for partial differential equations on distributed memory multiprocessors. An approach that periodically repartitions the grid is taken. The important properties of a partitioning algorithm are presented and discussed in this context. A partitioning algorithm based on the refinement tree of the adaptive grid is presented and analyzed in terms of these properties. Theoretical and numerical results are given.

  1. The explicit computation of integration algorithms and first integrals for ordinary differential equations with polynomials coefficients using trees

    NASA Technical Reports Server (NTRS)

    Crouch, P. E.; Grossman, Robert

    1992-01-01

    This note is concerned with the explicit symbolic computation of expressions involving differential operators and their actions on functions. The derivation of specialized numerical algorithms, the explicit symbolic computation of integrals of motion, and the explicit computation of normal forms for nonlinear systems all require such computations. More precisely, if R = k(x(sub 1),...,x(sub N)), where k = R or C, F denotes a differential operator with coefficients from R, and g member of R, we describe data structures and algorithms for efficiently computing g. The basic idea is to impose a multiplicative structure on the vector space with basis the set of finite rooted trees and whose nodes are labeled with the coefficients of the differential operators. Cancellations of two trees with r + 1 nodes translates into cancellation of O(N(exp r)) expressions involving the coefficient functions and their derivatives.

  2. Automatic Inference of Cryptographic Key Length Based on Analysis of Proof Tightness

    DTIC Science & Technology

    2016-06-01

    within an attack tree structure, then expand attack tree methodology to include cryptographic reductions. We then provide the algorithms for...maintaining and automatically reasoning about these expanded attack trees . We provide a software tool that utilizes machine-readable proof and attack metadata...and the attack tree methodology to provide rapid and precise answers regarding security parameters and effective security. This eliminates the need

  3. Layer stacking: A novel algorithm for individual forest tree segmentation from LiDAR point clouds

    Treesearch

    Elias Ayrey; Shawn Fraver; John A. Kershaw; Laura S. Kenefic; Daniel Hayes; Aaron R. Weiskittel; Brian E. Roth

    2017-01-01

    As light detection and ranging (LiDAR) technology advances, it has become common for datasets to be acquired at a point density high enough to capture structural information from individual trees. To process these data, an automatic method of isolating individual trees from a LiDAR point cloud is required. Traditional methods for segmenting trees attempt to isolate...

  4. Memory-Scalable GPU Spatial Hierarchy Construction.

    PubMed

    Qiming Hou; Xin Sun; Kun Zhou; Lauterbach, C; Manocha, D

    2011-04-01

    Recent GPU algorithms for constructing spatial hierarchies have achieved promising performance for moderately complex models by using the breadth-first search (BFS) construction order. While being able to exploit the massive parallelism on the GPU, the BFS order also consumes excessive GPU memory, which becomes a serious issue for interactive applications involving very complex models with more than a few million triangles. In this paper, we propose to use the partial breadth-first search (PBFS) construction order to control memory consumption while maximizing performance. We apply the PBFS order to two hierarchy construction algorithms. The first algorithm is for kd-trees that automatically balances between the level of parallelism and intermediate memory usage. With PBFS, peak memory consumption during construction can be efficiently controlled without costly CPU-GPU data transfer. We also develop memory allocation strategies to effectively limit memory fragmentation. The resulting algorithm scales well with GPU memory and constructs kd-trees of models with millions of triangles at interactive rates on GPUs with 1 GB memory. Compared with existing algorithms, our algorithm is an order of magnitude more scalable for a given GPU memory bound. The second algorithm is for out-of-core bounding volume hierarchy (BVH) construction for very large scenes based on the PBFS construction order. At each iteration, all constructed nodes are dumped to the CPU memory, and the GPU memory is freed for the next iteration's use. In this way, the algorithm is able to build trees that are too large to be stored in the GPU memory. Experiments show that our algorithm can construct BVHs for scenes with up to 20 M triangles, several times larger than previous GPU algorithms.

  5. IND - THE IND DECISION TREE PACKAGE

    NASA Technical Reports Server (NTRS)

    Buntine, W.

    1994-01-01

    A common approach to supervised classification and prediction in artificial intelligence and statistical pattern recognition is the use of decision trees. A tree is "grown" from data using a recursive partitioning algorithm to create a tree which has good prediction of classes on new data. Standard algorithms are CART (by Breiman Friedman, Olshen and Stone) and ID3 and its successor C4 (by Quinlan). As well as reimplementing parts of these algorithms and offering experimental control suites, IND also introduces Bayesian and MML methods and more sophisticated search in growing trees. These produce more accurate class probability estimates that are important in applications like diagnosis. IND is applicable to most data sets consisting of independent instances, each described by a fixed length vector of attribute values. An attribute value may be a number, one of a set of attribute specific symbols, or it may be omitted. One of the attributes is delegated the "target" and IND grows trees to predict the target. Prediction can then be done on new data or the decision tree printed out for inspection. IND provides a range of features and styles with convenience for the casual user as well as fine-tuning for the advanced user or those interested in research. IND can be operated in a CART-like mode (but without regression trees, surrogate splits or multivariate splits), and in a mode like the early version of C4. Advanced features allow more extensive search, interactive control and display of tree growing, and Bayesian and MML algorithms for tree pruning and smoothing. These often produce more accurate class probability estimates at the leaves. IND also comes with a comprehensive experimental control suite. IND consists of four basic kinds of routines: data manipulation routines, tree generation routines, tree testing routines, and tree display routines. The data manipulation routines are used to partition a single large data set into smaller training and test sets. The generation routines are used to build classifiers. The test routines are used to evaluate classifiers and to classify data using a classifier. And the display routines are used to display classifiers in various formats. IND is written in C-language for Sun4 series computers. It consists of several programs with controlling shell scripts. Extensive UNIX man entries are included. IND is designed to be used on any UNIX system, although it has only been thoroughly tested on SUN platforms. The standard distribution medium for IND is a .25 inch streaming magnetic tape cartridge in UNIX tar format. An electronic copy of the documentation in PostScript format is included on the distribution medium. IND was developed in 1992.

  6. On Determining if Tree-based Networks Contain Fixed Trees.

    PubMed

    Anaya, Maria; Anipchenko-Ulaj, Olga; Ashfaq, Aisha; Chiu, Joyce; Kaiser, Mahedi; Ohsawa, Max Shoji; Owen, Megan; Pavlechko, Ella; St John, Katherine; Suleria, Shivam; Thompson, Keith; Yap, Corrine

    2016-05-01

    We address an open question of Francis and Steel about phylogenetic networks and trees. They give a polynomial time algorithm to decide if a phylogenetic network, N, is tree-based and pose the problem: given a fixed tree T and network N, is N based on T? We show that it is [Formula: see text]-hard to decide, by reduction from 3-Dimensional Matching (3DM) and further that the problem is fixed-parameter tractable.

  7. Logrank test and Interval Overlap Test for Bactericera cockerelli (Hemiptera: Triozidae) under different fertilization treatments for 7705 tomato hybrid.

    PubMed

    Vargas-Madríz, Haidel; Bautista-Martínez, Néstor; Vera-Graziano, Jorge; Sánchez-García, Prometeo; García-Gutiérrez, Cipriano; Sánchez-Soto, Saúl; García-Avila, Clemente de Jesús

    2014-01-01

    It is known that some nutrients can have both negative and positive effects on some populations of insects. To test this, the Logrank test and the Interval Overlap Test were evaluated for two crop cycles (February-May and May-August) of the 7705 tomato hybrid, and the effect on the psyllid, Bactericera cockerelli (Sulc.) (Hemiptera: Triozidae), was examined under greenhouse conditions. Tomato plants were in polythene bags and irrigated with the following solutions: T1-Steiner solution, T2-Steiner solution with nitrogen reduced to 25%, T3-Steiner solution with potassium reduced to 25%, and T4-Steiner solution with calcium reduced to 25%. In the Logrank test, a significant difference was found when comparing the survival parameters of B. cockerelli generated from the treatment cohorts: T1-T2; T1-T3; T1-T4; T2-T3; and T3-T4, while no significant differences were found in the T2-T4 comparison in the February-May cycle. In the May-August cycle, significant differences were found when comparing the survival parameters generated from the treatment cohorts: T1-T2; T1-T3; and T1-T4, while no significant differences were found in the T2-T3; T2-T4; and T3-T4 comparisons of survival parameters of B. cockerelli fed with the 7705 tomato hybrid. Also, the Interval Overlap Test was done on the treatment cohorts (T1, T2, T3, and T4) in the February-May and May-August cycles. T1 and T2 compare similarly in both cycles when feeding on the treatments up to 36 d. Similarly, in T1 and T3, the behavior of the insect is similar when feeding on the treatments up to 40 and 73 d, respectively. Comparisons T2-T3 and T2-T4 are similar when feeding on both treatments up to 42, 38 and 37, 63 d, respectively. Finally, the T3-T4 comparison was similar when feeding in both treatments up to 20 and 46 d, respectively. © The Author 2014. Published by Oxford University Press on behalf of the Entomological Society of America.

  8. TREEGRAD: a grading program for eastern hardwoods

    Treesearch

    J.W. Stringer; D.W. Cremeans

    1991-01-01

    Assigning tree grades to eastern hardwoods is often a difficult task for neophyte graders. Recently several "dichotomous keys" have been developed for training graders in the USFS hardwood tree grading system. TREEGRAD uses the Tree Grading Algorithm (TGA) for determining grades from defect location data and is designed to be used as a teaching aid.

  9. Key algorithms used in GR02: A computer simulation model for predicting tree and stand growth

    Treesearch

    Garrett A. Hughes; Paul E. Sendak; Paul E. Sendak

    1985-01-01

    GR02 is an individual tree, distance-independent simulation model for predicting tree and stand growth over time. It performs five major functions during each run: (1) updates diameter at breast height, (2) updates total height, (3) estimates mortality, (4) determines regeneration, and (5) updates crown class.

  10. Using decision trees to characterize verbal communication during change and stuck episodes in the therapeutic process

    PubMed Central

    Masías, Víctor H.; Krause, Mariane; Valdés, Nelson; Pérez, J. C.; Laengle, Sigifredo

    2015-01-01

    Methods are needed for creating models to characterize verbal communication between therapists and their patients that are suitable for teaching purposes without losing analytical potential. A technique meeting these twin requirements is proposed that uses decision trees to identify both change and stuck episodes in therapist-patient communication. Three decision tree algorithms (C4.5, NBTree, and REPTree) are applied to the problem of characterizing verbal responses into change and stuck episodes in the therapeutic process. The data for the problem is derived from a corpus of 8 successful individual therapy sessions with 1760 speaking turns in a psychodynamic context. The decision tree model that performed best was generated by the C4.5 algorithm. It delivered 15 rules characterizing the verbal communication in the two types of episodes. Decision trees are a promising technique for analyzing verbal communication during significant therapy events and have much potential for use in teaching practice on changes in therapeutic communication. The development of pedagogical methods using decision trees can support the transmission of academic knowledge to therapeutic practice. PMID:25914657

  11. Using decision trees to characterize verbal communication during change and stuck episodes in the therapeutic process.

    PubMed

    Masías, Víctor H; Krause, Mariane; Valdés, Nelson; Pérez, J C; Laengle, Sigifredo

    2015-01-01

    Methods are needed for creating models to characterize verbal communication between therapists and their patients that are suitable for teaching purposes without losing analytical potential. A technique meeting these twin requirements is proposed that uses decision trees to identify both change and stuck episodes in therapist-patient communication. Three decision tree algorithms (C4.5, NBTree, and REPTree) are applied to the problem of characterizing verbal responses into change and stuck episodes in the therapeutic process. The data for the problem is derived from a corpus of 8 successful individual therapy sessions with 1760 speaking turns in a psychodynamic context. The decision tree model that performed best was generated by the C4.5 algorithm. It delivered 15 rules characterizing the verbal communication in the two types of episodes. Decision trees are a promising technique for analyzing verbal communication during significant therapy events and have much potential for use in teaching practice on changes in therapeutic communication. The development of pedagogical methods using decision trees can support the transmission of academic knowledge to therapeutic practice.

  12. Treelink: data integration, clustering and visualization of phylogenetic trees.

    PubMed

    Allende, Christian; Sohn, Erik; Little, Cedric

    2015-12-29

    Phylogenetic trees are central to a wide range of biological studies. In many of these studies, tree nodes need to be associated with a variety of attributes. For example, in studies concerned with viral relationships, tree nodes are associated with epidemiological information, such as location, age and subtype. Gene trees used in comparative genomics are usually linked with taxonomic information, such as functional annotations and events. A wide variety of tree visualization and annotation tools have been developed in the past, however none of them are intended for an integrative and comparative analysis. Treelink is a platform-independent software for linking datasets and sequence files to phylogenetic trees. The application allows an automated integration of datasets to trees for operations such as classifying a tree based on a field or showing the distribution of selected data attributes in branches and leafs. Genomic and proteonomic sequences can also be linked to the tree and extracted from internal and external nodes. A novel clustering algorithm to simplify trees and display the most divergent clades was also developed, where validation can be achieved using the data integration and classification function. Integrated geographical information allows ancestral character reconstruction for phylogeographic plotting based on parsimony and likelihood algorithms. Our software can successfully integrate phylogenetic trees with different data sources, and perform operations to differentiate and visualize those differences within a tree. File support includes the most popular formats such as newick and csv. Exporting visualizations as images, cluster outputs and genomic sequences is supported. Treelink is available as a web and desktop application at http://www.treelinkapp.com .

  13. The Laws of Nature and the Effectiveness of Mathematics

    NASA Astrophysics Data System (ADS)

    Dorato, Mauro

    In this paper I try to evaluate what I regard as the main attempts at explaining the effectiveness of mathematics in the natural sciences, namely (1) Antinaturalism, (2) Kantism, (3) Semanticism, (4) Algorithmic Complexity Theory. The first position has been defended by Mark Steiner, who claims that the "user friendliness" of nature for the applied mathematician is the best argument against a naturalistic explanation of the origin of the universe. The second is naturalistic and mixes the Kantian tradition with evolutionary studies about our innate mathematical abilities. The third turns to the Fregean tradition and considers mathematics a particular kind of language, thus treating the effectiveness of mathematics as a particular instance of the effectiveness of natural languages. The fourth hypothesis, building on formal results by Kolmogorov, Solomonov and Chaitin, claims that mathematics is so useful in describing the natural world because it is the science of the abbreviation of sequences, and mathematically formulated laws of nature enable us to compress the information contained in the sequence of numbers in which we code our observations. In this tradition, laws are equivalent to the shortest algorithms capable of generating the lists of zeros and ones representing the empirical data. Along the way, I present and reject the "deflationary explanation", which claims that in wondering about the applicability of so many mathematical structures to nature, we tend to forget the many cases in which no application is possible.

  14. M-AMST: an automatic 3D neuron tracing method based on mean shift and adapted minimum spanning tree.

    PubMed

    Wan, Zhijiang; He, Yishan; Hao, Ming; Yang, Jian; Zhong, Ning

    2017-03-29

    Understanding the working mechanism of the brain is one of the grandest challenges for modern science. Toward this end, the BigNeuron project was launched to gather a worldwide community to establish a big data resource and a set of the state-of-the-art of single neuron reconstruction algorithms. Many groups contributed their own algorithms for the project, including our mean shift and minimum spanning tree (M-MST). Although M-MST is intuitive and easy to implement, the MST just considers spatial information of single neuron and ignores the shape information, which might lead to less precise connections between some neuron segments. In this paper, we propose an improved algorithm, namely M-AMST, in which a rotating sphere model based on coordinate transformation is used to improve the weight calculation method in M-MST. Two experiments are designed to illustrate the effect of adapted minimum spanning tree algorithm and the adoptability of M-AMST in reconstructing variety of neuron image datasets respectively. In the experiment 1, taking the reconstruction of APP2 as reference, we produce the four difference scores (entire structure average (ESA), different structure average (DSA), percentage of different structure (PDS) and max distance of neurons' nodes (MDNN)) by comparing the neuron reconstruction of the APP2 and the other 5 competing algorithm. The result shows that M-AMST gets lower difference scores than M-MST in ESA, PDS and MDNN. Meanwhile, M-AMST is better than N-MST in ESA and MDNN. It indicates that utilizing the adapted minimum spanning tree algorithm which took the shape information of neuron into account can achieve better neuron reconstructions. In the experiment 2, 7 neuron image datasets are reconstructed and the four difference scores are calculated by comparing the gold standard reconstruction and the reconstructions produced by 6 competing algorithms. Comparing the four difference scores of M-AMST and the other 5 algorithm, we can conclude that M-AMST is able to achieve the best difference score in 3 datasets and get the second-best difference score in the other 2 datasets. We develop a pathway extraction method using a rotating sphere model based on coordinate transformation to improve the weight calculation approach in MST. The experimental results show that M-AMST utilizes the adapted minimum spanning tree algorithm which takes the shape information of neuron into account can achieve better neuron reconstructions. Moreover, M-AMST is able to get good neuron reconstruction in variety of image datasets.

  15. Efficient algorithms for dilated mappings of binary trees

    NASA Technical Reports Server (NTRS)

    Iqbal, M. Ashraf

    1990-01-01

    The problem is addressed to find a 1-1 mapping of the vertices of a binary tree onto those of a target binary tree such that the son of a node on the first binary tree is mapped onto a descendent of the image of that node in the second binary tree. There are two natural measures of the cost of this mapping, namely the dilation cost, i.e., the maximum distance in the target binary tree between the images of vertices that are adjacent in the original tree. The other measure, expansion cost, is defined as the number of extra nodes/edges to be added to the target binary tree in order to ensure a 1-1 mapping. An efficient algorithm to find a mapping of one binary tree onto another is described. It is shown that it is possible to minimize one cost of mapping at the expense of the other. This problem arises when designing pipelined arithmetic logic units (ALU) for special purpose computers. The pipeline is composed of ALU chips connected in the form of a binary tree. The operands to the pipeline can be supplied to the leaf nodes of the binary tree which then process and pass the results up to their parents. The final result is available at the root. As each new application may require a distinct nesting of operations, it is useful to be able to find a good mapping of a new binary tree over existing ALU tree. Another problem arises if every distinct required binary tree is known beforehand. Here it is useful to hardwire the pipeline in the form of a minimal supertree that contains all required binary trees.

  16. Multi-level tree analysis of pulmonary artery/vein trees in non-contrast CT images

    NASA Astrophysics Data System (ADS)

    Gao, Zhiyun; Grout, Randall W.; Hoffman, Eric A.; Saha, Punam K.

    2012-02-01

    Diseases like pulmonary embolism and pulmonary hypertension are associated with vascular dystrophy. Identifying such pulmonary artery/vein (A/V) tree dystrophy in terms of quantitative measures via CT imaging significantly facilitates early detection of disease or a treatment monitoring process. A tree structure, consisting of nodes and connected arcs, linked to the volumetric representation allows multi-level geometric and volumetric analysis of A/V trees. Here, a new theory and method is presented to generate multi-level A/V tree representation of volumetric data and to compute quantitative measures of A/V tree geometry and topology at various tree hierarchies. The new method is primarily designed on arc skeleton computation followed by a tree construction based topologic and geometric analysis of the skeleton. The method starts with a volumetric A/V representation as input and generates its topologic and multi-level volumetric tree representations long with different multi-level morphometric measures. A new recursive merging and pruning algorithms are introduced to detect bad junctions and noisy branches often associated with digital geometric and topologic analysis. Also, a new notion of shortest axial path is introduced to improve the skeletal arc joining two junctions. The accuracy of the multi-level tree analysis algorithm has been evaluated using computer generated phantoms and pulmonary CT images of a pig vessel cast phantom while the reproducibility of method is evaluated using multi-user A/V separation of in vivo contrast-enhanced CT images of a pig lung at different respiratory volumes.

  17. Algorithmic Complexity. Volume II.

    DTIC Science & Technology

    1982-06-01

    digital computers, this improvement will go unnoticed if only a few complex products are to be taken, however it can become increasingly important as...computed in the reverse order. If the products are formed moving from the top of the tree downward, and then the divisions are performed going from the...the reverse order, going up the tree. (r- a mod m means that r is the remainder when a is divided by M.) The overall running time of the algorithm is

  18. Orthology and paralogy constraints: satisfiability and consistency.

    PubMed

    Lafond, Manuel; El-Mabrouk, Nadia

    2014-01-01

    A variety of methods based on sequence similarity, reconciliation, synteny or functional characteristics, can be used to infer orthology and paralogy relations between genes of a given gene family  G. But is a given set  C of orthology/paralogy constraints possible, i.e., can they simultaneously co-exist in an evolutionary history for  G? While previous studies have focused on full sets of constraints, here we consider the general case where  C does not necessarily involve a constraint for each pair of genes. The problem is subdivided in two parts: (1) Is  C satisfiable, i.e. can we find an event-labeled gene tree G inducing  C? (2) Is there such a G which is consistent, i.e., such that all displayed triplet phylogenies are included in a species tree? Previous results on the Graph sandwich problem can be used to answer to (1), and we provide polynomial-time algorithms for satisfiability and consistency with a given species tree. We also describe a new polynomial-time algorithm for the case of consistency with an unknown species tree and full knowledge of pairwise orthology/paralogy relationships, as well as a branch-and-bound algorithm in the case when unknown relations are present. We show that our algorithms can be used in combination with ProteinOrtho, a sequence similarity-based orthology detection tool, to extract a set of robust orthology/paralogy relationships.

  19. Orthology and paralogy constraints: satisfiability and consistency

    PubMed Central

    2014-01-01

    Background A variety of methods based on sequence similarity, reconciliation, synteny or functional characteristics, can be used to infer orthology and paralogy relations between genes of a given gene family  G. But is a given set  C of orthology/paralogy constraints possible, i.e., can they simultaneously co-exist in an evolutionary history for  G? While previous studies have focused on full sets of constraints, here we consider the general case where  C does not necessarily involve a constraint for each pair of genes. The problem is subdivided in two parts: (1) Is  C satisfiable, i.e. can we find an event-labeled gene tree G inducing  C? (2) Is there such a G which is consistent, i.e., such that all displayed triplet phylogenies are included in a species tree? Results Previous results on the Graph sandwich problem can be used to answer to (1), and we provide polynomial-time algorithms for satisfiability and consistency with a given species tree. We also describe a new polynomial-time algorithm for the case of consistency with an unknown species tree and full knowledge of pairwise orthology/paralogy relationships, as well as a branch-and-bound algorithm in the case when unknown relations are present. We show that our algorithms can be used in combination with ProteinOrtho, a sequence similarity-based orthology detection tool, to extract a set of robust orthology/paralogy relationships. PMID:25572629

  20. Development of Gis Tool for the Solution of Minimum Spanning Tree Problem using Prim's Algorithm

    NASA Astrophysics Data System (ADS)

    Dutta, S.; Patra, D.; Shankar, H.; Alok Verma, P.

    2014-11-01

    minimum spanning tree (MST) of a connected, undirected and weighted network is a tree of that network consisting of all its nodes and the sum of weights of all its edges is minimum among all such possible spanning trees of the same network. In this study, we have developed a new GIS tool using most commonly known rudimentary algorithm called Prim's algorithm to construct the minimum spanning tree of a connected, undirected and weighted road network. This algorithm is based on the weight (adjacency) matrix of a weighted network and helps to solve complex network MST problem easily, efficiently and effectively. The selection of the appropriate algorithm is very essential otherwise it will be very hard to get an optimal result. In case of Road Transportation Network, it is very essential to find the optimal results by considering all the necessary points based on cost factor (time or distance). This paper is based on solving the Minimum Spanning Tree (MST) problem of a road network by finding it's minimum span by considering all the important network junction point. GIS technology is usually used to solve the network related problems like the optimal path problem, travelling salesman problem, vehicle routing problems, location-allocation problems etc. Therefore, in this study we have developed a customized GIS tool using Python script in ArcGIS software for the solution of MST problem for a Road Transportation Network of Dehradun city by considering distance and time as the impedance (cost) factors. It has a number of advantages like the users do not need a greater knowledge of the subject as the tool is user-friendly and that allows to access information varied and adapted the needs of the users. This GIS tool for MST can be applied for a nationwide plan called Prime Minister Gram Sadak Yojana in India to provide optimal all weather road connectivity to unconnected villages (points). This tool is also useful for constructing highways or railways spanning several cities optimally or connecting all cities with minimum total road length.

  1. Mirroring co-evolving trees in the light of their topologies.

    PubMed

    Hajirasouliha, Iman; Schönhuth, Alexander; de Juan, David; Valencia, Alfonso; Sahinalp, S Cenk

    2012-05-01

    Determining the interaction partners among protein/domain families poses hard computational problems, in particular in the presence of paralogous proteins. Available approaches aim to identify interaction partners among protein/domain families through maximizing the similarity between trimmed versions of their phylogenetic trees. Since maximization of any natural similarity score is computationally difficult, many approaches employ heuristics to evaluate the distance matrices corresponding to the tree topologies in question. In this article, we devise an efficient deterministic algorithm which directly maximizes the similarity between two leaf labeled trees with edge lengths, obtaining a score-optimal alignment of the two trees in question. Our algorithm is significantly faster than those methods based on distance matrix comparison: 1 min on a single processor versus 730 h on a supercomputer. Furthermore, we outperform the current state-of-the-art exhaustive search approach in terms of precision, while incurring acceptable losses in recall. A C implementation of the method demonstrated in this article is available at http://compbio.cs.sfu.ca/mirrort.htm

  2. Evolving optimised decision rules for intrusion detection using particle swarm paradigm

    NASA Astrophysics Data System (ADS)

    Sivatha Sindhu, Siva S.; Geetha, S.; Kannan, A.

    2012-12-01

    The aim of this article is to construct a practical intrusion detection system (IDS) that properly analyses the statistics of network traffic pattern and classify them as normal or anomalous class. The objective of this article is to prove that the choice of effective network traffic features and a proficient machine-learning paradigm enhances the detection accuracy of IDS. In this article, a rule-based approach with a family of six decision tree classifiers, namely Decision Stump, C4.5, Naive Baye's Tree, Random Forest, Random Tree and Representative Tree model to perform the detection of anomalous network pattern is introduced. In particular, the proposed swarm optimisation-based approach selects instances that compose training set and optimised decision tree operate over this trained set producing classification rules with improved coverage, classification capability and generalisation ability. Experiment with the Knowledge Discovery and Data mining (KDD) data set which have information on traffic pattern, during normal and intrusive behaviour shows that the proposed algorithm produces optimised decision rules and outperforms other machine-learning algorithm.

  3. An efficient 3D R-tree spatial index method for virtual geographic environments

    NASA Astrophysics Data System (ADS)

    Zhu, Qing; Gong, Jun; Zhang, Yeting

    A three-dimensional (3D) spatial index is required for real time applications of integrated organization and management in virtual geographic environments of above ground, underground, indoor and outdoor objects. Being one of the most promising methods, the R-tree spatial index has been paid increasing attention in 3D geospatial database management. Since the existing R-tree methods are usually limited by their weakness of low efficiency, due to the critical overlap of sibling nodes and the uneven size of nodes, this paper introduces the k-means clustering method and employs the 3D overlap volume, 3D coverage volume and the minimum bounding box shape value of nodes as the integrative grouping criteria. A new spatial cluster grouping algorithm and R-tree insertion algorithm is then proposed. Experimental analysis on comparative performance of spatial indexing shows that by the new method the overlap of R-tree sibling nodes is minimized drastically and a balance in the volumes of the nodes is maintained.

  4. BIMLR: a method for constructing rooted phylogenetic networks from rooted phylogenetic trees.

    PubMed

    Wang, Juan; Guo, Maozu; Xing, Linlin; Che, Kai; Liu, Xiaoyan; Wang, Chunyu

    2013-09-15

    Rooted phylogenetic trees constructed from different datasets (e.g. from different genes) are often conflicting with one another, i.e. they cannot be integrated into a single phylogenetic tree. Phylogenetic networks have become an important tool in molecular evolution, and rooted phylogenetic networks are able to represent conflicting rooted phylogenetic trees. Hence, the development of appropriate methods to compute rooted phylogenetic networks from rooted phylogenetic trees has attracted considerable research interest of late. The CASS algorithm proposed by van Iersel et al. is able to construct much simpler networks than other available methods, but it is extremely slow, and the networks it constructs are dependent on the order of the input data. Here, we introduce an improved CASS algorithm, BIMLR. We show that BIMLR is faster than CASS and less dependent on the input data order. Moreover, BIMLR is able to construct much simpler networks than almost all other methods. BIMLR is available at http://nclab.hit.edu.cn/wangjuan/BIMLR/. © 2013 Elsevier B.V. All rights reserved.

  5. Personalized Risk Prediction in Clinical Oncology Research: Applications and Practical Issues Using Survival Trees and Random Forests.

    PubMed

    Hu, Chen; Steingrimsson, Jon Arni

    2018-01-01

    A crucial component of making individualized treatment decisions is to accurately predict each patient's disease risk. In clinical oncology, disease risks are often measured through time-to-event data, such as overall survival and progression/recurrence-free survival, and are often subject to censoring. Risk prediction models based on recursive partitioning methods are becoming increasingly popular largely due to their ability to handle nonlinear relationships, higher-order interactions, and/or high-dimensional covariates. The most popular recursive partitioning methods are versions of the Classification and Regression Tree (CART) algorithm, which builds a simple interpretable tree structured model. With the aim of increasing prediction accuracy, the random forest algorithm averages multiple CART trees, creating a flexible risk prediction model. Risk prediction models used in clinical oncology commonly use both traditional demographic and tumor pathological factors as well as high-dimensional genetic markers and treatment parameters from multimodality treatments. In this article, we describe the most commonly used extensions of the CART and random forest algorithms to right-censored outcomes. We focus on how they differ from the methods for noncensored outcomes, and how the different splitting rules and methods for cost-complexity pruning impact these algorithms. We demonstrate these algorithms by analyzing a randomized Phase III clinical trial of breast cancer. We also conduct Monte Carlo simulations to compare the prediction accuracy of survival forests with more commonly used regression models under various scenarios. These simulation studies aim to evaluate how sensitive the prediction accuracy is to the underlying model specifications, the choice of tuning parameters, and the degrees of missing covariates.

  6. Initialization Method for Grammar-Guided Genetic Programming

    NASA Astrophysics Data System (ADS)

    García-Arnau, M.; Manrique, D.; Ríos, J.; Rodríguez-Patón, A.

    This paper proposes a new tree-generation algorithm for grammarguided genetic programming that includes a parameter to control the maximum size of the trees to be generated. An important feature of this algorithm is that the initial populations generated are adequately distributed in terms of tree size and distribution within the search space. Consequently, genetic programming systems starting from the initial populations generated by the proposed method have a higher convergence speed. Two different problems have been chosen to carry out the experiments: a laboratory test involving searching for arithmetical equalities and the real-world task of breast cancer prognosis. In both problems, comparisons have been made to another five important initialization methods.

  7. Automatic determination of trunk diameter, crown base and height of scots pine (Pinus Sylvestris L.) Based on analysis of 3D point clouds gathered from multi-station terrestrial laser scanning. (Polish Title: Automatyczne okreslanie srednicy pnia, podstawy korony oraz wysokosci sosny zwyczajnej (Pinus Silvestris L.) Na podstawie analiz chmur punktow 3D pochodzacych z wielostanowiskowego naziemnego skanowania laserowego)

    NASA Astrophysics Data System (ADS)

    Ratajczak, M.; Wężyk, P.

    2015-12-01

    Rapid development of terrestrial laser scanning (TLS) in recent years resulted in its recognition and implementation in many industries, including forestry and nature conservation. The use of the 3D TLS point clouds in the process of inventory of trees and stands, as well as in the determination of their biometric features (trunk diameter, tree height, crown base, number of trunk shapes), trees and lumber size (volume of trees) is slowly becoming a practice. In addition to the measurement precision, the primary added value of TLS is the ability to automate the processing of the clouds of points 3D in the direction of the extraction of selected features of trees and stands. The paper presents the original software (GNOM) for the automatic measurement of selected features of trees, based on the cloud of points obtained by the ground laser scanner FARO. With the developed algorithms (GNOM), the location of tree trunks on the circular research surface was specified and the measurement was performed; the measurement covered the DBH (l: 1.3m), further diameters of tree trunks at different heights of the tree trunk, base of the tree crown and volume of the tree trunk (the selection measurement method), as well as the tree crown. Research works were performed in the territory of the Niepolomice Forest in an unmixed pine stand (Pinussylvestris L.) on the circular surface with a radius of 18 m, within which there were 16 pine trees (14 of them were cut down). It was characterized by a two-storey and even-aged construction (147 years old) and was devoid of undergrowth. Ground scanning was performed just before harvesting. The DBH of 16 pine trees was specified in a fully automatic way, using the algorithm GNOM with an accuracy of +2.1%, as compared to the reference measurement by the DBH measurement device. The medium, absolute measurement error in the cloud of points - using semi-automatic methods "PIXEL" (between points) and PIPE (fitting the cylinder) in the FARO Scene 5.x., showed the error, 3.5% and 5.0%,.respectively The reference height was assumed as the measurement performed by the tape on the cut tree. The average error of automatic determination of the tree height by the algorithm GNOM based on the TLS point clouds amounted to 6.3% and was slightly higher than when using the manual method of measurements on profiles in the TerraScan (Terrasolid; the error of 5.6%). The relatively high value of the error may be mainly related to the small number of points TLS in the upper parts of crowns. The crown height measurement showed the error of +9.5%. The reference in this case was the tape measurement performed already on the trunks of cut pine trees. Processing the clouds of points by the algorithms GNOM for 16 analyzed trees took no longer than 10 min. (37 sec. /tree). The paper mainly showed the TLS measurement innovation and its high precision in acquiring biometric data in forestry, and at the same time also the further need to increase the degree of automation of processing the clouds of points 3D from terrestrial laser scanning.

  8. Military Periodicals.

    DTIC Science & Technology

    1983-05-01

    4401 Vine Grove Road Fort Knox, Kentucky 40121 Telephone: (502) 942-8624 Editor-in-Chief: MAJ C. R. Steiner , Jr. $10.00 Army (M) Association...Wehrkunde) Verlag Europaische Wehrkunde Gmb H Herzog- Rudolf -Str. 1 8000 Munich 22 West Germany Telephone: (089) 293883 Editor: Ewald Heinrich von

  9. A flooding algorithm for multirobot exploration.

    PubMed

    Cabrera-Mora, Flavio; Xiao, Jizhong

    2012-06-01

    In this paper, we present a multirobot exploration algorithm that aims at reducing the exploration time and to minimize the overall traverse distance of the robots by coordinating the movement of the robots performing the exploration. Modeling the environment as a tree, we consider a coordination model that restricts the number of robots allowed to traverse an edge and to enter a vertex during each step. This coordination is achieved in a decentralized manner by the robots using a set of active landmarks that are dropped by them at explored vertices. We mathematically analyze the algorithm on trees, obtaining its main properties and specifying its bounds on the exploration time. We also define three metrics of performance for multirobot algorithms. We simulate and compare the performance of this new algorithm with those of our multirobot depth first search (MR-DFS) approach presented in our recent paper and classic single-robot DFS.

  10. Multistage classification of multispectral Earth observational data: The design approach

    NASA Technical Reports Server (NTRS)

    Bauer, M. E. (Principal Investigator); Muasher, M. J.; Landgrebe, D. A.

    1981-01-01

    An algorithm is proposed which predicts the optimal features at every node in a binary tree procedure. The algorithm estimates the probability of error by approximating the area under the likelihood ratio function for two classes and taking into account the number of training samples used in estimating each of these two classes. Some results on feature selection techniques, particularly in the presence of a very limited set of training samples, are presented. Results comparing probabilities of error predicted by the proposed algorithm as a function of dimensionality as compared to experimental observations are shown for aircraft and LANDSAT data. Results are obtained for both real and simulated data. Finally, two binary tree examples which use the algorithm are presented to illustrate the usefulness of the procedure.

  11. Efficient enumeration of monocyclic chemical graphs with given path frequencies

    PubMed Central

    2014-01-01

    Background The enumeration of chemical graphs (molecular graphs) satisfying given constraints is one of the fundamental problems in chemoinformatics and bioinformatics because it leads to a variety of useful applications including structure determination and development of novel chemical compounds. Results We consider the problem of enumerating chemical graphs with monocyclic structure (a graph structure that contains exactly one cycle) from a given set of feature vectors, where a feature vector represents the frequency of the prescribed paths in a chemical compound to be constructed and the set is specified by a pair of upper and lower feature vectors. To enumerate all tree-like (acyclic) chemical graphs from a given set of feature vectors, Shimizu et al. and Suzuki et al. proposed efficient branch-and-bound algorithms based on a fast tree enumeration algorithm. In this study, we devise a novel method for extending these algorithms to enumeration of chemical graphs with monocyclic structure by designing a fast algorithm for testing uniqueness. The results of computational experiments reveal that the computational efficiency of the new algorithm is as good as those for enumeration of tree-like chemical compounds. Conclusions We succeed in expanding the class of chemical graphs that are able to be enumerated efficiently. PMID:24955135

  12. Treecode with a Special-Purpose Processor

    NASA Astrophysics Data System (ADS)

    Makino, Junichiro

    1991-08-01

    We describe an implementation of the modified Barnes-Hut tree algorithm for a gravitational N-body calculation on a GRAPE (GRAvity PipE) backend processor. GRAPE is a special-purpose computer for N-body calculations. It receives the positions and masses of particles from a host computer and then calculates the gravitational force at each coordinate specified by the host. To use this GRAPE processor with the hierarchical tree algorithm, the host computer must maintain a list of all nodes that exert force on a particle. If we create this list for each particle of the system at each timestep, the number of floating-point operations on the host and that on GRAPE would become comparable, and the increased speed obtained by using GRAPE would be small. In our modified algorithm, we create a list of nodes for many particles. Thus, the amount of the work required of the host is significantly reduced. This algorithm was originally developed by Barnes in order to vectorize the force calculation on a Cyber 205. With this algorithm, the computing time of the force calculation becomes comparable to that of the tree construction, if the GRAPE backend processor is sufficiently fast. The obtained speed-up factor is 30 to 50 for a RISC-based host computer and GRAPE-1A with a peak speed of 240 Mflops.

  13. Forest structures retrieval from LiDAR onboard ULA

    NASA Astrophysics Data System (ADS)

    Shang, Xiaoxia; Chazette, Patrick; Totems, Julien; Marnas, Fabien; Sanak, Joseph

    2013-04-01

    Following the United Nations Framework Convention on Climate Change, the assessment of forest carbon stock is one of the main elements for a better understanding of the carbon cycle and its evolution following the climate change. The forests sequester 80% of the continental biospheric carbon and this efficiency is a function of the tree species and the tree health. The airborne backscatter LiDAR onboard the ultra light aircraft (ULA) can provide the key information on the forest vertical structures and evolution in the time. The most important structural parameter is the tree top height, which is directly linked to the above-ground biomass using non-linear relationships. In order to test the LiDAR capability for retrieving the tree top height, the LiDAR ULICE (Ultraviolet LIdar for Canopy Experiment) has been used over different forest types, from coniferous (maritime pins) to deciduous (oaks, hornbeams ...) trees. ULICE works at the wavelength of 355 nm with a sampling along the line-of-sight between 15 and 75 cm. According to the LiDAR signal to noise ratio (SNR), two different algorithms have been used in our study. The first algorithm is a threshold method directly based on the comparison between the LiDAR signal and the noise distributions, while the second one used a low pass filter by fitting a Gaussian curve family. In this paper, we will present these two algorithms and their evolution as a function of the SNR. The main error sources will be also discussed and assessed for each algorithm. The results show that these algorithms have great potential for ground-segment of future space borne LiDAR missions dedicated to the forest survey at the global scale. Acknowledgements: the canopy LiDAR system ULICE has been developed by CEA (Commissariat à l'Energie Atomique). It has been deployed with the support of CNES (Centre National d'Etude Spariales) and ANR (Agence Nationale de la Recherche). We acknowledge the ULA pilots Franck Toussaint for logistical help during the ULA campaign.

  14. Deriving Continuous Fields of Tree Cover at 1-m over the Continental United States From the National Agriculture Imagery Program (NAIP) Imagery to Reduce Uncertainties in Forest Carbon Stock Estimation

    NASA Astrophysics Data System (ADS)

    Ganguly, S.; Basu, S.; Mukhopadhyay, S.; Michaelis, A.; Milesi, C.; Votava, P.; Nemani, R. R.

    2013-12-01

    An unresolved issue with coarse-to-medium resolution satellite-based forest carbon mapping over regional to continental scales is the high level of uncertainty in above ground biomass (AGB) estimates caused by the absence of forest cover information at a high enough spatial resolution (current spatial resolution is limited to 30-m). To put confidence in existing satellite-derived AGB density estimates, it is imperative to create continuous fields of tree cover at a sufficiently high resolution (e.g. 1-m) such that large uncertainties in forested area are reduced. The proposed work will provide means to reduce uncertainty in present satellite-derived AGB maps and Forest Inventory and Analysis (FIA) based regional estimates. Our primary objective will be to create Very High Resolution (VHR) estimates of tree cover at a spatial resolution of 1-m for the Continental United States using all available National Agriculture Imaging Program (NAIP) color-infrared imagery from 2010 till 2012. We will leverage the existing capabilities of the NASA Earth Exchange (NEX) high performance computing and storage facilities. The proposed 1-m tree cover map can be further aggregated to provide percent tree cover at any medium-to-coarse resolution spatial grid, which will aid in reducing uncertainties in AGB density estimation at the respective grid and overcome current limitations imposed by medium-to-coarse resolution land cover maps. We have implemented a scalable and computationally-efficient parallelized framework for tree-cover delineation - the core components of the algorithm [that] include a feature extraction process, a Statistical Region Merging image segmentation algorithm and a classification algorithm based on Deep Belief Network and a Feedforward Backpropagation Neural Network algorithm. An initial pilot exercise has been performed over the state of California (~11,000 scenes) to create a wall-to-wall 1-m tree cover map and the classification accuracy has been assessed. Results show an improvement in accuracy of tree-cover delineation as compared to existing forest cover maps from NLCD, especially over fragmented, heterogeneous and urban landscapes. Estimates of VHR tree cover will complement and enhance the accuracy of present remote-sensing based AGB modeling approaches and forest inventory based estimates at both national and local scales. A requisite step will be to characterize the inherent uncertainties in tree cover estimates and propagate them to estimate AGB.

  15. Node Redeployment Algorithm Based on Stratified Connected Tree for Underwater Sensor Networks

    PubMed Central

    Liu, Jun; Jiang, Peng; Wu, Feng; Yu, Shanen; Song, Chunyue

    2016-01-01

    During the underwater sensor networks (UWSNs) operation, node drift with water environment causes network topology changes. Periodic node location examination and adjustment are needed to maintain good network monitoring quality as long as possible. In this paper, a node redeployment algorithm based on stratified connected tree for UWSNs is proposed. At every network adjustment moment, self-examination and adjustment on node locations are performed firstly. If a node is outside the monitored space, it returns to the last location recorded in its memory along straight line. Later, the network topology is stratified into a connected tree that takes the sink node as the root node by broadcasting ready information level by level, which can improve the network connectivity rate. Finally, with synthetically considering network coverage and connectivity rates, and node movement distance, the sink node performs centralized optimization on locations of leaf nodes in the stratified connected tree. Simulation results show that the proposed redeployment algorithm can not only keep the number of nodes in the monitored space as much as possible and maintain good network coverage and connectivity rates during network operation, but also reduce node movement distance during node redeployment and prolong the network lifetime. PMID:28029124

  16. Intelligent Diagnostic Assistant for Complicated Skin Diseases through C5's Algorithm.

    PubMed

    Jeddi, Fatemeh Rangraz; Arabfard, Masoud; Kermany, Zahra Arab

    2017-09-01

    Intelligent Diagnostic Assistant can be used for complicated diagnosis of skin diseases, which are among the most common causes of disability. The aim of this study was to design and implement a computerized intelligent diagnostic assistant for complicated skin diseases through C5's Algorithm. An applied-developmental study was done in 2015. Knowledge base was developed based on interviews with dermatologists through questionnaires and checklists. Knowledge representation was obtained from the train data in the database using Excel Microsoft Office. Clementine Software and C5's Algorithms were applied to draw the decision tree. Analysis of test accuracy was performed based on rules extracted using inference chains. The rules extracted from the decision tree were entered into the CLIPS programming environment and the intelligent diagnostic assistant was designed then. The rules were defined using forward chaining inference technique and were entered into Clips programming environment as RULE. The accuracy and error rates obtained in the training phase from the decision tree were 99.56% and 0.44%, respectively. The accuracy of the decision tree was 98% and the error was 2% in the test phase. Intelligent diagnostic assistant can be used as a reliable system with high accuracy, sensitivity, specificity, and agreement.

  17. Optimal tree-stem bucking of northeastern species of China

    Treesearch

    Jingxin Wang; Chris B. LeDoux; Joseph McNeel

    2004-01-01

    An application of optimal tree-stem bucking to the northeastern tree species of China is reported. The bucking procedures used in this region are summarized, which are the basic guidelines for the optimal bucking design. The directed graph approach was adopted to generate the bucking patterns by using the network analysis labeling algorithm. A computer-based bucking...

  18. Principal component analysis and the locus of the Fréchet mean in the space of phylogenetic trees.

    PubMed

    Nye, Tom M W; Tang, Xiaoxian; Weyenberg, Grady; Yoshida, Ruriko

    2017-12-01

    Evolutionary relationships are represented by phylogenetic trees, and a phylogenetic analysis of gene sequences typically produces a collection of these trees, one for each gene in the analysis. Analysis of samples of trees is difficult due to the multi-dimensionality of the space of possible trees. In Euclidean spaces, principal component analysis is a popular method of reducing high-dimensional data to a low-dimensional representation that preserves much of the sample's structure. However, the space of all phylogenetic trees on a fixed set of species does not form a Euclidean vector space, and methods adapted to tree space are needed. Previous work introduced the notion of a principal geodesic in this space, analogous to the first principal component. Here we propose a geometric object for tree space similar to the [Formula: see text]th principal component in Euclidean space: the locus of the weighted Fréchet mean of [Formula: see text] vertex trees when the weights vary over the [Formula: see text]-simplex. We establish some basic properties of these objects, in particular showing that they have dimension [Formula: see text], and propose algorithms for projection onto these surfaces and for finding the principal locus associated with a sample of trees. Simulation studies demonstrate that these algorithms perform well, and analyses of two datasets, containing Apicomplexa and African coelacanth genomes respectively, reveal important structure from the second principal components.

  19. An efficient non-dominated sorting method for evolutionary algorithms.

    PubMed

    Fang, Hongbing; Wang, Qian; Tu, Yi-Cheng; Horstemeyer, Mark F

    2008-01-01

    We present a new non-dominated sorting algorithm to generate the non-dominated fronts in multi-objective optimization with evolutionary algorithms, particularly the NSGA-II. The non-dominated sorting algorithm used by NSGA-II has a time complexity of O(MN(2)) in generating non-dominated fronts in one generation (iteration) for a population size N and M objective functions. Since generating non-dominated fronts takes the majority of total computational time (excluding the cost of fitness evaluations) of NSGA-II, making this algorithm faster will significantly improve the overall efficiency of NSGA-II and other genetic algorithms using non-dominated sorting. The new non-dominated sorting algorithm proposed in this study reduces the number of redundant comparisons existing in the algorithm of NSGA-II by recording the dominance information among solutions from their first comparisons. By utilizing a new data structure called the dominance tree and the divide-and-conquer mechanism, the new algorithm is faster than NSGA-II for different numbers of objective functions. Although the number of solution comparisons by the proposed algorithm is close to that of NSGA-II when the number of objectives becomes large, the total computational time shows that the proposed algorithm still has better efficiency because of the adoption of the dominance tree structure and the divide-and-conquer mechanism.

  20. Land cover and land use mapping of the iSimangaliso Wetland Park, South Africa: comparison of oblique and orthogonal random forest algorithms

    NASA Astrophysics Data System (ADS)

    Bassa, Zaakirah; Bob, Urmilla; Szantoi, Zoltan; Ismail, Riyad

    2016-01-01

    In recent years, the popularity of tree-based ensemble methods for land cover classification has increased significantly. Using WorldView-2 image data, we evaluate the potential of the oblique random forest algorithm (oRF) to classify a highly heterogeneous protected area. In contrast to the random forest (RF) algorithm, the oRF algorithm builds multivariate trees by learning the optimal split using a supervised model. The oRF binary algorithm is adapted to a multiclass land cover and land use application using both the "one-against-one" and "one-against-all" combination approaches. Results show that the oRF algorithms are capable of achieving high classification accuracies (>80%). However, there was no statistical difference in classification accuracies obtained by the oRF algorithms and the more popular RF algorithm. For all the algorithms, user accuracies (UAs) and producer accuracies (PAs) >80% were recorded for most of the classes. Both the RF and oRF algorithms poorly classified the indigenous forest class as indicated by the low UAs and PAs. Finally, the results from this study advocate and support the utility of the oRF algorithm for land cover and land use mapping of protected areas using WorldView-2 image data.

  1. Parenting as a Vocation: Lifelong Learning Can Begin in the Home.

    ERIC Educational Resources Information Center

    Stehlik, Tom

    2003-01-01

    Reviews theories of adult learning over the lifespan grounded in anthroposophy, the philosophy of Rudolf Steiner's Waldorf Schools. Examines parenting as a vocation through this perspective and the implications for the learning needs of parents. (Contains 35 references.) (SK)

  2. A simple and robust classification tree for differentiation between benign and malignant lesions in MR-mammography.

    PubMed

    Baltzer, Pascal A T; Dietzel, Matthias; Kaiser, Werner A

    2013-08-01

    In the face of multiple available diagnostic criteria in MR-mammography (MRM), a practical algorithm for lesion classification is needed. Such an algorithm should be as simple as possible and include only important independent lesion features to differentiate benign from malignant lesions. This investigation aimed to develop a simple classification tree for differential diagnosis in MRM. A total of 1,084 lesions in standardised MRM with subsequent histological verification (648 malignant, 436 benign) were investigated. Seventeen lesion criteria were assessed by 2 readers in consensus. Classification analysis was performed using the chi-squared automatic interaction detection (CHAID) method. Results include the probability for malignancy for every descriptor combination in the classification tree. A classification tree incorporating 5 lesion descriptors with a depth of 3 ramifications (1, root sign; 2, delayed enhancement pattern; 3, border, internal enhancement and oedema) was calculated. Of all 1,084 lesions, 262 (40.4 %) and 106 (24.3 %) could be classified as malignant and benign with an accuracy above 95 %, respectively. Overall diagnostic accuracy was 88.4 %. The classification algorithm reduced the number of categorical descriptors from 17 to 5 (29.4 %), resulting in a high classification accuracy. More than one third of all lesions could be classified with accuracy above 95 %. • A practical algorithm has been developed to classify lesions found in MR-mammography. • A simple decision tree consisting of five criteria reaches high accuracy of 88.4 %. • Unique to this approach, each classification is associated with a diagnostic certainty. • Diagnostic certainty of greater than 95 % is achieved in 34 % of all cases.

  3. Statistical Methods in Ai: Rare Event Learning Using Associative Rules and Higher-Order Statistics

    NASA Astrophysics Data System (ADS)

    Iyer, V.; Shetty, S.; Iyengar, S. S.

    2015-07-01

    Rare event learning has not been actively researched since lately due to the unavailability of algorithms which deal with big samples. The research addresses spatio-temporal streams from multi-resolution sensors to find actionable items from a perspective of real-time algorithms. This computing framework is independent of the number of input samples, application domain, labelled or label-less streams. A sampling overlap algorithm such as Brooks-Iyengar is used for dealing with noisy sensor streams. We extend the existing noise pre-processing algorithms using Data-Cleaning trees. Pre-processing using ensemble of trees using bagging and multi-target regression showed robustness to random noise and missing data. As spatio-temporal streams are highly statistically correlated, we prove that a temporal window based sampling from sensor data streams converges after n samples using Hoeffding bounds. Which can be used for fast prediction of new samples in real-time. The Data-cleaning tree model uses a nonparametric node splitting technique, which can be learned in an iterative way which scales linearly in memory consumption for any size input stream. The improved task based ensemble extraction is compared with non-linear computation models using various SVM kernels for speed and accuracy. We show using empirical datasets the explicit rule learning computation is linear in time and is only dependent on the number of leafs present in the tree ensemble. The use of unpruned trees (t) in our proposed ensemble always yields minimum number (m) of leafs keeping pre-processing computation to n × t log m compared to N2 for Gram Matrix. We also show that the task based feature induction yields higher Qualify of Data (QoD) in the feature space compared to kernel methods using Gram Matrix.

  4. Analytical and CASE study on Limited Search, ID3, CHAID, C4.5, Improved C4.5 and OVA Decision Tree Algorithms to design Decision Support System

    NASA Astrophysics Data System (ADS)

    Kaur, Parneet; Singh, Sukhwinder; Garg, Sushil; Harmanpreet

    2010-11-01

    In this paper we study about classification algorithms for farm DSS. By applying classification algorithms i.e. Limited search, ID3, CHAID, C4.5, Improved C4.5 and One VS all Decision Tree on common data set of crop with specified class, results are obtained. The tool used to derive results is SPINA. The graphical results obtained from tool are compared to suggest best technique to develop farm Decision Support System. This analysis would help to researchers to design effective and fast DSS for farmer to take decision for enhancing their yield.

  5. Toward a Better Compression for DNA Sequences Using Huffman Encoding

    PubMed Central

    Almarri, Badar; Al Yami, Sultan; Huang, Chun-Hsi

    2017-01-01

    Abstract Due to the significant amount of DNA data that are being generated by next-generation sequencing machines for genomes of lengths ranging from megabases to gigabases, there is an increasing need to compress such data to a less space and a faster transmission. Different implementations of Huffman encoding incorporating the characteristics of DNA sequences prove to better compress DNA data. These implementations center on the concepts of selecting frequent repeats so as to force a skewed Huffman tree, as well as the construction of multiple Huffman trees when encoding. The implementations demonstrate improvements on the compression ratios for five genomes with lengths ranging from 5 to 50 Mbp, compared with the standard Huffman tree algorithm. The research hence suggests an improvement on all such DNA sequence compression algorithms that use the conventional Huffman encoding. The research suggests an improvement on all DNA sequence compression algorithms that use the conventional Huffman encoding. Accompanying software is publicly available (AL-Okaily, 2016). PMID:27960065

  6. Toward a Better Compression for DNA Sequences Using Huffman Encoding.

    PubMed

    Al-Okaily, Anas; Almarri, Badar; Al Yami, Sultan; Huang, Chun-Hsi

    2017-04-01

    Due to the significant amount of DNA data that are being generated by next-generation sequencing machines for genomes of lengths ranging from megabases to gigabases, there is an increasing need to compress such data to a less space and a faster transmission. Different implementations of Huffman encoding incorporating the characteristics of DNA sequences prove to better compress DNA data. These implementations center on the concepts of selecting frequent repeats so as to force a skewed Huffman tree, as well as the construction of multiple Huffman trees when encoding. The implementations demonstrate improvements on the compression ratios for five genomes with lengths ranging from 5 to 50 Mbp, compared with the standard Huffman tree algorithm. The research hence suggests an improvement on all such DNA sequence compression algorithms that use the conventional Huffman encoding. The research suggests an improvement on all DNA sequence compression algorithms that use the conventional Huffman encoding. Accompanying software is publicly available (AL-Okaily, 2016 ).

  7. Technology transfer by means of fault tree synthesis

    NASA Astrophysics Data System (ADS)

    Batzias, Dimitris F.

    2012-12-01

    Since Fault Tree Analysis (FTA) attempts to model and analyze failure processes of engineering, it forms a common technique for good industrial practice. On the contrary, fault tree synthesis (FTS) refers to the methodology of constructing complex trees either from dentritic modules built ad hoc or from fault tress already used and stored in a Knowledge Base. In both cases, technology transfer takes place in a quasi-inductive mode, from partial to holistic knowledge. In this work, an algorithmic procedure, including 9 activity steps and 3 decision nodes is developed for performing effectively this transfer when the fault under investigation occurs within one of the latter stages of an industrial procedure with several stages in series. The main parts of the algorithmic procedure are: (i) the construction of a local fault tree within the corresponding production stage, where the fault has been detected, (ii) the formation of an interface made of input faults that might occur upstream, (iii) the fuzzy (to count for uncertainty) multicriteria ranking of these faults according to their significance, and (iv) the synthesis of an extended fault tree based on the construction of part (i) and on the local fault tree of the first-ranked fault in part (iii). An implementation is presented, referring to 'uneven sealing of Al anodic film', thus proving the functionality of the developed methodology.

  8. Adaptive Broadcasting Mechanism for Bandwidth Allocation in Mobile Services

    PubMed Central

    Horng, Gwo-Jiun; Wang, Chi-Hsuan; Chou, Chih-Lun

    2014-01-01

    This paper proposes a tree-based adaptive broadcasting (TAB) algorithm for data dissemination to improve data access efficiency. The proposed TAB algorithm first constructs a broadcast tree to determine the broadcast frequency of each data and splits the broadcast tree into some broadcast wood to generate the broadcast program. In addition, this paper develops an analytical model to derive the mean access latency of the generated broadcast program. In light of the derived results, both the index channel's bandwidth and the data channel's bandwidth can be optimally allocated to maximize bandwidth utilization. This paper presents experiments to help evaluate the effectiveness of the proposed strategy. From the experimental results, it can be seen that the proposed mechanism is feasible in practice. PMID:25057509

  9. Data-Parallel Algorithm for Contour Tree Construction

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

    Sewell, Christopher Meyer; Ahrens, James Paul; Carr, Hamish

    2017-01-19

    The goal of this project is to develop algorithms for additional visualization and analysis filters in order to expand the functionality of the VTK-m toolkit to support less critical but commonly used operators.

  10. Searching Dynamic Agents with a Team of Mobile Robots

    PubMed Central

    Juliá, Miguel; Gil, Arturo; Reinoso, Oscar

    2012-01-01

    This paper presents a new algorithm that allows a team of robots to cooperatively search for a set of moving targets. An estimation of the areas of the environment that are more likely to hold a target agent is obtained using a grid-based Bayesian filter. The robot sensor readings and the maximum speed of the moving targets are used in order to update the grid. This representation is used in a search algorithm that commands the robots to those areas that are more likely to present target agents. This algorithm splits the environment in a tree of connected regions using dynamic programming. This tree is used in order to decide the destination for each robot in a coordinated manner. The algorithm has been successfully tested in known and unknown environments showing the validity of the approach. PMID:23012519

  11. Searching dynamic agents with a team of mobile robots.

    PubMed

    Juliá, Miguel; Gil, Arturo; Reinoso, Oscar

    2012-01-01

    This paper presents a new algorithm that allows a team of robots to cooperatively search for a set of moving targets. An estimation of the areas of the environment that are more likely to hold a target agent is obtained using a grid-based Bayesian filter. The robot sensor readings and the maximum speed of the moving targets are used in order to update the grid. This representation is used in a search algorithm that commands the robots to those areas that are more likely to present target agents. This algorithm splits the environment in a tree of connected regions using dynamic programming. This tree is used in order to decide the destination for each robot in a coordinated manner. The algorithm has been successfully tested in known and unknown environments showing the validity of the approach.

  12. New methods, algorithms, and software for rapid mapping of tree positions in coordinate forest plots

    Treesearch

    A. Dan Wilson

    2000-01-01

    The theories and methodologies for two new tree mapping methods, the Sequential-target method and the Plot-origin radial method, are described. The methods accommodate the use of any conventional distance measuring device and compass to collect horizontal distance and azimuth data between source or reference positions (origins) and target trees. Conversion equations...

  13. Optimal Path Planning Program for Autonomous Speed Sprayer in Orchard Using Order-Picking Algorithm

    NASA Astrophysics Data System (ADS)

    Park, T. S.; Park, S. J.; Hwang, K. Y.; Cho, S. I.

    This study was conducted to develop a software program which computes optimal path for autonomous navigation in orchard, especially for speed sprayer. Possibilities of autonomous navigation in orchard were shown by other researches which have minimized distance error between planned path and performed path. But, research of planning an optimal path for speed sprayer in orchard is hardly founded. In this study, a digital map and a database for orchard which contains GPS coordinate information (coordinates of trees and boundary of orchard) and entity information (heights and widths of trees, radius of main stem of trees, disease of trees) was designed. An orderpicking algorithm which has been used for management of warehouse was used to calculate optimum path based on the digital map. Database for digital map was created by using Microsoft Access and graphic interface for database was made by using Microsoft Visual C++ 6.0. It was possible to search and display information about boundary of an orchard, locations of trees, daily plan for scattering chemicals and plan optimal path on different orchard based on digital map, on each circumstance (starting speed sprayer in different location, scattering chemicals for only selected trees).

  14. Real-Time Interactive Tree Animation.

    PubMed

    Quigley, Ed; Yu, Yue; Huang, Jingwei; Lin, Winnie; Fedkiw, Ronald

    2018-05-01

    We present a novel method for posing and animating botanical tree models interactively in real time. Unlike other state of the art methods which tend to produce trees that are overly flexible, bending and deforming as if they were underwater plants, our approach allows for arbitrarily high stiffness while still maintaining real-time frame rates without spurious artifacts, even on quite large trees with over ten thousand branches. This is accomplished by using an articulated rigid body model with as-stiff-as-desired rotational springs in conjunction with our newly proposed simulation technique, which is motivated both by position based dynamics and the typical algorithms for articulated rigid bodies. The efficiency of our algorithm allows us to pose and animate trees with millions of branches or alternatively simulate a small forest comprised of many highly detailed trees. Even using only a single CPU core, we can simulate ten thousand branches in real time while still maintaining quite crisp user interactivity. This has allowed us to incorporate our framework into a commodity game engine to run interactively even on a low-budget tablet. We show that our method is amenable to the incorporation of a large variety of desirable effects such as wind, leaves, fictitious forces, collisions, fracture, etc.

  15. Directions in Rehabilitation Counseling, 2001.

    ERIC Educational Resources Information Center

    Flach, Frederic, Ed.

    2001-01-01

    This volume of 12 lessons provides expert information on a variety of medical and psychological issues in rehabilitative counseling. The lessons, which may be applied toward continuing education credits, are: (1) "Integration of Psychiatric Treatment and Rehabilitation" (Jeanne Steiner, Larry Davidson, Michael A. Hoge, and Selby Jacobs);…

  16. Teacher Training in Curative Education.

    ERIC Educational Resources Information Center

    Juul, Kristen D.; Maier, Manfred

    1992-01-01

    This article considers the application of the philosophical and educational principles of Rudolf Steiner, called "anthroposophy," to the training of teachers and curative educators in the Waldorf schools. Special emphasis is on the Camphill movement which focuses on therapeutic schools and communities for children with special needs. (DB)

  17. 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.

  18. Analyzing the genes related to Alzheimer's disease via a network and pathway-based approach.

    PubMed

    Hu, Yan-Shi; Xin, Juncai; Hu, Ying; Zhang, Lei; Wang, Ju

    2017-04-27

    Our understanding of the molecular mechanisms underlying Alzheimer's disease (AD) remains incomplete. Previous studies have revealed that genetic factors provide a significant contribution to the pathogenesis and development of AD. In the past years, numerous genes implicated in this disease have been identified via genetic association studies on candidate genes or at the genome-wide level. However, in many cases, the roles of these genes and their interactions in AD are still unclear. A comprehensive and systematic analysis focusing on the biological function and interactions of these genes in the context of AD will therefore provide valuable insights to understand the molecular features of the disease. In this study, we collected genes potentially associated with AD by screening publications on genetic association studies deposited in PubMed. The major biological themes linked with these genes were then revealed by function and biochemical pathway enrichment analysis, and the relation between the pathways was explored by pathway crosstalk analysis. Furthermore, the network features of these AD-related genes were analyzed in the context of human interactome and an AD-specific network was inferred using the Steiner minimal tree algorithm. We compiled 430 human genes reported to be associated with AD from 823 publications. Biological theme analysis indicated that the biological processes and biochemical pathways related to neurodevelopment, metabolism, cell growth and/or survival, and immunology were enriched in these genes. Pathway crosstalk analysis then revealed that the significantly enriched pathways could be grouped into three interlinked modules-neuronal and metabolic module, cell growth/survival and neuroendocrine pathway module, and immune response-related module-indicating an AD-specific immune-endocrine-neuronal regulatory network. Furthermore, an AD-specific protein network was inferred and novel genes potentially associated with AD were identified. By means of network and pathway-based methodology, we explored the pathogenetic mechanism underlying AD at a systems biology level. Results from our work could provide valuable clues for understanding the molecular mechanism underlying AD. In addition, the framework proposed in this study could be used to investigate the pathological molecular network and genes relevant to other complex diseases or phenotypes.

  19. Characterizing the degree of convective clustering using radar reflectivity and its application to evaluating model simulations

    NASA Astrophysics Data System (ADS)

    Cheng, W. Y.; Kim, D.; Rowe, A.; Park, S.

    2017-12-01

    Despite the impact of mesoscale convective organization on the properties of convection (e.g., mixing between updrafts and environment), parameterizing the degree of convective organization has only recently been attempted in cumulus parameterization schemes (e.g., Unified Convection Scheme UNICON). Additionally, challenges remain in determining the degree of convective organization from observations and in comparing directly with the organization metrics in model simulations. This study addresses the need to objectively quantify the degree of mesoscale convective organization using high quality S-PolKa radar data from the DYNAMO field campaign. One of the most noticeable aspects of mesoscale convective organization in radar data is the degree of convective clustering, which can be characterized by the number and size distribution of convective echoes and the distance between them. We propose a method of defining contiguous convective echoes (CCEs) using precipitating convective echoes identified by a rain type classification algorithm. Two classification algorithms, Steiner et al. (1995) and Powell et al. (2016), are tested and evaluated against high-resolution WRF simulations to determine which method better represents the degree of convective clustering. Our results suggest that the CCEs based on Powell et al.'s algorithm better represent the dynamical properties of the convective updrafts and thus provide the basis of a metric for convective organization. Furthermore, through a comparison with the observational data, the WRF simulations driven by the DYNAMO large-scale forcing, similarly applied to UNICON Single Column Model simulations, will allow us to evaluate the ability of both WRF and UNICON to simulate convective clustering. This evaluation is based on the physical processes that are explicitly represented in WRF and UNICON, including the mechanisms leading to convective clustering, and the feedback to the convective properties.

  20. Decision-Tree Analysis for Predicting First-Time Pass/Fail Rates for the NCLEX-RN® in Associate Degree Nursing Students.

    PubMed

    Chen, Hsiu-Chin; Bennett, Sean

    2016-08-01

    Little evidence shows the use of decision-tree algorithms in identifying predictors and analyzing their associations with pass rates for the NCLEX-RN(®) in associate degree nursing students. This longitudinal and retrospective cohort study investigated whether a decision-tree algorithm could be used to develop an accurate prediction model for the students' passing or failing the NCLEX-RN. This study used archived data from 453 associate degree nursing students in a selected program. The chi-squared automatic interaction detection analysis of the decision trees module was used to examine the effect of the collected predictors on passing/failing the NCLEX-RN. The actual percentage scores of Assessment Technologies Institute®'s RN Comprehensive Predictor(®) accurately identified students at risk of failing. The classification model correctly classified 92.7% of the students for passing. This study applied the decision-tree model to analyze a sequence database for developing a prediction model for early remediation in preparation for the NCLEXRN. [J Nurs Educ. 2016;55(8):454-457.]. Copyright 2016, SLACK Incorporated.

  1. SATCHMO-JS: a webserver for simultaneous protein multiple sequence alignment and phylogenetic tree construction.

    PubMed

    Hagopian, Raffi; Davidson, John R; Datta, Ruchira S; Samad, Bushra; Jarvis, Glen R; Sjölander, Kimmen

    2010-07-01

    We present the jump-start simultaneous alignment and tree construction using hidden Markov models (SATCHMO-JS) web server for simultaneous estimation of protein multiple sequence alignments (MSAs) and phylogenetic trees. The server takes as input a set of sequences in FASTA format, and outputs a phylogenetic tree and MSA; these can be viewed online or downloaded from the website. SATCHMO-JS is an extension of the SATCHMO algorithm, and employs a divide-and-conquer strategy to jump-start SATCHMO at a higher point in the phylogenetic tree, reducing the computational complexity of the progressive all-versus-all HMM-HMM scoring and alignment. Results on a benchmark dataset of 983 structurally aligned pairs from the PREFAB benchmark dataset show that SATCHMO-JS provides a statistically significant improvement in alignment accuracy over MUSCLE, Multiple Alignment using Fast Fourier Transform (MAFFT), ClustalW and the original SATCHMO algorithm. The SATCHMO-JS webserver is available at http://phylogenomics.berkeley.edu/satchmo-js. The datasets used in these experiments are available for download at http://phylogenomics.berkeley.edu/satchmo-js/supplementary/.

  2. Calculating Higher-Order Moments of Phylogenetic Stochastic Mapping Summaries in Linear Time.

    PubMed

    Dhar, Amrit; Minin, Vladimir N

    2017-05-01

    Stochastic mapping is a simulation-based method for probabilistically mapping substitution histories onto phylogenies according to continuous-time Markov models of evolution. This technique can be used to infer properties of the evolutionary process on the phylogeny and, unlike parsimony-based mapping, conditions on the observed data to randomly draw substitution mappings that do not necessarily require the minimum number of events on a tree. Most stochastic mapping applications simulate substitution mappings only to estimate the mean and/or variance of two commonly used mapping summaries: the number of particular types of substitutions (labeled substitution counts) and the time spent in a particular group of states (labeled dwelling times) on the tree. Fast, simulation-free algorithms for calculating the mean of stochastic mapping summaries exist. Importantly, these algorithms scale linearly in the number of tips/leaves of the phylogenetic tree. However, to our knowledge, no such algorithm exists for calculating higher-order moments of stochastic mapping summaries. We present one such simulation-free dynamic programming algorithm that calculates prior and posterior mapping variances and scales linearly in the number of phylogeny tips. Our procedure suggests a general framework that can be used to efficiently compute higher-order moments of stochastic mapping summaries without simulations. We demonstrate the usefulness of our algorithm by extending previously developed statistical tests for rate variation across sites and for detecting evolutionarily conserved regions in genomic sequences.

  3. Calculating Higher-Order Moments of Phylogenetic Stochastic Mapping Summaries in Linear Time

    PubMed Central

    Dhar, Amrit

    2017-01-01

    Abstract Stochastic mapping is a simulation-based method for probabilistically mapping substitution histories onto phylogenies according to continuous-time Markov models of evolution. This technique can be used to infer properties of the evolutionary process on the phylogeny and, unlike parsimony-based mapping, conditions on the observed data to randomly draw substitution mappings that do not necessarily require the minimum number of events on a tree. Most stochastic mapping applications simulate substitution mappings only to estimate the mean and/or variance of two commonly used mapping summaries: the number of particular types of substitutions (labeled substitution counts) and the time spent in a particular group of states (labeled dwelling times) on the tree. Fast, simulation-free algorithms for calculating the mean of stochastic mapping summaries exist. Importantly, these algorithms scale linearly in the number of tips/leaves of the phylogenetic tree. However, to our knowledge, no such algorithm exists for calculating higher-order moments of stochastic mapping summaries. We present one such simulation-free dynamic programming algorithm that calculates prior and posterior mapping variances and scales linearly in the number of phylogeny tips. Our procedure suggests a general framework that can be used to efficiently compute higher-order moments of stochastic mapping summaries without simulations. We demonstrate the usefulness of our algorithm by extending previously developed statistical tests for rate variation across sites and for detecting evolutionarily conserved regions in genomic sequences. PMID:28177780

  4. Species Tree Inference Using a Mixture Model.

    PubMed

    Ullah, Ikram; Parviainen, Pekka; Lagergren, Jens

    2015-09-01

    Species tree reconstruction has been a subject of substantial research due to its central role across biology and medicine. A species tree is often reconstructed using a set of gene trees or by directly using sequence data. In either of these cases, one of the main confounding phenomena is the discordance between a species tree and a gene tree due to evolutionary events such as duplications and losses. Probabilistic methods can resolve the discordance by coestimating gene trees and the species tree but this approach poses a scalability problem for larger data sets. We present MixTreEM-DLRS: A two-phase approach for reconstructing a species tree in the presence of gene duplications and losses. In the first phase, MixTreEM, a novel structural expectation maximization algorithm based on a mixture model is used to reconstruct a set of candidate species trees, given sequence data for monocopy gene families from the genomes under study. In the second phase, PrIME-DLRS, a method based on the DLRS model (Åkerborg O, Sennblad B, Arvestad L, Lagergren J. 2009. Simultaneous Bayesian gene tree reconstruction and reconciliation analysis. Proc Natl Acad Sci U S A. 106(14):5714-5719), is used for selecting the best species tree. PrIME-DLRS can handle multicopy gene families since DLRS, apart from modeling sequence evolution, models gene duplication and loss using a gene evolution model (Arvestad L, Lagergren J, Sennblad B. 2009. The gene evolution model and computing its associated probabilities. J ACM. 56(2):1-44). We evaluate MixTreEM-DLRS using synthetic and biological data, and compare its performance with a recent genome-scale species tree reconstruction method PHYLDOG (Boussau B, Szöllősi GJ, Duret L, Gouy M, Tannier E, Daubin V. 2013. Genome-scale coestimation of species and gene trees. Genome Res. 23(2):323-330) as well as with a fast parsimony-based algorithm Duptree (Wehe A, Bansal MS, Burleigh JG, Eulenstein O. 2008. Duptree: a program for large-scale phylogenetic analyses using gene tree parsimony. Bioinformatics 24(13):1540-1541). Our method is competitive with PHYLDOG in terms of accuracy and runs significantly faster and our method outperforms Duptree in accuracy. The analysis constituted by MixTreEM without DLRS may also be used for selecting the target species tree, yielding a fast and yet accurate algorithm for larger data sets. MixTreEM is freely available at http://prime.scilifelab.se/mixtreem/. © The Author 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  5. Comparative assessment of four Steinernematidae and three Heterorhabditidae species for infectivity of larval Diabrotica virgifera virgifera

    USDA-ARS?s Scientific Manuscript database

    Larval Diabrotica virgifera virgifera LeConte were exposed to seven different entomopathogenic nematode species to test their potential infectivity in a laboratory setting. Known D. virgifera infecting nematode species Heterorhabditis bacteriophora Poinar, H. megidis Poinar, Jackson & Klein, Steiner...

  6. Faculty Involvement in Administration of Schools.

    ERIC Educational Resources Information Center

    Ogletree, Earl J.; Schmidt, Linda J.

    1992-01-01

    Contrasts the faculty-led administration of the Waldorf Schools founded by R. Steiner with the administration by local school councils established in the Chicago (Illinois) Public Schools through the School Reform Act. In Chicago, morale and status of teachers can be improved by increasing their administrative partnership. (SLD)

  7. The Nature of Imagination in Education for Sustainability

    ERIC Educational Resources Information Center

    Jensen, Sally

    2015-01-01

    The importance of imagination in education has a significant history (Egan, 1986, 2001; Eisner, 1976; Greene, 1988; Steiner, 1954; Warnock, 1976); however, scholarship is often theoretical, and the involvement of imagination in understanding sustainability is often overlooked (Jones, 1995; Judson, 2010; Stewart, 2009). Imagination has rarely been…

  8. [Visualisation methods for etheric formative forces].

    PubMed

    Burkhard, B; Kittel, R

    2009-09-01

    Rudolf Steiner, the founder of anthroposophy, suggested the development of visualisation methods for "etheric formative forces". The essential methods, their "spiritual scientific" basis and indications are described and their claims critically tested. The methods are not validated, the key criteria for diagnostic tests (reproducibility, sensitivity, specifity) are not given.

  9. The Common Vision. Reviews: Books.

    ERIC Educational Resources Information Center

    Chattin-McNichols, John

    1998-01-01

    Reviews Marshak's book describing the work of educators Maria Montessori, Rudolf Steiner, Aurobindo Ghose, and Inayat Khan. Maintains that the book gives clear, concise information on each educator and presents a common vision for children and their education; also maintains that it gives theoretical and practical information and discusses…

  10. Joint Power Charging and Routing in Wireless Rechargeable Sensor Networks.

    PubMed

    Jia, Jie; Chen, Jian; Deng, Yansha; Wang, Xingwei; Aghvami, Abdol-Hamid

    2017-10-09

    The development of wireless power transfer (WPT) technology has inspired the transition from traditional battery-based wireless sensor networks (WSNs) towards wireless rechargeable sensor networks (WRSNs). While extensive efforts have been made to improve charging efficiency, little has been done for routing optimization. In this work, we present a joint optimization model to maximize both charging efficiency and routing structure. By analyzing the structure of the optimization model, we first decompose the problem and propose a heuristic algorithm to find the optimal charging efficiency for the predefined routing tree. Furthermore, by coding the many-to-one communication topology as an individual, we further propose to apply a genetic algorithm (GA) for the joint optimization of both routing and charging. The genetic operations, including tree-based recombination and mutation, are proposed to obtain a fast convergence. Our simulation results show that the heuristic algorithm reduces the number of resident locations and the total moving distance. We also show that our proposed algorithm achieves a higher charging efficiency compared with existing algorithms.

  11. Joint Power Charging and Routing in Wireless Rechargeable Sensor Networks

    PubMed Central

    Jia, Jie; Chen, Jian; Deng, Yansha; Wang, Xingwei; Aghvami, Abdol-Hamid

    2017-01-01

    The development of wireless power transfer (WPT) technology has inspired the transition from traditional battery-based wireless sensor networks (WSNs) towards wireless rechargeable sensor networks (WRSNs). While extensive efforts have been made to improve charging efficiency, little has been done for routing optimization. In this work, we present a joint optimization model to maximize both charging efficiency and routing structure. By analyzing the structure of the optimization model, we first decompose the problem and propose a heuristic algorithm to find the optimal charging efficiency for the predefined routing tree. Furthermore, by coding the many-to-one communication topology as an individual, we further propose to apply a genetic algorithm (GA) for the joint optimization of both routing and charging. The genetic operations, including tree-based recombination and mutation, are proposed to obtain a fast convergence. Our simulation results show that the heuristic algorithm reduces the number of resident locations and the total moving distance. We also show that our proposed algorithm achieves a higher charging efficiency compared with existing algorithms. PMID:28991200

  12. Simulation of land use change in the three gorges reservoir area based on CART-CA

    NASA Astrophysics Data System (ADS)

    Yuan, Min

    2018-05-01

    This study proposes a new method to simulate spatiotemporal complex multiple land uses by using classification and regression tree algorithm (CART) based CA model. In this model, we use classification and regression tree algorithm to calculate land class conversion probability, and combine neighborhood factor, random factor to extract cellular transformation rules. The overall Kappa coefficient is 0.8014 and the overall accuracy is 0.8821 in the land dynamic simulation results of the three gorges reservoir area from 2000 to 2010, and the simulation results are satisfactory.

  13. 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.

  14. Stress wave velocity patterns in the longitudinal-radial plane of trees for defect diagnosis

    Treesearch

    Guanghui Li; Xiang Weng; Xiaocheng Du; Xiping Wang; Hailin Feng

    2016-01-01

    Acoustic tomography for urban tree inspection typically uses stress wave data to reconstruct tomographic images for the trunk cross section using interpolation algorithm. This traditional technique does not take into account the stress wave velocity patterns along tree height. In this study, we proposed an analytical model for the wave velocity in the longitudinal–...

  15. Portable Language-Independent Adaptive Translation from OCR. Phase 1

    DTIC Science & Technology

    2009-04-01

    including brute-force k-Nearest Neighbors ( kNN ), fast approximate kNN using hashed k-d trees, classification and regression trees, and locality...achieved by refinements in ground-truthing protocols. Recent algorithmic improvements to our approximate kNN classifier using hashed k-D trees allows...recent years discriminative training has been shown to outperform phonetic HMMs estimated using ML for speech recognition. Standard ML estimation

  16. A scale-based connected coherence tree algorithm for image segmentation.

    PubMed

    Ding, Jundi; Ma, Runing; Chen, Songcan

    2008-02-01

    This paper presents a connected coherence tree algorithm (CCTA) for image segmentation with no prior knowledge. It aims to find regions of semantic coherence based on the proposed epsilon-neighbor coherence segmentation criterion. More specifically, with an adaptive spatial scale and an appropriate intensity-difference scale, CCTA often achieves several sets of coherent neighboring pixels which maximize the probability of being a single image content (including kinds of complex backgrounds). In practice, each set of coherent neighboring pixels corresponds to a coherence class (CC). The fact that each CC just contains a single equivalence class (EC) ensures the separability of an arbitrary image theoretically. In addition, the resultant CCs are represented by tree-based data structures, named connected coherence tree (CCT)s. In this sense, CCTA is a graph-based image analysis algorithm, which expresses three advantages: 1) its fundamental idea, epsilon-neighbor coherence segmentation criterion, is easy to interpret and comprehend; 2) it is efficient due to a linear computational complexity in the number of image pixels; 3) both subjective comparisons and objective evaluation have shown that it is effective for the tasks of semantic object segmentation and figure-ground separation in a wide variety of images. Those images either contain tiny, long and thin objects or are severely degraded by noise, uneven lighting, occlusion, poor illumination, and shadow.

  17. MODIS Snow Cover Mapping Decision Tree Technique: Snow and Cloud Discrimination

    NASA Technical Reports Server (NTRS)

    Riggs, George A.; Hall, Dorothy K.

    2010-01-01

    Accurate mapping of snow cover continues to challenge cryospheric scientists and modelers. The Moderate-Resolution Imaging Spectroradiometer (MODIS) snow data products have been used since 2000 by many investigators to map and monitor snow cover extent for various applications. Users have reported on the utility of the products and also on problems encountered. Three problems or hindrances in the use of the MODIS snow data products that have been reported in the literature are: cloud obscuration, snow/cloud confusion, and snow omission errors in thin or sparse snow cover conditions. Implementation of the MODIS snow algorithm in a decision tree technique using surface reflectance input to mitigate those problems is being investigated. The objective of this work is to use a decision tree structure for the snow algorithm. This should alleviate snow/cloud confusion and omission errors and provide a snow map with classes that convey information on how snow was detected, e.g. snow under clear sky, snow tinder cloud, to enable users' flexibility in interpreting and deriving a snow map. Results of a snow cover decision tree algorithm are compared to the standard MODIS snow map and found to exhibit improved ability to alleviate snow/cloud confusion in some situations allowing up to about 5% increase in mapped snow cover extent, thus accuracy, in some scenes.

  18. The Optimization of Automatically Generated Compilers.

    DTIC Science & Technology

    1987-01-01

    than their procedural counterparts, and are also easier to analyze for storage optimizations; (2) AGs can be algorithmically checked to be non-circular...Providing algorithms to move the storage for many attributes from the For structure tree into global stacks and variables. -Dd(2) Creating AEs which build and...54 3.5.2. Partitioning algorithm

  19. TREAT (TREe-based Association Test)

    Cancer.gov

    TREAT is an R package for detecting complex joint effects in case-control studies. The test statistic is derived from a tree-structure model by recursive partitioning the data. Ultra-fast algorithm is designed to evaluate the significance of association between candidate gene and disease outcome

  20. a Gross Error Elimination Method for Point Cloud Data Based on Kd-Tree

    NASA Astrophysics Data System (ADS)

    Kang, Q.; Huang, G.; Yang, S.

    2018-04-01

    Point cloud data has been one type of widely used data sources in the field of remote sensing. Key steps of point cloud data's pro-processing focus on gross error elimination and quality control. Owing to the volume feature of point could data, existed gross error elimination methods need spend massive memory both in space and time. This paper employed a new method which based on Kd-tree algorithm to construct, k-nearest neighbor algorithm to search, settled appropriate threshold to determine with result turns out a judgement that whether target point is or not an outlier. Experimental results show that, our proposed algorithm will help to delete gross error in point cloud data and facilitate to decrease memory consumption, improve efficiency.

  1. An application of locally linear model tree algorithm with combination of feature selection in credit scoring

    NASA Astrophysics Data System (ADS)

    Siami, Mohammad; Gholamian, Mohammad Reza; Basiri, Javad

    2014-10-01

    Nowadays, credit scoring is one of the most important topics in the banking sector. Credit scoring models have been widely used to facilitate the process of credit assessing. In this paper, an application of the locally linear model tree algorithm (LOLIMOT) was experimented to evaluate the superiority of its performance to predict the customer's credit status. The algorithm is improved with an aim of adjustment by credit scoring domain by means of data fusion and feature selection techniques. Two real world credit data sets - Australian and German - from UCI machine learning database were selected to demonstrate the performance of our new classifier. The analytical results indicate that the improved LOLIMOT significantly increase the prediction accuracy.

  2. Detecting non-orthology in the COGs database and other approaches grouping orthologs using genome-specific best hits.

    PubMed

    Dessimoz, Christophe; Boeckmann, Brigitte; Roth, Alexander C J; Gonnet, Gaston H

    2006-01-01

    Correct orthology assignment is a critical prerequisite of numerous comparative genomics procedures, such as function prediction, construction of phylogenetic species trees and genome rearrangement analysis. We present an algorithm for the detection of non-orthologs that arise by mistake in current orthology classification methods based on genome-specific best hits, such as the COGs database. The algorithm works with pairwise distance estimates, rather than computationally expensive and error-prone tree-building methods. The accuracy of the algorithm is evaluated through verification of the distribution of predicted cases, case-by-case phylogenetic analysis and comparisons with predictions from other projects using independent methods. Our results show that a very significant fraction of the COG groups include non-orthologs: using conservative parameters, the algorithm detects non-orthology in a third of all COG groups. Consequently, sequence analysis sensitive to correct orthology assignments will greatly benefit from these findings.

  3. Tree tensor network approach to simulating Shor's algorithm

    NASA Astrophysics Data System (ADS)

    Dumitrescu, Eugene

    2017-12-01

    Constructively simulating quantum systems furthers our understanding of qualitative and quantitative features which may be analytically intractable. In this paper, we directly simulate and explore the entanglement structure present in the paradigmatic example for exponential quantum speedups: Shor's algorithm. To perform our simulation, we construct a dynamic tree tensor network which manifestly captures two salient circuit features for modular exponentiation. These are the natural two-register bipartition and the invariance of entanglement with respect to permutations of the top-register qubits. Our construction help identify the entanglement entropy properties, which we summarize by a scaling relation. Further, the tree network is efficiently projected onto a matrix product state from which we efficiently execute the quantum Fourier transform. Future simulation of quantum information states with tensor networks exploiting circuit symmetries is discussed.

  4. Bioinformatics in proteomics: application, terminology, and pitfalls.

    PubMed

    Wiemer, Jan C; Prokudin, Alexander

    2004-01-01

    Bioinformatics applies data mining, i.e., modern computer-based statistics, to biomedical data. It leverages on machine learning approaches, such as artificial neural networks, decision trees and clustering algorithms, and is ideally suited for handling huge data amounts. In this article, we review the analysis of mass spectrometry data in proteomics, starting with common pre-processing steps and using single decision trees and decision tree ensembles for classification. Special emphasis is put on the pitfall of overfitting, i.e., of generating too complex single decision trees. Finally, we discuss the pros and cons of the two different decision tree usages.

  5. Phylogenetic trees and Euclidean embeddings.

    PubMed

    Layer, Mark; Rhodes, John A

    2017-01-01

    It was recently observed by de Vienne et al. (Syst Biol 60(6):826-832, 2011) that a simple square root transformation of distances between taxa on a phylogenetic tree allowed for an embedding of the taxa into Euclidean space. While the justification for this was based on a diffusion model of continuous character evolution along the tree, here we give a direct and elementary explanation for it that provides substantial additional insight. We use this embedding to reinterpret the differences between the NJ and BIONJ tree building algorithms, providing one illustration of how this embedding reflects tree structures in data.

  6. Aesthetic Discourses in Early Childhood Settings: Dewey, Steiner, and Vygotsky

    ERIC Educational Resources Information Center

    Lim, Booyeun

    2004-01-01

    Early childhood, when young children are already capable of undergoing aesthetic experience, must be the starting point for aesthetic education. Despite increasing attention to the significant values of the arts in early childhood classrooms, no theoretical framework to support aesthetic education has been established. This article introduces the…

  7. Alternative Education for the 21st Century: Philosophies, Approaches, Visions

    ERIC Educational Resources Information Center

    Woods, Philip A., Ed.; Woods, Glenys J., Ed.

    2008-01-01

    This is a unique collection of leading examples of education grounded in alternative philosophies and cultures--from initiatives to create more democratic schools, through Quaker, Buddhist, Islamic, Montessori and Steiner/Waldorf schools, to Maori and First Nations education in Canada and Palestinian Jewish schools in Israel. Aimed at educational…

  8. Democracy and Spiritual Awareness: Interconnections and Implications for Educational Leadership

    ERIC Educational Resources Information Center

    Woods, Glenys J.; Woods, Philip A.

    2008-01-01

    This article sets out theorisations of developmental democracy and spiritual awareness formulated in previous work by the authors. These are used to explore collegial leadership in a case study Steiner school, with the aim of illuminating and illustrating the transformative demands of developmental democracy and its interconnection with spiritual…

  9. The Future of Literacy.

    ERIC Educational Resources Information Center

    Disch, Robert, Ed.

    A variety of contributors explore the implications and the historical background of the future of literacy. We have inherited a belief that a vital literary tradition can uphold humane values, but events of twentieth century history have completely undermined faith in literacy as a stronghold of humanism. George Steiner suggests that literature is…

  10. Towards a Pedagogy of Imagination: A Phenomenological Case Study of Holistic Education

    ERIC Educational Resources Information Center

    Nielsen, Thomas William

    2006-01-01

    This article offers a synthesis of my recently completed doctorate study of Rudolf Steiner's notion of imaginative teaching. Seven original imaginative teaching methods (drama, exploration, storytelling, routine, arts, discussion and empathy) are introduced via phenomenological moments, followed by analysis and discussion. The article concludes…

  11. Expression and Activation of STAT Transcription Factors in Breast Cancer

    DTIC Science & Technology

    1998-05-08

    clinicians. J~, 273: 577-585, 1995. 183 Hundertmark 5, Buhler H, Rudolf M, Weitzel HK, Ragosch V: Inhibition of 11 beta-hydroxysteroid dehydrogenase...activated protein kinase through a Jakl-dependent pathway. Mol. Cell. Bioi., 17:3833-40, 1997. Stewart JF, Rubens RO, King RJ, Minton MJ, Steiner R

  12. International Survey of the Status of Waldorf Schools.

    ERIC Educational Resources Information Center

    Ogletree, Earl J.

    This international survey study was the first to examine the Waldorf School movement worldwide and focused on the teaching practices, curricula, educational outcomes, and positive program features of Waldorf schools, as well as problems encountered by Waldorf staff. The role of Rudolf Steiner's philosophy, anthroposophy, and its esoteric aspects…

  13. "The City": The Rhetoric of Rhythm.

    ERIC Educational Resources Information Center

    Medhurst, Martin J.; Benson, Thomas W.

    1981-01-01

    Case study of Ralph Steiner and Willard Van Dyke's classic documentary, "The City," a work of cinematic art and a record of the problems confronting urban planners. Discusses how the film builds a rhythmic pattern through dramatic structure, image content and composition, editing, music, and narration to enhance its rhetorical appeal. (JMF)

  14. On the Suitability of Suffix Arrays for Lempel-Ziv Data Compression

    NASA Astrophysics Data System (ADS)

    Ferreira, Artur J.; Oliveira, Arlindo L.; Figueiredo, Mário A. T.

    Lossless compression algorithms of the Lempel-Ziv (LZ) family are widely used nowadays. Regarding time and memory requirements, LZ encoding is much more demanding than decoding. In order to speed up the encoding process, efficient data structures, like suffix trees, have been used. In this paper, we explore the use of suffix arrays to hold the dictionary of the LZ encoder, and propose an algorithm to search over it. We show that the resulting encoder attains roughly the same compression ratios as those based on suffix trees. However, the amount of memory required by the suffix array is fixed, and much lower than the variable amount of memory used by encoders based on suffix trees (which depends on the text to encode). We conclude that suffix arrays, when compared to suffix trees in terms of the trade-off among time, memory, and compression ratio, may be preferable in scenarios (e.g., embedded systems) where memory is at a premium and high speed is not critical.

  15. K-Means Algorithm Performance Analysis With Determining The Value Of Starting Centroid With Random And KD-Tree Method

    NASA Astrophysics Data System (ADS)

    Sirait, Kamson; Tulus; Budhiarti Nababan, Erna

    2017-12-01

    Clustering methods that have high accuracy and time efficiency are necessary for the filtering process. One method that has been known and applied in clustering is K-Means Clustering. In its application, the determination of the begining value of the cluster center greatly affects the results of the K-Means algorithm. This research discusses the results of K-Means Clustering with starting centroid determination with a random and KD-Tree method. The initial determination of random centroid on the data set of 1000 student academic data to classify the potentially dropout has a sse value of 952972 for the quality variable and 232.48 for the GPA, whereas the initial centroid determination by KD-Tree has a sse value of 504302 for the quality variable and 214,37 for the GPA variable. The smaller sse values indicate that the result of K-Means Clustering with initial KD-Tree centroid selection have better accuracy than K-Means Clustering method with random initial centorid selection.

  16. Scalable Regression Tree Learning on Hadoop using OpenPlanet

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

    Yin, Wei; Simmhan, Yogesh; Prasanna, Viktor

    As scientific and engineering domains attempt to effectively analyze the deluge of data arriving from sensors and instruments, machine learning is becoming a key data mining tool to build prediction models. Regression tree is a popular learning model that combines decision trees and linear regression to forecast numerical target variables based on a set of input features. Map Reduce is well suited for addressing such data intensive learning applications, and a proprietary regression tree algorithm, PLANET, using MapReduce has been proposed earlier. In this paper, we describe an open source implement of this algorithm, OpenPlanet, on the Hadoop framework usingmore » a hybrid approach. Further, we evaluate the performance of OpenPlanet using realworld datasets from the Smart Power Grid domain to perform energy use forecasting, and propose tuning strategies of Hadoop parameters to improve the performance of the default configuration by 75% for a training dataset of 17 million tuples on a 64-core Hadoop cluster on FutureGrid.« less

  17. Phylogenomic analyses data of the avian phylogenomics project.

    PubMed

    Jarvis, Erich D; Mirarab, Siavash; Aberer, Andre J; Li, Bo; Houde, Peter; Li, Cai; Ho, Simon Y W; Faircloth, Brant C; Nabholz, Benoit; Howard, Jason T; Suh, Alexander; Weber, Claudia C; da Fonseca, Rute R; Alfaro-Núñez, Alonzo; Narula, Nitish; Liu, Liang; Burt, Dave; Ellegren, Hans; Edwards, Scott V; Stamatakis, Alexandros; Mindell, David P; Cracraft, Joel; Braun, Edward L; Warnow, Tandy; Jun, Wang; Gilbert, M Thomas Pius; Zhang, Guojie

    2015-01-01

    Determining the evolutionary relationships among the major lineages of extant birds has been one of the biggest challenges in systematic biology. To address this challenge, we assembled or collected the genomes of 48 avian species spanning most orders of birds, including all Neognathae and two of the five Palaeognathae orders. We used these genomes to construct a genome-scale avian phylogenetic tree and perform comparative genomic analyses. Here we present the datasets associated with the phylogenomic analyses, which include sequence alignment files consisting of nucleotides, amino acids, indels, and transposable elements, as well as tree files containing gene trees and species trees. Inferring an accurate phylogeny required generating: 1) A well annotated data set across species based on genome synteny; 2) Alignments with unaligned or incorrectly overaligned sequences filtered out; and 3) Diverse data sets, including genes and their inferred trees, indels, and transposable elements. Our total evidence nucleotide tree (TENT) data set (consisting of exons, introns, and UCEs) gave what we consider our most reliable species tree when using the concatenation-based ExaML algorithm or when using statistical binning with the coalescence-based MP-EST algorithm (which we refer to as MP-EST*). Other data sets, such as the coding sequence of some exons, revealed other properties of genome evolution, namely convergence. The Avian Phylogenomics Project is the largest vertebrate phylogenomics project to date that we are aware of. The sequence, alignment, and tree data are expected to accelerate analyses in phylogenomics and other related areas.

  18. Evaluation of supervised machine-learning algorithms to distinguish between inflammatory bowel disease and alimentary lymphoma in cats.

    PubMed

    Awaysheh, Abdullah; Wilcke, Jeffrey; Elvinger, François; Rees, Loren; Fan, Weiguo; Zimmerman, Kurt L

    2016-11-01

    Inflammatory bowel disease (IBD) and alimentary lymphoma (ALA) are common gastrointestinal diseases in cats. The very similar clinical signs and histopathologic features of these diseases make the distinction between them diagnostically challenging. We tested the use of supervised machine-learning algorithms to differentiate between the 2 diseases using data generated from noninvasive diagnostic tests. Three prediction models were developed using 3 machine-learning algorithms: naive Bayes, decision trees, and artificial neural networks. The models were trained and tested on data from complete blood count (CBC) and serum chemistry (SC) results for the following 3 groups of client-owned cats: normal, inflammatory bowel disease (IBD), or alimentary lymphoma (ALA). Naive Bayes and artificial neural networks achieved higher classification accuracy (sensitivities of 70.8% and 69.2%, respectively) than the decision tree algorithm (63%, p < 0.0001). The areas under the receiver-operating characteristic curve for classifying cases into the 3 categories was 83% by naive Bayes, 79% by decision tree, and 82% by artificial neural networks. Prediction models using machine learning provided a method for distinguishing between ALA-IBD, ALA-normal, and IBD-normal. The naive Bayes and artificial neural networks classifiers used 10 and 4 of the CBC and SC variables, respectively, to outperform the C4.5 decision tree, which used 5 CBC and SC variables in classifying cats into the 3 classes. These models can provide another noninvasive diagnostic tool to assist clinicians with differentiating between IBD and ALA, and between diseased and nondiseased cats. © 2016 The Author(s).

  19. Semiautomated landscape feature extraction and modeling

    NASA Astrophysics Data System (ADS)

    Wasilewski, Anthony A.; Faust, Nickolas L.; Ribarsky, William

    2001-08-01

    We have developed a semi-automated procedure for generating correctly located 3D tree objects form overhead imagery. Cross-platform software partitions arbitrarily large, geocorrected and geolocated imagery into management sub- images. The user manually selected tree areas from one or more of these sub-images. Tree group blobs are then narrowed to lines using a special thinning algorithm which retains the topology of the blobs, and also stores the thickness of the parent blob. Maxima along these thinned tree grous are found, and used as individual tree locations within the tree group. Magnitudes of the local maxima are used to scale the radii of the tree objects. Grossly overlapping trees are culled based on a comparison of tree-tree distance to combined radii. Tree color is randomly selected based on the distribution of sample tree pixels, and height is estimated form tree radius. The final tree objects are then inserted into a terrain database which can be navigated by VGIS, a high-resolution global terrain visualization system developed at Georgia Tech.

  20. Scalable Nearest Neighbor Algorithms for High Dimensional Data.

    PubMed

    Muja, Marius; Lowe, David G

    2014-11-01

    For many computer vision and machine learning problems, large training sets are key for good performance. However, the most computationally expensive part of many computer vision and machine learning algorithms consists of finding nearest neighbor matches to high dimensional vectors that represent the training data. We propose new algorithms for approximate nearest neighbor matching and evaluate and compare them with previous algorithms. For matching high dimensional features, we find two algorithms to be the most efficient: the randomized k-d forest and a new algorithm proposed in this paper, the priority search k-means tree. We also propose a new algorithm for matching binary features by searching multiple hierarchical clustering trees and show it outperforms methods typically used in the literature. We show that the optimal nearest neighbor algorithm and its parameters depend on the data set characteristics and describe an automated configuration procedure for finding the best algorithm to search a particular data set. In order to scale to very large data sets that would otherwise not fit in the memory of a single machine, we propose a distributed nearest neighbor matching framework that can be used with any of the algorithms described in the paper. All this research has been released as an open source library called fast library for approximate nearest neighbors (FLANN), which has been incorporated into OpenCV and is now one of the most popular libraries for nearest neighbor matching.

  1. Not seeing the forest for the trees: size of the minimum spanning trees (MSTs) forest and branch significance in MST-based phylogenetic analysis.

    PubMed

    Teixeira, Andreia Sofia; Monteiro, Pedro T; Carriço, João A; Ramirez, Mário; Francisco, Alexandre P

    2015-01-01

    Trees, including minimum spanning trees (MSTs), are commonly used in phylogenetic studies. But, for the research community, it may be unclear that the presented tree is just a hypothesis, chosen from among many possible alternatives. In this scenario, it is important to quantify our confidence in both the trees and the branches/edges included in such trees. In this paper, we address this problem for MSTs by introducing a new edge betweenness metric for undirected and weighted graphs. This spanning edge betweenness metric is defined as the fraction of equivalent MSTs where a given edge is present. The metric provides a per edge statistic that is similar to that of the bootstrap approach frequently used in phylogenetics to support the grouping of taxa. We provide methods for the exact computation of this metric based on the well known Kirchhoff's matrix tree theorem. Moreover, we implement and make available a module for the PHYLOViZ software and evaluate the proposed metric concerning both effectiveness and computational performance. Analysis of trees generated using multilocus sequence typing data (MLST) and the goeBURST algorithm revealed that the space of possible MSTs in real data sets is extremely large. Selection of the edge to be represented using bootstrap could lead to unreliable results since alternative edges are present in the same fraction of equivalent MSTs. The choice of the MST to be presented, results from criteria implemented in the algorithm that must be based in biologically plausible models.

  2. An implementation of a tree code on a SIMD, parallel computer

    NASA Technical Reports Server (NTRS)

    Olson, Kevin M.; Dorband, John E.

    1994-01-01

    We describe a fast tree algorithm for gravitational N-body simulation on SIMD parallel computers. The tree construction uses fast, parallel sorts. The sorted lists are recursively divided along their x, y and z coordinates. This data structure is a completely balanced tree (i.e., each particle is paired with exactly one other particle) and maintains good spatial locality. An implementation of this tree-building algorithm on a 16k processor Maspar MP-1 performs well and constitutes only a small fraction (approximately 15%) of the entire cycle of finding the accelerations. Each node in the tree is treated as a monopole. The tree search and the summation of accelerations also perform well. During the tree search, node data that is needed from another processor is simply fetched. Roughly 55% of the tree search time is spent in communications between processors. We apply the code to two problems of astrophysical interest. The first is a simulation of the close passage of two gravitationally, interacting, disk galaxies using 65,636 particles. We also simulate the formation of structure in an expanding, model universe using 1,048,576 particles. Our code attains speeds comparable to one head of a Cray Y-MP, so single instruction, multiple data (SIMD) type computers can be used for these simulations. The cost/performance ratio for SIMD machines like the Maspar MP-1 make them an extremely attractive alternative to either vector processors or large multiple instruction, multiple data (MIMD) type parallel computers. With further optimizations (e.g., more careful load balancing), speeds in excess of today's vector processing computers should be possible.

  3. A voxel-based technique to estimate the volume of trees from terrestrial laser scanner data

    NASA Astrophysics Data System (ADS)

    Bienert, A.; Hess, C.; Maas, H.-G.; von Oheimb, G.

    2014-06-01

    The precise determination of the volume of standing trees is very important for ecological and economical considerations in forestry. If terrestrial laser scanner data are available, a simple approach for volume determination is given by allocating points into a voxel structure and subsequently counting the filled voxels. Generally, this method will overestimate the volume. The paper presents an improved algorithm to estimate the wood volume of trees using a voxel-based method which will correct for the overestimation. After voxel space transformation, each voxel which contains points is reduced to the volume of its surrounding bounding box. In a next step, occluded (inner stem) voxels are identified by a neighbourhood analysis sweeping in the X and Y direction of each filled voxel. Finally, the wood volume of the tree is composed by the sum of the bounding box volumes of the outer voxels and the volume of all occluded inner voxels. Scan data sets from several young Norway maple trees (Acer platanoides) were used to analyse the algorithm. Therefore, the scanned trees as well as their representing point clouds were separated in different components (stem, branches) to make a meaningful comparison. Two reference measurements were performed for validation: A direct wood volume measurement by placing the tree components into a water tank, and a frustum calculation of small trunk segments by measuring the radii along the trunk. Overall, the results show slightly underestimated volumes (-0.3% for a probe of 13 trees) with a RMSE of 11.6% for the individual tree volume calculated with the new approach.

  4. The estimation of tree posterior probabilities using conditional clade probability distributions.

    PubMed

    Larget, Bret

    2013-07-01

    In this article I introduce the idea of conditional independence of separated subtrees as a principle by which to estimate the posterior probability of trees using conditional clade probability distributions rather than simple sample relative frequencies. I describe an algorithm for these calculations and software which implements these ideas. I show that these alternative calculations are very similar to simple sample relative frequencies for high probability trees but are substantially more accurate for relatively low probability trees. The method allows the posterior probability of unsampled trees to be calculated when these trees contain only clades that are in other sampled trees. Furthermore, the method can be used to estimate the total probability of the set of sampled trees which provides a measure of the thoroughness of a posterior sample.

  5. Estimating babassu palm density using automatic palm tree detection with very high spatial resolution satellite images.

    PubMed

    Dos Santos, Alessio Moreira; Mitja, Danielle; Delaître, Eric; Demagistri, Laurent; de Souza Miranda, Izildinha; Libourel, Thérèse; Petit, Michel

    2017-05-15

    High spatial resolution images as well as image processing and object detection algorithms are recent technologies that aid the study of biodiversity and commercial plantations of forest species. This paper seeks to contribute knowledge regarding the use of these technologies by studying randomly dispersed native palm tree. Here, we analyze the automatic detection of large circular crown (LCC) palm tree using a high spatial resolution panchromatic GeoEye image (0.50 m) taken on the area of a community of small agricultural farms in the Brazilian Amazon. We also propose auxiliary methods to estimate the density of the LCC palm tree Attalea speciosa (babassu) based on the detection results. We used the "Compt-palm" algorithm based on the detection of palm tree shadows in open areas via mathematical morphology techniques and the spatial information was validated using field methods (i.e. structural census and georeferencing). The algorithm recognized individuals in life stages 5 and 6, and the extraction percentage, branching factor and quality percentage factors were used to evaluate its performance. A principal components analysis showed that the structure of the studied species differs from other species. Approximately 96% of the babassu individuals in stage 6 were detected. These individuals had significantly smaller stipes than the undetected ones. In turn, 60% of the stage 5 babassu individuals were detected, showing significantly a different total height and a different number of leaves from the undetected ones. Our calculations regarding resource availability indicate that 6870 ha contained 25,015 adult babassu palm tree, with an annual potential productivity of 27.4 t of almond oil. The detection of LCC palm tree and the implementation of auxiliary field methods to estimate babassu density is an important first step to monitor this industry resource that is extremely important to the Brazilian economy and thousands of families over a large scale. Copyright © 2017 Elsevier Ltd. All rights reserved.

  6. VC-dimension of univariate decision trees.

    PubMed

    Yildiz, Olcay Taner

    2015-02-01

    In this paper, we give and prove the lower bounds of the Vapnik-Chervonenkis (VC)-dimension of the univariate decision tree hypothesis class. The VC-dimension of the univariate decision tree depends on the VC-dimension values of its subtrees and the number of inputs. Via a search algorithm that calculates the VC-dimension of univariate decision trees exhaustively, we show that our VC-dimension bounds are tight for simple trees. To verify that the VC-dimension bounds are useful, we also use them to get VC-generalization bounds for complexity control using structural risk minimization in decision trees, i.e., pruning. Our simulation results show that structural risk minimization pruning using the VC-dimension bounds finds trees that are more accurate as those pruned using cross validation.

  7. PCA based feature reduction to improve the accuracy of decision tree c4.5 classification

    NASA Astrophysics Data System (ADS)

    Nasution, M. Z. F.; Sitompul, O. S.; Ramli, M.

    2018-03-01

    Splitting attribute is a major process in Decision Tree C4.5 classification. However, this process does not give a significant impact on the establishment of the decision tree in terms of removing irrelevant features. It is a major problem in decision tree classification process called over-fitting resulting from noisy data and irrelevant features. In turns, over-fitting creates misclassification and data imbalance. Many algorithms have been proposed to overcome misclassification and overfitting on classifications Decision Tree C4.5. Feature reduction is one of important issues in classification model which is intended to remove irrelevant data in order to improve accuracy. The feature reduction framework is used to simplify high dimensional data to low dimensional data with non-correlated attributes. In this research, we proposed a framework for selecting relevant and non-correlated feature subsets. We consider principal component analysis (PCA) for feature reduction to perform non-correlated feature selection and Decision Tree C4.5 algorithm for the classification. From the experiments conducted using available data sets from UCI Cervical cancer data set repository with 858 instances and 36 attributes, we evaluated the performance of our framework based on accuracy, specificity and precision. Experimental results show that our proposed framework is robust to enhance classification accuracy with 90.70% accuracy rates.

  8. Energy aware path planning in complex four dimensional environments

    NASA Astrophysics Data System (ADS)

    Chakrabarty, Anjan

    This dissertation addresses the problem of energy-aware path planning for small autonomous vehicles. While small autonomous vehicles can perform missions that are too risky (or infeasible) for larger vehicles, the missions are limited by the amount of energy that can be carried on board the vehicle. Path planning techniques that either minimize energy consumption or exploit energy available in the environment can thus increase range and endurance. Path planning is complicated by significant spatial (and potentially temporal) variations in the environment. While the main focus is on autonomous aircraft, this research also addresses autonomous ground vehicles. Range and endurance of small unmanned aerial vehicles (UAVs) can be greatly improved by utilizing energy from the atmosphere. Wind can be exploited to minimize energy consumption of a small UAV. But wind, like any other atmospheric component , is a space and time varying phenomenon. To effectively use wind for long range missions, both exploration and exploitation of wind is critical. This research presents a kinematics based tree algorithm which efficiently handles the four dimensional (three spatial and time) path planning problem. The Kinematic Tree algorithm provides a sequence of waypoints, airspeeds, heading and bank angle commands for each segment of the path. The planner is shown to be resolution complete and computationally efficient. Global optimality of the cost function cannot be claimed, as energy is gained from the atmosphere, making the cost function inadmissible. However the Kinematic Tree is shown to be optimal up to resolution if the cost function is admissible. Simulation results show the efficacy of this planning method for a glider in complex real wind data. Simulation results verify that the planner is able to extract energy from the atmosphere enabling long range missions. The Kinematic Tree planning framework, developed to minimize energy consumption of UAVs, is applied for path planning in ground robots. In traditional path planning problem the focus is on obstacle avoidance and navigation. The optimal Kinematic Tree algorithm named Kinematic Tree* is shown to find optimal paths to reach the destination while avoiding obstacles. A more challenging path planning scenario arises for planning in complex terrain. This research shows how the Kinematic Tree* algorithm can be extended to find minimum energy paths for a ground vehicle in difficult mountainous terrain.

  9. Efficient Construction of Mesostate Networks from Molecular Dynamics Trajectories.

    PubMed

    Vitalis, Andreas; Caflisch, Amedeo

    2012-03-13

    The coarse-graining of data from molecular simulations yields conformational space networks that may be used for predicting the system's long time scale behavior, to discover structural pathways connecting free energy basins in the system, or simply to represent accessible phase space regions of interest and their connectivities in a two-dimensional plot. In this contribution, we present a tree-based algorithm to partition conformations of biomolecules into sets of similar microstates, i.e., to coarse-grain trajectory data into mesostates. On account of utilizing an architecture similar to that of established tree-based algorithms, the proposed scheme operates in near-linear time with data set size. We derive expressions needed for the fast evaluation of mesostate properties and distances when employing typical choices for measures of similarity between microstates. Using both a pedagogically useful and a real-word application, the algorithm is shown to be robust with respect to tree height, which in addition to mesostate threshold size is the main adjustable parameter. It is demonstrated that the derived mesostate networks can preserve information regarding the free energy basins and barriers by which the system is characterized.

  10. A splay tree-based approach for efficient resource location in P2P networks.

    PubMed

    Zhou, Wei; Tan, Zilong; Yao, Shaowen; Wang, Shipu

    2014-01-01

    Resource location in structured P2P system has a critical influence on the system performance. Existing analytical studies of Chord protocol have shown some potential improvements in performance. In this paper a splay tree-based new Chord structure called SChord is proposed to improve the efficiency of locating resources. We consider a novel implementation of the Chord finger table (routing table) based on the splay tree. This approach extends the Chord finger table with additional routing entries. Adaptive routing algorithm is proposed for implementation, and it can be shown that hop count is significantly minimized without introducing any other protocol overheads. We analyze the hop count of the adaptive routing algorithm, as compared to Chord variants, and demonstrate sharp upper and lower bounds for both worst-case and average case settings. In addition, we theoretically analyze the hop reducing in SChord and derive the fact that SChord can significantly reduce the routing hops as compared to Chord. Several simulations are presented to evaluate the performance of the algorithm and support our analytical findings. The simulation results show the efficiency of SChord.

  11. Searching Information Sources in Networks

    DTIC Science & Technology

    2017-06-14

    SECURITY CLASSIFICATION OF: During the course of this project, we made significant progresses in multiple directions of the information detection...result on information source detection on non-tree networks; (2) The development of information source localization algorithms to detect multiple... information sources. The algorithms have provable performance guarantees and outperform existing algorithms in 1. REPORT DATE (DD-MM-YYYY) 4. TITLE AND

  12. Evaluating the ecosystem water use efficiency and gross primary productivity in boreal forest based on tree ring data

    NASA Astrophysics Data System (ADS)

    Liu, S.; Zhuang, Q.

    2016-12-01

    Climatic change affects the plant physiological and biogeochemistry processes, and therefore on the ecosystem water use efficiency (WUE). Therefore, a comprehensive understanding of WUE would help us understand the adaptability of ecosystem to variable climate conditions. Tree ring data have great potential in addressing the forest response to climatic changes compared with mechanistic model simulations, eddy flux measurement and manipulative experiments. Here, we collected the tree ring isotopic carbon data in 12 boreal forest sites to develop a multiple linear regression model, and the model was extrapolated to the whole boreal region to obtain the WUE spatial and temporal variation from 1948 to 2010. Two algorithms were also used to estimate the inter-annual gross primary productivity (GPP) based on our derived WUE. Our results demonstrated that most of boreal regions showed significant increasing WUE trend during the period except parts of Alaska. The spatial averaged annual mean WUE was predicted to increase by 13%, from 2.3±0.4 g C kg-1 H2O at 1948 to 2.6±0.7 g C kg-1 H2O at 2012, which was much higher than other land surface models. Our predicted GPP by the WUE definition algorithm was comparable with site observation, while for the revised light use efficiency algorithm, GPP estimation was higher than site observation as well as than land surface models. In addition, the increasing GPP trends by two algorithms were similar with land surface model simulations. This is the first study to evaluate regional WUE and GPP in forest ecosystem based on tree ring data and future work should consider other variables (elevation, nitrogen deposition) that influence tree ring isotopic signals and the dual-isotope approach may help improve predicting the inter-annual WUE variation.

  13. The Dynamics of Germinal Centre Selection as Measured by Graph-Theoretical Analysis of Mutational Lineage Trees

    PubMed Central

    Dunn-Walters, Deborah K.; Belelovsky, Alex; Edelman, Hanna; Banerjee, Monica; Mehr, Ramit

    2002-01-01

    We have developed a rigorous graph-theoretical algorithm for quantifying the shape properties of mutational lineage trees. We show that information about the dynamics of hypermutation and antigen-driven clonal selection during the humoral immune response is contained in the shape of mutational lineage trees deduced from the responding clones. Age and tissue related differences in the selection process can be studied using this method. Thus, tree shape analysis can be used as a means of elucidating humoral immune response dynamics in various situations. PMID:15144020

  14. A Mixtures-of-Trees Framework for Multi-Label Classification

    PubMed Central

    Hong, Charmgil; Batal, Iyad; Hauskrecht, Milos

    2015-01-01

    We propose a new probabilistic approach for multi-label classification that aims to represent the class posterior distribution P(Y|X). Our approach uses a mixture of tree-structured Bayesian networks, which can leverage the computational advantages of conditional tree-structured models and the abilities of mixtures to compensate for tree-structured restrictions. We develop algorithms for learning the model from data and for performing multi-label predictions using the learned model. Experiments on multiple datasets demonstrate that our approach outperforms several state-of-the-art multi-label classification methods. PMID:25927011

  15. Binary Classification using Decision Tree based Genetic Programming and Its Application to Analysis of Bio-mass Data

    NASA Astrophysics Data System (ADS)

    To, Cuong; Pham, Tuan D.

    2010-01-01

    In machine learning, pattern recognition may be the most popular task. "Similar" patterns identification is also very important in biology because first, it is useful for prediction of patterns associated with disease, for example cancer tissue (normal or tumor); second, similarity or dissimilarity of the kinetic patterns is used to identify coordinately controlled genes or proteins involved in the same regulatory process. Third, similar genes (proteins) share similar functions. In this paper, we present an algorithm which uses genetic programming to create decision tree for binary classification problem. The application of the algorithm was implemented on five real biological databases. Base on the results of comparisons with well-known methods, we see that the algorithm is outstanding in most of cases.

  16. Genetic Algorithms and Classification Trees in Feature Discovery: Diabetes and the NHANES database

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

    Heredia-Langner, Alejandro; Jarman, Kristin H.; Amidan, Brett G.

    2013-09-01

    This paper presents a feature selection methodology that can be applied to datasets containing a mixture of continuous and categorical variables. Using a Genetic Algorithm (GA), this method explores a dataset and selects a small set of features relevant for the prediction of a binary (1/0) response. Binary classification trees and an objective function based on conditional probabilities are used to measure the fitness of a given subset of features. The method is applied to health data in order to find factors useful for the prediction of diabetes. Results show that our algorithm is capable of narrowing down the setmore » of predictors to around 8 factors that can be validated using reputable medical and public health resources.« less

  17. Content addressable memory project

    NASA Technical Reports Server (NTRS)

    Hall, J. Storrs; Levy, Saul; Smith, Donald E.; Miyake, Keith M.

    1992-01-01

    A parameterized version of the tree processor was designed and tested (by simulation). The leaf processor design is 90 percent complete. We expect to complete and test a combination of tree and leaf cell designs in the next period. Work is proceeding on algorithms for the computer aided manufacturing (CAM), and once the design is complete we will begin simulating algorithms for large problems. The following topics are covered: (1) the practical implementation of content addressable memory; (2) design of a LEAF cell for the Rutgers CAM architecture; (3) a circuit design tool user's manual; and (4) design and analysis of efficient hierarchical interconnection networks.

  18. Numerical taxonomy on data: Experimental results

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

    Cohen, J.; Farach, M.

    1997-12-01

    The numerical taxonomy problems associated with most of the optimization criteria described above are NP - hard [3, 5, 1, 4]. In, the first positive result for numerical taxonomy was presented. They showed that if e is the distance to the closest tree metric under the L{sub {infinity}} norm. i.e., e = min{sub T} [L{sub {infinity}} (T-D)], then it is possible to construct a tree T such that L{sub {infinity}} (T-D) {le} 3e, that is, they gave a 3-approximation algorithm for this problem. We will refer to this algorithm as the Single Pivot (SP) heuristic.

  19. Instruction-matrix-based genetic programming.

    PubMed

    Li, Gang; Wang, Jin Feng; Lee, Kin Hong; Leung, Kwong-Sak

    2008-08-01

    In genetic programming (GP), evolving tree nodes separately would reduce the huge solution space. However, tree nodes are highly interdependent with respect to their fitness. In this paper, we propose a new GP framework, namely, instruction-matrix (IM)-based GP (IMGP), to handle their interactions. IMGP maintains an IM to evolve tree nodes and subtrees separately. IMGP extracts program trees from an IM and updates the IM with the information of the extracted program trees. As the IM actually keeps most of the information of the schemata of GP and evolves the schemata directly, IMGP is effective and efficient. Our experimental results on benchmark problems have verified that IMGP is not only better than those of canonical GP in terms of the qualities of the solutions and the number of program evaluations, but they are also better than some of the related GP algorithms. IMGP can also be used to evolve programs for classification problems. The classifiers obtained have higher classification accuracies than four other GP classification algorithms on four benchmark classification problems. The testing errors are also comparable to or better than those obtained with well-known classifiers. Furthermore, an extended version, called condition matrix for rule learning, has been used successfully to handle multiclass classification problems.

  20. Quantifying Standing Dead Tree Volume and Structural Loss with Voxelized Terrestrial Lidar Data

    NASA Astrophysics Data System (ADS)

    Popescu, S. C.; Putman, E.

    2017-12-01

    Standing dead trees (SDTs) are an important forest component and impact a variety of ecosystem processes, yet the carbon pool dynamics of SDTs are poorly constrained in terrestrial carbon cycling models. The ability to model wood decay and carbon cycling in relation to detectable changes in tree structure and volume over time would greatly improve such models. The overall objective of this study was to provide automated aboveground volume estimates of SDTs and automated procedures to detect, quantify, and characterize structural losses over time with terrestrial lidar data. The specific objectives of this study were: 1) develop an automated SDT volume estimation algorithm providing accurate volume estimates for trees scanned in dense forests; 2) develop an automated change detection methodology to accurately detect and quantify SDT structural loss between subsequent terrestrial lidar observations; and 3) characterize the structural loss rates of pine and oak SDTs in southeastern Texas. A voxel-based volume estimation algorithm, "TreeVolX", was developed and incorporates several methods designed to robustly process point clouds of varying quality levels. The algorithm operates on horizontal voxel slices by segmenting the slice into distinct branch or stem sections then applying an adaptive contour interpolation and interior filling process to create solid reconstructed tree models (RTMs). TreeVolX estimated large and small branch volume with an RMSE of 7.3% and 13.8%, respectively. A voxel-based change detection methodology was developed to accurately detect and quantify structural losses and incorporated several methods to mitigate the challenges presented by shifting tree and branch positions as SDT decay progresses. The volume and structural loss of 29 SDTs, composed of Pinus taeda and Quercus stellata, were successfully estimated using multitemporal terrestrial lidar observations over elapsed times ranging from 71 - 753 days. Pine and oak structural loss rates were characterized by estimating the amount of volumetric loss occurring in 20 equal-interval height bins of each SDT. Results showed that large pine snags exhibited more rapid structural loss in comparison to medium-sized oak snags in this study.

  1. Multi-Parent Clustering Algorithms from Stochastic Grammar Data Models

    NASA Technical Reports Server (NTRS)

    Mjoisness, Eric; Castano, Rebecca; Gray, Alexander

    1999-01-01

    We introduce a statistical data model and an associated optimization-based clustering algorithm which allows data vectors to belong to zero, one or several "parent" clusters. For each data vector the algorithm makes a discrete decision among these alternatives. Thus, a recursive version of this algorithm would place data clusters in a Directed Acyclic Graph rather than a tree. We test the algorithm with synthetic data generated according to the statistical data model. We also illustrate the algorithm using real data from large-scale gene expression assays.

  2. Coherent multiscale image processing using dual-tree quaternion wavelets.

    PubMed

    Chan, Wai Lam; Choi, Hyeokho; Baraniuk, Richard G

    2008-07-01

    The dual-tree quaternion wavelet transform (QWT) is a new multiscale analysis tool for geometric image features. The QWT is a near shift-invariant tight frame representation whose coefficients sport a magnitude and three phases: two phases encode local image shifts while the third contains image texture information. The QWT is based on an alternative theory for the 2-D Hilbert transform and can be computed using a dual-tree filter bank with linear computational complexity. To demonstrate the properties of the QWT's coherent magnitude/phase representation, we develop an efficient and accurate procedure for estimating the local geometrical structure of an image. We also develop a new multiscale algorithm for estimating the disparity between a pair of images that is promising for image registration and flow estimation applications. The algorithm features multiscale phase unwrapping, linear complexity, and sub-pixel estimation accuracy.

  3. The use of decision trees and naïve Bayes algorithms and trace element patterns for controlling the authenticity of free-range-pastured hens' eggs.

    PubMed

    Barbosa, Rommel Melgaço; Nacano, Letícia Ramos; Freitas, Rodolfo; Batista, Bruno Lemos; Barbosa, Fernando

    2014-09-01

    This article aims to evaluate 2 machine learning algorithms, decision trees and naïve Bayes (NB), for egg classification (free-range eggs compared with battery eggs). The database used for the study consisted of 15 chemical elements (As, Ba, Cd, Co, Cs, Cu, Fe, Mg, Mn, Mo, Pb, Se, Sr, V, and Zn) determined in 52 eggs samples (20 free-range and 32 battery eggs) by inductively coupled plasma mass spectrometry. Our results demonstrated that decision trees and NB associated with the mineral contents of eggs provide a high level of accuracy (above 80% and 90%, respectively) for classification between free-range and battery eggs and can be used as an alternative method for adulteration evaluation. © 2014 Institute of Food Technologists®

  4. 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

  5. Evolutionary Algorithm Based Automated Reverse Engineering and Defect Discovery

    DTIC Science & Technology

    2007-09-21

    a previous application of a GP as a data mining function to evolve fuzzy decision trees symbolically [3-5], the terminal set consisted of fuzzy...of input and output information is required. In the case of fuzzy decision trees, the database represented a collection of scenarios about which the...fuzzy decision tree to be evolved would make decisions . The database also had entries created by experts representing decisions about the scenarios

  6. Interpretable Categorization of Heterogeneous Time Series Data

    NASA Technical Reports Server (NTRS)

    Lee, Ritchie; Kochenderfer, Mykel J.; Mengshoel, Ole J.; Silbermann, Joshua

    2017-01-01

    We analyze data from simulated aircraft encounters to validate and inform the development of a prototype aircraft collision avoidance system. The high-dimensional and heterogeneous time series dataset is analyzed to discover properties of near mid-air collisions (NMACs) and categorize the NMAC encounters. Domain experts use these properties to better organize and understand NMAC occurrences. Existing solutions either are not capable of handling high-dimensional and heterogeneous time series datasets or do not provide explanations that are interpretable by a domain expert. The latter is critical to the acceptance and deployment of safety-critical systems. To address this gap, we propose grammar-based decision trees along with a learning algorithm. Our approach extends decision trees with a grammar framework for classifying heterogeneous time series data. A context-free grammar is used to derive decision expressions that are interpretable, application-specific, and support heterogeneous data types. In addition to classification, we show how grammar-based decision trees can also be used for categorization, which is a combination of clustering and generating interpretable explanations for each cluster. We apply grammar-based decision trees to a simulated aircraft encounter dataset and evaluate the performance of four variants of our learning algorithm. The best algorithm is used to analyze and categorize near mid-air collisions in the aircraft encounter dataset. We describe each discovered category in detail and discuss its relevance to aircraft collision avoidance.

  7. Stacked Denoising Autoencoders Applied to Star/Galaxy Classification

    NASA Astrophysics Data System (ADS)

    Qin, Hao-ran; Lin, Ji-ming; Wang, Jun-yi

    2017-04-01

    In recent years, the deep learning algorithm, with the characteristics of strong adaptability, high accuracy, and structural complexity, has become more and more popular, but it has not yet been used in astronomy. In order to solve the problem that the star/galaxy classification accuracy is high for the bright source set, but low for the faint source set of the Sloan Digital Sky Survey (SDSS) data, we introduced the new deep learning algorithm, namely the SDA (stacked denoising autoencoder) neural network and the dropout fine-tuning technique, which can greatly improve the robustness and antinoise performance. We randomly selected respectively the bright source sets and faint source sets from the SDSS DR12 and DR7 data with spectroscopic measurements, and made preprocessing on them. Then, we randomly selected respectively the training sets and testing sets without replacement from the bright source sets and faint source sets. At last, using these training sets we made the training to obtain the SDA models of the bright sources and faint sources in the SDSS DR7 and DR12, respectively. We compared the test result of the SDA model on the DR12 testing set with the test results of the Library for Support Vector Machines (LibSVM), J48 decision tree, Logistic Model Tree (LMT), Support Vector Machine (SVM), Logistic Regression, and Decision Stump algorithm, and compared the test result of the SDA model on the DR7 testing set with the test results of six kinds of decision trees. The experiments show that the SDA has a better classification accuracy than other machine learning algorithms for the faint source sets of DR7 and DR12. Especially, when the completeness function is used as the evaluation index, compared with the decision tree algorithms, the correctness rate of SDA has improved about 15% for the faint source set of SDSS-DR7.

  8. The Estimation of Tree Posterior Probabilities Using Conditional Clade Probability Distributions

    PubMed Central

    Larget, Bret

    2013-01-01

    In this article I introduce the idea of conditional independence of separated subtrees as a principle by which to estimate the posterior probability of trees using conditional clade probability distributions rather than simple sample relative frequencies. I describe an algorithm for these calculations and software which implements these ideas. I show that these alternative calculations are very similar to simple sample relative frequencies for high probability trees but are substantially more accurate for relatively low probability trees. The method allows the posterior probability of unsampled trees to be calculated when these trees contain only clades that are in other sampled trees. Furthermore, the method can be used to estimate the total probability of the set of sampled trees which provides a measure of the thoroughness of a posterior sample. [Bayesian phylogenetics; conditional clade distributions; improved accuracy; posterior probabilities of trees.] PMID:23479066

  9. Tree Classification Software

    NASA Technical Reports Server (NTRS)

    Buntine, Wray

    1993-01-01

    This paper introduces the IND Tree Package to prospective users. IND does supervised learning using classification trees. This learning task is a basic tool used in the development of diagnosis, monitoring and expert systems. The IND Tree Package was developed as part of a NASA project to semi-automate the development of data analysis and modelling algorithms using artificial intelligence techniques. The IND Tree Package integrates features from CART and C4 with newer Bayesian and minimum encoding methods for growing classification trees and graphs. The IND Tree Package also provides an experimental control suite on top. The newer features give improved probability estimates often required in diagnostic and screening tasks. The package comes with a manual, Unix 'man' entries, and a guide to tree methods and research. The IND Tree Package is implemented in C under Unix and was beta-tested at university and commercial research laboratories in the United States.

  10. Expert-guided evolutionary algorithm for layout design of complex space stations

    NASA Astrophysics Data System (ADS)

    Qian, Zhiqin; Bi, Zhuming; Cao, Qun; Ju, Weiguo; Teng, Hongfei; Zheng, Yang; Zheng, Siyu

    2017-08-01

    The layout of a space station should be designed in such a way that different equipment and instruments are placed for the station as a whole to achieve the best overall performance. The station layout design is a typical nondeterministic polynomial problem. In particular, how to manage the design complexity to achieve an acceptable solution within a reasonable timeframe poses a great challenge. In this article, a new evolutionary algorithm has been proposed to meet such a challenge. It is called as the expert-guided evolutionary algorithm with a tree-like structure decomposition (EGEA-TSD). Two innovations in EGEA-TSD are (i) to deal with the design complexity, the entire design space is divided into subspaces with a tree-like structure; it reduces the computation and facilitates experts' involvement in the solving process. (ii) A human-intervention interface is developed to allow experts' involvement in avoiding local optimums and accelerating convergence. To validate the proposed algorithm, the layout design of one-space station is formulated as a multi-disciplinary design problem, the developed algorithm is programmed and executed, and the result is compared with those from other two algorithms; it has illustrated the superior performance of the proposed EGEA-TSD.

  11. The Big Disconnect: Your Student in Class vs. Your Student Online

    ERIC Educational Resources Information Center

    Steiner-Adair, Catherine

    2015-01-01

    Catherine Steiner-Adair, clinical psychologist, has consulted for more than 350 independent and public schools, parents, and students, on a wide range of topics related to strengthening children's social and emotional development, shaping school culture, and deepening parents' connections to their children. Four years ago, she was able to collect…

  12. Homer: A Collection of Critical Essays. Twentieth Century Views Series.

    ERIC Educational Resources Information Center

    Steiner, George, Ed.; Fagles, Robert, Ed.

    One of a series of works aimed at presenting contemporary critical opinion on major authors, this collection includes essays by George Steiner, Leo Tolstoy, Ezra Pound, Erich Auerbach, Edwin Muir, Cedric H. Whitman, Albert B. Lord, W. H. Auden, Ernst Bloch, Georg Lukacs, C. Day Lewis, Gabriel Germain, Franz Kafka, Rachel Bespaloff, Robert…

  13. Unbiased Causal Inference from an Observational Study: Results of a Within-Study Comparison

    ERIC Educational Resources Information Center

    Pohl, Steffi; Steiner, Peter M.; Eisermann, Jens; Soellner, Renate; Cook, Thomas D.

    2009-01-01

    Adjustment methods such as propensity scores and analysis of covariance are often used for estimating treatment effects in nonexperimental data. Shadish, Clark, and Steiner used a within-study comparison to test how well these adjustments work in practice. They randomly assigned participating students to a randomized or nonrandomized experiment.…

  14. Mimogonellus dreybrodti sp. n., a new cave-inhabiting Osoriinae from Laos (Coleoptera: Staphylinidae).

    PubMed

    Yin, Zi-Wei; Steiner, Helmut

    2017-10-17

    A new osoriine species, Mimogonellus dreybrodti Yin & Steiner, sp. n., collected from a cave in Houaphanh Province, Laos, is described and illustrated. This represents the third Mimogonellus species in Asia, and the first in the genus known to inhabit a cave environment.

  15. Creating Relational Spaces: Everyday Spirituality in Early Childhood Settings

    ERIC Educational Resources Information Center

    Bone, Jane

    2008-01-01

    This research addressed the question of how the spiritual experience of young children might be supported in early childhood educational settings. Qualitative case study research took place in three different contexts: a Montessori casa, a Rudolf Steiner kindergarten and a private preschool. Children aged 2 1/2-6 years, their parents and teachers…

  16. Politics of Externalization in Reflexive Times: Reinventing Japanese Education Reform Discourses through "Finnish PISA Success"

    ERIC Educational Resources Information Center

    Takayama, Keita

    2010-01-01

    Drawing on a critical theoretical paradigm and critically engaging with the externalization thesis that Gita Steiner-Khamsi and Jurgen Schriewer have developed, this article examines the politics of "Finnish education" in the ongoing Japanese education reform debate. More specifically, it examines the various discursive uses of…

  17. Student Adjustment to Higher Education: The Role of Alternative Educational Pathways in Coping with the Demands of Student Life

    ERIC Educational Resources Information Center

    Shankland, Rebecca; Genolini, Christophe; Franca, Lionel Riou; Guelfi, Julien-Daniel; Ionescu, Serban

    2010-01-01

    The present longitudinal study measured student adjustment to higher education, comparing 50 participants from alternative schools (Steiner, Montessori, New Schools) with 80 students from the traditional school system. We hypothesized that students from alternative schools adapt better, because of greater perceived social support, academic…

  18. Peer Inquiry: Discovering What You Know through Dialogue

    ERIC Educational Resources Information Center

    Wix, Linney; John-Steiner, Vera

    2008-01-01

    The article discusses a dialogical peer inquiry process as a practice of co-constructing knowledge in graduate coursework. The process, formerly structured as an exam, was developed by Dr. Vera John-Steiner more than 30 years ago and has been implemented in adapted forms by her students in their teaching. The dialogical peer inquiry process…

  19. THE INTERNATIONAL WALDORF SCHOOL MOVEMENT.

    ERIC Educational Resources Information Center

    VON BARAVALLE, HERMANN

    AN HISTORICAL REVIEW OF THE WALDORF SCHOOL PLAN TRACES THE MOVEMENT FROM ITS FOUNDING IN STUTTGART, GERMANY IN 1919, BY THE WALDORF ASTORIA COMPANY AND UNDER THE DIRECTION OF RUDOLF STEINER, TO ITS INTRODUCTION INTO SWITZERLAND, OTHER EUROPEAN COUNTRIES, THE AMERICAS, AUSTRALIA, NEW ZEALAND, AND SOUTH AFRICA, A TOTAL OF 175 SCHOOLS AS OF 1963. THE…

  20. Learning That Grows with the Learner: An Introduction to Waldorf Education.

    ERIC Educational Resources Information Center

    Barnes, Henry

    1991-01-01

    Waldorf education, rooted in the spiritual-scientific research of the Austrian scientist Rudolf Steiner, conceives man/woman as a three-fold being of spirit, soul, and body whose capacities unfold in three developmental stages: early childhood, middle childhood, and adolescence. Waldorf schools educate the whole human being--head, heart, and…

  1. Wind Shear Modeling for Aircraft Hazard Definition

    DTIC Science & Technology

    1977-03-01

    Fichtl, "Rough to Smooth Transition of an Equilibrium Neutral Constant Stress Layer," NASA TM X-3322, (1975). 5-36 Geiger, Rudolf , The Climate Near the...Roy Steiner , and K. G. Pratt. "Dynamic Response of Airplanes to Atmospheric Turbulence Including Flight Data on Input and Response," NASA TR R-199

  2. A Note on Time and Education.

    ERIC Educational Resources Information Center

    Leichter, Hope Jensen

    1980-01-01

    The temporal organization of the Rudolf Steiner School in New York City is examined in terms of daily or microtime, calendric time, and developmental time. The question of continuities over time, that is, the interweaving of past, present, and future, and the relation of these continuities to the transformations of education are also considered.…

  3. The Waldorf Curriculum as a Framework for Moral Education: One Dimension of a Fourfold System.

    ERIC Educational Resources Information Center

    Armon, Joan

    This paper examines moral education as a holistic structure that evolves from the interplay between the educational applications of anthroposophy, students' developmental needs, the curriculum, as indicated by Rudolf Steiner, and teachers' roles in fashioning the curriculum. The methodology draws upon the qualitative research paradigm of…

  4. Reconstructing Unrooted Phylogenetic Trees from Symbolic Ternary Metrics.

    PubMed

    Grünewald, Stefan; Long, Yangjing; Wu, Yaokun

    2018-03-09

    Böcker and Dress (Adv Math 138:105-125, 1998) presented a 1-to-1 correspondence between symbolically dated rooted trees and symbolic ultrametrics. We consider the corresponding problem for unrooted trees. More precisely, given a tree T with leaf set X and a proper vertex coloring of its interior vertices, we can map every triple of three different leaves to the color of its median vertex. We characterize all ternary maps that can be obtained in this way in terms of 4- and 5-point conditions, and we show that the corresponding tree and its coloring can be reconstructed from a ternary map that satisfies those conditions. Further, we give an additional condition that characterizes whether the tree is binary, and we describe an algorithm that reconstructs general trees in a bottom-up fashion.

  5. An efficient parallel termination detection algorithm

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

    Baker, A. H.; Crivelli, S.; Jessup, E. R.

    2004-05-27

    Information local to any one processor is insufficient to monitor the overall progress of most distributed computations. Typically, a second distributed computation for detecting termination of the main computation is necessary. In order to be a useful computational tool, the termination detection routine must operate concurrently with the main computation, adding minimal overhead, and it must promptly and correctly detect termination when it occurs. In this paper, we present a new algorithm for detecting the termination of a parallel computation on distributed-memory MIMD computers that satisfies all of those criteria. A variety of termination detection algorithms have been devised. Ofmore » these, the algorithm presented by Sinha, Kale, and Ramkumar (henceforth, the SKR algorithm) is unique in its ability to adapt to the load conditions of the system on which it runs, thereby minimizing the impact of termination detection on performance. Because their algorithm also detects termination quickly, we consider it to be the most efficient practical algorithm presently available. The termination detection algorithm presented here was developed for use in the PMESC programming library for distributed-memory MIMD computers. Like the SKR algorithm, our algorithm adapts to system loads and imposes little overhead. Also like the SKR algorithm, ours is tree-based, and it does not depend on any assumptions about the physical interconnection topology of the processors or the specifics of the distributed computation. In addition, our algorithm is easier to implement and requires only half as many tree traverses as does the SKR algorithm. This paper is organized as follows. In section 2, we define our computational model. In section 3, we review the SKR algorithm. We introduce our new algorithm in section 4, and prove its correctness in section 5. We discuss its efficiency and present experimental results in section 6.« less

  6. Joint amalgamation of most parsimonious reconciled gene trees

    PubMed Central

    Scornavacca, Celine; Jacox, Edwin; Szöllősi, Gergely J.

    2015-01-01

    Motivation: Traditionally, gene phylogenies have been reconstructed solely on the basis of molecular sequences; this, however, often does not provide enough information to distinguish between statistically equivalent relationships. To address this problem, several recent methods have incorporated information on the species phylogeny in gene tree reconstruction, leading to dramatic improvements in accuracy. Although probabilistic methods are able to estimate all model parameters but are computationally expensive, parsimony methods—generally computationally more efficient—require a prior estimate of parameters and of the statistical support. Results: Here, we present the Tree Estimation using Reconciliation (TERA) algorithm, a parsimony based, species tree aware method for gene tree reconstruction based on a scoring scheme combining duplication, transfer and loss costs with an estimate of the sequence likelihood. TERA explores all reconciled gene trees that can be amalgamated from a sample of gene trees. Using a large scale simulated dataset, we demonstrate that TERA achieves the same accuracy as the corresponding probabilistic method while being faster, and outperforms other parsimony-based methods in both accuracy and speed. Running TERA on a set of 1099 homologous gene families from complete cyanobacterial genomes, we find that incorporating knowledge of the species tree results in a two thirds reduction in the number of apparent transfer events. Availability and implementation: The algorithm is implemented in our program TERA, which is freely available from http://mbb.univ-montp2.fr/MBB/download_sources/16__TERA. Contact: celine.scornavacca@univ-montp2.fr, ssolo@angel.elte.hu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:25380957

  7. Understanding the Scalability of Bayesian Network Inference Using Clique Tree Growth Curves

    NASA Technical Reports Server (NTRS)

    Mengshoel, Ole J.

    2010-01-01

    One of the main approaches to performing computation in Bayesian networks (BNs) is clique tree clustering and propagation. The clique tree approach consists of propagation in a clique tree compiled from a Bayesian network, and while it was introduced in the 1980s, there is still a lack of understanding of how clique tree computation time depends on variations in BN size and structure. In this article, we improve this understanding by developing an approach to characterizing clique tree growth as a function of parameters that can be computed in polynomial time from BNs, specifically: (i) the ratio of the number of a BN s non-root nodes to the number of root nodes, and (ii) the expected number of moral edges in their moral graphs. Analytically, we partition the set of cliques in a clique tree into different sets, and introduce a growth curve for the total size of each set. For the special case of bipartite BNs, there are two sets and two growth curves, a mixed clique growth curve and a root clique growth curve. In experiments, where random bipartite BNs generated using the BPART algorithm are studied, we systematically increase the out-degree of the root nodes in bipartite Bayesian networks, by increasing the number of leaf nodes. Surprisingly, root clique growth is well-approximated by Gompertz growth curves, an S-shaped family of curves that has previously been used to describe growth processes in biology, medicine, and neuroscience. We believe that this research improves the understanding of the scaling behavior of clique tree clustering for a certain class of Bayesian networks; presents an aid for trade-off studies of clique tree clustering using growth curves; and ultimately provides a foundation for benchmarking and developing improved BN inference and machine learning algorithms.

  8. Minimizing the average distance to a closest leaf in a phylogenetic tree.

    PubMed

    Matsen, Frederick A; Gallagher, Aaron; McCoy, Connor O

    2013-11-01

    When performing an analysis on a collection of molecular sequences, it can be convenient to reduce the number of sequences under consideration while maintaining some characteristic of a larger collection of sequences. For example, one may wish to select a subset of high-quality sequences that represent the diversity of a larger collection of sequences. One may also wish to specialize a large database of characterized "reference sequences" to a smaller subset that is as close as possible on average to a collection of "query sequences" of interest. Such a representative subset can be useful whenever one wishes to find a set of reference sequences that is appropriate to use for comparative analysis of environmentally derived sequences, such as for selecting "reference tree" sequences for phylogenetic placement of metagenomic reads. In this article, we formalize these problems in terms of the minimization of the Average Distance to the Closest Leaf (ADCL) and investigate algorithms to perform the relevant minimization. We show that the greedy algorithm is not effective, show that a variant of the Partitioning Around Medoids (PAM) heuristic gets stuck in local minima, and develop an exact dynamic programming approach. Using this exact program we note that the performance of PAM appears to be good for simulated trees, and is faster than the exact algorithm for small trees. On the other hand, the exact program gives solutions for all numbers of leaves less than or equal to the given desired number of leaves, whereas PAM only gives a solution for the prespecified number of leaves. Via application to real data, we show that the ADCL criterion chooses chimeric sequences less often than random subsets, whereas the maximization of phylogenetic diversity chooses them more often than random. These algorithms have been implemented in publicly available software.

  9. Tests with VHR images for the identification of olive trees and other fruit trees in the European Union

    NASA Astrophysics Data System (ADS)

    Masson, Josiane; Soille, Pierre; Mueller, Rick

    2004-10-01

    In the context of the Common Agricultural Policy (CAP) there is a strong interest of the European Commission for counting and individually locating fruit trees. An automatic counting algorithm developed by the JRC (OLICOUNT) was used in the past for olive trees only, on 1m black and white orthophotos but with limits in case of young trees or irregular groves. This study investigates the improvement of fruit tree identification using VHR images on a large set of data in three test sites, one in Creta (Greece; one in the south-east of France with a majority of olive trees and associated fruit trees, and the last one in Florida on citrus trees. OLICOUNT was compared with two other automatic tree counting, applications, one using the CRISP software on citrus trees and the other completely automatic based on regional minima (morphological image analysis). Additional investigation was undertaken to refine the methods. This paper describes the automatic methods and presents the results derived from the tests.

  10. Point-in-convex polygon and point-in-convex polyhedron algorithms with O(1) complexity using space subdivision

    NASA Astrophysics Data System (ADS)

    Skala, Vaclav

    2016-06-01

    There are many space subdivision and space partitioning techniques used in many algorithms to speed up computations. They mostly rely on orthogonal space subdivision, resp. using hierarchical data structures, e.g. BSP trees, quadtrees, octrees, kd-trees, bounding volume hierarchies etc. However in some applications a non-orthogonal space subdivision can offer new ways for actual speed up. In the case of convex polygon in E2 a simple Point-in-Polygon test is of the O(N) complexity and the optimal algorithm is of O(log N) computational complexity. In the E3 case, the complexity is O(N) even for the convex polyhedron as no ordering is defined. New Point-in-Convex Polygon and Point-in-Convex Polyhedron algorithms are presented based on space subdivision in the preprocessing stage resulting to O(1) run-time complexity. The presented approach is simple to implement. Due to the principle of duality, dual problems, e.g. line-convex polygon, line clipping, can be solved in a similarly.

  11. An Asymptotically-Optimal Sampling-Based Algorithm for Bi-directional Motion Planning

    PubMed Central

    Starek, Joseph A.; Gomez, Javier V.; Schmerling, Edward; Janson, Lucas; Moreno, Luis; Pavone, Marco

    2015-01-01

    Bi-directional search is a widely used strategy to increase the success and convergence rates of sampling-based motion planning algorithms. Yet, few results are available that merge both bi-directional search and asymptotic optimality into existing optimal planners, such as PRM*, RRT*, and FMT*. The objective of this paper is to fill this gap. Specifically, this paper presents a bi-directional, sampling-based, asymptotically-optimal algorithm named Bi-directional FMT* (BFMT*) that extends the Fast Marching Tree (FMT*) algorithm to bidirectional search while preserving its key properties, chiefly lazy search and asymptotic optimality through convergence in probability. BFMT* performs a two-source, lazy dynamic programming recursion over a set of randomly-drawn samples, correspondingly generating two search trees: one in cost-to-come space from the initial configuration and another in cost-to-go space from the goal configuration. Numerical experiments illustrate the advantages of BFMT* over its unidirectional counterpart, as well as a number of other state-of-the-art planners. PMID:27004130

  12. Simulation-Based Model Checking for Nondeterministic Systems and Rare Events

    DTIC Science & Technology

    2016-03-24

    year, we have investigated AO* search and Monte Carlo Tree Search algorithms to complement and enhance CMU’s SMCMDP. 1 Final Report, March 14... tree , so we can use it to find the probability of reachability for a property in PRISM’s Probabilistic LTL. By finding the maximum probability of...savings, particularly when handling very large models. 2.3 Monte Carlo Tree Search The Monte Carlo sampling process in SMCMDP can take a long time to

  13. Nearest Neighbor Searching in Binary Search Trees: Simulation of a Multiprocessor System.

    ERIC Educational Resources Information Center

    Stewart, Mark; Willett, Peter

    1987-01-01

    Describes the simulation of a nearest neighbor searching algorithm for document retrieval using a pool of microprocessors. Three techniques are described which allow parallel searching of a binary search tree as well as a PASCAL-based system, PASSIM, which can simulate these techniques. Fifty-six references are provided. (Author/LRW)

  14. Invasion Percolation and Global Optimization

    NASA Astrophysics Data System (ADS)

    Barabási, Albert-László

    1996-05-01

    Invasion bond percolation (IBP) is mapped exactly into Prim's algorithm for finding the shortest spanning tree of a weighted random graph. Exploring this mapping, which is valid for arbitrary dimensions and lattices, we introduce a new IBP model that belongs to the same universality class as IBP and generates the minimal energy tree spanning the IBP cluster.

  15. What Satisfies Students?: Mining Student-Opinion Data with Regression and Decision Tree Analysis

    ERIC Educational Resources Information Center

    Thomas, Emily H.; Galambos, Nora

    2004-01-01

    To investigate how students' characteristics and experiences affect satisfaction, this study uses regression and decision tree analysis with the CHAID algorithm to analyze student-opinion data. A data mining approach identifies the specific aspects of students' university experience that most influence three measures of general satisfaction. The…

  16. A diagnosis system using object-oriented fault tree models

    NASA Technical Reports Server (NTRS)

    Iverson, David L.; Patterson-Hine, F. A.

    1990-01-01

    Spaceborne computing systems must provide reliable, continuous operation for extended periods. Due to weight, power, and volume constraints, these systems must manage resources very effectively. A fault diagnosis algorithm is described which enables fast and flexible diagnoses in the dynamic distributed computing environments planned for future space missions. The algorithm uses a knowledge base that is easily changed and updated to reflect current system status. Augmented fault trees represented in an object-oriented form provide deep system knowledge that is easy to access and revise as a system changes. Given such a fault tree, a set of failure events that have occurred, and a set of failure events that have not occurred, this diagnosis system uses forward and backward chaining to propagate causal and temporal information about other failure events in the system being diagnosed. Once the system has established temporal and causal constraints, it reasons backward from heuristically selected failure events to find a set of basic failure events which are a likely cause of the occurrence of the top failure event in the fault tree. The diagnosis system has been implemented in common LISP using Flavors.

  17. FDT 2.0: Improving scalability of the fuzzy decision tree induction tool - integrating database storage.

    PubMed

    Durham, Erin-Elizabeth A; Yu, Xiaxia; Harrison, Robert W

    2014-12-01

    Effective machine-learning handles large datasets efficiently. One key feature of handling large data is the use of databases such as MySQL. The freeware fuzzy decision tree induction tool, FDT, is a scalable supervised-classification software tool implementing fuzzy decision trees. It is based on an optimized fuzzy ID3 (FID3) algorithm. FDT 2.0 improves upon FDT 1.0 by bridging the gap between data science and data engineering: it combines a robust decisioning tool with data retention for future decisions, so that the tool does not need to be recalibrated from scratch every time a new decision is required. In this paper we briefly review the analytical capabilities of the freeware FDT tool and its major features and functionalities; examples of large biological datasets from HIV, microRNAs and sRNAs are included. This work shows how to integrate fuzzy decision algorithms with modern database technology. In addition, we show that integrating the fuzzy decision tree induction tool with database storage allows for optimal user satisfaction in today's Data Analytics world.

  18. Seasonal variations of isoprene emissions from deciduous trees

    NASA Astrophysics Data System (ADS)

    Xiaoshan, Zhang; Yujing, Mu; Wenzhi, Song; Yahui, Zhuang

    Isoprene emission fluxes were investigated for 12 tree species in and around Beijing city. Bag-enclosure method was used to collect the air sample and GC-PID was used to directly analyze isoprene. Ginkgo and Magnolia denudata had negligible isoprene emissions, while significant emissions were observed for Platanus orientalis, Pendula loud, Populus simonii, and Salix matsudana koidz, and other remaining trees showed no sign of isoprene emission. Variations in isoprene emission with changes in light, temperature and season were investigated for Platanus orientalis and Pendula loud. Isoprene emission rates strongly depended on light, temperature and leaf age. The maximum emission rates for the two trees were observed in summer with values of about 232 and 213 μg g -1 dw h -1, respectively. The measured emission fluxes were used to evaluate "Guenther" emission algorithm. The emission fluxes predicted by the algorithm were in relatively good agreement with field measurements. However, there were large differences for the calculated median emission factors during spring, summer and fall. The 25-75 percentiles span of the emission factor data sets ranged from -33 to +15% of the median values.

  19. Compact 0-complete trees: A new method for searching large files

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

    Orlandic, R.; Pfaltz, J.L.

    1988-01-26

    In this report, a novel approach to ordered retrieval in very large files is developed. The method employs a B-tree like search algorithm that is independent of key type or key length because all keys in index blocks are encoded by a 1 byte surrogate. The replacement of actual key sequences by the 1 byte surrogate ensures a maximal possible fan out and greatly reduces the storage overhead of maintaining access indices. Initially, retrieval in binary trie structure is developed. With the aid of a fairly complex recurrence relation, the rather scraggly binary trie is transformed into compact multi-way searchmore » tree. Then the recurrence relation itself is replaced by an unusually simple search algorithm. Then implementation details and empirical performance results are presented. Reduction of index size by 50%--75% opens up the possibility of replicating system-wide indices for parallel access in distributed databases. 23 figs.« less

  20. Retinal optical coherence tomography image enhancement via shrinkage denoising using double-density dual-tree complex wavelet transform

    PubMed Central

    Mayer, Markus A.; Boretsky, Adam R.; van Kuijk, Frederik J.; Motamedi, Massoud

    2012-01-01

    Abstract. Image enhancement of retinal structures, in optical coherence tomography (OCT) scans through denoising, has the potential to aid in the diagnosis of several eye diseases. In this paper, a locally adaptive denoising algorithm using double-density dual-tree complex wavelet transform, a combination of the double-density wavelet transform and the dual-tree complex wavelet transform, is applied to reduce speckle noise in OCT images of the retina. The algorithm overcomes the limitations of commonly used multiple frame averaging technique, namely the limited number of frames that can be recorded due to eye movements, by providing a comparable image quality in significantly less acquisition time equal to an order of magnitude less time compared to the averaging method. In addition, improvements of image quality metrics and 5 dB increase in the signal-to-noise ratio are attained. PMID:23117804

  1. Retinal optical coherence tomography image enhancement via shrinkage denoising using double-density dual-tree complex wavelet transform.

    PubMed

    Chitchian, Shahab; Mayer, Markus A; Boretsky, Adam R; van Kuijk, Frederik J; Motamedi, Massoud

    2012-11-01

    ABSTRACT. Image enhancement of retinal structures, in optical coherence tomography (OCT) scans through denoising, has the potential to aid in the diagnosis of several eye diseases. In this paper, a locally adaptive denoising algorithm using double-density dual-tree complex wavelet transform, a combination of the double-density wavelet transform and the dual-tree complex wavelet transform, is applied to reduce speckle noise in OCT images of the retina. The algorithm overcomes the limitations of commonly used multiple frame averaging technique, namely the limited number of frames that can be recorded due to eye movements, by providing a comparable image quality in significantly less acquisition time equal to an order of magnitude less time compared to the averaging method. In addition, improvements of image quality metrics and 5 dB increase in the signal-to-noise ratio are attained.

  2. Evolutionary tree reconstruction

    NASA Technical Reports Server (NTRS)

    Cheeseman, Peter; Kanefsky, Bob

    1990-01-01

    It is described how Minimum Description Length (MDL) can be applied to the problem of DNA and protein evolutionary tree reconstruction. If there is a set of mutations that transform a common ancestor into a set of the known sequences, and this description is shorter than the information to encode the known sequences directly, then strong evidence for an evolutionary relationship has been found. A heuristic algorithm is described that searches for the simplest tree (smallest MDL) that finds close to optimal trees on the test data. Various ways of extending the MDL theory to more complex evolutionary relationships are discussed.

  3. Tiling a figure using a height in a tree

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

    Remila, E.

    1996-12-31

    We first give a new presentation of an algorithm from Thurston of tiling with lozenges formed from two cells of the triangular lattice A. Secondly we extend the method to get a linear algorithm of tiling with leaning dominoes (parallelograms formed from four cells of {Lambda}) and triangles (formed from four cells of {Lambda}). Thirdly, we produce a quadratic algorithm of tiling with leaning dominoes.

  4. Observation Uncertainty in Gaussian Sensor Networks

    DTIC Science & Technology

    2006-01-23

    Ziv , J., and Lempel , A. A universal algorithm for sequential data compression . IEEE Transactions on Information Theory 23, 3 (1977), 337–343. 73 ...using the Lempel - Ziv algorithm [42], context-tree weighting [41], or the Burrows-Wheeler Trans- form [4], [15], for example. These source codes will...and Computation (Monticello, IL, September 2004). [4] Burrows, M., and Wheeler, D. A block sorting lossless data compression algorithm . Tech.

  5. Fast Marching Tree: a Fast Marching Sampling-Based Method for Optimal Motion Planning in Many Dimensions*

    PubMed Central

    Janson, Lucas; Schmerling, Edward; Clark, Ashley; Pavone, Marco

    2015-01-01

    In this paper we present a novel probabilistic sampling-based motion planning algorithm called the Fast Marching Tree algorithm (FMT*). The algorithm is specifically aimed at solving complex motion planning problems in high-dimensional configuration spaces. This algorithm is proven to be asymptotically optimal and is shown to converge to an optimal solution faster than its state-of-the-art counterparts, chiefly PRM* and RRT*. The FMT* algorithm performs a “lazy” dynamic programming recursion on a predetermined number of probabilistically-drawn samples to grow a tree of paths, which moves steadily outward in cost-to-arrive space. As such, this algorithm combines features of both single-query algorithms (chiefly RRT) and multiple-query algorithms (chiefly PRM), and is reminiscent of the Fast Marching Method for the solution of Eikonal equations. As a departure from previous analysis approaches that are based on the notion of almost sure convergence, the FMT* algorithm is analyzed under the notion of convergence in probability: the extra mathematical flexibility of this approach allows for convergence rate bounds—the first in the field of optimal sampling-based motion planning. Specifically, for a certain selection of tuning parameters and configuration spaces, we obtain a convergence rate bound of order O(n−1/d+ρ), where n is the number of sampled points, d is the dimension of the configuration space, and ρ is an arbitrarily small constant. We go on to demonstrate asymptotic optimality for a number of variations on FMT*, namely when the configuration space is sampled non-uniformly, when the cost is not arc length, and when connections are made based on the number of nearest neighbors instead of a fixed connection radius. Numerical experiments over a range of dimensions and obstacle configurations confirm our the-oretical and heuristic arguments by showing that FMT*, for a given execution time, returns substantially better solutions than either PRM* or RRT*, especially in high-dimensional configuration spaces and in scenarios where collision-checking is expensive. PMID:27003958

  6. The stopping rules for winsorized tree

    NASA Astrophysics Data System (ADS)

    Ch'ng, Chee Keong; Mahat, Nor Idayu

    2017-11-01

    Winsorized tree is a modified tree-based classifier that is able to investigate and to handle all outliers in all nodes along the process of constructing the tree. It overcomes the tedious process of constructing a classical tree where the splitting of branches and pruning go concurrently so that the constructed tree would not grow bushy. This mechanism is controlled by the proposed algorithm. In winsorized tree, data are screened for identifying outlier. If outlier is detected, the value is neutralized using winsorize approach. Both outlier identification and value neutralization are executed recursively in every node until predetermined stopping criterion is met. The aim of this paper is to search for significant stopping criterion to stop the tree from further splitting before overfitting. The result obtained from the conducted experiment on pima indian dataset proved that the node could produce the final successor nodes (leaves) when it has achieved the range of 70% in information gain.

  7. HD-MTL: Hierarchical Deep Multi-Task Learning for Large-Scale Visual Recognition.

    PubMed

    Fan, Jianping; Zhao, Tianyi; Kuang, Zhenzhong; Zheng, Yu; Zhang, Ji; Yu, Jun; Peng, Jinye

    2017-02-09

    In this paper, a hierarchical deep multi-task learning (HD-MTL) algorithm is developed to support large-scale visual recognition (e.g., recognizing thousands or even tens of thousands of atomic object classes automatically). First, multiple sets of multi-level deep features are extracted from different layers of deep convolutional neural networks (deep CNNs), and they are used to achieve more effective accomplishment of the coarseto- fine tasks for hierarchical visual recognition. A visual tree is then learned by assigning the visually-similar atomic object classes with similar learning complexities into the same group, which can provide a good environment for determining the interrelated learning tasks automatically. By leveraging the inter-task relatedness (inter-class similarities) to learn more discriminative group-specific deep representations, our deep multi-task learning algorithm can train more discriminative node classifiers for distinguishing the visually-similar atomic object classes effectively. Our hierarchical deep multi-task learning (HD-MTL) algorithm can integrate two discriminative regularization terms to control the inter-level error propagation effectively, and it can provide an end-to-end approach for jointly learning more representative deep CNNs (for image representation) and more discriminative tree classifier (for large-scale visual recognition) and updating them simultaneously. Our incremental deep learning algorithms can effectively adapt both the deep CNNs and the tree classifier to the new training images and the new object classes. Our experimental results have demonstrated that our HD-MTL algorithm can achieve very competitive results on improving the accuracy rates for large-scale visual recognition.

  8. An Improved Heuristic Method for Subgraph Isomorphism Problem

    NASA Astrophysics Data System (ADS)

    Xiang, Yingzhuo; Han, Jiesi; Xu, Haijiang; Guo, Xin

    2017-09-01

    This paper focus on the subgraph isomorphism (SI) problem. We present an improved genetic algorithm, a heuristic method to search the optimal solution. The contribution of this paper is that we design a dedicated crossover algorithm and a new fitness function to measure the evolution process. Experiments show our improved genetic algorithm performs better than other heuristic methods. For a large graph, such as a subgraph of 40 nodes, our algorithm outperforms the traditional tree search algorithms. We find that the performance of our improved genetic algorithm does not decrease as the number of nodes in prototype graphs.

  9. Global tree network for computing structures enabling global processing operations

    DOEpatents

    Blumrich; Matthias A.; Chen, Dong; Coteus, Paul W.; Gara, Alan G.; Giampapa, Mark E.; Heidelberger, Philip; Hoenicke, Dirk; Steinmacher-Burow, Burkhard D.; Takken, Todd E.; Vranas, Pavlos M.

    2010-01-19

    A system and method for enabling high-speed, low-latency global tree network communications among processing nodes interconnected according to a tree network structure. The global tree network enables collective reduction operations to be performed during parallel algorithm operations executing in a computer structure having a plurality of the interconnected processing nodes. Router devices are included that interconnect the nodes of the tree via links to facilitate performance of low-latency global processing operations at nodes of the virtual tree and sub-tree structures. The global operations performed include one or more of: broadcast operations downstream from a root node to leaf nodes of a virtual tree, reduction operations upstream from leaf nodes to the root node in the virtual tree, and point-to-point message passing from any node to the root node. The global tree network is configurable to provide global barrier and interrupt functionality in asynchronous or synchronized manner, and, is physically and logically partitionable.

  10. Constructing high-quality bounding volume hierarchies for N-body computation using the acceptance volume heuristic

    NASA Astrophysics Data System (ADS)

    Olsson, O.

    2018-01-01

    We present a novel heuristic derived from a probabilistic cost model for approximate N-body simulations. We show that this new heuristic can be used to guide tree construction towards higher quality trees with improved performance over current N-body codes. This represents an important step beyond the current practice of using spatial partitioning for N-body simulations, and enables adoption of a range of state-of-the-art algorithms developed for computer graphics applications to yield further improvements in N-body simulation performance. We outline directions for further developments and review the most promising such algorithms.

  11. Novel ID-based anti-collision approach for RFID

    NASA Astrophysics Data System (ADS)

    Zhang, De-Gan; Li, Wen-Bin

    2016-09-01

    Novel correlation ID-based (CID) anti-collision approach for RFID under the banner of the Internet of Things (IOT) has been presented in this paper. The key insights are as follows: according to the deterministic algorithms which are based on the binary search tree, we propose a method to increase the association between tags so that tags can initiatively send their own ID under certain trigger conditions, at the same time, we present a multi-tree search method for querying. When the number of tags is small, by replacing the actual ID with the temporary ID, it can greatly reduce the number of times that the reader reads and writes to tag's ID. Active tags send data to the reader by the way of modulation binary pulses. When applying this method to the uncertain ALOHA algorithms, the reader can determine the locations of the empty slots according to the position of the binary pulse, so it can avoid the decrease in efficiency which is caused by reading empty slots when reading slots. Theory and experiment show that this method can greatly improve the recognition efficiency of the system when applied to either the search tree or the ALOHA anti-collision algorithms.

  12. INDDGO: Integrated Network Decomposition & Dynamic programming for Graph Optimization

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

    Groer, Christopher S; Sullivan, Blair D; Weerapurage, Dinesh P

    2012-10-01

    It is well-known that dynamic programming algorithms can utilize tree decompositions to provide a way to solve some \\emph{NP}-hard problems on graphs where the complexity is polynomial in the number of nodes and edges in the graph, but exponential in the width of the underlying tree decomposition. However, there has been relatively little computational work done to determine the practical utility of such dynamic programming algorithms. We have developed software to construct tree decompositions using various heuristics and have created a fast, memory-efficient dynamic programming implementation for solving maximum weighted independent set. We describe our software and the algorithms wemore » have implemented, focusing on memory saving techniques for the dynamic programming. We compare the running time and memory usage of our implementation with other techniques for solving maximum weighted independent set, including a commercial integer programming solver and a semi-definite programming solver. Our results indicate that it is possible to solve some instances where the underlying decomposition has width much larger than suggested by the literature. For certain types of problems, our dynamic programming code runs several times faster than these other methods.« less

  13. Holoentropy enabled-decision tree for automatic classification of diabetic retinopathy using retinal fundus images.

    PubMed

    Mane, Vijay Mahadeo; Jadhav, D V

    2017-05-24

    Diabetic retinopathy (DR) is the most common diabetic eye disease. Doctors are using various test methods to detect DR. But, the availability of test methods and requirements of domain experts pose a new challenge in the automatic detection of DR. In order to fulfill this objective, a variety of algorithms has been developed in the literature. In this paper, we propose a system consisting of a novel sparking process and a holoentropy-based decision tree for automatic classification of DR images to further improve the effectiveness. The sparking process algorithm is developed for automatic segmentation of blood vessels through the estimation of optimal threshold. The holoentropy enabled decision tree is newly developed for automatic classification of retinal images into normal or abnormal using hybrid features which preserve the disease-level patterns even more than the signal level of the feature. The effectiveness of the proposed system is analyzed using standard fundus image databases DIARETDB0 and DIARETDB1 for sensitivity, specificity and accuracy. The proposed system yields sensitivity, specificity and accuracy values of 96.72%, 97.01% and 96.45%, respectively. The experimental result reveals that the proposed technique outperforms the existing algorithms.

  14. Prediction of microRNA target genes using an efficient genetic algorithm-based decision tree.

    PubMed

    Rabiee-Ghahfarrokhi, Behzad; Rafiei, Fariba; Niknafs, Ali Akbar; Zamani, Behzad

    2015-01-01

    MicroRNAs (miRNAs) are small, non-coding RNA molecules that regulate gene expression in almost all plants and animals. They play an important role in key processes, such as proliferation, apoptosis, and pathogen-host interactions. Nevertheless, the mechanisms by which miRNAs act are not fully understood. The first step toward unraveling the function of a particular miRNA is the identification of its direct targets. This step has shown to be quite challenging in animals primarily because of incomplete complementarities between miRNA and target mRNAs. In recent years, the use of machine-learning techniques has greatly increased the prediction of miRNA targets, avoiding the need for costly and time-consuming experiments to achieve miRNA targets experimentally. Among the most important machine-learning algorithms are decision trees, which classify data based on extracted rules. In the present work, we used a genetic algorithm in combination with C4.5 decision tree for prediction of miRNA targets. We applied our proposed method to a validated human datasets. We nearly achieved 93.9% accuracy of classification, which could be related to the selection of best rules.

  15. Application of Machine-Learning Models to Predict Tacrolimus Stable Dose in Renal Transplant Recipients

    NASA Astrophysics Data System (ADS)

    Tang, Jie; Liu, Rong; Zhang, Yue-Li; Liu, Mou-Ze; Hu, Yong-Fang; Shao, Ming-Jie; Zhu, Li-Jun; Xin, Hua-Wen; Feng, Gui-Wen; Shang, Wen-Jun; Meng, Xiang-Guang; Zhang, Li-Rong; Ming, Ying-Zi; Zhang, Wei

    2017-02-01

    Tacrolimus has a narrow therapeutic window and considerable variability in clinical use. Our goal was to compare the performance of multiple linear regression (MLR) and eight machine learning techniques in pharmacogenetic algorithm-based prediction of tacrolimus stable dose (TSD) in a large Chinese cohort. A total of 1,045 renal transplant patients were recruited, 80% of which were randomly selected as the “derivation cohort” to develop dose-prediction algorithm, while the remaining 20% constituted the “validation cohort” to test the final selected algorithm. MLR, artificial neural network (ANN), regression tree (RT), multivariate adaptive regression splines (MARS), boosted regression tree (BRT), support vector regression (SVR), random forest regression (RFR), lasso regression (LAR) and Bayesian additive regression trees (BART) were applied and their performances were compared in this work. Among all the machine learning models, RT performed best in both derivation [0.71 (0.67-0.76)] and validation cohorts [0.73 (0.63-0.82)]. In addition, the ideal rate of RT was 4% higher than that of MLR. To our knowledge, this is the first study to use machine learning models to predict TSD, which will further facilitate personalized medicine in tacrolimus administration in the future.

  16. Prediction of microRNA target genes using an efficient genetic algorithm-based decision tree

    PubMed Central

    Rabiee-Ghahfarrokhi, Behzad; Rafiei, Fariba; Niknafs, Ali Akbar; Zamani, Behzad

    2015-01-01

    MicroRNAs (miRNAs) are small, non-coding RNA molecules that regulate gene expression in almost all plants and animals. They play an important role in key processes, such as proliferation, apoptosis, and pathogen–host interactions. Nevertheless, the mechanisms by which miRNAs act are not fully understood. The first step toward unraveling the function of a particular miRNA is the identification of its direct targets. This step has shown to be quite challenging in animals primarily because of incomplete complementarities between miRNA and target mRNAs. In recent years, the use of machine-learning techniques has greatly increased the prediction of miRNA targets, avoiding the need for costly and time-consuming experiments to achieve miRNA targets experimentally. Among the most important machine-learning algorithms are decision trees, which classify data based on extracted rules. In the present work, we used a genetic algorithm in combination with C4.5 decision tree for prediction of miRNA targets. We applied our proposed method to a validated human datasets. We nearly achieved 93.9% accuracy of classification, which could be related to the selection of best rules. PMID:26649272

  17. Evaluation of Algorithms for a Miles-in-Trail Decision Support Tool

    NASA Technical Reports Server (NTRS)

    Bloem, Michael; Hattaway, David; Bambos, Nicholas

    2012-01-01

    Four machine learning algorithms were prototyped and evaluated for use in a proposed decision support tool that would assist air traffic managers as they set Miles-in-Trail restrictions. The tool would display probabilities that each possible Miles-in-Trail value should be used in a given situation. The algorithms were evaluated with an expected Miles-in-Trail cost that assumes traffic managers set restrictions based on the tool-suggested probabilities. Basic Support Vector Machine, random forest, and decision tree algorithms were evaluated, as was a softmax regression algorithm that was modified to explicitly reduce the expected Miles-in-Trail cost. The algorithms were evaluated with data from the summer of 2011 for air traffic flows bound to the Newark Liberty International Airport (EWR) over the ARD, PENNS, and SHAFF fixes. The algorithms were provided with 18 input features that describe the weather at EWR, the runway configuration at EWR, the scheduled traffic demand at EWR and the fixes, and other traffic management initiatives in place at EWR. Features describing other traffic management initiatives at EWR and the weather at EWR achieved relatively high information gain scores, indicating that they are the most useful for estimating Miles-in-Trail. In spite of a high variance or over-fitting problem, the decision tree algorithm achieved the lowest expected Miles-in-Trail costs when the algorithms were evaluated using 10-fold cross validation with the summer 2011 data for these air traffic flows.

  18. Crown-Level Tree Species Classification Using Integrated Airborne Hyperspectral and LIDAR Remote Sensing Data

    NASA Astrophysics Data System (ADS)

    Wang, Z.; Wu, J.; Wang, Y.; Kong, X.; Bao, H.; Ni, Y.; Ma, L.; Jin, J.

    2018-05-01

    Mapping tree species is essential for sustainable planning as well as to improve our understanding of the role of different trees as different ecological service. However, crown-level tree species automatic classification is a challenging task due to the spectral similarity among diversified tree species, fine-scale spatial variation, shadow, and underlying objects within a crown. Advanced remote sensing data such as airborne Light Detection and Ranging (LiDAR) and hyperspectral imagery offer a great potential opportunity to derive crown spectral, structure and canopy physiological information at the individual crown scale, which can be useful for mapping tree species. In this paper, an innovative approach was developed for tree species classification at the crown level. The method utilized LiDAR data for individual tree crown delineation and morphological structure extraction, and Compact Airborne Spectrographic Imager (CASI) hyperspectral imagery for pure crown-scale spectral extraction. Specifically, four steps were include: 1) A weighted mean filtering method was developed to improve the accuracy of the smoothed Canopy Height Model (CHM) derived from LiDAR data; 2) The marker-controlled watershed segmentation algorithm was, therefore, also employed to delineate the tree-level canopy from the CHM image in this study, and then individual tree height and tree crown were calculated according to the delineated crown; 3) Spectral features within 3 × 3 neighborhood regions centered on the treetops detected by the treetop detection algorithm were derived from the spectrally normalized CASI imagery; 4) The shape characteristics related to their crown diameters and heights were established, and different crown-level tree species were classified using the combination of spectral and shape characteristics. Analysis of results suggests that the developed classification strategy in this paper (OA = 85.12 %, Kc = 0.90) performed better than LiDAR-metrics method (OA = 79.86 %, Kc = 0.81) and spectral-metircs method (OA = 71.26, Kc = 0.69) in terms of classification accuracy, which indicated that the advanced method of data processing and sensitive feature selection are critical for improving the accuracy of crown-level tree species classification.

  19. Model-based conifer crown surface reconstruction from multi-ocular high-resolution aerial imagery

    NASA Astrophysics Data System (ADS)

    Sheng, Yongwei

    2000-12-01

    Tree crown parameters such as width, height, shape and crown closure are desirable in forestry and ecological studies, but they are time-consuming and labor intensive to measure in the field. The stereoscopic capability of high-resolution aerial imagery provides a way to crown surface reconstruction. Existing photogrammetric algorithms designed to map terrain surfaces, however, cannot adequately extract crown surfaces, especially for steep conifer crowns. Considering crown surface reconstruction in a broader context of tree characterization from aerial images, we develop a rigorous perspective tree image formation model to bridge image-based tree extraction and crown surface reconstruction, and an integrated model-based approach to conifer crown surface reconstruction. Based on the fact that most conifer crowns are in a solid geometric form, conifer crowns are modeled as a generalized hemi-ellipsoid. Both the automatic and semi-automatic approaches are investigated to optimal tree model development from multi-ocular images. The semi-automatic 3D tree interpreter developed in this thesis is able to efficiently extract reliable tree parameters and tree models in complicated tree stands. This thesis starts with a sophisticated stereo matching algorithm, and incorporates tree models to guide stereo matching. The following critical problems are addressed in the model-based surface reconstruction process: (1) the problem of surface model composition from tree models, (2) the occlusion problem in disparity prediction from tree models, (3) the problem of integrating the predicted disparities into image matching, (4) the tree model edge effect reduction on the disparity map, (5) the occlusion problem in orthophoto production, and (6) the foreshortening problem in image matching, which is very serious for conifer crown surfaces. Solutions to the above problems are necessary for successful crown surface reconstruction. The model-based approach was applied to recover the canopy surface of a dense redwood stand using tri-ocular high-resolution images scanned from 1:2,400 aerial photographs. The results demonstrate the approach's ability to reconstruct complicated stands. The model-based approach proposed in this thesis is potentially applicable to other surfaces recovering problems with a priori knowledge about objects.

  20. Pine wilt disease in Yunnan, China: Evidence of non-local pine sawyer Monochamus alternatus (Coloptera: Cerambycidae) populations revealed by mitochondrial DNA

    Treesearch

    Da-Ying Fu; Shao-Ji Hu; Hui Ye; Robert A. Haack; Ping-Yang Zhou

    2010-01-01

    Monochamus alternatus (Hope) specimens were collected from nine geographical populations in China,where the pinewood nematode Bursaphelenchus xylophilus (Steiner et Buhrer) was present. There were seven populations in southwestern China in Yunnan Province (Ruili,Wanding, Lianghe, Pu'er, Huaning, Stone Forest and Yongsheng),...

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