Assignment methods for incidence calculus

Incidence calculus is a mechanism for probabilistic reasoning in which sets of possible worlds, called incidences, are associated with axioms, and probabilities are then associated with these sets. Inference rules are used to deduce bounds on the incidence of formulae which are not axioms, and bounds for the probability of such a formula can then be obtained. In practice an assignment of probabilities directly to axioms may be given, and it is then necessary to find an assignment of incidence which will reproduce these probabilities. We show that this task of assigning incidences can be viewed as a tree searching problem, and two techniques for performing this research are discussed. One of these is a new proposal involving a depth first search, while the other incorporates a random element. A Prolog implementation of these methods has been developed. The two approaches are compared for efficiency and the significance of their results are discussed. Finally we discuss a new proposal for applying techniques from linear programming to incidence calculus.

Toward efficient multifeature query processing

In many advanced applications, data are described by multiple high-dimensional features. Moreover, different queries may weight these features differently; some may not even specify all the features. In this paper, we propose our solution to support efficient query processing in these applications. We devise a novel representation that compactly captures f features into two components: The first component is a 2D vector that reflects a distance range ( minimum and maximum values) of the f features with respect to a reference point ( the center of the space) in a metric space and the second component is a bit signature, with two bits per dimension, obtained by analyzing each feature's descending energy histogram. This representation enables two levels of filtering: The first component prunes away points that do not share similar distance ranges, while the bit signature filters away points based on the dimensions of the relevant features. Moreover, the representation facilitates the use of a single index structure to further speed up processing. We employ the classical B+-tree for this purpose. We also propose a KNN search algorithm that exploits the access orders of critical dimensions of highly selective features and partial distances to prune the search space more effectively. Our extensive experiments on both real-life and synthetic data sets show that the proposed solution offers significant performance advantages over sequential scan and retrieval methods using single and multiple VA-files.

Searching Baxter's URDF robot joint and link tree for active serial chains

Teleoperation is integral to society's uptake of modern robotic systems. Given the wide array of readily available robots, ranging from simple mobile platforms and UAVs to advanced humanoid robots such as ASIMO and PR2, teleoperation is required in many different forms. The recent advances in virtual reality systems, interactive input controls and even haptic devices facilitate a wide range of new approaches to teleoperation control. This paper considers a dynamic user interface for improving the operator's ability to teleoperate heterogeneous robotic systems in dynamic and challenging environments. In order to achieve the proposed dynamic user interface the robot(s) comprising the heterogeneous robotic system and their active components need to be categorized. The recent uptake of ROS means that many robots are now represented within the standardized Unified Robot Descriptive Format (URDF), and this paper proposes a method for searching the URDF for active serial chains in individual robot systems. Results demonstrate the ability of the approach to determine active serial chains and associated kinematic information for the Baxter torso robot.

Rapid match-searching for gene silencing assessment

Motivation: Gene silencing, also called RNA interference, requires reliable assessment of silencer impacts. A critical task is to find matches between silencer oligomers and sites in the genome, in accordance with one-to-many matching rules (G-U matching, with provision for mismatches). Fast search algorithms are required to support silencer impact assessments in procedures for designing effective silencer sequences.Results: The article presents a matching algorithm and data structures specialized for matching searches, including a kernel procedure that addresses a Boolean version of the database task called the skyline search. Besides exact matches, the algorithm is extended to allow for the location-specific mismatches applicable in plants. Computational tests show that the algorithm is significantly faster than suffix-tree alternatives. © The Author 2010. Published by Oxford University Press. All rights reserved.

Secondary attribute retrieval using tree data structures

Several techniques are known for searching an ordered collection of data. The techniques and analyses of retrieval methods based on primary attributes are straightforward. Retrieval using secondary attributes depends on several factors. For secondary attribute retrieval, the linear structures—inverted lists, multilists, doubly linked lists—and the recently proposed nonlinear tree structures—multiple attribute tree (MAT), K-d tree (kdT)—have their individual merits. It is shown in this paper that, of the two tree structures, MAT possesses several features of a systematic data structure for external file organisation which make it superior to kdT. Analytic estimates for the complexity of node searchers, in MAT and kdT for several types of queries, are developed and compared.

A comparative study of multiple attribute tree and inverted file structures for large bibliographic files

A variety of data structures such as inverted file, multi-lists, quad tree, k-d tree, range tree, polygon tree, quintary tree, multidimensional tries, segment tree, doubly chained tree, the grid file, d-fold tree. super B-tree, Multiple Attribute Tree (MAT), etc. have been studied for multidimensional searching and related problems. Physical data base organization, which is an important application of multidimensional searching, is traditionally and mostly handled by employing inverted file. This study proposes MAT data structure for bibliographic file systems, by illustrating the superiority of MAT data structure over inverted file. Both the methods are compared in terms of preprocessing, storage and query costs. Worst-case complexity analysis of both the methods, for a partial match query, is carried out in two cases: (a) when directory resides in main memory, (b) when directory resides in secondary memory. In both cases, MAT data structure is shown to be more efficient than the inverted file method. Arguments are given to illustrate the superiority of MAT data structure in an average case also. An efficient adaptation of MAT data structure, that exploits the special features of MAT structure and bibliographic files, is proposed for bibliographic file systems. In this adaptation, suitable techniques for fixing and ranking of the attributes for MAT data structure are proposed. Conclusions and proposals for future research are presented.

Searching for larval support for majoid families (Crustacea : Brachyura) with particular reference to Inachoididae Dana, 1851

We re-evaluated the larval support for families within majoids using the Wilcoxon signed-rank test with emphasis on Inachoididae. To accomplish our objectives, we added 10 new taxa, two of which are traditionally assigned to the family of special interest, to a previous larval database for majoids, and re-appraised the larval characters used in earlier studies. Phylogenetic analysis was performed with PAUP* using the heuristic search with 50 replicates or the branch-and-bound algorithm when possible. Multi-state transformation series were considered unordered; initially characters were equally weighted followed by successive weighting, and trees were rooted at the Oregoniidae node. Ten different topological constraints were enforced for families to evaluate tree length under the assumption of monophyly for each taxonomic entity. Our results showed that the tree length of most constrained topologies was not considerably greater than that of unconstrained analysis in which most families nested as paraphyletic taxa. This may indicate that the present larval database does not provide strong support for paraphyly of the taxa in question. For Inachoididae, although the Wilcoxon signed-rank test rejected a significant difference between unconstrained and constrained cladograms, we were unable to provide a single synapomorphy for this clade. Except for the conflicting position of Leurocyclus and Stenorhynchus, the two clades correspond to the traditional taxonomic arrangement. Among inachoidids, the clade (Anasimus (Paradasygyius (Collodes + Pyromaia))) is supported, whereas for inachids, the clade (Inachus (Macropodia + Achaeus)) is one of the most supported clades within majids. As often stated, only additional characters will provide a better test for the monophyly of Inachoididae and other families within Majoidea.

Searching for Elko dark matter spinors at the CERN LHC

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Canopy cover mediates interactions between a specialist caterpillar and seedlings of a neotropical tree

1 Light availability may be crucial for understanding dynamics of plant–herbivore interactions in temperate and tropical forest communities. This is because local light availability can influence both tree seedling tolerance and susceptibility to herbivory – yet how they mediate levels of insect herbivory that vary with the density of host population is virtually unknown. Here we tested predictions of three key, non-mutually exclusive hypotheses of plant–herbivore interactions: the Limiting Resource Model (LRM), the Plant Vigour Hypothesis (PVH), and the Janzen-Connell Mechanism (JCM). 2 In an Amazonian forest, we planted Swietenia macrophylla seedlings (c. 5 months old) into natural canopy gaps and the shaded understorey and simulated the damage patterns of the specialist herbivore moth, Steniscadia poliophaea, by clipping seedling leaves. Over the next 8 months, we monitored seedling performance in terms of growth and survivorship and also quantified herbivory to new young leaves on a seasonal basis. 3 In support of the LRM, severe leaf damage (≥ 50%) was lethal for Swietenia macrophylla seedlings in the understorey, but in gaps only reduced seedling growth. In support of the PVH, gap seedlings suffered greater post-simulated herbivory (up to 100% defoliation) by S. poliophaea caterpillars than their understorey counterparts. 4 Adding a novel dimension to the Janzen–Connell hypothesis, we found that early wet season herbivory of seedlings in gaps increased with conspecific adult density within a 125-m radius; whereas in the understorey only those seedlings within 50 m of a Swietenia tree were attacked by caterpillars. 5 Synthesis. These results suggest lepidopterans that need young leaves for food may forage more widely in forests to find seedlings in light-rich canopy gaps. Moths may achieve this successfully by being first attracted to gaps, and then searching within them for suitable hosts. A conceptual model, integrating conspecific adult tree density with light-driven changes in seedling tolerance/vigour and their susceptibility to herbivory and mortality, is presented. Spatial variation in the light available to tree seedlings often affects their tolerance and vigour, which may have important consequences for leaf-chewing insects and the scale of density-dependent herbivory in forests.

Searching for convergence in phylogenetic Markov chain Monte Carlo

Markov chain Monte Carlo (MCMC) is a methodology that is gaining widespread use in the phylogenetics community and is central to phylogenetic software packages such as MrBayes. An important issue for users of MCMC methods is how to select appropriate values for adjustable parameters such as the length of the Markov chain or chains, the sampling density, the proposal mechanism, and, if Metropolis-coupled MCMC is being used, the number of heated chains and their temperatures. Although some parameter settings have been examined in detail in the literature, others are frequently chosen with more regard to computational time or personal experience with other data sets. Such choices may lead to inadequate sampling of tree space or an inefficient use of computational resources. We performed a detailed study of convergence and mixing for 70 randomly selected, putatively orthologous protein sets with different sizes and taxonomic compositions. Replicated runs from multiple random starting points permit a more rigorous assessment of convergence, and we developed two novel statistics, delta and epsilon, for this purpose. Although likelihood values invariably stabilized quickly, adequate sampling of the posterior distribution of tree topologies took considerably longer. Our results suggest that multimodality is common for data sets with 30 or more taxa and that this results in slow convergence and mixing. However, we also found that the pragmatic approach of combining data from several short, replicated runs into a metachain to estimate bipartition posterior probabilities provided good approximations, and that such estimates were no worse in approximating a reference posterior distribution than those obtained using a single long run of the same length as the metachain. Precision appears to be best when heated Markov chains have low temperatures, whereas chains with high temperatures appear to sample trees with high posterior probabilities only rarely. [Bayesian phylogenetic inference; heating parameter; Markov chain Monte Carlo; replicated chains.]

Searching for Predictive Subgroups

Thesis (Ph.D.)--University of Washington, 2016-08