Generating Linear Orders of Events for Geospatial Domains

Events in the world do not occur in neat chronological order, but may take place, for example, during or overlapping each other, or as simultaneous events. Efficient summaries of real-world events are important in many disciplines and require events to be modeled in a linear fashion. This thesis focuses on modeling events as intervals and using relations between the events to derive linear orders from more complex partially ordered sets. A method is developed for mapping Allen\u27s thirteen temporal relations to only two relations, before and equals, which allow a linear ordering of all events present in the set. This mapping requires additional constraints to preserve semantics of the original relations as the orders are generated. Depending on the relations present, several linear orders may be possible, and methods are discussed of filtering the possible orders so as to present only the most plausible orders to a user. The result is a methodology that allows plausible linear orders to be automatically generated from partially-ordered sets of events

Establishing parameters for problem difficulty in permutation-based genetic algorithms

This thesis examines the performance of genetic algorithm (GA) crossover techniques within two problems: n-queens with poison (NQWP) and processor scheduling (PS). Each problem was analyzed at sizes of 32, 64, and 128, referring to number of queens to be placed and number of single-time-unit processes to be scheduled, respectively. The specific crossover techniques studied were cycle crossover, order crossover, partially mapped crossover, merging crossover, and one-point, two-point, and uniform signature representation crossover, in addition to various greedy approaches. In conjunction with tests that vary crossover techniques, experimentation was performed to determine what percentage of problem constraints (poisoned squares for NQWP or precedence relationships between tasks for PS) makes the problems most difficult to solve, that is, the constraint densities at which optimal solutions require the highest number of GA fitness evaluations. While minor fluctuations in difficulty occur upon variations in fitness function and problem size, the NQWP problem is most difficult around a constraint density of 0.8 and the PS problem is most difficult around constraint densities of 0.2 to 0.3. Even within an individual problem, one crossover technique does not irreproachably outperform others. However, cycle crossover stands out in its performance in the PS problem while merging crossover and uniform signature crossovers most often perform well for NQWP

Application of a MHD hybrid solar wind model with latitudinal dependences to Ulysses data at minimum

In a previous work, Ulysses data was analyzed to build a complete axisymmetric MHD solution for the solar wind at minimum including rotation and the initial flaring of the solar wind in the low corona. This model has some problems in reproducing the values of magnetic field at 1 AU despite the correct values of the velocity. Here, we intend to extend the previous analysis to another type of solutions and to improve our modelling of the wind from the solar surface to 1 AU. We compare the previous results to those obtained with a fully helicoidal model and construct a hybrid model combining both previous solutions, keeping the flexibility of the parent models in the appropriate domain. From the solar surface to the Alfven, point, a three component solution for velocity and magnetic field is used, reproducing the complex wind geometry and the well-known flaring of the field lines observed in coronal holes. From the Alfven radius to 1 AU and further, the hybrid model keeps the latitudinal dependences as flexible as possible, in order to deal with the sharp variations near the equator and we use the helicoidal solution, turning the poloidal streamlines into radial ones. Despite the absence of the initial flaring, the helicoidal model and the first hybrid solution suffer from the same low values of the magnetic field at 1 AU. However, by adjusting the parameters with a second hybrid solution, we are able to reproduce both the velocity and magnetic profiles observed by Ulysses and a reasonable description of the low corona, provided that a certain amount of energy deposit exists along the flow. The present paper shows that analytical axisymmetric solutions can be constructed to reproduce the solar structure and dynamics from 1 solar radius up to 1 AU.Comment: 12 pages, 16 figure

Task-Based Parallelism for General Purpose Graphics Processing Units and Hybrid Shared-Distributed Memory Systems.

Modern computers can no longer rely on increasing CPU speed to improve their performance as further increasing the clock speed of single CPU machines will make them too difficult to cool, or the cooling require too much power. Hardware manufacturers must now use parallelism to drive performance to the levels expected by Moore's Law. More recently, High Performance Computers (HPCs) have adopted heterogeneous architectures, i.e.having multiple types of computing hardware (such as CPU & GPU) on a single node. These architectures allow the opportunity to extract performance from non-CPU architectures, while still providing a general purpose platform for less modern codes. In this thesis we investigate Task-Based Parallelism, a shared-memory paradigm for parallel computing. Task-Based Parallelism requires the programmer to divide the work into chunks (known as tasks) and describe the data dependencies between tasks. The tasks are then scheduled amongst the threads automatically by the task-based scheduler. In this thesis we examine how Task-Based Parallelism can be used with GPUs and hybrid shared-distributed memory, in particular we examine how data transfer can be incorporated into a task-based framework, either to the GPU from the host, or between separate nodes. We also examine how we can use the task graph to load balance the computation between multiple nodes or GPUs. We test our task-based methods with Molecular Dynamics, a tiled QR decomposition, and a new task-based Barnes-Hut algorithm. These are problems with different dependency structures which tests the ability of the scheduler to handle a variety of different types of computation. The results with these testcases show improved performance when we use asynchronous data transfer to and from the GPU, and show reasonable parallel efficiency over a small number of MPI ranks

Teak: A Novel Computational And Gui Software Pipeline For Reconstructing Biological Networks, Detecting Activated Biological Subnetworks, And Querying Biological Networks.

As high-throughput gene expression data becomes cheaper and cheaper, researchers are faced with a deluge of data from which biological insights need to be extracted and mined since the rate of data accumulation far exceeds the rate of data analysis. There is a need for computational frameworks to bridge the gap and assist researchers in their tasks. The Topology Enrichment Analysis frameworK (TEAK) is an open source GUI and software pipeline that seeks to be one of many tools that fills in this gap and consists of three major modules. The first module, the Gene Set Cultural Algorithm, de novo infers biological networks from gene sets using the KEGG pathways as prior knowledge. The second and third modules query against the KEGG pathways using molecular profiling data and query graphs, respectively. In particular, the second module, also called TEAK, is a network partitioning module that partitions the KEGG pathways into both linear and nonlinear subpathways. In conjunction with molecular profiling data, the subpathways are ranked and displayed to the user within the TEAK GUI. Using a public microarray yeast data set, previously unreported fitness defects for dpl1 delta and lag1 delta mutants under conditions of nitrogen limitation were found using TEAK. Finally, the third module, the Query Structure Enrichment Analysis framework, is a network query module that allows researchers to query their biological hypotheses in the form of Directed Acyclic Graphs against the KEGG pathways

A Nine Month Report on Progress Towards a Framework for Evaluating Advanced Search Interfaces considering Information Retrieval and Human Computer Interaction

This is a nine month progress report detailing my research into supporting users in their search for information, where the questions, results or even thei

Spatial Relations and Natural-Language Semantics for Indoor Scenes

Over the past 15 years, there have been increased efforts to represent and communicate spatial information about entities within indoor environments. Automated annotation of information about indoor environments is needed for natural-language processing tasks, such as spatially anchoring events, tracking objects in motion, scene descriptions, and interpretation of thematic places in relationship to confirmed locations. Descriptions of indoor scenes often require a fine granularity of spatial information about the meaning of natural-language spatial utterances to improve human-computer interactions and applications for the retrieval of spatial information. The development needs of these systems provide a rationale as to why—despite an extensive body of research in spatial cognition and spatial linguistics—it is still necessary to investigate basic understandings of how humans conceptualize and communicate about objects and structures in indoor space. This thesis investigates the alignment of conceptual spatial relations and naturallanguage (NL) semantics in the representation of indoor space. The foundation of this work is grounded in spatial information theory as well as spatial cognition and spatial linguistics. In order to better understand how to align computational models and NL expressions about indoor space, this dissertation used an existing dataset of indoor scene descriptions to investigate patterns in entity identification, spatial relations, and spatial preposition use within vista-scale indoor settings. Three human-subject experiments were designed and conducted within virtual indoor environments. These experiments investigate alignment of human-subject NL expressions for a sub-set of conceptual spatial relations (contact, disjoint, and partof) within a controlled virtual environment. Each scene was designed to focus participant attention on a single relation depicted in the scene and elicit a spatial preposition term(s) to describe the focal relationship. The major results of this study are the identification of object and structure categories, spatial relationships, and patterns of spatial preposition use in the indoor scene descriptions that were consistent across both open response, closed response and ranking type items. There appeared to be a strong preference for describing scene objects in relation to the structural objects that bound the room depicted in the indoor scenes. Furthermore, for each of the three relations (contact, disjoint, and partof), a small set of spatial prepositions emerged that were strongly preferred by participants at statistically significant levels based on the overall frequency of response, image sorting, and ranking judgments. The use of certain spatial prepositions to describe relations between room structures suggests there may be differences in how indoor vista-scale space is understood in relation to tabletop and geographic scales. Finally, an indoor scene description corpus was developed as a product of this work, which should provide researchers with new human-subject based datasets for training NL algorithms used to generate more accurate and intuitive NL descriptions of indoor scenes

Interactive computer methods for plant layout scheduling and group technology

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