Semantic scheduling of virtualized infrastructures for scientific workflows

Virtualized Infrastructures are a promising way for providing flexible and dynamic computing solutions for resourceconsuming tasks. Scientific Workflows are one of these kind of tasks, as they need a large amount of computational resources during certain periods of time. To provide the best infrastructure configuration for a workflow it is necessary to explore as many providers as possible taking into account different criteria like Quality of Service, pricing, response time, network latency, etc. Moreover, each one of these new resources must be tuned to provide the tools and dependencies required by each of the steps of the workflow. Working with different infrastructure providers, either public or private using their own concepts and terms, and with a set of heterogeneous applications requires a framework for integrating all the information about these elements. This work proposes semantic technologies for describing and integrating all the information about the different components of the overall system and a set of policies created by the user. Based on this information a scheduling process will be performed to generate an infrastructure configuration defining the set of virtual machines that must be run and the tools that must be deployed on them.

SIMLIDAR Simulation of LiDAR performance in artificially simulate orchards

SIMLIDAR is an application developed in C��þ that generates an artificial orchard using a Lindenmayer system. The application simulates the lateral interaction between the artificial orchard and a laser scanner or LIDAR (Light Detection and Ranging). To best highlight the unique qualities of the LIDAR simulation, this work focuses on apple trees without leaves, i.e. the woody structure. The objective is to simulate a terrestrial laser sensor (LIDAR) when applied to different artificially created orchards and compare the simulated characteristics of trees with the parameters obtained with the LIDAR. The scanner is mounted on a virtual tractor and measures the distance between the origin of the laser beam and the nearby plant object. This measurement is taken with an angular scan in a plane which is perpendicular to the route of the virtual tractor. SIMLIDAR determines the distance measured in a bi-dimensional matrix N M, where N is the number of angular scans and M is the number of steps in the tractor route. In order to test the data and performance of SIMLIDAR, the simulation has been applied to 42 different artificial orchards. After previously defining and calculating two vegetative parameters (wood area and wood projected area) of the simulated trees, a good correlation (R2 ¼ 0.70e0.80) was found between these characteristics and the wood area detected (impacted) by the laser beam. The designed software can be valuable in horticulture for estimating biomass and optimising the pesticide treatments that are performed in winter.

Computational methods to create and analyze a digital gene expression atlas of embryo development from microscopy images

Abstract The creation of atlases, or digital models where information from different subjects can be combined, is a field of increasing interest in biomedical imaging. When a single image does not contain enough information to appropriately describe the organism under study, it is then necessary to acquire images of several individuals, each of them containing complementary data with respect to the rest of the components in the cohort. This approach allows creating digital prototypes, ranging from anatomical atlases of human patients and organs, obtained for instance from Magnetic Resonance Imaging, to gene expression cartographies of embryo development, typically achieved from Light Microscopy. Within such context, in this PhD Thesis we propose, develop and validate new dedicated image processing methodologies that, based on image registration techniques, bring information from multiple individuals into alignment within a single digital atlas model. We also elaborate a dedicated software visualization platform to explore the resulting wealth of multi-dimensional data and novel analysis algo-rithms to automatically mine the generated resource in search of bio¬logical insights. In particular, this work focuses on gene expression data from developing zebrafish embryos imaged at the cellular resolution level with Two-Photon Laser Scanning Microscopy. Disposing of quantitative measurements relating multiple gene expressions to cell position and their evolution in time is a fundamental prerequisite to understand embryogenesis multi-scale processes. However, the number of gene expressions that can be simultaneously stained in one acquisition is limited due to optical and labeling constraints. These limitations motivate the implementation of atlasing strategies that can recreate a virtual gene expression multiplex. The developed computational tools have been tested in two different scenarios. The first one is the early zebrafish embryogenesis where the resulting atlas constitutes a link between the phenotype and the genotype at the cellular level. The second one is the late zebrafish brain where the resulting atlas allows studies relating gene expression to brain regionalization and neurogenesis. The proposed computational frameworks have been adapted to the requirements of both scenarios, such as the integration of partial views of the embryo into a whole embryo model with cellular resolution or the registration of anatom¬ical traits with deformable transformation models non-dependent on any specific labeling. The software implementation of the atlas generation tool (Match-IT) and the visualization platform (Atlas-IT) together with the gene expression atlas resources developed in this Thesis are to be made freely available to the scientific community. Lastly, a novel proof-of-concept experiment integrates for the first time 3D gene expression atlas resources with cell lineages extracted from live embryos, opening up the door to correlate genetic and cellular spatio-temporal dynamics. La creación de atlas, o modelos digitales, donde la información de distintos sujetos puede ser combinada, es un campo de creciente interés en imagen biomédica. Cuando una sola imagen no contiene suficientes datos como para describir apropiadamente el organismo objeto de estudio, se hace necesario adquirir imágenes de varios individuos, cada una de las cuales contiene información complementaria respecto al resto de componentes del grupo. De este modo, es posible crear prototipos digitales, que pueden ir desde atlas anatómicos de órganos y pacientes humanos, adquiridos por ejemplo mediante Resonancia Magnética, hasta cartografías de la expresión genética del desarrollo de embrionario, típicamente adquiridas mediante Microscopía Optica. Dentro de este contexto, en esta Tesis Doctoral se introducen, desarrollan y validan nuevos métodos de procesado de imagen que, basándose en técnicas de registro de imagen, son capaces de alinear imágenes y datos provenientes de múltiples individuos en un solo atlas digital. Además, se ha elaborado una plataforma de visualization espec��ficamente diseñada para explorar la gran cantidad de datos, caracterizados por su multi-dimensionalidad, que resulta de estos métodos. Asimismo, se han propuesto novedosos algoritmos de análisis y minería de datos que permiten inspeccionar automáticamente los atlas generados en busca de conclusiones biológicas significativas. En particular, este trabajo se centra en datos de expresión genética del desarrollo embrionario del pez cebra, adquiridos mediante Microscopía dos fotones con resolución celular. Disponer de medidas cuantitativas que relacionen estas expresiones genéticas con las posiciones celulares y su evolución en el tiempo es un prerrequisito fundamental para comprender los procesos multi-escala característicos de la morfogénesis. Sin embargo, el número de expresiones genéticos que pueden ser simultáneamente etiquetados en una sola adquisición es reducido debido a limitaciones tanto ópticas como del etiquetado. Estas limitaciones requieren la implementación de estrategias de creación de atlas que puedan recrear un multiplexado virtual de expresiones genéticas. Las herramientas computacionales desarrolladas han sido validadas en dos escenarios distintos. El primer escenario es el desarrollo embrionario temprano del pez cebra, donde el atlas resultante permite constituir un vínculo, a nivel celular, entre el fenotipo y el genotipo de este organismo modelo. El segundo escenario corresponde a estadios tardíos del desarrollo del cerebro del pez cebra, donde el atlas resultante permite relacionar expresiones genéticas con la regionalización del cerebro y la formación de neuronas. La plataforma computacional desarrollada ha sido adaptada a los requisitos y retos planteados en ambos escenarios, como la integración, a resolución celular, de vistas parciales dentro de un modelo consistente en un embrión completo, o el alineamiento entre estructuras de referencia anatómica equivalentes, logrado mediante el uso de modelos de transformación deformables que no requieren ningún marcador espec��fico. Está previsto poner a disposición de la comunidad científica tanto la herramienta de generación de atlas (Match-IT), como su plataforma de visualización (Atlas-IT), así como las bases de datos de expresión genética creadas a partir de estas herramientas. Por último, dentro de la presente Tesis Doctoral, se ha incluido una prueba conceptual innovadora que permite integrar los mencionados atlas de expresión genética tridimensionales dentro del linaje celular extraído de una adquisición in vivo de un embrión. Esta prueba conceptual abre la puerta a la posibilidad de correlar, por primera vez, las dinámicas espacio-temporales de genes y c��lulas.

Container Terminal Simulation. A case study: port of Valencia.

This paper is concerned with the study of non-Markovian queuing systems in container terminals. The methodology presented has been applied to analyze the ship traffic in the port of Valencia located in the Western Mediterranean. Two container terminals have been studied: the public container terminal of NOATUM and the dedicated container terminal of MSC. This paper contains the results of a simulation model based on queuing theory. The methodology presented is found to be effective in replicating realistic ship traffic operations in port as well as in conducting capacity evaluations. Thus the methodology can be used for capacity planning (long term), tactical planning (medium term) and even for the container terminal design (port enlargement purposes).

Simulation of oil productivity and quality of N-S oriented olive hedgerow orchards in response to structure and interception of radiation

Simulations of oil yield and quality are presented for N–S oriented, hedgerow olive orchards of a range of structures (viz. canopy depth, canopy width, canopy slope and row spacing) using responses of yield and quality parameters to solar irradiance on canopy walls measured in a range of orchards, cv. Arbequina, in Spain. Results reveal that orchard yield of hedgerows of rectangular shape reaches a maximum when canopy depth equals alley width (row spacing−canopy width) and decreases at wider spacing, and/or with wider canopies, as the length of productive row decreases per unit area. Maximum yields for 4-m deep canopies were 2885 kg ha−1 at 1-m width and 5-m row spacing, 2400 kg ha−1 at 2-m width and 6-m spacing, and 2050 kg ha−1 at 3-m width and 7-m spacing. Illumination of canopies can be increased by applying slopes to form rhomboidal hedgerows. Substantial yield advantage can be achieved, especially for wide hedgerows, partly by closer row spacing that increases row length per unit area. By comparison, responses to latitude in the range 30–40◦ are small and do not warrant different row spacing. Oil quality parameters also respond to orchard structure. Responses are presented for oleic and palmitic acid, stability, and maturity index. Oleic acid content declines as alley spacing increases and is smaller, shallow than in wide, deep canopies. Palmitic acid content, stability, and maturity index increase with row alley spacing and are greater in narrow, shallow than in wide, deep canopies.

An approach to automatic learning assessment based on the computational theory of perceptions

E-learning systems output a huge quantity of data on a learning process. However, it takes a lot of specialist human resources to manually process these data and generate an assessment report. Additionally, for formative assessment, the report should state the attainment level of the learning goals defined by the instructor. This paper describes the use of the granular linguistic model of a phenomenon (GLMP) to model the assessment of the learning process and implement the automated generation of an assessment report. GLMP is based on fuzzy logic and the computational theory of perceptions. This technique is useful for implementing complex assessment criteria using inference systems based on linguistic rules. Apart from the grade, the model also generates a detailed natural language progress report on the achieved proficiency level, based exclusively on the objective data gathered from correct and incorrect responses. This is illustrated by applying the model to the assessment of Dijkstra’s algorithm learning using a visual simulation-based graph algorithm learning environment, called GRAPHs

Computational Fluid Dynamics Expert System using Artificial Neural Networks

The design of a modern aircraft is based on three pillars: theoretical results, experimental test and computational simulations. As a results of this, Computational Fluid Dynamic (CFD) solvers are widely used in the aeronautical field. These solvers require the correct selection of many parameters in order to obtain successful results. Besides, the computational time spent in the simulation depends on the proper choice of these parameters. In this paper we create an expert system capable of making an accurate prediction of the number of iterations and time required for the convergence of a computational fluid dynamic (CFD) solver. Artificial neural network (ANN) has been used to design the expert system. It is shown that the developed expert system is capable of making an accurate prediction the number of iterations and time required for the convergence of a CFD solver.

Simulation of wind farms in flat and complex terrain using CFD

Use of computational fluid dynamic (CFD) methods to predict the power production from wind entire wind farms in flat and complex terrain is presented in this paper. Two full 3D Navier–Stokes solvers for incompressible flow are employed that incorporate the k–ε and k–ω turbulence models respectively. The wind turbines (W/Ts) are modelled as momentum absorbers by means of their thrust coefficient using the actuator disk approach. The WT thrust is estimated using the wind speed one diameter upstream of the rotor at hub height. An alternative method that employs an induction-factor based concept is also tested. This method features the advantage of not utilizing the wind speed at a specific distance from the rotor disk, which is a doubtful approximation when a W/T is located in the wake of another and/or the terrain is complex. To account for the underestimation of the near wake deficit, a correction is introduced to the turbulence model. The turbulence time scale is bounded using the general “realizability” constraint for the turbulent velocities. Application is made on two wind farms, a five-machine one located in flat terrain and another 43-machine one located in complex terrain. In the flat terrain case, the combination of the induction factor method along with the turbulence correction provides satisfactory results. In the complex terrain case, there are some significant discrepancies with the measurements, which are discussed. In this case, the induction factor method does not provide satisfactory results.

Quantifying Reproducibility in Computational Biology: The Case of the Tuberculosis Drugome

How easy is it to reproduce the results found in a typical computational biology paper? Either through experience or intuition the reader will already know that the answer is with difficulty or not at all. In this paper we attempt to quantify this difficulty by reproducing a previously published paper for different classes of users (ranging from users with little expertise to domain experts) and suggest ways in which the situation might be improved. Quantification is achieved by estimating the time required to reproduce each of the steps in the method described in the original paper and make them part of an explicit workflow that reproduces the original results. Reproducing the method took several months of effort, and required using new versions and new software that posed challenges to reconstructing and validating the results. The quantification leads to “reproducibility maps” that reveal that novice researchers would only be able to reproduce a few of the steps in the method, and that only expert researchers with advance knowledge of the domain would be able to reproduce the method in its entirety. The workflow itself is published as an online resource together with supporting software and data. The paper concludes with a brief discussion of the complexities of requiring reproducibility in terms of cost versus benefit, and a desiderata with our observations and guidelines for improving reproducibility. This has implications not only in reproducing the work of others from published papers, but reproducing work from one’s own laboratory.

Numerical methods for option pricing.

This thesis aims to introduce some fundamental concepts underlying option valuation theory including implementation of computational tools. In many cases analytical solution for option pricing does not exist, thus the following numerical methods are used: binomial trees, Monte Carlo simulations and finite difference methods. First, an algorithm based on Hull and Wilmott is written for every method. Then these algorithms are improved in different ways. For the binomial tree both speed and memory usage is significantly improved by using only one vector instead of a whole price storing matrix. Computational time in Monte Carlo simulations is reduced by implementing a parallel algorithm (in C) which is capable of improving speed by a factor which equals the number of processors used. Furthermore, MatLab code for Monte Carlo was made faster by vectorizing simulation process. Finally, obtained option values are compared to those obtained with popular finite difference methods, and it is discussed which of the algorithms is more appropriate for which purpose.

A stochastic model updating method for parameter variability quantification based on response surface models and Monte Carlo simulation

Stochastic model updating must be considered for quantifying uncertainties inherently existing in real-world engineering structures. By this means the statistical properties,instead of deterministic values, of structural parameters can be sought indicating the parameter variability. However, the implementation of stochastic model updating is much more complicated than that of deterministic methods particularly in the aspects of theoretical complexity and low computational efficiency. This study attempts to propose a simple and cost-efficient method by decomposing a stochastic updating process into a series of deterministic ones with the aid of response surface models and Monte Carlo simulation. The response surface models are used as surrogates for original FE models in the interest of programming simplification, fast response computation and easy inverse optimization. Monte Carlo simulation is adopted for generating samples from the assumed or measured probability distributions of responses. Each sample corresponds to an individual deterministic inverse process predicting the deterministic values of parameters. Then the parameter means and variances can be statistically estimated based on all the parameter predictions by running all the samples. Meanwhile, the analysis of variance approach is employed for the evaluation of parameter variability significance. The proposed method has been demonstrated firstly on a numerical beam and then a set of nominally identical steel plates tested in the laboratory. It is found that compared with the existing stochastic model updating methods, the proposed method presents similar accuracy while its primary merits consist in its simple implementation and cost efficiency in response computation and inverse optimization.

Simulation of impulse response for indoor visible light communications using 3D CAD models

n this article, a tool for simulating the channel impulse response for indoor visible light communications using 3D computer-aided design (CAD) models is presented. The simulation tool is based on a previous Monte Carlo ray-tracing algorithm for indoor infrared channel estimation, but including wavelength response evaluation. The 3D scene, or the simulation environment, can be defined using any CAD software in which the user specifies, in addition to the setting geometry, the reflection characteristics of the surface materials as well as the structures of the emitters and receivers involved in the simulation. Also, in an effort to improve the computational efficiency, two optimizations are proposed. The first one consists of dividing the setting into cubic regions of equal size, which offers a calculation improvement of approximately 50% compared to not dividing the 3D scene into sub-regions. The second one involves the parallelization of the simulation algorithm, which provides a computational speed-up proportional to the number of processors used.

Computational Study of the Fe(CN)(2)CO Cofactor and Its Binding to HypC Protein.

In the intricate maturation process of [NiFe]-hydrogenases, the Fe(CN)2CO cofactor is first assembled in a HypCD complex with iron coordinated by cysteines from both proteins and CO is added after ligation of cyanides. The small accessory protein HypC is known to play a role in delivering the cofactor needed for assembling the hydrogenase active site. However, the chemical nature of the Fe(CN)2CO moiety and the stability of the cofactor–HypC complex are open questions. In this work, we address geometries, properties, and the nature of bonding of all chemical species involved in formation and binding of the cofactor by means of quantum calculations. We also study the influence of environmental effects and binding to cysteines on vibrational frequencies of stretching modes of CO and CN used to detect the presence of Fe(CN)2CO. Carbon monoxide is found to be much more sensitive to sulfur binding and the polarity of the medium than cyanides. The stability of the HypC���cofactor complex is analyzed by means of molecular dynamics simulation of cofactor-free and cofactor-bound forms of HypC. The results show that HypC is stable enough to carry the cofactor, but since its binding cysteine is located at the N-terminal unstructured tail, it presents large motions in solution, which suggests the need for a guiding interaction to achieve delivery of the cofactor.

Finite element simulation of sandwich panels of laminated plaster and rockwool under mixed mode fracture

Sandwich panels of laminated gypsum and rock wool have shown large pathology of cracking due to excessive slabs deflection. Currently the most widespread use of this material is as vertical elements of division or partition, with no structural function, what justifies that there are no studies on the mechanism of fracture and mechanical properties related to it. Therefore, and in order to reduce the cracking problem, it is necessary to progress in the simulation and prediction of the behaviour under tensile and shear load of such panels, although in typical applications have no structural responsability.

A Semantic-Based Approach to Attain Reproducibility of Computational Environments in Scientic Work ows: A Case Study

Reproducible research in scientic work ows is often addressed by tracking the provenance of the produced results. While this approach allows inspecting intermediate and nal results, improves understanding, and permits replaying a work ow execution, it does not ensure that the computational environment is available for subsequent executions to reproduce the experiment. In this work, we propose describing the resources involved in the execution of an experiment using a set of semantic vocabularies, so as to conserve the computational environment. We dene a process for documenting the work ow application, management system, and their dependencies based on 4 domain ontologies. We then conduct an experimental evaluation sing a real work ow application on an academic and a public Cloud platform. Results show that our approach can reproduce an equivalent execution environment of a predened virtual machine image on both computing platforms.