An efficient, approximate path-following algorithm for elastic net based nonlinear spike enhancement

Unwanted spike noise in a digital signal is a common problem in digital filtering. However, sometimes the spikes are wanted and other, superimposed, signals are unwanted, and linear, time invariant (LTI) filtering is ineffective because the spikes are wideband - overlapping with independent noise in the frequency domain. So, no LTI filter can separate them, necessitating nonlinear filtering. However, there are applications in which the noise includes drift or smooth signals for which LTI filters are ideal. We describe a nonlinear filter formulated as the solution to an elastic net regularization problem, which attenuates band-limited signals and independent noise, while enhancing superimposed spikes. Making use of known analytic solutions a novel, approximate path-following algorithm is given that provides a good, filtered output with reduced computational effort by comparison to standard convex optimization methods. Accurate performance is shown on real, noisy electrophysiological recordings of neural spikes.

A New Method for Modeling Free Surface Flows and Fluid-structure Interaction with Ocean Applications

The computational modeling of ocean waves and ocean-faring devices poses numerous challenges. Among these are the need to stably and accurately represent both the fluid-fluid interface between water and air as well as the fluid-structure interfaces arising between solid devices and one or more fluids. As techniques are developed to stably and accurately balance the interactions between fluid and structural solvers at these boundaries, a similarly pressing challenge is the development of algorithms that are massively scalable and capable of performing large-scale three-dimensional simulations on reasonable time scales. This dissertation introduces two separate methods for approaching this problem, with the first focusing on the development of sophisticated fluid-fluid interface representations and the second focusing primarily on scalability and extensibility to higher-order methods.

We begin by introducing the narrow-band gradient-augmented level set method (GALSM) for incompressible multiphase Navier-Stokes flow. This is the first use of the high-order GALSM for a fluid flow application, and its reliability and accuracy in modeling ocean environments is tested extensively. The method demonstrates numerous advantages over the traditional level set method, among these a heightened conservation of fluid volume and the representation of subgrid structures.

Next, we present a finite-volume algorithm for solving the incompressible Euler equations in two and three dimensions in the presence of a flow-driven free surface and a dynamic rigid body. In this development, the chief concerns are efficiency, scalability, and extensibility (to higher-order and truly conservative methods). These priorities informed a number of important choices: The air phase is substituted by a pressure boundary condition in order to greatly reduce the size of the computational domain, a cut-cell finite-volume approach is chosen in order to minimize fluid volume loss and open the door to higher-order methods, and adaptive mesh refinement (AMR) is employed to focus computational effort and make large-scale 3D simulations possible. This algorithm is shown to produce robust and accurate results that are well-suited for the study of ocean waves and the development of wave energy conversion (WEC) devices.

Directional genetic differentiation and relative migration

Understanding the population structure and patterns of gene flow within species is of fundamental importance to the study of evolution. In the fields of population and evolutionary genetics, measures of genetic differentiation are commonly used to gather this information. One potential caveat is that these measures assume gene flow to be symmetric. However, asymmetric gene flow is common in nature, especially in systems driven by physical processes such as wind or water currents. As information about levels of asymmetric gene flow among populations is essential for the correct interpretation of the distribution of contemporary genetic diversity within species, this should not be overlooked. To obtain information on asymmetric migration patterns from genetic data, complex models based on maximum-likelihood or Bayesian approaches generally need to be employed, often at great computational cost. Here, a new simpler and more efficient approach for understanding gene flow patterns is presented. This approach allows the estimation of directional components of genetic divergence between pairs of populations at low computational effort, using any of the classical or modern measures of genetic differentiation. These directional measures of genetic differentiation can further be used to calculate directional relative migration and to detect asymmetries in gene flow patterns. This can be done in a user-friendly web application called divMigrate-online introduced in this study. Using simulated data sets with known gene flow regimes, we demonstrate that the method is capable of resolving complex migration patterns under a range of study designs.

An efficient parallel MoM to analyze microstrip structures

[EN]The increasing use of microstrip technology require more accurate analysis methods like full wave method of moments. However, this involves a great computational effort. To reduce the computation time, an alternative parallel method to analyze irregular microstrip structures is presented in this paper. This method calculates the unknown surface current on the planar structure trough a irregular rectangular division using basis and weighted functions. The parallel algorithm performs the calculus of a [Z] matrix and then solves the system using current densities as the unknowns. This parallel program was implemented in the IBM-SP2 using MPI library.

Exergetic, energetic, economic and environmental evaluation of concentrated solar power plants in Libya

The PhD project addresses the potential of using concentrating solar power (CSP) plants as a viable alternative energy producing system in Libya. Exergetic, energetic, economic and environmental analyses are carried out for a particular type of CSP plants. The study, although it aims a particular type of CSP plant – 50 MW parabolic trough-CSP plant, it is sufficiently general to be applied to other configurations. The novelty of the study, in addition to modeling and analyzing the selected configuration, lies in the use of a state-of-the-art exergetic analysis combined with the Life Cycle Assessment (LCA). The modeling and simulation of the plant is carried out in chapter three and they are conducted into two parts, namely: power cycle and solar field. The computer model developed for the analysis of the plant is based on algebraic equations describing the power cycle and the solar field. The model was solved using the Engineering Equation Solver (EES) software; and is designed to define the properties at each state point of the plant and then, sequentially, to determine energy, efficiency and irreversibility for each component. The developed model has the potential of using in the preliminary design of CSPs and, in particular, for the configuration of the solar field based on existing commercial plants. Moreover, it has the ability of analyzing the energetic, economic and environmental feasibility of using CSPs in different regions of the world, which is illustrated for the Libyan region in this study. The overall feasibility scenario is completed through an hourly analysis on an annual basis in chapter Four. This analysis allows the comparison of different systems and, eventually, a particular selection, and it includes both the economic and energetic components using the “greenius” software. The analysis also examined the impact of project financing and incentives on the cost of energy. The main technological finding of this analysis is higher performance and lower levelized cost of electricity (LCE) for Libya as compared to Southern Europe (Spain). Therefore, Libya has the potential of becoming attractive for the establishment of CSPs in its territory and, in this way, to facilitate the target of several European initiatives that aim to import electricity generated by renewable sources from North African and Middle East countries. The analysis is presented a brief review of the current cost of energy and the potential of reducing the cost from parabolic trough- CSP plant. Exergetic and environmental life cycle assessment analyses are conducted for the selected plant in chapter Five; the objectives are 1) to assess the environmental impact and cost, in terms of exergy of the life cycle of the plant; 2) to find out the points of weakness in terms of irreversibility of the process; and 3) to verify whether solar power plants can reduce environmental impact and the cost of electricity generation by comparing them with fossil fuel plants, in particular, Natural Gas Combined Cycle (NGCC) plant and oil thermal power plant. The analysis also targets a thermoeconomic analysis using the specific exergy costing (SPECO) method to evaluate the level of the cost caused by exergy destruction. The main technological findings are that the most important contribution impact lies with the solar field, which reports a value of 79%; and the materials with the vi highest impact are: steel (47%), molten salt (25%) and synthetic oil (21%). The “Human Health” damage category presents the highest impact (69%) followed by the “Resource” damage category (24%). In addition, the highest exergy demand is linked to the steel (47%); and there is a considerable exergetic demand related to the molten salt and synthetic oil with values of 25% and 19%, respectively. Finally, in the comparison with fossil fuel power plants (NGCC and Oil), the CSP plant presents the lowest environmental impact, while the worst environmental performance is reported to the oil power plant followed by NGCC plant. The solar field presents the largest value of cost rate, where the boiler is a component with the highest cost rate among the power cycle components. The thermal storage allows the CSP plants to overcome solar irradiation transients, to respond to electricity demand independent of weather conditions, and to extend electricity production beyond the availability of daylight. Numerical analysis of the thermal transient response of a thermocline storage tank is carried out for the charging phase. The system of equations describing the numerical model is solved by using time-implicit and space-backward finite differences and which encoded within the Matlab environment. The analysis presented the following findings: the predictions agree well with the experiments for the time evolution of the thermocline region, particularly for the regions away from the top-inlet. The deviations observed in the near-region of the inlet are most likely due to the high-level of turbulence in this region due to the localized level of mixing resulting; a simple analytical model to take into consideration this increased turbulence level was developed and it leads to some improvement of the predictions; this approach requires practically no additional computational effort and it relates the effective thermal diffusivity to the mean effective velocity of the fluid at each particular height of the system. Altogether the study indicates that the selected parabolic trough-CSP plant has the edge over alternative competing technologies for locations where DNI is high and where land usage is not an issue, such as the shoreline of Libya.

Digital nonlinear equalization for optical transmission systems

This thesis focuses on digital equalization of nonlinear fiber impairments for coherent optical transmission systems. Building from well-known physical models of signal propagation in single-mode optical fibers, novel nonlinear equalization techniques are proposed, numerically assessed and experimentally demonstrated. The structure of the proposed algorithms is strongly driven by the optimization of the performance versus complexity tradeoff, envisioning the near-future practical application in commercial real-time transceivers. The work is initially focused on the mitigation of intra-channel nonlinear impairments relying on the concept of digital backpropagation (DBP) associated with Volterra-based filtering. After a comprehensive analysis of the third-order Volterra kernel, a set of critical simplifications are identified, culminating in the development of reduced complexity nonlinear equalization algorithms formulated both in time and frequency domains. The implementation complexity of the proposed techniques is analytically described in terms of computational effort and processing latency, by determining the number of real multiplications per processed sample and the number of serial multiplications, respectively. The equalization performance is numerically and experimentally assessed through bit error rate (BER) measurements. Finally, the problem of inter-channel nonlinear compensation is addressed within the context of 400 Gb/s (400G) superchannels for long-haul and ultra-long-haul transmission. Different superchannel configurations and nonlinear equalization strategies are experimentally assessed, demonstrating that inter-subcarrier nonlinear equalization can provide an enhanced signal reach while requiring only marginal added complexity.

Noise Reduction Technique for a Simulation Optimisation Study

This paper reports on an attempt to apply Genetic Algorithms to the problem of optimising a complex system, through discrete event simulation (Simulation Optimisation), with a view to reducing the noise associated with such a procedure. We are applying this proposed solution approach to our application test bed, a Crossdocking distribution centre, because it provides a good representative of the random and unpredictable behaviour of complex systems i.e. automated machine random failure and the variability of manual order picker skill. It is known that there is noise in the output of discrete event simulation modelling. However, our interest focuses on the effect of noise on the evaluation of the fitness of candidate solutions within the search space, and the development of techniques to handle this noise. The unique quality of our proposed solution approach is we intend to embed a noise reduction technique in our Genetic Algorithm based optimisation procedure, in order for it to be robust enough to handle noise, efficiently estimate suitable fitness function, and produce good quality solutions with minimal computational effort.

Estudo de modelos simplificados com interações de longo alcance no ensemble microcanônico

Tese (doutorado)Universidade de Brasília, Instituto de Física, Programa de Pós-Graduação em Física, 2015.

Tabu search for the cyclic bandwidth problem

International audience

RISK-BASED MULTIOBJECTIVE PATH PLANNING AND DESIGN OPTIMIZATION FOR UNMANNED AERIAL VEHICLES

Safe operation of unmanned aerial vehicles (UAVs) over populated areas requires reducing the risk posed by a UAV if it crashed during its operation. We considered several types of UAV risk-based path planning problems and developed techniques for estimating the risk to third parties on the ground. The path planning problem requires making trade-offs between risk and flight time. Four optimization approaches for solving the problem were tested; a network-based approach that used a greedy algorithm to improve the original solution generated the best solutions with the least computational effort. Additionally, an approach for solving a combined design and path planning problems was developed and tested. This approach was extended to solve robust risk-based path planning problem in which uncertainty about wind conditions would affect the risk posed by a UAV.

Visualization of flow fields in the web platform

Visualization of vector fields plays an important role in research activities nowadays -- Web applications allow a fast, multi-platform and multi-device access to data, which results in the need of optimized applications to be implemented in both high-performance and low-performance devices -- Point trajectory calculation procedures usually perform repeated calculations due to the fact that several points might lie over the same trajectory -- This paper presents a new methodology to calculate point trajectories over highly-dense and uniformly-distributed grid of points in which the trajectories are forced to lie over the points in the grid -- Its advantages rely on a highly parallel computing architecture implementation and in the reduction of the computational effort to calculate the stream paths since unnecessary calculations are avoided, reusing data through iterations -- As case study, the visualization of oceanic currents through in the web platform is presented and analyzed, using WebGL as the parallel computing architecture and the rendering Application Programming Interface

Simple approximate MAP inference for Dirichlet processes mixtures

The Dirichlet process mixture model (DPMM) is a ubiquitous, flexible Bayesian nonparametric statistical model. However, full probabilistic inference in this model is analytically intractable, so that computationally intensive techniques such as Gibbs sampling are required. As a result, DPMM-based methods, which have considerable potential, are restricted to applications in which computational resources and time for inference is plentiful. For example, they would not be practical for digital signal processing on embedded hardware, where computational resources are at a serious premium. Here, we develop a simplified yet statistically rigorous approximate maximum a-posteriori (MAP) inference algorithm for DPMMs. This algorithm is as simple as DP-means clustering, solves the MAP problem as well as Gibbs sampling, while requiring only a fraction of the computational effort. (For freely available code that implements the MAP-DP algorithm for Gaussian mixtures see http://www.maxlittle.net/.) Unlike related small variance asymptotics (SVA), our method is non-degenerate and so inherits the “rich get richer” property of the Dirichlet process. It also retains a non-degenerate closed-form likelihood which enables out-of-sample calculations and the use of standard tools such as cross-validation. We illustrate the benefits of our algorithm on a range of examples and contrast it to variational, SVA and sampling approaches from both a computational complexity perspective as well as in terms of clustering performance. We demonstrate the wide applicabiity of our approach by presenting an approximate MAP inference method for the infinite hidden Markov model whose performance contrasts favorably with a recently proposed hybrid SVA approach. Similarly, we show how our algorithm can applied to a semiparametric mixed-effects regression model where the random effects distribution is modelled using an infinite mixture model, as used in longitudinal progression modelling in population health science. Finally, we propose directions for future research on approximate MAP inference in Bayesian nonparametrics.

A Trans-dimensional inversion algorithm to model deformation sources with unconstrained shape in finite element domains

Ground deformation provides valuable insights on subsurface processes with pattens reflecting the characteristics of the source at depth. In active volcanic sites displacements can be observed in unrest phases; therefore, a correct interpretation is essential to assess the hazard potential. Inverse modeling is employed to obtain quantitative estimates of parameters describing the source. However, despite the robustness of the available approaches, a realistic imaging of these reservoirs is still challenging. While analytical models return quick but simplistic results, assuming an isotropic and elastic crust, more sophisticated numerical models, accounting for the effects of topographic loads, crust inelasticity and structural discontinuities, require much higher computational effort and information about the crust rheology may be challenging to infer. All these approaches are based on a-priori source shape constraints, influencing the solution reliability. In this thesis, we present a new approach aimed at overcoming the aforementioned limitations, modeling sources free of a-priori shape constraints with the advantages of FEM simulations, but with a cost-efficient procedure. The source is represented as an assembly of elementary units, consisting in cubic elements of a regular FE mesh loaded with a unitary stress tensors. The surface response due to each of the six stress tensor components is computed and linearly combined to obtain the total displacement field. In this way, the source can assume potentially any shape. Our tests prove the equivalence of the deformation fields due to our assembly and that of corresponding cavities with uniform boundary pressure. Our ability to simulate pressurized cavities in a continuum domain permits to pre-compute surface responses, avoiding remeshing. A Bayesian trans-dimensional inversion algorithm implementing this strategy is developed. 3D Voronoi cells are used to sample the model domain, selecting the elementary units contributing to the source solution and those remaining inactive as part of the crust.

Numerical prediction of the lateral displacement capacity of flexural reinforced concrete shear walls

Previous earthquakes showed that shear wall damage could lead to catastrophic failures of the reinforced concrete building. The lateral load capacity of shear walls needs to be estimated to minimize associated losses during catastrophic events; hence it is necessary to develop and validate reliable and stable numerical methods able to converge to reasonable estimations with minimum computational effort. The beam-column 1-D line element with fiber-type cross-section model is a practical option that yields results in agreement with experimental data. However, shortcomings of using this model to predict the local damage response may come from the fact that the model requires fine calibration of material properties to overcome regularization and size effects. To reduce the mesh-dependency of the numerical model, a regularization method based on the concept of post-yield energy is applied in this work to both the concrete and the steel material constitutive laws to predict the nonlinear cyclic response and failure mechanism of concrete shear walls. Different categories of wall specimens known to produce a different response under in plane cyclic loading for their varied geometric and detailing characteristics are considered in this study, namely: 1) scaled wall specimens designed according to the European seismic design code and 2) unique full-scale wall specimens detailed according to the U.S. design code to develop a ductile behavior under cyclic loading. To test the boundaries of application of the proposed method, two full-scale walls with a mixed shear-flexure response and different values of applied axial load are also considered. The results of this study show that the use of regularized constitutive models considerably enhances the response predictions capabilities of the model with regards to global force-drift response and failure mode. The simulations presented in this thesis demonstrate the proposed model to be a valuable tool for researchers and engineers.

Methods for construction and analysis of computational models in systems biology : applications to the modelling of the heat shock response and the self-assembly of intermediate filaments

Systems biology is a new, emerging and rapidly developing, multidisciplinary research field that aims to study biochemical and biological systems from a holistic perspective, with the goal of providing a comprehensive, system- level understanding of cellular behaviour. In this way, it addresses one of the greatest challenges faced by contemporary biology, which is to compre- hend the function of complex biological systems. Systems biology combines various methods that originate from scientific disciplines such as molecu- lar biology, chemistry, engineering sciences, mathematics, computer science and systems theory. Systems biology, unlike “traditional” biology, focuses on high-level concepts such as: network, component, robustness, efficiency, control, regulation, hierarchical design, synchronization, concurrency, and many others. The very terminology of systems biology is “foreign” to “tra- ditional” biology, marks its drastic shift in the research paradigm and it indicates close linkage of systems biology to computer science. One of the basic tools utilized in systems biology is the mathematical modelling of life processes tightly linked to experimental practice. The stud- ies contained in this thesis revolve around a number of challenges commonly encountered in the computational modelling in systems biology. The re- search comprises of the development and application of a broad range of methods originating in the fields of computer science and mathematics for construction and analysis of computational models in systems biology. In particular, the performed research is setup in the context of two biolog- ical phenomena chosen as modelling case studies: 1) the eukaryotic heat shock response and 2) the in vitro self-assembly of intermediate filaments, one of the main constituents of the cytoskeleton. The range of presented approaches spans from heuristic, through numerical and statistical to ana- lytical methods applied in the effort to formally describe and analyse the two biological processes. We notice however, that although applied to cer- tain case studies, the presented methods are not limited to them and can be utilized in the analysis of other biological mechanisms as well as com- plex systems in general. The full range of developed and applied modelling techniques as well as model analysis methodologies constitutes a rich mod- elling framework. Moreover, the presentation of the developed methods, their application to the two case studies and the discussions concerning their potentials and limitations point to the difficulties and challenges one encounters in computational modelling of biological systems. The problems of model identifiability, model comparison, model refinement, model inte- gration and extension, choice of the proper modelling framework and level of abstraction, or the choice of the proper scope of the model run through this thesis.