Improvements in the score matrix calculation method using parallel score estimating algorithm

The increasing amount of sequences stored in genomic databases has become unfeasible to the sequential analysis. Then, the parallel computing brought its power to the Bioinformatics through parallel algorithms to align and analyze the sequences, providing improvements mainly in the running time of these algorithms. In many situations, the parallel strategy contributes to reducing the computational complexity of the big problems. This work shows some results obtained by an implementation of a parallel score estimating technique for the score matrix calculation stage, which is the first stage of a progressive multiple sequence alignment. The performance and quality of the parallel score estimating are compared with the results of a dynamic programming approach also implemented in parallel. This comparison shows a significant reduction of running time. Moreover, the quality of the final alignment, using the new strategy, is analyzed and compared with the quality of the approach with dynamic programming.

Routing Algorithms for All-Optical Networks with Power Considerations: The Unicast Case

In this paper, we investigate the problem of routing connections in all-optical networks while allowing for degradation of routed signals by different optical components. To overcome the complexity of the problem, we divide it into two parts. First, we solve the pure RWA problem using fixed routes for every connection. Second, power assignment is accomplished by either using the smallest-gain first (SGF) heuristic or using a genetic algorithm. Numerical examples on a wide variety of networks show that (a) the number of connections established without considering the signal attenuation was most of the time greater than that achievable considering attenuation and (b) the genetic solution quality was much better than that of SGF, especially when the conflict graph of the connections generated by the linear solver is denser.

Collaborative fuzzy clustering algorithms: some refinements and design guidelines

There are some variants of the widely used Fuzzy C-Means (FCM) algorithm that support clustering data distributed across different sites. Those methods have been studied under different names, like collaborative and parallel fuzzy clustering. In this study, we offer some augmentation of the two FCM-based clustering algorithms used to cluster distributed data by arriving at some constructive ways of determining essential parameters of the algorithms (including the number of clusters) and forming a set of systematically structured guidelines such as a selection of the specific algorithm depending on the nature of the data environment and the assumptions being made about the number of clusters. A thorough complexity analysis, including space, time, and communication aspects, is reported. A series of detailed numeric experiments is used to illustrate the main ideas discussed in the study.

The dual pathway in action: decoupling parallel routes for CO2 production during the oscillatory electro-oxidation of methanol

As in the case of most small organic molecules, the electro-oxidation of methanol to CO2 is believed to proceed through a so-called dual pathway mechanism. The direct pathway proceeds via reactive intermediates such as formaldehyde or formic acid, whereas the indirect pathway occurs in parallel, and proceeds via the formation of adsorbed carbon monoxide (COad). Despite the extensive literature on the electro-oxidation of methanol, no study to date distinguished the production of CO2 from direct and indirect pathways. Working under, far-from-equilibrium, oscillatory conditions, we were able to decouple, for the first time, the direct and indirect pathways that lead to CO2 during the oscillatory electro-oxidation of methanol on platinum. The CO2 production was followed by differential electrochemical mass spectrometry and the individual contributions of parallel pathways were identified by a combination of experiments and numerical simulations. We believe that our report opens some perspectives, particularly as a methodology to be used to identify the role played by surface modifiers in the relative weight of both pathways-a key issue to the effective development of catalysts for low temperature fuel cells.

Parallel implementation of a robust optical flow technique

[EN] The accuracy and performance of current variational optical ow methods have considerably increased during the last years. The complexity of these techniques is high and enough care has to be taken for the implementation. The aim of this work is to present a comprehensible implementation of recent variational optical flow methods. We start with an energy model that relies on brightness and gradient constancy terms and a ow-based smoothness term. We minimize this energy model and derive an e cient implicit numerical scheme. In the experimental results, we evaluate the accuracy and performance of this implementation with the Middlebury benchmark database. We show that it is a competitive solution with respect to current methods in the literature. In order to increase the performance, we use a simple strategy to parallelize the execution on multi-core processors.

Topological analysis of singularity loci for serial and parallel manipulators

Singularities of robot manipulators have been intensely studied in the last decades by researchers of many fields. Serial singularities produce some local loss of dexterity of the manipulator, therefore it might be desirable to search for singularityfree trajectories in the jointspace. On the other hand, parallel singularities are very dangerous for parallel manipulators, for they may provoke the local loss of platform control, and jeopardize the structural integrity of links or actuators. It is therefore utterly important to avoid parallel singularities, while operating a parallel machine. Furthermore, there might be some configurations of a parallel manipulators that are allowed by the constraints, but nevertheless are unreachable by any feasible path. The present work proposes a numerical procedure based upon Morse theory, an important branch of differential topology. Such procedure counts and identify the singularity-free regions that are cut by the singularity locus out of the configuration space, and the disjoint regions composing the configuration space of a parallel manipulator. Moreover, given any two configurations of a manipulator, a feasible or a singularity-free path connecting them can always be found, or it can be proved that none exists. Examples of applications to 3R and 6R serial manipulators, to 3UPS and 3UPU parallel wrists, to 3UPU parallel translational manipulators, and to 3RRR planar manipulators are reported in the work.

Application of evolutionary algorithms and the boundary element method in the optimization of noise barrier profiles

[EN]This Ph.D. thesis presents a general, robust methodology that may cover any type of 2D acoustic optimization problem. A procedure involving the coupling of Boundary Elements (BE) and Evolutionary Algorithms is proposed for systematic geometric modifications of road barriers that lead to designs with ever-increasing screening performance. Numerical simulations involving single- and multi-objective optimizations of noise barriers of varied nature are included in this document. results disclosed justify the implementation of this methodology by leading to optimal solutions of previously defined topologies that, in general, greatly outperform the acoustic efficiency of classical, widely used barrier designs normally erected near roads.

Numerical simulation of ion transport through ion channels and solid-state nanopores

Ion channels are pore-forming proteins that regulate the flow of ions across biological cell membranes. Ion channels are fundamental in generating and regulating the electrical activity of cells in the nervous system and the contraction of muscolar cells. Solid-state nanopores are nanometer-scale pores located in electrically insulating membranes. They can be adopted as detectors of specific molecules in electrolytic solutions. Permeation of ions from one electrolytic solution to another, through a protein channel or a synthetic pore is a process of considerable importance and realistic analysis of the main dependencies of ion current on the geometrical and compositional characteristics of these structures are highly required. The project described by this thesis is an effort to improve the understanding of ion channels by devising methods for computer simulation that can predict channel conductance from channel structure. This project describes theory, algorithms and implementation techniques used to develop a novel 3-D numerical simulator of ion channels and synthetic nanopores based on the Brownian Dynamics technique. This numerical simulator could represent a valid tool for the study of protein ion channel and synthetic nanopores, allowing to investigate at the atomic-level the complex electrostatic interactions that determine channel conductance and ion selectivity. Moreover it will provide insights on how parameters like temperature, applied voltage, and pore shape could influence ion translocation dynamics. Furthermore it will help making predictions of conductance of given channel structures and it will add information like electrostatic potential or ionic concentrations throughout the simulation domain helping the understanding of ion flow through membrane pores.

Parallel modeling of the electric field distribution in the brain

The term "Brain Imaging" identi�es a set of techniques to analyze the structure and/or functional behavior of the brain in normal and/or pathological situations. These techniques are largely used in the study of brain activity. In addition to clinical usage, analysis of brain activity is gaining popularity in others recent �fields, i.e. Brain Computer Interfaces (BCI) and the study of cognitive processes. In this context, usage of classical solutions (e.g. f MRI, PET-CT) could be unfeasible, due to their low temporal resolution, high cost and limited portability. For these reasons alternative low cost techniques are object of research, typically based on simple recording hardware and on intensive data elaboration process. Typical examples are ElectroEncephaloGraphy (EEG) and Electrical Impedance Tomography (EIT), where electric potential at the patient's scalp is recorded by high impedance electrodes. In EEG potentials are directly generated from neuronal activity, while in EIT by the injection of small currents at the scalp. To retrieve meaningful insights on brain activity from measurements, EIT and EEG relies on detailed knowledge of the underlying electrical properties of the body. This is obtained from numerical models of the electric �field distribution therein. The inhomogeneous and anisotropic electric properties of human tissues make accurate modeling and simulation very challenging, leading to a tradeo�ff between physical accuracy and technical feasibility, which currently severely limits the capabilities of these techniques. Moreover elaboration of data recorded requires usage of regularization techniques computationally intensive, which influences the application with heavy temporal constraints (such as BCI). This work focuses on the parallel implementation of a work-flow for EEG and EIT data processing. The resulting software is accelerated using multi-core GPUs, in order to provide solution in reasonable times and address requirements of real-time BCI systems, without over-simplifying the complexity and accuracy of the head models.

Zweischleifenkorrekturen zum leptonischen Zerfall des Z-Bosons

Im Rahmen der vorliegenden Dissertation wurde, basierend auf der Parallel-/Orthogonalraum-Methode, eine neue Methode zur Berechnung von allgemeinen massiven Zweischleifen-Dreipunkt-Tensorintegralen mit planarer und gedrehter reduzierter planarer Topologie entwickelt. Die Ausarbeitung und Implementation einer Tensorreduktion fuer Integrale, welche eine allgemeine Tensorstruktur im Minkowski-Raum besitzen koennen, wurde durchgefuehrt. Die Entwicklung und Implementation eines Algorithmus zur semi-analytischen Berechnung der schwierigsten Integrale, die nach der Tensorreduktion verbleiben, konnte vollendet werden. (Fuer die anderen Basisintegrale koennen wohlbekannte Methoden verwendet werden.) Die Implementation ist bezueglich der UV-endlichen Anteile der Masterintegrale, die auch nach Tensorreduktion noch die zuvor erwaehnten Topologien besitzen, abgeschlossen. Die numerischen Integrationen haben sich als stabil erwiesen. Fuer die verbleibenden Teile des Projektes koennen wohlbekannte Methoden verwendet werden. In weiten Teilen muessen lediglich noch Links zu existierenden Programmen geschrieben werden. Fuer diejenigen wenigen verbleibenden speziellen Topologien, welche noch zu implementieren sind, sind (wohlbekannte) Methoden zu implementieren. Die Computerprogramme, die im Rahmen dieses Projektes entstanden, werden auch fuer allgemeinere Prozesse in das xloops-Projekt einfliessen. Deswegen wurde sie soweit moeglich fuer allgemeine Prozesse entwickelt und implementiert. Der oben erwaehnte Algorithmus wurde insbesondere fuer die Evaluation der fermionischen NNLO-Korrekturen zum leptonischen schwachen Mischungswinkel sowie zu aehnlichen Prozessen entwickelt. Im Rahmen der vorliegenden Dissertation wurde ein Grossteil der fuer die fermionischen NNLO-Korrekturen zu den effektiven Kopplungskonstanten des Z-Zerfalls (und damit fuer den schachen Mischungswinkel) notwendigen Arbeit durchgefuehrt.

Theoretical and numerical study of the laser-plasma ion acceleration

The laser driven ion acceleration is a burgeoning field of resarch and is attracting a growing number of scientists since the first results reported in 2000 obtained irradiating thin solid foils by high power laser pulses. The growing interest is driven by the peculiar characteristics of the produced bunches, the compactness of the whole accelerating system and the very short accelerating length of this all-optical accelerators. A fervent theoretical and experimental work has been done since then. An important part of the theoretical study is done by means of numerical simulations and the most widely used technique exploits PIC codes (“Particle In Cell'”). In this thesis the PIC code AlaDyn, developed by our research group considering innovative algorithms, is described. My work has been devoted to the developement of the code and the investigation of the laser driven ion acceleration for different target configurations. Two target configurations for the proton acceleration are presented together with the results of the 2D and 3D numerical investigation. One target configuration consists of a solid foil with a low density layer attached on the irradiated side. The nearly critical plasma of the foam layer allows a very high energy absorption by the target and an increase of the proton energy up to a factor 3, when compared to the ``pure'' TNSA configuration. The differences of the regime with respect to the standard TNSA are described The case of nearly critical density targets has been investigated with 3D simulations. In this case the laser travels throughout the plasma and exits on the rear side. During the propagation, the laser drills a channel and induce a magnetic vortex that expanding on the rear side of the targer is source of a very intense electric field. The protons of the plasma are strongly accelerated up to energies of 100 MeV using a 200PW laser.

Numerical simulation of interdigitated back contact hetero-junction solar cells

The goal of this thesis is the application of an opto-electronic numerical simulation to heterojunction silicon solar cells featuring an all back contact architecture (Interdigitated Back Contact Hetero-Junction IBC-HJ). The studied structure exhibits both metal contacts, emitter and base, at the back surface of the cell with the objective to reduce the optical losses due to the shadowing by front contact of conventional photovoltaic devices. Overall, IBC-HJ are promising low-cost alternatives to monocrystalline wafer-based solar cells featuring front and back contact schemes, in fact, for IBC-HJ the high concentration doping diffusions are replaced by low-temperature deposition processes of thin amorphous silicon layers. Furthermore, another advantage of IBC solar cells with reference to conventional architectures is the possibility to enable a low-cost assembling of photovoltaic modules, being all contacts on the same side. A preliminary extensive literature survey has been helpful to highlight the specific critical aspects of IBC-HJ solar cells as well as the state-of-the-art of their modeling, processing and performance of practical devices. In order to perform the analysis of IBC-HJ devices, a two-dimensional (2-D) numerical simulation flow has been set up. A commercial device simulator based on finite-difference method to solve numerically the whole set of equations governing the electrical transport in semiconductor materials (Sentuarus Device by Synopsys) has been adopted. The first activity carried out during this work has been the definition of a 2-D geometry corresponding to the simulation domain and the specification of the electrical and optical properties of materials. In order to calculate the main figures of merit of the investigated solar cells, the spatially resolved photon absorption rate map has been calculated by means of an optical simulator. Optical simulations have been performed by using two different methods depending upon the geometrical features of the front interface of the solar cell: the transfer matrix method (TMM) and the raytracing (RT). The first method allows to model light prop-agation by plane waves within one-dimensional spatial domains under the assumption of devices exhibiting stacks of parallel layers with planar interfaces. In addition, TMM is suitable for the simulation of thin multi-layer anti reflection coating layers for the reduction of the amount of reflected light at the front interface. Raytracing is required for three-dimensional optical simulations of upright pyramidal textured surfaces which are widely adopted to significantly reduce the reflection at the front surface. The optical generation profiles are interpolated onto the electrical grid adopted by the device simulator which solves the carriers transport equations coupled with Poisson and continuity equations in a self-consistent way. The main figures of merit are calculated by means of a postprocessing of the output data from device simulation. After the validation of the simulation methodology by means of comparison of the simulation result with literature data, the ultimate efficiency of the IBC-HJ architecture has been calculated. By accounting for all optical losses, IBC-HJ solar cells result in a theoretical maximum efficiency above 23.5% (without texturing at front interface) higher than that of both standard homojunction crystalline silicon (Homogeneous Emitter HE) and front contact heterojuction (Heterojunction with Intrinsic Thin layer HIT) solar cells. However it is clear that the criticalities of this structure are mainly due to the defects density and to the poor carriers transport mobility in the amorphous silicon layers. Lastly, the influence of the most critical geometrical and physical parameters on the main figures of merit have been investigated by applying the numerical simulation tool set-up during the first part of the present thesis. Simulations have highlighted that carrier mobility and defects level in amorphous silicon may lead to a potentially significant reduction of the conversion efficiency.

A numerical methodology for the multi-objective optimization of the DI Diesel engine combustion

DI Diesel engine are widely used both for industrial and automotive applications due to their durability and fuel economy. Nonetheless, increasing environmental concerns force that type of engine to comply with increasingly demanding emission limits, so that, it has become mandatory to develop a robust design methodology of the DI Diesel combustion system focused on reduction of soot and NOx simultaneously while maintaining a reasonable fuel economy. In recent years, genetic algorithms and CFD three-dimensional combustion simulations have been successfully applied to that kind of problem. However, combining GAs optimization with actual CFD three-dimensional combustion simulations can be too onerous since a large number of calculations is usually needed for the genetic algorithm to converge, resulting in a high computational cost and, thus, limiting the suitability of this method for industrial processes. In order to make the optimization process less time-consuming, CFD simulations can be more conveniently used to generate a training set for the learning process of an artificial neural network which, once correctly trained, can be used to forecast the engine outputs as a function of the design parameters during a GA optimization performing a so-called virtual optimization. In the current work, a numerical methodology for the multi-objective virtual optimization of the combustion of an automotive DI Diesel engine, which relies on artificial neural networks and genetic algorithms, was developed.

Experimental and Numerical Analysis of Gas Forced Convection through Microtubes and Micro Heat Exchangers

The last decade has witnessed very fast development in microfabrication technologies. The increasing industrial applications of microfluidic systems call for more intensive and systematic knowledge on this newly emerging field. Especially for gaseous flow and heat transfer at microscale, the applicability of conventional theories developed at macro scale is not yet completely validated; this is mainly due to scarce experimental data available in literature for gas flows. The objective of this thesis is to investigate these unclear elements by analyzing forced convection for gaseous flows through microtubes and micro heat exchangers. Experimental tests have been performed with microtubes having various inner diameters, namely 750 m, 510 m and 170 m, over a wide range of Reynolds number covering the laminar region, the transitional zone and also the onset region of the turbulent regime. The results show that conventional theory is able to predict the flow friction factor when flow compressibility does not appear and the effect of fluid temperature-dependent properties is insignificant. A double-layered microchannel heat exchanger has been designed in order to study experimentally the efficiency of a gas-to-gas micro heat exchanger. This microdevice contains 133 parallel microchannels machined into polished PEEK plates for both the hot side and the cold side. The microchannels are 200 µm high, 200 µm wide and 39.8 mm long. The design of the micro device has been made in order to be able to test different materials as partition foil with flexible thickness. Experimental tests have been carried out for five different partition foils, with various mass flow rates and flow configurations. The experimental results indicate that the thermal performance of the countercurrent and cross flow micro heat exchanger can be strongly influenced by axial conduction in the partition foil separating the hot gas flow and cold gas flow.

Implementation of network entropy algorithms on hpc machines, with application to high-dimensional experimental data

Network Theory is a prolific and lively field, especially when it approaches Biology. New concepts from this theory find application in areas where extensive datasets are already available for analysis, without the need to invest money to collect them. The only tools that are necessary to accomplish an analysis are easily accessible: a computing machine and a good algorithm. As these two tools progress, thanks to technology advancement and human efforts, wider and wider datasets can be analysed. The aim of this paper is twofold. Firstly, to provide an overview of one of these concepts, which originates at the meeting point between Network Theory and Statistical Mechanics: the entropy of a network ensemble. This quantity has been described from different angles in the literature. Our approach tries to be a synthesis of the different points of view. The second part of the work is devoted to presenting a parallel algorithm that can evaluate this quantity over an extensive dataset. Eventually, the algorithm will also be used to analyse high-throughput data coming from biology.