Visualizing control systems performance: A fractional perspective

This article presents a novel method for visualizing the control systems behavior. The proposed scheme uses the tools of fractional calculus and computes the signals propagating within the system structure as a time/frequency-space wave. Linear and nonlinear closed-loop control systems are analyzed, for both the time and frequency responses, under the action of a reference step input signal. Several nonlinearities, namely, Coulomb friction and backlash, are also tested. The numerical experiments demonstrate the feasibility of the proposed methodology as a visualization tool and motivate its extension for other systems and classes of nonlinearities.

Kalman tracking linear predictor for vowel intelligibility enhancement on european portuguese HMM based speech synthesis

The recent developments on Hidden Markov Models (HMM) based speech synthesis showed that this is a promising technology fully capable of competing with other established techniques. However some issues still lack a solution. Several authors report an over-smoothing phenomenon on both time and frequencies which decreases naturalness and sometimes intelligibility. In this work we present a new vowel intelligibility enhancement algorithm that uses a discrete Kalman filter (DKF) for tracking frame based parameters. The inter-frame correlations are modelled by an autoregressive structure which provides an underlying time frame dependency and can improve time-frequency resolution. The system’s performance has been evaluated using objective and subjective tests and the proposed methodology has led to improved results.

Linear amplification with multiple nonlinear devices

Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e Computadores

Complex networks and data mining: toward a new perspective for the understanding of complex systems

Complex systems, i.e. systems composed of a large set of elements interacting in a non-linear way, are constantly found all around us. In the last decades, different approaches have been proposed toward their understanding, one of the most interesting being the Complex Network perspective. This legacy of the 18th century mathematical concepts proposed by Leonhard Euler is still current, and more and more relevant in real-world problems. In recent years, it has been demonstrated that network-based representations can yield relevant knowledge about complex systems. In spite of that, several problems have been detected, mainly related to the degree of subjectivity involved in the creation and evaluation of such network structures. In this Thesis, we propose addressing these problems by means of different data mining techniques, thus obtaining a novel hybrid approximation intermingling complex networks and data mining. Results indicate that such techniques can be effectively used to i) enable the creation of novel network representations, ii) reduce the dimensionality of analyzed systems by pre-selecting the most important elements, iii) describe complex networks, and iv) assist in the analysis of different network topologies. The soundness of such approach is validated through different validation cases drawn from actual biomedical problems, e.g. the diagnosis of cancer from tissue analysis, or the study of the dynamics of the brain under different neurological disorders.

Over expression of AdeABC and AcrAB-TolC efflux systems confers tigecycline resistance in clinical isolates of Acinetobacter baumannii and Klebsiella pneumoniae

Abstract: INTRODUCTION: Due to the wide use of tigecycline in the treatment of severe infections caused by multidrug-resistant (MDR) bacteria, clinical resistance to tigecycline has increased in recent years. Here, we investigated the relationship between tigecycline resistance and the expression of efflux pumps. METHODS: Clinical isolates of Acinetobacter baumannii and Klebsiella pneumoniae were consecutively collected from hospitalized patients in three hospitals. The minimum inhibitory concentration (MIC) of tigecycline was determined using the broth microdilution method. Expression levels of efflux pump genes and regulators were examined by quantitative real-time reverse transcription polymerase chain reaction. The correlations between tigecycline MICs and gene expression levels were analyzed. RESULTS: Overall, 1,026 A. baumannii and 725 K. pneumoniae strains were collected. Most strains were isolated from sputum. The tigecycline resistance rate was 13.4% in A. baumannii isolates and 6.5% in K. pneumoniae isolates. Overexpression of AdeABC and AcrAB-TolC efflux systems was observed found in clinical tigecycline-resistant isolates. The tigecycline MIC had a linear relationship with the adeB expression level in A. baumannii isolates, but not with the acrB expression level in K. pneumoniae isolates. There were significant linear trends in the overexpression of ramA as the tigecycline MIC increased in K. pneumoniae isolates. CONCLUSIONS: Tigecycline resistance in A. baumannii and K. pneumoniae was strongly associated with the overexpression of efflux systems. More studies are needed to elucidate whether there are other regulators that affect the expression of adeB in A. baumannii and how ramA affects the expression of acrB in K. pneumoniae.

Non emergency patients transport - a mixed integer linear programming

This work presents a model and a heuristic to solve the non-emergency patients transport (NEPT) service issues given the new rules recently established in Portugal. The model follows the same principle of the Team Orienteering Problem by selecting the patients to be included in the routes attending the maximum reduction in costs when compared with individual transportation. This model establishes the best sets of patients to be transported together. The model was implemented in AMPL and a compact formulation was solved using NEOS Server. A heuristic procedure based on iteratively solving problems with one vehicle was presented, and this heuristic provides good results in terms of accuracy and computation time.

Otimização com restrições de complementaridade: algoritmos e aplicações

Tese de Doutoramento em Engenharia Industrial e de Sistemas (PDEIS)

Interrelationship between partition behavior of organic compounds and proteins in aqueous dextran-Polyethylene glycol and Polyethylene glycol-sodium sulfate two-phase systems

Partition behavior of adenosine and guanine mononucleotides was examined in aqueous dextran-polyethylene glycol (PEG) and PEG-sodium sulfate two-phase systems. The partition coefficients for each series of mononucleotides were analyzed as a functions of the number of phosphate groups and found to be dependent on the nature of nucleic base and on the type of \ATPS\ utilized. It was concluded that an average contribution of a phosphate group into logarithm of partition coefficient of a mononucleotide cannot be used to estimate the difference between the electrostatic properties of the coexisting phases of ATPS. The data obtained in this study were considered together with those for other organic compounds and proteins reported previously, and the linear interrelationship between logarithms of partition coefficients in dextran-PEG, PEG-Na2SO4 and PEG-Na2SO4-0.215 M NaCl (all in 0.01 M Na- or K/Na-phosphate buffer, pH 7.4 or 6.8) was established. Similar relationship was found for the previously reported data for proteins in Dex-PEG, PEG-600-Na2SO4, and PEG-8000-Na2SO4 ATPS. It is suggested that the linear relationships of the kind established in \ATPS\ may be observed for biological properties of compounds as well.

New delay-dependent stability criteria for uncertain neutral systems with mixed time-varying delays and nonlinear perturbations

The problem of stability analysis for a class of neutral systems with mixed time-varying neutral, discrete and distributed delays and nonlinear parameter perturbations is addressed. By introducing a novel Lyapunov-Krasovskii functional and combining the descriptor model transformation, the Leibniz-Newton formula, some free-weighting matrices, and a suitable change of variables, new sufficient conditions are established for the stability of the considered system, which are neutral-delay-dependent, discrete-delay-range dependent, and distributeddelay-dependent. The conditions are presented in terms of linear matrix inequalities (LMIs) and can be efficiently solved using convex programming techniques. Two numerical examples are given to illustrate the efficiency of the proposed method

An LMI approach to H∞ synchronization of second-order neutral master-slave systems

The H∞ synchronization problem of the master and slave structure of a second-order neutral master-slave systems with time-varying delays is presented in this paper. Delay-dependent sufficient conditions for the design of a delayed output-feedback control are given by Lyapunov-Krasovskii method in terms of a linear matrix inequality (LMI). A controller, which guarantees H∞ synchronization of the master and slave structure using some free weighting matrices, is then developed. A numerical example has been given to show the effectiveness of the method

N-dimensional dynamical systems exploiting instabilities in full

We report experimental and numerical results showing how certain N-dimensional dynamical systems are able to exhibit complex time evolutions based on the nonlinear combination of N-1 oscillation modes. The experiments have been done with a family of thermo-optical systems of effective dynamical dimension varying from 1 to 6. The corresponding mathematical model is an N-dimensional vector field based on a scalar-valued nonlinear function of a single variable that is a linear combination of all the dynamic variables. We show how the complex evolutions appear associated with the occurrence of successive Hopf bifurcations in a saddle-node pair of fixed points up to exhaust their instability capabilities in N dimensions. For this reason the observed phenomenon is denoted as the full instability behavior of the dynamical system. The process through which the attractor responsible for the observed time evolution is formed may be rather complex and difficult to characterize. Nevertheless, the well-organized structure of the time signals suggests some generic mechanism of nonlinear mode mixing that we associate with the cluster of invariant sets emerging from the pair of fixed points and with the influence of the neighboring saddle sets on the flow nearby the attractor. The generation of invariant tori is likely during the full instability development and the global process may be considered as a generalized Landau scenario for the emergence of irregular and complex behavior through the nonlinear superposition of oscillatory motions

A systolic array for linear MIMO detection based on an all-swap lattice reduction algorithm

A systolic array to implement lattice-reduction-aided lineardetection is proposed for a MIMO receiver. The lattice reductionalgorithm and the ensuing linear detections are operated in the same array, which can be hardware-efficient. All-swap lattice reduction algorithm (ASLR) is considered for the systolic design.ASLR is a variant of the LLL algorithm, which processes all lattice basis vectors within one iteration. Lattice-reduction-aided linear detection based on ASLR and LLL algorithms have very similarbit-error-rate performance, while ASLR is more time efficient inthe systolic array, especially for systems with a large number ofantennas.

Towards robust network based complex systems : from evolutionary cellular automata to biological models

Abstract Sitting between your past and your future doesn't mean you are in the present. Dakota Skye Complex systems science is an interdisciplinary field grouping under the same umbrella dynamical phenomena from social, natural or mathematical sciences. The emergence of a higher order organization or behavior, transcending that expected of the linear addition of the parts, is a key factor shared by all these systems. Most complex systems can be modeled as networks that represent the interactions amongst the system's components. In addition to the actual nature of the part's interactions, the intrinsic topological structure of underlying network is believed to play a crucial role in the remarkable emergent behaviors exhibited by the systems. Moreover, the topology is also a key a factor to explain the extraordinary flexibility and resilience to perturbations when applied to transmission and diffusion phenomena. In this work, we study the effect of different network structures on the performance and on the fault tolerance of systems in two different contexts. In the first part, we study cellular automata, which are a simple paradigm for distributed computation. Cellular automata are made of basic Boolean computational units, the cells; relying on simple rules and information from- the surrounding cells to perform a global task. The limited visibility of the cells can be modeled as a network, where interactions amongst cells are governed by an underlying structure, usually a regular one. In order to increase the performance of cellular automata, we chose to change its topology. We applied computational principles inspired by Darwinian evolution, called evolutionary algorithms, to alter the system's topological structure starting from either a regular or a random one. The outcome is remarkable, as the resulting topologies find themselves sharing properties of both regular and random network, and display similitudes Watts-Strogtz's small-world network found in social systems. Moreover, the performance and tolerance to probabilistic faults of our small-world like cellular automata surpasses that of regular ones. In the second part, we use the context of biological genetic regulatory networks and, in particular, Kauffman's random Boolean networks model. In some ways, this model is close to cellular automata, although is not expected to perform any task. Instead, it simulates the time-evolution of genetic regulation within living organisms under strict conditions. The original model, though very attractive by it's simplicity, suffered from important shortcomings unveiled by the recent advances in genetics and biology. We propose to use these new discoveries to improve the original model. Firstly, we have used artificial topologies believed to be closer to that of gene regulatory networks. We have also studied actual biological organisms, and used parts of their genetic regulatory networks in our models. Secondly, we have addressed the improbable full synchronicity of the event taking place on. Boolean networks and proposed a more biologically plausible cascading scheme. Finally, we tackled the actual Boolean functions of the model, i.e. the specifics of how genes activate according to the activity of upstream genes, and presented a new update function that takes into account the actual promoting and repressing effects of one gene on another. Our improved models demonstrate the expected, biologically sound, behavior of previous GRN model, yet with superior resistance to perturbations. We believe they are one step closer to the biological reality.

The achievable region approach to the optimal control of stochastic systems

The achievable region approach seeks solutions to stochastic optimisation problems by: (i) characterising the space of all possible performances(the achievable region) of the system of interest, and (ii) optimisingthe overall system-wide performance objective over this space. This isradically different from conventional formulations based on dynamicprogramming. The approach is explained with reference to a simpletwo-class queueing system. Powerful new methodologies due to the authorsand co-workers are deployed to analyse a general multiclass queueingsystem with parallel servers and then to develop an approach to optimalload distribution across a network of interconnected stations. Finally,the approach is used for the first time to analyse a class of intensitycontrol problems.

3D seismic facies characterization and geological patterns recognition (Australian North West Shelf)

EXECUTIVE SUMMARY This PhD research, funded by the Swiss Sciences Foundation, is principally devoted to enhance the recognition, the visualisation and the characterization of geobodies through innovative 3D seismic approaches. A series of case studies from the Australian North West Shelf ensures the development of reproducible integrated 3D workflows and gives new insight into local and regional stratigraphic as well as structural issues. This project was initiated in year 2000 at the Geology and Palaeontology Institute of the University of Lausanne (Switzerland). Several collaborations ensured the improvement of technical approaches as well as the assessment of geological models. - Investigations into the Timor Sea structural style were carried out at the Tectonics Special Research Centre of the University of Western Australia and in collaboration with Woodside Energy in Perth. - Seismic analysis and attributes classification approach were initiated with Schlumberger Oilfield Australia in Perth; assessments and enhancements of the integrated seismic approaches benefited from collaborations with scientists from Schlumberger Stavanger Research (Norway). Adapting and refining from "linear" exploration techniques, a conceptual "helical" 3D seismic approach has been developed. In order to investigate specific geological issues this approach, integrating seismic attributes and visualisation tools, has been refined and adjusted leading to the development of two specific workflows: - A stratigraphic workflow focused on the recognition of geobodies and the characterization of depositional systems. Additionally, it can support the modelling of the subsidence and incidentally the constraint of the hydrocarbon maturity of a given area. - A structural workflow used to quickly and accurately define major and secondary fault systems. The integration of the 3D structural interpretation results ensures the analysis of the fault networks kinematics which can affect hydrocarbon trapping mechanisms. The application of these integrated workflows brings new insight into two complex settings on the Australian North West Shelf and ensures the definition of astonishing stratigraphic and structural outcomes. The stratigraphic workflow ensures the 3D characterization of the Late Palaeozoic glacial depositional system on the Mermaid Nose (Dampier Subbasin, Northern Carnarvon Basin) that presents similarities with the glacial facies along the Neotethys margin up to Oman (chapter 3.1). A subsidence model reveals the Phanerozoic geodynamic evolution of this area (chapter 3.2) and emphasizes two distinct mode of regional extension for the Palaeozoic (Neotethys opening) and Mesozoic (abyssal plains opening). The structural workflow is used for the definition of the structural evolution of the Laminaria High area (Bonaparte Basin). Following a regional structural characterization of the Timor Sea (chapter 4.1), a thorough analysis of the Mesozoic fault architecture reveals a local rotation of the stress field and the development of reverse structures (flower structures) in extensional setting, that form potential hydrocarbon traps (chapter 4.2). The definition of the complex Neogene structural architecture associated with the fault kinematic analysis and a plate flexure model (chapter 4.3) suggest that the Miocene to Pleistocene reactivation phases recorded at the Laminaria High most probably result from the oblique normal reactivation of the underlying Mesozoic fault planes. This episode is associated with the deformation of the subducting Australian plate. Based on these results three papers were published in international journals and two additional publications will be submitted. Additionally this research led to several communications in international conferences. Although the different workflows presented in this research have been primarily developed and used for the analysis of specific stratigraphic and structural geobodies on the Australian North West Shelf, similar integrated 3D seismic approaches will have applications to hydrocarbon exploration and production phases; for instance increasing the recognition of potential source rocks, secondary migration pathways, additional traps or reservoir breaching mechanisms. The new elements brought by this research further highlight that 3D seismic data contains a tremendous amount of hidden geological information waiting to be revealed and that will undoubtedly bring new insight into depositional systems, structural evolution and geohistory of the areas reputed being explored and constrained and other yet to be constrained. The further development of 3D texture attributes highlighting specific features of the seismic signal, the integration of quantitative analysis for stratigraphic and structural processes, the automation of the interpretation workflow as well as the formal definition of "seismo-morphologic" characteristics of a wide range of geobodies from various environments would represent challenging examples of continuation of this present research. The 21st century will most probably represent a transition period between fossil and other alternative energies. The next generation of seismic interpreters prospecting for hydrocarbon will undoubtedly face new challenges mostly due to the shortage of obvious and easy targets. They will probably have to keep on integrating techniques and geological processes in order to further capitalise the seismic data for new potentials definition. Imagination and creativity will most certainly be among the most important quality required from such geoscientists.