881 resultados para fractal microstrip


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The reliable and objective assessment of chronic disease state has been and still is a very significant challenge in clinical medicine. An essential feature of human behavior related to the health status, the functional capacity, and the quality of life is the physical activity during daily life. A common way to assess physical activity is to measure the quantity of body movement. Since human activity is controlled by various factors both extrinsic and intrinsic to the body, quantitative parameters only provide a partial assessment and do not allow for a clear distinction between normal and abnormal activity. In this paper, we propose a methodology for the analysis of human activity pattern based on the definition of different physical activity time series with the appropriate analysis methods. The temporal pattern of postures, movements, and transitions between postures was quantified using fractal analysis and symbolic dynamics statistics. The derived nonlinear metrics were able to discriminate patterns of daily activity generated from healthy and chronic pain states.

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In this work, the calcium-induced aggregation of phosphatidylserine liposomes is probed by means of the analysis of the kinetics of such process as well as the aggregate morphology. This novel characterization of liposome aggregation involves the use of static and dynamic light-scattering techniques to obtain kinetic exponents and fractal dimensions. For salt concentrations larger than 5 mM, a diffusion-limited aggregation regime is observed and the Brownian kernel properly describes the time evolution of the diffusion coefficient. For slow kinetics, a slightly modified multiple contact kernel is required. In any case, a time evolution model based on the numerical resolution of Smoluchowski's equation is proposed in order to establish a theoretical description for the aggregating system. Such a model provides an alternative procedure to determine the dimerization constant, which might supply valuable information about interaction mechanisms between phospholipid vesicles.

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The present research studies the spatial patterns of the distribution of the Swiss population (DSP). This description is carried out using a wide variety of global spatial structural analysis tools such as topological, statistical and fractal measures, which enable the estimation of the spatial degree of clustering of a point pattern. A particular attention is given to the analysis of the multifractality to characterize the spatial structure of the DSP at different scales. This will be achieved by measuring the generalized q-dimensions and the singularity spectrum. This research is based on high quality data of the Swiss Population Census of the Year 2000 at a hectometric resolution (grid 100 x 100 m) issued by the Swiss Federal Statistical Office (FSO).

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The work presented here is part of a larger study to identify novel technologies and biomarkers for early Alzheimer disease (AD) detection and it focuses on evaluating the suitability of a new approach for early AD diagnosis by non-invasive methods. The purpose is to examine in a pilot study the potential of applying intelligent algorithms to speech features obtained from suspected patients in order to contribute to the improvement of diagnosis of AD and its degree of severity. In this sense, Artificial Neural Networks (ANN) have been used for the automatic classification of the two classes (AD and control subjects). Two human issues have been analyzed for feature selection: Spontaneous Speech and Emotional Response. Not only linear features but also non-linear ones, such as Fractal Dimension, have been explored. The approach is non invasive, low cost and without any side effects. Obtained experimental results were very satisfactory and promising for early diagnosis and classification of AD patients.

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Defining the limits of an urban agglomeration is essential both for fundamental and applied studies in quantitative and theoretical geography. A simple and consistent way for defining such urban clusters is important for performing different statistical analysis and comparisons. Traditionally, agglomerations are defined using a rather qualitative approach based on various statistical measures. This definition varies generally from one country to another, and the data taken into account are different. In this paper, we explore the use of the City Clustering Algorithm (CCA) for the agglomeration definition in Switzerland. This algorithm provides a systemic and easy way to define an urban area based only on population data. The CCA allows the specification of the spatial resolution for defining the urban clusters. The results from different resolutions are compared and analysed, and the effect of filtering the data investigated. Different scales and parameters allow highlighting different phenomena. The study of Zipf's law using the visual rank-size rule shows that it is valid only for some specific urban clusters, inside a narrow range of the spatial resolution of the CCA. The scale where emergence of one main cluster occurs can also be found in the analysis using Zipf's law. The study of the urban clusters at different scales using the lacunarity measure - a complementary measure to the fractal dimension - allows to highlight the change of scale at a given range.

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This paper contains a study of the synchronization by homogeneous nonlinear driving of systems that are symmetric in phase space. The main consequence of this symmetry is the ability of the response to synchronize in more than just one way to the driving systems. These different forms of synchronization are to be understood as generalized synchronization states in which the motions of drive and response are in complete correlation, but the phase space distance between them does not converge to zero. In this case the synchronization phenomenon becomes enriched because there is multistability. As a consequence, there appear multiple basins of attraction and special responses to external noise. It is shown, by means of a computer simulation of various nonlinear systems, that: (i) the decay to the generalized synchronization states is exponential, (ii) the basins of attraction are symmetric, usually complicated, frequently fractal, and robust under the changes in the parameters, and (iii) the effect of external noise is to weaken the synchronization, and in some cases to produce jumps between the various synchronization states available

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This work describes a simulation tool being developed at UPC to predict the microwave nonlinear behavior of planar superconducting structures with very few restrictions on the geometry of the planar layout. The software is intended to be applicable to most structures used in planar HTS circuits, including line, patch, and quasi-lumped microstrip resonators. The tool combines Method of Moments (MoM) algorithms for general electromagnetic simulation with Harmonic Balance algorithms to take into account the nonlinearities in the HTS material. The Method of Moments code is based on discretization of the Electric Field Integral Equation in Rao, Wilton and Glisson Basis Functions. The multilayer dyadic Green's function is used with Sommerfeld integral formulation. The Harmonic Balance algorithm has been adapted to this application where the nonlinearity is distributed and where compatibility with the MoM algorithm is required. Tests of the algorithm in TM010 disk resonators agree with closed-form equations for both the fundamental and third-order intermodulation currents. Simulations of hairpin resonators show good qualitative agreement with previously published results, but it is found that a finer meshing would be necessary to get correct quantitative results. Possible improvements are suggested.

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The quality of environmental data analysis and propagation of errors are heavily affected by the representativity of the initial sampling design [CRE 93, DEU 97, KAN 04a, LEN 06, MUL07]. Geostatistical methods such as kriging are related to field samples, whose spatial distribution is crucial for the correct detection of the phenomena. Literature about the design of environmental monitoring networks (MN) is widespread and several interesting books have recently been published [GRU 06, LEN 06, MUL 07] in order to clarify the basic principles of spatial sampling design (monitoring networks optimization) based on Support Vector Machines was proposed. Nonetheless, modelers often receive real data coming from environmental monitoring networks that suffer from problems of non-homogenity (clustering). Clustering can be related to the preferential sampling or to the impossibility of reaching certain regions.

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Position sensitive particle detectors are needed in high energy physics research. This thesis describes the development of fabrication processes and characterization techniques of silicon microstrip detectors used in the work for searching elementary particles in the European center for nuclear research, CERN. The detectors give an electrical signal along the particles trajectory after a collision in the particle accelerator. The trajectories give information about the nature of the particle in the struggle to reveal the structure of the matter and the universe. Detectors made of semiconductors have a better position resolution than conventional wire chamber detectors. Silicon semiconductor is overwhelmingly used as a detector material because of its cheapness and standard usage in integrated circuit industry. After a short spread sheet analysis of the basic building block of radiation detectors, the pn junction, the operation of a silicon radiation detector is discussed in general. The microstrip detector is then introduced and the detailed structure of a double-sided ac-coupled strip detector revealed. The fabrication aspects of strip detectors are discussedstarting from the process development and general principles ending up to the description of the double-sided ac-coupled strip detector process. Recombination and generation lifetime measurements in radiation detectors are discussed shortly. The results of electrical tests, ie. measuring the leakage currents and bias resistors, are displayed. The beam test setups and the results, the signal to noise ratio and the position accuracy, are then described. It was found out in earlier research that a heavy irradiation changes the properties of radiation detectors dramatically. A scanning electron microscope method was developed to measure the electric potential and field inside irradiated detectorsto see how a high radiation fluence changes them. The method and the most important results are discussed shortly.

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Diplomityössä on käsitelty paperin pinnankarkeuden mittausta, joka on keskeisimpiä ongelmia paperimateriaalien tutkimuksessa. Paperiteollisuudessa käytettävät mittausmenetelmät sisältävät monia haittapuolia kuten esimerkiksi epätarkkuus ja yhteensopimattomuus sileiden papereiden mittauksissa, sekä suuret vaatimukset laboratorio-olosuhteille ja menetelmien hitaus. Työssä on tutkittu optiseen sirontaan perustuvia menetelmiä pinnankarkeuden määrittämisessä. Konenäköä ja kuvan-käsittelytekniikoita tutkittiin karkeilla paperipinnoilla. Tutkimuksessa käytetyt algoritmit on tehty Matlab® ohjelmalle. Saadut tulokset osoittavat mahdollisuuden pinnankarkeuden mittaamiseen kuvauksen avulla. Parhaimman tuloksen perinteisen ja kuvausmenetelmän välillä antoi fraktaaliulottuvuuteen perustuva menetelmä.

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Tässä diplomityössä tutkittiin ja kehitettiin edelleen mikroliuskarakenteisen T-resonaattorin käyttöä laajakaistaisessa piirilevylaminaattien dielektrisyysvakion ja häviökertoimen määrityksessä. Työssä perehdyttiin eristeominaisuuksien määrityksessä tarvittaviin laskentamenetelmiin sekä T-resonaattorin toimintaan. T-resonaattorin suunnittelu ja käyttöä varten valitut laskentamenetelmät on esitelty. Työssä suunniteltiin ja valmistettiin mikroliuskarakenteinen T-resonaattorimittausrakenne, jolla määritettiin erään FR-4 -tyyppisen piirilevylaminaattimateriaalin dielektrisyysvakio sekä häviökerroin mittausten ja laskennan avulla taajuuskaistalla 0,5 - 10 GHz. Tuloksia verrattiin muilla käytössä olevilla menetelmillä määritettyihin tuloksiin. Tulosten perusteella voitiin osoittaa, että mikroliuskarakenteinen T-resonaattori soveltuu hyvin piirilevylaminaattien eristeominaisuuksien määritykseen, ja käytetyt laskenta-menetelmät antavat realistisia tuloksia.

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Tässä diplomityössä tutkittiin TRL-kalibroinnin käyttämistä tasomaisten siirtojohtojen sähköisten parametrien määrittämisessä taajuusalueella 0,3 – 12 GHz. Työssä perehdyttiin TRL-kalibroinnin käyttämiseen piirianalysaattorilla toteutettujen mittauksien mittauskalibrointiin sekä kalibrointiin tarvittavien kalibrointistandardien mitoittamiseen. Kalibrointistandardit suunniteltiin ja toteutettiin sekä mikroliuska- että liuskajohdoille, joiden toiminnallisuutta tarkasteltiin sekä taajuustason että aikatason mittausten avulla. Työssä perehdyttiin myös kalibrointistandardien liityntärajapinnan suunniteluun ja toteuttamiseen. Saatujen tulosten perusteella voitiin osoittaa mikroliuskajohtokitin soveltuvan hyvin mittauskalibroinnin toteuttamiseen tarkoissa mittaussovelluksissa.

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Tässä diplomityössä on käsitelty mikroliuskarakenteen johdinhäviöiden määrittämistä kokeellisin ja analyyttisin menetelmin. Työssä on käyty läpi mikroliuskarakenteen ominaisuudet sekä esitetty tärkeimmät kirjallisuudessa esitellyt menetelmät johdinhäviöiden laskemiseksi. Mikroliuskarakenteen häviöitä mallinnettiin modernilla momenttimenetelmään perustuvalla kenttälaskentasimulaattorilla. Simulaattorin toimintaperiaate on esitelty ja sen soveltaminen mikroliuskarakenteen simuloimiseen on käyty läpi. Eräs mikroliuskarakenne mallinnettiin taajuusalueella 1-10 GHz ja simuloituja johdinhäviöitä verrattiin analyyttisesti määritettyihin. Mikroliuskarakenteen vaste mitattiin ja sitä verrattiin mallinnetun mikroliuskarakenteen vasteeseen. Tulosten perusteella on pohdittu simulaattorin soveltuvuutta mikroliuskarakenteen johdinhäviöiden mallintamiseen. Mikroliuskarakenteen johdinhäviöiden määrittämiseen mittausten avulla on esitetty ideoita jatkotutkimusta varten.

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The purpose of our project is to contribute to earlier diagnosis of AD and better estimates of its severity by using automatic analysis performed through new biomarkers extracted from non-invasive intelligent methods. The methods selected in this case are speech biomarkers oriented to Sponta-neous Speech and Emotional Response Analysis. Thus the main goal of the present work is feature search in Spontaneous Speech oriented to pre-clinical evaluation for the definition of test for AD diagnosis by One-class classifier. One-class classifi-cation problem differs from multi-class classifier in one essen-tial aspect. In one-class classification it is assumed that only information of one of the classes, the target class, is available. In this work we explore the problem of imbalanced datasets that is particularly crucial in applications where the goal is to maximize recognition of the minority class as in medical diag-nosis. The use of information about outlier and Fractal Dimen-sion features improves the system performance.