929 resultados para Pattern-matching technique


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A simple analog instrumentation for Electrical Impedance Tomography is developed and calibrated using the practical phantoms. A constant current injector consisting of a modified Howland voltage controlled current source fed by a voltage controlled oscillator is developed to inject a constant current to the phantom boundary. An instrumentation amplifier, 50 Hz notch filter and a narrow band pass filter are developed and used for signal conditioning. Practical biological phantoms are developed and the forward problem is studied to calibrate the EIT-instrumentation. An array of sixteen stainless steel electrodes is developed and placed inside the phantom tank filled with KCl solution. 1 mA, 50 kHz sinusoidal current is injected at the phantom boundary using adjacent current injection protocol. The differential potentials developed at the voltage electrodes are measured for sixteen current injections. Differential voltage signal is passed through an instrumentation amplifier and a filtering block and measured by a digital multimeter. A forward solver is developed using Finite Element Method in MATLAB7.0 for solving the EIT governing equation. Differential potentials are numerically calculated using the forward solver with a simulated current and bathing solution conductivity. Measured potential data is compared with the differential potentials calculated for calibrating the instrumentation to acquire the voltage data suitable for better image reconstruction.

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A new approach for unwrapping phase maps, obtained during the measurement of 3-D surfaces using sinusoidal structured light projection technique, is proposed. "Takeda's method" is used to obtain the wrapped phase map. Proposed method of unwrapping makes use of an additional image of the object captured under the illumination of a specifically designed color-coded pattern. The new approach demonstrates, for the first time, a method of producing reliable unwrapping of objects even with surface discontinuities from a single-phase map. It is shown to be significantly faster and reliable than temporal phase unwrapping procedure that uses a complete exponential sequence. For example, if a measurement with the accuracy obtained by interrogating the object with S fringes in the projected pattern is carried out with both the methods, new method requires only 2 frames as compared to (log(2)S +1) frames required by the later method.

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The main method of modifying properties of semiconductors is to introduce small amount of impurities inside the material. This is used to control magnetic and optical properties of materials and to realize p- and n-type semiconductors out of intrinsic material in order to manufacture fundamental components such as diodes. As diffusion can be described as random mixing of material due to thermal movement of atoms, it is essential to know the diffusion behavior of the impurities in order to manufacture working components. In modified radiotracer technique diffusion is studied using radioactive isotopes of elements as tracers. The technique is called modified as atoms are deployed inside the material by ion beam implantation. With ion implantation, a distinct distribution of impurities can be deployed inside the sample surface with good con- trol over the amount of implanted atoms. As electromagnetic radiation and other nuclear decay products emitted by radioactive materials can be easily detected, only very low amount of impurities can be used. This makes it possible to study diffusion in pure materials without essentially modifying the initial properties by doping. In this thesis a modified radiotracer technique is used to study the diffusion of beryllium in GaN, ZnO, SiGe and glassy carbon. GaN, ZnO and SiGe are of great interest to the semiconductor industry and beryllium as a small and possibly rapid dopant hasn t been studied previously using the technique. Glassy carbon has been added to demonstrate the feasibility of the technique. In addition, the diffusion of magnetic impurities, Mn and Co, has been studied in GaAs and ZnO (respectively) with spintronic applications in mind.

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We present a measurement of the $WW+WZ$ production cross section observed in a final state consisting of an identified electron or muon, two jets, and missing transverse energy. The measurement is carried out in a data sample corresponding to up to 4.6~fb$^{-1}$ of integrated luminosity at $\sqrt{s} = 1.96$ TeV collected by the CDF II detector. Matrix element calculations are used to separate the diboson signal from the large backgrounds. The $WW+WZ$ cross section is measured to be $17.4\pm3.3$~pb, in agreement with standard model predictions. A fit to the dijet invariant mass spectrum yields a compatible cross section measurement.

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The rate of absorption of amino acids from mixtures has been studied in the silkworm midgut by using an in vitro perfusion technique. The rates differ for individual amino acids. A characteristic absorption pattern is observed which is independent of the amino acid composition of the mixture used. The metabolic inhibitors dinitrophenol and cyanide have no effect on the amino acid transport from mixtures. Based on these results an energy-independent, carrier-mediated transport is postulated.

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A voltage source inverter-fed induction motor produces a pulsating torque due to application of nonsinusoidal voltages. Torque pulsation is strongly influenced by the pulsewidth modulation (PWM) method employed. Conventional space vector PWM (CSVPWM) is known to result in less torque ripple than sine-triangle PWM. This paper aims at further reduction in the pulsating torque by employing advanced bus-clamping switching sequences, which apply an active vector twice in a subcycle. This paper proposes a hybrid PWM technique which employs such advanced bus-clamping sequences in conjunction with a conventional switching sequence. The proposed hybrid PWM technique is shown to reduce the torque ripple considerably over CSVPWM along with a marginal reduction in current ripple.

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The absolute configuration of echitamine iodide has been determined by the Bijvoet technique, making use of the intensity differences between hkl and {Mathematical expression} reflections due to the anomalous scattering of CuKa radiation by the iodine atom. The various steps in the procedure are discussed in detail in this paper.

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The qualitative and quantitative aspects of the proteins of the silkworm blood were studied by the technique of agarophoresis. The blood of larvae at the final stage revealed the presence of six different protein zones. Considerable differences in the patterns were observed at different stages of growth. There was an increase in the total nitrogen of the blood up to the 5th instar and then came a sudden decrease in the one-day old pupae. Nitrogen concentration was at its highest in egg 1 stage and the electrophoretic pattern closely corresponded to the final larval pattern. Results indicate to the involvement of silk glands in the synthesis and breakdown of a protein designated as protein 5.

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We present a measurement of the top quark mass in the all-hadronic channel (\tt $\to$ \bb$q_{1}\bar{q_{2}}q_{3}\bar{q_{4}}$) using 943 pb$^{-1}$ of \ppbar collisions at $\sqrt {s} = 1.96$ TeV collected at the CDF II detector at Fermilab (CDF). We apply the standard model production and decay matrix-element (ME) to $\ttbar$ candidate events. We calculate per-event probability densities according to the ME calculation and construct template models of signal and background. The scale of the jet energy is calibrated using additional templates formed with the invariant mass of pairs of jets. These templates form an overall likelihood function that depends on the top quark mass and on the jet energy scale (JES). We estimate both by maximizing this function. Given 72 observed events, we measure a top quark mass of 171.1 $\pm$ 3.7 (stat.+JES) $\pm$ 2.1 (syst.) GeV/$c^{2}$. The combined uncertainty on the top quark mass is 4.3 GeV/$c^{2}$.

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The core aim of machine learning is to make a computer program learn from the experience. Learning from data is usually defined as a task of learning regularities or patterns in data in order to extract useful information, or to learn the underlying concept. An important sub-field of machine learning is called multi-view learning where the task is to learn from multiple data sets or views describing the same underlying concept. A typical example of such scenario would be to study a biological concept using several biological measurements like gene expression, protein expression and metabolic profiles, or to classify web pages based on their content and the contents of their hyperlinks. In this thesis, novel problem formulations and methods for multi-view learning are presented. The contributions include a linear data fusion approach during exploratory data analysis, a new measure to evaluate different kinds of representations for textual data, and an extension of multi-view learning for novel scenarios where the correspondence of samples in the different views or data sets is not known in advance. In order to infer the one-to-one correspondence of samples between two views, a novel concept of multi-view matching is proposed. The matching algorithm is completely data-driven and is demonstrated in several applications such as matching of metabolites between humans and mice, and matching of sentences between documents in two languages.

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The mechanism of sub-microscopic precipitation in an Al-Zn-Mg alloy selected for its maximum response to ageing has been studied by a standardized oxide-replica technique in a 100 kV. Philips Electron Microscope. Contrary to earlier conclusions, examination of the oxide replicas has been shown to reveal details of the precipitation process almost as clearly as the thin-foil transmission technique. The reported formation of spherical Guinier-Preston zones followed by the development of a Widmanstaetten pattern of precipitated platelets has been confirmed. The zones have, however, been shown to grow into the platelets and not to dissolve in the matrix as reported earlier. The precipitation process has been correlated with the Hardness/Ageing Time curve and the structure of the precipitates has also been discussed.

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The fracture behavior of concrete–concrete interface is characterized using acoustic emission (AE). Beams of different sizes having jointed interface between two different strengths of concrete are tested. The results of load, displacement, CMOD, AE-events and AE-energy are analyzed. The width of fracture process zone and damage zone are computed using AE-data and are found to be independent of size. It is observed that, as the difference in compressive strength of concrete on either side of interface increases, the load carrying capacity, number of AE-events, AE-energy, width of fracture process zone and damage zone decreases.

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Accurate mass flow measurement is very important in various monitoring and control applications. This paper proposes a novel method of fluid flow measurement by compensating the pressure drop across the ends of measuring unit using a compensating pump. The pressure drop due to the flow is balanced by a feedback control loop. This is a null-deflection type of measurement. As the insertion of such a measuring unit does not affect the functioning of the systems, this is also a non-disruptive flow measurement method. The implementation and design of such a unit are discussed. The system is modeled and simulated using the bond graph technique and it is experimentally validated. (C) 2009 Elsevier Ltd. All rights reserved.

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This thesis analyzes how matching takes place at the Finnish labor market from three different angles. The Finnish labor market has undergone severe structural changes following the economic crisis in the early 1990s. The labor market has had problems adjusting from these changes and hence a high and persistent unemployment has followed. In this thesis I analyze if matching problems, and in particular if changes in matching, can explain some of this persistence. The thesis consists of three essays. In the first essay Finnish Evidence of Changes in the Labor Market Matching Process the matching process at the Finnish labor market is analyzed. The key finding is that the matching process has changed thoroughly between the booming 1980s and the post-crisis period. The importance of the number of unemployed, and in particular long-term unemployed, for the matching process has vanished. More unemployed do not increase matching as theory predicts but rather the opposite. In the second essay, The Aggregate Matching Function and Directed Search -Finnish Evidence, stock-flow matching as a potential micro foundation of the aggregate matching function is studied. In the essay I show that newly unemployed match mainly with the stock of vacancies while longer term unemployed match with the inflow of vacancies. When aggregating I still find evidence of the traditional aggregate matching function. This could explain the huge support the aggregate matching function has received despite its odd randomness assumption. The third essay, How do Registered Job Seekers really match? -Finnish occupational level Evidence, studies matching for nine occupational groups and finds that very different matching problems exist for different occupations. In this essay also misspecification stemming from non-corresponding variables is dealt with through the introduction of a completely new set of variables. The new outflow measure used is vacancies filled with registered job seekers and it is matched by the supply side measure registered job seekers.

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In this paper we show the applicability of Ant Colony Optimisation (ACO) techniques for pattern classification problem that arises in tool wear monitoring. In an earlier study, artificial neural networks and genetic programming have been successfully applied to tool wear monitoring problem. ACO is a recent addition to evolutionary computation technique that has gained attention for its ability to extract the underlying data relationships and express them in form of simple rules. Rules are extracted for data classification using training set of data points. These rules are then applied to set of data in the testing/validation set to obtain the classification accuracy. A major attraction in ACO based classification is the possibility of obtaining an expert system like rules that can be directly applied subsequently by the user in his/her application. The classification accuracy obtained in ACO based approach is as good as obtained in other biologically inspired techniques.