1000 resultados para Multi-langage


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The following work explores the processes individuals utilize when making multi-attribute choices. With the exception of extremely simple or familiar choices, most decisions we face can be classified as multi-attribute choices. In order to evaluate and make choices in such an environment, we must be able to estimate and weight the particular attributes of an option. Hence, better understanding the mechanisms involved in this process is an important step for economists and psychologists. For example, when choosing between two meals that differ in taste and nutrition, what are the mechanisms that allow us to estimate and then weight attributes when constructing value? Furthermore, how can these mechanisms be influenced by variables such as attention or common physiological states, like hunger?

In order to investigate these and similar questions, we use a combination of choice and attentional data, where the attentional data was collected by recording eye movements as individuals made decisions. Chapter 1 designs and tests a neuroeconomic model of multi-attribute choice that makes predictions about choices, response time, and how these variables are correlated with attention. Chapter 2 applies the ideas in this model to intertemporal decision-making, and finds that attention causally affects discount rates. Chapter 3 explores how hunger, a common physiological state, alters the mechanisms we utilize as we make simple decisions about foods.

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Many applications in cosmology and astrophysics at millimeter wavelengths including CMB polarization, studies of galaxy clusters using the Sunyaev-Zeldovich effect (SZE), and studies of star formation at high redshift and in our local universe and our galaxy, require large-format arrays of millimeter-wave detectors. Feedhorn and phased-array antenna architectures for receiving mm-wave light present numerous advantages for control of systematics, for simultaneous coverage of both polarizations and/or multiple spectral bands, and for preserving the coherent nature of the incoming light. This enables the application of many traditional "RF" structures such as hybrids, switches, and lumped-element or microstrip band-defining filters.

Simultaneously, kinetic inductance detectors (KIDs) using high-resistivity materials like titanium nitride are an attractive sensor option for large-format arrays because they are highly multiplexable and because they can have sensitivities reaching the condition of background-limited detection. A KID is a LC resonator. Its inductance includes the geometric inductance and kinetic inductance of the inductor in the superconducting phase. A photon absorbed by the superconductor breaks a Cooper pair into normal-state electrons and perturbs its kinetic inductance, rendering it a detector of light. The responsivity of KID is given by the fractional frequency shift of the LC resonator per unit optical power.

However, coupling these types of optical reception elements to KIDs is a challenge because of the impedance mismatch between the microstrip transmission line exiting these architectures and the high resistivity of titanium nitride. Mitigating direct absorption of light through free space coupling to the inductor of KID is another challenge. We present a detailed titanium nitride KID design that addresses these challenges. The KID inductor is capacitively coupled to the microstrip in such a way as to form a lossy termination without creating an impedance mismatch. A parallel plate capacitor design mitigates direct absorption, uses hydrogenated amorphous silicon, and yields acceptable noise. We show that the optimized design can yield expected sensitivities very close to the fundamental limit for a long wavelength imager (LWCam) that covers six spectral bands from 90 to 400 GHz for SZE studies.

Excess phase (frequency) noise has been observed in KID and is very likely caused by two-level systems (TLS) in dielectric materials. The TLS hypothesis is supported by the measured dependence of the noise on resonator internal power and temperature. However, there is still a lack of a unified microscopic theory which can quantitatively model the properties of the TLS noise. In this thesis we derive the noise power spectral density due to the coupling of TLS with phonon bath based on an existing model and compare the theoretical predictions about power and temperature dependences with experimental data. We discuss the limitation of such a model and propose the direction for future study.

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Morphogenesis is a phenomenon of intricate balance and dynamic interplay between processes occurring at a wide range of scales (spatial, temporal and energetic). During development, a variety of physical mechanisms are employed by tissues to simultaneously pattern, move, and differentiate based on information exchange between constituent cells, perhaps more than at any other time during an organism's life. To fully understand such events, a combined theoretical and experimental framework is required to assist in deciphering the correlations at both structural and functional levels at scales that include the intracellular and tissue levels as well as organs and organ systems. Microscopy, especially diffraction-limited light microscopy, has emerged as a central tool to capture the spatio-temporal context of life processes. Imaging has the unique advantage of watching biological events as they unfold over time at single-cell resolution in the intact animal. In this work I present a range of problems in morphogenesis, each unique in its requirements for novel quantitative imaging both in terms of the technique and analysis. Understanding the molecular basis for a developmental process involves investigating how genes and their products- mRNA and proteins-function in the context of a cell. Structural information holds the key to insights into mechanisms and imaging fixed specimens paves the first step towards deciphering gene function. The work presented in this thesis starts with the demonstration that the fluorescent signal from the challenging environment of whole-mount imaging, obtained by in situ hybridization chain reaction (HCR), scales linearly with the number of copies of target mRNA to provide quantitative sub-cellular mapping of mRNA expression within intact vertebrate embryos. The work then progresses to address aspects of imaging live embryonic development in a number of species. While processes such as avian cartilage growth require high spatial resolution and lower time resolution, dynamic events during zebrafish somitogenesis require higher time resolution to capture the protein localization as the somites mature. The requirements on imaging are even more stringent in case of the embryonic zebrafish heart that beats with a frequency of ~ 2-2.5 Hz, thereby requiring very fast imaging techniques based on two-photon light sheet microscope to capture its dynamics. In each of the hitherto-mentioned cases, ranging from the level of molecules to organs, an imaging framework is developed, both in terms of technique and analysis to allow quantitative assessment of the process in vivo. Overall the work presented in this thesis combines new quantitative tools with novel microscopy for the precise understanding of processes in embryonic development.

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Frequency resolved optical gating (FROG), is an effective technique for characterizing the ultrafast laser pulses. The multi-shot second harmonic generation (SHG) FROG is the most sensitive one in different FROGs. In this paper we use this technique to measure the femtosecond optical pulses generated by a conventional Ti:sapphire oscillator.

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In recent years, the performance of semi-supervised learning has been theoretically investigated. However, most of this theoretical development has focussed on binary classification problems. In this paper, we take it a step further by extending the work of Castelli and Cover [1] [2] to the multi-class paradigm. Particularly, we consider the key problem in semi-supervised learning of classifying an unseen instance x into one of K different classes, using a training dataset sampled from a mixture density distribution and composed of l labelled records and u unlabelled examples. Even under the assumption of identifiability of the mixture and having infinite unlabelled examples, labelled records are needed to determine the K decision regions. Therefore, in this paper, we first investigate the minimum number of labelled examples needed to accomplish that task. Then, we propose an optimal multi-class learning algorithm which is a generalisation of the optimal procedure proposed in the literature for binary problems. Finally, we make use of this generalisation to study the probability of error when the binary class constraint is relaxed.

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An optical communication scheme of 2-D pattern transfer based on imaging optics for submarine laser uplink communication (SLUC) is suggested. Unlike the methods aiming at avoiding neighboring crosstalk used in traditional multi-channel optical beam transferring, we make full use of the overlapping of each spreading beam other than controlling divergence effect of each beam to avoid interference noise. The apparent parameters have been introduced to simplify theoretical analysis of optical pattern transfer problem involving underwater condition, with the help of which the complex beam propagation inside two kinds of mediums can be easily reduced to brief beam transfer only inside air medium. In this paper, optical transmission path and receiver terminal optics geometry have been described in detail. The link range equation and system uplink performance analysis have also been given. At last, results of a proof-of-concept experiment indicate good feasibility of the proposed SLUC model. © 2007 Elsevier GmbH. All rights reserved.