924 resultados para INTRINSIC NOISE
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This thesis concerns with the main aspects of medical trace molecules detection by means of intracavity laser absorption spectroscopy (ICLAS), namely with the equirements for highly sensitive, highly selective, low price, and compact size sensor. A novel two modes semiconductor laser sensor is demonstrated. Its operation principle is based on the competition between these two modes. The sensor sensitivity is improved when the sample is placed inside the two modes laser cavity, and the competition between the two modes exists. The effects of the mode competition in ICLAS are discussed theoretically and experimentally. The sensor selectivity is enhanced using external cavity diode laser (ECDL) configuration, where the tuning range only depends on the external cavity configuration. In order to considerably reduce the sensor cost, relative intensity noise (RIN) is chosen for monitoring the intensity ratio of the two modes. RIN is found to be an excellent indicator for the two modes intensity ratio variations which strongly supports the sensor methodology. On the other hand, it has been found that, wavelength tuning has no effect on the RIN spectrum which is very beneficial for the proposed detection principle. In order to use the sensor for medical applications, the absorption line of an anesthetic sample, propofol, is measured. Propofol has been dissolved in various solvents. RIN has been chosen to monitor the sensor response. From the measured spectra, the sensor sensitivity enhancement factor is found to be of the order of 10^(3) times of the conventional laser spectroscopy.
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Signalling off-chip requires significant current. As a result, a chip's power-supply current changes drastically during certain output-bus transitions. These current fluctuations cause a voltage drop between the chip and circuit board due to the parasitic inductance of the power-supply package leads. Digital designers often go to great lengths to reduce this "transmitted" noise. Cray, for instance, carefully balances output signals using a technique called differential signalling to guarantee a chip has constant output current. Transmitted-noise reduction costs Cray a factor of two in output pins and wires. Coding achieves similar results at smaller costs.
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Support Vector Machines Regression (SVMR) is a regression technique which has been recently introduced by V. Vapnik and his collaborators (Vapnik, 1995; Vapnik, Golowich and Smola, 1996). In SVMR the goodness of fit is measured not by the usual quadratic loss function (the mean square error), but by a different loss function called Vapnik"s $epsilon$- insensitive loss function, which is similar to the "robust" loss functions introduced by Huber (Huber, 1981). The quadratic loss function is well justified under the assumption of Gaussian additive noise. However, the noise model underlying the choice of Vapnik's loss function is less clear. In this paper the use of Vapnik's loss function is shown to be equivalent to a model of additive and Gaussian noise, where the variance and mean of the Gaussian are random variables. The probability distributions for the variance and mean will be stated explicitly. While this work is presented in the framework of SVMR, it can be extended to justify non-quadratic loss functions in any Maximum Likelihood or Maximum A Posteriori approach. It applies not only to Vapnik's loss function, but to a much broader class of loss functions.
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We enhance photographs shot in dark environments by combining a picture taken with the available light and one taken with the flash. We preserve the ambiance of the original lighting and insert the sharpness from the flash image. We use the bilateral filter to decompose the images into detail and large scale. We reconstruct the image using the large scale of the available lighting and the detail of the flash. We detect and correct flash shadows. This combines the advantages of available illumination and flash photography.
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This paper considers a connection between the deterministic and noisy behavior of nonlinear networks. Specifically, a particular bridge circuit is examined which has two possibly nonlinear energy storage elements. By proper choice of the constitutive relations for the network elements, the deterministic terminal behavior reduces to that of a single linear resistor. This reduction of the deterministic terminal behavior, in which a natural frequency of a linear circuit does not appear in the driving-point impedance, has been shown in classical circuit theory books (e.g. [1, 2]). The paper shows that, in addition to the reduction of the deterministic behavior, the thermal noise at the terminals of the network, arising from the usual Nyquist-Johnson noise model associated with each resistor in the network, is also exactly that of a single linear resistor. While this result for the linear time-invariant (LTI) case is a direct consequence of a well-known result for RLC circuits, the nonlinear result is novel. We show that the terminal noise current is precisely that predicted by the Nyquist-Johnson model for R if the driving voltage is zero or constant, but not if the driving voltage is time-dependent or the inductor and capacitor are time-varying
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This paper proposes three tests to determine whether a given nonlinear device noise model is in agreement with accepted thermodynamic principles. These tests are applied to several models. One conclusion is that every Gaussian noise model for any nonlinear device predicts thermodynamically impossible circuit behavior: these models should be abandoned. But the nonlinear shot-noise model predicts thermodynamically acceptable behavior under a constraint derived here. Further, this constraint specifies the current noise amplitude at each operating point from knowledge of the device v - i curve alone. For the Gaussian and shot-noise models, this paper shows how the thermodynamic requirements can be reduced to concise mathematical tests involving no approximatio
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A condition needed for testing nested hypotheses from a Bayesian viewpoint is that the prior for the alternative model concentrates mass around the small, or null, model. For testing independence in contingency tables, the intrinsic priors satisfy this requirement. Further, the degree of concentration of the priors is controlled by a discrete parameter m, the training sample size, which plays an important role in the resulting answer regardless of the sample size. In this paper we study robustness of the tests of independence in contingency tables with respect to the intrinsic priors with different degree of concentration around the null, and compare with other “robust” results by Good and Crook. Consistency of the intrinsic Bayesian tests is established. We also discuss conditioning issues and sampling schemes, and argue that conditioning should be on either one margin or the table total, but not on both margins. Examples using real are simulated data are given
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Resumen tomado de la publicaci??n
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El treball desenvolupat en aquesta tesi presenta un profund estudi i proveïx solucions innovadores en el camp dels sistemes recomanadors. Els mètodes que usen aquests sistemes per a realitzar les recomanacions, mètodes com el Filtrat Basat en Continguts (FBC), el Filtrat Col·laboratiu (FC) i el Filtrat Basat en Coneixement (FBC), requereixen informació dels usuaris per a predir les preferències per certs productes. Aquesta informació pot ser demogràfica (Gènere, edat, adreça, etc), o avaluacions donades sobre algun producte que van comprar en el passat o informació sobre els seus interessos. Existeixen dues formes d'obtenir aquesta informació: els usuaris ofereixen explícitament aquesta informació o el sistema pot adquirir la informació implícita disponible en les transaccions o historial de recerca dels usuaris. Per exemple, el sistema recomanador de pel·lícules MovieLens (http://movielens.umn.edu/login) demana als usuaris que avaluïn almenys 15 pel·lícules dintre d'una escala de * a * * * * * (horrible, ...., ha de ser vista). El sistema genera recomanacions sobre la base d'aquestes avaluacions. Quan els usuaris no estan registrat en el sistema i aquest no té informació d'ells, alguns sistemes realitzen les recomanacions tenint en compte l'historial de navegació. Amazon.com (http://www.amazon.com) realitza les recomanacions tenint en compte les recerques que un usuari a fet o recomana el producte més venut. No obstant això, aquests sistemes pateixen de certa falta d'informació. Aquest problema és generalment resolt amb l'adquisició d'informació addicional, se li pregunta als usuaris sobre els seus interessos o es cerca aquesta informació en fonts addicionals. La solució proposada en aquesta tesi és buscar aquesta informació en diverses fonts, específicament aquelles que contenen informació implícita sobre les preferències dels usuaris. Aquestes fonts poden ser estructurades com les bases de dades amb informació de compres o poden ser no estructurades com les pàgines web on els usuaris deixen la seva opinió sobre algun producte que van comprar o posseïxen. Nosaltres trobem tres problemes fonamentals per a aconseguir aquest objectiu: 1 . La identificació de fonts amb informació idònia per als sistemes recomanadors. 2 . La definició de criteris que permetin la comparança i selecció de les fonts més idònies. 3 . La recuperació d'informació de fonts no estructurades. En aquest sentit, en la tesi proposada s'ha desenvolupat: 1 . Una metodologia que permet la identificació i selecció de les fonts més idònies. Criteris basats en les característiques de les fonts i una mesura de confiança han estat utilitzats per a resoldre el problema de la identificació i selecció de les fonts. 2 . Un mecanisme per a recuperar la informació no estructurada dels usuaris disponible en la web. Tècniques de Text Mining i ontologies s'han utilitzat per a extreure informació i estructurar-la apropiadament perquè la utilitzin els recomanadors. Les contribucions del treball desenvolupat en aquesta tesi doctoral són: 1. Definició d'un conjunt de característiques per a classificar fonts rellevants per als sistemes recomanadors 2. Desenvolupament d'una mesura de rellevància de les fonts calculada sobre la base de les característiques definides 3. Aplicació d'una mesura de confiança per a obtenir les fonts més fiables. La confiança es definida des de la perspectiva de millora de la recomanació, una font fiable és aquella que permet millorar les recomanacions. 4. Desenvolupament d'un algorisme per a seleccionar, des d'un conjunt de fonts possibles, les més rellevants i fiable utilitzant les mitjanes esmentades en els punts previs. 5. Definició d'una ontologia per a estructurar la informació sobre les preferències dels usuaris que estan disponibles en Internet. 6. Creació d'un procés de mapatge que extreu automàticament informació de les preferències dels usuaris disponibles en la web i posa aquesta informació dintre de l'ontologia. Aquestes contribucions permeten aconseguir dos objectius importants: 1 . Millorament de les recomanacions usant fonts d'informació alternatives que sigui rellevants i fiables. 2 . Obtenir informació implícita dels usuaris disponible en Internet.
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A study of strial capillary permeability using fluorescent microspheres and immunohistochemistry in mice that do or do not exhibit a reduction in endocochlear potential following a single, intense noise exposure.
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This paper presents a curriculum in noise awareness developed for use in the second and fourth grades, to teach children about the harmful effects of elevated noise levels.
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This dissertation examines the frequency response that results in the maximum level of speech intelligibility for persons with noise-induced hearing loss.
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This paper discusses a study done to determine noise levels in operating rooms
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This study investigates the relation between physical measurements of pure-tones, third-octave bands of noise and third-octave bands of speech and subjective judgments of auditory threshold, most-comfortable listening level (MCL) and uncomfortable-listening level (UCL) for three normally hearing listeners.
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This paper describes a study assessing the sound levels and noise exposures of a municipal water treatment plant to determine the level of employee noise exposure dosages and to make any necessary recommendations regarding reducing the risk of noise induced hearing loss in employees.