Electron g factors and optical properties of InAs quantum ellipsoids

The electronic structure, electron g factors and optical properties of InAs quantum ellipsoids are investigated, in the framework of the eight-band effective-mass approximation. It is found that the light-hole states come down in comparison with the heavy-hole states when the spheres are elongated, and become the lowest states of the valence band. Circularly polarized emissions under circularly polarized excitations may have opposite polarization factors to the exciting light. For InAs ellipsoids the length, which is smaller than 35 nm, is still in a strongly quantum-confined regime. The electron g factors of InAs spheres decrease with increasing radius, and are nearly 2 when the radius is very small. The quantization of the electron states quenches the orbital angular momentum of the states. Actually, as some of the three dimensions increase, the electron g factors decrease. As more dimensions increase, the g factors decrease more. The dimensions perpendicular to the direction of the magnetic field affect the g factors more than the other dimension. The magnetic field along the z axis of the crystal structure causes linearly polarized emissions in the spheres, which emit unpolarized light in the absence of magnetic field.

Learning Fine Motion by Markov Mixtures of Experts

Compliant control is a standard method for performing fine manipulation tasks, like grasping and assembly, but it requires estimation of the state of contact between the robot arm and the objects involved. Here we present a method to learn a model of the movement from measured data. The method requires little or no prior knowledge and the resulting model explicitly estimates the state of contact. The current state of contact is viewed as the hidden state variable of a discrete HMM. The control dependent transition probabilities between states are modeled as parametrized functions of the measurement We show that their parameters can be estimated from measurements concurrently with the estimation of the parameters of the movement in each state of contact. The learning algorithm is a variant of the EM procedure. The E step is computed exactly; solving the M step exactly would require solving a set of coupled nonlinear algebraic equations in the parameters. Instead, gradient ascent is used to produce an increase in likelihood.

Analysis of classification accuracy for pre-filtered multichannel remote sensing data

Noise is one of the main factors degrading the quality of original multichannel remote sensing data and its presence influences classification efficiency, object detection, etc. Thus, pre-filtering is often used to remove noise and improve the solving of final tasks of multichannel remote sensing. Recent studies indicate that a classical model of additive noise is not adequate enough for images formed by modern multichannel sensors operating in visible and infrared bands. However, this fact is often ignored by researchers designing noise removal methods and algorithms. Because of this, we focus on the classification of multichannel remote sensing images in the case of signal-dependent noise present in component images. Three approaches to filtering of multichannel images for the considered noise model are analysed, all based on discrete cosine transform in blocks. The study is carried out not only in terms of conventional efficiency metrics used in filtering (MSE) but also in terms of multichannel data classification accuracy (probability of correct classification, confusion matrix). The proposed classification system combines the pre-processing stage where a DCT-based filter processes the blocks of the multichannel remote sensing image and the classification stage. Two modern classifiers are employed, radial basis function neural network and support vector machines. Simulations are carried out for three-channel image of Landsat TM sensor. Different cases of learning are considered: using noise-free samples of the test multichannel image, the noisy multichannel image and the pre-filtered one. It is shown that the use of the pre-filtered image for training produces better classification in comparison to the case of learning for the noisy image. It is demonstrated that the best results for both groups of quantitative criteria are provided if a proposed 3D discrete cosine transform filter equipped by variance stabilizing transform is applied. The classification results obtained for data pre-filtered in different ways are in agreement for both considered classifiers. Comparison of classifier performance is carried out as well. The radial basis neural network classifier is less sensitive to noise in original images, but after pre-filtering the performance of both classifiers is approximately the same.

Fatores associados ao controle metabólico em pacientes com diabetes melito tipo 2 não usuários de insulina

Introdução: a obtenção de um bom controle metabólico é essencial para a prevenção das complicações crônicas do Diabetes Melito (DM). O tratamento é complexo e depende da implementação efetiva das diferentes estratégias terapêuticas disponíveis. Para que isso seja possível, é necessário que o paciente entenda os princípios terapêuticos e consiga executá-los. A precária educação em diabetes é percebida como um dos obstáculos para o alcance das metas terapêuticas. Objetivo: analisar, os fatores associados ao controle metabólico, em pacientes com DM tipo 2 (DM2) não usuários de insulina. Métodos: foi realizado um estudo transversal em pacientes com DM2 não usuários de insulina, selecionados ao acaso entre aqueles que consultavam nos ambulatórios de Medicina Interna, Endocrinologia e Enfermagem do Hospital de Clínicas de Porto Alegre. Os pacientes foram submetidos à avaliação clínica, laboratorial e responderam um questionário que incluía o tipo de tratamento realizado para DM, outros medicamentos e co-morbidades, pesquisa de complicações em ano prévio e avaliação do conhecimento sobre DM. Os pacientes foram classificados em dois grupos, com bom ou mau controle glicêmico, de acordo com o valor da glico-hemoglobina de 1 ponto % acima do limite superior do método utilizado. As comparações entre variáveis contínuas, com distribuição normal, foram analisadas pelo teste t de Student para amostras não-pareadas e para as variáveis de distribuição assimétrica ou com variância heterogênea o teste U de Mann-Whitney. A comparação entre percentagem foi feita pelo teste de qui-quadrado ou exato de Fisher. Foi realizada uma análise logística múltipla para identificar os fatores mais relevantes associados ao controle metabólico (variável dependente). As variáveis independentes com um nível de significância de P < 0,1 na análise bivariada, foram incluídas no modelo. Resultados: foram avaliados 143 pacientes com DM2, idade de 59,3 ± 10,1 anos, duração conhecida do DM 7,5 ± 6,3 anos, índice de massa corporal (IMC) de 29,7 ± 5,2 kg/m².Destes, 94 pacientes (65,73%) apresentavam bom controle glicêmico. Os pacientes com mau controle glicêmico usavam mais anti-hiperglicemiantes orais como monoterapia (OR = 9,37; IC = 2,60-33,81; P=0,004) ou associados (OR = 31,08; IC = 7,42-130,15; P < 0,001). Da mesma maneira, não fizeram dieta em dias de festa (OR = 3,29; IC = 1,51-7,16; P = 0,012). A inclusão do conhecimento sobre diabetes não foi diferente entre os pacientes com bom ou mau controle glicêmico (OR = 1,08; IC = 0,97 - 1,21; P = 0,219). A análise multivariada demonstrou que a consulta com a enfermeira educadora (OR = 0,24; IC = 0,108-0,534; P = 0,003), com o endocrinologista (OR = 0,15 ; IC = 0,063-0,373; P = 0,001) e o uso de hipolipemiantes (OR = 0,10; IC = 0,016 - 0,72; P = 0,054) foram associados ao bom controle glicêmico, ajustados para a não realização de dieta em festas, uso de anti-hiperglicemiantes orais e conhecimento sobre diabetes. Conclusão: o controle metabólico em pacientes DM2 é influenciado pelas atividades de educação com enfermeira e endocrinologista. O tratamento do DM2 deve incluir atividades de educação de forma sistemática.

Desenvolvimento de uma metodologia para elaboração de modelos de predição dos níveis de ruído do campo acústico de usinas hidrelétricas

Pós-graduação em Engenharia Mecânica - FEIS

Desenvolvimento de uma metodologia para elaboração de modelos de predição dos níveis de ruído do campo acústico de usinas hidrelétricas

Pós-graduação em Engenharia Mecânica - FEIS

Reconhecimento da perda de eficácia de protetor intra-auricular

Among the harmful health agents, it is given to the noise, one of the most present in urban and social environments. There are efficient measures to control the noise and the auricular Individual Protection Equipment (IPEa) is the most used. It has been observed the shortage in the comfortable and functional individual auditory protection products, related to durability, face to the efficiency right of the equipment. The main objective of this study was to recognize if there is effectiveness loss toward the used time on the Auditory Equipment, intra-auricular Individual Protection, of foam (3M), model 1110. It has been verified that the equipments suffer efficiency alteration according to the time of use, and the material consuming initiates reliable loss, mainly in audible frequencies going up to 100Hz, and from 16 days for sonorous pressure suffered started in 101dB 20Hz. For sonorous pressure suffered from 107dB to 20Hz, the reliable loss for the usage was of 8 days. The IPEas do not lose effectiveness on important attenuation by the daily use in frequencies from 1KHz until 20KHz. It has been concluded that there is effectiveness loss, according to the daily and frequent use of the IPEa studied.

Soluciones constructivas frente al ruido

En el presente proyecto, se han abordado las distintas soluciones constructivas para tratar las principales exigencias en edificación: aislamiento acústico, acondicionamiento acústico y ruido y vibraciones de las instalaciones. Estas soluciones constructivas, se enmarcan dentro de un conjunto de leyes vigentes en España, provenientes de la trasposición de la legislación Europea. Basándose en el Documento Básico HR Protección frente al ruido, donde se encuentran las soluciones constructivas, comentadas anteriormente, se ha llevado a cabo un estudio exhaustivo de las mismas, con la finalidad de crear una herramienta de consulta de fácil y rápido acceso para cualquier persona. En especial, se enfoca a una finalidad didáctica accesible al personal universitario. Se pretende que cualquier persona, con base mínima en la materia, pueda acceder y entender la herramienta creada. Para lograr a esta finalidad, se ha analizado otra documentación, como la Guía de aplicación del DB HR, donde se explica de forma más detallada el Documento Básico HR Protección frente al ruido. Además, se han consultado diferentes normativas españolas, para conseguir que la información aportada al usuario sea completa y no sea necesario acudir a diferentes documentos externos. De esta manera, un usuario podrá realizar un proyecto para: aislar, acondicionar o controlar el ruido y vibraciones de las instalaciones, en una edificación, acudiendo a esta herramienta. Con el objeto de que sea un proyecto enmarcado en un contexto didáctico, con fácil acceso y tratando que sea lo más intuitivo posible, se buscó una plataforma de acceso gratuito y disponible para distintos equipos y sistemas operativos. El programa empleado ha sido tomado del paquete Office creado por Microsoft. El programa se denomina OneNote. Se trata de un programa para realizar, compartir y gestionar notas de forma rápida y sencilla. Los archivos creados en él, se almacenan en OneDrive, por lo tanto, el usuario puede acceder a ellos desde cualquier parte, en cualquier momento y plataforma disponible. ABSTRACT. The aforementioned project approaches the diverse solutions available to accomplish the chief edification requirements in the Spanish Legal System, remarkably influenced by the European Law, in Construction Planning. The key elements of those solutions are acoustic isolation, acoustic conditioning and noise and vibration of installations. Basing most part of our research in the academic report “Documento Básico HR Protección frente al ruido”, which addresses effective solutions about the mentioned queries, but also implements a useful tool that supplies access to the broad public to obtain a wide variety of answers regarding those issues. Its main aim is to improve the knowledge about that subject, however also the access and usage to that system, of every person, although its previous experience. In order to achieve that purpose, the paper also combines an analysis of the study “Guía de aplicación del DB HR” where different elements of the report “Documento Básico HR Protección frente al ruido” are examined in further detail. It is important to remark that all the information provided comply with the current legislation present in Spain at the time this paper was written, so the reader may work on a project of isolation, conditioning or control of noise and vibrations of installations without the requirement of applying external resources. Conclusively, with the intention of giving the paper an educational usage, with intuitive and easy access, the reader is able to join to the platform OneNote by Microsoft Office, software available in utmost part of operating systems and devices. This program allows us to produce, share and manage notes swiftly and efficiently, but also it stores them in The Cloud called OneDrive, so the user can get access to them anywhere and anytime.

Methods for reducing large speed differences in traffic streams. Volume I - inventory of methods. Task A report.

Federal Highway Administration, Office of Safety and Traffic Operations Research and Development, Washington, D.C.

Economic impact of removing numerical limits on sound emissions to class C land, R76-19 /

"Project no. 30.014."

Outlier detection in scatterometer data:Neural network approaches

Satellite-borne scatterometers are used to measure backscattered micro-wave radiation from the ocean surface. This data may be used to infer surface wind vectors where no direct measurements exist. Inherent in this data are outliers owing to aberrations on the water surface and measurement errors within the equipment. We present two techniques for identifying outliers using neural networks; the outliers may then be removed to improve models derived from the data. Firstly the generative topographic mapping (GTM) is used to create a probability density model; data with low probability under the model may be classed as outliers. In the second part of the paper, a sensor model with input-dependent noise is used and outliers are identified based on their probability under this model. GTM was successfully modified to incorporate prior knowledge of the shape of the observation manifold; however, GTM could not learn the double skinned nature of the observation manifold. To learn this double skinned manifold necessitated the use of a sensor model which imposes strong constraints on the mapping. The results using GTM with a fixed noise level suggested the noise level may vary as a function of wind speed. This was confirmed by experiments using a sensor model with input-dependent noise, where the variation in noise is most sensitive to the wind speed input. Both models successfully identified gross outliers with the largest differences between models occurring at low wind speeds. © 2003 Elsevier Science Ltd. All rights reserved.

Contrast matching and discrimation in human vision

The aim of this work was to investigate human contrast perception at various contrast levels ranging from detection threshold to suprathreshold levels by using psychophysical techniques. The work consists of two major parts. The first part deals with contrast matching, and the second part deals with contrast discrimination. Contrast matching technique was used to determine when the perceived contrasts of different stimuli were equal. The effects of spatial frequency, stimulus area, image complexity and chromatic contrast on contrast detection thresholds and matches were studied. These factors influenced detection thresholds and perceived contrast at low contrast levels. However, at suprathreshold contrast levels perceived contrast became directly proportional to the physical contrast of the stimulus and almost independent of factors affecting detection thresholds. Contrast discrimination was studied by measuring contrast increment thresholds which indicate the smallest detectable contrast difference. The effects of stimulus area, external spatial image noise and retinal illuminance were studied. The above factors affected contrast detection thresholds and increment thresholds measured at low contrast levels. At high contrast levels, contrast increment thresholds became very similar so that the effect of these factors decreased. Human contrast perception was modelled by regarding the visual system as a simple image processing system. A visual signal is first low-pass filtered by the ocular optics. This is followed by spatial high-pass filtering by the neural visual pathways, and addition of internal neural noise. Detection is mediated by a local matched filter which is a weighted replica of the stimulus whose sampling efficiency decreases with increasing stimulus area and complexity. According to the model, the signals to be compared in a contrast matching task are first transferred through the early image processing stages mentioned above. Then they are filtered by a restoring transfer function which compensates for the low-level filtering and limited spatial integration at high contrast levels. Perceived contrasts of the stimuli are equal when the restored responses to the stimuli are equal. According to the model, the signals to be discriminated in a contrast discrimination task first go through the early image processing stages, after which signal dependent noise is added to the matched filter responses. The decision made by the human brain is based on the comparison between the responses of the matched filters to the stimuli, and the accuracy of the decision is limited by pre- and post-filter noises. The model for human contrast perception could accurately describe the results of contrast matching and discrimination in various conditions.

UNDERSTANDING CHASSIS INPUTS FROM THE REAR SUSPENSION OF A SNOWMOBILE

Today’s snowmobile industry faces great challenges in the field of noise & vibration. The area of main concern is the pass-by noise restriction defined by the Society of Automotive Engineers (SAE) test standard J192, with a maximum sound pressure level of 78 dB(A) being required by many states and national parks. To continue meet or beat this requirement without effecting machine performance, a deeper understanding of the sound transfer paths is required. This thesis examines the transfer paths created by the tunnel, rear suspension, drive shaft, and rubber composite track, with the primary source being suspension input through the ground. Using a combination of field experiments and analytical modeling, perspective was gained on which suspension and drive elements create the primary transfer paths. With further understanding of these paths, industry can tailor and fine-tune the approaches taken in to control overall noise output.