Nested Sampling and its Applications in Stable Compressive Covariance Estimation and Phase Retrieval with Near-Minimal Measurements

Compressed covariance sensing using quadratic samplers is gaining increasing interest in recent literature. Covariance matrix often plays the role of a sufficient statistic in many signal and information processing tasks. However, owing to the large dimension of the data, it may become necessary to obtain a compressed sketch of the high dimensional covariance matrix to reduce the associated storage and communication costs. Nested sampling has been proposed in the past as an efficient sub-Nyquist sampling strategy that enables perfect reconstruction of the autocorrelation sequence of Wide-Sense Stationary (WSS) signals, as though it was sampled at the Nyquist rate. The key idea behind nested sampling is to exploit properties of the difference set that naturally arises in quadratic measurement model associated with covariance compression. In this thesis, we will focus on developing novel versions of nested sampling for low rank Toeplitz covariance estimation, and phase retrieval, where the latter problem finds many applications in high resolution optical imaging, X-ray crystallography and molecular imaging. The problem of low rank compressive Toeplitz covariance estimation is first shown to be fundamentally related to that of line spectrum recovery. In absence if noise, this connection can be exploited to develop a particular kind of sampler called the Generalized Nested Sampler (GNS), that can achieve optimal compression rates. In presence of bounded noise, we develop a regularization-free algorithm that provably leads to stable recovery of the high dimensional Toeplitz matrix from its order-wise minimal sketch acquired using a GNS. Contrary to existing TV-norm and nuclear norm based reconstruction algorithms, our technique does not use any tuning parameters, which can be of great practical value. The idea of nested sampling idea also finds a surprising use in the problem of phase retrieval, which has been of great interest in recent times for its convex formulation via PhaseLift, By using another modified version of nested sampling, namely the Partial Nested Fourier Sampler (PNFS), we show that with probability one, it is possible to achieve a certain conjectured lower bound on the necessary measurement size. Moreover, for sparse data, an l1 minimization based algorithm is proposed that can lead to stable phase retrieval using order-wise minimal number of measurements.

Texture-Detail Preservation Measurement in Camera Phones: An Updated Approach

Recent advances in mobile phone cameras have poised them to take over compact hand-held cameras as the consumer’s preferred camera option. Along with advances in the number of pixels, motion blur removal, face-tracking, and noise reduction algorithms have significant roles in the internal processing of the devices. An undesired effect of severe noise reduction is the loss of texture (i.e. low-contrast fine details) of the original scene. Current established methods for resolution measurement fail to accurately portray the texture loss incurred in a camera system. The development of an accurate objective method to identify the texture preservation or texture reproduction capability of a camera device is important in this regard. The ‘Dead Leaves’ target has been used extensively as a method to measure the modulation transfer function (MTF) of cameras that employ highly non-linear noise-reduction methods. This stochastic model consists of a series of overlapping circles with radii r distributed as r−3, and having uniformly distributed gray level, which gives an accurate model of occlusion in a natural setting and hence mimics a natural scene. This target can be used to model the texture transfer through a camera system when a natural scene is captured. In the first part of our study we identify various factors that affect the MTF measured using the ‘Dead Leaves’ chart. These include variations in illumination, distance, exposure time and ISO sensitivity among others. We discuss the main differences of this method with the existing resolution measurement techniques and identify the advantages. In the second part of this study, we propose an improvement to the current texture MTF measurement algorithm. High frequency residual noise in the processed image contains the same frequency content as fine texture detail, and is sometimes reported as such, thereby leading to inaccurate results. A wavelet thresholding based denoising technique is utilized for modeling the noise present in the final captured image. This updated noise model is then used for calculating an accurate texture MTF. We present comparative results for both algorithms under various image capture conditions.

Mutual Information-based RBM Neural Networks

(Deep) neural networks are increasingly being used for various computer vision and pattern recognition tasks due to their strong ability to learn highly discriminative features. However, quantitative analysis of their classication ability and design philosophies are still nebulous. In this work, we use information theory to analyze the concatenated restricted Boltzmann machines (RBMs) and propose a mutual information-based RBM neural networks (MI-RBM). We develop a novel pretraining algorithm to maximize the mutual information between RBMs. Extensive experimental results on various classication tasks show the eectiveness of the proposed approach.

Railgun

Com a presente evolução das railguns na Marinha dos Estados Unidos da América e possível instalação em seus navios num futuro muito próximo, outras marinhas se seguirão. Creio que será do interesse da Marinha Portuguesa acompanhar esta evolução tecnológica, considerando as vantagens que advém da adoção deste tipo de armamento. Neste documento são abordados os princípios básicos subjacentes ao funcionamento da railgun, com principal foco nas questões eletrodinâmicas. Pretende-se adquirir familiaridade com este novo tipo de armamento através do estudo crítico dos seus princípios de funcionamento. O princípio básico de funcionamento de uma railgun, à primeira vista, parece bastante simples, à luz da aplicação imediata da expressão da força de Lorentz sobre um condutor percorrido por corrente elétrica. No entanto, tudo se torna mais complicado no caso de uma variação rápida dos parâmetros envolvidos (regime transitório), que exige uma análise mais aprofundada do comportamento da corrente, campos elétrico e magnético, e todos os materiais envolvidos neste sistema. Este trabalho envolveu ainda a construção de duas railguns, uma primeira de dimensões mais pequenas para ganhar familiaridade com o sistema, e uma última de dimensões de laboratório na qual foram feitos vários disparos para testar diferentes tipos de material e dimensões de projétil. Em suma, é demonstrado neste documento uma análise, no domínio do tempo, da distribuição espacial do campo eletromagnético, corrente elétrica e consequente fluxo de energia, complementados por uma parte experimental.

The Amplifier - v. 13, Supplement (75th Anniversary)

In this issue...75th Anniversary, School of Mines Building, Electrical Engineer, Leonard Field, Library Renovation, Research Complex, Montana Tech Booster Club

Safe operation of transmission system considering EV at distribution level

In this paper, the IEEE 14 bus test system is used in order to perform adequacy assessment of a transmission system when large scale integration of electric vehicles is considered at distribution levels. In this framework, the symmetric/constr ained fuzzy power flow (SFPF/CFPF) was proposed. The SFPF/CFPF models are suitable to quantify the adequacy of transmission network to satisfy “reasonable demands for the transmission of electricity” as defined, for instance, in the European Directive 2009/72/EC. In this framework, electric vehicles of different types will be treated as fuzzy loads configuring part of the “reasonable demands”. With this study, it is also intended to show how to evaluate the amount of EVs that can be safely accommodated to the grid meeting a certain adequacy level.

A practical MEMS gravimeter

The ability to measure tiny variations in the local gravitational acceleration allows – amongst other applications – the detection of hidden hydrocarbon reserves, magma build-up before volcanic eruptions, and subterranean tunnels. Several technologies are available that achieve the sensitivities required (tens of μGal/√Hz), and stabilities required (periods of days to weeks) for such applications: free-fall gravimeters, spring-based gravimeters, superconducting gravimeters, and atom interferometers. All of these devices can observe the Earth tides; the elastic deformation of the Earth’s crust as a result of tidal forces. This is a universally predictable gravitational signal that requires both high sensitivity and high stability over timescales of several days to measure. All present gravimeters, however, have limitations of excessive cost (£70 k) and high mass (<8 kg). In this thesis, the building of a microelectromechanical system (MEMS) gravimeter with a sensitivity of 40 μGal/√Hz in a package size of only a few cubic centimetres is discussed. MEMS accelerometers – found in most smart phones – can be mass-produced remarkably cheaply, but most are not sensitive enough, and none have been stable enough to be called a ‘gravimeter’. The remarkable stability and sensitivity of the device is demonstrated with a measurement of the Earth tides. Such a measurement has never been undertaken with a MEMS device, and proves the long term stability of the instrument compared to any other MEMS device, making it the first MEMS accelerometer that can be classed as a gravimeter. This heralds a transformative step in MEMS accelerometer technology. Due to their small size and low cost, MEMS gravimeters could create a new paradigm in gravity mapping: exploration surveys could be carried out with drones instead of low-flying aircraft; they could be used for distributed land surveys in exploration settings, for the monitoring of volcanoes; or built into multi-pixel density contrast imaging arrays.

An Artificial Intelligence Approach to Dyscalculia

Dyscalculia stands for a brain-based condition that makes it hard to make sense of numbers and mathematical concepts. Some adolescents with dyscalculia cannot grasp basic number concepts. They work hard to learn and memorize basic number facts. They may know what to do in mathematical classes but do not understand why they are doing it. In other words, they miss the logic behind it. However, it may be worked out in order to decrease its degree of severity. For example, disMAT, an app developed for android may help children to apply mathematical concepts, without much effort, that is turning in itself, a promising tool to dyscalculia treatment. Thus, this work focuses on the development of an Intelligent System to estimate children evidences of dyscalculia, based on data obtained on-the-fly with disMAT. The computational framework is built on top of a Logic Programming framework to Knowledge Representation and Reasoning, complemented with a Case-Based problem solving approach to computing, that allows for the handling of incomplete, unknown, or even contradictory information.

Study of the Electromagnetic Interference Generated by Wireless Power Transfer Systems

This paper presents a study related with measuring of radio frequency emissions. The purpose is to determine the level of interference generated by wireless power transfer equipment in a specific frequency range, and to compare those levels to the existing standards. The technology of wireless power transfer, especially for electric vehicles batteries charging, is rapidly developing in the recent years. An increasing use of this technology in industrial and consumer electronic products has raised concerns about the possible unfavorable health-effects onto the human being. Another concern is raised from the high intensity fields produced by wireless power transfer systems which will generate highly undesired influence on other electrical and electronic equipment. As a protection against the potential health effects, the governments imposed limits on the occupational and general public exposure to the radio frequencies. These limitations are set out in national and international safety guidelines, standards and regulations. The measurement and evaluation of the human exposure to electromagnetic fields are essential to guarantee occupational and general public safety.

A fuzzy clustering approach to a demand response model

This paper proposes a novel demand response model using a fuzzy subtractive cluster approach. The model development provides support to domestic consumer decisions on controllable loads management, considering consumers’ consumption needs and the appropriate load shape or rescheduling in order to achieve possible economic benefits. The model based on fuzzy subtractive clustering method considers clusters of domestic consumption covering an adequate consumption range. Analysis of different scenarios is presented considering available electric power and electric energy prices. Simulation results are presented and conclusions of the proposed demand response model are discussed.

Towards Improving the Academic Bodies of FIME in the Autonomous University of Nuevo León, México

This paper refers to a crucial issue for higher education institutions.  In Mexico, particularly, the collective work of academic bodies is an unresolved issue despite the efforts made in this regard. In this context, a well-founded systematic discussion is essential to understand the potential of these academic bodies on faculty strengthening and their subsequent impact on the quality of education. This paper presents the results of a research project conducted by FIME  with the purpose of identifying the characteristics of its academic bodies as well as their current and potential condition. (1) Translator’s Note: FIME refers to the Facultad de Ingeniería Mecánica y Eléctrica (College of Mechanical and Electrical Engineering).

Nanocrystalline Ge Flash Memories: Electrical Characterization and Trap Engineering

Conventional floating gate non-volatile memories (NVMs) present critical issues for device scalability beyond the sub-90 nm node, such as gate length and tunnel oxide thickness reduction. Nanocrystalline germanium (nc-Ge) quantum dot flash memories are fully CMOS compatible technology based on discrete isolated charge storage nodules which have the potential of pushing further the scalability of conventional NVMs. Quantum dot memories offer lower operating voltages as compared to conventional floating-gate (FG) Flash memories due to thinner tunnel dielectrics which allow higher tunneling probabilities. The isolated charge nodules suppress charge loss through lateral paths, thereby achieving a superior charge retention time. Despite the considerable amount of efforts devoted to the study of nanocrystal Flash memories, the charge storage mechanism remains obscure. Interfacial defects of the nanocrystals seem to play a role in charge storage in recent studies, although storage in the nanocrystal conduction band by quantum confinement has been reported earlier. In this work, a single transistor memory structure with threshold voltage shift, Vth, exceeding ~1.5 V corresponding to interface charge trapping in nc-Ge, operating at 0.96 MV/cm, is presented. The trapping effect is eliminated when nc-Ge is synthesized in forming gas thus excluding the possibility of quantum confinement and Coulomb blockade effects. Through discharging kinetics, the model of deep level trap charge storage is confirmed. The trap energy level is dependent on the matrix which confines the nc-Ge.

A combined engineering and statistical model of UK domestic appliance electrical load profiles

The development of a combined engineering and statistical Artificial Neural Network model of UK domestic appliance load profiles is presented. The model uses diary-style appliance use data and a survey questionnaire collected from 51 suburban households and 46 rural households during the summer of 2010 and2011 respectively. It also incorporates measured energy data and is sensitive to socioeconomic, physical dwelling and temperature variables. A prototype model is constructed in MATLAB using a two layer feed forward network with back propagation training which has a 12:10:24 architecture. Model outputs include appliance load profiles which can be applied to the fields of energy planning (microrenewables and smart grids), building simulation tools and energy policy.

Orientation dependence of stored energy of cold work in semi-processed electrical steels after temper rolling

Microhardness measurements were carried out in a low carbon lamination steel after 6% of temper rolling, in order to evaluate local variations of work hardening as a function of crystallographic orientation. EBSD (electron back scattered diffraction) was used to determine grain orientations with respect to individual rolling planes and rolling directions. Hardness was shown to increase with the local Taylor factor. TEM observations and a well-known dislocation hardening model were used to confirm the equivalence between hardness values and the stored energy of cold work. A definite correlation between stored energy and Taylor factors could therefore be established, being more consistent than previous data reported in the literature. The improvement was thought to be related to the rather small plastic deformation, during which Taylor factors could be considered to remain constant. (c) 2006 Elsevier B.V. All rights reserved.