Applications of Microwave Antenna Array for Wireless Power Transmission and Radar Imaging in Complex Environment

Thesis (Ph.D.)--University of Washington, 2016-08

Dithen: A Computation-as-a-Service Cloud Platform For Large-Scale Multimedia Processing

We present Dithen, a novel computation-as-a-service (CaaS) cloud platform specifically tailored to the parallel ex-ecution of large-scale multimedia tasks. Dithen handles the upload/download of both multimedia data and executable items, the assignment of compute units to multimedia workloads, and the reactive control of the available compute units to minimize the cloud infrastructure cost under deadline-abiding execution. Dithen combines three key properties: (i) the reactive assignment of individual multimedia tasks to available computing units according to availability and predetermined time-to-completion constraints; (ii) optimal resource estimation based on Kalman-filter estimates; (iii) the use of additive increase multiplicative decrease (AIMD) algorithms (famous for being the resource management in the transport control protocol) for the control of the number of units servicing workloads. The deployment of Dithen over Amazon EC2 spot instances is shown to be capable of processing more than 80,000 video transcoding, face detection and image processing tasks (equivalent to the processing of more than 116 GB of compressed data) for less than $1 in billing cost from EC2. Moreover, the proposed AIMD-based control mechanism, in conjunction with the Kalman estimates, is shown to provide for more than 27% reduction in EC2 spot instance cost against methods based on reactive resource estimation. Finally, Dithen is shown to offer a 38% to 500% reduction of the billing cost against the current state-of-the-art in CaaS platforms on Amazon EC2 (Amazon Lambda and Amazon Autoscale). A baseline version of Dithen is currently available at dithen.com.

The Museum of Atheism.

It is Christmas Eve in a mountainous, isolated prison community, the day of the baby beauty pageant. Ava is the star attraction. She's six years old. Ava's older brother Jonny hears strange noises in the attic and sees his father go out late at night with a gun with their lodger, prison warden Leo. Daniel, a man who repairs sex dolls for a living, has just moved into the area and he is Ava's biggest fan. There are rabid, wild foxes roaming the area, terrorising the community. The action culminates in a bizarre fetish party at the local strip club, a fox cull and the death of Ava. Finally, the secrets of her life are revealed.

Impact of Cryptosporidium spp. interaction with co-occurring microorganisms on moderate-to-severe diarrhea in the developing world

Diarrheal illness is responsible for over a quarter of all deaths in children under 5 years of age in sub-Saharan Africa and South Asia. Recent findings have identified the parasite Cryptosporidium as a contributor to enteric disease. We examined 9,348 cases and 13,128 controls from the Global Enteric Multicenter Study to assess whether Cryptosporidium interacted with co-occurring pathogens based on adjusted odds of moderate-to-severe diarrhea (MSD). Cryptosporidium was found to interact negatively with Shigella spp., with multiplicative interaction score of 0.16 (95% CI: 0.07 to 0.37, p-value=0.000), and an additive interaction score of -9.81 (95% CI: -13.61 to -6.01, p-value=0.000). Cryptosporidium also interacted negatively with Aeromonas spp., Adenovirus, Norovirus, and Astrovirus with marginal significance. Odds of MSD for Cryptosporidium co-infection with Shigella spp., Aeromonas spp., Adenovirus, Norovirus, or Astrovirus are lower than odds of MSD with either organism alone. This may reduce the efficacy of intervention strategies targeted at Cryptosporidium.

A simple but efficient voice activity detection algorithm through Hilbert transform and dynamic threshold for speech pathologies

A simple but efficient voice activity detector based on the Hilbert transform and a dynamic threshold is presented to be used on the pre-processing of audio signals -- The algorithm to define the dynamic threshold is a modification of a convex combination found in literature -- This scheme allows the detection of prosodic and silence segments on a speech in presence of non-ideal conditions like a spectral overlapped noise -- The present work shows preliminary results over a database built with some political speech -- The tests were performed adding artificial noise to natural noises over the audio signals, and some algorithms are compared -- Results will be extrapolated to the field of adaptive filtering on monophonic signals and the analysis of speech pathologies on futures works

Approximation Algorithms for Network Design and Orienteering

This thesis presents approximation algorithms for some NP-Hard combinatorial optimization problems on graphs and networks; in particular, we study problems related to Network Design. Under the widely-believed complexity-theoretic assumption that P is not equal to NP, there are no efficient (i.e., polynomial-time) algorithms that solve these problems exactly. Hence, if one desires efficient algorithms for such problems, it is necessary to consider approximate solutions: An approximation algorithm for an NP-Hard problem is a polynomial time algorithm which, for any instance of the problem, finds a solution whose value is guaranteed to be within a multiplicative factor of the value of an optimal solution to that instance. We attempt to design algorithms for which this factor, referred to as the approximation ratio of the algorithm, is as small as possible. The field of Network Design comprises a large class of problems that deal with constructing networks of low cost and/or high capacity, routing data through existing networks, and many related issues. In this thesis, we focus chiefly on designing fault-tolerant networks. Two vertices u,v in a network are said to be k-edge-connected if deleting any set of k − 1 edges leaves u and v connected; similarly, they are k-vertex connected if deleting any set of k − 1 other vertices or edges leaves u and v connected. We focus on building networks that are highly connected, meaning that even if a small number of edges and nodes fail, the remaining nodes will still be able to communicate. A brief description of some of our results is given below. We study the problem of building 2-vertex-connected networks that are large and have low cost. Given an n-node graph with costs on its edges and any integer k, we give an O(log n log k) approximation for the problem of finding a minimum-cost 2-vertex-connected subgraph containing at least k nodes. We also give an algorithm of similar approximation ratio for maximizing the number of nodes in a 2-vertex-connected subgraph subject to a budget constraint on the total cost of its edges. Our algorithms are based on a pruning process that, given a 2-vertex-connected graph, finds a 2-vertex-connected subgraph of any desired size and of density comparable to the input graph, where the density of a graph is the ratio of its cost to the number of vertices it contains. This pruning algorithm is simple and efficient, and is likely to find additional applications. Recent breakthroughs on vertex-connectivity have made use of algorithms for element-connectivity problems. We develop an algorithm that, given a graph with some vertices marked as terminals, significantly simplifies the graph while preserving the pairwise element-connectivity of all terminals; in fact, the resulting graph is bipartite. We believe that our simplification/reduction algorithm will be a useful tool in many settings. We illustrate its applicability by giving algorithms to find many trees that each span a given terminal set, while being disjoint on edges and non-terminal vertices; such problems have applications in VLSI design and other areas. We also use this reduction algorithm to analyze simple algorithms for single-sink network design problems with high vertex-connectivity requirements; we give an O(k log n)-approximation for the problem of k-connecting a given set of terminals to a common sink. We study similar problems in which different types of links, of varying capacities and costs, can be used to connect nodes; assuming there are economies of scale, we give algorithms to construct low-cost networks with sufficient capacity or bandwidth to simultaneously support flow from each terminal to the common sink along many vertex-disjoint paths. We further investigate capacitated network design, where edges may have arbitrary costs and capacities. Given a connectivity requirement R_uv for each pair of vertices u,v, the goal is to find a low-cost network which, for each uv, can support a flow of R_uv units of traffic between u and v. We study several special cases of this problem, giving both algorithmic and hardness results. In addition to Network Design, we consider certain Traveling Salesperson-like problems, where the goal is to find short walks that visit many distinct vertices. We give a (2 + epsilon)-approximation for Orienteering in undirected graphs, achieving the best known approximation ratio, and the first approximation algorithm for Orienteering in directed graphs. We also give improved algorithms for Orienteering with time windows, in which vertices must be visited between specified release times and deadlines, and other related problems. These problems are motivated by applications in the fields of vehicle routing, delivery and transportation of goods, and robot path planning.

A noise simulator for eLISA: Migrating LISA Pathfinder knowledge to the eLISA mission

We present a new technical simulator for the eLISA mission, based on state space modeling techniques and developed in MATLAB. This simulator computes the coordinate and velocity over time of each body involved in the constellation, i.e. the spacecraft and its test masses, taking into account the different disturbances and actuations. This allows studying the contribution of instrumental noises and system imperfections on the residual acceleration applied on the TMs, the latter reflecting the performance of the achieved free-fall along the sensitive axis. A preliminary version of the results is presented.

The relationship of early social, mental, and behavioral experiences with adult obesity and Alcohol Use Disorder

Stressful life events early in life, including symptoms of mental disorders or childhood maltreatment, may increase risk for worse mental and physical health outcomes in adulthood. The purpose of this dissertation was to examine the effects of childhood Attention Deficit Hyperactivity Disorder (ADHD) symptoms and maltreatment experience on two adult outcomes: obesity and alcohol use disorder (AUD). Mediational effects of adolescent characteristics were explored. This dissertation used Waves I, III, and IV of the National Longitudinal Study of Adolescent to Adult Health. In Paper 1 (Chapter 3), we investigated the association between multiple types of child maltreatment and adult objective (body mass index; BMI) and subjective (self-rated) obesity, as well as mediating effects by adolescent characteristics including depressive symptoms and BMI. Results showed that after adjusting for sex, race/ethnicity, and maternal education, physical maltreatment was moderately associated with adulthood obesity as measured by BMI and self-reported obesity, while sexual maltreatment was more strongly associated with the objective measure but not the subjective measure. The indirect effects of mediation of adolescent BMI and depressive symptoms were statistically significant. In Paper 2 (Chapter 4), the objective was to examine mediation by adolescent depressive symptoms, alcohol consumption, peer alcohol consumption, and delinquency in the relationship between ADHD symptoms and adult AUD. The indirect effects of mediation of adolescent delinquency, alcohol consumption, and peer alcohol consumption were statistically significant in single and multiple mediator models. In Paper 3 (Chapter 5), the objective was to assess the joint effects of maltreatment/neglect on adult AUD. After adjusting for sex, race/ethnicity, child maltreatment, and parental AUD, ADHD symptoms were significantly associated with increased odds of AUD. There was no strong evidence of multiplicative interaction by maltreatment. This association was stronger for males than females, although the interaction term was not statistically significant. This dissertation adds to the literature by examining relationships between several major public health problems: ADHD symptoms, childhood maltreatment, AUD, depressive symptoms, and obesity. This project has implications for understanding how early life stress increases risk for later physical and mental health problems, and identifying potential intervention targets for adolescents.

On the size of the fibers of spectral maps induced by semialgebraic embeddings

Let S(M) be the ring of (continuous) semialgebraic functions on a semialgebraic set M and S*(M) its subring of bounded semialgebraic functions. In this work we compute the size of the fibers of the spectral maps Spec(j)1:Spec(S(N))→Spec(S(M)) and Spec(j)2:Spec(S*(N))→Spec(S*(M)) induced by the inclusion j:N M of a semialgebraic subset N of M. The ring S(M) can be understood as the localization of S*(M) at the multiplicative subset WM of those bounded semialgebraic functions on M with empty zero set. This provides a natural inclusion iM:Spec(S(M)) Spec(S*(M)) that reduces both problems above to an analysis of the fibers of the spectral map Spec(j)2:Spec(S*(N))→Spec(S*(M)). If we denote Z:=ClSpec(S*(M))(M N), it holds that the restriction map Spec(j)2|:Spec(S*(N)) Spec(j)2-1(Z)→Spec(S*(M)) Z is a homeomorphism. Our problem concentrates on the computation of the size of the fibers of Spec(j)2 at the points of Z. The size of the fibers of prime ideals "close" to the complement Y:=M N provides valuable information concerning how N is immersed inside M. If N is dense in M, the map Spec(j)2 is surjective and the generic fiber of a prime ideal p∈Z contains infinitely many elements. However, finite fibers may also appear and we provide a criterium to decide when the fiber Spec(j)2-1(p) is a finite set for p∈Z. If such is the case, our procedure allows us to compute the size s of Spec(j)2-1(p). If in addition N is locally compact and M is pure dimensional, s coincides with the number of minimal prime ideals contained in p. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

THE STOCHASTIC NAVIER STOKES EQUATIONS FOR HEAT CONDUCTING, COMPRESSIBLE FLUIDS

This dissertation is devoted to the equations of motion governing the evolution of a fluid or gas at the macroscopic scale. The classical model is a PDE description known as the Navier-Stokes equations. The behavior of solutions is notoriously complex, leading many in the scientific community to describe fluid mechanics using a statistical language. In the physics literature, this is often done in an ad-hoc manner with limited precision about the sense in which the randomness enters the evolution equation. The stochastic PDE community has begun proposing precise models, where a random perturbation appears explicitly in the evolution equation. Although this has been an active area of study in recent years, the existing literature is almost entirely devoted to incompressible fluids. The purpose of this thesis is to take a step forward in addressing this statistical perspective in the setting of compressible fluids. In particular, we study the well posedness for the corresponding system of Stochastic Navier Stokes equations, satisfied by the density, velocity, and temperature. The evolution of the momentum involves a random forcing which is Brownian in time and colored in space. We allow for multiplicative noise, meaning that spatial correlations may depend locally on the fluid variables. Our main result is a proof of global existence of weak martingale solutions to the Cauchy problem set within a bounded domain, emanating from large initial datum. The proof involves a mix of deterministic and stochastic analysis tools. Fundamentally, the approach is based on weak compactness techniques from the deterministic theory combined with martingale methods. Four layers of approximate stochastic PDE's are built and analyzed. A careful study of the probability laws of our approximating sequences is required. We prove appropriate tightness results and appeal to a recent generalization of the Skorohod theorem. This ultimately allows us to deduce analogues of the weak compactness tools of Lions and Feireisl, appropriately interpreted in the stochastic setting.

Intolerance of uncertainty modulates the insensitivity to reinforcer devaluation found in an avoidance task

The reinforcer devaluation paradigm has been regarded as a canonical paradigm to detect habit-like behavior in animal and human instrumental learning. Though less studied, avoidance situations set a scenario where habit-like behavior may be of great experimental and clinical interest. On the other hand, proactive intolerance of uncertainty has been shown as a factor facilitating responses in uncertain situations. Thus, avoidance situations in which uncertainty is favoured, may be taken as a relevant paradigm to examine the role of intolerance of uncertainty as a facilitatory factor for habit-like behavior to occur. In our experiment we used a free-operant discriminative avoidance procedure to implement a devaluation paradigm. Participants learned to avoid an aversive noise presented either to the right or to the left ear by pressing two different keys. After a devaluation phase where the volume of one of the noises was reduced, they went through a test phase identical to the avoidance phase except for the fact that the noise was never administered. Sensitivity to reinforcer devaluation was examined by comparing the response rate to the cue associated to the devalued reinforcer with that to the cue associated to the still aversive reinforcer. The results showed that intolerance of uncertainty was positively associated to insensitivity to reinforcer devaluation. Finally, we discuss the theoretical and clinical implications of the habit-like behavior obtained in our avoidance procedure.

A aprendizagem da multiplicação perspetiva através através da resolução da sequência de problemas

Este estudo tem como objetivo compreender de que forma os alunos desenvolvem a aprendizagem da multiplicação através da resolução de uma sequência de problemas. Mais concretamente, pretende Identificar e analisar as estratégias e procedimentos de cálculo utilizados pelos alunos quando resolvem problemas de multiplicação e o contributo da sequência de problemas na aprendizagem desta operação. O quadro teórico integra duas secções que discutem as seguintes temáticas: a resolução de problemas e o ensino e aprendizagem da multiplicação. A metodologia deste estudo segue uma abordagem qualitativa, na vertente de investigação-ação. Nele participaram 20 alunos de uma turma do 2.º ano de escolaridade. A recolha de dados foi realizada com recurso à observação participante, à recolha documental, a conversas informais e à entrevista. Os resultados deste estudo sobre as estratégias e procedimentos de cálculo usados pelos alunos quando resolvem problemas de multiplicação revelam que: (i) recorrem a alguma diversidade de estratégias e procedimentos de cálculo na resolução de problemas de multiplicação, (ii) há alunos que, numa fase inicial, recorrem a várias estratégias e procedimentos para resolver um mesmo problema, (iii) por vezes, os alunos regridem na estratégia utilizada comparando com a que usou no problema anterior da sequência e (iv) associada a cada uma das estratégias há procedimentos de cálculo mais frequentes do que outros. Estes resultados mostram, ainda, no que se refere ao contributo da sequência de problemas na aprendizagem da multiplicação que: (i) problemas com contextos associados ao modelo de disposição retangular contribuem para o uso de estratégias multiplicativas, desde que os números envolvidos sejam adequados, (ii) os números de referência e do conhecimento dos alunos facilitam os cálculos efetuados pelos mesmos e (iii) a articulação entre os problemas da sequência contribui para a progressão das estratégias utilizadas pelos alunos.

Remoção de ruídos sísmicos utilizando transformada de wavelet 1D e 2D com software em desenvolvimento

In the Hydrocarbon exploration activities, the great enigma is the location of the deposits. Great efforts are undertaken in an attempt to better identify them, locate them and at the same time, enhance cost-effectiveness relationship of extraction of oil. Seismic methods are the most widely used because they are indirect, i.e., probing the subsurface layers without invading them. Seismogram is the representation of the Earth s interior and its structures through a conveniently disposed arrangement of the data obtained by seismic reflection. A major problem in this representation is the intensity and variety of present noise in the seismogram, as the surface bearing noise that contaminates the relevant signals, and may mask the desired information, brought by waves scattered in deeper regions of the geological layers. It was developed a tool to suppress these noises based on wavelet transform 1D and 2D. The Java language program makes the separation of seismic images considering the directions (horizontal, vertical, mixed or local) and bands of wavelengths that form these images, using the Daubechies Wavelets, Auto-resolution and Tensor Product of wavelet bases. Besides, it was developed the option in a single image, using the tensor product of two-dimensional wavelets or one-wavelet tensor product by identities. In the latter case, we have the wavelet decomposition in a two dimensional signal in a single direction. This decomposition has allowed to lengthen a certain direction the two-dimensional Wavelets, correcting the effects of scales by applying Auto-resolutions. In other words, it has been improved the treatment of a seismic image using 1D wavelet and 2D wavelet at different stages of Auto-resolution. It was also implemented improvements in the display of images associated with breakdowns in each Auto-resolution, facilitating the choices of images with the signals of interest for image reconstruction without noise. The program was tested with real data and the results were good

Ensemble Stream Model for Data-Cleaning in Sensor Networks

Ensemble Stream Modeling and Data-cleaning are sensor information processing systems have different training and testing methods by which their goals are cross-validated. This research examines a mechanism, which seeks to extract novel patterns by generating ensembles from data. The main goal of label-less stream processing is to process the sensed events to eliminate the noises that are uncorrelated, and choose the most likely model without over fitting thus obtaining higher model confidence. Higher quality streams can be realized by combining many short streams into an ensemble which has the desired quality. The framework for the investigation is an existing data mining tool. First, to accommodate feature extraction such as a bush or natural forest-fire event we make an assumption of the burnt area (BA*), sensed ground truth as our target variable obtained from logs. Even though this is an obvious model choice the results are disappointing. The reasons for this are two: One, the histogram of fire activity is highly skewed. Two, the measured sensor parameters are highly correlated. Since using non descriptive features does not yield good results, we resort to temporal features. By doing so we carefully eliminate the averaging effects; the resulting histogram is more satisfactory and conceptual knowledge is learned from sensor streams. Second is the process of feature induction by cross-validating attributes with single or multi-target variables to minimize training error. We use F-measure score, which combines precision and accuracy to determine the false alarm rate of fire events. The multi-target data-cleaning trees use information purity of the target leaf-nodes to learn higher order features. A sensitive variance measure such as f-test is performed during each node’s split to select the best attribute. Ensemble stream model approach proved to improve when using complicated features with a simpler tree classifier. The ensemble framework for data-cleaning and the enhancements to quantify quality of fitness (30% spatial, 10% temporal, and 90% mobility reduction) of sensor led to the formation of streams for sensor-enabled applications. Which further motivates the novelty of stream quality labeling and its importance in solving vast amounts of real-time mobile streams generated today.

A novel ranking procedure for forecasting approaches using Data Envelopment Analysis

To compare the accuracy of different forecasting approaches an error measure is required. Many error measures have been proposed in the literature, however in practice there are some situations where different measures yield different decisions on forecasting approach selection and there is no agreement on which approach should be used. Generally forecasting measures represent ratios or percentages providing an overall image of how well fitted the forecasting technique is to the observations. This paper proposes a multiplicative Data Envelopment Analysis (DEA) model in order to rank several forecasting techniques. We demonstrate the proposed model by applying it to the set of yearly time series of the M3 competition. The usefulness of the proposed approach has been tested using the M3-competition where five error measures have been applied in and aggregated to a single DEA score.