Multistatic Tracking with the Maximum Likelihood Probabilistic Multi-Hypothesis Tracker

Multistatic sonar tracking is a difficult proposition. The ocean environment typically features very complex propagation conditions, causing low target probabilities of detection and high clutter levels. Additionally, most sonar targets are relatively low speed, which makes it difficult to use Doppler (if available) to separate target returns from clutter returns. The Maximum Likelihood Probabilistic Data Association Tracker (ML-PDA) and the Maximum Likelihood Probabilistic Multi-Hypothesis Tracker (ML-PMHT) --- a similar algorithm to ML-PDA --- can be implemented as effective multistatic trackers. This dissertation will develop a tracking framework for these algorithms. This framework will focus mainly on ML-PMHT, which has an inherent advantage in that its log-likelihood ratio (LLR) has a simple multitarget formulation, which allows it to be implemented as a true multitarget tracker. First, this multitarget LLR will be implemented for ML-PMHT, which will give it superior performance over ML-PDA for instances where multiple targets are closely spaced with similar motion dynamics. Next, the performance of ML-PMHT will be compared when it is applied in Cartesian measurement space and in delay-bearing measurement space, where the measurement covariance is more accurately represented. Following this, a maneuver-model parameterization will be introduced that will allow ML-PDA and ML-PMHT to follow sharply maneuvering targets; their previous straight-line parameterization only allowed them to follow moderately maneuvering targets. Finally, a novel method of determining a tracking threshold for ML-PMHT will be developed by applying extreme value theory to the probabilistic properties of the clutter. This will also be done with target measurements, which will allow the issue of trackability for ML-PMHT to be explored. Probabilistic expressions for the maximum values of the LLR surface caused by both clutter and the target will be developed, which will allow for the determination of target trackability in any given scenario

A Search for Boosted Low Mass Resonances Decaying to the bb̅ Final State and Produced in Association with a Jet at √s = 13 TeV with the ATLAS Detector

A search in the high momentum regime for new resonances, produced in association with a jet, decaying into a pair of bottom quarks is presented using an integrated luminosity of 80.5 fb-1 of proton-proton collisions at center-of-mass energy √s = 13 TeV recorded by the ATLAS detector at the Large Hadron Collider. The search was performed for low mass resonances, including the Standard Model Higgs boson and leptophobic Z\u27 dark matter mediators, in the mass range of 100 GeV to 200 GeV. For the Standard Model Higgs boson, the observed signal strength is μH = 5.8 ± 3.1 (stat.) ± 1.9 (syst.) ± 1.7 (th.), which is consistent with the background-only hypothesis at 1.6 standard deviations. No evidence of a significant excess of events beyond the expected background is found and competitive limits on leptophobic Z\u27 boson axial-vector couplings to Standard Model quarks with democratic couplings to all quark generations are set for the mass range considered. The dominant background in this analysis is irreducible multijet events from QCD interactions, which I modeled using a parametric function that was robust to fitting bias and spurious signals

Proceedings of the Fifth European Workshop on Probabilistic Graphical Models

Peer reviewe

Characterization of Field Pennycress (Thlaspi arvense L.) Germplasm for Use as a Cover Crop and Biofuel Feedstock

University of Minnesota M.S. thesis. January 2017. Major: Applied Plant Sciences. Advisors: James Anderson, Donald Wyse. 1 computer file (PDF); vi, 104 pages.Field pennycress (Thlaspi arvense L.) is a winter annual oilseed crop currently under investigation for use as a feedstock for domestic biofuel production. As an undomesticated species, pennycress has a variety of undesirable traits and the species has seen very limited formal selection or genetic improvement. This research seeks to characterize a collection of 42 wild, winter type accessions for morphological and yield component traits (Chapter 2) as well as seed chemistry traits (Chapter 3). This data will be used to guide the breeding and development of improved germplasm and eventual variety release. The germplasm collection was grown in five unique Minnesota environments in 2013/2014 and 2014/2015. Mixed effects models were used to estimate best linear unbiased estimates (BLUEs) for each of the accessions and traits, which were used in subsequent analyses. Within the morphological traits and yield component traits, relationships between traits were assessed using Pearson’s correlation coefficients and estimates of heritability were calculated for each trait. Hierarchical clustering was used to identify groups of accessions based on similarity of trait values. Significant variation for accession was detected in 13 of the 19 trait models for morphological and yield component traits at P < 0.05, and for 1 of 19 at P < 0.10 (Table 2.7). Pairwise differences after adjusting for multiple comparisons using Tukey’s Honest Significant Difference (HSD) resulted in more than one grouping in 9 of the 13 models in which accession was significant (P < 0.05). For seed chemistry traits, significant variation (P < 0.05) for accession was detected for nine of the ten fatty acids detected and oil percentage. Significant variation was observed for many of the traits evaluated, but to make sizable gains in selection for certain traits, additional genetic variation in the form of mutants and additional collections is required

CA and Monte Carlo models of HIV infection

The models presented are discrete Monte Carlo(MC) and Cellular Automata(CA) representations of the interaction of HIV with the immune system. HIV is characterised by the depletion of Helper T cells in the body. Helper T cells are essential to the correct regulation of the immune system. Their degradation leaves the body incapable of defending itself, even against what is usually an unharmful infection. The models consider just four cell types the Macrophage, M, the helper T cell, H , the cytotoxic Killer cell, C and the virus, V. Each cell type can either be in high concentration (1) or low concentration (0). An up d a te of a site consists of nearest-neighbour interaction followed by intra-site interactions. The nearest-neighbour interaction represents the influence of a site’s surroundings on it. The intra-site interactions are Boolean equations which represent a succinct interpretation of HIV infection and its effect on the host immune system. Mutation is considered via a probabilistic parameter P m u t - Each cell type has inherent mobility due to the nearest-neighbour interactions, explicit mobility is explored by a probabilistic parameter Pmob• The MC and CA .simulations differ in their updating, with CA updating is synchronous and with MC it is asynchronous. MC is explored as an alternative to the CA model form. Due to th e Boolean concentrations of the cell types, synchronous (CA) updating leads to overshooting, there is either complete viral dominance or immune dominance and no intermediate state. Asynchronous (MC) updating smoothes these extremes; intermediate states between immuno-dominance and immuno-deficiency exist. These intermediate states offer new insight into the dynamics of HIV and the immune system. Asynchronous updating gives clearly defined growth patterns and this enables th e exploration of critical points. One such critical point is the value of Pmut for which the cross-over between immune dominance and deficiency occurs. Also characteristics of the disease progression such as latency can be investigated

Optical parametric oscillators and precision optical frequency measurements

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Physics, 1996.Includes bibliographical references (leaves 254-258).by Dicky Lee.Ph.D