Multipath Parameter Estimation from OFDM Signals in Mobile Channels

We study multipath parameter estimation from orthogonal frequency division multiplex signals transmitted over doubly dispersive mobile radio channels. We are interested in cases where the transmission is long enough to suffer time selectivity, but short enough such that the time variation can be accurately modeled as depending only on per-tap linear phase variations due to Doppler effects. We therefore concentrate on the estimation of the complex gain, delay and Doppler offset of each tap of the multipath channel impulse response. We show that the frequency domain channel coefficients for an entire packet can be expressed as the superimposition of two-dimensional complex sinusoids. The maximum likelihood estimate requires solution of a multidimensional non-linear least squares problem, which is computationally infeasible in practice. We therefore propose a low complexity suboptimal solution based on iterative successive and parallel cancellation. First, initial delay/Doppler estimates are obtained via successive cancellation. These estimates are then refined using an iterative parallel cancellation procedure. We demonstrate via Monte Carlo simulations that the root mean squared error statistics of our estimator are very close to the Cramer-Rao lower bound of a single two-dimensional sinusoid in Gaussian noise.Comment: Submitted to IEEE Transactions on Wireless Communications (26 pages, 9 figures and 3 tables

Triple Helix, Fall 2018

Table of Contents: Science Agenda: The Politics of Grant Writing / by Kavya Rajesh (p. 4) -- From the Experts / by Katherine Bruner (p. 5) -- 3D Printed Drugs: The Future of Pharmaceuticals / by Ethan Wang (p. 6) -- Computerized Markets: Wall Street Takeover / by James Kiraly (p. 10) -- The Evolution of Fear / by Alisha Ahmed (p. 14) -- ADDing Up / by Victor Liaw (p. 18) -- The Clone Wars / by Jina Zhou (p. 22) -- Physician-Assisted Suicide: Drawing the Line / by Haley Wolf (p. 26) -- Supervised Injection Sites / by Alex Gajewski (p. 30) -- On Emerging Medicalization and Health Care / by Patrick Lee (p. 33) -- The Future of Human Gene Modifications / by Elizabeth Robinson (p. 36)College of Natural SciencesUT LibrariesLiberal Art

Predicting Precedent: A Psycholinguistic Artificial Intelligence in the Supreme Court

Since the proliferation of analytic methodologies and ‘big data’ in the 1980s, there have been multiple studies claiming to offer consistent predictions for Supreme Court behavior. Political scientists focus on analyzing the ideology of judges, with prediction accuracy as high as 70%. Institutionalists, such as Kaufmann (2019), seek to make predictions on verdicts based on a thorough, qualitative analysis of rules and structures, with predictive accuracy as high as 75%. We argue that a psycholinguistic model utilizing machine learning (SCOTUS_AI) can best predict Court outcomes. Extracting sentiment features from parsed briefs through the Linguistic Inquiry and Word Count (LIWC), our results indicate SCOTUS_AI (AUC = .8087; Top K=.9144) outcompetes traditional analysis in both class-controlled accuracy and range of possible, specific outcomes. Moreover, unlike traditional models, SCOTUS_AI can also predict the procedural outcome of the case as one-hot encoded by remand (AUC=.76). Our findings support a psycholinguistic paradigm of case analysis, suggesting that the framing of arguments is a relatively strong predictor of case results. Finally, we cast predictions for the Supreme Court docket, demonstrating that SCOTUS_AI can be practically deployed in the field for individual cases

The sum-product problem for small sets

For $A\subseteq \mathbb{R}$, let $A+A=\{a+b: a,b\in A\}$ and $AA=\{ab: a,b\in A\}$. For $k\in \mathbb{N}$, let $SP(k)$ denote the minimum value of $\max\{|A+A|, |AA|\}$ over all $A\subseteq \mathbb{N}$ with $|A|=k$. Here we establish $SP(k)=3k-3$ for $2\leq k \leq 7$, the $k=7$ case achieved for example by $\{1,2,3,4,6,8,12\}$, while $SP(k)=3k-2$ for $k=8,9$, the $k=9$ case achieved for example by $\{1,2,3,4,6,8,9,12,16\}$. For $4\leq k \leq 7$, we provide two proofs using different applications of Freiman's $3k-4$ theorem; one of the proofs includes extensive case analysis on the product sets of $k$-element subsets of $(2k-3)$-term arithmetic progressions. For $k=8,9$, we apply Freiman's $3k-3$ theorem for product sets, and investigate the sumset of the union of two geometric progressions with the same common ratio $r>1$, with separate treatments of the overlapping cases $r\neq 2$ and $r\geq 2$.Comment: 10 pages, 1 table, 4 figure

Rapid and robust association mapping of expression quantitative trait loci

We applied a simple and efficient two-step method to analyze a family-based association study of gene expression quantitative trait loci (eQTL) in a mixed model framework. This two-step method produces very similar results to the full mixed model method, with our method being significantly faster than the full model. Using the Genetic Analysis Workshop 15 (GAW15) Problem 1 data, we demonstrated the value of data filtering for reducing the number of tests and controlling the number of false positives. Specifically, we showed that removing non-expressed genes by filtering on expression variability effectively reduced the number of tests by nearly 50%. Furthermore, we demonstrated that filtering on genotype counts substantially reduced spurious detection. Finally, we restricted our analysis to the markers and transcripts that were closely located. We found five times more signals in close proximity (cis-) to transcripts than in our genome-wide analysis. Our results suggest that careful pre-filtering and partitioning of data are crucial for controlling false positives and allowing detection of genuine effects in genetic analysis of gene expression

Reliability Improvements for Phonetic Transcription of Lengthening

The purpose of this study was to determine ways to improve the reliability of narrow phonetic transcription of lengthening distortions in AOS. More specifically, we looked for ways to make the narrow transcription of segment lengthening more accurate and consistent among transcribers

A combined strategy for quantitative trait loci detection by genome-wide association

We applied a range of genome-wide association (GWA) methods to map quantitative trait loci (QTL) in the simulated dataset provided by the 12th QTLMAS workshop in order to derive an effective strategy.A variance component linkage analysis revealed QTLs but with low resolution. Three single-marker based GWA methods were then applied: Transmission Disequilibrium Test and single marker regression, fitting an additive model or a genotype model, on phenotypes pre-corrected for pedigree and fixed effects. These methods detected QTL positions with high concordance to each other and with greater refinement of the linkage signals. Further multiple-marker and haplotype analyses confirmed the results with higher significance. Two-locus interaction analysis detected two epistatic pairs of markers that were not significant by marginal effects. Overall, using stringent Bonferroni thresholds we identified 9 additive QTL and 2 epistatic interactions, which together explained about 12.3% of the corrected phenotypic variance.The combination of methods that are robust against population stratification, like QTDT, with flexible linear models that take account of the family structure provided consistent results. Extensive simulations are still required to determine appropriate thresholds for more advanced model including epistasis

Single Molecule-Level Study of Donor-Acceptor Interactions and Nanoscale Environment in Blends

Organic semiconductors have attracted considerable attention due to their applications in low-cost (opto)electronic devices. The most successful organic materials for applications that rely on charge carrier generation, such as solar cells, utilize blends of several types of molecules. In blends, the local environment strongly influences exciton and charge carrier dynamics. However, relationship between nanoscale features and photophysics is difficult to establish due to the lack of necessary spatial resolution. We use functionalized fluorinated pentacene (Pn) molecule as single molecule probes of intermolecular interactions and of the nanoscale environment in blends containing donor and acceptor molecules. Single Pn donor (D) molecules were imaged in PMMA in the presence of acceptor (A) molecules using wide-field fluorescence microscopy. Two sample configurations were realized: (i) a fixed concentration of Pn donor molecules, with increasing concentration of acceptor molecules (functionalized indenflouorene or PCBM) and (ii) a fixed concentration of acceptor molecules with an increased concentration of the Pn donor. The D-A energy transfer and changes in the donor emission due to those in the acceptor- modified polymer morphology were quantified. The increase in the acceptor concentration was accompanied by enhanced photobleaching and blinking of the Pn donor molecules. To better understand the underlying physics of these processes, we modeled photoexcited electron dynamics using Monte Carlo simulations. The simulated blinking dynamics were then compared to our experimental data, and the changes in the transition rates were related to the changes in the nanoscale environment. Our study provides insight into evolution of nanoscale environment during the formation of bulk heterojunctions