A kinetic and equilibrium analysis of silicon carbide chemical vapor deposition on monofilaments

Chemical kinetics of atmospheric pressure silicon carbide (SiC) chemical vapor deposition (CVD) from dilute silane and propane source gases in hydrogen is numerically analyzed in a cylindrical upflow reactor designed for CVD on monofilaments. The chemical composition of the SiC deposit is assessed both from the calculated total fluxes of carbon and silicon and from chemical equilibrium considerations for the prevailing temperatures and species concentrations at and along the filament surface. The effects of gas and surface chemistry on the evolution of major gas phase species are considered in the analysis

Formant Trajectories in CV Clusters for German Stops

This paper presents an attempt to demonstrate the nonlinear progress of vowel formants in German CV clusters with stop sounds and identify it as a significant acoustic property characterizing the place of articulation of the stop consonant

Modeling of Polish Intonation for Statistical-Parametric Speech Synthesis

Wydział NeofilologiiBieżąca praca prezentuje próbę budowy neurobiologicznie umotywowanego modelu mapowań pomiędzy wysokopoziomowymi dyskretnymi kategoriami lingwistycznymi a ciągłym sygnałem częstotliwości podstawowej w polskiej neutralnej mowie czytanej, w oparciu o konwolucyjne sieci neuronowe. Po krótkim wprowadzeniu w problem badawczy w kontekście intonacji, syntezy mowy oraz luki pomiędzy fonetyką a fonologią, praca przedstawia opis uczenia modelu na podstawie specjalnego korpusu mowy oraz ewaluację naturalności konturu F0 generowanego przez wyuczony model za pomocą eksperymentów percepcyjnych typu ABX oraz MOS przy użyciu specjalnie w tym celu zbudowanego resyntezatora Neural Source Filter. Następnie, prezentowane są wyniki eksploracji fonologiczno-fonetycznych mapowań wyuczonych przez model. W tym celu wykorzystana została jedna z tzw. metod wyjaśniających dla sztucznej inteligencji – Layer-wise Relevance Propagation. W pracy przedstawione zostały wyniki powstałej na tej podstawie obszernej analizy ilościowej istotności dla konturu częstotliwości podstawowej każdej z 1297 specjalnie wygenerowanych lingwistycznych kategorii wejściowych modelu oraz ich wielorakich grupowań na różnorodnych poziomach abstrakcji. Pracę kończy dogłębna analiza oraz interpretacja uzyskanych wyników oraz rozważania na temat mocnych oraz słabych stron zastosowanych metod, a także lista proponowanych usprawnień.This work presents an attempt to build a neurobiologically inspired Convolutional Neural Network-based model of the mappings between discrete high-level linguistic categories into a continuous signal of fundamental frequency in Polish neutral read speech. After a brief introduction of the current research problem in the context of intonation, speech synthesis and the phonetic-phonology gap, the work goes on to describe the training of the model on a special speech corpus, and an evaluation of the naturalness of the F0 contour produced by the trained model through ABX and MOS perception experiments conducted with help of a specially built Neural Source Filter resynthesizer. Finally, an in-depth exploration of the phonology-to-phonetics mappings learned by the model is presented; the Layer-wise Relevance Propagation explainability method was used to perform an extensive quantitative analysis of the relevance of 1297 specially engineered linguistic input features and their groupings at various levels of abstraction for the specific contours of the fundamental frequency. The work ends with an in-depth interpretation of these results and a discussion of the advantages and disadvantages of the current method, and lists a number of potential future improvements.Badania przedstawione w pracy zostały cz˛e´sciowo zrealizowane w ramach grantu badawczego Harmonia nr UMO-2014/14/M/HS2/00631 przyznanego przez Narodowe Centrum Nauki

Convection and chemistry effects in CVD: A 3-D analysis for silicon deposition

The computational fluid dynamics code FLUENT has been adopted to simulate the entire rectangular-channel-like (3-D) geometry of an experimental CVD reactor designed for Si deposition. The code incorporated the effects of both homogeneous (gas phase) and heterogeneous (surface) chemistry with finite reaction rates of important species existing in silane dissociation. The experiments were designed to elucidate the effects of gravitationally-induced buoyancy-driven convection flows on the quality of the grown Si films. This goal is accomplished by contrasting the results obtained from a carrier gas mixture of H2/Ar with the ones obtained from the same molar mixture ratio of H2/He, without any accompanying change in the chemistry. Computationally, these cases are simulated in the terrestrial gravitational field and in the absence of gravity. The numerical results compare favorably with experiments. Powerful computational tools provide invaluable insights into the complex physicochemical phenomena taking place in CVD reactors. Such information is essential for the improved design and optimization of future CVD reactors

Gender-Aware Natural Language Translation

Languages differ in the way they express gender. Some languages are gender-neutral, while others have masculine, feminine, or neuter forms. When translating gender-neutral text into a language with gender, there can be more than one valid translation. For example, the Turkish query “O bir doktor” is translated into English as either “He is a doctor” or “She is a doctor.” Historically, machine translation has not been able to generate more than one gender specific translation. Put differently, machine translation would “choose” a single masculine form, feminine form, or other gender variant as the translation output. In neural machine translation, this “choice” reflects bias in the training data used to train the translation model. This disclosure presents techniques to generate both a masculine and a feminine translation for gender-neutral text, thereby reducing or eliminating gender bias in machine translation. The technique includes three main components: detection, generation of alternatives, and validation. In the detection phase, it is detected whether a given query is gender-ambiguous or not. If the detection component triggers, two translations for the query are generated: one masculine and one feminine. Finally, the validation step verifies that the two translations are high quality before showing them to users

Population dynamics of garlic mustard (Alliaria petiolata): A new invader to Alberta’s central parkland subregion

Garlic mustard (Alliaria petiolata), a highly invasive biennial plant species, was first discovered in Alberta in 2010. It is present in two urban ravines in Edmonton and one in St. Albert. Introduced from Europe, this invasive species can be found in 37 US states and 7 Canadian provinces. This species rapidly invades forest ecosystems by dominating native vegetation. Garlic mustard is a threat to Edmonton’s River Valley due to its highly interconnected nature and the many native flora and fauna that inhabit this area. Understanding the population dynamics of an invasive species is critical to making informed management decisions. Previous research on the population dynamics of garlic mustard in other regions has reported high mortality in the first year and low second year mortality. The goal of our project was to assess garlic mustard mortality in its first and second year of growth within Edmonton’s central parkland subregion. To assess first year mortality fifteen 0.5 m2 quadrats were established in spring and monitored with biweekly counts over the first growing season in 2014 and 2015. To assess second year mortality fifteen 0.5 m2 quadrats were established in fall and then relocated in spring and monitored with biweekly counts over the second growing season in 2013-2014 and 2014-2015. Overall, first year mortality was 27% in 2014 and 2015 and second year mortality was 31% and 47%, respectively. This research will contribute to a broader understanding of the population dynamics of this species and may inform management decisions. *Indicates faculty mentor

Method and apparatus for measuring thermal conductivity of small, highly insulating specimens

A hot plate method and apparatus for the measurement of thermal conductivity combines the following capabilities: 1) measurements of very small specimens; 2) measurements of specimens with thermal conductivity on the same order of that as air; and, 3) the ability to use air as a reference material. Care is taken to ensure that the heat flow through the test specimen is essentially one-dimensional. No attempt is made to use heated guards to minimize the flow of heat from the hot plate to the surroundings. Results indicate that since large correction factors must be applied to account for guard imperfections when specimen dimensions are small, simply measuring and correcting for heat from the heater disc that does not flow into the specimen is preferable. The invention is a hot plate method capable of using air as a standard reference material for the steady-state measurement of the thermal conductivity of very small test samples having thermal conductivity on the order of air

The W_L W_L scattering at the LHC: improving the selection criteria

We present a systematic study of the different mechanisms leading to WW pair production at the LHC, both in the same-sign and opposite-sign channels, and we emphasize that the former offers much better potential for investigating non-resonant W_L W_L scattering. We propose a new kinematic variable to isolate the W_L W_L scattering component in same-sign WW production at the LHC. Focusing on purely leptonic W decay channels, we show that it considerably improves the LHC capabilities to shed light on the electroweak symmetry breaking mechanism after collecting 100 fb^{-1} of data at sqrt{s} = 14 TeV. The new variable is less effective in the opposite-sign WW channel due to different background composition.Comment: 25 pages, 32 figure