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<p>While pronunciation has previously been described as a neglected skill in the second language classroom, a growing body of literature has demonstrated that pronunciation training improves students’ productions (Derwing & Munro, 2005). Mispronunciations have been shown to impact comprehensibility, intelligibility, and accentedness (Derwing & Munro, 2009). As pronunciation instruction methods have begun to be the subject of empirical research, Visual Feedback (VF) has begun to emerge as a novel method for teaching pronunciation. This method has been shown to be particularly effective for teaching voice onset time (VOT), a characteristic of voiceless stop consonants (e.g., /p, t, k/). Worth noting, English and Spanish differ concerning VOT, with English employing long VOTs (30-100ms) and Spanish short VOTs (0-30ms) (Lisker & Abramson’s, 1964). Previous research has focused exclusively on employing VF for shortening VOT, although there are some compelling reasons to question whether the size and nature of the effect would be similar for lengthening VOT. The present study examines the potential effectiveness of VF as a means of lengthening the VOT of Spanish learners of English.</p> <p>The participants of the study were twenty-six students from a large Colombian university. The experiment design consisted of a pretest, three VF interventions, a posttest, and a delayed posttest. The tests were composed of two tasks, differing in their complexity: recording words in isolation and words in utterances. Stimuli consisted of English words (n= 4266) with word-initial voiceless stops (/p, t, k/). Stimuli were controlled for stress, following vowel, and word familiarity  and were measured for VOT using Praat (Boersma & Weenink, 2022).</p> <p>Results from statistical analysis coupled with a visual inspection of the data indicated that the experimental group performed similarly in the three stages of the study and that the visual feedback paradigm did not result in changes in VOT. However, some degree of variation was found among the participants concerning their average VOTs. While some participants showed an overall increase (i.e., improvement) in English VOTs for the three phonemes /p/, /t/, and /k/ over time, other participants did not. In general, most of the participants produced English-like VOTs in the pretest, constituting a degree of ceiling effects. The rate of exposure to the target language and the saliency of English are factors that could have played a role in the development of the VOT scores of the participants before the study. Therefore, the discussion focuses on both the nature of the individual variability and the theoretical implications of ceiling effects found in the current study versus the lack of ceiling effects in other studies with similar populations.</p>

Stop-and-Go Adaptive Cruise Control (ACC+) is an extension of Adaptive Cruise Control (ACC) that works at low speed as well as normal highway speeds to regulate the speed of the vehicle relative to the vehicle it is following. In this thesis, we design an ACC+ controller for a scale model electric vehicle that ensures the robust performance of the system under various models of uncertainty. We capture the operation of the hybrid system via a state-chart model that performs mode switching between different digital controllers with additional decision logic to guarantee the collision freedom of the system under normal operation. We apply different controller design methods such as Linear Quadratic Regulator (LQR) and H-infinity and perform multiple simulation runs in MATLAB/Simulink to validate the performance of the proposed designs. We compare the practicality of our design with existing formally verified ACC designs from the literature. The comparisons show that the other formally verified designs exhibit unacceptable behaviour in the form of mode thrashing that produces excessive acceleration and deceleration of the vehicle. While simulations provide some assurance of safe operation of the system design, they do not guarantee system safety under all possible cases. To increase confidence in the system, we use Differential Dynamic Logic (dL) to formally state environmental assumptions and prove safety goals, including collision freedom. The verification is done in two stages. First, we identify the invariant required to ensure the safe operation of the system and we formally verify that the invariant preserves the safety property of any system with similar dynamics. This procedure provides a high level abstraction of a class of safe solutions for ACC+ system designs. Second, we show that our ACC+ system design is a refinement of the abstract model. The safety of the closed loop ACC+ system is proven by verifying bounds on the system variables using the KeYmaera verification tool for hybrid systems. The thesis demonstrates how practical ACC+ controller designs optimized for fuel economy, passenger comfort, etc., can be verified by showing that they are a refinement of the abstract high level design. / Thesis / Master of Applied Science (MASc)

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Ride sharing—the bundling of simultaneous trips of several people in one vehicle—may help to reduce the carbon footprint of human mobility. However, the complex collective dynamics pose a challenge when predicting the efficiency and sustainability of ride sharing systems. Standard door-to-door ride sharing services trade reduced route length for increased user travel times and come with the burden of many stops and detours to pick up individual users. Requiring some users to walk to nearby shared stops reduces detours, but could become inefficient if spatio-temporal demand patterns do not well fit the stop locations. Here, we present a simple model of dynamic stop pooling with flexible stop positions. We analyze the performance of ride sharing services with and without stop pooling by numerically and analytically evaluating the steady state dynamics of the vehicles and requests of the ride sharing service. Dynamic stop pooling does a priori not save route length, but occupancy. Intriguingly, it also reduces the travel time, although users walk parts of their trip. Together, these insights explain how dynamic stop pooling may break the trade-off between route lengths and travel time in door-to-door ride sharing, thus enabling higher sustainability and service quality.

High Spectral Resolution Lidar (HSRL) is a backscatter lidar technique that employs an optical/spectral filter to distinguish between particulate (Mie) and molecular (Rayleigh) backscattered light. By separating the two types of returns, higher accuracy measurements are possible that will enable improved climate models, air quality measurements, and climate forecasting. A spaceborne HSRL instrument can provide great impact in these areas by enabling near-continuous measurements across the Earth, however the optical filter technology has typically been too complex for reliable long-duration space flight due to the need for complicated and costly electro-optic feedback loops, extra alignment detectors, and additional laser sources. Furthermore, these complexities limit the filter from use in other applications. In this research, a high-performance, ultra-narrowband interferometric optical filter with a specific thermo-optical behavior has been designed and built. The interferometer has been designed such that it can be reliably adjusted/tuned by simply monitoring and adjusting the temperature. The greatly reduced operational complexity was made possible through high-accuracy thermal characterization of the interferometer materials, combined with detailed Structural-Thermal-Optical-Performance (STOP) modeling to capture the complicated interactions between the materials. The overall design process, fabrication procedures, and characterization of the optical filter are presented. / Doctor of Philosophy / LiDAR (an acronym for Light Detection and Ranging) is a technology that can be used to measure properties of the atmosphere. It is similar to radar, but uses much smaller light waves rather than larger radio waves, enabling more detailed information to be obtained. High Spectral Resolution Lidar (HSRL) is a lidar technique that uses a high precision optical filter to distinguish between light that scatters from particulates (such as dust, smoke, or fog) and light that scatters from molecules (such as oxygen, nitrogen, or carbon dioxide) in the atmosphere. By separating the two types of backscattered light, higher accuracy measurements are possible that will enable improvements in climate models, air quality measurements, and climate forecasting. A spaceborne HSRL instrument can provide great impact in these areas by enabling near-continuous measurements across the Earth; however, the optical filter technology has typically been too complex for reliable long-duration spaceflight due to the need for complicated and expensive additional hardware. In this research, a high-performance HSRL optical filter that can be reliably operated by simply monitoring and adjusting the temperature has been designed, built, and tested. The greatly-reduced operational complexity has been made possible through a new process that enables more accurate prediction of the complicated interactions between the materials of the optical filter. This process is based on a combination of high-accuracy characterization of the materials and detailed structural-thermal-optical-performance (STOP) modeling. The overall design process, fabrication procedures, and characterization of the optical filter are presented.

Self-regulation, the ability to guide behavior according to one’s goals, plays an integral role in understanding loss of control over unwanted behaviors, for example in alcohol use disorder (AUD). Yet, experimental tasks that measure processes underlying self-regulation are not easy to deploy in contexts where such behaviors usually occur, namely outside the laboratory, and in clinical populations such as people with AUD. Moreover, lab-based tasks have been criticized for poor test–retest reliability and lack of construct validity. Smartphones can be used to deploy tasks in the field, but often require shorter versions of tasks, which may further decrease reliability. Here, we show that combining smartphone-based tasks with joint hierarchical modeling of longitudinal data can overcome at least some of these shortcomings. We test four short smartphone-based tasks outside the laboratory in a large sample (N = 488) of participants with AUD. Although task measures indeed have low reliability when data are analyzed traditionally by modeling each session separately, joint modeling of longitudinal data increases reliability to good and oftentimes excellent levels. We next test the measures’ construct validity and show that extracted latent factors are indeed in line with theoretical accounts of cognitive control and decision-making. Finally, we demonstrate that a resulting cognitive control factor relates to a real-life measure of drinking behavior and yields stronger correlations than single measures based on traditional analyses. Our findings demonstrate how short, smartphone-based task measures, when analyzed with joint hierarchical modeling and latent factor analysis, can overcome frequently reported shortcomings of experimental tasks.

I’ve chosen primary to analyze commercial form of advertising by world leading companies; McDonald’s, Coca-Cola and HP due to their implementation of global advertising. The fourth campaign that’s being analyzed is not of commercial type instead it’s characterized as an informative campaign that the ideal organization Amnesty is carring out.  The study has been successful in gathering data that could be presented in correlation with already established theories and then comparing the results. The goal of the research is to create an understanding regarding global advertising as well as the scientific debate that’s going on within the subject. The scientific research has been debated for a long time regarding advertising that’s positioned globally; whether it should be standardized or adapted. This means whether advertising should look the same in all countries or if it should be adapted to a nation’s specific culture. Scientists haven’t yet been successful in establishing what’s considered to be more prominent due to various diverse opinions. By implementing content analysis together with semiotic analysis as a reinforcer, the study was able to examine the global advertising’s design and their common characteristics. Within this study the campaigns have been studied both visually and verbally in addition to their messages and values. The McDonald’s and Coke campaign has been categorized as advertising that reflect specific kinds of lifestyles and therefore characterized as “lifestyle format”. HP campaign on the other hand was using celebrities. This contributed that their global campaign became very personal because the celebrities were reflecting their own personality in the commercials. That’s why HP was categorized as the “personalized format” while Amnesty remained characterized as an informative campaign. Results show that these campaigns’ global form of advertising weren’t only implementing standardized form but also incorporated adapted commercial characteristics as well. This is what the theorizers Hassan, Craft and Kortam call a”hybrid strategy” that’s by their opinion most effective form of global advertising. Another important result was that the “creative strategy” (its promise/statement) is what makes the campaign cohesive. While the “creative tactic” (the visual elements) differs more or less within an advertising campaign. / Jag har valt att främst analysera kommersiella kampanjer från de världsledande företagen McDonald’s, Coca-Cola och HP eftersom de tillämpar global form av reklam.  Den fjärde kampanjen som analyseras är inte av kommersiellt slag då den karaktäriseras som en informativ kampanj som den ideella organisationen Amnesty har genomfört.  Studien har lyckats generera data som kunde sättas i relation med de redan fastställda teorierna och på så vis jämföra resultaten. Forskningens mål är att skapa en förståelse angående global reklam samt den vetenskapliga debatten i ämnet. Den vetenskapliga forskningen har länge debatterat angående om reklam som appliceras globalt borde vara standardiserad eller anpassad, det vill säga om den ska se lika ut i alla länder eller om man borde anpassa den till varje lands individuella kultur. Forskarna har fortfarande inte kommit fram till vad som anses vara mest effektivt då en splittrad syn angående denna fråga uppstår.   Genom kvalitativ innehållsanalys med förstärkning av den semiotiska analysen så kunde studien granska den globala reklamens utformning och dess gemensamma karaktäristiker som uppstår. I denna studie så har reklamkampanjerna granskats både visuellt och språkmässigt samt dess budskap och värderingar. Reklamkampanjerna McDonald’s och Coca-Cola blev kategoriserade som den form av reklam som reflekterar specifika livsstilar och därför karaktäriserades som ”livsstilsformatet”. HP är den reklamkampanj som använde sig av kändisar. Detta gjorde att deras globala reklam blev väldigt personlig då den reflekterade kändisarnas personligheter. Därför kategoriserades HP:s reklamkampanj som det” personifierade formatet” medan Amnesty förblev karaktäriserad som informativ form av kampanj. Resultatet visade att dessa reklamkampanjers globala reklam inte endast implementerade standardiserad form utan likaså integrerade anpassad form. Detta kallar teoretikerna Hassan, Craft och Kortam för ”hybridstrategi” och anses enligt dem vara mest effektivt tillvägagångssätt när det gäller global reklam.  En annan viktig sak som resultatet påvisade var att den ”kreativa strategin” (dess utlovande/påstående) är det som gör kampanjen sammanhängande medan den ”kreativa taktiken” (dess visuella element) mer eller mindre skiljer sig inom en kampanj.