The purpose of this study was to examine the second language development of a native-speaker of Spanish learning English over a period of 15 months. More specifically, I explored the interaction of complexity (advanced forms of grammar and vocabulary), accuracy (grammatical and semantic), and fluency, commonly referred to as the CAF constructs. While findings in CAF literature tend to focus on one construct using experimental or cross-sectional studies (Bulté & Housen, 2012; Kormos & Dénes, 2004; Vyatkina, 2012), this case study investigated non-linear and interconnected CAF development, periods of fluctuation, and the effects of motivational factors on 14 variables. In order to explore the data as a system developing simultaneously, Complex Dynamic Systems Theory (CDST) (Larsen-Freeman, 1997; 2006) was applied as the theoretical framework. Through CDST’s theoretical lens and the tools developed for it (Verspoor, de Bot & Lowie, 2011), I found that knowledge variables (lexical diversity, accuracy, and elaboration) maintained consistent correlations, whereas their relationship with fluency variables (speed, repairs, and pauses) changed based on the cognitive strain the learner was experiencing at the time. I also found that the learner shifted his focus between the knowledge variables and that the complexity and accuracy variable on which he chose to focus appeared to be affected by changing motivational factors. / Applied Linguistics

no / This research explores the possibility that a person's (perceiver's) prospects of making a correct inference of another person's (target's) inner states depends on the personal characteristics of the target, potentially relating to how readable they are. Twenty-seven targets completed the Empathy Quotient (EQ) and were classified as having low, average or high EQ. They were unobtrusively videoed while thinking of an event of happiness, gratitude, anger and sadness. After observing targets thinking of such a past event, fifty-two perceivers (participants) in Study 1 were asked to infer what the target was thinking, and fifty perceivers in Study 2 were asked to rate the target's expression – positive or negative. Results suggested that (1) perceivers' accuracy in detecting targets' thoughts depended on which EQ group the target belonged to, and (2) target readability is not a proxy measure for level of target expressiveness. In other words, something about EQ status renders targets more or less easy to read in a way that is not simply explained by expressive people being more readable. We conclude with discussion of the importance of the target's trait as well as situation they experience in determining how accurately a perceiver might infer their inner states.

Automatic Speech Recognition (ASR) research has been primarily focused towards large-scale systems and industry, while other areas that require attention are often over-looked by researchers. For this reason, this research looked at automatic speech recognition at the consumer level. Many individual consumers will purchase and use automatic software recognition for a different purpose than that of the military or commercial industries, such as telecommunications. Consumers who purchase the software for personal use will mainly use ASR for dictation of correspondences and documents. Two ASR dictation software packages were used to conduct the study. The research examined the relationships between (1) speech recognition software training and word accuracy, (2) error-correction time by the user and word accuracy, and (3) correspondence type and word accuracy. The correspondences evaluated were those that resemble Personal, Business, and Technical Correspondences. Word accuracy was assessed after initial system training, five minutes of error-correction time, and ten minutes of error-correction time. Results indicated that word recognition accuracy achieved does affect user satisfaction. It was also found that with increased error-correction time, word accuracy results improved. Additionally, the results found that Personal Correspondence achieved the highest mean word accuracy rate for both systems and that Dragon Systems achieved the highest mean word accuracy recognition for the Correspondences explored in this research. Results were discussed in terms of subjective and objective measures, advantages and disadvantages of speech input, and design recommendations were provided. / Master of Science

Road smoothness is one of the most important road functional characteristics because it affects ride quality, operation cost, and vehicle dynamic load. There are many types of devices that measure the road profile, which is often used to compute different smoothness indices. The development of performance-based specifications and pavement warranties that use ride quality as a performance measure has increased the need for accurate measurement of pavement smoothness. For this reason, researchers have compared and evaluated the performance of available profilers and several profiler accuracy criteria have been proposed. However, there is not a definite answer on the ability of available profilers to accurately measure the actual road profile as well as the various smoothness indices. A recent profiler round-up compared the performance of 68 profilers on five test sections at Virginia Smart Road. The equipment evaluated included high-speed, light-weight, and walking-speed profilers, in addition to the reference device (rod and level). The test sites included two sites with traditional hot-mix asphalt (HMA) surfaces, one with a coarse-textured HMA surface, one on a continuously reinforced concrete pavement (CRCP), and one on a jointed plain concrete pavement (JCP). This investigation used a sample of the data collected during the experiment to compare the profiles and International Roughness Index (IRI) measured by each type of equipment with each other and with the reference. These comparisons allowed determination of the accuracy and repeatability capabilities of the existing equipment, evaluation of the appropriateness of various profiler accuracy criteria, and recommendations of usage criteria for different applications. The main conclusion of this investigation is that there are profilers available that can produce the level of accuracy (repeatability and bias) required for construction quality control and assurance. However, the analysis also showed that the accuracy varies significantly even with the same type of device. None of the inertial profilers evaluated met the current IRI bias standard requirements on all five test sites. On average, the profilers evaluated produced more accurate results on the conventional smooth pavement than on the coarse textured pavements. The cross-correlation method appears to have some advantages over the conventional point-to-point statistics method for comparing the measured profiles. On the sites investigated, good cross-correlation among the measured and reference profiles assured acceptable IRI accuracy. Finally, analysis based on Power Spectral Density and gain method showed that the profiler gain errors are nonuniformly distributed and that errors at different wavelengths have variable effects on the IRI bias. / Master of Science

<p dir="ltr">This paper examines the resilience of global food and energy supply chains against the background of recent world disruptions such as China-US trade war, novel coronavirus disease 2019 (COVID-19) pandemic, and Russia’s incursion into Ukraine. It aims at improving forecast methodologies and providing early indications of market stressors by considering three key cracks or spreads within the food and energy industries soy crush spread, crude crack spread, and cattle finish spread. The study uses Autoregressive Integrated Moving Average (ARIMA), Exponential Smoothing State Space (ETS) and Vector Error Correction Model (VECM). The profit relationships are examined in these models with regard to potential problems for supply chains in the soybean crushing industry, cattle finishing, and crude oil refining sectors. It also compares forecasting approaches like univariate (ARIMA & ETS) and multivariate (VECM). This means that it tries to gauge how accurate each one is in predicting where a given sector may be heading or where there are risks likely to happen. The situation is further complicated by on-going capacity expansions in these sectors which are expected to face more challenges due to geopolitical tensions as well as efforts to mitigate climate change internationally.The overall goal of the research is to develop forecasting methods to help industry participants, policymakers, and small producers make informed decisions amid volatility and the threat of imminent supply chain disruptions.</p>

Radiographers and other healthcare professionals are becoming increasingly involved in radiological reporting, for instance plain radiographs, mammography and ultrasound. Systematic reviews of research evidence can help to assimilate a knowledge base by ordering and evaluating the available evidence on the reporting accuracy of different professional groups. This article reviews the biases that can undermine the results of plain ¿lm reading performance studies. These biases are subdivided into three categories. The ¿rst category refers to the selection of subjects, including both ¿lms and professionals, and covers the validity of generalizing results beyond the study population. The other two categories are concerned with study design and the interpretation both of ¿lms and of reports and the effect on study validity. An understanding of these biases is essential when designing such studies and when interpreting the results of existing studies.

Endometriosis is a heterogeneous chronic pain and inflammatory disease associated with negative impacts on quality of life. Among the phenotypes of endometriosis, deep endometriosis (DE) is the most aggressive form of the disease, associated with complex disease states, such as adhesions within the pouch of Douglas (POD) and bowel DE. The most common site of DE is the uterosacral ligaments (USLs), which are bilateral structures between the uterus and sacrum conjoined by the torus uterinus (TU), with a prevalence of 20 to 70%. The USLs have historically been the hardest to visualize using non-invasive modalities, such as transvaginal ultrasound (TVS), resulting in poor identification of endometriosis when present on/within the USLs, contributing to the significant diagnostic delay associated with the disease. This thesis details a novel diagnostic approach, utilizing TVS within the posterior vaginal fornix as the index test and laparoscopic visualization as the reference standard, aiming to evaluate the diagnostic accuracy of TVS for DE of the USLs and TU. Additionally, the USLs and TU are commonly associated with complex disease presentations, including POD obliteration and bowel DE, though the impact on diagnostic accuracy remains unknown. We theorize that these concurrent complex disease states will lead to the distortion of the anatomical environment and, in turn, negatively alter the diagnostic performance of the novel posterior approach. This thesis further aimed to determine the impact of concurrent complex disease states on diagnostic performance. We found enhanced diagnostic accuracy in the detection of endometriosis in the left USL, right USL, and TU compared to previous studies, with our sensitivity ranging from 75.0-100%, specificity of 100%, positive predictive values of 100%, and negative predictive value ranging from 88.6-100%. Furthermore, contrary to our hypothesis, diagnostic performance appeared unaffected by the presence of complex disease states. The ability to diagnose USL DE non-invasively can have profound implications for introducing personalized treatment plans in a timely manner, which should improve patient outcomes. With this enhanced diagnostic performance, fewer people will require a surgical diagnosis, which reduces the burden on the health system and decreases surgical complications associated with diagnostic surgery. / Thesis / Master of Science (MSc) / Endometriosis is a common gynecological disease involving the abnormal growth of uterine-like cells outside the uterus, causing significant negative impacts on quality of life and diagnostic delays. Deep endometriosis (DE) is the most aggressive form, infiltrating surrounding tissues and leading to complex disease states. The uterosacral ligaments (USLs; connective structures between the lower spine and uterus) are the most common site for DE, but diagnosing them non-invasively remains challenging, aiding the diagnostic delay. Following updated classification guidelines, the overarching aim of this thesis is to enhance our understanding of transvaginal ultrasound (TVS) as a safe and rapid diagnostic for DE of the USLs and TU. In doing so, this thesis aims to assess the accuracy of a new TVS technique for DE of the USLs and determine how other related health conditions might affect the accuracy of this diagnostic approach. The findings from this study indicate that using TVS could greatly assist in diagnosing DE in the USLs, potentially leading to more personalized treatment approaches by healthcare providers and better outcomes for individuals with endometriosis. In summary, this research contributes significantly to our understanding and management of this complex condition.

Yes / Based on a robust analysis of the existing literature on performance appraisal (PA), this paper makes a case for an integrated framework of effectiveness of performance appraisal (EPA). To achieve this, it draws on the expanded view of measurement criteria of EPA, i.e. purposefulness, fairness and accuracy, and identifies their relationships with ratee reactions. The analysis reveals that the expanded view of purposefulness includes more theoretical anchors for the purposes of PA and relates to various aspects of human resource functions, e.g. feedback and goal orientation. The expansion in the PA fairness criterion suggests certain newly established nomological networks, which were ignored in the past, e.g. the relationship between distributive fairness and organization‐referenced outcomes. Further, refinements in PA accuracy reveal a more comprehensive categorization of rating biases. Coherence among measurement criteria has resulted in a ratee reactions‐based integrated framework, which should be useful for both researchers and practitioners.

Yes / Aims: Levels of false positive referral to ophthalmology departments can be high. This study aimed to evaluate commonality between false positive referrals in order to find the factors which may influence referral accuracy. Methods: In 2007/08, a sample of 431 new Ophthalmology referrals from the catchment area of Bradford Royal Infirmary were retrospectively analysed. Results: The proportion of false positive referrals generated by optometrists decreases with experience at a rate of 6.2% per year since registration (p < 0.0001). Community services which involved further investigation done by the optometrist before directly referring to the hospital were 2.7 times less likely to refer false positively than other referral formats (p = 0.007). Male optometrists were about half as likely to generate a false positive referral than females (OR = 0.51, p = 0.008) and as multiple/corporate practices in the Bradford area employ less experienced and more female staff, independent practices generate about half the number of false positive referrals (OR = 0.52, p = 0.005). Conclusions: Clinician experience has the greatest effect on referral accuracy although there is also a significant effect of gender with women tending to refer more false positives. This may be due to a different approach to patient care and possibly a greater sensitivity to litigation. The improved accuracy of community services (which often refer directly after further investigation) supports further growth of these schemes. / This study was funded by the University of Bradford.

Background: In a computed protein multiple sequence alignment, the coreness of a column is the fraction of its substitutions that are in so-called core columns of the gold-standard reference alignment of its proteins. In benchmark suites of protein reference alignments, the core columns of the reference alignment are those that can be confidently labeled as correct, usually due to all residues in the column being sufficiently close in the spatial superposition of the known three-dimensional structures of the proteins. Typically the accuracy of a protein multiple sequence alignment that has been computed for a benchmark is only measured with respect to the core columns of the reference alignment. When computing an alignment in practice, however, a reference alignment is not known, so the coreness of its columns can only be predicted. Results: We develop for the first time a predictor of column coreness for protein multiple sequence alignments. This allows us to predict which columns of a computed alignment are core, and hence better estimate the alignment's accuracy. Our approach to predicting coreness is similar to nearest-neighbor classification from machine learning, except we transform nearest-neighbor distances into a coreness prediction via a regression function, and we learn an appropriate distance function through a new optimization formulation that solves a large-scale linear programming problem. We apply our coreness predictor to parameter advising, the task of choosing parameter values for an aligner's scoring function to obtain a more accurate alignment of a specific set of sequences. We show that for this task, our predictor strongly outperforms other column-confidence estimators from the literature, and affords a substantial boost in alignment accuracy.