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Chapter 6 considers the scribes’ copying of the text itself in the fifteenth century, especially in works by Thomas Hoccleve and Geoffrey Chaucer and spurious lines added to Chaucer’s poetry. It queries the assumption that scribes vary the text a lot, and in three quantitative samples it suggests that, despite the difficulties of transcription and the acceptability of revision, scribes could copy exemplars very closely. As a result, despite the material differences between books, what most distinguished them was verbal likeness. It suggests that this reproduction reflects an interest in the text’s survival as an immaterial, verbal artefact, partly out of respect for certain kinds of English poetry, and a disregard for its material form.
The sophisticated spatial reference tools that exist today greatly facilitate studies of spatial ecology. Historically, however, the lack of such tools meant that spatial data were often imprecise, ambiguous or sometimes inaccurate. This can hinder or confound assessments of whether species distributions have changed in the past over decadal timescales. This is the case for Adélie penguins breeding at the southern limit of their breeding range in East Antarctica. In this short note, we resolve uncertainties in the locations of Adélie penguin breeding sites observed in the first population survey in Prydz Bay in 1981 by examining the original working notes of that work in combination with data from a recent survey in 2009 and a recently published spatial reference and identification system for coastal East Antarctica. By clarifying the historical locations, we conclude that the Adélie penguin breeding distribution has remained unchanged in this region over the past three decades, and we provide a robust baseline for assessing change in the future.
We emphasize that the ability for a corpus to provide accurate estimates of a linguistic parameter depends on the combined influence of domain considerations (coverage bias and selection bias) and distribution considerations (corpus size). By using a series of experimental corpora on the domain of Wikipedia articles, we can demonstrate the impact of corpus size, coverage bias, selection bias, and stratification on representativeness. Empirical results show that robust sampling methods and large sample sizes can only give you a better representation of the operational domain (i.e. overcome selection bias). However, by themselves, these factors cannot help you achieve accurate quantitative-linguistic analyses for the actual domain (i.e. overcome coverage bias) Uncontrolled domain considerations can lead to unpredictable results with respect to accuracy.
We define a linguistic distribution as the range of values for a quantitative linguistic variable across the texts in a corpus. An accurate parameter estimate means that the measures based on the corpus are close to the actual values of a parameter in the domain. Precision refers to whether or not the corpus is large enough to reliably capture the distribution of a particular linguistic feature. Distribution considerations relate to the question of how many texts are needed. The answer will vary depending on the nature of the linguistic variable of interest. Linguistic variables can be categorized broadly as linguistic tokens (rates of occurrence for a feature) and linguistic types (the number of different items that occur). The distribution considerations for linguistic tokens and linguistic types are fundamentally different. Corpora can be “undersampled” or “oversampled” – neither of which is desirable. Statistical measures can be used to evaluate corpus size relative to research goals – one set of measures enables researchers to determine the required sample size for a new corpus, while another provides a means to determine precision for an existing corpus. The adage “bigger is better” aptly captures our best recommendation for studies of words and other linguistic types.
The discipline of “diplomatics” – originating in the seventeenth century to systematically test the authenticity of medieval documents – has more recently been adapted to the study of digital records and their systems. In establishing the necessary elements for the long-term preservation of authentic records, archival diplomatics provides one possible (and powerful) analytic framework and methodology for analyzing the trustworthiness of records, including those to be found in blockchain and distributed ledgers. Regardless of the type of blockchain and distributed ledger system under examination, each relies upon trust in the ledger and in the records the ledger contains. Yet each type of blockchain and distributed ledger system still has limitations when judged against archival diplomatic standards of records’ trustworthiness, which demands the accuracy, reliability, and authenticity of records. By gaining an understanding of the elemental requirements for trust in records (and in record systems), there is hope that the designers of blockchain and distributed ledger systems might continue to improve the evidentiary quality of blockchain records and recordkeeping.
Studies exploring the accuracy of equations calculating resting energy expenditure (REE) in patients with Crohn’s disease (CD) are lacking. The aim of this study was to investigate the accuracy of REE predictive equations against indirect calorimetry in CD patients. REE was measured using indirect calorimetry (mREE) after an overnight fasting. Fourteen predictive equations, with and without body composition analysis parameters, were compared with mREE using different body weight approaches. Body composition analysis was performed using dual X-ray absorptiometry. One hundred and eighty-six CD outpatients (102 males) with mean age 41·3 (sd 14·1) years and 37·6 % with active disease were evaluated. Mean mREE in the total sample was 7255 (sd 1854) kJ/day. All equations underpredicted REE and showed moderate correlations with mREE (Pearson’s r or Spearman’s rho 0·600–0·680 for current weight, all P-values < 0·001). Accuracy was low for all equations at the individual level (28–42 and 25–40 % for current and adjusted body weight, respectively, 19–33 % for equations including body composition parameters). At the group level, accuracy showed wide limits of agreement and proportional biases. Accuracy remained low when sample was studied according to disease activity, sex, BMI and medication use. All predictive equations underestimated REE and showed low accuracy. Indirect calorimetry remains the best method for estimating REE of patients with CD.
This chapter presents a general overview of sensor characterization from a system perspective, without any reference to a specific implementation. The systems are defined on the basis of input and output signal description and the overall architecture is discussed, showing how the information is transduced, limited, and corrupted by errors. One of the main points of this chapter is the characterization of the error model, and how this one could be used to evaluate the uncertainty of the measure, along with its relationship with resolution, precision and accuracy of the overall system. Finally, the quantization process, which is at the base of any digital sensor systems, is illustrated, interpreted, and included in the error model.
Get up to speed with the fundamentals of electronic sensor design with this comprehensive guide, and discover powerful techniques to reduce the overall design timeline for your specific applications. Includes a step-by-step introduction to a generalized information-centric approach for designing electronic sensors, demonstrating universally applicable practical approaches to speed up the design process. Features detailed coverage of all the tools necessary for effective characterization and organization of the design process, improving overall process efficiency. Provides a coherent and rigorous theoretical framework for understanding the fundamentals of sensor design, to encourage an intuitive understanding of sensor design requirements. Emphasising an integrated interdisciplinary approach throughout, this is an essential tool for professional engineers and graduate students keen to improve their understanding of cutting-edge electronic sensor design.
Effective nutrition policies require timely, accurate individual dietary consumption data; collection of such information has been hampered by cost and complexity of dietary surveys and lag in producing results. The objective of this work was to assess accuracy and cost-effectiveness of a streamlined, tablet-based dietary data collection platform for 24-hour individual dietary recalls (24HR) administered using INDDEX24 platform v. a pen-and-paper interview(PAPI) questionnaire, with weighed food record (WFR) as a benchmark. This cross-sectional comparative study included women 18–49 years old from rural Burkina Faso (n 116 INDDEX24; n 115 PAPI). A WFR was conducted; the following day, a 24HR was administered by different interviewers. Food consumption data were converted into nutrient intakes. Validity of 24HR estimates of nutrient and food group consumption was based on comparison with WFR using equivalence tests (group level) and percentages of participants within ranges of percentage error (individual level). Both modalities performed comparably estimating consumption of macro- and micronutrients, food groups and quantities (modalities’ divergence from WFR not significantly different). Accuracy of both modalities was acceptable (equivalence to WFR significant at P < 0·05) at group level for macronutrients, less so for micronutrients and individual-level consumption (percentage within ±20 % for WFR, 17–45 % for macronutrients, 5–17 % for micronutrients). INDDEX24 was more cost-effective than PAPI based on superior accuracy of a composite nutrient intake measure (but not gram amount or item count) due to lower time and personnel costs. INDDEX24 for 24HR dietary surveys linked to dietary reference data shows comparable accuracy to PAPI at lower cost.
A core claim of big-data-algorithm enthusiasts – producers, champions, consumers – is that big-data algorithms are able to deliver insightful and accurate predictions about human behaviour. This chapter challenges this claim. I make three contributions: First, I perform a conceptual analysis and argue that big-data analytics is by design a-theoretical and does not provide process-based explanations of human behaviour, making it unfit to support insight and deliberation, which is transparent to both legal experts and non-experts. Second, I review empirical evidence from dozens of data sets, which suggests that the predictive accuracy of mathematically sophisticated algorithms is not consistently higher than that of simple rules (rules that tap on available domain knowledge or observed human decision-making); rather, big-data algorithms are less accurate across a range of problems, including predicting election results and criminal profiling (this work presented here refer to understanding and predicting human behaviour in legal and regulatory contexts). Third, I synthesize the above points in order to conclude that simple, process-based, domain-grounded theories of human behaviour should be put forth as benchmarks, which big-data algorithms, if they are to be considered as tools for personalization, should match in terms of transparency and accuracy.
As an empirical science, the study of animal behaviour involves measurement. When an animal engages in a series of actions, such as exploring or catching prey, the problem becomes that of identifying suitable components from that stream of action to use as markers suitable to score. The markers selected reflect the observer’s hypothesis of the organisation of the behaviour. Unfortunately, in most cases, researchers only provide heuristic descriptions of what they measure. To make the study of animal behaviour more scientific, the hypotheses underlying the decision of what to measure should be made explicit so as to allow them to be tested. Using hypothesis testing as a guiding framework, several principles that have been shown to be useful in identifying behavioural organisation are presented, providing a starting point in deciding what markers to select for measurement.
Poor-quality measurements are likely to yield meaningless or unrepeatable findings. High-quality measurements are characterised by validity and reliability. Validity relates to whether the right quantity is measured and is assessed by comparing a metric with a gold-standard metric. Reliability relates to whether measurements are repeatable and is assessed by comparing repeated measurements. The accuracy and precision with which measurements are made affect both validity and reliability. A major source of unreliability in behavioural data comes from the involvement of human observers in the measurement process. Where trade-offs are necessary, it is better to measure the right quantity somewhat unreliably than to measure the wrong quantity very reliably. Floor and ceiling effects can make measurements useless for answering a question, even if they are valid and reliable. Outlying data points should only be removed if they can be proved to be biologically impossible or to result from errors.
In a previous study (Sarré, Grosbois & Brudermann, 2019), we explored the effects of various corrective feedback (CF) strategies on interlanguage development for the online component of a blended English as a foreign language (EFL) course we had designed and implemented. Our results showed that unfocused indirect CF (feedback on all error types through the provision of metalinguistic comments on the nature of the errors made) combined with extra computer-mediated micro-tasks was the most efficient CF type to foster writing accuracy development in our context. Following up on this study, this paper further explores the effects of this specific CF type on learners’ written accuracy development in an online EFL course designed for freshmen STEM (science, technology, engineering, and mathematics) students. In the online course under study, this specific CF type was experimented with different cohorts of STEM learners (N = 1,150) over a five-year period (from 2014 to 2019) and was computer-assisted: CF provision online by a human tutor was combined with predetermined CF comments. The aim of this paper is to investigate the impact of this specific CF strategy on error types. In this respect, the data yield encouraging results in terms of writing accuracy development when learners benefit from this computer-assisted specific CF. This study thus helps to gain a better understanding of the role that CF plays in shaping students’ revision processes and could inform language (teacher) education regarding the use of digital tools for the development of foreign language accuracy and the issues related to online CF provision.
This chapter reviews themes in research into the effectiveness of oral corrective feedback, typically provided by language teachers, on L2 grammatical development. It synthesizes research evidence for the effects of oral corrective feedback on learners’ development of grammar and the relative efficacy of different corrective feedback strategies, such as output-prompting and input-providing. Further themes concern the effectiveness of oral corrective feedback on salient and non-salient grammatical features and in relation to learners’ varying levels of knowledge of the targeted features. Even though most research in this area concerns the development of accuracy, the chapter includes a review of the considerably smaller body of literature that offers insights into the potential value of oral corrective feedback on the development of fluency. The chapter reviews the different kinds of oral and written tests that have been used in research to gauge grammar learning, some of which teachers may wish to consider adopting to assess their learners. Based on the cumulative evidence from research, we make suggestions for classroom teachers, although we recognize that teachers’ decisions about the provision of oral corrective feedback are often based on multiple factors, including affective factors and teaching objectives.
While written language development involves reducing erroneous expressions, traditional error-based measures are problematic for several reasons, including low inter-coder reliability for lexical errors, limited sensitivity for capturing development within a short time period, and the questionable separation of lexical and grammatical errors. Given these problems, we explore automated accuracy measures rooted in a usage-based theory of Second Language Acquisition, which views language as a set of constructions or chunks. For this study, we examined 139 essays in terms of using traditional measures of complexity, accuracy, lexical sophistication, and fluency, as well as novel corpus-based n-gram measures. A factor analysis was conducted to explore how traditional measures grouped with corpus-based measures, and regression analyses were used to examine how corpus-based measures predicted error counts and holistic accuracy scores. With the results of these analyses, we suggest that automated n-gram based measures are a viable alternative to traditional accuracy measures.
This article explores how Qin Dynasty bureaucrats attained accuracy and precision in producing and designing measuring containers. One of the salient achievements of the Qin empire was the so-called unification of measurement systems. Yet measurement systems and the technological methods employed to achieve accuracy and precision in ancient China have scarcely been explored in English-language scholarship. I will examine the material features of the containers and reconstruct the production methods with which the clay models, molds, and cores of the containers were prepared before casting. I also investigate the inscriptions on the containers to determine whether they were cast or engraved. In so doing, I supply the field of Qin history with additional solid evidence about how accuracy and precision were defined in the Qin empire.
The docking simulators are significant ground test equipment for aerospace projects. The fidelity of docking simulation highly depends on the accuracy performance. This paper investigates the kinematic accuracy for the developed docking simulator. A novel kinematic calibration method which can reduce the number of parameters for error modeling is presented. The principle of parameters separation is studied. A simplified error model is derived based on Taylor series. This method can contribute to the simplification of the error model, fewer measurements, and easier convergence during the parameters identification. The calibration experiment validates this method for further accuracy enhancement.
This study introduces a new real-time kinematic (RTK) positioning method which is suitable for baselines of different lengths. The method merges carrier-phase wide-lane, and ionosphere-free observation combinations (LWLC) instead of using pseudo-range, and carrier-phase ionosphere-free combination (PCLC), or single-frequency pseudo-range and phase combination (P1L1). In a first step, the double-differenced wide-lane ambiguities were calculated and fixed using the pseudo-range and carrier-phase wide-lane combination observations. Once the double-differenced wide-lane integer ambiguities were known, the wide-lane combined observations were regarded as accurate pseudo-range observations. Subsequently, the carrier-phase wide-lane, and ionosphere-free combined observations were used to fix the double-differenced carrier-phase integer ambiguities, achieving the final RTK positioning. The RTK positioning analysis was performed for short, medium, and long baselines, using the P1L1, PCLC, and LWLC methods, respectively. For a short baseline, the LWLC method demonstrated positioning accuracy similar to the P1L1 method, and performed better than the PCLC method. For medium and long baselines, the positioning accuracy of the LWLC method was slightly higher than those of the PCLC and P1L1 methods. In conclusion, the LWLC method provided high-precision RTK positioning results for baselines with different lengths, as it used high-precision carrier-phase observations with fixed ambiguities instead of low-precision pseudo-range observations.