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Materials for HybridNeuro webinar titled "Validation of results: statistical models and MU identification accuracy"
Aleš Holobar, Nina Murks, 2024, complete scientific database of research data

Abstract: This dataset contains a collection of teaching materials that were used in the HybridNeuro project webinar titled "Validation of results: statistical models and MU identification accuracy". The webinar was presented by Aleš Holobar and covered the complexities of motor unit (MU) identification accuracy, regression analysis and Bayesian models. The primary aim of the webinar was to spark a robust discussion within the scientific community, particularly focusing on the application and implications of linear mixed models and Bayesian regression in the realm of MU identification. The teaching materials include Matlab and R source code for statistical analysis of the included data, as well as three examples of MU identification results in CSV format (from both synthetic and experimental HDEMG signals). The presentation slides in PDF format are also included. The dataset is approximately 9 MB in size.
Keywords: HybridNeuro, webinar, teaching materials, statistical models, regression analysis, motor unit identification, matlab, rstudio, statistics, surface high density electromyogram (HDEMG), tibialis anterior, dataset
Published in DKUM: 30.05.2024; Views: 221; Downloads: 23
.pdf Full text (108,35 KB)
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New computational models for better predictions of the soil-compression index
Ahmet Demir, 2015, original scientific article

Abstract: The compression index is one of the important soil parameters that are essential for geotechnical designs. Because laboratory and in-situ tests for determining the compression index (Cc) value are laborious, time consuming and costly, empirical formulas based on soil parameters are commonly used. Over the years a number of empirical formulas have been proposed to relate the compressibility to other soil parameters, such as the natural water content, the liquid limit, the plasticity index, the specific gravity. These empirical formulas provide good results for a specific test set, but cannot accurately or reliably predict the compression index from various test sets. The other disadvantage is that they tend to use a single parameter to estimate the compression index (Cc), even though Cc exhibits spatial characteristics depending on several soil parameters. This study presents the potential for Genetic Expression Programming (GEP) and the Adaptive Neuro-Fuzzy (ANFIS) computing paradigm to predict the compression index from soil parameters such as the natural water content, the liquid limit, the plastic index, the specific gravity and the void ratio. A total of 299 data sets collected from the literature were used to develop the models. The performance of the models was comprehensively evaluated using several statistical verification tools. The predicted results showed that the GEP and ANFIS models provided fairly promising approaches to the prediction of the compression index of soils and could provide a better performance than the empirical formulas.
Keywords: compression index, statistical analysis, genetic expression programming, adaptive neuro-fuzzy, empirical equations
Published in DKUM: 14.06.2018; Views: 1499; Downloads: 91
.pdf Full text (274,65 KB)
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PHONETIC ANALYSIS OF THE COCKNEY DIALECT IN THE TV SERIES EASTENDERS
Tina Novak, 2015, undergraduate thesis

Abstract: The graduation thesis presents the dialectal features of Cockney in the series EastEnders. The theoretical part includes the definitions of the following concepts: language variety, dialect levelling, accent, dialect. This is followed by a brief presentation of the historical background and social perception of Cockney. The last and most extended segment of the theoretical part presents the linguistic features of Cockney, with emphasis on the phonological characteristics and the comparison of its phonological features with those of Received Pronunciation and Estuary English. The empirical part consists of the phonetic transcription of two chosen episodes of EastEnders, accounted for through auditory analysis. As in spoken conversation, especially in rapid speech, the neighbouring phonemes of words affect each other’s articulation, consideration is given to most common accommodation processes that appear in connected speech: assimilation, elision, epenthesis, and liaison. The aim of the graduation thesis is to analyse the phonetic features of Cockney in EastEnders. Moreover, the examination indicates how frequently a certain Cockney feature is used by each speaker and in what way its occurrence varies depending on the age, gender, and education of the characters in the series. The results of the statistical analysis are given for each phoneme separately.
Keywords: Cockney, phonetic analysis, EastEnders, British English, dialectology, phonetics, phonology, statistical analysis
Published in DKUM: 19.01.2016; Views: 10876; Downloads: 311
.pdf Full text (2,90 MB)

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