Learning to Sort Handwritten Text Lines in Reading Order through Estimated Binary Order Relations

2021 ◽  
Author(s):  
Lorenzo Quiros ◽  
Enrique Vidal
Keyword(s):  
Order Relations ◽  
Handwritten Text ◽  
Reading Order

EFFECTS OF LANGUAGE AND PRIOR KNOWLEDGE LEVELS ON HYPERTEXT READING COMPREHENSION

2020 ◽  
Author(s):  
Kshema Jose
Keyword(s):  
Reading Comprehension ◽  
Prior Knowledge ◽  
Language Proficiency ◽  
Language Competence ◽  
Additional Information ◽  
Reading Order ◽  
Low Levels ◽  
Online Texts ◽  
Characteristic Features ◽  
Better Than

<p>This study observed how two hypertext features – absence of a linear or author-specified order and availability of multiple reading aids – influence reading comprehension processes of ESL readers. Studies with native or highly proficient users of English, have suggested that readers reading hypertexts comprehend better than readers reading print texts. This was attributed to (i) presence of hyperlinks that provide access to additional information that can potentially help overcome comprehension obstacles and (ii) the absence of an author-imposed reading order that helps readers exercise cognitive flexibility. An aspect that remains largely un-researched is how well readers with low language competence comprehend hypertexts. This research sought to initiate research in the area by exploring the question: Do all ESL readers comprehend a hypertext better than a print text?</p> <p>Keeping in mind the fact that a majority of readers reading online texts in English can be hindered by three types of comprehension deficits – low levels of language proficiency, non-availability of prior knowledge, or both – this study investigated how two characteristic features of hypertext, viz., linking to additional information and non-linearity in presentation of information, affect reading comprehension of ESL readers. </p> <p>Two types of texts that occur in the electronic medium – linear or pre-structured texts and non-linear or self-navigating texts, were used in this study. Based on a comparison of subjects’ comprehension outcomes and free recalls, text factors and reader factors that can influence hypertext reading comprehension of ESL readers are identified. </p> Contradictory to what many researchers believe, results indicate that self-navigating hypertexts might not promote deep comprehension in all ESL readers.

Using Video Self-Modelling to Teach Combined Vocational and Social Skills to an Adult with Autism Spectrum Disorder

2020 ◽  
Author(s):  
Nicholas Parsons ◽  
Fiore D'Aprano ◽  
Matthew Hughes ◽  
Annie Parish ◽  
Nasia Outsikas
Keyword(s):  
Autism Spectrum Disorder ◽  
Social Skills ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Vocational Skills ◽  
Baseline Design ◽  
Old Adult ◽  
Reading Order ◽  
Successful Employment ◽  
Employment Rates

Abstract Background, Aims and MethodsAdults with ASD have difficulty in learning vocational and social skills, which often translates into low employment rates. Video self-modelling (VSM) is an effective educational technique for low functioning individuals with Autism Spectrum Disorder, with the ability to teach challenging vocational skills as well as basic social skills. Procedures and Outcomes The present study examined the use of video self-modelling to teach these skills to a 22-year-old adult with Autism Spectrum Disorder. Target behaviours categories included (1) reading order forms, (2) transporting goods, and (3) engaging with customers. A multiple baseline design was used to evaluate the effectiveness of the videos in teaching these target behaviours. The dependent variables were the percentage of tasks completed correctly, and quantitative prompt dependency using a least to most prompting strategy. Results and Conclusions Results showed that VSM modestly improved reading order forms and transporting goods, and moderately improved engagement with customers. ImplicationsThis intervention resulted in the successful employment of an adult with ASD in a job that he specifically desired, whilst teaching him skills he specifically struggled with. As such, VSM should be considered for others wanting to learn combined social and vocational skills.

On the numerical semigroup generated by {bn+1+i+bn+i−1b−1∣i∈N}$\begin{array}{} \{b^{n+1+i}+\frac{b^{n+i}-1}{b-1}\mid i\in\mathbb{N}\} \end{array}$

2020 ◽  
Vol 30 (4) ◽  
pp. 257-264
Author(s):  
Ze Gu
Keyword(s):  
Numerical Semigroup ◽  
Frobenius Number ◽  
Embedding Dimension ◽  
Order Relations ◽  
Positive Integers

AbstractLet b, n be two positive integers such that b ≥ 2, and S(b, n) be the numerical semigroup generated by $\begin{array}{} \{b^{n+1+i}+\frac{b^{n+i}-1}{b-1}\mid i\in\mathbb{N}\} \end{array}$. Applying two order relations, we give formulas for computing the embedding dimension, the Frobenius number, the type and the genus of S(b, n).

Poverty, Philanthropy and Social Conditions in Victorian Britain

2020 ◽  
Vol 22 (1) ◽  
pp. 51-55
Author(s):  
Dawn Behrend
Keyword(s):  
Social Conditions ◽  
British Library ◽  
Settlement Houses ◽  
Handwritten Documents ◽  
Victorian Era ◽  
Victorian Britain ◽  
Handwritten Text ◽  
Handwritten Text Recognition ◽  
The Uk ◽  
Keyword Searching

Poverty, Philanthropy and Social Conditions in Victorian Britain published by Adam Matthew Digital is comprised of primary digital materials culled from three major archives in Britain and the UK focused on the experience of poverty in Victorian Britain and efforts involving economic, government, and social reform such as the Poor Law, workhouses, settlement houses, and philanthropic initiatives. Content is derived from the National Archives at Kew, British Library, and Senate House Library and includes pamphlets, correspondence, newspaper clippings, books, and other resources. A small portion of the collection utilizes Adam Matthew Digital’s Handwritten Text Recognition (HTR) to enable keyword searching of handwritten documents. The digitized images and documents are clear, searchable, and user-friendly to access, save, and share. Contract provisions are standard to the product with authenticated access across institutional locations and guidelines for Interlibrary Loan sharing. Pricing is determined by institutional size and enrollment. While the product is a one-time purchase, annual hosting fees apply for ongoing access. Content is currently heavily derived from one archive, the Senate House Library, with pamphlets from this source making up nearly half of the total holdings. Users seeking access to a more extensive collection of similar material may prefer subscribing to JSTOR which includes JSTOR 19th Century British Pamphlets with over 26,000 pamphlets along with secondary scholarly journals and eBooks on the Victorian era. While not providing the primary sources of Poverty, Philanthropy and Social Conditions in Victorian Britain or JSTOR, Historical Abstracts may be an alternative resource in providing access to notable scholarly resources on the period.

HANDWRITTEN WORD RECOGNITION USING CLASSIFIER ENSEMBLES GENERATED FROM MULTIPLE PROTOTYPES

2004 ◽  
Vol 18 (05) ◽  
pp. 957-974 ◽  
Author(s):  
SIMON GÜNTER ◽  
HORST BUNKE
Keyword(s):  
Handwriting Recognition ◽  
Recognition Rate ◽  
Classifier Ensembles ◽  
Multiple Classifier Systems ◽  
Classification Problems ◽  
Classifier Systems ◽  
Handwritten Text ◽  
Handwritten Text Recognition ◽  
Multiple Classifier ◽  
System 1

Handwritten text recognition is one of the most difficult problems in the field of pattern recognition. In this paper, we describe our efforts towards improving the performance of state-of-the-art handwriting recognition systems through the use of classifier ensembles. There are many examples of classification problems in the literature where multiple classifier systems increase the performance over single classifiers. Normally one of the two following approaches is used to create a multiple classifier system. (1) Several classifiers are developed completely independent of each other and combined in a last step. (2) Several classifiers are created out of one prototype classifier by using so-called classifier ensemble creation methods. In this paper an algorithm which combines both approaches is introduced and it is used to increase the recognition rate of a hidden Markov model (HMM) based handwritten word recognizer.

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