Variety of the Ciryllic Alphabet in Teaching Bulgarian as a Foreign Language

The focus of this article are the issues of teaching and acquiring Cyrillic alphabet. In the first part of the text a contrastive analysis of the Cyrillic and Latin alphabet is made. The second and third part are dealing respectively with reading and writing (manuscript and cursive handwriting and keyboarding).

BuddhistRoadPaper 1.2 "Toward A Typology of Chödrup’s (Tib. Chos Grub, Chin. Facheng 法成) Cursive Handwriting: A Palaeographical Perspective"

In this paper, I focus on the palaeography of a collection of eight Tibetan manuscripts hypothesised to have been written by the same scribal hand. The eight manuscripts—IOL Tib J 217, IOL Tib J 686, IOL Tib J 687, IOL Tib J 625, IOL Tib J 588, IOL Tib J 619, P. T. 770, and P. T. 783v—are closely related, not merely in light of their sophisticated cursive handwriting, but also by virtue of their common textual genre (being summaries or commentaries rather than direct scriptural translations) and thematic content: these Tibetan texts were all based on Chinese sources and attributed to Gö Chödrup (fl. first half of the 9th c., Tib. ’Gos Chos grub, Chin. Wu Facheng 吳法成), either directly or indirectly. Moreover, many manuscripts produced by the imperial Tibetan copying project contain editorial records written in the same hand; these records indicate that Chödrup acted as the final proofreader. Therefore, we can now more confidently attribute this hand to Chödrup himself. By establishing a typology of this handwriting and offering a table of how syllables are written by this hand in the appendix, this paper contributes to a better reading of manuscripts containing this type of script and can potentially provide a benchmark for further recognition of works written in the same hand.

Marianne Moore’s Ghost Revisions

The Rosenbach Museum and Library contains The Marianne Moore Library (MML), the largest collection of Marianne Moore’s personal objects and literary papers. Among these objects and papers are the poet’s personal copies of each of her published books. One of the first observations to be made about Moore’s revising method is her habit of revising on copies of her books from her first publication, Poems (1921), through her final publication, Complete Poems (1967), often neatly writing in an updated word or phrase in small cursive handwriting. Indeed, her lifelong habit of using published texts as sites of revision began with Poems (1921) not long after it was published. To date, I have not found a study that addresses these revisions made upon her own copies of her books, especially Poems (1921) and both editions of Observations (1924 and 1925). In order to better understand Moore’s revision process in her early years before becoming editor of The Dial, their curious presence becomes a prerequisite for reading and positing a chronology to the revisions on her manuscripts and typed scripts of her other early poetry. This essay intends to explore the revisions that Moore made on her two copies of Poems (1921) and on Observations (1924).

Children’s Online Handwriting Quality Analysis.

<div>An innovative e-learning project is presented in this paper, which is a mobile workbook that teaches handwriting at school. This mobile application proposes a new qualitative and quantitative analysis process of online cursive handwriting. It gives a real-time feedback, detects mistakes and helps teachers evaluate children’s writing skills. The main aim of this notebook is to aid kids learn how to write correctly. We analyze handwriting according to major criteria like shape, kinematics of the trace, position respect to the reference lines,</div><div>stroke order and direction.</div>

Children’s Online Handwriting Quality Analysis.

<div>An innovative e-learning project is presented in this paper, which is a mobile workbook that teaches handwriting at school. This mobile application proposes a new qualitative and quantitative analysis process of online cursive handwriting. It gives a real-time feedback, detects mistakes and helps teachers evaluate children’s writing skills. The main aim of this notebook is to aid kids learn how to write correctly. We analyze handwriting according to major criteria like shape, kinematics of the trace, position respect to the reference lines,</div><div>stroke order and direction.</div>

Workbook for e-Education: Children’s Online Handwriting Quality Analysis.

<div>This paper describes an innovative e-learning project which is the development of a digital workbook that helps teaching handwriting at school. In this work, we propose a new qualitative and quantitative analysis process of cursive handwriting. This process detects automatically mistakes, gives a real-time feedback and helps teachers evaluate children’s writing skills. The main aim of this digital workbook is to help children learn how to write correctly. The proposed process is composed of five main criteria: shape,direction, stroke order, position respect to the reference lines and kinematics of the trace. It analyzes the handwriting quality and gives automatically feedback based on the Beta-Elliptic Model using similarity detection (SD) and dissimilarity distance (DD) measure. Our work apprehends dynamic and visual representation of the acquired traces and selects efficient features adapted to various handwriting styles and multiple script languages such as Arabic, Latin, digits, and symbols drawing. It demonstrates that beta-elliptic is not only a model for segmentation and recognition but also a tool to evaluate handwriting. Our application offers two interactive interfaces respectively dedicated to learners, and experts or teachers who can adapt it easily to the specificity of each child. The validation of the proposed system is done on a database collected in Tunisia primary schools with 400 children. Experimental results show that the efficiency and robustness of our suggested framework that do help teachers and children by offering positive feedback throughout the handwriting learning process using tactile digital devices.</div>

Workbook for e-Education: Children’s Online Handwriting Quality Analysis.

<div>This paper describes an innovative e-learning project which is the development of a digital workbook that helps teaching handwriting at school. In this work, we propose a new qualitative and quantitative analysis process of cursive handwriting. This process detects automatically mistakes, gives a real-time feedback and helps teachers evaluate children’s writing skills. The main aim of this digital workbook is to help children learn how to write correctly. The proposed process is composed of five main criteria: shape,direction, stroke order, position respect to the reference lines and kinematics of the trace. It analyzes the handwriting quality and gives automatically feedback based on the Beta-Elliptic Model using similarity detection (SD) and dissimilarity distance (DD) measure. Our work apprehends dynamic and visual representation of the acquired traces and selects efficient features adapted to various handwriting styles and multiple script languages such as Arabic, Latin, digits, and symbols drawing. It demonstrates that beta-elliptic is not only a model for segmentation and recognition but also a tool to evaluate handwriting. Our application offers two interactive interfaces respectively dedicated to learners, and experts or teachers who can adapt it easily to the specificity of each child. The validation of the proposed system is done on a database collected in Tunisia primary schools with 400 children. Experimental results show that the efficiency and robustness of our suggested framework that do help teachers and children by offering positive feedback throughout the handwriting learning process using tactile digital devices.</div>

Artificial Neural Network for Cursive Handwriting Recognition System

Cursive Handwriting acknowledgment is an extremely testing zone because of the one of a kind styles of composing starting with one individual then onto the next. Right now, disconnected cursive composing character acknowledgment framework is portrayed utilizing an Artificial Neural Network. The highlights of every character written in the information are extricated and afterward sent to the neural system. Informational collections, having writings of various individuals are utilized in making framework. The suggested acknowledgment framework yields elevated steps of exactness when contrasted with the ordinary methodologies right now. This framework can effectively perceive cursive messages and convert them into auxiliary structure.