scholarly journals Elementary Algebra on Vedic Mathematics

2021 ◽  
Vol 6 (6) ◽  
pp. 82-94
Author(s):  
Krishna Kanta Parajuli

The South Asian region has a long history of discovering new ideas, ideologies, and technologies. Since the Vedic period, the land has been known as a fertile place for innovative discoveries. The Vedic technique used by Bharati Krishna Tirthaji is unique among South Asian studies. The focus of this study was mostly on algebraic topics, which are typically taught in our school level. The study also looked at how Vedic Mathematics solves issues of elementary algebra using Vedic techniques such as Paravartya Yojayet, Sunyam Samyasamuccaye, Anurupye Sunyamanyat, Antyayoreva and Lopanasthapanabhyam. The comparison and discussion of the Vedic with the conventional techniques indicate that the Vedic Mathematics and its five unique formulas are more beneficial and realistic to those learners who are experiencing problems with elementary level algebra utilizing conventional methods.

Author(s):  
Pashaura Singh

Over 350 entries This new dictionary provides accessible definitions of the terms that the growing number of students of Sikhism will encounter. It covers beliefs, practices, festivals, sacred sites, and principal languages, as well as the social and religious processes through which Sikhism has evolved. A major focus is the teachings of the founder of Sikhism, Gurū Nānak, and doctrinal developments under subsequent Gurūs. Incorporating the 500-year history of Sikhism, from its birth in northern India to its more recent spread around the world, it covers the interplay between the Sikh tradition and other religious traditions, including Hindu and Sufi. It is an invaluable first reference for students and teachers of Sikhism, religious studies, South Asian studies, philosophy, and the related disciplines of history, sociology, and anthropology, as well as for all practising Sikhs and anyone with an interest in Sikh religion and culture.


Author(s):  
Hussein Mohammed ◽  
Volker Märgner ◽  
Giovanni Ciotti

AbstractAutomatic pattern detection has become increasingly important for scholars in the humanities as the number of manuscripts that have been digitised has grown. Most of the state-of-the-art methods used for pattern detection depend on the availability of a large number of training samples, which are typically not available in the humanities as they involve tedious manual annotation by researchers (e.g. marking the location and size of words, drawings, seals and so on). This makes the applicability of such methods very limited within the field of manuscript research. We propose a learning-free approach based on a state-of-the-art Naïve Bayes Nearest-Neighbour classifier for the task of pattern detection in manuscript images. The method has already been successfully applied to an actual research question from South Asian studies about palm-leaf manuscripts. Furthermore, state-of-the-art results have been achieved on two extremely challenging datasets, namely the AMADI_LontarSet dataset of handwriting on palm leaves for word-spotting and the DocExplore dataset of medieval manuscripts for pattern detection. A performance analysis is provided as well in order to facilitate later comparisons by other researchers. Finally, an easy-to-use implementation of the proposed method is developed as a software tool and made freely available.


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