Diagrammatic Reasoning and Modelling in the Imagination: The Secret Weapons of the Scientific Revolution

Just before the Scientific Revolution, there was a "Mathematical Revolution", heavily based on geometrical and machine diagrams. The "faculty of imagination" (now called scientific visualization) was developed to allow 3D understanding of planetary motion, human anatomy and the workings of machines. 1543 saw the publication of the heavily geometrical work of Copernicus and Vesalius, as well as the first Italian translation of Euclid

Approaches Used to Recognise and Decipher Ancient Inscriptions: A Review

Inscriptions play a vital role in historical studies. In order to boost tourism and academic necessities, archaeological experts, epigraphers and researchers recognised and deciphered a great number of inscriptions using numerous approaches. Due to the technological revolution and inefficiencies of manual methods, humans tend to use automated systems. Hence, computational archaeology plays an important role in the current era. Even though different types of research are conducted in this domain, it still poses a big challenge and needs more accurate and efficient methods. This paper presents a review of manual and computational approaches used to recognise and decipher ancient inscriptions.Keywords: ancient inscriptions, computational archaeology, decipher, script

Ancient Chinese Tombs: Western Han Dynasty Chapter

The study of history is one way of preserving human culture. In China, a country with thousands of years long history, a vast number of historical events have been recorded in different literary works, including history books, fictions, biographies, and so on. However, we still need evidence to support or verify those literatures. One physical evidence are antiques excavated from tombs of different dynasties. The ancient tomb mirrors a micro society of a certain dynasty. This project presented in this study is a 3D environmental design, comprised of four 3D scenes in high quality rendering to show the architecture and interior environment of an ancient tomb. Due to the long history of China (more than 3000 years), it is impossible to cover all dynasties here. Hence in this study, the author focuses on the Western Han dynasty (206BC - 9AD) because it was one of the peaks of the development of Chinese culture, and the royal mausoleums from Han spread all over the city of Taiyuan where rich cultural relics were perfectly excavated. This 3D design reproduced the ancient tomb’s architecture using softwares such as, Maya, Zbrush and Substance Painter. The author created 3 important rooms including the chariot room, the front room and the main room. In each room, specific lighting, different decoration and beautiful burial objects were created and carefully added to restore an incredibly lifelike 3D ancient tomb. This 3D design can easily attract people’s attention and help audience understand this ancient cultural relics that were extensively destroyed by now

Machine learning for ancient languages: a survey

Ancient languages preserve the cultures and histories of the past. However, their study is fraught with difficulties, and experts must tackle a range of challenging text-based tasks, from deciphering lost languages to restoring damaged inscriptions, to determining the authorship of works of literature. Technological aids have long supported the study of ancient texts, but in recent years advances in artificial intelligence and machine learning have enabled analyses on a scale and in a detail that are reshaping the field of humanities, similarly to how microscopes and telescopes have contributed to the realm of science. This article aims to provide a comprehensive survey of published research using machine learning for the study of ancient texts written in any language, script, and medium, spanning over three and a half millennia of civilizations around the ancient world. To analyze the relevant literature, we introduce a taxonomy of tasks inspired by the steps involved in the study of ancient documents: digitization, restoration, attribution, linguistic analysis, textual criticism, translation, and decipherment. This work offers three major contributions: first, mapping the interdisciplinary field carved out by the synergy between the humanities and machine learning; second, highlighting how active collaboration between specialists from both fields is key to producing impactful and compelling scholarship; third, highlighting promising directions for future work in this field. Thus, this work promotes and supports the continued collaborative impetus between the humanities and machine learning

Thai dance knowledge archive framework based on Labanotation represented in 3D animation

© 2017 IEEE.Southeast Asia is one of the most rapidly growing regions in the world with natural and cultural resources. It is important to pass on the cultural knowledge to the next generation. Intangible Cultural Heritage like traditional dances, or folk dance is a valuable cultural knowledge to be maintained and passed on by transferring tacit knowledge, and even explicit knowledge such as books, or video presentations. Issues of passing on the knowledge can be the loss of knowledge from time to time by the reduction of the number of dance masters, unreliable sources, and low quality. To retrieve such valuable knowledge, there is a widely-used tool in Europe, in the United States, Asia and Southeast Asia, called 'Labanotation' which is about recording and analyzing the dance movement. This paper focuses on proposing a framework for a traditional Thai dance knowledge archive creating an ontology using knowledge engineering based on Labanotation by transferring notation scores to represent the dance in 3D Animation. The framework assists dancers, notators, knowledge engineers, software engineers to successfully communicate with each other