During the Old Uighur period, many works were translated into Old Uighur under the influence of Buddhism. Among these works, literary works such as $Da{\acute{s}}akarmapath{\bar{a}}vad{\bar{a}}nam{\bar{a}}l{\bar{a}}$ hold an important place. These works were usually translated from Pali to Sanskrit, from Sanskrit to Sogdian, Tocharian and Chinese, and to Old Uighur from these languages. These works which were added to the Old Uighur repertoire by translation indicate that different peoples along the ancient Silk Road had deep linguistic interactions with one another. Aside from these works, other narratives that we have been so far unable to determine whether they were translations, adaptations or original works have also been discovered. The Tale of King Chashtana, which was found in the work titled $Da{\acute{s}}akarmapath{\bar{a}}vad{\bar{a}}nam{\bar{a}}l{\bar{a}}$, is one of the tales we have been unable to classify as a translation or an original work. This tale has never been discovered with this title or this content in the languages of any of the peoples that were exposed to Buddhism along the Silk Road. On the other hand, the person whom the protagonist of this tale was named after has a very important place in the history of India, one of the countries that the Silk Road goes through. Saka Mahakshatrapa Chashtana (or Cashtana), a contemporary of Nahapana, declared himself king in Gujarat. A short time later, Chashtana, having invaded Ujjain and Maharashtra, established a powerful Saka kingdom in the west of India. His descendants reigned in the region for a long time. Another important fact about Chashtana is that coinage minted in his name was used all along the Silk Road. Chashtana, who became a significant historical figure in north western India, inspired the name of the protagonist of a tale in Old Uighur. That it is probable that the tale of King Chashtana is an original Old Uighur tale and not found in any other languages of the Silk Road brings some questions to mind: Who is Chashtana, the hero of the story? Is he related to the Saka king Chashtana in any way? What sort of influence did Chashtana have on the Silk Road and its languages? If this tale which we have never encountered in any other language of the Silk Road is indeed an original tale, why did the Old Uighurs use the name of an important Saka ruler? Is Saka-Uighur contact in question, given tales of this kind? What can we say about the historical and cultural geography of the Silk Road, given the fact that coinage was minted in his name and used along the Silk Road? In this study, I will attempt to answer these questions and share the information we have gleaned about Chashtana the hero of the tale and the Saka king Chashtana. One of the main aim of this study is to reveal the relationship between the narrative hero Chashtana and the Saka king Chashtana according to this information. Another aim of this study is to understand the history of the Saka, the Uighur and the Silk Road and to reveal the relationship between these three important subjects of history. The importance of the Silk Road will be emphasized again with the understanding of these relations. In this way, new information about Chashtana, who is an important name in the history of the India and the Silk Road, will be put forward. The history of the Sakas will be viewed from a different perspective through the Old Uighur Buddhist story.
This study identifies the terms frequently used together with energy in online science news articles and topics of the news reports to find out how the term energy is used in everyday life and to draw implications for science curriculum and instruction about energy. A total of 2,171 online news articles in science category published by 11 major newspaper companies in Korea for one year from March 1, 2018 were selected by using energy as a search term. As a result of natural language processing, a total of 51,224 sentences consisting of 507,901 words were compiled for analysis. Using the R program, term frequency analysis, semantic network analysis, and structural topic modeling were performed. The results show that the terms with exceptionally high frequencies were technology, research, and development, which reflected the characteristics of news articles that report new findings. On the other hand, terms used more than once per two articles were industry-related terms (industry, product, system, production, market) and terms that were sufficiently expected as energy-related terms such as 'electricity' and 'environment.' Meanwhile, 'sun', 'heat', 'temperature', and 'power generation', which are frequently used in energy-related science classes, also appeared as terms belonging to the highest frequency. From a network analysis, two clusters were found including terms related to industry and technology and terms related to basic science and research. From the analysis of terms paired with energy, it was also found that terms related to the use of energy such as 'energy efficiency,' 'energy saving,' and 'energy consumption' were the most frequently used. Out of 16 topics found, four contexts of energy were drawn including 'high-tech industry,' 'industry,' 'basic science,' and 'environment and health.' The results suggest that the introduction of the concept of energy degradation as a starting point for energy classes can be effective. It also shows the need to introduce high-tech industries or the context of environment and health into energy learning.
Automatic Target Recognition (ATR) technology is emerging as a core technology of Future Combat Systems (FCS). Conventional ATR is performed based on IMINT (image information) collected from the SAR sensor, and various image-based deep learning models are used. However, with the development of IT and sensing technology, even though data/information related to ATR is expanding to HUMINT (human information) and SIGINT (signal information), ATR still contains image oriented IMINT data only is being used. In complex and diversified battlefield situations, it is difficult to guarantee high-level ATR accuracy and generalization performance with image data alone. Therefore, we propose a knowledge graph-based ATR method that can utilize image and text data simultaneously in this paper. The main idea of the knowledge graph and deep model-based ATR method is to convert the ATR image and text into graphs according to the characteristics of each data, align it to the knowledge graph, and connect the heterogeneous ATR data through the knowledge graph. In order to convert the ATR image into a graph, an object-tag graph consisting of object tags as nodes is generated from the image by using the pre-trained image object recognition model and the vocabulary of the knowledge graph. On the other hand, the ATR text uses the pre-trained language model, TF-IDF, co-occurrence word graph, and the vocabulary of knowledge graph to generate a word graph composed of nodes with key vocabulary for the ATR. The generated two types of graphs are connected to the knowledge graph using the entity alignment model for improvement of the ATR performance from images and texts. To prove the superiority of the proposed method, 227 documents from web documents and 61,714 RDF triples from dbpedia were collected, and comparison experiments were performed on precision, recall, and f1-score in a perspective of the entity alignment..
This is a paper that examines the meaning and changes of how Dalgang Song, a parenting song, is accepted in pansori works and how it plays a role in the narrative of the work. In Chapter 2, Compared the lyrics of Dalgang-Dalgang in actual parenting scene and Dalgang-Dalgang in Pansori's work. As a result, the songs in Pansori, show some differences in lyrics, but most of them kept the narrative structure intact. Among them, Gangreung-maehwa-ga maintained the phrase "Dalgang-Dalgang" in front and back, making the least changes. Simcheong-ga and Jeokbyeok-ga maintained their epic structures, but the the front and the rear phrase turned into a "Uh huh, Doong doong". And Dalgang-Dalgang was sung mostly by its mother or grandmother at the actual parenting scene, but the song in Pansori, was all sung by men. Dalgang song in Pansori, had a mostly Gyemyeon melody due to the genre characteristics of Pansori. Also Dalgang-Dalgang for actual parenting, was sung with a leisurely, soft beat. But Dalgang song in Pansori's works were sung rhythmical with Jungjungmori rhythm or Jajinmori rhythm to maximize joy. In Chapter 3, I discussed the roles and meanings of Dalgang song contained in Pansori. Dalgang-Dalgang of Simcheong-ga appeared in the crucial process of Sim Hak-kyu's return to will of life through Simcheong after the death of his wife. In Jeokbyeok-ga, Dalgang song also appeared as a tool to recall the happy memories with his son. On the other hand, Dalgang-Dalgang of Gangreung-maehwa-ga played a role of expressing affection for relationships between men and women, not between parents and children. This is beyond the original meaning of parenting, which means the hedonistic and excessive affection of Mr. Gol. The desire to change a relationship between a man and a woman into between parents and children is also found in Kim Yeon-soo's Chunhyang-ga. This change is an example of how the role and meaning of Dalgang song has changed dramatically as it was inserted into pansori. And the reason why Dalgang-Dalgang was so important in the narrative of Pansori was because of The lyrics of the song contain the love of the baby.
This study aims to closely read Kim Jong-il's "About Stage Drama Arts" and disclose the new reality as evaluated by him. The study took the method by which to compare Kim Jong-il's theory on drama and North Korea's drama theory in the 1950s, and the findings of this study revealed that it was irrational to grant the adjective "new" to Kim Jong-il's drama theory. This is because tradition inheritance and newness cross each other. First, his tradition inheritance aspect was found in his playwriting method. In playwriting method, Kim Jong-il's argument about characters and language is an extension of the 1950s drama theory, and his theory on JongZa(seeds) is the transformation of the concept proposed in the 1950s. Also, the expression means of dramas and drama arts is dialogue, and his guideline to focus on the art of conversation rather than on acting is interpreted to be a reduced concept of drama arts, compared with the 1950s drama theory. On the other hand, his newness aspect can be clearly discovered in the materialization of stage. The fixed stage background, without dark change, shifts to another situation as it is, and this stage setting is clearly distinguished from the previous stage setting. The attempt is worth highly evaluating to allow the stage to reflect actors' emotional flows and let them act. Also, the attempt is distinctively distinguished from previous drama theories to allow the chorus' positive involvement in dramas so as to directly deliver characters' emotions to the audience and to trigger the audience' response as intended by creators. From the perspectives of drama evaluation, Kim Jong-il's theory and practice regarding stage and music is understood to maximize the audio-visual effects. Therefore, Kim Jeong-il's drama theory, as he argues, is not a completely new theory, but a transformational inheritance of existing drama theories, and a creation theory with focus on expansion of spectacles.
Sang-Gu Lee;Doyoung Park;Jae Yoon Lee;Dong Sun Lim;Jae Hwa Lee
The Mathematical Education
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v.63
no.2
/
pp.123-138
/
2024
This study described the utilization of ChatGPT in teaching and students' learning processes for the course "Introductory Mathematics for Artificial Intelligence (Math4AI)" at 'S' University. We developed a customized ChatGPT and presented a learning model in which students supplement their knowledge of the topic at hand by utilizing this model. More specifically, first, students learn the concepts and questions of the course textbook by themselves. Then, for any question they are unsure of, students may submit any questions (keywords or open problem numbers from the textbook) to our own ChatGPT at https://math4ai.solgitmath.com/ to get help. Notably, we optimized ChatGPT and minimized inaccurate information by fully utilizing various types of data related to the subject, such as textbooks, labs, discussion records, and codes at http://matrix.skku.ac.kr/Math4AI-ChatGPT/. In this model, when students have questions while studying the textbook by themselves, they can ask mathematical concepts, keywords, theorems, examples, and problems in natural language through the ChatGPT interface. Our customized ChatGPT then provides the relevant terms, concepts, and sample answers based on previous students' discussions and/or samples of Python or R code that have been used in the discussion. Furthermore, by providing students with real-time, optimized advice based on their level, we can provide personalized education not only for the Math4AI course, but also for any other courses in college math education. The present study, which incorporates our ChatGPT model into the teaching and learning process in the course, shows promising applicability of AI technology to other college math courses (for instance, calculus, linear algebra, discrete mathematics, engineering mathematics, and basic statistics) and in K-12 math education as well as the Lifespan Learning and Continuing Education.
Journal of The Korean Association For Science Education
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v.29
no.8
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pp.990-1010
/
2009
To derive brain-based evolutionary educational principles, this study examined the studies on the structural and functional characteristics of human brain, the biological evolution occurring between- and within-organism, and the evolutionary attributes embedded in science itself and individual scientist's scientific activities. On the basis of the core characteristics of human brain and the framework of universal Darwinism or universal selectionism consisted of generation-test-retention (g-t-r) processes, a Model of Brain-based Evolutionary Scientific Teaching for Learning (BEST-L) was developed. The model consists of three components, three steps, and assessment part. The three components are the affective (A), behavioral (B), and cognitive (C) components. Each component consists of three steps of Diversifying $\rightarrow$ Emulating (Executing, Estimating, Evaluating) $\rightarrow$ Furthering (ABC-DEF). The model is 'brain-based' in the aspect of consecutive incorporation of the affective component which is based on limbic system of human brain associated with emotions, the behavioral component which is associated with the occipital lobes performing visual processing, temporal lobes performing functions of language generation and understanding, and parietal lobes, which receive and process sensory information and execute motor activities of the body, and the cognitive component which is based on the prefrontal lobes involved in thinking, planning, judging, and problem solving. On the other hand, the model is 'evolutionary' in the aspect of proceeding according to the processes of the diversifying step to generate variants in each component, the emulating step to test and select useful or valuable things among the variants, and the furthering step to extend or apply the selected things. For three components of ABC, to reflect the importance of emotional factors as a starting point in scientific activity as well as the dominant role of limbic system relative to cortex of brain, the model emphasizes the DARWIN (Driving Affective Realm for Whole Intellectual Network) approach.
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