This study introduces and experimentally validates a novel approach that combines Instruction fine-tuning and Low-Rank Adaptation (LoRA) fine-tuning to optimize the performance of Large Language Models (LLMs). These models have become revolutionary tools in natural language processing, showing remarkable performance across diverse application areas. However, optimizing their performance for specific domains necessitates fine-tuning of the base models (FMs), which is often limited by challenges such as data complexity and resource costs. The proposed approach aims to overcome these limitations by enhancing the performance of LLMs, particularly in the analysis precision and efficiency of national Research and Development (R&D) data. The study provides theoretical foundations and technical implementations of Instruction fine-tuning and LoRA fine-tuning. Through rigorous experimental validation, it is demonstrated that the proposed method significantly improves the precision and efficiency of data analysis, outperforming traditional fine-tuning methods. This enhancement is not only beneficial for national R&D data but also suggests potential applicability in various other data-centric domains, such as medical data analysis, financial forecasting, and educational assessments. The findings highlight the method's broad utility and significant contribution to advancing data analysis techniques in specialized knowledge domains, offering new possibilities for leveraging LLMs in complex and resource- intensive tasks. This research underscores the transformative potential of combining Instruction fine-tuning with LoRA fine-tuning to achieve superior performance in diverse applications, paving the way for more efficient and effective utilization of LLMs in both academic and industrial settings.

We compared and analyzed the astronomy terms currently used by astronomers in the two Koreas to promote inter-Korean astronomy cooperation. We analyzed a total of 2716 pairs of terms common in both Koreas glossaries, using the astronomical terminology contained in the South Korean source, the ‘Terminology of Astronomy’, and the North Korean source, ‘Mirror 2.0’. For each pair of terms, their morphological features and meanings were compared. We categorized into 11 groups for comparison of astronomical terms. We found that most of the terms are used similarly in the two Koreas. About 47% of the total is similar in form. Although terms are different, meanings communicate about 37% of the total. As a result, similar terms used by the two Koreas correspond to about 85% of the total. However, 15% of terms are difficult to understand because they have different forms or meanings such as diffraction (회 절/에돌이), flare (플레어/요반) etc. Further research on terms that are used differently by the two Koreas, and the conversion of appropriate terms through mutual understanding should be made in the future.

Recent rapid development of the Chinese economy based on science and technology is challenging Korean industries and economy. Since the driving force for this rapid development of China is known to be scientific technologies, the purpose of this research is to confirm the current status of Chinese scientific research in the field of "Materials Science and Engineering" and propose a strategy for competition with China. Even though there are numerous journals of "Materials Science and Engineering", the 10 most popular journals with high impact factors were selected to cover general materials, nano materials, bio materials, and electronic materials. It was found that the number of scientific papers written by Chinese scientists for the materials field in the 10 journals was slowly increasing from the year 2000 until 2005, but has been rapidly increasing since 2005. This research found that Chinese research activities in the traditional metallic materials and nano materials have tremendously increased to occupy around 30 % or more papers published in several major journals related with materials science and engineering. On the other hand, bio materials and electronic materials research has not been pursued so actively; however, very recently the number of publications in these fields is also beginning to increase. To compete with this tremendously growing Chinese scientific development, Korea should have a policy of "selection and concentration" in materials-related fields, including basic science in nano, bio, and electronic materials.

이 연구는 현직 중등교사의 관점에서 입직 전 예비교사가 갖춰야 할 교직 적성과 인성 요소 간 중요도 분석을 목적으로 계층 분석적 의사결정방법(AHP)을 적용하여 경력 10년 이상의 현직 중등교사 36명으로부터 얻은 응답 자료를 분석하였다. 그 결과 첫째, 교직 적 인성 영역 중의지적 영역이 상대적으로 가장 중요한 것으로 나타났다. 둘째, 영역 내 하위요소 간 중요도 분석 결과 관계형성능력(인지 영역), 공감/포용력(정서 영역), 항상 학습하는 자세(의지 영역)등이 각 영역에서 상대적으로 가장 중요한 요소들로 도출되었다. 끝으로 전체 하위요소 간 중요도를 분석한 결과 의지적 영역의 항상 학습하는 자세, 변화에 대한 긍정적 마인드, 성실성/책임감 등이 상대적으로 가장 중요한 적 인성 요소로 도출되었다.