As the Fourth Industrial Revolution advances, smart factories have become a new manufacturing paradigm, integrating technologies such as Information and Communication Technology (ICT), the Internet of Things (IoT), Artificial Intelligence (AI), and big data analytics to overcome traditional manufacturing limitations and enhance global competitiveness. This study offers a comprehensive approach by evaluating both technological and economic performance of smart factory Research and Development (R&D) projects, addressing gaps in previous studies that focused narrowly on either aspect. The research combines Latent Dirichlet Allocation (LDA) topic modeling and Data Envelopment Analysis (DEA) to quantitatively compare the efficiency of various topics. This integrated approach not only identifies key research themes but also evaluates how effectively resources are utilized within each theme, supporting strategic decision-making for optimal resource allocation. Additionally, non-parametric statistical tests are applied to detect performance differences between topics, providing insights into areas of comparative advantage. Unlike traditional DEA methods, which face limitations in generalizing results, this study offers a more nuanced analysis by benchmarking efficiency across thematic areas. The findings highlight the superior performance of projects incorporating AI, IoT, and big data, as well as those led by the Ministry of Trade, Industry, and Energy (MOTIE) and small and medium-sized enterprises (SMEs). The regional analysis reveals significant contributions from non-metropolitan areas, emphasizing the need for balanced development. This research provides policymakers and industry leaders with strategic insights, guiding the efficient allocation of R&D resources and fostering the development of smart factories aligned with global trends and national goals.

본 연구는 YOLO(You Only Look Once)-Segmentation 기반 해양생물 탐지 모델의 성능 비교와 수중 이미지의 색상 왜곡 보정을 위한 딥러닝 모델 구축에 중점을 둔다. 탐지 모델 구축에는 Ultralytics에서 공식적으로 배포하는 YOLO의 버전별 객체분할 모델인 YOLOv5-Seg, YOLOv8-Seg, YOLOv9-Seg, YOLOv11-Seg를 활용하였으며, 22종의 해양생물 데이터셋을 사용해 동일한 학습 과정을 거쳤다. 이 를 통해 각 버전의 탐지 성능을 비교한 결과, YOLOv9c-Seg 모델이 정밀도(Precision) 0.908, 재현율(Recall) 0.912, mAP@50 0.943으로 가장 높 은 성능을 기록하며 최적의 모델로 선정되었다. 또한, 수중 환경에서 발생하는 색상 왜곡 문제를 해결하고 탐지 정확도를 높이기 위해 CLAHE, White Balance, Image Filter 등의 RGB 요소 변환 기법을 적용한 PhysicalNN 기반 이미지 보정 모델을 구축하였다. 선정된 탐지 모델 과 이미지 보정 모델을 이용해 수중영상 내 탐지된 생물의 위치를 정확히 파악하고, Monocular Depth Estimation(MDE) 알고리즘과 거리 및 크기 측정을 위한 가이드 스틱을 활용하여 대상 생물의 거리와 크기를 추정하였다. 이를 통해 단안 카메라 영상만으로도 3차원 공간의 해 양생물 크기와 이에 따른 체중을 간접적으로 추정하였으며, 향후 해양 생태계 모니터링에 활용할 수 있는 가능성을 시사한다.

In the context of the rapid development of information technology and the continuous transformation of work patterns, the phenomenon of work-related electronic communication during non-working hours has become increasingly prevalent, and its impact on employees has become an important research topic. This study conducted in-depth interviews with 18 employees from different industries and job levels, and used open coding and axial coding to conduct an in-depth analysis of the interview results to construct the relevant main categories and content framework. Based on this, a questionnaire was designed and 526 valid questionnaires were obtained through the Questionnaire Star platform. Subsequently, through reliability analysis, exploratory and confirmatory factor analysis, a systematic and comprehensive measurement dimension system was finally constructed. This system includes two first-level indicators of internal personal traits and external communication situations, and is further subdivided into six second-level indicators and eight third-level indicators. The scale system constructed in this study provides a scientific empirical basis for enterprises in managing work-related electronic communication during non-working hours, helps enterprises gain an in-depth understanding of the behavior patterns and ability characteristics of employees in this context, and thus optimize management strategies. At the same time, employees can also better understand their own situation based on this scale system, and then adjust their own behaviors and mindsets in a targeted manner to achieve a balance between work and life.

This paper explores a convergent approach that combines advanced informatics and computational science to develop road-paving materials. It also analyzes research trends that apply artificial-intelligence technologies to propose research directions for developing new materials and optimizing them for road pavements. This paper reviews various research trends in material design and development, including studies on materials and substances, quantitative structure–activity/property relationship (QSAR/QSPR) research, molecular data, and descriptors, and their applications in the fields of biomedicine, composite materials, and road-construction materials. Data representation is crucial for applying deep learning to construction-material data. Moreover, selecting significant variables for training is important, and the importance of these variables can be evaluated using Pearson’s correlation coefficients or ensemble techniques. In selecting training data and applying appropriate prediction models, the author intends to conduct future research on property prediction and apply string-based representations and generative adversarial networks (GANs). The convergence of artificial intelligence and computational science has enabled transformative changes in the field of material development, contributing significantly to enhancing the performance of road-paving materials. The future impacts of discovering new materials and optimizing research outcomes are highly anticipated.

PURPOSES : As evaluation methods for road paving materials become increasingly complex, there is a need for a method that combines computational science and informatics for new material development. This study aimed to develop a rational methodology for applying molecular dynamics and AI-based material development techniques to the development of additives for asphalt mixtures. METHODS : This study reviewed relevant literature to analyze various molecular models, evaluation methods, and metrics for asphalt binders. It examined the molecular structures and conditions required for calculations using molecular dynamics and evaluated methods for assessing the interactions between additives and asphalt binders, as well as properties such as the density, viscosity, and glass transition temperature. Key evaluation indicators included the concept and application of interaction energy, work of adhesion, cohesive energy density, solubility parameters, radial distribution function, energy barriers, elastic modulus, viscosity, and stress-strain curves. RESULTS : The study identified key factors and conditions for effectively evaluating the physical properties of asphalt binders and additives. It proposed selective application methods and ranges for the layer structure, temperature conditions, and evaluation metrics, considering the actual conditions in which asphalt binders were used. Additional elements and conditions considered in the literature may be further explored, considering the computational demands. CONCLUSIONS : This study devised a methodology for evaluating the physical properties of asphalt binders considering temperature and aging. It reviewed and selected useful indicators for assessing the interaction between asphalt binders, additives, and modified asphalt binders and aggregates under various environmental conditions. By applying the proposed methods and linking the results with informatics, the interaction between asphalt binders and additives could be efficiently evaluated, serving as a reliable method for new material development.

본 연구는 국가 연구개발(R&D) 과제 데이터를 기반으로 국내 화장품 산업의 연구개발 동향을 분석하여 중소기업의 경쟁력 강화 방안을 제시하고자 하였다. 2019년부터 2023년까지의 화장품 관련 국가 R&D 과제 데이터를 활용하여 연도별, 주요 수행 주체, 지역적 특성, 주요 부처, 주요 기능 및 효능별 R&D 현황을 종합적으로 분석하고 고찰함으로써, 중소기업 R&D의 방향성 및 전략을 도출하였다. 분석 결 과, 화장품 산업은 중소기업을 중심으로 다양한 기능성 제품 개발에 주력하고 있으며, 최근에는 특히 친환 경적이고 지속 가능한 소재 개발에 큰 비중을 두고 있는 것으로 나타났다. 지역적으로는 경기도와 충청북 도에서 R&D 활동이 가장 활발하며, 이는 지역 산업의 R&D 역량이 높음을 반영한다. 본 연구는 국가 R&D 과제 데이터 기반의 체계적인 R&D 종합 분석을 통해 화장품 산업의 최근 동향을 파악하고, 중소기 업의 시장 경쟁력 강화 및 지속 가능한 성장 전략 수립에 필요한 근거를 제공하였다. 이러한 연구 결과는 중소기업 뿐만 아니라 정책 입안자에게도 유용한 정보와 통찰을 제공하여, 화장품 산업의 발전을 위한 정 책 수립 및 실행에 중요한 기초자료로 활용될 수 있을 것이다.

The sustainable development of livelihood is of great significance to improve the livelihood of farmers. It‘s necessary to broaden farmers’ livelihood strategy choices. Intangible cultural heritage tourism diversifies livelihoods and improves stability of farmers‘ lives. Taking Yangjiabu Folk Art Park and Red Sorghum Movie City as research objects, this study uses sustainable livelihood analysis framework, in-depth interviews, and participatory observation methods to explore the impact of intangible cultural heritage tourism on sustainable livelihoods, providing reference for rural development in need of enriching livelihood strategies. The research finds that different paths of intangible cultural heritage tourism lead to different accumulation of livelihood capital. Therefore, when planning and developing intangible cultural heritage tourism, rural areas should solve the shortage of livelihood capital brought by different types of development paths, promoting sustainable development of intangible cultural heritage tourism and farmers’ livelihoods. Secondly, in the process of rural development of intangible cultural heritage tourism, there is a mutual transformation and substitution, mutual influence and restriction relationship between different livelihood capital. Rural development of intangible cultural heritage tourism needs to consider the relationship between various livelihood capital, ensuring they can promote each other and coordinate development.

산림치유는 다양한 자연의 요소를 활용하여 인체에 면역력을 높이는 건강증진 활동이다. 산림치유는 스트레스 해소, 삶의 질 향상, 심폐기능 향상, 혈액순환 등 심리적·생리적으로 긍정적 영향을 주는 것으 로 밝혀졌다. 그러나 산림치유 연구는 대부분이 프로그램 효과검증 위주의 연구로 산림치유자원 효과 에 대한 검증은 미비한 실정이다. 본 연구는 산림치유자원의 효과검증을 위해 숲 방문 이용객이 느끼는 산림치유자원인 피톤치드, 음이온 등을 측정하는 척도개발과 이에 따른 치유효과를 검증하는데 목적 이 있다. 효과검증을 위한 척도개발을 위해 선행연구 분석 후 산림치유자원과 치유효과를 선정하고 척 도를 구성하였다. 명품숲 방문객 대상으로 설문을 실시하여 531부의 데이터를 수집하였다. 데이터 분 석결과 문항신뢰도는 Cronbach's alpha값 산림치유자원 항목 0.928, 치유효과 항목 0.908로 신뢰할만한 내적일치도로 나타났다. 선정된 14종의 치유효과는 신체·생리, 심리, 사회요인으로 구성되어 내용의 타당도를 확인하였다. 본 연구는 구조방정식 모델을 검증하여 적합성을 확인하고 산림이용객이 느끼 는 산림치유자원의 효과 검증과 인식정도를 측정할 수 있는 첫 척도를 개발한 것에 의의가 있다. 본 연구 에서 개발된 척도를 사용해 데이터를 축척하고 분석한다면 산림치유자원과 치유효과 구명의 기준 자 료가 될 것이다. 또한, 실제 산림에서 측정한 자원 값과의 비교연구를 통하여 척도의 신뢰도 타당도를 더 높인 척도로 보완할 것을 제언한다.

콘크리트 포장의 조기 파손을 초래하는 콘크리트 혼합물의 품질 저하는 최근 종종 발생되고 있다. 이로 인한 유지보수 비용 또한 증 가하는 추세이다. 본 연구는 이러한 문제를 해결하고자 콘크리트 배합 시 효과적으로 유변학적 특성을 측정하여 콘크리트 품질을 예 측할 수 있는 시제품 개발을 연구 중이다. 현재 상용화되어 사용되고 있는 ICAR Plus Rheometer 장비의 이론을 변경 적용하여, 본 시제품 Twin Shaft Rheometer mixer를 개발하였다. 동시에 레오미터 장비를 활용해 유변학적 특성을 확인하고 측정하였다. 콘크리트 의 변형과 움직임을 분석하기 위해 수직, 수평 거동의 비교분석을 진행하였고, 흐름 저항성과 토크 점성을 이용하여 유변학적 특성을 기존 장비와 비교 분석하였다. 그 결과 절댓값의 차이는 존재하나 선형적 유사성을 가지는 것을 알 수 있었다. 높은 정확성을 위해 추 가연구는 진행하고 있다. 추가로 슬럼프 측정 센서 또한 개발 진행 중이며, 이 장비는 마이크로파를 통해 매질의 변화를 측정하여 슬 럼프를 유추하는 센서로 더욱 정밀한 결과값을 위해 추가연구 진행하고 있다.

This article presents the crucial role played by the French underground research laboratory (URL) in initiating the deep geological repository project Cigéo. In January 2023, Andra finalized the license application for the initial construction of Cigéo. Depending on Government’s decision, the construction of Cigéo may be authorized around 2027. Cigéo is the result of a National program, launched in 1991, aiming to safely manage high-level and intermediate level long-lived radioactive wastes. This National program is based on four principles: 1) excellent science and technical knowledge, 2) safety and security as primary goals for waste management, 3) high requirements for environment protection, 4) transparent and openpublic exchanges preceding the democratic decisions and orientations by the Parliament. The research and development (R&D) activities carried out in the URL supported the design and the safety demonstration of the Cigéo project. Moreover, running the URL has provided an opportunity to gain practical experience with regard to the security of underground operations, assessment of environmental impacts, and involvement of the public in the preparation of decisions. The practices implemented have helped gradually build confidence in the Cigéo project.

In this study, project information of government-funded research institute in the food field was collected and analyzed to systematically identify the factors affecting the process of transferring technological achievements of public research institute to the private sector. This study hypothesized that human resources, financial resources, and technological characteristics as input factors of R&D projects affect output factors, such as research papers or patents produced by R&D projects. Moreover, these outputs would serve as drivers of the technology transfer as one of the R&D outcomes. Linear Regression Analysis and Poisson Regression Analysis were conducted to empirically and sequentially investigate the relationship between input factors and output and outcome of R&D projects and the results are as follows: First, the principle investigator's career and participating researcher's size as human resource factors have an influence on both the number of SCI (science citation index) papers and patent registration. Second, the research duration and research expenses for the current year have an influence on the number of SCI papers and patent registrations, which are the main outputs of R&D projects. Third, the technology life cycle affects the number of SCI papers and patent registrations. Lastly, the higher the number of SCI papers and patent registrations, the more it affected the number of technology transfers and the amount of technology transfer contract.

This study deeply discusses the development status of e-learning in basic music education in China, and summarizes the characteristics and development of music education course content, resources, evaluation and certification in the three countries through comparative analysis with e-learning platforms in South Korea and the United States, revealing the development trends and differences of global online music teaching. In the strategic analysis part, it is pointed out that, firstly, the development of basic music online teaching needs to be combined with online and offline hybrid teaching to promote the development of music education. Secondly, while learning from the advanced experience of e-learning in other countries, we should pay attention to innovative education methods、 expand the subject content. Finally, we should pay attention to the cultivation of students' learning ability to facilitate the establishment of an efficient learning model. The innovation of this paper lies in the comprehensive and in-depth research and comparison of the characteristics and case analysis of e-learning in music education in China, and at the same time, combined with the experience of South Korea and the United States, the implementation conditions and strategies for the situation in China are proposed, which provides strong theoretical support and practical guidance for the development of e-learning in music education in China based on the practical experience of different countries, and provides specific suggestions for further optimizing the practice of online music teaching.