This study aims to construct a corpus of 17th-century Korean personal letters, classifying them into royal and aristocratic (yangban) correspondences, and to compare their linguistic features through quantitative analysis. Based on a total of 285 letters—including ｢현풍곽씨언간｣, ｢숙명신한첩｣, ｢숙휘신한첩｣—the 17th Century Eongan Corpus was developed with detailed morphological analysis and lemmatization. The findings reveal that yangban letters tend to utilize practical and colloquial expressions, whereas royal letters demonstrate a more written style with enhanced forms of greeting and ritual politeness. Distinct differences were observed in pronoun usage, speech levels, sentence endings, and adjectives. Furthermore, phonological changes and dialectal vocabulary appeared more frequently in yangban letters, whereas royal letters maintained linguistic conservatism. This study contributes a new methodological approach to the field of historical Korean linguistics by providing a structured corpus and employing corpus-based analysis to elucidate stratified stylistic features.

Reinforcement learning (RL) is successfully applied to various engineering fields. RL is generally used for structural control cases to develop the control algorithms. On the other hand, a machine learning (ML) is adopted in various research to make automated structural design model for reinforced concrete (RC) beam members. In this case, ML models are developed to produce results that are as similar to those of training data as possible. The ML model developed in this way is difficult to produce better results than the training data. However, in reinforcement learning, an agent learns to make decisions by interacting with an environment. Therefore, the RL agent can find better design solution than the training data. In the structural design process (environment), the action of RL agent represent design variables of RC beam. Because the number of design variables of RC beam section is many, multi-agent DQN (Deep Q-Network) was used in this study to effectively find the optimal design solution. Among various versions of DQN, Double Q-Learning (DDQN) that not only improves accuracy in estimating the action-values but also improves the policy learned was used in this study. American Concrete Institute (318) was selected as the design codes for optimal structural design of RC beam and it was used to train the RL model without any hand-labeled dataset. Six agents of DDQN provides actions for beam with, beam depth, bottom rebar size, number of bottom rebar, top rebar size, and shear stirrup size, respectively. Six agents of DDQN were trained for 5,000 episodes and the performance of the multi-agent of DDQN was evaluated with 100 test design cases that is not used for training. Based on this study, it can be seen that the multi-agent RL algorithm can provide successfully structural design results of doubly reinforced beam.

Blow-up in jointed concrete pavements refers to a type of distress caused by the excessive accumulation of compressive stress within concrete slabs, primarily resulting from internal expansion and elevated environmental temperatures. This phenomenon frequently leads to slab buckling and is challenging to predict in terms of both timing and location, thereby significantly threatening the long-term structural stability of the pavement. In the present study, the pavement growth and blow-up analysis (PGBA) model was employed to quantitatively predict the timing of blow-up events in jointed concrete pavements. The model estimates the maximum compressive stress within the slab throughout the pavement’s service life using input parameters such as reliability, climatic conditions, pavement structure, material properties, and expansion joint configurations. Subsequently, the model compares the estimated stress to the threshold stress associated with blow-up to determine the likely time of occurrence. A sensitivity analysis was performed on a range of design and environmental factors, including annual maximum temperature, annual maximum precipitation, coefficient of thermal expansion, ASR, pavement thickness, geometric imperfection, and expansion joint spacing and width. The influence of each factor on the predicted blow-up occurrence time was quantitatively evaluated. The analysis demonstrated that climatic conditions, pavement structure, material properties, and expansion joint characteristics, as considered in the PGBA model, collectively govern the timing of blow-up events. These findings offer critical insights for informing the design and maintenance strategies of jointed concrete pavements.

2024년 3월부터 2024년 12월까지 충주호 상류에서 채집된 대농갱이(Leiocassis ussuriensis) 274개체의 척추골을 이용하여 연령과 성장을 분석하였다. 대농갱이의 연령은 척추골에 형성된 윤문을 통해 결정하였다. 본 연구 결과 척추골는 연령 측정에 적합한 자료로 판단되었다. 척추골에는 매년 4월에 1회 성장륜이 형성되었으며, 산란기는 5월부터 7월, 초륜은 약 10개월(0.83년)이 지난 시점에 형성되었다. 척추골을 기준으로 분석한 결과, 암컷과 수컷 간의 전장의 성장에는 유의한 차이가 없었다(p>0.05). 척추골을 기준으로 전장(TL)에 대해 추정된 von Bertalanffy 성장식은 다음과 같다:          .

본 연구는 중국 중학교 『도덕과 법치』 교과서의 인물 분석을 통해 시 진핑 시대 중국의 영웅관을 연구하는 것을 목적으로 한다. 연구 결과, 시 진핑 신시대 중국의 영웅관은 서구의 개인주의적 영웅관과는 달리 집단 주의적 성격을 강조한다. 교과서 속 인물의 85%가 중국인, 73%가 남성 으로 나타나 중국적 영웅관을 강조하며, 성별 불균형이 확인된다. 또한 직업 분포에서 전문 기술 인력이 전체의 58%를 차지하여 국가 발전을 위한 전문 인력을 중시하는 경향이 두드러진다. 이는 중국의 유교적 전 통과 마오쩌둥 시대의 ‘인민 영웅’의 개념이 시대적 요구에 맞추어 발전 하고 있음을 시사한다. 중국적 영웅관은 집단주의적 가치를 강조하는 한 편 국가 주도의 영웅 만들기라는 한계를 지닌다. 그러나 다양한 직업군 의 인물과 자신의 자리에서 최선을 다하는 소시민이 국민적 영웅으로 인 정받을 수 있다는 점은 한국 사회의 정형화된 영웅 관념을 재정립하는 데 중요한 시사점을 제공한다.

This study aims to explore the public perception of sports welfare by employing big data analysis techniques and to analyze it through a multi-layered lens grounded in Bronfenbrenner’s ecological systems theory. To this end, text mining software Textom and Ucinet 6 were utilized to examine online textual data related to “sports welfare” collected from May 2017 to February 2025. frequency analysis, TF-IDF analysis, degree centrality analysis, and CONCOR analysis were conducted. The results identified keywords such as “physical education.” “fitness.” “citizens.” “society.” “support.” “disability.” “voucher.” “university.” and “center.” as having high co-occurrence with sports welfare. CONCOR analysis revealed six major clusters: National Fitness 100 Service, Sports Voucher Program, Health Programs at Public Sports Centers, Community-Based Sports Welfare Environment, Training of Sports Welfare Professionals, and Support System Centered on the Korea Sports Promotion Foundation. This study suggests that the level of individual sports welfare can be enhanced through dynamic and interactive relationships between the individual and various environmental systems. Furthermore, to realize sustainable sports welfare, it is essential to develop long-term national strategies that holistically integrate all levels of the ecological systems from the micro system to the chrono system.

This study was attempted to solve the problem that the current training is not consistent with the actual working environment of the fishing vessel, even though the advanced fire extinguishing training for international fishing vessels is mandatory. As a result of the survey, the lack of timely use of fire extinguishing equipment and the difficulty of organizing the fire extinguishing organization were found, and the main problems were analyzed as low understanding of fixed fire extinguishing facilities, low awareness of fire-related laws and regulations, and inefficiency of fire extinguishing training. It was found that the current Seafarers Act does not clearly define the roles and responsibilities of advanced fire extinguishers, and lacks specific standards for designated educational institutions, so there is a problem that the accuracy and reliability of the training contents with the STCW-F Convention and STCW Convention are inconsistent. In addition, it has been confirmed that the fire extinguishing organization, internal communication, and fire extinguishing training in ships, as stipulated in international agreements, are not properly reflected in the domestic curriculum. In particular, the current training consists of general contents that do not take into account the characteristics of fishing vessels, so there is a lack of practical emergency response fire extinguishing training manuals. Therefore, this study proposes the development of customized training content for fishing vessels considering the special working environment and risk factors of fishing vessels based on international agreements, and emphasizes the need for policy support, such as strengthening participation of fishing vessels in education and training, and establishing a legal basis for the operation of emergency fire extinguishing organizations.

This study aimed to enhance the operational efficiency and safety of offshore eel trap fisheries by developing six types of automated fishing equipment: a bait crusher, bait cutter, main line arranging device, trap cleaning device, eel sorting device, and fish pump system. Sea trials demonstrated that the bait crusher and bait cutter significantly reduced manual labor and processing time while maintaining bait quality. The main line arranging device improved productivity and safety by automating the sorting of looped cords. The trap cleaning device effectively removed fouling organisms using high-pressure water and rotating brushes. The eel sorting device enabled automatic size-based selection, improving resource management and operational efficiency. The fish pump system transferred eels rapidly with minimal physical damage, reducing unloading time by over 80% and decreasing labor requirements. A satisfaction survey of fishery participants confirmed that all developed devices were highly effective in reducing workload, enhancing safety, and improving operational performance. The automated equipment developed in this study is expected to contribute to the sustainable management of offshore eel trap fisheries and to offer potential applicability to other coastal and offshore fisheries.

This study examined the offshore eel trap fishing process using one year of fishing logs and fishermen’s insights to identify key operational challenges and propose equipment improvement for greater efficiency and safety. Conger eel catches varied significantly by season, depth, and temperature, peaking in winter at 85–90 m and 23°C. The western waters of Jeju Island were identified as a major fishing ground, with the highest catch recorded in November and the lowest in July, reflecting seasonal trends. Each fishing operation deployed about 10,000 traps, with an average loss of 38 traps, posing economic concerns. The process involved intensive manual labor in bait preparation, trap retrieval, catch separation, line loading, and unloading, leading to high physical demands and safety risks. To address these issues, the study proposed automation through the development of a line loading device, trap cleaning device, bait processing machine, and automatic catch separator. These innovations could reduce the labor force required by one to two workers per process, alleviate workloads, and enhance resource management. By integrating quantitative logbook analysis with field-based knowledge, this study offers practical value. Further research is recommended on automation development, cost-effectiveness, and field validation to support safer and more sustainable eel trap fisheries.