This study was conducted to evaluate the effects of intercropping hairy vetch (HV) with Italian ryegrass (IRG), oat, and rye on forage productivity and nutritive value under a rice-forage double-cropping system. A field experiment was carried out in a paddy field using six treatments (IRG, IRG+HV, oat, oat+HV, rye, and rye+HV) arranged in a randomized complete block design with three biological replications. The results showed that dry matter (DM) yield and total digestible nutrients (TDN) yield were significantly higher in rye monoculture than in the rye+HV mixture, whereas no significant differences were observed between monoculture and intercropping in IRG or oat. In contrast, crude protein (CP) yield increased significantly under intercropping in IRG and oat, confirming the nitrogen contribution and protein-enhancing effects of the legume component. For forage quality, intercropping consistently reduced neutral detergent fiber (NDF) and acid detergent fiber (ADF) concentrations and improved DM intake (DMI), digestible DM (DDM), TDN, and relative feed value (RFV) in all three species. These findings indicate that the productivity-enhancing effect of intercropping is limited under paddy field conditions, while the improvement of forage quality is substantial and consistent. Therefore, intercropping with hairy vetch can serve as an effective strategy in systems where the primary objective is to enhance CP content and overall forage quality.

This study investigated cultivar variation in biomass partitioning patterns and nutrient harvest index across eight Brassica napus cultivars (Akela, Capitol, Colosse, Naehan, Pollen, Saturnin, Sparta, and Tamra). Seed dry weight varied ranging from 5.8 ± 0.3 g DW to 35.7 ± 6.7 g DW, with Colosse showing the highest seed production and Tamra showing the lowest. Harvest index (HI) was divided two groups showing high group (Capitol, Colosse, Pollen, Tamra) and low group (Akela, Naehan, Saturnin, Sparta), which were ranged from 10.8% to 31.7%. Sulfur harvest index (SHI) ranged from 25.6% to 46.5%, with Capitol and Pollen exhibiting the highest efficiency and with Akela and Naehan exhibiting the lowest efficiency. Nitrogen harvest index (NHI) showed greater variation, ranging from 39.8% to 74.3%, with Capitol and Pollen recording the highest value but Akela and Naehan recording the lowest values. Together, these results demonstrate that seed yield, HI, and nutrient harvest index can be partially decoupled among cultivars, highlighting SHI and NHI as complementary traits for selecting nutrient-efficient rapeseed germplasm. Consequently, Colosse and Pollen emerge as promising cultivars for seed oil production, whereas Akela, Sparta, and Naehan are better suited for feed use.

최근 건축 구조공학 분야에서도 대규모 언어 모델(LLM)을 활용한 인공지능(AI) 기술 도입이 증가하고 있지만, 한국형 구조설계 기준과 같은 지역 특화 규정을 반영하지 못하거나 잘못된 정보를 제공하는 환각 현상 등 여러 한계를 보인다. 이를 극복할 수 있는 유 망한 기술로서 검색-증강 생성(RAG)이 제시되고 있으며, 본 논문에서는 한국 건축 구조공학 도메인에 특화된 RAG 시스템인 StructCPT를 개발하여 그 성능을 평가하였다. StructCPT는 한국어 기반 구조공학 지식베이스에서 질의에 적합한 정보를 실시간으로 추출하는 도메인 특화 검색기이며, 대조학습 기반의 MAXIM(Maximum Similarity Retrieval) 임베딩 기법을 이용하여 질의와 문서 간 최대 의미적 유사도를 학습한다. 실험 결과 StructCPT는 BM25, Contriever, SPECTER와 같은 기존 범용 검색 기법들 대비 정량적 평 가 지표에서 일관되고 유의미한 성능 향상을 보여주었다. 특히 구조공학 전문 용어 처리와 복합적 질의에 대한 검색 정확도 및 재현율 에서 월등히 높은 성과를 나타냈으며, 실제 구조공학 문제 적용에서도 높은 정확도를 달성하였다. 또한 검색 속도와 메모리 사용 측면 에서도 실무 적용에 적합한 효율성을 입증하였다. 본 연구는 구조공학 분야에 특화된 최초의 RAG 시스템 개발 사례로서, 향후 도면･ 이미지 등 멀티모달 정보와 지식그래프 통합을 통한 추가 발전 방향을 제시하며, 안전하고 신뢰할 수 있는 AI 기반 구조공학 의사결 정 지원의 기초를 마련하였다.

본 연구는 한국 건축･구조공학 도메인에 특화된 SAFE(Safetyoriented AI Framework for Engineering) 지식베이스와 이를 활용한 검 색 증강 생성(RAG) 시스템을 제안한다. SAFE는 전문용어집, 설계 기준, 교과서, 프로젝트 보고서에서 추출한 37.7만개 스니펫을 통 합하여 국내 구조설계기준(KDS)과 최신 실무 사례를 포괄한다. SAFE 기반 파이프라인은 5개 대표 과업(MMLUStruct, Struct QAKO, SPED, StructMCQA, StructCaseY/N)으로 구성된 4,200문항 벤치마크에서 전체 정확도 89.1%를 기록하여, 체인오브생각(CoT) 방식 의 최고 성능 LLM 대비 3.87%p 향상 효과를 나타냈다 . 특히 국내 기준･실무 판정 과업인 StructCaseY/N에서 94.9%의 정확도를 달성 하였다 . 절편 분석 결과, 질의당 32개 스니펫을 투입할 때 정확도와 응답 지연 간 최적 균형점이 형성되며, 그 이상에서는 성능 개선 대 비 비용이 급격히 감소함을 확인하였다. 또한 질문 유형별로 최적 정보 출처가 상이함을 규명하여, 도메인 맞춤형 코퍼스 가중치 조정 의 필요성을 제시하였다. 본 연구는 국내 최초의 구조공학 RAG 평가 체계를 확립함으로써, 안전 중심 AI 의사결정 지원 도구의 실무 적용 가능성을 입증하고 향후 연구의 기반을 마련하였다.

The utilization of pig slurry (PS) as an organic fertilizer plays a pivotal role in nutrient recycling within agricultural systems. However, this practice concomitantly leads nitrogen (N) losses through ammonia (NH₃) volatilization and nitrous oxide (N₂O) emissions. The objective of this study was to investigate the effect of wood biochar on mitigating NH3 and N2O emissions and enhancing N retention from PS-applied soil, and plant biomass production during the vegetative growth of rapeseed (Brassica napus L.). The experiment consisted of three treatments: 1) water (non-PS), 2) PS, and 3) PS combined with wood biochar (PS+WB). The PS+WB treatment resulted in the maintenance of elevated soil water content during the experimental period. The PS+WB treatment significantly enhanced soil nitrogen retention compared to PS alone, maintaining higher total N and NH₄⁺-N levels while reducing NO₃⁻ -N accumulation. Wood biochar application also leds to substantial reductions in NH₃ and N₂O emissions, mitigating environmental N losses. The PS+WB treatment resulted in an improvement of shoot biomass, crude protein content, and total digestible nutrients, indicating enhanced forage quality. The increased soil moisture content in PS+WB further contributed to plant growth benefits. These findings demonstrate that wood biochar is an effective amendment for improving nitrogen retention, reducing gaseous N emissions, and enhancing crop productivity in PS-amended soils.

This study aimed to evaluate the effectiveness of a zeolite and sulfuric acid mixture (ZS) as an air filter to mitigate the emissions of ammonia (NH3), nitrous oxide (N2O), and methane (CH4) during the composting of cattle manure. Compared to the control group (blank), ZS reduced NH3 emissions by 91.4%, N2O emissions by 33.6%, and CH4 emissions by 20.0% over the 100-day composting period. Additionally, sulfuric acid in the ZS reacted with NH3, storing it as ammonium sulfate [(NH4)2SO4], which can serve as a source of nutrients such as nitrogen (N) and sulfur (S). To evaluate the fertilizing efficiency of [(NH4)2SO4] in ZS for maize growth, we applied four treatments: control (non-N fertilizer), collected ZS (cZS), cattle manure (organic fertilizer, OF), and urea (chemical fertilizer, CF). Compared to the control, cZS increased total dry weight (DW) by 48%, total digestible nutrients (TDN) by 7.3%, and crude protein (CP) by 77.8%. No significant differences were found among the applications of cZS, OF, and CF. These results suggest that the zeolite mixed with sulfuric acid effectively reduces hazardous gas emissions such as NH3, CH4, and N2O during cattle manure composting. Furthermore, the collected zeolite can potentially be reused as fertilizer, suggesting a positive opportunity for resource recycling to mitigate environmental pollution.

This study aimed to evaluate the efficiency of combining acidification with adsorbents (zeolite and biochar) to mitigate the environmental impacts of pig slurry, focusing on ammonia (NH3) emission and nitrate (NO3 -) leaching. The four treatments were applied: 1) pig slurry (PS) alone as a control, 2) acidified PS (AP), 3) acidified pig slurry with zeolite (APZ), and 4) acidified pig slurry with biochar (APB). The AP mitigates NH3 emission and NO3 - leaching compared to PS alone. Acidification reduced the cumulative NH3 emission and its emission factor by 35.9% and 12.5%, respectively. The APZ and APB increased NH4 +-N concentration, with the highest level in APB, compared to AP. The NH4 + adsorption capacity of APB (0.90 mg g-1) was higher than that of APZ (0.63 mg g-1). The APB and APZ treatments induced less NH3 emission compared to AP. The cumulative NH3 emission was reduced by 12.2% and 27.6% in APZ and APB, respectively, compared to AP treatment. NO3 - leaching began to appear on days 12 and 13, and its peak reached on days 16 and 17, which were later than AP. The cumulative NO3 - leaching decreased by 17.7% and 25.0% in APZ and APB, respectively, compared to AP treatment. These results suggest that combining biochar or zeolite with acidified pig slurry is an effective method to mitigate NH3 emission and NO3 - leaching, with biochar being particularly effective.

󰡔유몽천자(牖蒙千字)󰡕는 한국개신교선교사 게일(James Scarth Gale(한국명 : 奇一), 1863-1937)과 그의 조사(pundit) 이창직(李昌稙, 1866-1936)이 함께 편찬한 경신 학교와 정신여학교의 교과서이다. 이 책은 총 4권으로 구성된 교재다. 여기에 실린 내용 은 자연과학, 사회과학, 서양의 역사, 서양의 인물, 서양의 문학, 우리의 한문고전에 관한 것 등으로 이루어져 있다. 더불어 개화기에 우리의 어문 생활에 필요하다고 생각한 한자 와 관련 정보, 한자어, 국한문, 한문에 관한 지식을 정식 학교 교육을 받는 학생들에게 알 려 주기 위하여 편찬한 것이다. 본고에서는 이러한 󰡔유몽천자󰡕 전집의 체계와 구성, 전 집을 구성하는 3가지 문체 유형, 그리고 전집에 새겨져 있는 개신교선교사의 문체실험의 역사를 고찰했다.

The metal bush assembling process is a process of inserting and compressing a metal bush that serves to reduce the occurrence of noise and stable compression in the rotating section. In the metal bush assembly process, the head diameter defect and placement defect of the metal bush occur due to metal bush omission, non-pressing, and poor press-fitting. Among these causes of defects, it is intended to prevent defects due to omission of the metal bush by using signals from sensors attached to the facility. In particular, a metal bush omission is predicted through various data mining techniques using left load cell value, right load cell value, current, and voltage as independent variables. In the case of metal bush omission defect, it is difficult to get defect data, resulting in data imbalance. Data imbalance refers to a case where there is a large difference in the number of data belonging to each class, which can be a problem when performing classification prediction. In order to solve the problem caused by data imbalance, oversampling and composite sampling techniques were applied in this study. In addition, simulated annealing was applied for optimization of parameters related to sampling and hyper-parameters of data mining techniques used for bush omission prediction. In this study, the metal bush omission was predicted using the actual data of M manufacturing company, and the classification performance was examined. All applied techniques showed excellent results, and in particular, the proposed methods, the method of mixing Random Forest and SA, and the method of mixing MLP and SA, showed better results.

Ambient Air Vaporizer (AAV) is an essential facility in the process of generating natural gas that uses air in the atmosphere as a medium for heat exchange to vaporize liquid natural gas into gas-state gas. AAV is more economical and eco-friendly in that it uses less energy compared to the previously used Submerged vaporizer (SMV) and Open-rack vaporizer (ORV). However, AAV is not often applied to actual processes because it is heavily affected by external environments such as atmospheric temperature and humidity. With insufficient operational experience and facility operations that rely on the intuition of the operator, the actual operation of AAV is very inefficient. To address these challenges, this paper proposes an artificial intelligence-based model that can intelligent AAV operations based on operational big data. The proposed artificial intelligence model is used deep neural networks, and the superiority of the artificial intelligence model is verified through multiple regression analysis and comparison. In this paper, the proposed model simulates based on data collected from real-world processes and compared to existing data, showing a 48.8% decrease in power usage compared to previous data. The techniques proposed in this paper can be used to improve the energy efficiency of the current natural gas generation process, and can be applied to other processes in the future.

본 보고는 2020년 산림 지역에서 대발생하여 큰 피해를 준 매미나방과 대벌레에 의한 피해면적과 피해수종에 대해 기술하였다. 매미나방에 의한 식엽 피해는 강원(1,638 ha), 경기(1,134 ha), 충북(726 ha), 서울(476 ha) 등 중부지방을 중심으로 심각하였다. 대벌레는 서울시 은평구와 고양시 덕양구 사이에 위치한 봉산(약 19 ha)에서 대발생하였다.

2017년 발생한 포항 지진으로 인하여 천장재, 외장재, 커튼월 등 비구조재의 파괴에 의한 피해가 다수 보고되었으며 비구조재의 내진설계가 중요해지고 있다. 본 연구에서는 임팩트해머 테스트를 통해 행어볼트 길이에 따른 천장재의 고유진동수와 감쇠비를 식별하였다. 또한 천장재가 벽 또는 다른 구조체에 충돌하는 경우 발생하는 충격효과를 정확히 고려하기 위해 충돌실험을 수행하였다. 식별된 천장재의 동특성과 충격지속시간을 바탕으로 실제로 천장재가 지진하중으로 인하여 주변 구조물과 충돌이 발생하는 경우에 대한 천장재 응답특성을 수치해석을 통하여 분석하였다. 수치해석 시뮬레이션 결과, 충격하중은 이격거리에 따라 선형적으로 증가하는 경향을 보였으며, 달대길이와는 무관한 것으로 나타났다.