Fishways, particularly installed at the estuary, have a purpose to encourage fluent migration for migratory fishes, as well as amphidromous and even freshwater species. Not choosing the laborious traditional method of using traps, we assessed the efficiency of the two fishways installed at the west and east barrage of the Nakdong River estuarine barrage respectively, by analyzing the videos recorded through automatic monitoring system. We randomly selected 30 videos monthly at each fishways and identified what kind of fishes were using the fishways and categorised their behaviour such as size, time and whether they passed the monitoring system or not. As a result, a total 8 families 14 species were recorded by monitoring system, with the most dominance of Erythroculter erythropterus (Relative Abundance: 59.5%), followed by Micropterus salmoides (R.A: 19.9%) and Mugil cephalus (R.A: 9.9%). The monitoring system can capture passing fishes during night but the number of appearances of fish species at each hour of a day indicated significant diurnal activities (p<0.05). When fishes pass the monitoring system, approximately 70% of them passed through the monitoring device, while 17% of them showed fallback movement. Our finding indicates that species-specific characteristics of each fish are well represented through video monitoring method. In order to maximise advantages of using video monitoring, it is necessary to consider the installation point properly so that the monitoring system does not interfere with the movement of fish. Also, the utilisation of AI technology in the future is also necessary.

In this study, fire extinguisher system to which form fire extinguisher agents were adopted was applied to the combat vehicle crew room to apply fire extinguishing performance and acid gas safety that meet the national defense standards. As a result of evaluation and verification, the following conclusions were drawn. For standard fire sizes in the combat vehicle crew's standard model, we ignited using a mixture of Novec 1230 and Halon 1301 form extinguisher agent and released form extinguisher agent after 30 seconds to determine the fire extinguishing time. The amount of acid gas generated met the criteria in all cases. When the fire size was increased to 0.12m2 and a 2.0mm nozzle was used, all of the extinguishing time, the amount of acid gas generated, and the concentration of Novec 1230 met the criteria. Despite the more difficult conditions to extinguish the fire by making the fire larger, it was possible to confirm the extinguishing performance of the Novec 1230 form extinguisher agent and its safety against acid gas.

The importance of indoor air quality has significantly increased after the COVID-19 pandemic. This study analyzed the energy consumption of a ventilation system based on various operating methods considering indoor and outdoor conditions. From March to May 2024, experiments were conducted on ventilation systems installed in a hospital in Incheon, comparing the experimental and control groups. The results showed that using the bypass mode in the experimental group reduced total energy consumption by 25.34% compared to the control group. Additionally, utilizing the air-cleaner mode further reduced energy use. This study demonstrates that optimal use of bypass and air-cleaner modes can enhance energy efficiency. Further research is needed to verify long-term applicability under diverse conditions.

This study aims to propose new grading standards that can be applied to AI-based automatic sorting machines, reflecting current distribution and consumption trends. The current domestic grading standards for onions in South Korea are based on the “Agricultural and Fishery Products Quality Control Act”. They classify onions based on criteria such as uniformity, shape, color, and the presence of foreign matter. Onion grading standards are divided into four categories based on bulb diameter and weight. However, in the actual domestic market, onions are distributed according to a five-grade classification based on bulb diameter. Therefore, this study classified onions into eight grades, reflecting current distribution and consumption trends in the domestic market. These grades are applicable to AI-based automatic sorting machines. Marketable onions were classified into A1 (extra large) to A5 (extra small) based on the diameter of a single bulb. Onions used for non-marketable purposes (processing) were classified as grade B. Additionally, grade C and grade D were designated for processing and disposal, respectively. By establishing quality grading classifications that align with current distribution and consumption market trends as well as the operational characteristics of AI-based automatic sorting machines, we can expect improvements in work efficiency and reductions in distribution costs. Following this study, it will be necessary to establish comprehensive quality grading standards that include both external criteria (such as bulb weight and size) and internal criteria (such as detection of internal decay and disease occurrence).

To efficiently develop an automatic assembly system that can enhance the quality and assembly productivity of the shaft assembly in EV relays, a DMU model was utilized. After modeling each component of the assembly system using the CAD software CATIA, a DMU model of the assembly cells and the entire assembly system was created using the assembly model. Additionally, the DMU Kinematics Workbench was employed to verify and validate the design of the automatic assembly system for the shaft assembly, a key component of the EV relay, before actual construction. This approach helped reduce time and costs by minimizing trial and error.

포장상태 평가를 위한 노면영상 촬영은 라인스캔 방식이 주를 이루고 있다. 라인스캔 특성 상, 조사환경이나 장비특성이 달라질 경 우 밝기가 상이한 노면영상을 취득할 수 있고 이는 U-net과 같은 픽셀 단위 segmentation 딥러닝 모델의 균열 자동검출 성능에 영향을 미친다. 본 연구에서는 인공지능 검출 모델의 변경 없이 영상의 밝기 최적화와 morphology 연산기법을 노면영상 전·후처리 방법으로 제시하고 그 효과를 분석하였다. 영상 처리를 통해 과다 검출경향을 보인 이상치들이 제거되었으며 정답으로 간주할 수 있는 전문요 원 분석결과인 GT 균열률과의 상관성 또한 향상됨을 확인하였다.

The diversity of smart EV(electric vehicle)-related industries is increasing due to the growth of battery-based eco-friendly electric vehicle component material technology, and labor-intensive industries such as logistics, manufacturing, food, agriculture, and service have invested in and studied automation for a long time. Accordingly, various types of robots such as autonomous mobile robots and collaborative robots are being utilized for each process to improve industrial engineering such as optimization, productivity management, and work management. The technology that should accompany this unmanned automobile industry is unmanned automatic charging technology, and if autonomous mobile robots are manually charged, the utility of autonomous mobile robots will not be maximized. In this paper, we conducted a study on the technology of unmanned charging of autonomous mobile robots using charging terminal docking and undocking technology using an unmanned charging system composed of hardware such as a monocular camera, multi-joint robot, gripper, and server. In an experiment to evaluate the performance of the system, the average charging terminal recognition rate was 98%, and the average charging terminal recognition speed was 0.0099 seconds. In addition, an experiment was conducted to evaluate the docking and undocking success rate of the charging terminal, and the experimental results showed an average success rate of 99%.

현재 존재하는 인공지능 기반 음악 생성에 관한 여러 모델과 연구는 수동 텍스트(Text) 기반 음악 생성에 대해 다루고 있다. 본 논문은 사용자의 편의성을 높이고, 창의적인 음악 생성 과정 을 더욱 원활하게 할 수 있도록 텍스트(TEXT) 프롬프트(Prompt) 자동화를 통한 음악 생성시 스템 방안을 제안한다. 그 방안으로 음원 파일을 통해 수집한 음악 분석 및 데이터화와 가사 정보에서 추출한 키워드를 기반한 장르, 가수, 앨범 등의 정보가 포함된 데이터셋(Dataset)을 구축 후, 파이썬(Python)의 자연어 처리 방법인 Konlpy를 사용하여 가사 데이터를 토큰화하고, TF-IDF(Term Frequency-Inverse Document Frequency) 벡터화를 통해 중요한 단어를 추 출한다. 또한, MFCC, 템포 등의 특징 데이터셋을 통하여 모델을 통한 감정을 예측하고, CNN 모델 및 Chatgpt를 활용한 텍스트 프롬프트를 자동생성하는 방법을 구현하여, MusicGen 모델 을 사용한 자동화 생성 프롬프트 기반 음악을 생성한다. 본 텍스트 프롬프트 자동 생성 화를 통한 음악 생성 연구의 결과는 음악 데이터 분석 및 생성 분야에 기여될 것으로 기대한다.

In this study, we investigated the time signal devices of Deungnu (circa 1270) and Gungnu (1354), the water clocks produced during the Yuan Dynasty (1271–1368). These clocks influenced Heumgyeonggaknu (1438) of the Joseon Dynasty (1392–1910), exemplifying the automatic water clocks of the Yuan Dynasty. Deungnu, Gungnu, and Heumgyeonggaknu can be considered as automatic mechanical clocks capable of performances. The Jega-Yeoksang-Jip (Collection of Calendrical and Astronomical Theories of Various Chinese Masters) contains records of Deungnu extracted from the History of the Yuan Dynasty. We interpreted these records and analyzed reproduction models and technical data previously produced in China. The time signal device of Deungnu featured a four-story structure, with the top floor displaying the four divine constellations, the third floor showcasing models of these divinities, the second floor holding 12-h jacks and a 100-Mark ring, and the first floor with four musicians and a 100-Mark Time-Signal Puppet providing a variety of visual attractions. We developed a 3D model of Deungnu, proposing two possible mechanical devices to ensure that the Time-Signal Puppet simultaneously pointed to the 100-Mark graduations in the east, west, south, and north windows: one model reduced the rotation ratio of the 100-Mark ring to 1/4, whereas the other model maintained the rotation ratio using four separate 100-Mark rings. The power system of Deungnu was influenced by Suunuisangdae (the water-driven astronomical clock tower) of the Northern Song Dynasty (960–1127); this method was also applied to Heumgyeonggaknu in the Joseon Dynasty. In conclusion, these automatic water clocks of East Asia from the 13th to 15th centuries symbolized creativity and excellence, representing scientific devices that were the epitome of clock-making technology in their times.