Ensuring operational safety and reliability in Unmanned Aerial Vehicles (UAVs) necessitates advanced onboard fault detection. This paper presents a novel, mobility-aware multi-sensor health monitoring framework, uniquely fusing visual (camera) and vibration (IMU) data for enhanced near real-time inference of rotor and structural faults. Our approach is tailored for resource-constrained flight controllers (e.g., Pixhawk) without auxiliary hardware, utilizing standard flight logs. Validated on a 40 kg-class UAV with induced rotor damage (10% blade loss) over 100+ minutes of flight, the system demonstrated strong performance: a Multi-Layer Perceptron (MLP) achieved an RMSE of 0.1414 and R² of 0.92 for rotor imbalance, while a Convolutional Neural Network (CNN) detected visual anomalies. Significantly, incorporating UAV mobility context reduced false positives by over 30%. This work demonstrates a practical pathway to deploying sophisticated, lightweight diagnostic models on standard UAV hardware, supporting real-time onboard fault inference and paving the way for more autonomous and resilient health-aware aerial systems.

본 연구에서는 안전한 수질의 밭 관개용수를 확보하기 위한 다기능 저류조 용수공급시스템을 현장에 적용하여, 효과를 검증하여 현장 적용성을 분석하였다. 용수의 수질 특성을 고려하여 적정 모듈 프로세스로 AOP (Advanced Oxidation Process), SF (Soil Filter)를 적용하였으며, 저류조의 효과 검증은 앞서 다기능 저류조 수처리 저감효율, 미생물 위해성 평가 등을 통해 수행하였다. 시범시설의 조사는 유입수(지표수, 지하수) 2개, 유출수 1개 지점을 2022년 5월부터 9월까지 월 1회(총 5회), 수온, TOC, COD 등 13개 수질항목을 측정하였다. 유출수에서 전항목 수질기준을 만족하였다. 다기능 저류조의 저감효율은 지표수에서 TOC 평균 19.2%, SS 평균 43.8%, T-N 평균 28.1%, T-P 평균 46.9%, Chl-a 평균 70.1%, 지하수에서 수온 평균 7.5% 상승, EC 평균 54.3%의 저감효율을 보여, 다기능 저류조의 수질정화 개선효과를 검증하였다. 미생물 위해성 평가 결과, 평균 위해도 값은 유입수(지하수) –3.02 × 10-6, 유입수(지표수) 2.79 × 10-5로 나타났으며, 다기능 저류저 처리 후 E.coli가 전량 사멸함에 따라 영농작업자의 위해성은 없을 것으로 나타났다.

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.

This study develops a comprehensive road operation evaluation model that integrates the perspectives of three principal stakeholders: road users prioritizing congestion mitigation, operators emphasizing investment efficiency, and policymakers advocating broader societal goals such as carbon reduction. The analysis database was constructed using traffic data obtained from reliable sources, including the Korea Transport Institute's Big Data Center and Suwon City's Urban Safety Integration Center. Binary logistic regression was employed to identify the factors influencing traffic congestion from the users’ perspective, whereas multiple linear regression models were used to analyze road investment efficiency from the operators’ viewpoint and carbon dioxide emissions from the policymakers’ standpoint. Statistical analyses were conducted on 4,322 road segments in Suwon City, with each evaluation criterion assigned an equal weight of 33.3 points in a unified 100-point scoring system. The analysis identified 15 statistically significant indicators affecting the three evaluation criteria, with the resulting models demonstrating strong explanatory power, evidenced by adjusted R² values of 0.197, 0.593, and 0.544 for traffic congestion, road investment efficiency, and carbon dioxide emission models, respectively. A volume-to-capacity (V/C) ratio of 0.64 was determined to represent the optimal balance point at which the requirements of all stakeholder groups align. When applied to Suwon City's arterial road network, the model identified 248 high-congestion segments (53.13 km), 203 segments with low investment efficiency (26.8 km), and 357 segments with high carbon emissions (156.33 km), each requiring targeted operational improvements. The proposed model addresses the limitations of existing single-stakeholder evaluation frameworks by offering transportation authorities a systematic and multi-dimensional approach to road operation assessment.

Purpose: This study aimed to develop and implement a multi-patient simulation (MPS) program for nursing students with no prior clinical practice experience. It also examined the effects of the program on the students’ communication competence and clinical reasoning ability. Methods: A one-group pretest-posttest design was used. The MPS program, consisting of four patient scenarios was applied to second-year nursing students with no prior clinical practice experience. Communication competence, clinical reasoning ability, and the perceived effectiveness of the multi-patient simulation program were measured using structured tools before and after the program. Results: Communication competence significantly improved after the MPS program, whereas clinical reasoning did not show a statistically significant difference. Perceived effectiveness of the MPS program was generally high, with the debriefing component scoring the highest. Confidence scores were relatively low, suggesting the need for level-appropriate scenario. Conclusion: The MPS program was effectively enhanced communication competence among preclinical nursing students. Although clinical reasoning scores did not improve significantly, the study highlights the importance of introducing realistic simulation experiences early in nursing education. Future research should focus on developing suitable clinical reasoning assessment tools for early year students and conducting randomized controlled trials to validate the effectiveness of customized MPS programs.

본 연구는 2016년 SM엔터테인먼트가 론칭한 다국적 보이그룹 NCT(Neo Culture Technology)의 유닛 시스템이 가진 차별화된 특성이 K-Pop 산 업에 미친 영향과 확산 과정을 분석하였다. 연구 방법은 질적 내용분석을 선택하였고, 로저스의 혁신 확산 이론의 네 가지 핵심 요소(혁신, 커뮤니케 이션 채널, 시간, 사회 시스템)를 분석 프레임워크로 활용하였다. 분석 결 과, NCT 유닛 시스템은 콘텐츠 다양화, 시장 확장성, 리스크 분산, 아티스 트 개발 측면에서 상대적 이점을 가진 혁신으로, SM의 전략적 커뮤니케이 션과 팬 커뮤니티의 정보 공유가 확산에 중요한 역할을 했음을 발견하였 다. 시간적 측면에서는 2016년부터 현재까지 초기 도입기, 확산 성장기, 급속 확산기, 안정화 단계로 이어지는 S자형 확산 곡선이 관찰되었다. 또 한 NCT 유닛 시스템은 K-Pop 산업의 기존 규범에 도전하며 아이돌 그룹 의 정체성 형성, 경력 관리, 글로벌 확장 전략, 인재 개발 방식에 변화를 가져왔다. 본 연구는 NCT 유닛 시스템이 K-Pop 그룹의 지속 가능한 성장 모델, 글로벌 시장 접근 전략, 유연한 인재 관리, 다층적 팬덤 참여, 미디 어 기술 적응, 비즈니스 모델 다각화 측면에서 K-Pop 산업의 미래 발전 방향에 중요한 시사점을 제공함을 확인하였다.

현재 韓 육군은 다영역작전(Multi-Domain Operations) 개념을 발전 시키기 위해 다방면으로 연구를 진행 중이지만 전투수행기능 중 일부 분 야에만 편중된 연구가 진행 중이다. 또한 기존 다영역작전에 대한 선행 연구 자료들 역시 정치적·전략적 수준 측면의 기동과 화력 분야에만 집 중되어 있다. 따라서 본 연구의 목적은 韓 육군이 다영역작전 개념을 육 군 교리에 적용하기 위한 연구를 진행함에 있어서 전투수행기능 중 지속 지원의 일부인 군수지원 개념을 어떻게 발전시킬 것인지에 대한 방향성 을 제시하기 위함이다. 이를 위해 美 육군의 다영역작전 개념 및 다영역 작전을 위한 군수지원의 핵심 사항에 대하여 美 교리를 통한 문헌연구를 실시하였고, 군사이론의 사례를 통해 다영역작전과 군수지원에 대한 시 사점을 도출하였다. 또, 韓 육군의 군수지원 체계의 문제점이 다영역작전 에 미치는 영향을 분석 후, 이를 종합하여 발전 방향을 제시하였다. 이 연구는 육군이 다영역작전을 교리에 적용하기 위해 전투수행기능이 통합 된 연구를 진행 시 다영역작전을 위한 군수지원 개념의 기초자료로 활용 될 수 있음을 시사한다.

This study investigated dietary behaviors, nutrient intake, and quality of life among elderly individuals living alone compared to those in multi-person households. Data were obtained from 5,311 individuals aged 65 years and older who participated in the 2015-2019 Korea National Health and Nutrition Examination Survey (KNHANES). Nutritional intake was assessed by analyzing the proportion of individuals with insufficient intake relative to the Korean Dietary Reference Intakes (KDRIs) and the Acceptable Macronutrient Distribution Range (AMDR). Quality of life was measured using the EQ- 5D instrument. The results showed that single-person households were more likely to be female, older, and have lower income and education levels compared to multi-person households. Additionally, single-person households were more likely to skip breakfast, eat at places other than home, eat alone, and dine out less frequently. Nutritional intake was lower among elderly individuals living alone. Furthermore, after adjusting for relevant variables, single-person households were significantly more likely to report poor quality of life (OR: 1.05, 95% CI: 1.07-1.28)—defined as being in the lowest 20% of EQ-5D scores—compared to those in multi-person households. The findings highlight the need for targeted nutritional support and policy interventions to improve dietary intake and quality of life among elderly single-person households.

This study empirically analyzes the factors influencing the commuting time of households with multiple commuters in Chungnam Province. In particular, we examined how the commuting time varies between commuters depending on their wage gaps. A regression equation, in which the dependent variable was the difference in commuting time, was used. The key independent variable was the wage gap for households with two commuters. Further estimations were performed on samples restricted to dual-income couples with additional variables such as the wife’s household work burden, number of preschool children, and number of caregivers for children. Based on the results of the empirical analyses using the Chungnam Social Survey, the larger the wage gap between two commuters in a household, the longer the commuting time for high-wage commuters than for low-wage commuters. This contradicts the argument that a higher opportunity cost of commuting for higher wages should reduce the commuting time. In the analysis of dual-income couples, the wife’s commuting time was relatively shorter than that of the husband’s because of the burden of housework; however, the influence of childcare was not observed. As households with multiple commuters or dual-income couples become increasingly common, and the structure of cities changes from monocentric to multicentric, deciding where to live has become more complicated. Long-time and long-distance commuting can lead to wasteful commuting, and this needs to be considered as a social cost owing to the possibility of traffic congestion beyond the loss for the individual concerned. Therefore, the government’s urban policies, including housing and transportation policies, must be improved.

초임계 이산화탄소 조건에서 다중벽 탄소 나노튜브(MWCNT)에 공유결합으로 조합된 폴리(2-에티닐피리디 늄 염) 복합체를 제조하였다. 초기 반응 단계에서 MWCNT 표면에서 형성된 4차염화 2-에티닐피리디늄 염의 활성 화된 아세틸렌 삼중 결합이 MWCNT 표면에서 연속적으로 중합되어 폴리(2-에티닐피리디늄 염)이 공유결합으로 조 합된 MWCNT가 용이하게 제조되었다. MWCNT/폴리(2-에티닐피리디늄 염)의 전기 광학 및 전기화학적 특성을 측 정하고 분석하였다. 해당 복합체의 광발광 피크는 2.04 eV의 광자 에너지에 해당하는 610 nm에서 관찰되었다. SnO2:F/TiO2/N719 염료/고체 전해질/Pt 장치가 있는 준고체 DSSC를 MWCNT/P2EP로 제조하였는데, 이의 최대 에 너지 변환효율은 5.33%였다.