This study examines the seismic vulnerability of non-structural components in high-rise buildings by proposing a normalized floor response spectrum (FRS) suitable for practical application. A Bayesian-mode-based method (BMBM) is used to develop the FRS, incorporating both modal amplification effects and the probabilistic variability observed across different building heights and story levels. The resulting spectrum is methodically compared with existing code-based and empirical methods to assess its consistency, conservatism, and relevance to engineering practices. The findings demonstrate that the proposed FRS provides a realistic yet reliable upper-bound estimate of floor accelerations, particularly in the upper stories where modal interactions are significant. This research offers a robust and practical framework for enhancing the seismic design of nonstructural components in vertical structures.

For estimating ground motion intensity measures on the surface from seismic sensors installed in structures, it is crucial to correct structural response effects embedded in the recorded signals. This study proposes a model for peak ground acceleration (PGA) amplification based on VS30, derived from multi-degree-of-freedom analysis. PGA amplification factor (AFPGA) is defined as the ratio of peak floor acceleration (PFA) of structures to PGA. The model includes three key input parameters: the natural period of the structures (Tn), the ratio of stories to the total number of stories in the structures, and the time-averaged shear wave velocity down to a depth of 30 meters. It is developed using 78 ground motion records from both domestic and international earthquakes. A LOESS smoothing technique is applied using 3 span values, with the optimal span of 0.1 is determined based on RMSE performance and an analysis of local trend characteristics in the dataset. The model is verified using empirical data from the CESMD global strong motion database, which includes classification by Tn into short, intermediate, and long periods. The results show that although the model tends to predict higher AFPGA values than those observed in real structures, it effectively reflects the overall amplification trends. This approach enables the pre-earthquake estimation of structural amplification, allowing for the use of seismic sensors installed in structures as a complementary monitoring network for seismic response.

본 연구는 교회학교 교사들의 지속가능발전교육에 대한 인식과 실천 현황 을 조사하고, 이를 교회교육에 효과적으로 적용할 수 있는 방안을 탐구하였 다. 전국의 교회학교 교사 211명을 대상으로 2024년 9월부터 10월까지 약 4주간 온라인 설문조사를 실시하였으며, SPSS를 이용하여 데이터를 분석하 였다. 연구 결과, 교사들은 지속가능발전교육의 개념(평균 3.20)과 이해(평균 3.21)에 대한 기본적인 인식을 가지고 있었으나, 실천 의지(평균 3.12)는 상 대적으로 낮게 나타났다. 주요 장애 요인으로는 지속가능발전교육에 대한 이 해 및 전문성 부족(57.3%)과 담임목사 및 교역자들의 인식 및 지원 부족 (37.4%)이 지적되었으며, 실천하고 싶은 주제로는 기후 변화와 환경 문제 (40.3%)가 가장 높은 빈도를 차지하였다. 본 연구는 이러한 결과를 바탕으로 교사 연수 프로그램 개발, 신앙적 가치를 반영한 실천적 교육 활동, 교회 지 도자 및 공동체의 적극적인 지원 강화, 실행 평가와 피드백 체계 구축 등의 구체적인 방안을 제언하였다.

언뜻 생각하기에 비슷해 보이는 선교 활동과 개발NGO 활동은 깊이 들여다보지 않으면 알 수 없는 차이가 존재한다. 그래서 현장에서 활동하는 기독교인들은 여러 가지 갈등과 어려움을 겪기도 한다. 이에 본 연구는 해외 현장에서 선교 활동과 개발NGO 활동을 겪은 기독교인 개발NGO 활동가들의 경험을 탐색하여 선교 활동과 개발NGO 활동의 차이가 무엇인지를 발견하고, 갈등과 어려움 해결에 필요한 대안을 과제로 제시하고자 하였다. 연구 결과, 선교 활동과 개발NGO 활동의 차이에 대한 경험의 본질은 [비중이 큰 비기독교인], [현지 선교사 나름의 기독교 신앙기반 국제개발단체(CFBDO) 이해와 태도], [우선순위가 다른 활동가와 선교사], [선교사 지부장과 협업하기 어려운 부분]으로 드러났다. 그래서 갈등과 어려움 해결을 위한 대안적 과제로 다음 두 가지를 제시하였다. 첫째, 협업하는 교회의 리더나 선교사에게 ‘개발NGO 활동은 책무성이 필요한 전문적인 국제개발 활동’이라는 인식 개선이 필요하다. 둘째, 개발NGO에서 일하는 기독교인 활동가에게 20세기에 재정립된 선교신학적 개념인 ‘통전적 선교와 총체적 선교’에 대한 교육이 필요하다.

Current portable reference equipment used to evaluate the performance of vehicle detectors can collect traffic volume and speed only for the outermost lanes in each direction. Passing vehicles on the other lanes are manually counted by reviewing the recorded videos. Consequently, only traffic volume—without vehicle speed—is used as a reference value. This method is time-consuming for comparing the performance data from the equipment with the reference data and can compromise the performance evaluation. This study aims to enhance the efficiency of vehicle detection system (VDS) performance evaluations by developing multilane portable reference equipment that can accurately collect traffic information for lanes beyond the outermost lane or for more than two lanes. This study introduced the core technologies of multilane portable reference equipment and compared and analyzed the measurement accuracy of the developed equipment against data from fixed reference equipment operated by the Intelligent Transportation System (ITS) Certification and Performance Evaluation Center, following ITS performance evaluation criteria. The data from the fixed reference equipment were considered the true values, providing a basis for evaluating the accuracy of the measurements by the developed equipment. First, the accuracy of the vehicle length was determined by driving four test vehicles, each measuring 7,085 mm in length, 24–29 times in each lane. The accuracy was calculated by comparing the vehicle length data obtained from the fixed reference equipment with the actual vehicle length. A confidence interval was established for this accuracy. To assess the accuracy of the speed and occupancy time in relation to the accuracy of the analyzed vehicle length, we evaluated the error range of the vehicle length according to variations in speed and occupancy time. This analysis was based on the following relationship equation: “vehicle length = speed × occupied time – sensor spacing.” The analysis used data from approximately 16,000 vehicles, including the speed, occupancy time, and vehicle length, collected between 8:00 am and 12:00 pm on August 8, 2024. The principle behind measuring traffic volume and vehicle speed using multilane portable reference equipment involves detecting a vehicle by analyzing the time difference between the driver and passenger tires. The vehicle speed was calculated using the installation angle of the tire detection sensor and trigonometric functions. An analysis of the measurement accuracy revealed that the traffic volume accuracy of the outermost lane (the fourth lane) was 100% during both day and night. The speed accuracy was 98.8% during the day and 97.7% at night, representing the highest performance in these metrics. Additionally, the traffic volume accuracy for the innermost lane (the first lane), as measured by the detection sensor from the third lane, was more than 99.3% at all times, with a speed accuracy exceeding 96% during the day and night, that also demonstrated excellent results. The analysis results indicated that the multilane portable reference equipment developed in this study was suitable for evaluating the VDS performance. This equipment allowed the collection of traffic volume and speed data from all lanes, rather than only the outermost lanes. This capability enabled consistent analysis for each lane and enhanced efficiency by reducing the analysis time. Additionally, this is expected to improve the reliability of the performance evaluations.

본 연구는 국가 제조업 경쟁력 강화를 위한 핵심 R&D 사업인 소재부품 기술개발사업을 중심으로 산학연 공동연구 네트워크의 구조적 특성을 분석하고, 각 참여 주체들의 역할과 관계를 규명하여 시사점을 제시하는 것을 목적으로 한다. 이를 위해 최근 5년간 (2020년~2024년) 수행된 소재부품기술개발사업의 공동연구 과제 565건을 대상으로 소셜 네트 워크 분석(Social Network Analysis, SNA)을 수행하였다. 분석 결과, 소재부품기술개발사업의 공동연구 네트워크는 1,262개 기관과 2,048개 협력관계로 구성된 중심-주변부 구조를 가지고 있으며, 산학연 협력(49.4%)이 가장 많은 비중을 차지하였다. 전체 네트워크에서 일부 연구 기관이 지식 공급과 확산을, 기업은 주로 지식의 흡수와 통합 역할을 수행하는 구조를 보였다. 대학은 산업계와 연구계 사이에서 지식의 흐름을 중개하는 핵심 역할을 담당하고 있는 것으로 나타났다. 협력 유형별 분석 결과, 지식의 생산, 통합, 중개 역할을 담당하는 주체가 뚜렷하게 구분되었다. 산학연 협력과 산연 협력에서는 공공 연구기관이 지식 생산 및 확산의 중심 주체로 기능하는 반면, 산학 협력에서는 대학과 대기업이 네트워크의 핵심 허브로 작용하고 있다. 산산 협력에서는 소수의 대기업 중심의 위계적 구조가 두드러졌다. 중개 역할 또한 협력 유형에 따라 상이하게 나타나, 산학연과 산학 협력에서는 대학이, 산연 협력에서는 전문 연구 기관이, 산산 협력에서는 대기업이 지식 가교로서 기능을 수행하고 있음을 확인하였다. 기술 분야별 분석 결과, 전기·전자(33.6%), 기계·소재(27.1%), 화학(20.9%) 분야가 주요 영역으로, 가장 활발한 협력이 이루어지고 있는 것으로 나타났다. 정보통신 및 지식서비스 분야는 상대 적으로 작은 규모이지만 높은 네트워크 밀도를 보였다. 기술 분야별로 주도적 역할을 담당하는 기관 유형에 차이가 나타났는데, 전통적 제조업 기반 분야(기계·소재, 화학, 전기·전자)에서는 공공 연구기관이, 융합연구 기반 분야(정보통신, 바이오·의료)에서는 기업이 지식 생산을 주도 하는 것으로 나타났다. 본 연구는 소재부품 분야 산학연 협력 네트워크의 구조적 특성을 종합 적으로 분석함으로써, 분야별 맞춤형 협력 모델 개발, 핵심 연구기관 지원 강화, 중소기업의 네트워크 참여 활성화 등의 정책적 시사점을 제시하였다.

육묘과정에서 생리적 반응성이 다른 비료로 추비할 때 홍고 추 3품종의 생육에 미치는 영향을 구명하기 위하여 본 연구를 수행하였다. 72셀 트레이에 시판상토를 충진하고 ‘AT Sinhotan’, ‘Allbokhap’ 및 ‘Callatan’ 품종의 종자를 파종한 후 암상태에 서 발아시켰다. 발아 후 25℃의 육묘실로 옮겨 질소 기준 150mg·L-1으로 농도를 조절한 산성, 중성, 알칼리성 및 동일 한 농도의 산·알칼리성 비료 교호 처리구 등 4처리로 실험하 였다. 생육 조사는 파종 후 39일과 56일에 2회 수행하였으며, 처리한 생리적 반응성에 영향을 받아 고추의 초장, 경경, 지상 부 생체중 등에서 유의한 차이가 나타났다. 생리적 반응성 중 품종에 관계없이 중성 비료 처리구에서 경경과 생체중 등 모 든 조사항목에서 생육이 우수하였다. 파종 후 56일째 ‘Callatan’ 품종이 타 품종들 보다, 그리고 각 품종 내에서는 중성 비료와 교호 시비 처리구에서 개화수가 많았다. 중성 비료 처리구에 서 엽면적이 가장 넓었고, SPAD 값은 산성 비료 처리구에서 가장 컸다. 식물체의 무기원소 분석 결과, 교호 시비 처리구의 ‘Callatan’ 품종이 Ca을 제외한 모든 원소의 함량이 높았다. 생리적 반응성이 다른 비료를 처리할 때 생육 차이가 발생하 는 본 연구의 결과는 육묘과정의 생장조절을 위한 기초 자료 로 활용될 수 있다고 생각한다.

A high-pressure in-situ permeation measuring system was developed to evaluate the hydrogen permeation properties of polymer sealing materials in hydrogen environments up to 100 MPa. This system employs the manometric method, utilizing a compact and portable manometer to measure the permeated hydrogen over time, following high-pressure hydrogen injection. By utilizing a self-developed permeation-diffusion analysis program, this system enables precise evaluation of permeation properties, including permeability, diffusivity and solubility. To apply the developed system to high-pressure hydrogen permeation tests, the hydrogen permeation properties of ethylene propylene diene monomer (EPDM) materials containing silica fillers, specifically designed for gas seal in high-pressure hydrogen environments, were evaluated. The permeation measurements were conducted under pressure conditions ranging from 5 MPa to 90 MPa. The results showed that as pressure increased, hydrogen permeability and diffusivity decreased, while solubility remained constant regardless of pressure. Finally, the reliability of this system was confirmed through uncertainty analysis of the permeation measurements, with all results falling within an uncertainty of 11.2 %.

본 연구에서는 효과적인 뇌친화적 리더십과 비효과적인 뇌친화적 리더십을 비교하고 뇌친화적 리더십 유형별 성향을 탐색함으로써 강점 강화 코칭 스킬 (skill) 및 약점 보완 코칭 스킬(skill)을 개발하는 것은 물론, 뇌친화적 리더십 역 량 향상을 위한 코칭 모델을 개발하는데 연구의 목적이 있다. 코칭 및 리더십 전문가 15명을 대상으로 델파이 조사를 실시한 후, CVR값, 합의도, 수렴도를 분 석하여 뇌친화적 리더십 코칭 스킬 및 모델을 수정·보완하였다. 본 연구의 결론 은 다음과 같이 정리할 수 있다. 첫째, 뇌친화적 리더십 유형별로 강점 강화 코 칭 스킬(skill), 약점 보완 코칭 스킬(skill) 등 뇌친화적 리더십 코칭 스킬(skill) 개발함으로써 개별 맞춤형 리더십 역량을 향상할 수 있다. 둘째, 뇌친화적 리더 십 코칭 모델의 각 단계별로 코칭 원리 및 전략을 적용함으로써 뇌친화적 리더 십 코칭 목표를 달성할 수 있다. 본 연구에서 제안한 뇌친화적 리더십 코칭 스킬 및 모델은 기존의 거래적 리더십, 변혁적 리더십 차원에서 벗어나 뉴로리더십 (neuro-leadership) 등 뇌과학에 기반한 리더십 패러다임 전환을 시도하였다는 점에서의 의의가 있다.

Background: The Functional Movement Screen (FMS) is widely used for movement assessment but suffers from subjective scoring that leads to inconsistent evaluations. While previous studies have focused on reliability, the validity of AI-supported assessment remains unexplored. Objectives: To evaluate the reliability and validity of an AI-based motion analysis system using MediaPipe for three FMS movements. Design: Prospective reliability and validity study with repeated measures. Methods: Thirty healthy adults (age 23.4±2.8 years) performed three FMS tests (Deep Squat, Hurdle Step, Inline Lunge) recorded on video. Three evaluators (two experienced physical therapists and one novice) assessed recordings in three phases: Phase 1 involved traditional assessment by experts only to establish criterion reference, Phase 2 had all evaluators using AI support, and Phase 3 consisted of repeated AI-supported assessment. The AI system provided real-time visual feedback of joint angles and alignment through MediaPipe skeletal tracking. Results: Criterion validity showed strong agreement between traditional expert assessment and AI-supported assessment (r=0.94, P<.05). Inter-rater reliability improved from good (ICC=0.89) to excellent (ICC=0.91) with AI support. The novice evaluator achieved immediate expert-level performance with only 0.05 points difference from experts. Intra-rater reliability was excellent for all evaluators (ICC=0.84-0.89). Conclusion: The AI-based system demonstrated strong validity and improved reliability for fundamental movement assessment. While AI support enabled novice evaluators to achieve expert-level performance immediately, it may increase sensitivity to subtle movement variations. This technology shows promise for standardizing movement screening, though current limitations restrict its application to standing movements.

The purpose of this study is to develop customized suit designs incorporating flower and bird painting patterns from Korean folk painting and to propose differentiation strategies for customized fashion design in Korea. The research was conducted in three stages. First, concepts and types of customization were examined through theoretical analysis, identifying the characteristics of customized design. Second, flower and bird painting patterns found in Korean folk painting were classified according to their symbolic meanings and developed into digital patterns. Third, flower and bird painting patterns from Korean folk painting were utilized in the suit designs following the principles of customized design. The results are as follows. Customizations were classified into three types: simple combination, selective adjustment, and creative assembly. The characteristics of customized design were identified as customer participation and product modularity. The symbolic meanings of the flower and bird motifs were categorized into six themes: happiness, wealth, longevity, fertility, love, and protection against evil. The resulting digitally developed patterns sought to integrate traditional cultural elements into customized fashion design. The final suit designs demonstrated hyper-individuation through modular assembly, enabling both customer participation design and product modularity. Detachable elements that modularize the jacket structure enhanced customizability while promoting sustainable and eco-conscious design practices.

Anomaly detection technique for the Unmanned Aerial Vehicles (UAVs) is one of the important techniques for ensuring airframe stability. There have been many researches on anomaly detection techniques using deep learning. However, most of research on the anomaly detection techniques are not consider the limited computational processing power and available energy of UAVs. Deep learning model convert to the model compression has significant advantages in terms of computational and energy efficiency for machine learning and deep learning. Therefore, this paper suggests a real-time anomaly detection model for the UAVs, achieved through model compression. The suggested anomaly detection model has three main layers which are a convolutional neural network (CNN) layer, a long short-term memory model (LSTM) layer, and an autoencoder (AE) layer. The suggested anomaly detection model undergoes model compression to increase computational efficiency. The model compression has same level of accuracy to that of the original model while reducing computational processing time of the UAVs. The proposed model can increase the stability of UAVs from a software perspective and is expected to contribute to improving UAVs efficiency through increased available computational capacity from a hardware perspective.

Nitrogen fertilizers are generally known to be of great help in improving crop yields, but excessive nitrogen fertilizer usage can not only destroy the environment but also negatively affect crop growth. This study aims to develop a decision-making system for optimal nitrogen fertilizer use for efficient production of Chinese cabbage (Brassica rapa), one of the major vegetables. The proposed system has the functions of detecting farmland based on satellite images, predicting cabbage yields and greenhouse gas (e.g., nitrous oxide) emissions according to nitrogen fertilizer use, and making decisions using the prediction results. To develop the proposed system, a generalized prediction model is developed using experimental data collected from South Korea, Egypt, India, Canada, Lithuania, and China, and the effectiveness of the proposed system is validated through experiments. As a result, the proposed system will enable farmers to conduct eco-friendly agricultural activities through appropriate nitrogen fertilizer use while stably maximizing productivity of Chinese cabbages.

Background: The 75-kDa glucose-regulated protein (GRP75) plays a crucial role in regulating the formation of mitochondria-associated endoplasmic reticulum (ER) membranes (MAMs), facilitating the transfer of Ca2+ ions, and is essential for lipid metabolism, mitochondrial function, calcium homeostasis, and apoptosis in mammalian cells. However, the relationship between GRP75 expression and preimplantation embryonic development in pigs remains unknown. Methods: In this study, we investigated whether GRP75 influences ER–mitochondrial junctions and mitochondrial Ca2+ levels in porcine embryos in vitro . We examined the expression of GRP75 at the zygote, cleavage, and blastocyst stages using immunofluorescence staining and western blot analysis. Results: GRP75 fluorescence and mitochondrial Ca2+ levels were significantly lower (p < 0.01) in the blastocysts than in the zygotes. Western blot analysis revealed a decline in the expression of mitochondrial fusion factors mitofusin 2, GRP75, and the mitochondrial calcium uniporter complex MICU1 protein at the blastocyst stage. To investigate the effects of GRP75 on blastocyst developmental competence, porcinespecific GRP75-siRNA (25 nM) was microinjected at the zygote stage. The results showed a significant decrease in the development capacity until the blastocyst stage (Control: 31.2 ± 2.0%, N.C. siRNA (25 nM): 29.8 ± 3.1%, vs. GRP75-siRNA (25 nM): 24.1 ± 1.6%; p < 0.05). GRP75 in the mitochondria and ER-localized GRP75 were both significantly reduced in blastocysts of pigs microinjected with GRP75 siRNA. Along with ER–mitochondrial colocalization, the MAM formation ratio was significantly reduced in the GRP75-siRNA group compared with that in the control (Control: 29.3% vs. GRP75- siRNA (25 nM): 15.7%, p < 0.001). Conclusions: These findings demonstrate that the GRP75-derived MAM region is involved in the development of early embryos in porcine blastocysts.

The emergence and re-emergence of infectious diseases pose ongoing threats to public health. This study aims to develop an agent-based simulation model (ABM) to predict the spread of novel infectious diseases during early outbreak phases and evaluate the effectiveness of control measures, specifically focusing on the impact of interventions such as maskwearing, vaccination, and social distancing on outbreak dynamics and the reduction of symptomatic cases. Using demographic and COVID-19 outbreak data from South Korea, we constructed a detailed contact network model encompassing workplaces, schools, households, and communities. Using demographic and COVID-19 outbreak data from Seoul, South Korea, we constructed a detailed contact network model encompassing workplaces, schools, households, and communities. Key transmission parameters were inferred using Approximate Bayesian Computation. The resulting ABM platform, implemented in a C-based R package, allows for flexible scenario simulation involving 56 adjustable parameters, including mask-wearing, vaccination coverage, and social distancing. Simulation outputs demonstrated the model’s capacity to reproduce observed transmission patterns in workplace and school outbreaks, enabling public health authorities to anticipate outbreak dynamics and assess interventions. This framework provides a valuable decision-support tool for controlling future infectious disease incursions.