As domestic traffic policies have shifted from vehicle-centric approaches to a ‘Safe Speed’ paradigm, the installation of roundabouts has surged. However, existing studies based on linear statistical models have failed to identify the complex non-linear interactions between geometric features and accident severity, limiting their ability to provide concrete design thresholds. To overcome the lack of traffic volume data, this study developed a geometry-based Design Capacity Index (DCI) and proposed a new analytical framework using the Equivalent Property Damage Only (EPDO) rate per unit capacity as the dependent variable. Utilizing a dataset of nationwide roundabouts (2007–2020), a grid search-optimized eXtreme Gradient Boosting (XGBoost) model and SHAP analysis were applied, achieving a 40.5 % performance improvement over linear baselines. The results revealed that circulatory roadway width was a dominant factor; contrary to the 'Road Diet' theory, ensuring 'Geometric Sufficiency' (wider lanes) proved more effective for safety in medium-to-large roundabouts. Furthermore, a 'Broad Optimal Zone' was identified within an inscribed circle diameter (ICD) of 35–70 m, while a 'Paradox of Scale' emerged beyond 70 m where safety benefits plateaued. Additionally, raised crosswalks served as essential offset measures, consistently reducing accident costs regardless of the intersection size. Based on these findings, this study provides empirical evidence for revising design guidelines to prioritize the 35–70 m ICD range and advocates for the mandatory installation of physical calming measures in oversized roundabouts.

Background: Real-time ergonomic risk assessment in manufacturing environments is challenged by severe class imbalance in high-risk postures and the need for deployment-efficient models. Conventional oversampling techniques may violate biomechanical constraints, limiting their suitability for human motion data. Objectives: This study aimed to compare multiple machine learning models for real-time ergonomic risk assessment while addressing data imbalance using biomechanically appropriate learning strategies and evaluating both predictive performance and deployment efficiency. Design: Comparative study. Methods: A large-scale workplace safety dataset comprising image-based skeletal keypoints was analyzed. To mitigate class imbalance without generating biomechanically implausible samples, cost-sensitive learning and focal loss were employed instead of synthetic oversampling. Subject-wise data splitting was applied to prevent data leakage. Five model families, including Random Forest, convolutional neural networks, and a lightweight graphbased network, were evaluated using accuracy, F1-score, area under the receiver operating characteristic curve (AUC), and high-risk recall. Statistical significance was assessed using bootstrap confidence intervals and McNemar and DeLong tests. Results: The lightweight graph-based model demonstrated competitive classification performance while maintaining reduced computational complexity. Although none of the models achieved the predefined high-risk recall threshold, statistically significant performance differences were observed across model families. Conclusion: The findings suggest that biomechanically informed imbalance handling improves methodological validity in ergonomic risk assessment. While deployment feasibility appears promising, further empirical validation on edge hardware is required.

설악산국립공원에서 무인센서카메라의 효율적인 활용을 위해 종의 분포, 상대풍부도(RAI), 그리고 카메라 운용 일수와 탐지된 종 수 간의 상관관계 를 추정했다. 2020년 7월부터 9월까지 24대의 카메라로 총 1,704 카메라 운용 일수 동안 모니터링한 결과, 설악산에 서식하는 중대형 포유류 10종이 모두 탐지되었다. 오소리(Meles leucurus)는 23개 지점(95.8%)에서, 멧돼지(Sus scrofa)는 22개 지점(91.7%)에서 각각 포착되어 설악산국립 공원 전역에 넓게 분포하고 있음이 확인되었다. 이 두 종은 최초 감지까지의 평균 시간이 가장 짧았고 RAI가 가장 높아, 10종 중에서 가장 쉽게 관찰되는 종임을 시사했다. 멸종위기에 처한 산양(Naemorhedus caudatus)은 24개 지점 중 13개 지점(54.2%)에서 기록되었는데, 신속한 감지와 높은 RAI를 보여 설악산국립공원이 대한민국 내에서 이 종의 핵심 서식지임을 입증했다. 반면, 멧토끼(Lepus coreanus)는 3개 지점에서만 관찰되었다. 멧토끼의 RAI는 낮았으며, 최초 감지까지의 평균 시간이 길어 관찰 확률이 낮았다. G7, G26, G28, G36, G37 조사지점은 7~8종이 관찰되어 높은 종다양성을 보였다. 특히, G7, G26, G28에서는 산양, 삵(Prionailurus bengalensis), 담비(Martes flavigula) 등 3종의 멸종위기종이 탐지되어, 이 지역들이 집중적인 보호가 필요한 생태학적 핵심 구역으로 기능함을 시사했다. 따라서, 이 지역의 효과적인 보호 및 관리를 위해 장기적인 모니터링이 필요하다. 운용 효율성 분석 결과, 24대 카메라의 총 운용 일수 1,704일 중 10종 전체(100%) 탐지에 1,066일이 소요되는 것으로 예측되었다. 24대 카메라로 모니터링할 경우, 카메라당 최소 44.42일이 소요되어야 10종 전체를 감지할 수 있다는 것을 의미한다. 9종(90%)은 10.75일, 8종(80%)은 6.21일이 소요될 것으로 예측했다. 향후 카메라 트랩 모니터링은 카메라 수, 공간적 범위, 종다양성을 고려하여 설계되어야 한다.

Freshwater bivalves contribute to key ecological functions in lake ecosystems, yet their cryptic and benthic lifestyles often hinder detection through conventional surveys. In this study, we applied environmental DNA (eDNA) metabarcoding to assess the diversity and distribution of unionid bivalves in six lakes across Republic of Korea. Water samples were collected from three sampling strategies-Center Surface, Center Mix, and Waterside Surface-and processed using 16S rDNA-targeted primers followed by high-throughput sequencing. A total of four unionid species (Cristaria plicata, Sinanodonta lauta, Unio (Nodularia) douglasiae, and Anodonta woodiana) were detected across 18 sampling points. Notably, eDNA successfully identified unionid presence in all lakes, even where conventional surveys failed to observe individuals. Among the sampling strategies, Center Mix exhibited the highest values for Shannon and Simpson indices as well as ASV richness. Waterside Surface samples generally showed lower diversity and detection frequency. A Venn diagram of ASV occurrences revealed three ASVs shared across all sampling strategies and one unique ASV found only in Center Mix. These results indicate that sampling location significantly affects detection sensitivity and diversity representation in eDNA-based bivalve monitoring. Combined application of Center Mix and Center Surface strategies may enhance both detection efficiency and species diversity coverage in lentic environments.

Membrane-Aerated Biofilm Reactor(MABR)는 하수처리 공정의 에너지 효율을 획기적으로 개선할 수 있는 차세대 기술로 주목받고 있다. 기존 활성슬러지 공정의 기포형 산기 시스템은 산소전달효율(OTE)이 낮고 전체 에너지 소비의 80%까지 차지하는 등 에너지 비효율성을 내포하고 있다. 반면 MABR은 기체 투과성 막(membrane)을 통해 생물막으로 산소를 직접 공급함으로써, 이론적으로 100%까지 OTE 달성이 가능하다. 본 논문은 MABR의 산소전달 메커니즘과 구조적 특징을 정리하고, OTE, 산소전달속도(OTR), 폭기 효율(AE) 등의 에너지 효율 지표를 중심으로 파일럿 및 실규모 적용 사례 11건을 분석하였다. 분석 결과, AE는 기존 활성슬러지 공정 대비 약 4-5배 향상된 수치이다. 그러나 OTE와 OTR 간의 상충관계, 공정 규모, 기질 농도 등 다양한 운영 변수에 따라 성능이 상이하게 나타났으며, 현장 적용에서는 이론적 효율을 하회하는 사례도 확인되었다. 이러한 한계를 극복하기 위한 기술적 접근으로는 간헐 공기 공급, 주기적 환기, 막 소재 개선, 막 이완 제어 등이 시도되고 있다. 동시에, 실증 연구들 간 실험 조건 및 효율 지표 산정 기준의 상이함은 결과 해석의 일관성을 저해하는 요인으로 지적된다. 따라서 본 연구는 향후 MABR 기술의 실용화를 위해 에너지 효율 평가 기준의 표준화와 대규모 현장 검증의 필요성을 강조한다.

In this study, high-efficiency InZnP/ZnSe/ZnS quantum dots (QDs) were synthesized and applied to the development of self-luminous traffic signs. The synthesized QDs exhibited a photoluminescence (PL) peak wavelength of 613 nm and a uniform nanoparticle size of 6 nm in diameter. Quantum dot films were coated using a roll-to-roll process with varying thicknesses (110 μm, 85 μm, and 75 μm), and color coordinate analysis confirmed that all films fell within the red region. A 4CL resin and PCB with high thermal dissipation properties were employed to fabricate the self-luminous traffic signs. Performance evaluations showed a white luminance of 625.4 cd/㎡, a red luminance of 220.2 cd/㎡, an insulation resistance of 10,000 MΩ, and an insulation breakdown voltage of 500V, indicating excellent performance. This study confirms the potential of InZnP-based QDs as an environmentally friendly alternative to conventional Cd-based QDs. Furthermore, the integration of high-efficiency QD films with advanced heat-dissipating PCB technology is expected to improve traffic safety, particularly in low-visibility and nighttime environments

이 연구는 완주군의 농촌체험휴양마을 10개를 대상으로 상대적인 효율성을 분석하였다. 농촌체험 휴양마을은 마을이 갖고 있는 자연환경, 전통자원 등을 활용하여 농촌 활성화를 도모하고 있다. 농촌체험휴양마을의 상대적인 효율성의 분석은 DEA를 이용하였고, 투입과 산출변수는 직원 수, 체험프로그램 수, 체험시설 면적, 총 방문객, 매출액으로 설정하였다. 그리고 DEA 모형 중 투입지 향의 CCR 모형을 이용하였다. 분석결과 평균 효율성은 0.7891이며, 10개 농촌체험휴양마을 중 비율적이 60%, 효율적이 40%로 나타났다. 또한 투입 과다분과 투영점을 고려할 때 투입 과다분이 발생하여 향후 농촌체험마을의 특성이나 직원수, 체험프로그램 수, 체험시설 면적을 종합적으로 고려하여 직원역량강화, 프로그램과 시설의 효율적 관리와 활용이 필요할 것으로 판단된다.

Efficient and safe maritime navigation in complex and congested coastal regions requires advanced route optimization methods that surpass the limitations of traditional shortest-path algorithms. This study applies Deep Q-Network (DQN) and Proximal Policy Optimization (PPO) reinforcement learning (RL) algorithms to generate and refine optimal ship routes in East Asian waters, focusing on passages from Shanghai to Busan and Ulsan to Daesan. Operating within a grid-based representation of the marine environment and considering constraints such as restricted areas and Traffic Separation Schemes (TSS), both DQN and PPO learn policies prioritizing safety and operational efficiency. Comparative analyses with actual vessel routes demonstrate that RL-based methods yield shorter and safer paths. Among these methods, PPO outperforms DQN, providing more stable and coherent routes. Post-processing with the Douglas-Peucker (DP) algorithm further simplifies the paths for practical navigational use. The findings underscore the potential of RL in enhancing navigational safety, reducing travel distance, and advancing autonomous ship navigation technologies.

This study focuses on the effectiveness of regional business support programs funded by South Korea's Balanced National Development Special Account, one of the policies designed to address regional imbalances and promote local autonomy. Using the analytical approach including DEA (Data Envelopment Analysis) methodology, This study analyzed the efficiency of 76 star companies in the Jeonbuk region based on their performance from 2018 to 2023. This study was designed to improve previous studies limitations, which only analyzed simple input-output efficiency in the short term, by using six years of mid-term data to comprehensively evaluate input variables in both R&D and Non-R&D sectors. The main purpose of this study is to analyze the effectiveness of the expiring Star Company Development Program by evaluating efficiency of supported company groups using DEA and to propose support models and policy suggestions for upcoming regional specialized industries support program by identifying the features of both optimal and inefficiency models. For this, employments along with financial indicators such as sales revenue, operating profit, and total assets were set as output variables, with R&D and non-R&D support amounts were set as input variables for analysis. According to the results, the optimal efficiency model group has strong intellectual property acquisition capabilities, and continuous R&D investment. It shows that continuous innovation activities are a key factor for improving the effectiveness of support. This study found that, from a mid․long term perspective, policy support programs should be customized by unique characteristics of each industry field, Based on this, it was suggested that upcoming regional specialized industry support programs in the Jeonbuk region should include policy planning and support program design to complement the weaknesses of each industry field.

As the Fourth Industrial Revolution advances, smart factories have become a new manufacturing paradigm, integrating technologies such as Information and Communication Technology (ICT), the Internet of Things (IoT), Artificial Intelligence (AI), and big data analytics to overcome traditional manufacturing limitations and enhance global competitiveness. This study offers a comprehensive approach by evaluating both technological and economic performance of smart factory Research and Development (R&D) projects, addressing gaps in previous studies that focused narrowly on either aspect. The research combines Latent Dirichlet Allocation (LDA) topic modeling and Data Envelopment Analysis (DEA) to quantitatively compare the efficiency of various topics. This integrated approach not only identifies key research themes but also evaluates how effectively resources are utilized within each theme, supporting strategic decision-making for optimal resource allocation. Additionally, non-parametric statistical tests are applied to detect performance differences between topics, providing insights into areas of comparative advantage. Unlike traditional DEA methods, which face limitations in generalizing results, this study offers a more nuanced analysis by benchmarking efficiency across thematic areas. The findings highlight the superior performance of projects incorporating AI, IoT, and big data, as well as those led by the Ministry of Trade, Industry, and Energy (MOTIE) and small and medium-sized enterprises (SMEs). The regional analysis reveals significant contributions from non-metropolitan areas, emphasizing the need for balanced development. This research provides policymakers and industry leaders with strategic insights, guiding the efficient allocation of R&D resources and fostering the development of smart factories aligned with global trends and national goals.

This study aims to optimize the SDC (Spinning Dust Collector) system in amphibious assault vehicle engines through numerical analysis of dust and moisture particle separation efficiency using CFD-DPM. Focusing on an axial cyclone structure, the research evaluates separation efficiency across various particle sizes and flow conditions. The results demonstrate that vortices generated by cyclone blades play a critical role in influencing particle trajectories and improving separation performance. Additionally, the study highlights the significant impact of engine flow conditions and housing design, emphasizing that their careful optimization enhances the system's efficiency in separating dust and water. These findings offer valuable insights into optimizing inlet and outlet flow paths and cyclone housing design, providing a solid foundation for advancing SDC system performance in high-efficiency engines.

이 연구의 목적은 염전에서 폐기되는 간수로 만든 담체의 비소 제거 특성을 연구한 것이다. 간수담체의 물리적 특성은 800 ~ 900℃에서 소성된 것을 사용하여 검토하였다. 비표면적과 흡수율은 각각 16.670 m2/g, 42.3%이었고 압축강도와 총 기공부피는 각각 28.3 kgf/cm2, 0.00818 cm2/g이었다. 간수담체의 화학적 조성은 SiO2가 55.3%이었고 특히, MgO가 19.2%로 매우 높은 농도로 존재하였다. 이런 결 과는 마그네슘 이온을 고농도로 포함하고 있는 간수의 영향을 받은 것으로 판단된다. 또한, X-Ray 회절 분석 결과, 간수담체는 Forsterite(Mg2SiO4)와 결정구조가 유사한 것으로 밝혀졌다. 간수담체는 제올라이트와 다양한 간수 용량으로 제조되었고 20% 간수로 만든 간수담체에서 비소 제거 효율이 최대화되었다. 또한, 수용액 중 간수담체의 용량이 40%일 때 90% 이상의 비소 제거 효율을 나타냈다. 간 수담체의 비소 제거 반응은 매우 빠르게 발생하였고 대부분의 비소 제거 반응이 수 시간 내에 끝났다. 회분식 실험을 통해서 간수담체의 비소 제거율에 미치는 pH 영향을 검토한 결과, 간수담체는 넓은 pH 범위(pH 5 ~ 10)에서도 높은 비소 제거 효율을 나타내었다.

The purpose of this study is to estimate the production function of the oliver flounder (Paralichthys olivaceus) aquaculture industry, analyze its efficiency, and provide implications for sustainable aquaculture. For this purpose, the SFA model was utilized. The results of this study are as follows. First, the coefficient values of labor wages and farm area are higher than other inputs. This suggests that the Korean oliver flounder aquaculture industry is labor-intensive. Second, disease management is highly influenced by management efficiency. The more frequently farms are disinfected and culled, the higher the management efficiency with culling having a greater impact on management efficiency. Finally, the cost inputs of high and low-efficiency fish farms were analyzed, and it is recommended that wages, electricity, drugs, and oxygen should be kept at a reasonable level rather than excessive. However, the higher the inputs for mortality removal and disease management, the higher the management efficiency. In other words, improving the farm environment is the most important to achieve sustainability and management efficiency of Korean oliver flounder farming.

PURPOSES : This paper presents a foundational study aimed at strengthening the competitiveness of future overseas construction engineering projects, efficiently guiding investment decisions for the government or private sectors and establishing policy suggestions for areas that need to be supplemented and linked. METHODS : The data envelopment analysis (DEA) model was used to measure the operational efficiency for individual types of work. The DEA model for measuring efficiency uses the representative Charnes, Cooper, and Rhode (CCR) and Banker, Charnes, and Cooper (BCC) models. RESULTS : By using statistics of overseas construction projects and conducting DEA, it was revealed that construction management was most needed in the energy facility sector of overseas construction projects. CONCLUSIONS : Although the capabilities of our country's companies are excellent, it was evident that the energy and industrial facilities sectors, which need to be supplemented to enhance their competitiveness, require policy support that incorporates construction management (CM). Consequently, it was confirmed that the construction management sector needs investment that should continue to be activated in the future. Additional research is needed that considers variables and environments related to overseas construction projects’ on-site conditions. To this end, the government should continue to promote research and government investment linked to CM to make progress in overseas construction sectors.