In the practical tests for welding under the Korean National Technical Qualification system, four welding positions-including the overhead position-are currently evaluated. However, in the case of shielded metal arc welding (SMAW), the overhead position is noted to have a significant impact on test participation and pass rates due to psychological burden and difficulty. This study investigates and analyzes recent trends in national welding qualification tests, confirming a decline in the number of applicants and pass rates. Additionally, visual inspection and radiographic non-destructive testing of test specimens by welding position revealed that the overhead position exhibited a significantly higher frequency of surface and internal defects compared to other positions. Consequently, it received the lowest average quality scores. Meanwhile, major international organizations such as the American Welding Society (AWS), the American Society of Mechanical Engineers (ASME), and the International Association of Classification Societies (IACS) primarily adopt horizontal and vertical positions as their standard testing configurations. This indicates a notable discrepancy between Korea's current qualification system and international standards. Based on these findings, this study suggests the need for a more flexible approach to the configuration of welding test positions in order to enhance international alignment and encourage broader participation in national welding qualification exams.

This study analyzed the clinical characteristics and injury severity of severe trauma patients according to injury mechanisms using community-based severe trauma survey data from 2023. The primary injury mechanisms were falls/slips (48.2%) and transportation accidents (38.7%), accounting for approximately 87% of all cases. Although machinery-related injuries had a low incidence, they exhibited the highest Injury Severity Score (ISS) of 31.81. Transport times differed significantly by region, and patients who underwent emergency interventions such as surgery, blood transfusion, or embolization had significantly longer transport times. These findings provide essential baseline data for the management and prevention strategies of severe trauma.

This study investigates the use of phase change materials(PCMs) as a thermal energy storage method to regulate the temperature of EV charging cables. PCMs absorb heat during phase transitions, thus providing thermal buffering and enhancing system stability. Three organic fatty acids of lauric acid (LA), palmitic acid (PA), and stearic acid (SA) were selected as candidate materials based on their appropriate melting points, high latent heat, and chemical stability. Using Differential Scanning Calorimetry(DSC), the thermal properties of each pure PCM and their mixtures were analyzed. LA exhibited a melting point of 43.78℃ and a latent heat of 188.41kJ/kg, PA had 62.46℃ and 213.46kJ/kg, and SA recorded 69.49℃ and 232.28kJ/kg. Among the mixtures, the PA-SA mixture with 50 mass% PA showed the most promising performance, with a stable melting point below 60℃ and latent heat exceeding 200kJ/kg. The specific heat capacity of this mixture was measured as 1.85kJ/kg·K in the solid phase and 2.17kJ/kg·K in the liquid phase.

We present the development of a passive millimeter-wave imaging system with a two-dimensional imaging array receiver. Passive millimeter-wave imaging involves the detection of blackbody radiation emitted and/or reflected by objects at millimeter-wave frequencies, enabling non-invasive imaging under low-visibility conditions. By utilizing a two-dimensional receiver array, the system is capable of acquiring real-time images without mechanical scanning. To realize this system, we designed and fabricated a receiver in which key millimeter-wave components such as tapered slot antennas (TSAs), baluns, amplifiers, and detectors are integrated on a quartz substrate using gold plating and semiconductor bonding techniques. A critical element of the system is the transmission line transition between the antenna and the monolithic microwave integrated circuit (MMIC). This was implemented using a balun, which demonstrated low insertion loss and wide bandwidth performance in the 30-40 GHz range, as confirmed through fabrication and experimental measurements. For signal detection, we developed a compact, wideband, low-noise receiver module that integrates an MMIC amplifier with a Schottky barrier diode(SBD) detector. This detection system achieved a low noise figure of 1.9 dB at 13.5 GHz, demonstrating excellent noise performance suitable for high-sensitivity passive imaging applications.

This study explores national competitiveness and investment priorities in the space technology sector by analyzing patent portfolio trends across major countries. Using a large language model (LLM), more than 27,000 patent abstracts were classified into detailed technology categories based on NASA's space technology taxonomy. For each category, indices of technology importance and attractiveness were computed, and national positions were visualized using a portfolio matrix adapted from Ernst's strategic framework. The results showed that while the United States maintains a dominant position, China and Korea have made notable gains through targeted investments. This research demonstrates the utility of LLM-based patent classification for high-resolution technology mapping and offers strategic insights for national R&D policy in the evolving space economy.

Soil water content is crucial for crop growth, directly affecting plant health and productivity. Accurate prediction of soil water flow is essential for effective crop water management. HYDRUS and SWAP are widely used models for simulating soil water dynamics. This study aims to predict soil water content at various depths in upland soil using HYDRUS and SWAP, compare predictions with measured values, and assess model performance. Daily soil water content was calculated using soil hydraulic parameters, surface and subsoil conditions, crop characteristics, and meteorological data. To validate the models, soybeans were grown in sandy loam soil under non-irrigated conditions. Soil water content was measured at 10, 20, 30, and 40 cm depths using an FDR sensor and compared with model predictions. HYDRUS showed an R² of 0.97-0.98 and an RMSE of 2.7%-3.3%, while SWAP had an R² of 0.98-0.99 and an RMSE of 1.6%-3.2%. During the vegetative growth stage, both models closely matched measured values. However, during the reproductive stage (mid-August), HYDRUS showed larger discrepancies due to its lack of a crop growth module. Overall, both models effectively predicted soil water dynamics. Thus, HYDRUS and SWAP can serve as valuable tools for soil water management and productivity improvement in upland soils.

Intelligent Process Automation (IPA), which integrates robotic process automation with artificial intelligence, has been increasingly adopted across various industries. However, its application in medical imaging remains at an early stage. This study proposes a medical image classification system based on a Graph Attention Network (GAT) to detect pneumonia from chest X-ray images. To effectively capture local structural information, each input image is segmented into various numbers of superpixels using the Simple Linear Iterative Clustering (SLIC) algorithm. These superpixels serve as graph nodes, each represented by a feature vector. Edges are assigned using dilation to reflect neighboring relationships. The proposed GAT architecture incorporates multi-head attention, batch normalization, and dropout layers, and its performance was evaluated using stratified 5-fold cross-validation. Results showed that when the number of superpixels was set to 100, the model achieved its best performance with an accuracy of 87.7% and an F1-score of 88.2%, along with low standard deviations, indicating robust and consistent outcomes. In contrast, testing with 300 superpixels revealed a trade-off between precision and recall. These findings demonstrate that the proposed model shows potential for sensitive detection of pneumonia cases; however, excessive over-segmentation may hinder its generalizability.

Fuel cell electric vehicle(FCEV) using polymer electrolyte membrane fuel cell(PEMFC) consumes the hydrogen as fuel. The ejector with very simple structure in FCEV enhances the stack efficiency and supplies the humidity to hydrogen through recirculation system. Thus the ejector has been applied to many industrial fields such as aerospace, machinery as well as FCEV. This study aims to investigate the flow characteristics and prediction of flow rate for ejector in FCEV. As the results, as the inlet pressure of ejector was increased, the velocity in nozzle was decreased, on the other hand, the velocity in mixing section and diffuser was increased. In analysis conditions of this study, the flow rate of hydrogen was affected more density than velocity. In cases of 4~6 bar, the flow rate of hydrogen was supplied to stack about 0.15 times compared with that of air. Further it showed that the flow rate of hydrogen was about 10 times larger than that of commercial vehicle in case of 2 bar.

This study presents a digital twin-based methodology for predicting the lifetime of silicon carbide (SiC) power semiconductors in elevator power conversion systems. The framework integrates real-time sensor data with thermal and electrical simulations to monitor operational conditions of converter and inverter modules. Key parameters-including power loss, junction temperature, and fatigue-induced thermal stress-are dynamically evaluated under diverse load and acceleration scenarios. Results show that SiC devices achieve over 70% lower power losses and reduced temperature rises compared to silicon (Si), leading to improved energy efficiency and reliability. The digital twin further enables residual life estimation and predictive maintenance by quantifying fatigue damage. Additionally, optimized heat sink and cooling strategies effectively regulate temperatures under varying conditions. The proposed framework enhances reliability, reduces maintenance costs, and supports smart integration with renewable energy systems, laying the foundation for broader digital twin applications in high-efficiency power electronics.

Architectural design Architectural design has long been driven by human creativity and intuition. While these qualities express artistic sensibility, they face limitations in addressing modern demands such as energy efficiency, sustainability, and cost-effectiveness. In this context, digital technologies are increasingly adopted in architecture to support quantitative analysis and automate optimal design solutions. Key tools such as Building Information Modeling (BIM), Dynamo, and Generative Design (GD) enhance both precision and creativity by managing complex design variables. This study explores how these digital technologies are transforming architectural design and how they can address current challenges. Through literature review, case studies, and feasibility analysis, the research investigates the conceptual basis and practical roles of BIM, Dynamo, GD, and GD for Optimization in the design process. The study focuses on two areas: (1) building façades, where GD generates diverse and optimized designs, and (2) building forms, where BIM and Dynamo facilitate complex geometry manipulation. The findings confirm that digital tools are vital to evolving architectural practices and propose strategies to integrate them effectively into real-world design environments.

This study aimed to examine the experiences of safety accidents and preventive education needs of safety education among 157 foodservice personnel in army in Gyeongnam, in order to identify implications for effective accident prevention. Data were collected through structured questionnaires and statistically analyzed to compare officier with soldier. The accident experience rate among officier was 29.8%, significantly higher than that of soldier (11.0%) (p<0.01). The proportions of safety accidents were highest for burns (14.0%) and cuts (8.9%), with Self-negligence and unskilled use of equipment as main causes. The perceived importance of safety accident prevention management averaged 4.78 points (out of 5), and the performance score was 4.44 points, with significant differences observed according to status (p<0.001). In the comparison of the importance and performance of safety accident prevention management between officers and enlisted personnel, significant differences were found in all areas and items (p<0.01 to p<0.001). IPA revealed that musculoskeletal disorder-related items were categorized as low priority, indicating a need for focused improvement. It is expected that the findings of this study will contribute to improving the safety management system in army units and to developing effective prevention programs.

High manganese steels (Mn: 3-27 wt.%) have been developed in response to the growing demand for structural materials exhibiting both high strength and toughness in marine environments. These alloys possess the combined mechanical properties required for such potential for applications, thereby enhancing their potential for use in marine structures, ships, and naval vessels. In this study, as part of a comprehensive evaluation of the material properties of high-manganese steel for diverse engineering applications, fatigue crack growth tests were performed to investigate the fatigue behavior and resistance of high manganese steel under cyclic loading. The fatigue crack propagation test results indicated that, during the initial stage of fatigue cycling, crack propagation was negligible even with an increasing number of cycles. With further cycling, the crack propagation rate increased gradually, followed by a pronounced acceleration in the final stage. In addition, the relationship between crack length and fatigue cycles was used to plot a graph of the fatigue crack growth rate as a function of the stress intensity factor range.

Patent data are essential for tracking technological progress, assessing competitiveness, and forecasting future developments. However, the rapid evolution of technology and the rise of convergent fields make filtering irrelevant data a persistent challenge. Traditional statistical models and manual preprocessing by researchers require substantial time and effort, prompting continuous research on efficient information structuring. In particular, filtering methods based on statistics or keywords have limitations in fully capturing subtle technical nuances and complex contexts. To address these limitations, this study proposes a semantic noise filtering methodology for patent data leveraging the contextual understanding capabilities of large language models (LLMs). The approach integrates LLM-based classification, statistical stability analysis, and cross-LLM review procedures to enhance the consistency and reliability of the filtering results. Applied to 1,930 domestic patents in the bio-artificial organ domain from 2000 to 2024, the method identified 55.4% as noise. The results demonstrate the method's potential as an effective tool for technology policy formulation and strategic decision-making support.

Captive Flight Test (CFT) is an essential procedure in the development of guided weapons, enabling the verification of seeker performance under actual flight conditions. While manned fixed-wing aircraft have traditionally been used as CFT platforms, the use of unmanned helicopters has recently emerged due to their advantages in operational flexibility, cost-effectiveness, and the ability to reproduce flight scenarios with high precision. In this study, a configuration mounting the seeker pod on only one side of the unmanned helicopter is proposed. To evaluate the aerodynamic characteristics of this asymmetric configuration using Ansys Fluent, flow analyses were conducted comparing a symmetric configuration without a pod and an asymmetric configuration with the pod mounted on one side. The analysis results showed that the differences in flow patterns were minimal, and the difference in force in the Fy direction was 2.597%, which falls within the tolerance margin and is considered not significant in practical terms.

Recent vehicle displays include not only instrument clusters and navigation functions, but also touchscreen-enabled CIDs, HUDs, and infotainment displays. Ultra-large displays that contain instrument clusters, CIDs, and CDDs are also commercialized. While LCDs offer a price advantage, OLEDs offer a comparative advantage in performance. POLEDs are suitable for curved and non-standard vehicle interiors. E-paper display technology can be used to achieve vehicle exterior color shifting to suit consumer preferences. As display applications expand to include vehicle windows, mirrors, and ceilings, transparent display technology is being adopted. While LCDs are reaching saturation, OLEDs are steadily increasing their market share. The global vehicle display market is predicted to reach $39.1 billion or $48.9 billion by 2034, with the Asia-Pacific region expected to hold a 35% market share. Securing technologies applicable to automotive displays is crucial and urgent in preparation for the era of self-driving vehicles, necessitating ongoing research and development.

The purpose of this study was to evaluate the effect of surface treatment methods on the tensile bond strength and surface roughness between 3D-printed denture bases and chairside reline resin. Dumbbell-shaped specimens were fabricated using digital light processing(DLP)-based 3D printing technology with a 50 ㎛ layer thickness and 90° build angle. The experimental group was divided into four groups according to surface treatment: no surface treatment(Control), airborne-particle abrasion(APA), grinding with silicone carbide paper(Sandpaper), Tokuyama Rebase II Normal adhesive(Adhesive). Chairside reline resin was applied to the 3 mm repair area. Tensile bond strength was measured using a universal testing machine, and surface roughness(Ra) and surface shape were observed using a digital optical microscope. Statistical significance was tested using one-way ANOVA and Tukey HSD and Games-Howell post hoc tests(α = .05) . Adhesive showed superior tensile bond strength values compared to other groups(p < .05), whereas there was no statistically significant difference among the groups excluding Adhesive(p > .05). The Ra values of Adhesive and Control were significantly higher than those of other groups(p < .05). Within the limitations of this study, the bond strengths with reline materials in all groups were within the clinically acceptable range(> 0.44 MPa).

In the shipbuilding and offshore industries, safety accidents not only threaten the lives of workers but also significantly impact a business's productivity and reliability. Major accidents such as falling and colliding with heavy objects, workers falling from heights, and suffocation in confined spaces still frequently occur in shipyards. Conventional hard hats, as personal protective equipment, are a means of mitigating physical damage from accidents, but they have limitations in preventing accidents and ensuring a rapid response after an incident. Therefore, this study aims to develop a smart helmet that applies various ICT-based smart technologies to a conventional hard hat. We have designed the smart helmet, created a prototype based on an MCT-PC (Machine Tool Control - Personal Computer) system, and developed molds for commercialization. The goal is to create a smart helmet that can protect workers through real-time monitoring in hazardous environments and facilitate a swift response to accidents by tracking the worker’s location and status after an incident.

This paper proposes a collaborative robot-based measurement system for analyzing the force-torque profiles of home appliance mechanisms. While existing manual measurement methods suffer from operator-dependent variations and are limited to providing only a single maximum force value, which is insufficient for capturing dynamic characteristics, the proposed system overcomes these limitations. It utilizes a collaborative robot equipped with a 6-axis force/torque sensor and a control system to replicate the user's physical interaction, enabling the collection of continuous force and torque data across the entire operating range of the mechanism. The system's performance was validated through case studies on a refrigerator's swing door and a drawer-type door. The results demonstrated high repeat precision, acquiring comprehensive force-torque profiles that offer objective and reliable indicators for improving product design, enhancing quality control, and optimizing the user experience.

The primary reason for constructing public parking lots is to provide parking spaces. However, the efficiency of public parking lots is often not proven after the construction. Related attribute indicators were developed to evaluate the validity of the construction of a public parking lots. A survey was conducted to collect quantitative and qualitative opinions on public parking lots construction from the perspectives of both Administrator and user groups. The analysis was conducted using the Analytic Hierarchy Process(AHP) method. The CI and CR were below 0.1, indicating that the data were valid and weighted value and ranking were calculated. The results revealed that user groups prioritize convenience of use and operational efficiency when constructing public parking lots. It was analyzed that the rate of securing a parking lots is the most important even in detailed indicators. Next, the width of the access road and the distance to the main road appeared in order. The results of this study are expected to be practical and applicable to future public parking lots construction. Furthermore, the study presents a new method for evaluating the feasibility of public parking lots construction.

The unit construction cost is one of the key indicators for assessing the cost-effectiveness of road construction projects. However, existing government statistics are limited because they are based on design estimates rather than completion data, and comparative analyses considering project attributes are lacking. This study conducted a comparative analysis of unit construction costs for road construction projects by facility type, construction scale, and duration. Using data on 396 completed road projects from the Post-Construction Evaluation database, the Kruskal-Wallis test was used to examine cost differences among subgroups. The results show that: (1) highways have higher unit costs than national and provincial roads due to stricter design requirements; (2) larger projects tend to have higher unit costs because of increased construction complexity; and (3) projects with the shortest durations exhibit the highest unit costs, reflecting accelerated (crash) construction and intensive resource mobilization. These findings quantitatively demonstrate that unit construction costs vary significantly across multiple project attributes and highlight the importance of using actual completion cost data, rather than planning estimates, to assess cost performance in road construction.

In this paper, we designed a module using objects for velocity and current control of an integrated BLDC motor with an embedded controller, and conducted velocity and current control experiments using the control program. The developed program module for controlling a BLDC motor using objects was applied to a BLDC motor with an embedded controller, demonstrating basic controllability. Furthermore, the velocity control experiment demonstrated good target speed tracking and good control performance. For analog signal input calculations for the input/output devices, a 10-time average and offset value were applied to ensure high input signal stability. We designed an object-based control module capable of detecting operational errors and faults that may occur during BLDC motor operation.

This study investigates the effectiveness of the "Safety Call" system, a work stoppage policy introduced in energy public corporations to enhance workplace safety. The research employed a mixed approach combining Delphi-based expert review and a field survey of workers, with 15 validated items covering awareness, effectiveness, and user acceptability. The results show that while workers demonstrated relatively high awareness of the system's objectives and procedures, both effectiveness and acceptability were rated at moderate levels. Regression analysis further revealed that effectiveness and user acceptability significantly influenced the intention to use the system, whereas awareness alone had no meaningful impact. These findings highlight that raising awareness is not sufficient for institutionalization of the system; rather, improving user acceptability is crucial. In particular, follow-up management, transparent and fair handling of reports, anonymity and multi-channel access, feedback mechanisms, and data-driven operation were identified as essential factors to enhance practical utilization. The study also emphasizes the importance of extending the application of the system beyond public institutions to the private sector, thereby fostering a broader safety culture and contributing to the advancement of national occupational safety management.

In recent times, workers, both in domestic and abroad, tend to avoid working at manufacturing process and other industrial sites. Therefore, we propose a new approach to control and design of autonomous driving robot system based on iterative learning control for smart factory. In order to achieve the unmanned manufacturing, it is necessary to be performed the autonomous task performance by robot system with learning capabilities based on deep learning. In this study, the main focus is real time implementation of autonomous driving control and iterative learning control of mobile robot based on neural network. The detailed contents include the kinematic modeling and dynamic characteristics analysis, and the SLAM(simultaneous localization and mapping) for autonomous driving of mobile robot system. Furthermore, the paper proposes an accuracy path control technology of position and velocity control based on a neural network control algorithm. It has been verified the performance of the iterative learning control of mobile robotl based on voice command by experiments.

This study aimed to evaluate the performance of extracurricular programs by integrating efficiency and effectiveness. Fifty-six health-related extracurricular programs at a university in Jeollabuk-do, Korea, were analyzed using Data Envelopment Analysis (DEA) and Importance-Performance Analysis (IPA). Inputs included budget, staff, and facilities, while outputs were participant numbers and satisfaction scores. Efficiency was assessed with CCR, BCC, and scale efficiency models. Under the CCR model, communication, character, self-management, and creativity & innovation showed both high efficiency and satisfaction, whereas global competence remained low. The BCC model indicated generally high efficiency and satisfaction across all competencies, with information literacy and creativity & innovation being strongest. Scale efficiency analysis revealed global competence had high efficiency but low satisfaction. A multidimensional evaluation that incorporates both efficiency and effectiveness is necessary for understanding program performance. This study demonstrates the usefulness of combining DEA and IPA to overcome the limitations of satisfaction-based evaluations.

This study empirically investigates the effects of Occupational Health and Safety Management Systems (OHSMS), including ISO 45001 and KOSHA-MS, on safety and health activities within certified Korean workplaces. Unlike prior research largely focused on outcome metrics such as accident reduction and cost savings, this study categorizes safety practices into three domains: frontline, risk prevention, and administrative/procedural activities. Survey responses from 136 KOSHA-MS certified sites were analyzed using multiple regression to evaluate the influence of core OHSMS components-operational management, risk assessment, and contractor safety management-across these domains. Results show that OHSMS factors substantially enhance overall workplace safety and health activities, with operational management and risk assessment demonstrating the strongest positive effects, particularly on frontline and risk prevention practices. Intriguingly, education and competency management yielded negative short-term impacts on frontline activities, implying the need for practical, context-driven training approaches to maximize effectiveness. Additionally, contractor management and robust safety goal-setting were crucial for improving administrative/procedural practices, highlighting the significance of system integration with partner firms and strategic planning. The findings suggest differentiated management strategies are required to optimize each activity type, stressing the importance of tailored implementation, hazard prevention, and systemic reinforcement. Overall, this research provides new academic and practical insights for advancing robust safety and health management systems within Korean industrial settings.

This study reviews recent development trends and field applications of underwater cultural heritage (UCH) survey technologies. Synthesizing literature and representative case reports from the 1970s onward, we compare acoustic and magnetic sensors, including side-scan sonar (SSS), multibeam echosounder (MBES), sub-bottom profiler (SBP), and magnetometer (MAG), with complementary non-acoustic methods such as electrical resistivity tomography (ERT), ground-penetrating radar (GPR), and underwater metal detection. We also examine their integration with unmanned platforms (AUV/ASV/ROV/UAV) and GIS-based workflows for geodetic unification and data standardization. Our synthesis indicates substantial gains in wide-area search efficiency, high-resolution 3D documentation, repeatability, and operational safety across environments ranging from shallow, turbid waters to the deep sea; furthermore, site-level GIS integration and edge-computing-enabled quality control support near-real-time decision-making. Looking ahead, we identify four axes of progress: (1) coordinated multi-platform operations, (2) AI-driven automated interpretation and autonomous target reacquisition, (3) expanded digital documentation and public engagement via digital twins and VR/AR, and (4) open data-sharing frameworks aligned with ethical and permitting requirements. Limitations of this narrative review include the heterogeneity of sites and conditions, which precludes standardized head-to-head performance benchmarking; limited long-term repeat observations; and a paucity of quantified comparisons for non-acoustic methods and cost/logistics analyses. Nevertheless, the study organizes dispersed domestic and international practices, clarifies the technological evolution of UCH survey, and proposes a baseline and roadmap to guide future multi-platform experiments and reproducible, quantitative evaluations.

Large language models (LLMs) can exhibit reliability issues-most notably hallucinations-that undermine their suitability for high-stakes applications. We investigate a simple yet effective prompt-engineering strategy to improve response consistency and stability without modifying model internals. Our central technique prompts models to provide the reasoning evidence their answers, aiming for task-agnostic, broadly applicable gains in consistency. We compare two engineered prompt against one non-engineered baselines across three models (GPT-4o-mini, Llama-3.1-8B, and Gemini-2.0-Flash-Lite) and four datasets (BoolQ, QNLI, MRPC, SST-2). For every model-dataset-prompt combination, we run 10 trials and evaluate Accuracy, Precision, Recall, F1 score, and the standard deviation of F1. The engineered prompt yields the lowest F1 standard deviation across the full experimental suite, indicating markedly improved response stability; on several datasets, it also achieves substantial F1 gains over non-engineered prompts. These results suggest that explicitly requesting post-answer reasoning is a practical, cost-efficient, and broadly applicable method for reducing output variability and enhancing overall reliability in LLMs. Code: https://anonymous.4open.science/r/LLM_consitency-B0ED/README.md

This study analyzed a questionnaire to find out the relationship between the professional self-concept and clinical judgment ability of emergency medical workers. For the study, a questionnaire was conducted on emergency medical workers at general hospitals in Busan and Gyeongnam from November 1 to December 30, 2024. The questionnaire consisted of 7 general characteristics, 14 professional self-concept, and 23 clinical judgment ability items. The statistical program SPSS 24.0 was used as a data processing method for the questionnaire results, and the reliability analysis results of the questionnaire were Cronbach's = .759 and Cronbach's = .967, which were higher than the standard value of 0.6, indicating that the measurement data had internal consistency. The factors affecting clinical judgment ability were clinical experience, annual salary, and professional self-concept, and a statistically significant difference was confirmed (p<.01).In this study, the survey subjects were limited to some emergency medical workers. Therefore, I think there are limitations in generalizing the research results. However, I think the research is successful in that it identified the current status of some emergency medical workers' professional self-concept and clinical judgment ability and confirmed the level of demand. I hope that follow-up research will continue by expanding the subjects based on this study.

This study is a study to identify factors affecting suicide attempts of middle and high school students through youth health behaviors, and used primitive data from the 20th Youth Health Behavior Online Survey in 2024. The composition of the questionnaire consisted of five general characteristics, six health forms and emotional characteristics. The statistical program SPSS24.0 was used as the result data processing method. Factors affecting suicide attempts include school year, drinking, smoking, and grief over the past 12 months. The experience of despair, the experience of loneliness over the past 12 months, was able to confirm statistically meaningful differences (p<.01). Especially the sadness of the last 12 months. The higher the experience of despair and loneliness over the past 12 months, the more experience they have attempted suicide. Through the results of this study, we would like to come up with a plan to reduce the suicide problem of middle and high school students by identifying the factors that affect middle and high school students' suicide attempts.

This paper considers on the system response analysis by dynamic motion of movable object type wave power generation system using ball-screw device for energy conversion. A 3D simulation model was built using by multibody dynamics method for system performance analysis. The model was verified through comparison with 1D simulation tool widely used in the analysis of ball-screw devices. The verification results confirmed that 1D and 3D simulation models produced identical results. Using this verified 3D model, we analyzed the characteristic changes of the system by applying dynamic motion to the translational and rotational directions of the floating body. According the results, it was confirmed that the heave motion of the floating body is the main factor that has a dominant influence on the power generation performance. The rotational motion such as pitch affected the change in time-domain response characteristics, but did not affect the maximum rotational speed. This means that although the instantaneous maximum power rate remains the same even if the pitch changes, the total power rate changes.

Emergency medical settings are complex environments where crises frequently arise due to lack of communication and insufficient teamwork. The purpose of this study was to evaluate the effectiveness of simulation-based Crisis Resource Management (CRM) education for paramedic students and to verify the validity and reliability of the assessment tool. This study employed a case-control experimental design, conducted from October to December 2014, with 120 paramedic students. Participants were divided into an experimental group, which received simulation-based CRM training, and a control group, which received general simulation training. Data were analyzed using SPSS 18.0 with factor analysis and independent t-tests. The assessment tool demonstrated good validity and reliability (KMO=0.80, Bartlett's test p<0.001, Cronbach's α=0.75). The experimental group showed significantly higher CRM competency scores compared to the control group (p=0.02). These findings indicate that simulation-based CRM education is effective in enhancing crisis management skills among paramedic students and may contribute to the development of future curricula and continuing education programs.

This study investigates an upgraded Hanok-based lodging facility with unique architectural characteristics by implementing the as-operated HVAC specifications in a digital twin environment using OpenStudio to evaluate zone-level occupant thermal comfort and energy performance. The simulated scenarios included maintaining current operating guidelines, introducing central plant shutdown periods, and modifying zone-specific heating set points under dynamic conditions. The optimal outcome was achieved when the central heat source schedule was maintained as in current practice while a uniform heating set point of 21 ℃ was applied across all zones, resulting in an estimated 25.93 percent reduction in LP gas consumption. Thermal comfort indices were most stable in Zone S2 despite the highest heat demand, demonstrating robust comfort delivery under heavy load conditions. By explicitly incorporating the material properties of traditional elements such as hwangto loess and timber the study highlights the distinctive behavior of Hanok-based lodging facilities and provides insights transferable to eco-friendly wood-based housing research, offering useful foundations for low-carbon urban planning and sustainable architectural design.