Earticle

This study investigates the superior predictive performance of a DeepGBM model (combining boosting and deep learning) for identifying metabolic syndrome in the Korean adult population using KNHANES data. DeepGBM consistently showed superior performance compared to established algorithms. Feature prioritization revealed waist circumference and fasting glucose as critical predictors. This research demonstrates the potential of integrating advanced machine learning with public health data to improve early detection.

Unapproved parts are increasingly used in military aircraft due to part obsolescence, urgent operational needs, and domestic localization efforts. While such parts may offer short-term flexibility, they pose serious challenges to the integrity of airworthiness certification systems, which rely on part conformity, traceability, and validated performance data. This study identifies and classifies the key risks associated with unapproved parts and applies structured risk assessment tools—Failure Mode and Effects Analysis (FMEA) and the Bow-Tie Risk Model—to quantify and visualize potential failures. Risk elements such as functional mismatch, lack of traceability, and insufficient certification data are prioritized using the Risk Priority Number (RPN) metric. Additionally, the study proposes institutional improvements such as digital traceability systems, conditional approval frameworks, and shared certification databases to mitigate these risks. The findings contribute to enhancing both the safety and flexibility of the airworthiness certification process, particularly in contexts where non-standard parts cannot be avoided. This research offers a practical approach for integrating risk-based thinking into component approval, providing a framework that balances operational demands with safety assurance.

Recent advances in autonomous flight, electric propulsion, and distributed architectures have enabled the rapid emergence of future air systems such as AAVs, UAVs, and eVTOL aircraft, whose software-intensive and autonomous operational characteristics differ fundamentally from those of conventional manned aircraft. This study analyzes the technical and operational characteristics of these systems and identifies structural gaps in existing airworthiness certification frameworks, discussing the applicability of performance-based certification, risk-based airworthiness approaches, and digital airworthiness concepts as practical directions for future certification reform.

Hybrid transmissions are a component being researched and developed by major automakers to reduce fuel consumption and emissions. Power-split hybrid transmissions utilize two or more motors to enable continuously variable gear shifting and control the operating points of the engine and motor, thereby reducing engine fuel consumption and emissions. This study proposes a systematic design method for a two-mode hybrid system that minimizes power circulation. To achieve this, we design a two-mode hybrid system that combines three-axis and four-axis systems using two planetary gears and two clutches. We also propose a structure that operates only in modes where power circulation does not occur, thereby improving transmission efficiency.

In electric vehicles, lightweight design is an important development objective for improving energy efficiency. Seat frame materials that are important for weight reduction use steel. In this study, weight optimization analysis was conducted by applying Almag, an aluminu-magnesium alloy material that offers excellent weight reduction while maintaining structural strength, to the seat frame. First, key stiffness members among the seat components were identified. Static strength analysis and natural frequency analysis were then performed on the steel seat frame. Based on the analysis results, a static optimization analysis was carried out for the application of the Almag material to achieve displacement levels equivalent to the static strength analysis. In addition, a dynamic optimization analysis was performed to maximize the natural frequency. Through these analyses, the optimal thicknesses of the seat back and cushion frame were determined.

A needleless automatic injection syringe (Jet Injector) is a device that delivers drugs into the skin and tissues using high-speed fluid jets without the use of injection needles. Jet Injector's core technology is to penetrate the stratum corneum of the skin by converting pressure energy generated in the driving unit into fluid kinetic energy, and structural loads and dynamic responses generated in this process directly affect the performance and durability of the device. Therefore, the structural mechanical design of the drive unit can be said to be a key factor in securing the reliability and injection accuracy of the Jet Injector. This paper is intended to provide the basis data for the basic design of the drive unit of the "Animal Vaccine-free Automatic Injection Syringe (hereinafter referred to as the "Jet Injector"), and this calculation data provides basic data for the design. Based on this, it is possible to design the drive unit according to various assumptions and given conditions, and the expected performance can be reasonably inferred according to the design.

This study uses a frequency analyzer to measure and analyze the major alarm sounds of cars selected by domestic car manufacturer and car size, which are continuously improving in accordance with the continuous development of the automobile field. Therefore, the purpose is to find the alarm sound that modern people can hear best and find improvement measures accordingly. In the past, only the driving performance of vehicles was considered important, but as the industry and science developed, research was conducted to satisfy not only the driving performance of vehicles but also the comfort and emotional needs of drivers, such as ride comfort, safety, and noise issues. At the same time, it is progressing actively and continues to develop.

Locally resonant metamaterials (LRMs) are artificial periodic structures that effectively suppress elastic wave propagation within specific frequency bands, known as bandgaps, by utilizing local resonance phenomena of embedded mass-spring resonators.​ Conventional LRMs, however, are limited by fixed bandgap characteristics once fabricated, necessitating re-fabrication or complex processing for any frequency adjustment. This study proposes a novel, tunable bandgap LRM architecture constructed from readily available, off-the-shelf mechanical components: a plastic bolt serving as the stiffness element and a changeable steel square nut as the mass element. Numerical analyses, employing Bloch-Wave theory for dispersion curve calculations and finite element methods for frequency response function (FRF) simulations, validate the systematic tunability of the bandgap. Specifically, by simply adjusting the nut's position along the bolt, the bandgap's central frequency and bandwidth can be effectively modulated without re-machining. Experimental validation on an 8x8 finite array structure confirms the formation and adjustable nature of these bandgaps, demonstrating a consistent shift in the bandgap frequency range in response to nut position changes, which aligns well with numerical predictions. This approach offers a practical, low-cost, and easily manufacturable solution for vibration mitigation, enabling on-site adaptable designs for targeted frequency ranges.

This study proposes an automated torch angle and position adjustment mechanism for three-dimensional curved-surface welding in shipbuilding. Designed to replace manual operations, the mechanism actively responds to the relative angle between the base plate and stiffener, enabling simultaneous control of torch orientation and positioning using a single power source. The system is integrated into a tracker consisting of a pinion-sector gear assembly for angle adjustment and a cam mechanism for position control. Dynamic simulations confirmed that the torch stably follows the stiffener angle across varying welding speeds, with smooth compensatory motion between the carriage and tracker. Furthermore, a motor-torque-based PID control was implemented, maintaining the torch angle error within 0.23° and the wire tip position error within 0.02 mm. These results verify that the proposed mechanism is highly effective for the automated welding of complex curved structures.

Large bore LNG dual fuel (DF) engines are increasingly adopted in marine propulsion systems due to their high thermal efficiency and reduced regulated emissions. However, as the cylinder bore increases, combustion stability and knock propensity become more sensitive, while the isolated geometric effects of bore scaling governing these trends remain insufficiently clarified. In particular, the pure effect of bore scaling on wall heat loss, in-cylinder thermal conditions, and knock-related combustion characteristics has not been systematically investigated under identical operating conditions. In this study, a CFD based geometric scaling framework was developed and applied to investigate the influence of cylinder bore variation on combustion behavior and knock sensitivity in a four stroke LNG DF diesel engine. A reference engine geometry with a 350 mm bore was defined, and the bore diameter was systematically varied while maintaining identical stroke, compression ratio, combustion chamber geometry, valve timing, fuel properties, and injection conditions to isolate pure geometric effects. A sector based three dimensional in cylinder CFD model with dynamic mesh treatment was employed. The results indicate that increasing the bore diameter reduces the wall-area-to-volume ratio, leading to a reduction in relative wall heat loss and enhanced thermal energy retention in the core region. Consequently, the in cylinder core gas temperature increases near the end of compression and during the early combustion phase, which promotes higher heat release rates, advanced combustion phasing, and increased maximum pressure rise rates. As a result, the knock margin decreases and knock sensitivity increases under identical operating conditions. Rather than providing absolute quantitative predictions, this study presents a physically consistent, trend oriented framework to interpret bore-scaling effects on combustion stability and knock sensitivity in large bore LNG DF engines. The proposed framework provides a fundamental guideline for subsequent high-fidelity CFD simulations and experimental investigations aimed at knock mitigation and combustion control.

Fiber laser welding is considered an effective joining process for cryogenic storage structures because of its high welding speed, narrow heat-affected zone, and low thermal deformation. In this study, butt welding was performed on 10 mm-thick SUS316L plates using a fiber laser system, and the distortion behavior according to welding conditions was experimentally evaluated. The main process variables were laser power (4.0 and 4.5 kW) and welding speed (36–54 mm/s), and five welding cases were investigated. Distortion was measured at multiple locations on the welded specimens, and heat input was calculated from laser power and welding speed. The results showed that, under the 4.0 kW condition, distortion increased as welding speed decreased and heat input increased. At a constant welding speed of 48 mm/s, increasing the laser power from 4.0 kW to 4.5 kW caused a slight increase in distortion. Among all conditions, the 4.5 kW-54 mm/s case showed the largest distortion. In addition, identical heat input conditions did not always produce the same distortion level, indicating that welding distortion was affected not only by heat input but also by the combination of laser power and welding speed. These results provide basic data for the prediction and control of welding distortion in fiber laser butt-welded SUS316L for cryogenic hydrogen storage tank applications.

This study proposes a deep learning–based predictive maintenance model for condition monitoring and remaining useful life (RUL) estimation of a 1 kW brushless DC (BLDC) motor. Multi-sensor signals, including vibration (10 kHz), current (20 kHz), and surface temperature (10 Hz), were acquired under six health conditions: normal, bearing outer race fault (BPFO), bearing inner race fault (BPFI), unbalance, misalignment, and stator insulation degradation. To jointly exploit spatial patterns and temporal degradation behaviors, a hybrid CNN–LSTM model with a multi-task learning framework was developed to perform 6-class fault classification and RUL regression simultaneously. Experimental results on the constructed BLDC motor dataset show that the proposed model achieves a classification accuracy of 95.8%, outperforming conventional SVM and 1D-CNN baselines (85.2% and 90.7%, respectively). In addition, the proposed method significantly reduces RUL prediction error, yielding an RMSE of 9.6 and an MAE of 6.8, which corresponds to approximately 39% improvement over a single LSTM-based regression model. These results demonstrate that the proposed CNN–LSTM multi-sensor fusion framework is effective for intelligent condition monitoring and predictive maintenance of BLDC motor systems, and it can be extended to a wide range of rotating machinery applications.

With the increasing demand for high-power and high-efficiency power conversion systems, LLC resonant converters, which achieve both high efficiency and high power density through soft-switching operation, have attracted significant attention. Accordingly, various topologies based on LLC resonant converters have been proposed; however, studies on topology analysis and selection criteria remain insufficient. Therefore, this paper analyzes device losses, voltage and current stresses, and efficiency characteristics under different output power levels based on PSIM simulations, and proposes a topology selection methodology for the primary- and secondary-side structures of LLC resonant converters.

As outsourced maintenance in civil aviation expands, the allocation of safety management responsibilities between air carriers and maintenance organizations has become an important legal issue. This study examines the legal structure of outsourced maintenance contracts and the distribution of safety responsibilities through a comparative review of ICAO standards, IATA guidance, the FAA’s oversight approach, and the Korean aviation safety legal framework. The findings show that the Korean system includes key control elements for outsourced maintenance, but they remain dispersed across regulations and certification requirements. Accordingly, the air carrier’s safety oversight authority is not clearly defined. This study argues that the issue should be addressed not by granting comprehensive control, but by clarifying a functional and limited safety oversight authority necessary to ensure continuing airworthiness and safe operations.

This study was conducted to verify the structural stability of the chassis frame of the Small electric low-floor bus. The chassis frame model was analyzed under its own weight and external loads to determine deformation and stress distribution. A finite element method (FEM)-based structural analysis was performed to verify the strength and durability of the chassis frame assembly components. The analysis results identified the maximum stress values ​​and their locations throughout the system. Furthermore, considering the differences in materials used in each component, the maximum stress values ​​for each component were individually calculated. Comparing the maximum stress values ​​with the yield strength of each material confirmed the structural stability of the designed Small electric low-floor bus chassis frame.

This study proposes a distributed integrated control architecture based on Direct Digital Control(DDC) as an alternative to conventional centralized Distributed Control System(DCS) structures for a Canadian oil sands pilot plant, and theoretically analyzes its control characteristics and operational optimization potential. The target process consists of production and circulation, separation, water treatment, partial upgrading, and utility systems, and exhibits complex characteristics such as multiphase flow, high viscosity, time delay, strong coupling, and operation under extreme environmental conditions. In this study, an integrated control architecture combining independent DDC nodes for each process unit with a supervisory control layer is presented. A control model considering the coupling relationships among production, separation, water treatment, and upgrading processes is formulated, along with an objective function for energy optimization. Furthermore, through literature-based comparison and system architecture analysis, it is demonstrated that the DDC-based structure is suitable for oil sands pilot plants in terms of responsiveness, scalability, fault isolation, and energy efficiency.

In modern architecture acoustic design, the psychological feedback from the audience has been important as a traditional acoustic parameter. Therefore, this study analyzes an acoustic psychological feedback from audience through an exhibition performance. A feedback from 660 audiences for eight different categories was evaluated. For the result, above 5 out 7 in entire indicators which indicates that the audience was satisfied with the hall. There was a remarkable deviation depending on floors and age groups. 2nd floor provides higher points in most indicators with 5.75 for an envelopment and 5.61 for a balance, whereas 1st floor provides the least with 5.16 for loudness and 5.17 for envelopment. Moreover, audience in their 30s evaluated acoustics more critically, whereas audience in their 50s rated more positively.

This study examines the structural characteristics of interface design in experiential content environments, where users must process complex information in real time. Despite the growing importance of such environments, interface design has been primarily studied in terms of usability and efficiency, with limited attention to structural and cognitive aspects. To address this gap, this study analyzes aviation simulation content as a representative case of experiential media. Three cases—Microsoft Flight Simulator, X-Plane, and VR-based aviation simulation content—were comparatively examined based on visual interface structure, information visualization methods, and user interaction characteristics. The results reveal that experiential content interfaces share common structural patterns, including hierarchical information organization, multi-layered visualization, cognitive–immersion balance, and real-time interaction loops. Based on these findings, this study proposes a cognitive-based interface design model that explains how users prioritize, interpret, and respond to information within experiential environments. This study contributes to the field by reframing interface design as a structural and cognitive system, rather than merely a usability-driven process.

Finite Element Analysis (FEA) was conducted to verify the structural safety of thruster disc brakes applied to quay cranes. Since these disc brakes are continuously exposed to heavy loads and repetitive braking conditions, ensuring sufficient structural reliability is of paramount importance. SS410 was applied as the frame material and STS405 as the pin material, and structural analysis incorporating the respective material properties was performed using ANSYS Workbench. Based on a minimum operating range of 0.5 mm, the analysis yielded a maximum deformation of 0.52 mm, an equivalent stress of 231.79 MPa, and a shear stress of 79.09 MPa in the frame; the resulting safety factor of 1.77 confirmed that stress remained below the yield strength of SS410 (410 MPa), verifying structural safety under normal operating conditions. Under the maximum operating range of 3.0 mm, a maximum deformation of 3.13 mm, an equivalent stress of 340.26 MPa, a shear stress of 155.54 MPa, and a safety factor of 1.2 were obtained, all remaining below the yield strength limit of the frame material. Although stress concentrations were localized primarily in the frame region, both components remained within their respective yield limits. The results confirm the brake's structural integrity under normal operating conditions, though the 3.0 mm case warrants design refinement to meet the recommended safety factor of 1.5. Subsequent studies will address fatigue life, thermo-structural coupling, and dynamic loading to further validate and improve the design.

This study analyzed the security architecture of a blockchain-based authentication protocol and identified major vulnerabilities in smart health and Internet of Things (IoT) environments. The analysis confirmed potential risks including replay attacks due to key synchronization delays, incomplete verification logic in smart contracts, trust imbalance among nodes, and privacy breaches from private key reuse. To address these, the study proposes an enhanced protocol that integrates a time- and nonce-based multi-layered key derivation structure with dynamic trust indicators. Performance evaluation confirmed that the proposed solution simultaneously improves both throughput and security.

A needle-free automatic injection syringe is a device that delivers drugs into the skin and tissues using a high-speed fluid jet without using an injection needle. This technology is attracting attention as an efficient means of vaccine delivery in the veterinary and livestock fields that reduce the risk of cross-infection and require mass vaccination. In particular, animal vaccination provides various advantages over conventional needle injection methods in terms of worker safety, inoculation speed, and maintenance cost. Among these drivers, Jet Injector Nozzle's flow path design is very important in needleless automatic injection syringes. This paper was conducted to solve the problem of pressure loss at the nozzle discharge side of the existing Jet Injector in designing the flow path of the animal vaccine-free automatic injection syringe nozzle. To this end, CAE was performed and the optimum design of the flow path required by the company was performed, and a large flow rate was possible in the optimal shape design, but this focuses on the nozzle flow path, which requires a review of design additions of cylinders and motors on the rear side.

Injection-molded products frequently exhibit localized surface defects such as weld lines, flow marks, scratches, bubbles, and burn marks due to variations in material flow, mold temperature, and cooling conditions. Conventional visual inspection is highly dependent on operator experience, while rule-based machine vision methods are limited under variations in lighting and surface texture. This study proposes a deep learning–based defect detection model using YOLOv8 combined with a novel Defect-Aware Augmentation technique designed to enhance robustness for small, local defect regions. The proposed augmentation pipeline includes geometric transformations, optical perturbations, local defect patch synthesis, and diffusion-based synthetic defect generation. Experiments were conducted on a custom dataset of 5,000 images (3,000 normal and 2,000 defective). Results show that the proposed model achieves significant improvements over baseline models, obtaining 95% precision, 90% recall, and 0.96 mAP@0.5, outperforming the default YOLOv8 model by 7%p in mAP. Ablation studies verify that defect-aware augmentation is the dominant factor contributing to the performance gain. The proposed system demonstrates high applicability for automated quality inspection in injection- molding production lines.

Fiber laser welding is a promising joining process for cryogenic stainless steel structures because of its high energy density, narrow heat-affected zone, and low thermal distortion. In particular, SUS316L stainless steel has been considered a suitable candidate material for cryogenic storage systems due to its favorable corrosion resistance, weldability, and mechanical stability at low temperatures. In this study, butt welding of 10 mm-thick SUS316L plates was performed using a fiber laser process, and the effects of welding conditions on weld cross-sectional geometry and mechanical properties were investigated. Five welding conditions were applied by varying laser power and welding speed, and double-sided 2-pass welding was conducted for all cases. Cross-sectional observation was carried out to evaluate bead geometry, including bead width, concave geometry, and penetration depth. Tensile tests and Charpy impact tests at -196 °C were also performed on the welded joints. The results showed that decreasing welding speed and increasing laser power generally increased bead width and penetration depth. Yield strength ranged from 288.6 to 306.6 MPa, tensile strength from 584.3 to 595.7 MPa, elongation from 47.4 to 50.0%, and cryogenic impact value from 37.0 to 52.7 J. Among the tested conditions, the 4.0 kW-0.7 mpm condition showed the most balanced mechanical performance, especially in terms of elongation and cryogenic impact toughness. These results provide useful basic data for selecting reliable fiber laser welding conditions for SUS316L cryogenic storage structures.

Racing boats operate under high-speed conditions and repetitive rapid maneuvers, where the performance of the propulsion system plays a critical role in race outcomes. The propeller is a key component that converts engine rotational power into thrust and must maintain structural stability under high rotational speeds and hydrodynamic loading. In this study, a racing boat propeller based on a carbon fiber reinforced plastic(CFRP) laminate structure was designed and a manufacturing process was established. The proposed propeller consists of a two-blade configuration in which the hub and blades are integrated into a single structure to minimize structural discontinuity under high rotational conditions. The composite propeller was fabricated using a prepreg lay-up process followed by vacuum-assisted thermal curing. In addition, flat laminate panels with the same carbon fiber lay-up configuration as the propeller were simultaneously manufactured to prepare bending test specimens for process verification. Flexural tests were conducted to evaluate the mechanical characteristics of the CFRP laminate structure. The results of this study provide fundamental data for the design and manufacturing of lightweight CFRP-based racing boat propellers.

This study evaluates the bonding strength characteristics of carbon fiber–foam sandwich structures for application in Wing-In-Ground(WIG) craft. Sandwich panel specimens were fabricated using low-temperature curing carbon fiber prepreg and PVC foam cores. The specimens were manufactured through a vacuum oven molding process to produce composite sandwich panels. To investigate the structural performance and interfacial bonding characteristics between the face sheet and the core, flexural tests and drum peel tests were conducted. The flexural tests were performed to evaluate the structural stiffness and failure behavior of the sandwich structure, while the drum peel tests were used to assess the adhesive bonding strength between the carbon fiber skin and the foam core. Based on the experimental results, the interfacial bonding behavior and failure characteristics of the carbon fiber–foam sandwich structures were analyzed. The results of this study are expected to provide fundamental data for the structural design and bonding performance evaluation of composite sandwich structures for WIG craft applications.