• Journal of Korean Tunnelling and Underground Space Association
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• v.25 no.6
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• pp.555-567
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• 2023

The cracks in the tunnel are currently determined through visual inspections conducted by inspectors based on images acquired using tunnel imaging acquisition systems. This labor-intensive approach, relying on inspectors, has inherent limitations as it is subject to their subjective judgments. Recently research efforts have actively explored the use of deep learning to automatically detect tunnel cracks. However, most studies utilize public datasets or lack sufficient objectivity in the analysis process, making it challenging to apply them effectively in practical operations. In this study, we selected test datasets consisting of images in the same format as those obtained from the actual inspection system to perform an objective evaluation of deep learning models. Additionally, we introduced ensemble techniques to complement the strengths and weaknesses of the deep learning models, thereby improving the accuracy of crack detection. As a result, we achieved high recall rates of 80%, 88%, and 89% for cracks with sizes of 0.2 mm, 0.3 mm, and 0.5 mm, respectively, in the test images. In addition, the crack detection result of deep learning included numerous cracks that the inspector could not find. if cracks are detected with sufficient accuracy in a more objective evaluation by selecting images from other tunnels that were not used in this study, it is judged that deep learning will be able to be introduced to facility safety inspection.

• Journal of Food Hygiene and Safety
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• v.39 no.2
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• pp.102-108
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• 2024

This study was performed to establish the epidemiological features of a food poisoning outbreak that occurred in the cafeteria of a company in Chungcheongnam-do Province, Korea, in October 2020, and to recommend measures to prevent similar outbreaks. Twenty-one patients with acute gastroenteritis, three food handlers, seven cooking utensils, and 12 preserved food samples were subjected to viral and bacterial analyses based on procedures described in the "Manual for Detection of Foodborne Pathogens at Outbreaks". Among 135 individuals who had been served the meals, 21 (15.6%) showed symptoms of nausea and vomiting within an hour of consuming the food. Bacillus cereus were isolated from 11 (52.4%) of the 21 patients, one food service employee, one item of cooking ware, and 12 preserved food samples. In addition, we confirmed the toxin genes CER, nheA, and entFM from the isolated B. cereus strains. Pulsed-field gel electrophoresis results indicated that all of the isolated B. cereus strains were closely related, with the exception of strains obtained from one patient and one sample of preserved food. These findings provide evidence to indicate that the isolated B. cereus originated from preserved foods and an unhygienic eating environment. This outbreak highlights that the provision of food in non-commercial food systems must be thoroughly managed. In addition, it emphasizes the necessity for the correct and timely identification of causal pathogens for tracing the cause of food poisoning outbreaks, and the need to preserve food under appropriate conditions. To prevent similar cases of food poisoning, it is necessary to investigate cases based on an epidemiological approach and share the findings.

• Journal of Cadastre & Land InformatiX
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• v.54 no.1
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• pp.89-102
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• 2024

The recent advancements in Smart City and Digital Twin technologies have highlighted the critical role of integrating GIS and BIM in urban planning and construction projects. This integration ensures the consistency and accuracy of information, facilitating smooth information exchange. However, achieving interoperability requires standardization and effective project integration management strategies. This study proposes interoperability solutions for the integration of GIS and BIM for managing various projects. The research involves an in-depth analysis of the IFC schema and data structures based on the latest IFC4 version and proposes methods to ensure the consistency of reference point coordinates and coordinate systems. The study was conducted by setting the EPSG:5186 coordinate system, used by the National Geographic Information Institute's digital topographic map, and applying virtual shift origin coordinates. Through BIMvision, the results of the shape and error check coordinates' movement in the BIM model were reviewed, confirming that the error check coordinates moved consistently with the reference point coordinates. Additionally, it was verified that even when the coordinate system was changed to EPSG:5179 used by Naver Map and road name addresses, or EPSG:5181 used by Kakao Map, the BIM model's shape and coordinates remained consistently unchanged. Notably, by inputting the EPSG code information into the IFC file, the potential for coordinate system interoperability between projects was confirmed. Therefore, this study presents an integrated and systematic management approach for information sharing, automation processes, enhanced collaboration, and sustainable development of GIS and BIM. This is expected to improve compatibility across various software platforms, enhancing information consistency and efficiency across multiple projects.

• Journal of the Korea Society for Simulation
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• v.33 no.2
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• pp.37-44
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• 2024

The Korean Helicopter Development Program has successfully introduced the Surion helicopter, a versatile multi-domain operational aircraft that replaces the aging UH-1 and 500MD helicopters. Specifically designed for maneuverability, the Surion plays a crucial role in low-altitude tactical maneuvers for personnel transportation and specific missions, emphasizing the helicopter's survivability. Despite the significance of its low-altitude tactical maneuver capability, there is a notable gap in research focusing on multi-mission tactical maneuvers that consider the risk factors associated with deploying the Surion in the presence of enemy air defenses. This study addresses this gap by exploring a method to enhance the Surion's low-altitude maneuvering paths, incorporating information about enemy air defenses. Leveraging the Proximal Policy Optimization (PPO) algorithm, a reinforcement learning-based approach, the research aims to optimize the helicopter's path planning. Visualized experiments were conducted using a Surion model implemented in the Unity environment and ML-Agents library. The proposed method resulted in a rapid and stable policy convergence for generating optimal maneuvering paths for the Surion. The experiments, based on two key criteria, "operation time" and "minimum damage," revealed distinct optimal paths. This divergence suggests the potential for effective tactical maneuvers in low-altitude situations, considering the risk factors associated with enemy air defenses. Importantly, the Surion's capability for remote control in all directions enhances its adaptability in complex operational environments.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.3
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• pp.27-34
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• 2024

The direct and indirect damages caused by fires in underground utility tunnels have a great impact on society as a whole, so efforts are needed to prevent and manage them in advance. To this end, research is ongoing to prevent disasters such as fire flooding by applying digital twin technology to underground utility tunnels. A network is required to transmit the sensed signals from each sensor to the platform. In essence, it is necessary to analyze the application of wireless networks in the underground utility tunnel environments because the tunnel lacks the reception range of external wireless communication systems. Within the underground utility tunnels, electromagnetic interference caused by transmission and distribution cables, and diffuse reflection of signals from internal structures, obstacles, and metallic pipes such as water pipes can cause distortion or size reduction of wireless signals. To ensure real-time connectivity for remote surveillance and monitoring tasks through sensing, it is necessary to measure and analyze the wireless coverage in underground utility tunnels. Therefore, in order to build a wireless network environment in the underground utility tunnels. this study minimized the shaded area and measured the actual cavity environment so that there is no problem in connecting to the wireless environment inside the underground utility tunnels. We analyzed the data transmission rate, signal strength, and signal-to-noise ratio for each section of the terrain of the underground utility tunnels. The obtained results provide an appropriate wireless planning approach for installing wireless networks in underground utility tunnels.

• Journal of the Korea Society of Computer and Information
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• v.29 no.1
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• pp.273-285
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• 2024

With the active utilization of Online Judge (OJ) systems in the field of education, various studies utilizing learner data have emerged. This research proposes a problem recommendation based on a user-based collaborative filtering approach with learner data to support learners in their problem selection. Assistance in learners' problem selection within the OJ system is crucial for enhancing the effectiveness of education as it impacts the learning path. To achieve this, this system identifies learners with similar problem-solving tendencies and utilizes their problem-solving history. The proposed technique has been implemented on an OJ site in the fields of algorithms and programming, operated by the Chungbuk Education Research and Information Institute. The technique's service utility and usability were assessed through expert reviews using the Delphi technique. Additionally, it was piloted with site users, and an analysis of the ratio of correctness revealed approximately a 16% higher submission rate for recommended problems compared to the overall submissions. A survey targeting users who used the recommended problems yielded a 78% response rate, with the majority indicating that the feature was helpful. However, low selection rates of recommended problems and low response rates within the subset of users who used recommended problems highlight the need for future research focusing on improving accessibility, enhancing user feedback collection, and diversifying learner data analysis.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.37 no.1
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• pp.49-56
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• 2024

An automated dynamic structural analysis module stands as a crucial element within a structural integrated mitigation system. This module must deliver prompt real-time responses to enable timely actions, such as evacuation or warnings, in response to the severity posed by the structural system. The finite element method, a widely adopted approximate structural analysis approach globally, owes its popularity in part to its user-friendly nature. However, the computational efficiency and accuracy of results depend on the user-provided finite element mesh, with the number of elements and their quality playing pivotal roles. This paper introduces a computationally efficient adaptive mesh generation scheme that optimally combines the h-method of node movement and the r-method of element division for mesh refinement. Adaptive mesh generation schemes automatically create finite element meshes, and in this case, representative strain values for a given mesh are employed for error estimates. When applied to dynamic problems analyzed in the time domain, meshes need to be modified at each time step, considering a few hundred or thousand steps. The algorithm's specifics are demonstrated through a standard cantilever beam example subjected to a concentrated load at the free end. Additionally, a portal frame example showcases the generation of various robust meshes. These examples illustrate the adaptive algorithm's capability to produce robust meshes, ensuring reasonable accuracy and efficient computing time. Moreover, the study highlights the potential for the scheme's effective application in complex structural dynamic problems, such as those subjected to seismic or erratic wind loads. It also emphasizes its suitability for general nonlinear analysis problems, establishing the versatility and reliability of the proposed adaptive mesh generation scheme.

• Coupled systems mechanics
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• v.13 no.3
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• pp.201-217
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• 2024

This study aims to develop a new model to obtain the minimum area in circular isolated footings with eccentric column taking into account that the surface in contact with the ground works partially in compression, i.e., a part of the contact area of the footing is subject to compression and the other there is no pressure (pressure zero). The new model is formulated from a mathematical approach based on a minimum area, and it is developed by integration to obtain the axial load "P", moment around the X axis "M_x" and moment around the Y axis "M_y" in function of σ_max (available allowable soil pressure) R (radius of the circular footing), α (angle of inclination where the resultant moment appears), y₀ (distance from the center of the footing to the neutral axis measured on the axis where the resultant moment appears). The normal practice in structural engineering is to use the trial and error procedure to obtain the radius and area of the circular footing, and other engineers determine the radius and area of circular footing under biaxial bending supported on elastic soils, but considering a concentric column and the contact area with the ground works completely in compression. Three numerical problems are given to determine the lowest area for circular footings under biaxial bending. Example 1: Column concentric. Example 2: Column eccentric in the direction of the X axis to 1.50 m. Example 3: Column eccentric in the direction of the X axis to 1.50 m and in the direction of the Y axis to 1.50 m. The new model shows a great saving compared to the current model of 44.27% in Example 1, 50.90% in Example 2, 65.04% in Example 3. In this way, the new minimum area model for circular footings will be of great help to engineers when the column is located on the center or edge of the footing.

• Geophysics and Geophysical Exploration
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• v.27 no.2
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• pp.91-107
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• 2024

Single-channel seismic exploration has proven effective in delineating subsurface geological structures using small-scale survey systems. The seismic data acquired through zero- or near-offset methods directly capture subsurface features along the vertical axis, facilitating the construction of corresponding seismic sections. However, substantial noise in single-channel seismic data hampers precise interpretation because of the low signal-to-noise ratio. This study introduces a novel approach that integrate noise reduction and signal enhancement via matrix rank optimization to address this issue. Unlike conventional rank-reduction methods, which retain selected singular values to mitigate random noise, our method optimizes the entire singular value spectrum, thus effectively tackling both random and erratic noises commonly found in environments with low signal-to-noise ratio. Additionally, to enhance the horizontal continuity of seismic events and mitigate signal loss during noise reduction, we introduced an adaptive weighting factor computed from the eigenimage of the seismic section. To access the robustness of the proposed method, we conducted numerical experiments using single-channel Sparker seismic data from the Chukchi Plateau in the Arctic Ocean. The results demonstrated that the seismic sections had significantly improved signal-to-noise ratios and minimal signal loss. These advancements hold promise for enhancing single-channel and high-resolution seismic surveys and aiding in the identification of marine development and submarine geological hazards in domestic coastal areas.

• The Journal of the Acoustical Society of Korea
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• v.43 no.1
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• pp.39-48
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• 2024

A car horn serves a crucial safety role as a means of communication between drivers and a part that alerts pedestrians in advance. While previous studies have utilized finite element method and electric circuit model to simulate and analyze characteristics of the car horns, there remains a lack of research on design methods of a trumpet horn. This paper presents a design approach that predicts the operating frequency based on the acoustic reactance at the throat of the horn, once the vibrating part is determined. We deal with a horn combining both an exponential horn and a waveguide in the acoustic section, and confirm that the acoustic reactance at the horn throat measured by impedance tube experiment agrees well compared with the numerical result obtained using the finite element method. The resonance frequency of the car horn is predicted using the COMSOL Multiphysics finite element numerical analysis model, and the proposed design method is validated by measuring the operating frequency of the designed horn in a sound pressure experiment. As a result, the resonance measured in a semi-anechoic chamber environment by applying a DC voltage of 12 [V] excluding the holder occurs accurately within a few [Hz] of the design operating frequency. This paper discuss the design method of a trumpet horn from the perspective of the horn's acoustic reactance, and is expected to be useful for designing horn systems.