• Journal of the Korea institute for structural maintenance and inspection
• /
• v.26 no.4
• /
• pp.20-29
• /
• 2022

The operational modal analysis (OMA) technique, which extracts the modal parameters of a structural system using ambient vibrations, has been actively developed as a field of structural health monitoring of cable-supported bridges. In this paper, the short and long-term modal parameters of a cable-stayed bridge were evaluated using the acceleration data obtained from the two ambient vibration tests (AVTs) and three years of continuous measurements. A total of 27 vertical modes and 1 lateral mode in the range 0.1 ~ 2.5 Hz were extracted from the high-resolution AVTs which were conducted in the 6th and 19th years after its completion. Existing OMA methods such as Peak-Picking (PP), Eigensystem Realization Algorithm with Data Correlation (ERADC), Frequency Domain Decomposition (FDD) and Time Domain Decomposition (TDD) were applied for modal parameters extraction, and it was confirmed that there was no significant difference between the applied methods. From the correlation analysis between long-term natural frequencies and environmental factors, it was confirmed that temperature change is the dominant factor influencing natural frequency fluctuations. It was revealed that the decreased natural frequencies of the bridge were not due to changes in structural performance and integrity, but to the environmental effects caused by the temperature difference between the two AVTs. In addition, when the TDD technique is applied, the accuracy of extracted mode shapes is improved by adding a proposed algorithm that normalizes the sequence so that the autocorrelations at zero lag equal 1.

• Journal of Software Assessment and Valuation
• /
• v.16 no.2
• /
• pp.99-107
• /
• 2020

An underground integrated map is being built for underground safety management and is being updated periodically. The map update proceeds with the procedure of deleting all previously stored objects and saving newly entered objects. However, even unchanged objects are repeatedly stored, deleted, and stored. That causes the delay of the update time. In this study, in order to shorten the update time of the integrated map, an updated object and an unupdated object are separated, and only updated objects are reflected in the underground integrated map, and a system implementing this technology is described. For the updated object, an object comparison method using the center point of the object is used, and a quad tree is used to improve the search speed. The types of updated objects are classified into addition and deletion using the shape of the object, and change using its attributes. The proposed system consists of update object detection, extraction, conversion, storage, and history management modules. This system has the advantage of being able to update the integrated map about four times faster than the existing method based on the data used in the experiment, and has the advantage that it can be applied to both ground and underground facilities.

• Journal of the Korean Society of Radiology
• /
• v.16 no.6
• /
• pp.687-695
• /
• 2022

To find a 3D printer material that can replace lead used as a shield for high-energy electron beam treatment, the shielding composites were simulated by using MCNP6 programs. The Percent Depth Dose (PDD), Flatness, and Symmetry of linear accelerators emitting high-energy electron beams were measured, and the linear accelerator was compared with MCNP6 after simulation, confirming that the source term between the actual measurement and simulation was consistent. By simulating the lead shield, the appropriate thickness of the lead shield capable of shielding 95% or more of the absorbed dose was selected. Based on the absorption dose data for lead shield with a thickness of 3 mm, the shielding performance was analyzed by simulating 1, 5, 10, and 15 mm thicknesses of ABS+W (10%), ABS+Bi (10%), and PLA+Fe (10%). Each prototype was manufactured with a 3D printer, measured and analyzed under the same conditions as in the simulation, and found that when ABS+W (10%) material was formed to have a thickness of at least 10mm, it had a shielding performance that could replace lead with a thickness of 3mm. The surface morphology and atomic composition of the ABS+W (10%) material were evaluated using a scanning electron microscope (SEM) and an energy dispersive X-ray spectrometer (EDS). From these results, it was confirmed that replacing the commercialized lead shield with ABS+W (10%) material not only produces a shielding effect such as lead, but also can be customized to patients using a 3D printer, which can be very useful for high-energy electron beam treatment.

• Journal of Korean Society of Coastal and Ocean Engineers
• /
• v.34 no.1
• /
• pp.1-10
• /
• 2022

In this study, the two horizontal shroud tidal current energy converter, which can generate power even under low flow speed conditions, was developed. In order to determine the shape of the shroud system, a three-dimensional numerical simulation test was conducted, and a 1/6 scale down model was made to perform a hydraulic model experiment. The hydraulic model experiment was performed under four flow conditions, and the flow speed, torque, and RPM were measured for each experimental case. As a result of the numerical simulation test, it was found that the flow speeds passing through the nozzle were increased by about 2~3 times in the cylinder, and when the extension ratio was 2:1, the highest flow speed was shown. In addition, it was found that the flow speeds increased 2.8 times when the diameter ratio between the nozzle and the cylinder was 1.5:1. Meanwhile, as a result of the hydraulic model experiment, it was found that when the tip speed ratio was between 1.75 and 2, the power coefficient was 0.32 to 0.34.

• Journal of the Korea Computer Graphics Society
• /
• v.28 no.1
• /
• pp.1-9
• /
• 2022

Non-small cell lung cancer (NSCLC) accounts for a high proportion of 85% among all lung cancer and has a significantly higher mortality rate (22.7%) compared to other cancers. Therefore, it is very important to predict the prognosis after surgery in patients with non-small cell lung cancer. In this study, the types of preoperative chest CT image patches for non-small cell lung cancer patients with tumor as a region of interest are diversified into five types according to tumor-related information, and performance of single classifier model, ensemble classifier model with soft-voting method, and ensemble classifier model using 3 input channels for combination of three different patches using pre-trained ResNet and EfficientNet CNN networks are analyzed through misclassification cases and Grad-CAM visualization. As a result of the experiment, the ResNet152 single model and the EfficientNet-b7 single model trained on the peritumoral patch showed accuracy of 87.93% and 81.03%, respectively. In addition, ResNet152 ensemble model using the image, peritumoral, and shape-focused intratumoral patches which were placed in each input channels showed stable performance with an accuracy of 87.93%. Also, EfficientNet-b7 ensemble classifier model with soft-voting method using the image and peritumoral patches showed accuracy of 84.48%.

• Composites Research
• /
• v.36 no.1
• /
• pp.48-52
• /
• 2023

Fiber-reinforced composites have anisotropic material properties, so the mechanical properties of composite structures can vary depending on the stacking sequence. Therefore, it is essential to design the proper stacking sequence of composite structures according to the functional requirements. However, depending on the manufacturing condition or the shape of the structure, there are many cases where the designed stacking angle is out of range, which can affect structural performance. Accordingly, it is important to analyze the stacking angle in order to confirm that the composite structure is correctly fabricated as designed. In this study, the stacking angle was predicted from real cross-sectional images of fiber-reinforced composites using convolutional neural network (CNN)-based deep learning. Carbon fiber-reinforced composite specimens with several stacking angles were fabricated and their cross-sections were photographed on a micro-scale using an optical microscope. The training was performed for a CNN-based deep learning model using the cross-sectional image data of the composite specimens. As a result, the stacking angle can be predicted from the actual cross-sectional image of the fiber-reinforced composite with high accuracy.

• Journal of Korean Society of Coastal and Ocean Engineers
• /
• v.34 no.6
• /
• pp.266-274
• /
• 2022

In this study, a smoothing method was applied to improve the accuracy of peak wave period estimation using the water surface elevation observed from the Oceanographic and Meteorological Observation Tower located on the west coast of the Korean Peninsula. Validation of the application of the smoothing method was per- formed using variance of the surface elevation and total amount wave energy, and then the effect on the application of smoothing was analyzed. As a result of the analysis, the correlation coefficient between variance of the surface elevation and total amount wave energy was 0.9994, confirming that there was no problem in applying the method. Thereafter, as a result of reviewing the effect of smoothing, it was found to be reduced by about 4 times compared to the confidence interval of the existing estimated spectrum, confirming that the accuracy of the estimated peak wave period was improved. It was found that there was a statistically significant difference in proba- bility density between 4 and 6 seconds due to the smoothing application. In addition, for optimal smoothing, the appropriate number of smoothings according to the significant wave height range was calculated using a statistical technique, and the number of smoothings was found to increase due to the unstable spectral shape as the significant wave height decreased.

• Journal of Intelligence and Information Systems
• /
• v.29 no.3
• /
• pp.125-144
• /
• 2023

Recently, the use of Large Language Models (LLMs) such as ChatGPT has been increasing in various fields such as interactive commerce and mobile financial services. However, LMMs, which are mainly created by learning existing documents, can also learn various human biases inherent in documents. Nevertheless, there have been few comparative studies on the aspects of bias and discrimination in LLMs. The purpose of this study is to examine the existence and extent of nine types of discrimination (Age, Disability status, Gender identity, Nationality, Physical appearance, Race ethnicity, Religion, Socio-economic status, Sexual orientation) in LLMs and suggest ways to improve them. For this purpose, we utilized BBQ (Bias Benchmark for QA), a tool for identifying discrimination, to compare three large-scale language models including ChatGPT, GPT-3, and Bing Chat. As a result of the evaluation, a large number of discriminatory responses were observed in the mega-language models, and the patterns differed depending on the mega-language model. In particular, problems were exposed in elder discrimination and disability discrimination, which are not traditional AI ethics issues such as sexism, racism, and economic inequality, and a new perspective on AI ethics was found. Based on the results of the comparison, this paper describes how to improve and develop large-scale language models in the future.

• Korean Journal of Construction Engineering and Management
• /
• v.24 no.5
• /
• pp.52-62
• /
• 2023

The objective of this study is to propose an automated algorithm for precise cutting length of slab rebar complying with regulations such as anchorage length, standard hooks, and lapping length. This algorithm aims to improve the traditional manual quantity take-off process typically outsourced by external contractors. By providing accurate rebar quantity data at BBS(Bar Bending Schedule) level from the bidding phase, uncertainty in quantity take-off can be eliminated and reliance on out-sourcing reduced. In addition, the algorithm allows for early determination of precise quantities, enabling construction firms to preapre competitive and optimized bids, leading to increased profit margins during contract negotiations. The proposed algorithm not only streamlines redundant tasks across various processes, including estimating, budgeting, and BBS generation but also offers flexibility in handling post-contract structural drawing changes. In particular, the proposed algorithm, when combined with BIM, can solve the technical problems of using BIM in the early phases of construction, and the algorithm's formulas and shape codes that built as REVIT-based family files, can help saving time and manpower.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
• /
• v.7 no.11
• /
• pp.447-455
• /
• 2017

At the modern industry, the composite material has been widely used. Particularly, the material of carbon fiber reinforced plastic hardened with resin on the basis of fiber is excellent. As the specific strength and rigidity are also superior, it receives attention as the light material. Among these materials, the carbon fiber reinforced plastic using carbon fiber has the superior mechanical property different from another fiber. So, it is utilized in vehicle and airplane at which high strength and light weight are needed at the same time. In this paper, the tensile property due to the fiber design is investigated through the analysis study with CT specimen composed of carbon plastic reinforced plastic. At the stress analysis of CFRP composite material with hole, the fracture trend at the tensile environment is examined. Also, it is shown that the lowest stress value happens and the deformation energy of the pre-crack becomes lowest at the analysis model composed of the stacking angle of 60° through the result due to the stacking angle. On the basis of this study result, it is thought to apply the foundation data to anticipate the fracture configuration at the structure applied with the practical experiment.