• Journal of the Korean Society of Industry Convergence
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• v.25 no.6_2
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• pp.1119-1125
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• 2022

The depletion of resources and waste disposal caused by the continuous development of industry have emphasized the need to reduce consumption and production, recycle and reuse, and the importance of remanufacturing has increased in recent years. The spindle part of the aging planner miller, which is currently being remanufactured, is one of the factors that has the greatest impact on the performance of the machine tool. When designing the spindle part of the spindle shaft, there are considerations such as the configuration size bearing performance of the main shaft, but the diameter of the main shaft, the dangerous speed bearing, and the arrangement that affect the machining accuracy should be basically considered. As such, various studies have been conducted on the design of machine tool spindle spindles, but research on the reverse engineering of existing aging machine tool spindle spindles is poor. Reverse engineering is designing in the direction of improving performance by extracting specifications from already finished products, and first scanning the reverse engineered object through a 3D scanner, 3D modeling is performed based on the collected data, and then the process of deriving improvement plans by reverberating to improve performance by identifying wear and damage conditions is followed. Therefore, in this study, the purpose of this study is to provide data on reverse engineering by deriving improvement plans through optimal design for the bearing position of the aging planar Miller spindle spindle using central composite programming.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.12
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• pp.1709-1715
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• 2021

In order to accurately extract the necessary text from the web page, the method of specifying the tag and style attributes where the main contents exist to the web crawler has a problem in that the logic for extracting the main contents. This method needs to be modified whenever the web page configuration is changed. In order to solve this problem, the method of extracting the text by analyzing the frequency of appearance of the text proposed in the previous study had a limitation in that the performance deviation was large depending on the collection channel of the web page. Therefore, in this paper, we proposed a method of extracting texts with high accuracy from various collection channels by analyzing not only the frequency of appearance of text but also parent tag paths of text nodes extracted from the DOM tree of web pages.

• Smart Structures and Systems
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• v.31 no.4
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• pp.335-349
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• 2023

Bridges constantly undergo deterioration and damage, the most common ones being concrete damage and exposed rebar. Periodic inspection of bridges to identify damages can aid in their quick remediation. Likewise, identifying components can provide context for damage assessment and help gauge a bridge's state of interaction with its surroundings. Current inspection techniques rely on manual site visits, which can be time-consuming and costly. More recently, robotic inspection assisted by autonomous data analytics based on Computer Vision (CV) and Artificial Intelligence (AI) has been viewed as a suitable alternative to manual inspection because of its efficiency and accuracy. To aid research in this avenue, this study performs a comparative assessment of different architectures, loss functions, and ensembling strategies for the autonomous segmentation of bridge components and damages. The experiments lead to several interesting discoveries. Nested Reg-UNet architecture is found to outperform five other state-of-the-art architectures in both damage and component segmentation tasks. The architecture is built by combining a Nested UNet style dense configuration with a pretrained RegNet encoder. In terms of the mean Intersection over Union (mIoU) metric, the Nested Reg-UNet architecture provides an improvement of 2.86% on the damage segmentation task and 1.66% on the component segmentation task compared to the state-of-the-art UNet architecture. Furthermore, it is demonstrated that incorporating the Lovasz-Softmax loss function to counter class imbalance can boost performance by 3.44% in the component segmentation task over the most employed alternative, weighted Cross Entropy (wCE). Finally, weighted softmax ensembling is found to be quite effective when used synchronously with the Nested Reg-UNet architecture by providing mIoU improvement of 0.74% in the component segmentation task and 1.14% in the damage segmentation task over a single-architecture baseline. Overall, the best mIoU of 92.50% for the component segmentation task and 84.19% for the damage segmentation task validate the feasibility of these techniques for autonomous bridge component and damage segmentation using RGB images.

• Journal of Advanced Navigation Technology
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• v.27 no.4
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• pp.423-428
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• 2023

In the missile actuator system, the time and position of the wings of the drive device are very important factors in the initial maneuver of the missile, and therefore, the missile actuator device must be inspected while ensuring the accuracy and real-time of motion collection data of the actuator. In this study, the difference between the design and implementation method for checking the existing actuator device and the design implementation method of the actuator device through the DAQ(Data Acquisition) device is compared, and the difference in data collection amount and real-time data collection performance is compared and tested, and the data shown through actual tests are compared. is converted into a graph, the actuator waveform is compared and analyzed, and based on the analyzed data, DAQ device inspection configuration that guarantees real-time response speed and stability during inspection of existing actuators and DAQ devices is proposed.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.3
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• pp.449-458
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• 2023

Many people think that sign language is only for people who are deaf and cannot speak, but of course it is necessary for people who want to talk with them. One of the biggest challenges in ASL(American Sign Language) alphabet recognition is the high inter-class similarities and high intra-class variance. In this paper, we proposed an architecture that can overcome these two problems, which performs similarity learning to reduces inter-class similarities and intra-class variance between images. The proposed architecture consists of the same convolutional neural network with a double configuration that shares parameters (weights and biases) and also applies the Keras API to reduce similarity learning and variance through this pathway. The similarity learning results the use of the dual CNN shows that the accuracy is improved by reducing the similarity and variability between classes by not including the poor results of the two classes.

• Journal of the Korean Geotechnical Society
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• v.22 no.3
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• pp.37-43
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• 2006

An analytical solution method capable of determining the geometric configuration and developed tensile forces of mooring lines associated with fixed plate/pile or drag anchors has been developed. The solution method, satisfying complete equilibrium conditions, is capable of analyzing multi-segmented mooring lines that can consist of either chains, cables, or synthetic wires embedded in layered seafloor soils. The solution method utilizes a systematic iterative search method based on specific boundary conditions. This paper describes the principles associated with the development of the solution for the mooring line analysis. Comparisons of predictions with results from a series of field tests of mooring lines on various types of drag anchors are also described. Comparisons include the tension in anchor, the length of mooring line on the bottom, and the angle of mooring line at the water surface buoy. The results indicate that the analytical solution method is capable of predicting the behavior of mooring lines with high degree of accuracy.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.2
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• pp.325-332
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• 2022

In this study, real-time character navigation using AR lens developed by Nreal is developed. Real-time character navigation is not possible with general marker-based AR because NPC characters must guide while moving in an unspecified space. To replace this, a markerless AR system was developed using Digital Twin technology. Existing markerless AR is operated based on hardware such as GPS, gyroscope, and magnetic sensor, so location accuracy is low and processing time in the system is long, which results low reliability in real-time AR environment. In order to solve this problem, using the SLAM technique to construct a space into a 3D object and to construct a markerless AR based on point location, AR can be implemented without any hardware intervention in a real-time AR environment. This real-time AR environment configuration made it possible to implement a navigation system using characters in tourist attractions such as Suncheon Bay Garden and Suncheon Drama Filming Site.

• Journal of Korean Neurosurgical Society
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• v.66 no.4
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• pp.382-392
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• 2023

Objective : The use of indocyanine green videoangiography (ICG-VA) to assess blood flow in the brain during cerebrovascular surgery has been increasing. Clinical studies on ICG-VA have predominantly focused on qualitative analysis. However, quantitative analysis numerical modelling for time profiling enables a more accurate evaluation of blood flow kinetics. In this study, we established a multiple exponential modified Gaussian (multi-EMG) model for quantitative ICG-VA to understand accurately the status of cerebral hemodynamics. Methods : We obtained clinical data of cerebral blood flow acquired the quantitative analysis ICG-VA during cerebrovascular surgery. Varied asymmetric peak functions were compared to find the most matching function form with clinical data by using a nonlinear regression algorithm. To verify the result of the nonlinear regression, the mode function was applied to various types of data. Results : The proposed multi-EMG model is well fitted to the clinical data. Because the primary parameters-growth and decay rates, and peak center and heights-of the model are characteristics of model function, they provide accurate reference values for assessing cerebral hemodynamics in various conditions. In addition, the primary parameters can be estimated on the curves with partially missed data. The accuracy of the model estimation was verified by a repeated curve fitting method using manipulation of missing data. Conclusion : The multi-EMG model can possibly serve as a universal model for cerebral hemodynamics in a comparison with other asymmetric peak functions. According to the results, the model can be helpful for clinical research assessment of cerebrovascular hemodynamics in a clinical setting.

• Computers and Concrete
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• v.32 no.2
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• pp.149-163
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• 2023

One of the main design parameters traditionally utilized in projects of geotechnical engineering is the uniaxial compressive strength. The present paper employed three artificial intelligence methods, i.e., the stochastic fractal search (SFS), the multi-verse optimization (MVO), and the vortex search algorithm (VSA), in order to determine the compressive strength of concrete (CSC). For the same reason, 1030 concrete specimens were subjected to compressive strength tests. According to the obtained laboratory results, the fly ash, cement, water, slag, coarse aggregates, fine aggregates, and SP were subjected to tests as the input parameters of the model in order to decide the optimum input configuration for the estimation of the compressive strength. The performance was evaluated by employing three criteria, i.e., the root mean square error (RMSE), mean absolute error (MAE), and the determination coefficient (R²). The evaluation of the error criteria and the determination coefficient obtained from the above three techniques indicates that the SFS-MLP technique outperformed the MVO-MLP and VSA-MLP methods. The developed artificial neural network models exhibit higher amounts of errors and lower correlation coefficients in comparison with other models. Nonetheless, the use of the stochastic fractal search algorithm has resulted in considerable enhancement in precision and accuracy of the evaluations conducted through the artificial neural network and has enhanced its performance. According to the results, the utilized SFS-MLP technique showed a better performance in the estimation of the compressive strength of concrete (R²=0.99932 and 0.99942, and RMSE=0.32611 and 0.24922). The novelty of our study is the use of a large dataset composed of 1030 entries and optimization of the learning scheme of the neural prediction model via a data distribution of a 20:80 testing-to-training ratio.

• Journal of the Korean Recycled Construction Resources Institute
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• v.11 no.4
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• pp.467-475
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• 2023

To ensure the safety of the pipeline against large deformation of the pipeline during lowering construction, the analysis for pipeline becomes emphasized. The FE analysis has a lower efficiency at calculating time, while it could be obtained high accuracy. In this paper, a reasonable analytical model for analysis of pipeline is proposed during lowering-in. This analytical model is partitioned considering the geometrical characteristics and modeled as two parameters Beam On Elastic Foundation and Euler-Bernoulli beam considering the boundary condition. This takes into account the pipeline-soil interaction and the axial forces acting on the pipeline. Previous model can only be applied to standardized conditions, whereas the proposed model defined as Segmented Pipeline Model can be considered for the majority of construction conditions occurred during lowering-in. In addition, minimized assumptions and segmented elements lead to improve the convenience and applicability of modeling. Nevertheless, the model shows accurate results compared to the FE model. Accordingly, it is expected that it will be used efficiently for configuration management as well as safety assessment of pipeline during lowering-in.