• Steel and Composite Structures
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• v.38 no.2
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• pp.151-164
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• 2021

During the pipe forming process, a steel plate undergoes inelastic behavior multiple times under a load condition repeating tension and compression in the circumferential direction. It derives local reduction or increase of yield strength within the thickness of steel pipes by the plastic hardening and Bauschinger effect. In this study, a combined hardening model is proposed to effectively predict variations of yield strength in the circumferential direction of API-X65 and X70 steel pipes with relatively low t/D ratio during the forming process, which is expected to experience accumulated plastic strain of 2~3%, the typical Lüder band range in a low-carbon steel. Cyclic tensile tests of API-X65 and X70 steels were performed, and the parameters of the proposed model for the steels were calibrated using the test results. Bending-flattening tests to simulate repeated tension and compression during pipe forming were followed for API-X65 and X70 steels, and the results were compared with those by the proposed model and Zou et al. (2016), in order to verify the process of material model calibration based on tension-compression cyclic test, and the accuracy of the proposed model. Finally, parametric analysis for the yield strength of the steel plate in the circumferential direction of UOE pipe was conducted to investigate the effects of t/D and expansion ratios after O-forming on the yield strength. The results confirmed that the model by Zou et al. (2016) underestimated the yield strength of steel pipe with relatively low t/D ratio, and the parametric analysis showed that the t/D and expansion ratio have a significant impact on the strength of steel pipe.

• Journal of Advanced Navigation Technology
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• v.24 no.6
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• pp.540-548
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• 2020

In this paper, the performances of virtual reference station (VRS) and flächen korrektur parameter (FKP) based Network real time kinematics (RTK) according to baseline length were compared and analyzed. We applied the VRS and FKP corrections for each baseline length obtained from National Geographic Information Institute Network RTK services to an FKP-supported commercial receiver and analyzed the RTK results in the range and position domains. In the case of VRS, RTK performance was degraded due to the spatial error, which increase in proportion of the baseline length. On the other hand, FKP compensates for spatial errors by using the gradients of dispersive and non-dispersive errors, so it showed stable RTK performance compared to VRS even if the baseline length increases up to 130 km. However, in the case of long baseline of 150 km or more, integer ambiguities were incorrectly fixed due to the decrease in the performance of the FKP corrections.

• Journal of Microbiology and Biotechnology
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• v.31 no.5
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• pp.705-709
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• 2021

Porphyromonas gingivalis (P. gingivalis) is a major bacterial pathogen that causes periodontitis, a chronic inflammatory disease of tissues around the teeth. Periodontitis is known to be related to other diseases, such as oral cancer, Alzheimer's disease, and rheumatism. Thus, a precise and sensitive test to detect P. gingivalis is necessary for the early diagnosis of periodontitis. The objective of this study was to optimize a rapid visual detection system for P. gingivalis. First, we performed a visual membrane immunoassay using 3,3',5,5'-tetramethylbenzidine (TMB; blue) and coating and detection antibodies that could bind to the host laboratory strain, ATCC 33277. Antibodies against the P. gingivalis surface adhesion molecules RgpB (arginine proteinase) and Kgp (lysine proteinase) were determined to be the most specific coating and detection antibodies, respectively. Using these two selected antibodies, the streptavidin-horseradish peroxidase (HRP) reaction was performed using a nitrocellulose membrane and visualized with a detection range of 10³-10⁵ bacterial cells/ml following incubation for 15 min. These selected conditions were applied to test other oral bacteria, and the results showed that P. gingivalis could be detected without cross-reactivity to other bacteria, including Streptococcus mutans and Escherichia fergusonii. Furthermore, three clinical strains of P. gingivalis, KCOM 2880, KCOM 2803, and KCOM 3190, were also recognized using this optimized enzyme immunoassay (EIA) system. To conclude, we established optimized conditions for P. gingivalis detection with specificity, accuracy, and sensitivity. These results could be utilized to manufacture economical and rapid detection kits for P. gingivalis.

• Design & Manufacturing
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• v.15 no.4
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• pp.24-31
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• 2021

In this study, an artificial neural network model was constructed to convert CAE analysis data into similar experimental data. In the analysis and experiment, the injection molding data for 50 conditions were acquired through the design of experiment and random selection method. The injection molding conditions and the weight, height, and diameter of the product derived from CAE results were used as the input parameters for learning of the convert model. Also the product qualities of experimental results were used as the output parameters for learning of the convert model. The accuracy of the convert model showed RMSE values of 0.06g, 0.03mm, and 0.03mm in weight, height, and diameter, respectively. As the next step, additional randomly selected conditions were created and CAE analysis was performed. Then, the additional CAE analysis data were converted to similar experimental data through the conversion model. An artificial neural network model was constructed to predict the quality of injection molded product by using converted similar experimental data and injection molding experiment data. The injection molding conditions were used as input parameters for learning of the predicted model and weight, height, and diameter of the product were used as output parameters for learning. As a result of evaluating the performance of the prediction model, the predicted weight, height, and diameter showed RMSE values of 0.11g, 0.03mm, and 0.05mm and in terms of quality criteria of the target product, all of them showed accurate results satisfying the criteria range.

• Journal of the Korea Convergence Society
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• v.13 no.4
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• pp.137-145
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• 2022

The usability evaluation of the remote fluid monitoring device, which was introduced to reduce the work of nurses and increase the efficiency, was performed due to the expansion of the non-face-to-face medical system. Remote fluid monitoring is a fusion of various technologies such as fluid measurement and analysis, error correction technology, and transmission technology. The range of use by users, the information they want to obtain, and the control device, etc. are wide, and the factors that evaluate the product are also diverse. Therefore, it is difficult to improve the product through evaluation. In this study, a quantitative index was developed to help improve the product for commercialization by conducting 20 usability evaluations in three areas of product stability, operability, and satisfaction with the remote sap monitoring system device. It was performed through infrared and load cell-type sap monitoring devices. In terms of stability, there was a difference in installation work such as fixing the pole of the device, and high satisfaction was shown for operability and accuracy. In terms of product satisfaction, the satisfaction of load cell devices was generally high.

• Journal of the Economic Geographical Society of Korea
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• v.25 no.1
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• pp.171-181
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• 2022

The real estate price index plays key roles as quantitative data in real estate market analysis. International organizations including OECD publish the real estate price indexes by country, and the Korea Real Estate Board announces metropolitan-level and municipal-level indexes. However, when the index is set on the smaller spatial unit level than metropolitan and municipal-level, problems occur: missing values. As the spatial scope is narrowed down, there are cases where there are few or no transactions depending on the unit period, which lead index calculation difficult or even impossible. This study suggests a supervised learning-based machine learning model to compensate for missing values that may occur due to no transaction in a specific range and period. The models proposed in our research verify the accuracy of predicting the existing values and missing values.

• Journal of Radiation Protection and Research
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• v.47 no.1
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• pp.8-15
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• 2022

Background: We developed a machine vision technology program that tracks patients' real-time breathing and automatically analyzes their breathing patterns. Materials and Methods: To evaluate its potential for clinical application, the image tracking performance and accuracy of the program were analyzed using a respiratory motion phantom. Changes in the stability and regularity of breathing were observed in healthy adult volunteers according to whether the breathing pattern mirrored the breathing guidance. Results and Discussion: Displacement within a few millimeters was observed in real-time with a clear resolution, and the image tracking ability was excellent. This result was consistent even in the sections where breathing patterns changed rapidly. In addition, the respiratory gating method that reflected the individual breathing patterns improved breathing stability and regularity in all volunteers. Conclusion: The findings of this study suggest that this technology can be used to set the appropriate window and the range of internal target volume by reflecting the patient's breathing pattern during radiotherapy planning. However, further studies in clinical populations are required to validate this technology.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.4
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• pp.157-162
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• 2022

Today, most data is stored in a database (DB). In the DB environment, the users requests the DB to find the data they wants. Similarity Query has predicate that explained by a similarity. However, in the process of processing the similarity query, it is difficult to use an index that can reduce the range of processed records, so the cost of calculating the similarity for all records in the table is high each time. To solve this problem, this paper defines a lightweight similarity function. The lightweight similarity function has lower data filtering accuracy than the similarity function, but consumes less cost than the similarity function. We present a method for reducing similarity query processing cost by using the lightweight similarity function features. Then, Chebyshev distance is presented as a lightweight similarity function to the Euclidean distance function, and the processing cost of a query using the existing similarity function and a query using the lightweight similarity function is compared. And through experiments, it is confirmed that the similarity query processing cost is reduced when Chebyshev distance is applied as a lightweight similarity function for Euclidean similarity.

• Journal of IKEEE
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• v.26 no.2
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• pp.150-159
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• 2022

In this paper, we propose a physics simulation for augmented reality (AR) billiards content. The characteristics of the physics simulation for the proposed AR billiards content are as follows. First, physical equations are derived by calculating the force and moment of inertia applied to the billiards ball to realize the motion of the billiards ball similar to the real one in the AR environment. Then, we determine the velocity and angular velocity of the virtual billiards ball associated with the rotation of the virtual billiards ball with respect to the impact point. Second, using some vectors such as incidnet vector, normal vector, reflection vector, the trajectory of the virtual billiards ball would be implement. these equations are applied to AR environment so that AR billiards content could be implement. This physics simulation allows users to feel like the real world using a virtual pool table and induce them to interact with the real environment. As a result of the experiment, the accuracy range between the path of the real billiards ball and the path of the virtual billiards ball was calculated to be 97.75% to 99.11%. Therefore, it was determined that the performance of the physics simulation for the AR billiards content proposed in this paper performs similarly to the path of the real billiards ball.

• Journal of Internet of Things and Convergence
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• v.8 no.5
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• pp.127-132
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• 2022

As the IoT technology is more developed, it is more important for the accuracy of IoT data. Since the IoT data supports a different formats and protocols, it is often happened that the IoT system is failed or the incorrect data is generated with the unreliable IoT devices(sensor, actuator). Because the abnormality of IoT device or the user situation is not detected correctly, this problem makes the user to be unsatisfied with the IoT system. This study proposes the decision methodology of IoT data consistency whether the IoT data is generated in normal range or not by using the mathematical functions('gradient descent function' and 'linear regression function'). It may be concluded that the gradient function method is suitable for the IoT data which the 'increasing velocity' is related with the next generated pattern(eg. sensor devices), the linear regression function method is suitable for the IoT data which the 'the difference from linear regression function' is related with the next generated pattern in case the data has a linear pattern(eg. water meter, electric meter).