• Journal of the Korean GEO-environmental Society
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• v.10 no.7
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• pp.7-14
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• 2009

The correlation equation empirically proposed to obtain compression indexes has been proposed to conveniently obtain the value using the soil parameter that can be obtained through simple tests when the number of time of consolidation testing is low or the distribution is large but most of the analyzed regions are limited to certain regions abroad or in the country and multiple data were integrated for use in many cases, thus it is not very reasonable to apply it. Therefore, to establish a new design method considering the uncertainty of the ground, it was selected the Kwangyang port area of which the data have been collected recently thus are relatively more reliable as the subject region of the study in order to maximally reduce the uncertainty of test data. After performing the verification of the normality of the consolidation test data obtained from the selected region and the transformation of variables, a prediction formula was proposed through the regression model with the transformed variables and the proposed regression model with transformed variables was compared with existing empirical equations to verify the suitability of the proposed model formula. After analyzing, it was confirmed that the coefficient of determination was increased after the Box-Cox variable transformation, thus the explanatory power was being enhanced and through the root-mean-square-error method, it was confirmed that the proposed model formula showed the most closed value to the test value.

• Journal of the Korea institute for structural maintenance and inspection
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• v.14 no.6
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• pp.171-178
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• 2010

Pipeline structure is one of core underground infrastructure which transports primary sources. Since the almost pipeline structures are placed underground and connected each other complexly, it is difficult to monitor their structural health condition continuously. In order to overcome this limitation of recent monitoring technique, recently, a Ubiquitous Sensor Network (USN) system based on on-line and real-time monitoring system is being developed by the authors' research group. In this study, real-time pipeline health monitoring (PHM) methodology is presented based on electromechanical impedance methods using USN. Two types of damages including loosened bolts and notches are artificially inflicted on the pipeline structures, PZT and MFC sensors that have piezoelectric characteristics are employed to detect these damages. For objective evaluation of pipeline conditions, Damage metric such as Root Mean Square Deviation (RMSD) value was computed from the impedance signals to quantify the level of the damage. Optimal threshold levels for decision making are estimated by generalized extreme value(GEV) based statistical method. Throughout a series of experimental studies, it was reviewed the effectiveness and robustness of proposed PHM system.

• The Journal of the Convergence on Culture Technology
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• v.9 no.4
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• pp.487-494
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• 2023

In this study, performance comparison was performed on R and TensorFlow, which are free deep learning tools. In the experiment, six types of deep neural networks were built using each tool, and the neural networks were trained using the 10-year Korean temperature dataset. The number of nodes in the input layer of the constructed neural network was set to 10, the number of output layers was set to 5, and the hidden layer was set to 5, 10, and 20 to conduct experiments. The dataset includes 3600 temperature data collected from Gangnam-gu, Seoul from March 1, 2013 to March 29, 2023. For performance comparison, the future temperature was predicted for 5 days using the trained neural network, and the root mean square error (RMSE) value was measured using the predicted value and the actual value. Experiment results shows that when there was one hidden layer, the learning error of R was 0.04731176, and TensorFlow was measured at 0.06677193, and when there were two hidden layers, R was measured at 0.04782134 and TensorFlow was measured at 0.05799060. Overall, R was measured to have better performance. We tried to solve the difficulties in tool selection by providing quantitative performance information on the two tools to users who are new to machine learning.

• The Journal of Advanced Prosthodontics
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• v.14 no.2
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• pp.70-77
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• 2022

PURPOSE. This study evaluated screw loosening and 3D crown displacement after cyclic loading of implant-supported incisor crowns cemented with original titanium bases or with three compatible, nonoriginal components. MATERIALS AND METHODS. A total of 32 dental implants were divided into four groups (n = 8 each): Group 1 used original titanium bases, while Groups 2-4 used compatible components. The reverse torque value (RTV) was evaluated prior to and after cyclic loading (1,200,000 cycles). Samples (prior to and after cyclic loading) were scanned with a microcomputed tomography (micro-CT). Preload and postload files were superimposed by 3D inspection software, and 3D crown displacement analysis was performed using root-mean-square (RMS) values. All datasets were analyzed using one-way ANOVA and Tukey's post hoc analysis. RESULTS. Significant variations were observed in the postload RTV, depending on the titanium base brand (P < .001). The mean postload RTVs were significantly higher in Groups 1 and 2 than in the other study groups. While evaluating 3D crown displacement, the lowest mean RMS value was shown in the original Group 1, with the highest RMS value occurring in Group 4. CONCLUSION. Within the limitations of this in vitro study and under the implemented conditions, it was concluded that the manufacturer brand of the titanium base significantly influenced screw loosening following the fatigue test and influenced 3D crown displacement after cyclic loading.

• The Journal of Advanced Prosthodontics
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• v.10 no.3
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• pp.245-251
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• 2018

PURPOSE. To evaluate the accuracy of a model made using the computer-aided design/computer-aided manufacture (CAD/CAM) milling method and 3D printing method and to confirm its applicability as a work model for dental prosthesis production. MATERIALS AND METHODS. First, a natural tooth model (ANA-4, Frasaco, Germany) was scanned using an oral scanner. The obtained scan data were then used as a CAD reference model (CRM), to produce a total of 10 models each, either using the milling method or the 3D printing method. The 20 models were then scanned using a desktop scanner and the CAD test model was formed. The accuracy of the two groups was compared using dedicated software to calculate the root mean square (RMS) value after superimposing CRM and CAD test model (CTM). RESULTS. The RMS value ($152{\pm}52{\mu}m$) of the model manufactured by the milling method was significantly higher than the RMS value ($52{\pm}9{\mu}m$) of the model produced by the 3D printing method. CONCLUSION. The accuracy of the 3D printing method is superior to that of the milling method, but at present, both methods are limited in their application as a work model for prosthesis manufacture.

• Transactions of Materials Processing
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• v.26 no.6
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• pp.341-347
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• 2017

Flexibly-reconfigurable roll forming (FRRF) is a novel sheet metal forming technology conducive to produce multi-curvature surfaces by controlling strain distribution along longitudinal direction. Reconfigurable rollers could be arranged to implement a kind of punch die set. By utilizing these reconfigurable rollers, desired curved surface can be formed. In FRRF process, three-dimensional surface is formed from two-dimensional curve. Thus, it is difficult to predict the forming result. In this study, a regression analysis was suggested to construct a predictive model for a longitudinal curvature of FRRF process. To facilitate investigation, input parameters affecting the longitudinal curvature of FRRF were determined as maximum compression value, curvature radius in the transverse direction, and initial blank width. Three-factor three-level full factorial experimental design was utilized and 27 experiments using FRRF apparatus were performed to obtain sample data of the regression model. Regression analysis was carried out using experimental results as sample data. The model used for regression analysis was a quadratic nonlinear regression model. Determination factor and root mean square root error were calculated to confirm the conformity of this model. Through goodness of fit test, this regression predictive model was verified.

• Journal of the Korean Ceramic Society
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• v.44 no.6 s.301
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• pp.313-318
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• 2007

ITO (Indium-tin oxide) thin films have been prepared by a sol-gel spinning coating method and fired and annealed in the temperature range of $450-600^{\circ}C$. The XRD patterns of the films indicated the main peak of (222) plane and showed higher crystallinity with increasing an annealing temperature. The surface of the ITO thin films were treated with 0.1 N HCl 20% solution at room temperature. The effects of surface treatment on electrical properties and surface morphologies of the ITO films were investigated with the results of sheet resistance and FE-SEM, AFM images. The samples, subsequently treated with acidic solution for 40 sec showed the sheet resistance of $0.982\;k{\Omega}/square$. The surface treatment using acidic solution diminished the RMS (root mean square) value and the residual carbon content of the ITO films. It seemed that the acid-cleaning of the ITO thin films lead to the decrease of surface roughness and sheet resistance.

• KIEE International Transactions on Power Engineering
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• v.3A no.3
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• pp.130-138
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• 2003

This paper presents a discrete wavelet transform approach for determining the beginning and end times of voltage sags. Firstly, investigations in the use of some typical mother wavelets, namely Daubechies, Symlets, Coiflets and Biorthogonal are carried out and the most appropriate mother wavelet is selected. The proposed technique is based on utilizing the maximum value of Dl (at scale 1) coefficients in multiresolution analysis (MRA) based on the discrete wavelet transform. The results are compared with other methods for determining voltage sag duration, such as the Root Mean Square (RMS) voltage and Short Time Fourier Transform (STFT) methods. It is shown that the voltage sag detection technique based on the wavelet transform is a satisfactory and reliable method for detecting voltage sags in power quality disturbance analysis.

• IEMEK Journal of Embedded Systems and Applications
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• v.12 no.2
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• pp.79-88
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• 2017

One of the important applications of activity sensing in the home is energy monitoring. Many previous methodologies for detecting and recognizing household appliances have been proposed. This paper presents an approach that uses an energy metering circuit (EMC) to classify and identify the various electrical devices in home based on root-mean-square (RMS) consumed current value. EMC gathers the RMS current values created by appliance state transition (e.g., on to off) and apparatus operating process. In this paper, an identification algorithm is proposed to detect a change in current levels using the standard deviation of current signals and their average values. In addition, characteristic of the appliance is extracted concerning four feature parameters concerning the number of current levels, the minimum level, the maximum level, and signal-to-noise ratio (SNR) of them. Experiment results validate the reliable performance of the proposed identification method for 11 representative appliances.

• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.9
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• pp.2214-2222
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• 1993

With the use of the NC machine tool, the unmanned production system has been growing recently in the manufacturing field. This there are problems with monitoring adequate tool fracture during the cutting process efficiently. This study was planned and carried out to discover a way of monitoring tool condition in NO-LINE systems during the cutting process. The acquisition of data in cutting force and tool wear has been made in the section examined, to extract the RMS value of the cutting force as specific factors in the cutting process. The fluctuation of the RMS characteristics. From the results, it has been shown that the fluctuation of the RMS values for the cutting force has a close relation to flank wear.