• Applied Chemistry for Engineering
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• v.32 no.5
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• pp.574-580
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• 2021

The main goal of this study was to find an optimal surfactant mixture composition for the development of the best performing cleansing products. Three different surfactants including sodium cocoyl alaninate (SCoA), cocamidopropyl betaine (CPB), and decyl glucoside (DG) were selected, which showed excellent properties in detergency, foaming height, and contamination rate through preliminary experiments. The experiments by simplex centroid design matrix for surfactant mixtures were performed, and the regression analysis was conducted with the experimental data. Surface response model equations, which is statistically significant (p < 0.05), were obtained. The optimal composition of the surfactant mixture was also determined as SCoA (0.22), CPB (0.78), and DG(0.00) from simultaneous optimization of three response variables.

• The Journal of Korean Academy of Prosthodontics
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• v.60 no.3
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• pp.246-253
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• 2022

Flabby tissue is not rare for denture wearers. Mucostatic impression technique is necessary due to compromised retention and stability of denture resulting from distortion of mobile flabby tissue. In this report, individual tray was fabricated by model-scanning and 3D printing treatment denture. And then, mucostatic impression for flabby tissue was obtained by using individual tray modified with window technique. Definitive denture was fabricated based on information of treatment denture including incisal pontic arrangement, jaw relationship and occlusion.

• Journal of the Korea Society of Computer and Information
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• v.27 no.9
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• pp.41-47
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• 2022

In this paper, we propose a new and simple self-supervised learning method that predicts the middle image of a face image sequence for automatic expression recognition. Automatic facial expression recognition can achieve high performance through deep learning methods, however, generally requires a expensive large data set. The size of the data set and the performance of the algorithm are tend to be proportional. The proposed method learns latent deep representation of a face through self-supervised learning using an existing dataset without constructing an additional dataset. Then it transfers the learned parameter to new facial expression reorganization model for improving the performance of automatic expression recognition. The proposed method showed high performance improvement for two datasets, CK+ and AFEW 8.0, and showed that the proposed method can achieve a great effect.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.4
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• pp.171-181
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• 2013

Recently, ground penetrating radar(GPR) has been widely used in detecting metallic and nonmetallic buried landmines and a number of related researches have been reported. A novel preprocessing method is proposed in this paper to flag potential locations of buried mine-like objects from GPR array measurements. GPR operates by measuring the reflection of an electromagnetic pulse from discontinuities in subsurface dielectric properties. As the GPR pulse propagates in the geologic medium, it suffers nonlinear attenuation as the result of absorption and dispersion, besides spherical divergence. In the proposed algorithm, a logarithmic transformed regression model which successfully represents the time-varying signal amplitude of the GPR data is estimated at first. Then, background signals may be densely distributed near the regression model and candidate signals of targets may be far away from the regression model in the time-amplitude space. Based on the observation, GPR signals are decomposed into candidate signals of targets and background signals using residuals computed from the estimated value by regression and the measurement of GPR. Candidate signals which may contain target signals and noise signals need to be refined. Finally, targets are detected through the refinement of candidate signals based on geometric signatures of mine-like objects. Our algorithm is evaluated using real GPR data obtained from indoor controlled environment and the experimental results demonstrate remarkable performance of our mine-like object detection method.

• The Journal of Korean Academy of Prosthodontics
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• v.56 no.1
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• pp.8-16
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• 2018

Purpose: The purpose of this study is to evaluate the accuracy of surgical stent according to the supported type. Materials and methods: 5 sets of dental models which have tooth supported edentulous area and tooth-tissue supported edentulous area were made. Dental model were scanned with model scanner, and CBCT was taken. CT data and model scan data were overlapped using In2Guide software, implant were virtually planned in the software. Surgical stents are fabricated by 3D printing. The implant fixture were installed using the surgical stent, CBCT were retaken. CBCT before surgery and after surgery were overlapped, and the differences (angle difference, coronal difference, apical difference) were evaluated using statistical analysis. Results: In the assessment of the accuracy of surgical guides according to arch type, there are no statistically significant differences between maxilla and mandible. In the case of support type, tooth supported stents showed lower angle difference and length difference than tooth-tissue supported stents, which are statistically significant. Conclusion: Arch type does not affect the accuracy of surgical stents. But tooth support stents are more accurate than tooth-tissue support stents in the case of angle and length difference.

• Composites Research
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• v.32 no.5
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• pp.216-221
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• 2019

Piecewise integrated composite (PIC) beam has different stacking sequences for several regions with respect to their superior load-resisting capabilities. On the interest of current research is to improve bending characteristics of PIC beam, with assigning specific stacking sequence to a specific region with the help of machine learning techniques. 240 elements of from the FE model were chosen to be reference points. Preliminary FE analysis revealed triaxialities at those regularly distributed reference points to obtain learning data creation of machine learning. Triaxiality values catagorise the type of loading i.e. tension, compression or shear. Machine learning model was formulated by learning data as well as hyperparameters and proper load fidelity was suggested by tuned values of hyperparameters, however, comparatively higher nonlinearity intensive region, such as side face of the beam showed poor load fidelity. Therefore, irregular distribution of reference points, i.e., dense reference points were distributed in the severe changes of loading, on the contrary, coarse distribution for rare changes of loading, was prepared for machine learning model. FE model with irregularly distributed reference points showed better load fidelity compared to the results from the model with regular distribution of reference points.

• Journal of the Korea institute for structural maintenance and inspection
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• v.24 no.5
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• pp.45-52
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• 2020

An open-spandrel arch bridges, which consists of slab deck, arch rib, and vertical members, shows a various level of moment and axial forces according to the supporting boundary condition of arch rib and vehicle speeds. Also, the definition of impact factor accepts any kind of response parameters, not only displacement response at slab deck. The present study considers concrete open-spandrel arch bridges constrained with fixed conditions at the ends of arch rib and investigates the impact factor variation due to moving load speeds, response parameters, measuring locations, and vertical member spacing ratio of the bridges. The results of Reference model show that the impact factor is biggest when the reactive moment resulted at the vehicle-inducing opposite end of the arch rib is applied. The peak impact factor is a similar level obtained for the middle of the span adjacent to the slab deck center, but it is 19% higher than the peak impact factor calculated using the axial force developed at the same location. Reducing the spacing ratio of the vertical members as half as the reference model whose ratio is 1/9.375 produces a similar level of the moment-based peak impact factor compared to the reference model. However, when the spacing ratio is doubled, the peak impact factor is 4.4 times greater than the reference model.

• Clean Technology
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• v.28 no.3
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• pp.249-257
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• 2022

The adsorption equilibria of nitrogen on a region of nanoporous carbonaceous adsorbent with local molecular orientation (LMO) were calculated by grand canonical Monte Carlo simulation at 77.16 K. Regions of LMO of identical size were arranged on a regular lattice with uniform spacing. Microporosity was predominately introduced to the model by removing successive out-of-plane domains from the regions of LMO and tilting pores were generated by tilting the basic structure units. This pore structure is a more realistic model than slit-shaped pores for studying adsorption in nanoporous carbon adsorbents. Their porosities, surface areas, and pore size distributions according to constrained nonlinear optimization were also reported. The adsorption in slit shaped pores was also reported for reference. In the slit shaped pores, a clear hysteresis loop was observed in pores of greater than 5 times the nitrogen molecule size, and in capillary condensation and reverse condensation, evaporation occurred immediately at one pressure. In the LMO pore model, three series of local condensations at the basal slip plane, armchair slip plane and interconnected channel were observed during adsorption at pore sizes greater than about 6 times the nitrogen molecular size. In the hysteresis loop, on the other hand, evaporation occurred at one or two pressures during desorption.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.4 no.1
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• pp.41-50
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• 2006

In this paper, sets of engineering analyses were conducted to renew the overall dimensions and configurations of a disposal container proposed as a prototype in the previous study. Such efforts and calculation results can provide new design variables such as the inner basket array type and thickness of the outer shell and the lid & bottom of a spent nuclear fuel disposal container. These efforts include radiation shielding and nuclear criticality analyses to check to see whether the dimensions of the container proposed from the mechanical structural analyses can provide a nuclear safety or not. According to the results of the structural analysis of a PWR disposal container by varying the diameter of the container insert, the Maximum Von Mises stress from the 102 cm-container meets the safety factor of 2.0 for both extreme and normal load conditions. This container also satisfies the nuclear criticality and radiation safety limits. This decrease in the diameter results in a weight loss of a container by $\sim20$ tons.

• Proceedings of the Korean Radioactive Waste Society Conference
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• 2005.11a
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• pp.153-162
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• 2005

In this Paper, sets of engineering analyses were conducted to renew the overall dimensions and configurations of a disposal container proposed as a prototype in the previous study. Such efforts and calculation results can provide new design variables such as the inner basket array type and thickness of the outer shell and the lid & bottom of a spent nuclear fuel disposal container. These efforts include radiation shielding and nuclear criticality analyses to check to see whether the dimensions of the container proposed from the mechanical structural analyses can provide a nuclear safety or not. According to the results of the structural analysis of a PWR disposal container by varying the diameter of the container insert, the Maximum Von Mises stress from the 102 cm container meets the safety factor of 2.0 for both extreme and normal load conditions. This container also satisfies the nuclear criticality and radiation safety limits. This decrease in the diameter results in a weight loss of a container by ${\~}$20 tons.