• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.37 no.4
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• pp.302-307
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• 2001

The underwater background noise measured in Geoje and Tongyoung diving fishing ground from May to December, 2000 and analyzed to get optimum carrier frequency and transmitter power level for underwater wireless telephone design. The results obtained are summarized as follows: 1. At the Geoje and Tongyoung diving fishing ground, the lowest ambient noise band was 25~30kHz with 57dB and 52dB re 1$\mu$Pa, respectively. 2. At the Geoje and Tongyoung diving fishing ground, the lowest noise band during fishing activity was 67dB and 62dB re 1$\mu$Pa, respectively. 3. At the Geoje diving fishing ground, the noise of water jetter which is a digging machine for subbottom shells was 102dB re 1$\mu$Pa. 4. Considering the design parameters of underwater wireless telephone, it is found that the optimum carrier frequency band is around 30kHz and the transmitter source level should be at least 131dB re 1$\mu$Pa for 500m range telephone.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.40 no.3
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• pp.273-283
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• 2020

Because of climate change, the occurrence of localized and heavy rainfall is increasing. It is important to predict floods in urban areas that have suffered inundation in the past. For flood prediction, not only numerical analysis models but also machine learning-based models can be applied. The LSTM (Long Short-Term Memory) neural network used in this study is appropriate for sequence data, but it demands a lot of data. However, rainfall that causes flooding does not appear every year in a single urban basin, meaning it is difficult to collect enough data for deep learning. Therefore, in addition to the rainfall observed in the study area, the observed rainfall in another urban basin was applied in the predictive model. The LSTM neural network was used for predicting the total overflow, and the result of the SWMM (Storm Water Management Model) was applied as target data. The prediction of the inundation map was performed by using logistic regression; the independent variable was the total overflow and the dependent variable was the presence or absence of flooding in each grid. The dependent variable of logistic regression was collected through the simulation results of a two-dimensional flood model. The input data of the two-dimensional flood model were the overflow at each manhole calculated by the SWMM. According to the LSTM neural network parameters, the prediction results of total overflow were compared. Four predictive models were used in this study depending on the parameter of the LSTM. The average RMSE (Root Mean Square Error) for verification and testing was 1.4279 ㎥/s, 1.0079 ㎥/s for the four LSTM models. The minimum RMSE of the verification and testing was calculated as 1.1655 ㎥/s and 0.8797 ㎥/s. It was confirmed that the total overflow can be predicted similarly to the SWMM simulation results. The prediction of inundation extent was performed by linking the logistic regression with the results of the LSTM neural network, and the maximum area fitness was 97.33 % when more than 0.5 m depth was considered. The methodology presented in this study would be helpful in improving urban flood response based on deep learning methodology.

• Radiation Oncology Journal
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• v.25 no.3
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• pp.185-191
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• 2007

Purpose: This study was performed to investigate the effects of immune cell activation and the antitumor effect for the combination of treatment with X-irradiation and E/eutherococcus senticosus Maxim Root (ESMR) on mouse tumor cells. Materials and Methods: ESMR (250g) was extracted with 80% methanol, concentrated under decompression and lyophilized. To determine whether ESMR is able to activate the immune cells or not, the proliferation of splenocytes in vitro and the number of B cells and T cells in splenic lymphocytes in ESMR-pretreated mice were evaluated. X-irradiation was given to the mouse fibrosarcoma tumor cells (FSa II) by 250 kv X-irradiation machine. The cytotoxicity of ESMR was evaluated from its ability to reduce the clonogenecity of FSa II cells. In X-irradiation alone group, each 2, 4, 6 and 8 Gy was given to FSa II cells. In X-irradiation with ESMR group, 0.2 mg/ml of ESMR was exposed to FSa II cells for 1 hour before X-irradiation. Results: The proliferation of cultured mouse splenocytes and thymocytes were enhanced by the addition of ESMR in vitro. The number of B cells and T cells in mouse splenic lymphocytes was significantly increased in ESMR pretreated mice in vivo. In FSa II cells that received a combination of 0.2 mg/ml of ESMR with X-irradiation exposure, the survival fraction with a dose of 2, 4 and 6 Gy was $0.39{\pm}0.005$, $0.22{\pm}0.005$ and $0.06{\pm}0.007$, respectively. For FSa II cells treated with X-irradiation alone, the survival fraction with a dose of 2, 4 and 6 Gy was $0.76{\pm}0.02$, $0.47{\pm}0.008$ and $0.37{\pm}0.01$. The difference in the survival fraction of the mouse FSa II cells treated with and without ESMR was statistically significant (p<0.05). Conclusion: Treatment with ESMR increased cell viability of mouse splenocytes in vitro and especially the subpopulation of B cells and T cells in splenocytes in ESMR-pretreated mice. However, treatment with ESMR did not increase the level of Th and Tc subpopulations in the thymocytes. Treatment with the combination of ESMR and X-irradiation was more cytotoxic to mouse tumor cells than treatment with X-irradiation alone; this finding was statistically significant.

• Journal of Technologic Dentistry
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• v.19 no.1
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• pp.21-35
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• 1997

The Ag-Pd-Cu alloys containing a small amount of Au is commonly used for dental purposes, because this alloy is cheaper than Au-base alloys for clinical use. However, the most important characteristic of this alloy is age-hardenability, which is not exhibited by other Ag-base dental alloys. The specimens used were Ag-20Pd-20Cu ternary alloy and Au addition alloy. These alloys were melted and casted by induction electic furace and centrifugal casting machine in Ar atmoshpere. These specimens were solution treated for 2hr at $800^{\circ}C$ and were then quenched into iced water, and aged at $350{\sim}550^{\circ}C$ Age-hardening characteristics of the small Au-containing Ag-pPd-Cu dental alloys were investigated by means of hardness testing, X-ray diffraction and electron microscope observations, electrical resistance, differential scanning calorimetric, emergy dispersed spectra and electron probe microanalysis. Principal results are as follows : Hardening occured in two stages, I. e., stage I in low temperature and stage II in high temperature regions, during continuous aging. The case of hardening in stage I was due to the formation of the Llo type face centered tetragonal PdCu-ordered phase in the grain interior and hardening in stage I was affedted by the Cu concentration. In stage II, decomposition of the $\alpha$ solid solution to a PdCu ordered phase(L1o type) and an Agrich ${\alpha}2$ phase occurred and a discontiunous precipitation occurred at the grain boundary. Form the electron microscope study, it was concluded that the cause of age-hardening in this alloy is the precipitation of the PdCu ordered phase, which has AuCu I type face-centered tetragonal structure. Precipitation procedure was ${\alpha}\to{\alpha}+{\alpha}2+PdCu\to{\alpha}1+{\alpha}2+PdCu$ at Pd/Cu = 1 Ag-Pd-Cu alloy is more effective dental alloy as ageing treatment and is suitable to isothermal ageing at $450^{\circ}C$.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.66 no.2
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• pp.105-111
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• 2021

Rice lodging is an annual occurrence caused by typhoons accompanied by strong winds and strong rainfall, resulting in damage relating to pre-harvest sprouting during the ripening period. Thus, rapid estimations of the area of lodged rice are necessary to enable timely responses to damage. To this end, we obtained images related to rice lodging using a drone in Gimje, Buan, and Gunsan, which were converted to 128 × 128 pixels images. A convolutional neural network (CNN) model, a deep learning model based on these images, was used to predict rice lodging, which was classified into two types (lodging and non-lodging), and the images were divided in a 8:2 ratio into a training set and a validation set. The CNN model was layered and trained using three optimizers (Adam, Rmsprop, and SGD). The area of rice lodging was evaluated for the three fields using the obtained data, with the exception of the training set and validation set. The images were combined to give composites images of the entire fields using Metashape, and these images were divided into 128 × 128 pixels. Lodging in the divided images was predicted using the trained CNN model, and the extent of lodging was calculated by multiplying the ratio of the total number of field images by the number of lodging images by the area of the entire field. The results for the training and validation sets showed that accuracy increased with a progression in learning and eventually reached a level greater than 0.919. The results obtained for each of the three fields showed high accuracy with respect to all optimizers, among which, Adam showed the highest accuracy (normalized root mean square error: 2.73%). On the basis of the findings of this study, it is anticipated that the area of lodged rice can be rapidly predicted using deep learning.

• Restorative Dentistry and Endodontics
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• v.32 no.4
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• pp.343-355
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• 2007

The objectives of this study was to evaluate the durability of 4 resin cements by means of microtensile bond strength test combined with thermocycling method and fractographic FE-SEM analysis. Experimental groups were prepared according to thermocycling (0, 1,000, 5,000) and the kind of resin cements, those were Variolink II, Multilink, Panavia F 2.0, Rely X Unicem. Flat dentin surfaces were created on mid-coronal dentin of extracted third molars. Then fresh dentin surface was grounded with 320-grit silicon carbide abrasive papers to create uniform smear layers. Indirect composite block (Tescera, Bisco Inc., Schaumburg, IL, USA) was fabricated ($12\;{\times}\;12\;{\times}\;6\;mm^3$). It's surface for bonding to tooth was grounded with silicon carbide abrasive papers from 180- to 600-grit serially, then sandblasted witk $20\;-\;50\;{\mu}m$ alumina oxide. According to each manufacturer's instruction, dentin surface was treated and indirect composite block was luted on it using each resin cement. For Rely X Unicem, dentin surface was not treated. The bonded tooth-resin block were stored in distilled water at $37^{\circ}C$ for 24 hours. After thermocycling, the bonded tooth-resin block was sectioned occluso-gingivally to 1.0 mm thick serial slabs using all Isomet slow-speed saw (Isomet, Buehler Ltd, Lake Bluff, IL, USA). These sectioned slabs were further sectioned to $1.0\;{\times}\;1.0\;mm^2$ composite-dentin beams. The specimens were tested with universal testing machine (EZ-Test, Shimadzu, Japan) at a crosshead speed of 1.0 mm/min with maximum load of 500 N. The data was analyzed using one-way ANOVA and Duncan's multiple comparison test at $p\;{\leq}\;0.05$ level. Within the limited results, we conclude as follows; 1. The bond strength of Variolink II was evaluated the highest among experimental groups and was significantly decreased after 1,000 thermocycling (p < 0.05). 2. The bond strength of Multilink was more affected by thermocycling than the other experimental groups and significantly decreased after 1,000 thermocycling (p < 0.05). 3. Panavia F 2.0 and Rely X Unicem showed the gradually decreased tendency of microtensile bond strength according to thermocycling but there was no significant difference (p > 0.05). 4. Adhesive based-resin cements showed lower bond strength with or without thermocycling than composite based-resin cements. 5. Variolink II & Multilink showed high bond strength and mixed failure, which was occurred with a thin layer of luting resin cement before thermocycling and gradually increased adhesive failure along the dentin surface after thermocycling. The bonding performance of resin cement can be affected by application procedure and chemical composition. Composite based-resin cement showed higher bond strength and durability than adhesive based-resin cement.

• The Journal of Korean Academy of Prosthodontics
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• v.53 no.4
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• pp.345-351
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• 2015

Purpose: The purpose of this study was to evaluate the proper axial thickness of zirconia abutment applied to implant in the anterior region. Materials and methods: Zirconia abutments were prepared at different axial wall thickness by processing pre-sintered zirconia blocks via CAD/CAM to obtain equal specimens. The abutments were each produced with a thickness of 0.5 mm (Group 1), 0.8 mm (Group 2), 1.2 mm (Group 3), or 1.5 mm (Group 4). The implant used in this study was a external connection type one (US, Osstem, Pussan, Korea) product and the zirconia abutment was prepared via replication of a cemented abutment. The crowns were prepared via CAM/CAM with a thickness of 1.5 mm and were cemented to the abutments using $RelyX^{TM}$ UniCem cement. A universal testing machine was used to apply load at 30 degrees and measure fracture strength of the zirconia abutment. Results: Fracture strength of the abutments for Group 1, Group 2, Group 3, and Group 4 were $236.00{\pm}67.55N$, $599.00{\pm}15.80N$, $588.20{\pm}33.18N$, and $97.83{\pm}98.13N$, respectively. Group 1 showed a significantly lower value, as compared to the other groups (independent Mann-Whitney U-test. P<.05). No significant differences were detected among Group 2, Group 3, and Group 4 (independent Mann-Whitney U-test. P>.05). Conclusion: Zirconia abutment requires optimal thickness for fracture resistance. Within the limitation of this study, > 0.8 mm thickness is recommended for zirconia abutment in anterior implants.

• The korean journal of orthodontics
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• v.28 no.6 s.71
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• pp.955-974
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• 1998

The purpose of the present study was to seek bracket-adhesive combinations which have adequate bond strength with no enamel and bracket fracture. The shear bond strengths were measured, the sites of failure and the enamel damage were investigated and the peripheral sealing and adaptation between enamel surface, bonding adhesive and bracket were evaluated. 240 noncarious human premolars were divided into twenty four groups of ten teeth. Shear bond strengths of each group were determined in an universal testing machine after two days passed and the debonded specimens were inspected to determine the predominant bond failure sites. To evaluate peripheral sealing and adaption between enamel surface, adhesive and bracket, each specimen was cut longitudinally into two halves which included the midsection of the bracket, adhesive and enamel and exmined in scanning electron microscope. Six different types of brackets were bonded to the tooth with four different type of adhesives. Six different types of brackets were Image, Plastic, Crystaline, Fascination, Transcend 2000 and metal bracket and four different adhesives were No-mix, Light-Bond, OrthoLC and Superbond C&B. From this study, it may be concluded that (1) The mean shear bond strength varied from a high of 36.58 Kg (410.07 Kg/$cm^2$) with the Fascination-Light Bond combination group to a low of 8.93 Kg (75.51 Kg/$cm^2$) with theImage-OrthoLC combination group. When using OrthoLC as adhesive, the mean shear bond strength was significantly lower than that of other combination groups, (2) Regardless of adhesives, the mean shear bond strength of Fascination brackets was relatively high whereas Plastic and Image brackets had low shear bonding strength. The shear bond strength of Crystaline bracket and Transcend 2m was relatively equal to or lower than that of metal bracket, (3) There was a correlation between bond strength, enamel damage and bracket fracture. As the shear bond strength was increased, the rate of enamel damage and bracket fracture were increased, (4) The combination groups that use OrthoLC as adhesive were debonded in shear stress without enamel fracture and bracket fracture, whereas the combination groups that use Superbond C&B as adhesive experienced a relative high enamel fracture rate and bracket fracture rate, (5) Peripheral sealing and adaptation between enamel-adhesive-bracket were relatively good when using Light-Bond or No-mix as adhesive. Regardless of adhesives, adaptation between bracket-adhesive were relatively good in Ceramic brackets, (6) The combination groups which had adequate bonding strength with no enamel and bracket fracture were Crystaline-No mix, Crystaline-Light Bond, Crystaline-OrthoLC, metal-No mix, metal-Light Bond and metal-OrthoLC combination groups.

• Journal of the korean academy of Pediatric Dentistry
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• v.39 no.4
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• pp.383-388
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• 2012

The aim of this study was to compare the compressive strength and the surface microhardness of Beautifil flow (Shofu, Kyoto, Japan) with $Filtek^{TM}$ Z350, Z350XT (3M ESPE, USA). Fifteen specimens from each material were fabricated for testing. Compressive strength was measured by using a universal testing machine at a crosshead speed of 1 mm/min. Surface microhardness values were measured by using Vickers hardness tester under 4.9 N load and 10 seconds dwelling time. The compressive strength of Group 2 $Filtek^{TM}$ Z350XT shows the highest value as $218.7{\pm}18.4$ MPa and Group 1 $Filtek^{TM}$ Z350 was $205.5{\pm}27.1$ MPa. Group 3 Beautifil flow F00 was $176.5{\pm}30.3$ MPa, and Group 4 Beautifil flow F10 was $173.4{\pm}26.2$ MPa. The compressive strength of Group 2 is higher than Group 3 and 4 (p < 0.05). The surface microhardness of Group 2 $Filtek^{TM}$ Z350XT shows the highest value as $39.1{\pm}2.1$ and Group 4 Beautifil flow F10 was $27.9{\pm}1.8$. And Group 3 Beautifil flow F00 was $23.1{\pm}1.1$, Group 1 $Filtek^{TM}$ Z350 was $20.4{\pm}0.9$. There was a statistical significant difference in surface microhardness between all groups (p < 0.05). In conclusion, the compressive strength of giomer was below the level of flowable composite resin. However, the surface microhardness of giomer is comparable to that of flowable composite resin. Giomer would be the good alternative to composite resin, if there is improvement of the compressive strength of giomer.

• Investigative Magnetic Resonance Imaging
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• v.8 no.2
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• pp.79-85
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• 2004

Purpose : To evaluate the usefulness and reproducibility of $^1H$ MRS in different 1.5 T MR machines with different coils to compare the SNR, scan time and the spectral patterns in different brain regions in normal volunteers. Materials and Methods : Localized $^1H$ MR spectroscopy ($^1H$ MRS) was performed in a total of 10 normal volunteers (age; 20-45 years) with spectral parameters adjusted by the autoprescan routine (PROBE package). In all volunteers, MRS was performed in a three times using conventional MRS (Signa Horizon) with 1 channel coil and upgraded MRS (Echospeed plus with EXCITE) with both 1 channel and 8 channel coil. Using these three different machines and coils, SNRs of the spectra in both phantom and volunteers and (pre)scan time of MRS were compared. Two regions of the human brain (basal ganglia and deep white matter) were examined and relative metabolite ratios (NAA/Cr, Cho/Cr, and mI/Cr ratios) were measured in all volunteers. For all spectra, a STEAM localization sequence with three-pulse CHESS $H_2O$ suppression was used, with the following acquisition parameters: TR=3.0/2.0 sec, TE=30 msec, TM=13.7 msec, SW=2500 Hz, SI=2048 pts, AVG : 64/128, and NEX=2/8 (Signa/Echospeed). Results : The SNR was about over $30\%$ higher in Echospeed machine and time for prescan and scan was almost same in different machines and coils. Reliable spectra were obtained on both MRS systems and there were no significant differences in spectral patterns and relative metabolite ratios in two brain regions (p>0.05). Conclusion : Both conventional and new MRI systems are highly reliable and reproducible for $^1H$ MR spectroscopic examinations in human brains and there are no significant differences in applications for $^1H$ MRS between two different MRI systems.