• The Journal of Korean Academy of Prosthodontics
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• v.46 no.6
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• pp.628-633
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• 2008

STATEMENT OF PROBLEM: The application of a simple, clinically applicable noninvasive test to assess implant stability are considered highly desirable. So far there is still a controversy about correlation of various tests and implant stability. PURPOSE: In order to assess implant stability, the development of a new method is critical. It's possible to assess implant stability by calculating energy and angular momentum during implant installation. The purpose of this study is to evaluate the correlation of energy and implant stability. MATERIAL AND METHODS: Twenty three implants were installed in two different types of pig bone. Type I bone was retrieved from the distal aspect of the rib, with more cortical bone. Type II bone came from a more proximal region with less cortical components and a higher content of bone marrow and spongeous trabeculae. Insertion torque, removal torque, ISQ values and angular momentum and energy were measured. Pearson Correlation test was done to analyze the relation between RFA, maximum insertion torque, mean insertion torque, bone type, energy and removal torque. RESULTS: Type I bone showed higher removal torque than type II bone. Energy value was significantly correlated with maximum insertion torque and mean insertion torque. RFA values were related with insertion torques but the significance was lower than Energy value. CONCLUSION: Within the limitation of this study energy values were considered clinically predictable method to measure the implant stability.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.1
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• pp.175-182
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• 2018

In this study, flood quantiles were estimated at ungauged watersheds by adjusting the flood quantiles from the design rainfall - runoff analysis (DRRA) method based on regional frequency analysis. Comparing the flood frequency analysis (FFA) and DRRA, it was found that the flood quantiles estimated by the DRRA method were overestimated by 52%. In addition, a practical method was suggested to make an flood index using natural flows to apply the regional frequency analysis (RFA) to ungauged watersheds. Considering the relationships among DRRA, FFA, and RFA, we derived an adjusting formula that can be applied to estimate flood quantiles at ungauged watersheds. We also employed Leave-One-Out Cross-Validation scheme and skill score to verify the method proposed in this study. As a result, the proposed model increased the accuracy by 23.2% compared to the existing DRRA method.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.42 no.1
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• pp.2-8
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• 2016

Objectives: The purpose of this study was to investigate the effects of low-level laser therapy (LLLT) with a diode gallium-aluminum-arsenide (Ga-Al-As) low-level laser device on the healing and attachment of titanium implants in bone. Materials and Methods: Thirteen New Zealand white male rabbits weighing $3.0{\pm}0.5kg$ were used for this study. Dental titanium implants (3.75 mm in diameter and 8.5 mm in length, US II RBM plus fixture; Osstem, Seoul, Korea) were implanted into both femurs of each rabbit. The rabbits were randomly divided into a LLLT group and a control group. The LLLT was initiated immediately after surgery and then repeated daily for 7 consecutive days in the LLLT group. Six weeks and 12 weeks after implantation, we evaluated and compared the osseointegration of the LLLT group and control group, using histomorphometric analysis, removal torque testing, and resonance frequency analysis (RFA). The results were statistically significant when the level of probability was 0.05 or less based on a non-parametric Mann-Whitney U-test. Results: The implant survival rate was about 96%. Histologically and histomorphometrically, we observed that the titanium implants were more strongly attached in LLLT group than in control group. However, there was no significant difference between the LLLT group and control group in removal torque or RFA. Conclusion: Histologically, LLLT might promote cell-level osseointegration of titanium implants, but there was no statistically significant effects.

• Journal of the Korea Institute of Building Construction
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• v.15 no.2
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• pp.193-199
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• 2015

As a solution of both environmental issue of reducing carbon dioxide emission and sustainable issue of exhausting natural resources, in concrete industry, many research on recycling various by-products or industrial wastes as the concrete materials has been conducted. The aim of this research is feasibility analysis of additional reaction with ordinary Portland cement and flue gas desulfurization gypsum based on the blast furnace slag and recycled fine aggregate based mortar to achieve the normal strength range. Consequently, in the case of mortar replaced 10% FGD and 30% OPC for BS, 80% of plain OPC mortar's compressive strength was achieved. Furthermore, when the water-to-binder ratio is decreased to keep the practically similar level of flow, it is expected to be achieve the equivalent compressive strength to plain OPC mortar.

• Journal of the Korea Institute of Building Construction
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• v.14 no.3
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• pp.252-258
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• 2014

With the vision of 'a low carbon green develop' various industrial by-products were used as replacement of cement, in order to reduce $CO_2$ emissions from the manufacturing process of cement. Blast furnace slag is one of the industrial by-products. Due to the similar chemical compositions to ordinary Portland cement, blast furnace slag have been widely used in concrete with minimum side effects. Hence, in recent years, alkali activated slag-based composites are extensively studied by many researchers. However, the alkali activator can cause a number of problems in practice. Therefore, in this study, an alternative way of activating the slag was investigated. To activate the slag without using an alkali activator, calcium sulfate dihydrate was chosen and mixed with natural recycled fine aggregate. Fundamental properties of the slag-based mortar were tested to evaluate the effect of calcium sulfate dihydrate.

• Journal of Korean Dental Science
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• v.4 no.2
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• pp.52-58
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• 2011

Purpose: Modifications of implant design have been related to improving initial stability. The purpose of this study was to investigate their respective effect on initial stability between two tapered implant systems (self-tapping vs. non-self-tapping) in medium density bone using three different analytic methods. Materials and Methods: Self-tapping implant (GS III$^{(R)}$; Osstem Implant Co., Busan, Korea) and non-self-tapping implant (Replace Select$^{(R)}$; Nobel Biocare, G$\H{o}$teborg, Sweden) were investigated. In Solid rigid polyurethane blocks of artificially simulated Quality 2 bone, each of the 5 implants was inserted according to the manufacturer's instructions for medium-bone drilling protocol. Evaluation of initial stability was carried out by recording the maximum insertion torque (IT) and performing the resonance frequency analysis (RFA), and the pull-out test. Results: The IT and RFA values of self-tapping implant were significantly higher than those of non self-tapping implant (P=.009 and P=.047, respectively). In the pull-out values, no significant differences were found in implants between two groups (P=.117). Within each implant system, no statistically significant correlation was found among three different outcome variables. Conclusions: These findings suggest that design characteristics of implant geometry significantly influence the initial stability in medium bone density.

• Journal of Periodontal and Implant Science
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• v.38 no.3
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• pp.529-534
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• 2008

Purpose: The objective of this study was to compare initial implant stability measured by RFA between different implant systems during the initial healing period. Material and Methods: Fifty-four patients (36 males/18 females) who had been treated at the Department of Periodontology, Chonbuk National University Dental Hospital during the period between January and November in 2007 were included in the study. The mean age of the subjects was 49 years old (18 to 77). A total of 104 implants (Type A: 3i $Osseotite^{(R)}$, Type B: $Replace^{(R)}$ select, Type C: ITI implant) were placed following the manufacturer's standard surgical protocols. Implant stability quotient (ISQ) readings were obtained for each implant at the time of surgery, 2-, and 4-month postoperatively. Result: No implant was failed during the observation period. At the baseline, the difference between mean ISQ values of 3 implant systems was statistically significant (p<0.05). However, at 2-, and 4-month following implant surgery, no significant difference was observed between ISQ values of the implant systems. In the same implant, the ISQ values of Type B and C implants increased (p<0.05), but those of Type A implants decreased during the 2-month healing period. The mean ISQ values of Type B and C implants showed a increasing tendency, while those of Type A implants were stable for the 4-month follow-up period. Conclusion: Within limits of this study, it can be concluded that implant design and surface topography of implant might influence the ISQ value and changing pattern during the initial healing period.

• Journal of Sensor Science and Technology
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• v.17 no.6
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• pp.397-405
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• 2008

In this study, we have measured temperature distribution using infrared optical fibers during radiofrequency ablation (RFA). Infrared radiations generated from the water around inserted electrode are transferred by silver halide optical fibers and are measured by a thermopile sensor. Also, the output voltages of a thermopile sensor are compared with those of the thermocouple recorder. It is expected that a noncontact temperature sensor using an infrared optical fiber can be developed for the temperature monitoring during RFA treatments based on the results of this study.

• BMB Reports
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• v.52 no.4
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• pp.277-282
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• 2019

Currently speaking, it is noted that radiofrequency ablation (RFA) has been the most widely used treatment for hepatocellular carcinoma (HCC) occurring in patients. However, accumulating evidence has demonstrated that the incidence of insufficient RFA (IRFA) may result in the identified rapid progression of residual HCC in the patient, which can greatly hinder the effectiveness and patient reported benefits of utilizing this technique. Although many efforts have been proposed, the underlying mechanisms triggering the rapid progression of residual HCC after IRFA have not yet been fully clarified through current research literature reviews. It was shown in this study that cell proliferation, migration and invasion of residual HepG2 and SMMC7721 cells were significantly increased after the IRFA was simulated in vitro. In other words, it is noted that IRFA could do this by enhancing the image of autophagy of the residual HCC cell via the $HIF-1{\alpha}/BNIP3$ pathway. Consequently, the down-regulation of BNIP3 may result in the inhibition of the residual HCC cell progression and autophagy after IRFA. Our present study results suggest that IRFA could promote residual HCC cell progression in vitro by enhancing autophagy via the $HIF-1{\alpha}/BNIP3$ pathway. For this reason, it is noted that the targeting of the BNIP3 may be useful in preventing the rapid growth and metastasis of residual HCC after IRFA.

• Journal of the Korea Society of Computer and Information
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• v.26 no.2
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• pp.61-68
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• 2021

Recently, various technologies that use machine learning to classify malicious code have been studied. In order to enhance the effectiveness of machine learning, it is most important to extract properties to identify malicious codes and normal binaries. In this paper, we propose a feature extraction method for use in machine learning using recursive methods. The proposed method selects the final feature using recursive methods for individual features to maximize the performance of machine learning. In detail, we use the method of extracting the best performing features among individual feature at each stage, and then combining the extracted features. We extract features with the proposed method and apply them to machine learning algorithms such as Decision Tree, SVM, Random Forest, and KNN, to validate that machine learning performance improves as the steps continue.