• Journal of Periodontal and Implant Science
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• v.39 no.2
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• pp.149-156
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• 2009

Purpose: Deproteinized bovine bone substitutes are commonly used in dental regenerative surgery for treatment of alveolar defects. In this study, three different bovine bone minerals - OCS-B (NIBEC, Seoul, Korea), Bio-Oss (Geistlich - Pharma, Switzerland), Osteograft/N - 300 (OGN, Dentsply Friadent Ceramed. TN, USA) - were investigated to analyze the basic characteristics of commercially available bone substitutes. Methods: Their physicochemical properties were evaluated by scanning electron microscopy, energy dispersive X-ray spectrometer (EDS), surface area analysis, and Kjeldahl protein analysis. Cell proliferation and alkaline phosphatase (ALP) activity of human osteosarcoma cells on different bovine bone minerals were evaluated. Results: Three kinds of bone substitutes displayed different surface properties. Ca/P ratio of OCS - B shown to be lower than other two bovine bone minerals in EDS analysis. Bio-Oss had wider surface area and lower amount of residual protein than OCS - B and OGN. In addition Bio - Oss was proved to have lower cell proliferation and ALP activity due to lots of residual micro particles, compared with OCS - B and OGN. Conclusions: Based on the results of this study, three bovine bone minerals that produced by similar methods appear to have different property and characteristics. It is suggested that detailed studies and quality management is needed in operations for dental use and its biological effects on new bone formation.

• Proceedings of the Korean Vacuum Society Conference
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• 2013.02a
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• pp.275-275
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• 2013

Formation and characterization of self-assembled monolayers (SAMs) on various surfaces are the essential basis for many other applications, including molecular switches, biosensors, microfluidics, and fundamental studies in surfaces and interfaces. To improve the performance at these applications, it is a key to control the quantity of each molecule in various mixed SAMs on the surface. In this study, using mixed SAM of carbamate-based hydroquinone (HQ)-PhBr and11-mercaptoundecanol, the quantitative mass spectrometric method of mixed SAM was developed based on comparison study with XPS and FT-IR methods. In addition, our method was applied to another mixed SAM of biotinylated PEG alkane thiol and 11-mercaptoundecanol for verification purpose. Time-of-flight secondary mass spectrometry (ToF-SIMS) analysis was performed to identify and quantify each molecule of mixed SAM along with principal component analysis (PCA). Since there is no matrix effect in the X-ray photoelectron spectroscopy (XPS) and Fourier transform-infrared (FT-IR) techniques, we compared ToF-SIMS results with XPS and FT-IR results. Because PCA results from ToF-SIMS analysis are well matched with XPS and FT-IR results from both mixed SAMs, we are expecting that our method will be useful to identify and quantify each molecule in various mixed SAMs.

• Journal of Convergence for Information Technology
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• v.11 no.1
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• pp.175-182
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• 2021

The purpose of this study is to establish the direction of industrial policy by comparing the employment inducement effect on the related industries of the digital bio-healthcare industry. The analysis data used the three-year input-output table measured by the Bank of Korea. First, the research method was rewritten into 7 major industries to compare statistical data by period. Second, the Bank of Korea's industry-related analysis methodology was utilized. Third, the weight was reflected and compared by employment, production, and investment sectors of the digital bio-healthcare industry. As a result of the analysis, first, the employment sector had a higher effect than the average of the entire industry, second, the production sector was low, and third, the investment sector required investment in the service sector. The conclusions drawn from the analysis showed that direct investment and continuous investment are required in the employment sector, the development of professional manpower is urgent, and direct investment and long-term investment are effective in the production sector.

• Journal of Biosystems Engineering
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• v.41 no.3
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• pp.273-280
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• 2016

Purpose: This experiment was conducted to detect water stress in terms of the moisture content of cucumber seedlings under water stress condition using a hyperspectral image acquisition system, linear regression analysis, and partial least square regression (PLSR) to achieve a non-destructive measurement procedure. Methods: Changes in the reflectance spectrum of cucumber seedlings under water stress were measured using hyperspectral imaging techniques. A model for estimating moisture content of cucumber seedlings was constructed through a linear regression analysis that used the moisture content of cucumber seedlings and a normalized difference vegetation index (NDVI). A model using PLSR that used the moisture content of cucumber seedlings and reflectance spectrum was also created. Results: In the early stages of water stress, cucumber seedlings recovered completely when sub-irrigation was applied. However, the seedlings suffering from initial wilting did not recover when more than 42 h passed without irrigation. The reflectance spectrum of seedlings under water stress decreased gradually, but increased when irrigation was provided, except for the seedlings that had permanently wilted. From the results of the linear regression analysis using the NDVI, the model excluding wilted seedlings with less than 20% (n=97) moisture content showed a precision ($R^2$ and $R^2_{\alpha}$) of 0.573 and 0.568, respectively, and accuracy (RE) of 4.138% and 4.138%, which was higher than that for models including all seedlings (n=100). For PLS regression analysis using the reflectance spectrum, both models were found to have strong precision ($R^2$) with a rating of 0.822, but accuracy (RMSE and RE) was higher in the model excluding wilted seedlings as 5.544% and 13.65% respectively. Conclusions: The estimation model of the moisture content of cucumber seedlings showed better results in the PLSR analysis using reflectance spectrum than the linear regression analysis using NDVI.

• Journal of Applied Biological Chemistry
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• v.56 no.2
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• pp.95-100
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• 2013

Soil microbes are important integral components of soil ecosystem which have significant and diverse role in organic matter decomposition, nitrogen cycling, and nitrogen fixation. In this study an effective denaturing gradient gel electrophoresis (DGGE) method was employed for paddy soil microbial diversity survey. For optimum paddy soil microbial DNA extraction, different methods such as Lysis buffer, skim milk bead, sodium phosphate buffer, Epicentre Soil Master DNA extraction kit (Epicentre, USA) and Mo Bio Power Soil DNA kit (MO BIO, USA) methods were utilized. Among all the method, using Mo Bio Power Soil kit was most effective. DGGE analysis of Bacteria was carried out at 6% polyacylamide gel and 45-60% denaturing gradient in the optimal conditions. Whereas DGGE analysis of fungi was done at 6% polyacrylamide gel and 45-80% denaturing gradient in the optimal conditions. By applying the above assay, it was found that variation within the microbial community of paddy soil occurs by a factor of time. DGGE assay used in this study through for a variety of soil microbial analysis suggests the potential use of this method.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.19 no.9
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• pp.1010-1019
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• 2008

In this paper, we present a noise analysis and measurement results of a bio-radar system that can detect human heartbeat and respiration signals. The noise analysis including various phase noise effects is very important in designing the bio-radar system, since the frequency difference between the received signal and local oscillator is very small and the received power is very low. All of the noise components in a bio-radar system are considered from the point of view of SNR. From this analysis, it can be concluded that the phase noise due to antenna leakage is a dominant factor and is a function of range correlation. Therefore, the phase noise component with range correlation effect, which is the most important noise contribution, is measured using the measurement setup and compared with the calculated results. From the measurement results, our measurement setup can measure a closed-in phase noise of a free-running oscillator. Based on these results, it is possible to design a 2.4 GHz bio-radar system quantitatively which has a detection range of 50 cm and low power of 1 mW without additional PLL circuits.

• Journal of Microbiology and Biotechnology
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• v.16 no.7
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• pp.1139-1143
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• 2006

Various techniques and strategies have been developed for the identification of intracellular metabolic conditions, and among them, isotope balance-based flux analysis with gas chromatography/mass spectrometry (GC/ MS) has recently become popular. Even though isotope balance-based flux analysis allows a more accurate estimation of intracellular fluxes, its application has been restricted to relatively small metabolic systems because of the limited number of measurable metabolites. In this paper, a strategy for incorporating isotope balance-based flux data obtained for a small network into metabolic flux analysis was examined as a feasible alternative allowing more accurate quantification of intracellular flux distribution in a large metabolic system. To impose GC/MS based data into a large metabolic network and obtain optimum flux distribution profile, data reconciliation procedure was applied. As a result, metabolic flux values of 308 intracellular reactions could be estimated from 29 GC/ MS based fluxes with higher accuracy.

• Journal of Bio-Environment Control
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• v.30 no.1
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• pp.19-26
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• 2021

In this study, analysis was performed to identify three greenhouses located in the same area using principal component analysis (PCA) and linear discrimination analysis (LDA). The environmental data in the greenhouse were from 3 farms in the same area, and the values collected at 1 hour intervals for a total of 4 weeks from April 1 to April 28 were used. Before analyzing the data, it was pre-processed to normalize the data, and the analysis was performed by dividing it into 80% of the training data and 20% of the test data. As a result of PCA and LDA analysis, it was found that PCA classification accuracy was 57.51% and LDA classification was 67.06%, indicating that it can be classified by greenhouse. Based on the farmhouse data classified in advance, the data of the new environment can be classified into specific groups to determine the tendency of the data. Such data is judged to be a way to increase the utilization of data by facilitating identification.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.26 no.1
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• pp.217-231
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• 2015

This study aims to infer the gene-protein 'brings_about' chains of pancreatic cancer which were referred to in the pancreatic cancer related researches by constructing the gene-protein interaction network of pancreatic cancer. The chains can help us uncover publicly unknown knowledge that would develop as empirical studies for investigating the cause of pancreatic cancer. In this study, we applied a novel approach that grafts text mining and the main path analysis into Swanson's ABC model for expanding intermediate concepts to multi-levels and extracting the most significant path. We carried out text mining analysis on the full texts of the pancreatic cancer research papers published during the last ten-year period and extracted the gene-protein entities and relations. The 'brings_about' network was established with bio relations represented by bio verbs. We also applied main path analysis to the network. We found the main direct 'brings_about' path of pancreatic cancer which includes 14 nodes and 13 arcs. 9 arcs were confirmed as the actual relations emerged on the related researches while the other 4 arcs were arisen in the network transformation process for main path analysis. We believe that our approach to combining text mining analysis with main path analysis can be a useful tool for inferring undiscovered knowledge in the situation where either a starting or an ending point is unknown.

• Journal of the Korean Wood Science and Technology
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• v.34 no.6
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• pp.36-43
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• 2006

Using fluidized bed type fast pyrolysis system (capacity 400 g/h) bio-oils were produced from beech (Fagus sylvatica) and softwood mixture (spruce and larch, 50:50). The pyrolysis was performed for 1~2 s at the temperature of $470{\pm}5^{\circ}C$. Pyrolysis products consisted of liquid form of bio-oil, char and gases. In beech wood bio-oil was formed to ca. 60% based on dry biomass weight and the yield of bio-oil was 49% in soft wood mixture. The moisture contents in both bio-oils were ranged between 17% and 22% and the bio-oil's density was measured to $1.2kg/{\ell}$. Bio-oils were composed of 45% carbon, 47% oxygen, 7% hydrogen and lower than 1% nitrogen,which was very similar to those of original biomass. In comparison with oils from fossil resources, oxygen content was very high in bio-oils, while no sulfur was found. More than 90 low molecular weight components, classified to aromatic and non aromatic compounds, were identified in bio-oils by gas chromatographic analysis, which amounted to 31~33% based on the dry weight of bio-oils.