• The Journal of Korean Academy of Prosthodontics
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• v.41 no.2
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• pp.182-206
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• 2003

Statement of problem : Successful osseointegration of endosseous threaded implants is dependent on many factors. These may include the surface characteristics and gross geometry of implants, the quality and quantity of bone where implants are placed, and the magnitude and direction of stress in functional occlusion. Therefore clinical quantitative measurement of primary stability at placement and functional state of implant may play a role in prediction of possible clinical symptoms and the renovation of implant geometry, types and surface characteristic according to each patients conditions. Ultimately, it may increase success rate of implants. Purpose : Many available non-invasive techniques used for the clinical measurement of implant stability and osseointegration include percussion, radiography, the $Periotest^{(R)}$, Dental Fine $Tester^{(R)}$ and so on. There is, however, relatively little research undertaken to standardize quantitative measurement of stability of implant and osseointegration due to the various clinical applications performed by each individual operator. Therefore, in order to develop non-invasive experimental method to measure stability of implant quantitatively, the resonance frequency analyzer to measure the natural frequency of specific substance was developed in the procedure of this study. Material & method : To test the stability of the resonance frequency analyzer developed in this study, following methods and materials were used : 1) In-vitro study: the implant was placed in both epoxy resin of which physical properties are similar to the bone stiffness of human and fresh cow rib bone specimen. Then the resonance frequency values of them were measured and analyzed. In an attempt to test the reliability of the data gathered with the resonance frequency analyzer, comparative analysis with the data from the Periotest was conducted. 2) In-vivo study: the implants were inserted into the tibiae of 10 New Zealand rabbits and the resonance frequency value of them with connected abutments at healing time are measured immediately after insertion and gauged every 4 weeks for 16 weeks. Results : Results from these studies were such as follows : The same length implants placed in Hot Melt showed the repetitive resonance frequency values. As the length of abutment increased, the resonance frequency value changed significantly (p<0.01). As the thickness of transducer increased in order of 0.5, 1.0 and 2.0 mm, the resonance frequency value significantly increased (p<0.05). The implants placed in PL-2 and epoxy resin with different exposure degree resulted in the increase of resonance frequency value as the exposure degree of implants and the length of abutment decreased. In comparative experiment based on physical properties, as the thickness of transducer increased, the resonance frequency value increased significantly(p<0.01). As the stiffness of substances where implants were placed increased, and the effective length of implants decreased, the resonance frequencies value increased significantly (p<0.05). In the experiment with cow rib bone specimen, the increase of the length of abutment resulted in significant difference between the results from resonance frequency analyzer and the $Periotest^{(R)}$. There was no difference with significant meaning in the comparison based on the direction of measurement between the resonance frequency value and the $Periotest^{(R)}$ value (p<0.05). In-vivo experiment resulted in repetitive patternes of resonance frequency. As the time elapsed, the resonance frequency value increased significantly with the exception of 4th and 8th week (p<0.05). Conclusion : The development of resonance frequency analyzer is an attempt to standardize the quantitative measurement of stability of implant and osseointegration and compensate for the reliability of data from other non-invasive measuring devices It is considered that further research is needed to improve the efficiency of clinical application of resonance frequency analyzer. In addition, further investigation is warranted on the standardized quantitative analysis of the stability of implant.

• Korean Journal of Organic Agriculture
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• v.18 no.2
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• pp.257-269
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• 2010

To investigate the possibility of discrimination between organic and non-organic rice using stable isotope nitrogen of natural abundance, organic rice of 17 samples and non-organic rice of 13 samples grown at adjoining organic rice field were collected in 2008. Rice was grinded into brown rice, milled rice and hull, and samples were analysed for nitrogen and $\delta^{15}N$ at NICEM. Authors also made inquiries about N source for both farmers who conduct organic- and non-organic rice cultivation. In order to know whether the $\delta^{15}N$ can be used in discrimination between organic and non-organic rice, discriminant analysis were made with SPSS and logistic method. 1. Organic farmers used manure, rice bran, used mushroom culture, fermented fertilizer (company products), and oil cake, but non-organic farmers applied compound fertilizer. Rice straws were remained in organic rice field while moved out in non-organic field. 2. There were difference in $\delta^{15}N$ among organic rice and its byproduct(7.760????% in hull, 6.720????% in rice), but significant difference was not found between them. And the trend was same between province. Non-organic rice showed similar results. 3. Significant difference of $\delta^{15}N$ were found between organic rice and non-organic rice (p<0.01) and between hull of organic rice and that of non-organic rice hull (p<0.05). $\delta^{15}N$ seemed to be useful criteria for discrimination of organic and non-organic rice. 4. When applied discrimination analysis of SPSS and logistic, there were significant difference between organic rice, non-organic rice and its byproducts except brown rice and hull in SPSS method. Hull can be used as the most useful component for unknown sample prediction with 83.3% probability.

• Korean Journal of Ecology and Environment
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• v.48 no.3
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• pp.153-167
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• 2015

In order to understand the relationship between the distribution of epilithic diatoms and the habitual environments, land-use, water qualities, and epilithic diatoms were studied at 141 sampling sites in the midwestern stream of Korean peninsula (Geum river, Mangyeong river, Dongjin river, and Sapgyo river). The total 183 diatom taxa was appeared in the study, while the dominant species were found to be Nitzschia palea (10.9%) and Achnanthes convergens (8.4%). Based on the abundance of epilithic diatoms, a cluster analysis results indicate that the sampling sites divided the sampling sites into 4 groups (G) at the 25% level. In term of geographic and aquatic environments, G-I and -II accounted for the upper and mid streams of the Geum river, and had large forest areas and good in water quality. G-III accounted for farmland and urban, and high concentration nutrient levels (TN and TP) and electric conductivity. G-IV accounted for mostly farmland, and high levels in turbidity, BOD, nutrient and electric conductivity. CCA results showed that the saproxenous taxa Meridion circulare was the indicator species of G-I, which strongly influenced by altitude and forests. In G-II, the indifferent taxa Navicula cryptocephala was influenced by Chl-a, AFDM, and DO. In G-III and -IV, the indifferent taxa Fragilaria elliptica and saprophilous taxa Aulacoseira ambigua were influenced by electric conductivity, turbidity, and nutrient counts. Meanwhile, random forest results showed that the predicting factor of indicator species appearance in G-I, -II, and -III was found to be electric conductivity whereas in G-IV it was found to be turbidity. Collectively, the distribution of diatoms in the midwestern of Korean peninsula was found to depend more on the land-use and its subsequent water qualities than the inherent characteristics of the aquatic environment.

• Fire Science and Engineering
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• v.18 no.1
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• pp.54-66
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• 2004

In this article, we are to suggest the hazard-assessing method for the underground pipelines, and find out the pipeline-maintenance schemes of high efficiency in cost. Three kinds of methods are applied in order to refer to the approaching methods of listing the hazards for the underground pipelines: the first is RBI(Risk Based Inspection), which firstly assess the effect of the neighboring population, the dimension, thickness of pipe, and working time. It enables us to estimate quantitatively the risk exposure. The second is the scoring system which is based on the environmental factors of the buried pipelines. Last we quantify the frequency of the releases using the present THOMAS' theory. In this work, as a result of assessing the hazard of it using SPC scheme, the hazard score related to how the gas pipelines erodes indicate the numbers from 30 to 70, which means that the assessing criteria define well the relative hazards of actual pipelines. Therefore. even if one pipeline region is relatively low score, it can have the high frequency of leakage due to its longer length. The acceptable limit of the release frequency of pipeline shows 2.50E-2 to 1.00E-l/yr, from which we must take the appropriate actions to have the consequence to be less than the acceptable region. The prediction of total frequency using regression analysis shows the limit operating time of pipeline is the range of 11 to 13 years, which is well consistent with that of the actual pipeline. Concludingly, the hazard-listing scheme suggested in this research will be very effectively applied to maintaining the underground pipelines.

• Korean Journal of Remote Sensing
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• v.14 no.1
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• pp.53-68
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• 1998

Observation of hydrometeors' behavior in the atmosphere is important to understand weather and climate. By conventional observations, we can get the distribution of water vapor at limited number of points on the earth. In this study, the precipitable water has been estimated from the split window channel data on GMS-5 based upon the technique developed by Chesters et al.(1983). To retrieve the precipitable water, water vapor absorption parameter depending on filter function of sensor has been derived using the regression analysis between the split window channel data and the radiosonde data observed at Osan, Pohang, Kwangiu and Cheju staions for 4 months. The air temperature of 700 hPa from the Global Spectral Model of Korea Meteorological Administration (GSM/KMA) has been used as mean air temperature for single layer radiation model. The retrieved precipitable water for the period from August 1996 through December 1996 are compared to radiosonde data. It is shown that the root mean square differences between radiosonde observations and the GMS-5 retrievals range from 0.65 g/$cm^2$ to 1.09 g/$cm^2$ with correlation coefficient of 0.46 on hourly basis. The monthly distribution of precipitable water from GMS-5 shows almost good representation in large scale. Precipitable water is produced 4 times a day at Korea Meteorological Administration in the form of grid point data with 0.5 degree lat./lon. resolution. The data can be used in the objective analysis for numerical weather prediction and to increase the accuracy of humidity analysis especially under clear sky condition. And also, the data is a useful complement to existing data set for climatological research. But it is necessary to get higher correlation between radiosonde observations and the GMS-5 retrievals for operational applications.

• Journal of the Korean earth science society
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• v.42 no.5
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• pp.496-503
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• 2021

By analyzing the characteristics of atmospheric stability in the southern coastal region of the Korean Peninsula in the summer of 2019, a quantitative threshold of atmospheric instability indices was derived for predicting rainfall events in the Korean Peninsula. For this analysis, we used data from all of the 243 radiosonde intensive observations recorded at the Boseong Standard Weather Observatory (BSWO) in the summer of 2019. To analyze the atmospheric stability of rain events and mesoscale atmospheric phenomena, convective available potential energy (CAPE) and storm relative helicity (SRH) were calculated and compared. In particular, SRH analysis was divided into four levels based on the depth of the atmosphere (0-1, 0-3, 0-6, and 0-10 km). The rain events were categorized into three cases: that of no rain, that of 12 h before the rain, and that of rain. The results showed that SRH was more suitable than CAPE for the prediction of the rainfall events in Boseong during the summer of 2019, and that the rainfall events occurred when the 0-6 km SRH was 150 m² s^-2 or more, which is the same standard as that for a possible weak tornado. In addition, the results of the atmospheric stability analysis during the Changma, which is the rainy period in the Korean Peninsula during the summer and typhoon seasons, showed that the 0-6 km SRH was larger than the mean value of the 0-10 km SRH, whereas SRH generally increased as the depth of the atmosphere increased. Therefore, it can be said that the 0-6 km SRH was more effective in determining the rainfall events caused by typhoons in Boseong in the summer of 2019.

• Journal of the Korean Society of Radiology
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• v.82 no.2
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• pp.406-416
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• 2021

Purpose To evaluate the association between magnetic resonance imaging (MRI)-based texture parameters and Kirsten rat sarcoma viral oncogene homolog (KRAS) mutation in patients with non-mucinous rectal cancer. Materials and Methods Seventy-nine patients who had pathologically confirmed rectal non-mucinous adenocarcinoma with or without KRAS-mutation and had undergone rectal MRI were divided into a training (n = 46) and validation dataset (n = 33). A texture analysis was performed on the axial T2-weighted images. The association was statistically analyzed using the Mann-Whitney U test. To extract an optimal cut-off value for the prediction of KRAS mutation, a receiver operating characteristic curve analysis was performed. The cut-off value was verified using the validation dataset. Results In the training dataset, skewness in the mutant group (n = 22) was significantly higher than in the wild-type group (n = 24) (0.221 ± 0.283; -0.006 ± 0.178, respectively, p = 0.003). The area under the curve of the skewness was 0.757 (95% confidence interval, 0.606 to 0.872) with a maximum accuracy of 71%, a sensitivity of 64%, and a specificity of 78%. None of the other texture parameters were associated with KRAS mutation (p > 0.05). When a cut-off value of 0.078 was applied to the validation dataset, this had an accuracy of 76%, a sensitivity of 86%, and a specificity of 68%. Conclusion Skewness was associated with KRAS mutation in patients with non-mucinous rectal cancer.

• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.23-46
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• 2017

Although there have been cases of evaluating the value of specific companies or projects which have centralized on developed countries in North America and Europe from the early 2000s, the system and methodology for estimating the economic value of individual technologies or patents has been activated on and on. Of course, there exist several online systems that qualitatively evaluate the technology's grade or the patent rating of the technology to be evaluated, as in 'KTRS' of the KIBO and 'SMART 3.1' of the Korea Invention Promotion Association. However, a web-based technology valuation system, referred to as 'STAR-Value system' that calculates the quantitative values of the subject technology for various purposes such as business feasibility analysis, investment attraction, tax/litigation, etc., has been officially opened and recently spreading. In this study, we introduce the type of methodology and evaluation model, reference information supporting these theories, and how database associated are utilized, focusing various modules and frameworks embedded in STAR-Value system. In particular, there are six valuation methods, including the discounted cash flow method (DCF), which is a representative one based on the income approach that anticipates future economic income to be valued at present, and the relief-from-royalty method, which calculates the present value of royalties' where we consider the contribution of the subject technology towards the business value created as the royalty rate. We look at how models and related support information (technology life, corporate (business) financial information, discount rate, industrial technology factors, etc.) can be used and linked in a intelligent manner. Based on the classification of information such as International Patent Classification (IPC) or Korea Standard Industry Classification (KSIC) for technology to be evaluated, the STAR-Value system automatically returns meta data such as technology cycle time (TCT), sales growth rate and profitability data of similar company or industry sector, weighted average cost of capital (WACC), indices of industrial technology factors, etc., and apply adjustment factors to them, so that the result of technology value calculation has high reliability and objectivity. Furthermore, if the information on the potential market size of the target technology and the market share of the commercialization subject refers to data-driven information, or if the estimated value range of similar technologies by industry sector is provided from the evaluation cases which are already completed and accumulated in database, the STAR-Value is anticipated that it will enable to present highly accurate value range in real time by intelligently linking various support modules. Including the explanation of the various valuation models and relevant primary variables as presented in this paper, the STAR-Value system intends to utilize more systematically and in a data-driven way by supporting the optimal model selection guideline module, intelligent technology value range reasoning module, and similar company selection based market share prediction module, etc. In addition, the research on the development and intelligence of the web-based STAR-Value system is significant in that it widely spread the web-based system that can be used in the validation and application to practices of the theoretical feasibility of the technology valuation field, and it is expected that it could be utilized in various fields of technology commercialization.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.219-239
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• 2019

As the importance of providing customized services to individuals becomes important, researches on personalized recommendation systems are constantly being carried out. Collaborative filtering is one of the most popular systems in academia and industry. However, there exists limitation in a sense that recommendations were mostly based on quantitative information such as users' ratings, which made the accuracy be lowered. To solve these problems, many studies have been actively attempted to improve the performance of the recommendation system by using other information besides the quantitative information. Good examples are the usages of the sentiment analysis on customer review text data. Nevertheless, the existing research has not directly combined the results of the sentiment analysis and quantitative rating scores in the recommendation system. Therefore, this study aims to reflect the sentiments shown in the reviews into the rating scores. In other words, we propose a new algorithm that can directly convert the user 's own review into the empirically quantitative information and reflect it directly to the recommendation system. To do this, we needed to quantify users' reviews, which were originally qualitative information. In this study, sentiment score was calculated through sentiment analysis technique of text mining. The data was targeted for movie review. Based on the data, a domain specific sentiment dictionary is constructed for the movie reviews. Regression analysis was used as a method to construct sentiment dictionary. Each positive / negative dictionary was constructed using Lasso regression, Ridge regression, and ElasticNet methods. Based on this constructed sentiment dictionary, the accuracy was verified through confusion matrix. The accuracy of the Lasso based dictionary was 70%, the accuracy of the Ridge based dictionary was 79%, and that of the ElasticNet (${\alpha}=0.3$) was 83%. Therefore, in this study, the sentiment score of the review is calculated based on the dictionary of the ElasticNet method. It was combined with a rating to create a new rating. In this paper, we show that the collaborative filtering that reflects sentiment scores of user review is superior to the traditional method that only considers the existing rating. In order to show that the proposed algorithm is based on memory-based user collaboration filtering, item-based collaborative filtering and model based matrix factorization SVD, and SVD ++. Based on the above algorithm, the mean absolute error (MAE) and the root mean square error (RMSE) are calculated to evaluate the recommendation system with a score that combines sentiment scores with a system that only considers scores. When the evaluation index was MAE, it was improved by 0.059 for UBCF, 0.0862 for IBCF, 0.1012 for SVD and 0.188 for SVD ++. When the evaluation index is RMSE, UBCF is 0.0431, IBCF is 0.0882, SVD is 0.1103, and SVD ++ is 0.1756. As a result, it can be seen that the prediction performance of the evaluation point reflecting the sentiment score proposed in this paper is superior to that of the conventional evaluation method. In other words, in this paper, it is confirmed that the collaborative filtering that reflects the sentiment score of the user review shows superior accuracy as compared with the conventional type of collaborative filtering that only considers the quantitative score. We then attempted paired t-test validation to ensure that the proposed model was a better approach and concluded that the proposed model is better. In this study, to overcome limitations of previous researches that judge user's sentiment only by quantitative rating score, the review was numerically calculated and a user's opinion was more refined and considered into the recommendation system to improve the accuracy. The findings of this study have managerial implications to recommendation system developers who need to consider both quantitative information and qualitative information it is expect. The way of constructing the combined system in this paper might be directly used by the developers.

• Journal of Korean Society of Environmental Engineers
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• v.32 no.1
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• pp.33-46
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• 2010

We investigated and estimated at the characteristics of decomposition and by-products of N-Nitrosodimethylamine (NDMA) using a design of experiment (DOE) based on the Box-Behken design in an UV process, and also the main factors (variables) with UV intensity($X_2$) (range: $1.5{\sim}4.5\;mW/cm^2$), NDMA concentration ($X_2$) (range: 100~300 uM) and pH ($X_2$) (rang: 3~9) which consisted of 3 levels in each factor and 4 responses ($Y_1$ (% of NDMA removal), $Y_2$ (dimethylamine (DMA) reformation (uM)), $Y_3$ (dimethylformamide (DMF) reformation (uM), $Y_4$ ($NO_2$-N reformation (uM)) were set up to estimate the prediction model and the optimization conditions. The results of prediction model and optimization point using the canonical analysis in order to obtain the optimal operation conditions were $Y_1$ [% of NDMA removal] = $117+21X_1-0.3X_2-17.2X_3+{2.43X_1}^2+{0.001X_2}^2+{3.2X_3}^2-0.08X_1X_2-1.6X_1X_3-0.05X_2X_3$ ($R^2$= 96%, Adjusted $R^2$ = 88%) and 99.3% ($X_1:\;4.5\;mW/cm^2$, $X_2:\;190\;uM$, $X_3:\;3.2$), $Y_2$ [DMA conc] = $-101+18.5X_1+0.4X_2+21X_3-{3.3X_1}^2-{0.01X_2}^2-{1.5X_3}^2-0.01X_1X_2+0.07X_1X_3-0.01X_2X_3$ ($R^2$= 99.4%, 수정 $R^2$ = 95.7%) and 35.2 uM ($X_1$: 3 $mW/cm^2$, $X_2$: 220 uM, $X_3$: 6.3), $Y_3$ [DMF conc] = $-6.2+0.2X_1+0.02X_2+2X_3-0.26X_1^2-0.01X_2^2-0.2X_3^2-0.004X_1X_2+0.1X_1X_3-0.02X_2X_3$ ($R^2$= 98%, Adjusted $R^2$ = 94.4%) and 3.7 uM ($X_1:\;4.5\;$mW/cm^2$, $X_2:\;290\;uM$, $X_3:\;6.2$) and $Y_4$ [$NO_2$-N conc] = $-25+12.2X_1+0.15X_2+7.8X_3+{1.1X_1}^2+{0.001X_2}^2-{0.34X_3}^2+0.01X_1X_2+0.08X_1X_3-3.4X_2X_3$ ($R^2$= 98.5%, Adjusted $R^2$ = 95.7%) and 74.5 uM ($X_1:\;4.5\;mW/cm^2$, $X_2:\;220\;uM$, $X_3:\;3.1$). This study has demonstrated that the response surface methodology and the Box-Behnken statistical experiment design can provide statistically reliable results for decomposition and by-products of NDMA by the UV photolysis and also for determination of optimum conditions. Predictions obtained from the response functions were in good agreement with the experimental results indicating the reliability of the methodology used.