• Journal of Korean Society of Forest Science
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• v.95 no.4
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• pp.483-494
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• 2006

We conducted QTL mapping for 6-year growths of open-pollinated half-sib progenies from a selected clone 7-1037 in Pinus taeda. With an AFLP marker analysis on haploid DNA samples from the megagametophytes of the open-pollinated seeds, we constructed 20 framework maps spanning a total of 1,869 cM in total length and 18.5 cM in an average interval length between markers. Composite interval mapping reveals that one QTL explains 5.9% of the total phenotypic variation of height, and three QTLs account for 3.9~5.6% of the variation of diameter at breast height (DBH). There are no correlations between the QTLs. The genetic effects of the QTLs are 39.6 cm in height and 7.20~9.41 mm in DBH, respectively, The average effects of gene substitution of the markers closely linked with the QTLs are 44.3 cm in height and 8.38~11.81 m in DBH. Under an assumption that the within-family heritability for the growth traits of loblolly pine is less than 0.2, the QTLs account for 26.8% of the additive genetic variance of the progenies. In terms of relative selection efficiency, the individual selection based on QTL markers could be 5 times as high as phenotypic selection. The results in this study indicate that the QTL mapping method with open-pollinated half-sib family could be more practical and applicable to the conventional seed orchard-based selection work than other mapping methods with a single full-sib family, in particular from the viewpoint that it can provide crucial information for within-family individual selection such as breeding value.

• Restorative Dentistry and Endodontics
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• v.32 no.3
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• pp.208-221
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• 2007

The fracture toughness test is believed as a clinically relevant method for assessing the fracture resistance of the dentinal restoratives. The objectives of this study were to measure the fracture toughness $(K_{1C})$ and microtensile bond strength of dentin-resin composite interface and compare their relationship for their use in evaluation of the integrity of the dentin-resin bond. A minimum of six short-rod specimens for fracture toughness test and fifteen specimens for microtensile bond strength test was fabricated for each group of materials used. After all specimens storing for 24 hours in distilled water at $37^{\circ}C$, they were tensile-loaded with an EZ tester universal testing machin. Statistical analysis was performed using ANOVA and Tukey's test at the 95% confidence level, Pearson's coefficient was used to verify the correlation between the mean of fracture toughness and microtensile bond strength. FE-SEM was employed on fractured surface to describe the crack propagation. Fracture toughness value of Clearfil SE Bond (SE) was the highest, followed by Adper Single Bond 2 (SB), OptiBond Solo (OB), ONE-STEP PLUS (0S), ScotchBond Multi-purpose (SM) and there was significant difference between SE and other 4 groups (p < 0.05). There were, however, no significant difference among SB, OB, OS, SM (p > 0.05). Microtensile bond strength of SE was the highest, followed by SB, OB, SM, OS and OS only showed significant lower value (p < 0.05). There was no correlation between fracture toughness and microtensile bond strength values. FE-SEM examination revealed that dentin bonding agent showed different film thickness and different failure pattern according to the film thickness. From the limited results of this study, it was noted that there was statistically no correlation between K1C and ${\mu}TBS$. We can conclude that for obtaining the reliability of bond strength test of dentin bonding agent, we must pay more attention to the test procedure and its profound scrutiny.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.99-118
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• 2015

Object-oriented programming languages have been widely selected for developing modern information systems. The use of concepts relating to object-oriented (OO, in short) programming has reduced efforts of reusing pre-existing codes, and the OO concepts have been proved to be a useful in interpreting system requirements. In line with this, we have witnessed that a modern conceptual modeling approach supports features of object-oriented programming. Unified Modeling Language or UML becomes one of de-facto standards for information system designers since the language provides a set of visual diagrams, comprehensive frameworks and flexible expressions. In a modeling process, UML users need to consider relationships between classes. Based on an explicit and clear representation of classes, the conceptual model from UML garners necessarily attributes and methods for guiding software engineers. Especially, identifying an association between a class of part and a class of whole is included in the standard grammar of UML. The representation of part-whole relationship is natural in a real world domain since many physical objects are perceived as part-whole relationship. In addition, even abstract concepts such as roles are easily identified by part-whole perception. It seems that a representation of part-whole in UML is reasonable and useful. However, it should be admitted that the use of UML is limited due to the lack of practical guidelines on how to identify a part-whole relationship and how to classify it into an aggregate- or a composite-association. Research efforts on developing the procedure knowledge is meaningful and timely in that misleading perception to part-whole relationship is hard to be filtered out in an initial conceptual modeling thus resulting in deterioration of system usability. The current method on identifying and classifying part-whole relationships is mainly counting on linguistic expression. This simple approach is rooted in the idea that a phrase of representing has-a constructs a par-whole perception between objects. If the relationship is strong, the association is classified as a composite association of part-whole relationship. In other cases, the relationship is an aggregate association. Admittedly, linguistic expressions contain clues for part-whole relationships; therefore, the approach is reasonable and cost-effective in general. Nevertheless, it does not cover concerns on accuracy and theoretical legitimacy. Research efforts on developing guidelines for part-whole identification and classification has not been accumulated sufficient achievements to solve this issue. The purpose of this study is to provide step-by-step guidelines for identifying and classifying part-whole relationships in the context of UML use. Based on the theoretical work on Meta-model Formalization, self-check forms that help conceptual modelers work on part-whole classes are developed. To evaluate the performance of suggested idea, an experiment approach was adopted. The findings show that UML users obtain better results with the guidelines based on Meta-model Formalization compared to a natural language classification scheme conventionally recommended by UML theorists. This study contributed to the stream of research effort about part-whole relationships by extending applicability of Meta-model Formalization. Compared to traditional approaches that target to establish criterion for evaluating a result of conceptual modeling, this study expands the scope to a process of modeling. Traditional theories on evaluation of part-whole relationship in the context of conceptual modeling aim to rule out incomplete or wrong representations. It is posed that qualification is still important; but, the lack of consideration on providing a practical alternative may reduce appropriateness of posterior inspection for modelers who want to reduce errors or misperceptions about part-whole identification and classification. The findings of this study can be further developed by introducing more comprehensive variables and real-world settings. In addition, it is highly recommended to replicate and extend the suggested idea of utilizing Meta-model formalization by creating different alternative forms of guidelines including plugins for integrated development environments.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.39-54
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• 2013

Recent explosive increase of electronic commerce provides many advantageous purchase opportunities to customers. In this situation, customers who do not have enough knowledge about their purchases, may accept product recommendations. Product recommender systems automatically reflect user's preference and provide recommendation list to the users. Thus, product recommender system in online shopping store has been known as one of the most popular tools for one-to-one marketing. However, recommender systems which do not properly reflect user's preference cause user's disappointment and waste of time. In this study, we propose a novel recommender system which uses data mining and multi-model ensemble techniques to enhance the recommendation performance through reflecting the precise user's preference. The research data is collected from the real-world online shopping store, which deals products from famous art galleries and museums in Korea. The data initially contain 5759 transaction data, but finally remain 3167 transaction data after deletion of null data. In this study, we transform the categorical variables into dummy variables and exclude outlier data. The proposed model consists of two steps. The first step predicts customers who have high likelihood to purchase products in the online shopping store. In this step, we first use logistic regression, decision trees, and artificial neural networks to predict customers who have high likelihood to purchase products in each product group. We perform above data mining techniques using SAS E-Miner software. In this study, we partition datasets into two sets as modeling and validation sets for the logistic regression and decision trees. We also partition datasets into three sets as training, test, and validation sets for the artificial neural network model. The validation dataset is equal for the all experiments. Then we composite the results of each predictor using the multi-model ensemble techniques such as bagging and bumping. Bagging is the abbreviation of "Bootstrap Aggregation" and it composite outputs from several machine learning techniques for raising the performance and stability of prediction or classification. This technique is special form of the averaging method. Bumping is the abbreviation of "Bootstrap Umbrella of Model Parameter," and it only considers the model which has the lowest error value. The results show that bumping outperforms bagging and the other predictors except for "Poster" product group. For the "Poster" product group, artificial neural network model performs better than the other models. In the second step, we use the market basket analysis to extract association rules for co-purchased products. We can extract thirty one association rules according to values of Lift, Support, and Confidence measure. We set the minimum transaction frequency to support associations as 5%, maximum number of items in an association as 4, and minimum confidence for rule generation as 10%. This study also excludes the extracted association rules below 1 of lift value. We finally get fifteen association rules by excluding duplicate rules. Among the fifteen association rules, eleven rules contain association between products in "Office Supplies" product group, one rules include the association between "Office Supplies" and "Fashion" product groups, and other three rules contain association between "Office Supplies" and "Home Decoration" product groups. Finally, the proposed product recommender systems provides list of recommendations to the proper customers. We test the usability of the proposed system by using prototype and real-world transaction and profile data. For this end, we construct the prototype system by using the ASP, Java Script and Microsoft Access. In addition, we survey about user satisfaction for the recommended product list from the proposed system and the randomly selected product lists. The participants for the survey are 173 persons who use MSN Messenger, Daum Caf$\acute{e}$, and P2P services. We evaluate the user satisfaction using five-scale Likert measure. This study also performs "Paired Sample T-test" for the results of the survey. The results show that the proposed model outperforms the random selection model with 1% statistical significance level. It means that the users satisfied the recommended product list significantly. The results also show that the proposed system may be useful in real-world online shopping store.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.4
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• pp.93-99
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• 2019

The purpose of this study was to investigate the bond strength between PEKK(Polyetherketoneketone) and Sinfony(3M ESPE, Seefeld, Germany) the dental composite resin by proposing the three representative surface treatment methods and evaluate to see if they affect the bond strength between two materials. A total of 30 PEKK($Pekkton^{(R)}$ Ivory, $Cendres+M{\acute{e}}taux$, Bienne, Switzerland) specimens were prepared, embedded in acrylic resin, polished(P 1200 grid) to surface, and each group was divided into 10 specimens. After then, by the surface treatment method, it classified into three groups(n=10) such as Air abrasion group(PN), applying Single Bond Universal(3M ESPE) after Air abrasion(PB), applying OPAQUE(3M ESPE) after Air abrasion(PO). Then, veneering was performed by using Sinfony(3M ESPE, Seefeld, Germany). All completed specimens were allowed to rest in a $37^{\circ}C$ water bath for 24 hours. Shear bond strength of each group was measured and fracture patterns were classified. Statistic analysis was performed with One-way ANOVA followed by post hoc Scheffe tast (p<.05). Statistical analysis was performed using the SPSSWIN 21.0 program. As a result of one-way ANOVA, the average value of PB group was $27.67{\pm}4,18MPa$ and it was shown as the highest bond strength, PN and PO were $20.43{\pm}1.70$ and $19.8{\pm}4.77MPa$ each, and these were relatively low(F=18.4, P<.001), and as the post-test the Scheffe test was conducted and verified (p<.05). After examining the scheffe test, it was showed significant differences as PB>PO, PB>PN(p<.001). Through this study, in order to enhance the bonding force between PEKK and the composite resin, perform the Air abrasion and surface treatment by using Single Bond Universal(3M ESPE) is recommended, and as coMPared with other studies. And it is assumed that the increase of the application time of the Air abrasion affects the increase of the shear bond strength. Thus, further research is required.

• KSBB Journal
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• v.22 no.5
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• pp.297-304
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• 2007

For large and rapid screening of high-yielding mutants of lovastatin produced by filamentous fungal cells of Aspergillus terreus, one of the most important stage is to test as large amounts of mutated strains as possible. For this purpose, we intended to develop a miniaturized cultivation method using $7m{\ell}$ culture tube instead of traditional $250m{\ell}$ flask (working volume $50m{\ell}$). For obtaining large amounts of conidiospores to be used as inoculums for miniaturized cultures, 4 components i.e., glucose, sucrose, yeast extract and $KH_2PO_4$ were intensively investigated, which had been observed to show positive effect on enhancement of spore production through Plackett-Burman design experimet. When optimum concentrations of these components that were determined through application of response surface method (RSM) based on central composite design (CCD) were used, maximum spore numbers amounting to $1.9\times10^{10}$ spores/plate were obtained, resulting in approximately 190 fold increase as compared to the commonly used PDA sporulation medium. Using the miniaturized cultures, intensive strain development programs were carried out for screening of lovastatin high-yielding as well as highly reproducible mutants. It was observed that, for maximum production of lovastatin, the producers should be activated through 'PaB' adaptation process during the early solid culture stage. In addition, they should be proliferated in condensed filamentous forms in miniaturized growth cultures, so that optimum amounts of highly active cells could be transferred to the production culture-tube as reproducible inoculums. Under these highly controlled fermentation conditions, compact-pelleted morphology of optimum size (less than 1 mm in diameter) was successfully induced in the miniaturized production cultures, which proved essential for maximal utilization of the producers' physiology leading to significantly enhanced production of lovastatin. As a result of continuous screening in the miniaturized cultures, lovastatin production levels of the 81% of the daughter cells derived from the high-yielding producers turned out to be in the range of 80%$\sim$120% of the lovastatin production level of the parallel flask cultures. These results demonstrate that the miniaturized cultivation method developed in this study is efficient high throughput system for large and rapid screening of highly stable and productive strains.

• KSBB Journal
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• v.24 no.1
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• pp.30-40
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• 2009

Statistical optimization of the production medium was carried out in order to find an optimal medium composition in itaconic acid fermentation process. Itaconic acid utilized in the manufacture of various synthetic resins is a dicarboxylic acid biosynthesized by fungal cells of Aspergillus terreus in a branch of the TCA cycle via decarboxylation of cis-aconitate. Through OFAT (one factor at a time) experiments, six components (glucose, fructose, sucrose, soluble starch, soybean meal and cottonseed flour) were found to have significant effects on itaconic production among various carbon- and nitrogen-sources. Hence, using these six factors, interactive effects were investigated via fractional factorial design, showing that the initial concentrations of sucrose and cottonseed flour should be high for enhanced production of itaconic acid. Furthermore, through full factorial design (FFD) experiments, negative effects of $KH_2PO_4$ and $MgSO_4$ on itaconic acid biosynthesis were demonstrated, when excess amounts of the each component were initially added. Based on the FFD analysis, further statistical experiments were conducted along the steepest ascent path, followed by response surface method (RSM) in order to obtain optimal concentrations of the constituent nutrients. As a result, optimized concentrations of sucrose and cottonseed flour were found to be 90.4g/L and 53.8g/L respectively, with the corresponding production level of itaconic acid to be 4.36 g/L (about 7 fold higher productivity as compared to the previous production medium). From these experimental results, it was assumed that optimum ratio of the constituent carbon (sucrose) and nitrogen (cottonseed flour) sources was one of the most important factors for the enhanced production of itaconic acid.

• Progress in Medical Physics
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• v.21 no.2
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• pp.201-208
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• 2010

Recently, along with technology development of endoscopic equipment, a stent has been developed for the convenience of operation, shortening of recovery times, and reduction of patient's pain. To this end, optimal factors are simulated for the stent structure and mechanical reaction and verified using finite element analysis. In order to compare to present commercialized product such as Zilver (Cook, Bloomington, Indiana, USA) and S.M.A.R.T (Cordis, Bridgewater Towsnhip, New Jersey, USA), mechanical impact factors were determined through Taguchi factor analysis, and flexibility and expandability of all the products including ours were tested using finite element analysis. Also, important factors were sought that fulfill the optimal condition using central composition method of response surface analysis, and optimal design were carried out based on the important factors. From the centra composition method of Response surface analysis, it is found that importat factors for flexibility is stent thickness (T) and unit area (W) and those for expandability is stent thickness (T). In results, important factors for optimum condition are 0.17 mm for stent thickness (T) and $0.09\;mm^2$ for unit area (W). Determined and verified by finite element analysis in out research institute, a stent was manufactured and tested with the results of better flexibility and expandability in optimal condition compared to other products. Recently, As Finite element analysis stent mechanical property assessment for research much proceed. But time and reduce expenses research rarely stent of optimum coditions. In this research, Important factor as mechanical impact factor stent Taguchi factor analysis arrangement to find flexibility with expansibility as Finite element analysis. Also, Using to Center composition method of Response surface method appropriate optimized condition searching for important factor, these considering had design optimized. Production stent time and reduce expenses was able to do the more coincide with optimum conditions. These kind of things as application plan industry of stent development period of time and reduce expenses etc. be of help to many economic development.

• Journal of Environmental Impact Assessment
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• v.28 no.4
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• pp.387-399
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• 2019

This research aimed to prepare the classification of the damage types and the damage rating system of noise barriers for expressway noise barriers and to develop deterioration evaluation method of noise barriers by reflecting them. The noise barrier consists of soundproof panels, foundations and posts and the soundproof panels with 10 different types of materials are used in a single or mixed form.In this paper, damage of soundproof panel shows a single or composite damage, and thus a evaluation model of deterioration has been developed for noise barriers that can reflect the characteristic of noise barriers. Materials used mainly for soundproof walls were divided into material types for metal, plastic, timber, transparent and concrete. And damage types for noise barrier were classified into corrosion, discoloration, deformation, spalling and dislocation and damage types were subdivided according to the noise barrier's components and materials. Damage rating was divided into good, minor, normal and severe for each major part of noise barrier to assess damage rating of soundproof panel, foundation and post. The deterioration degree of noise barrier was evaluated comprehensively by using the deterioration evaluation method of whole noise barrier using weighted average. Deterioration evaluation method that can be systematically assessed has been developed for noise barrier using single or mixed soundproof panel and noise barrier with single or complex damage types. Through such an evaluation system, it is deemed that the deterioration status of noise barrier installed can be systematically understood and utilized for efficient maintenance planning and implementation for repair and improvement of noise barriers.

• Journal of Soil and Groundwater Environment
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• v.18 no.1
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• pp.26-35
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• 2013

Outbreak of animal infectious diseases such as foot-and-mouth disease, avian influenza are becoming prevalent worldwide. For prevent the further infection, tremendous numbers of the infected or culled stocks are buried around farm. This burial method can generate a wide range of detrimental components such as leachate, nutrient, salt, and pathogenic bacteria, consequently. In this study, for the stabilization of livestock carcasses leachate, advanced oxidation processes utilizing the Fenton reaction was investigated in lab-scale experiments for the treatment for $COD_{Cr}$ of livestock carcass leachate. $COD_{Cr}$ reduction by the Fenton oxidation was investigated response surface methodology using the Box-Begnken methods were applied to the experimental results. A central composite design was used to investigate the effects of the independent variables of pH ($x_1$), dosage of $FeCl_2{\cdot}4H_2O$ ($x_2$) and dosage of $H_2O_2$ ($x_3$) on the dependent variables $COD_{Cr}$ concentration ($y_1$). A 1 M NaOH and $H_2SO_4$ was using for pH control, $FeCl_2{\cdot}4H_2O$ was used as iron catalyst and NaOH was used for Fenton reaction. The optimal conditions for Fenton oxidation process were determined: pH, dosage of $FeCl_2{\cdot}4H_2O$ and dosage of $H_2O_2$ were 3, 0.6 g (0.0151 M) and 7 mL(0.259 M), respectively. Statistical results showed the order of significance of the independent variables to be pH > initial concentration of ferrous ion > initial concentration of hydrogen peroxide.