• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.263-286
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• 2022

This study acquires NBA statistical information for a total of 32 years from 1990 to 2022 using web crawling, observes variables of interest through exploratory data analysis, and generates related derived variables. Unused variables were removed through a purification process on the input data, and correlation analysis, t-test, and ANOVA were performed on the remaining variables. For the variable of interest, the difference in the mean between the groups that advanced to the playoffs and did not advance to the playoffs was tested, and then to compensate for this, the average difference between the three groups (higher/middle/lower) based on ranking was reconfirmed. Of the input data, only this year's season data was used as a test set, and 5-fold cross-validation was performed by dividing the training set and the validation set for model training. The overfitting problem was solved by comparing the cross-validation result and the final analysis result using the test set to confirm that there was no difference in the performance matrix. Because the quality level of the raw data is high and the statistical assumptions are satisfied, most of the models showed good results despite the small data set. This study not only predicts NBA game results or classifies whether or not to advance to the playoffs using machine learning, but also examines whether the variables of interest are included in the major variables with high importance by understanding the importance of input attribute. Through the visualization of SHAP value, it was possible to overcome the limitation that could not be interpreted only with the result of feature importance, and to compensate for the lack of consistency in the importance calculation in the process of entering/removing variables. It was found that a number of variables related to three points and errors classified as subjects of interest in this study were included in the major variables affecting advancing to the playoffs in the NBA. Although this study is similar in that it includes topics such as match results, playoffs, and championship predictions, which have been dealt with in the existing sports data analysis field, and comparatively analyzed several machine learning models for analysis, there is a difference in that the interest features are set in advance and statistically verified, so that it is compared with the machine learning analysis result. Also, it was differentiated from existing studies by presenting explanatory visualization results using SHAP, one of the XAI models.

• Korean Journal of Plant Resources
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• v.28 no.1
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• pp.101-110
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• 2015

Parameters of mating system and pollen flow of a Pinus densiflora population in Buan, South Korea, were estimated using seven nuclear microsatellite markers. The expected heterozygosity ($H_e$) was 0.614 in mother trees and 0.624 in seeds. Fixation index (F) was 0.018 and 0.087 in each generation. There was no significant genetic difference between the generations (P > 0.05). From MLTR, the outcrossing rate ($t_m$), the biparental inbreeding ($t_m-t_s$), and the correlation of paternity ($r_p$) were 0.967, 0.057, and 0.012, respectively. tm was larger but $t_m-t_s$ and $r_p$ were smaller than those of allozyme markers in Pinus densiflora. These values were similar to those of microsatellite markers in other pine species. The optimal pollen dispersal model from TwoGener was the normal dispersal model with the effective density of 220 trees/ha and its level of genetic differentiation in pollen pool structure (${\Phi}_{ft}$) was 0.021. The average radial distance of pollen flow (${\delta}$) was calculated as 11.42 m, but no correlation between the pairwise-${\Phi}_{ft}$ and the geographical distance among mother trees was at Mantel test (r = -0.141, P > 0.05). Although the effective pollen dispersal in the population seems to be restricted, the amount of genetic variation might be maintained in each generation without a loss of genetic diversity. It might be because the genetic diversity in pollen pool was high but the genetic difference between pollen donors was small under the complete random mating condition in the Pinus densiflora population in Buan.

• Korean Journal of Agricultural Science
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• v.22 no.1
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• pp.1-10
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• 1995

All agricultural crops and products should be cultured, harvested, handled and processed by the proper mechanical methods in the mechanized farming systems. Agricultural crops might be injured or deformed through various working stages due to static or dynamic forces of machines. Mechanical forces had to be applied with proper degrees to the agricultural crops in incoincidence with properties of crops without any damage of crops so as to increase the work efficiency qualitatively. Knowledges of mechanical properties of agricultural materials are essential to prevent of agricultural crops in relation with mechanical farming system. This study was carried out to examine and analyze the creep behavior of the rice stalk on growing and harvesting periods by mechanical model with computer measurement system in radial directional compressive force and bending force. The creep behavior of the rice stalk could be predicted precisely and its results approached closely to the measured values. The creep behaviors were increased greatly with increase of compressive force, namely, the steady state creep behavior occurred at the force less then 25N and the logarithmic creep behavior at the force bigger than 30N. The instantaneous elastic modulus $E_o$ and the retardation time ${\tau}_K$ were increased together with increase of applied forces, meanwhile the retarded elastic modulus $E_r$ and viscosity ${\eta}_v$ were decreased with increase of applied forces in mechanical model being expected the creep behavior in relation with the level of applied forces, which was well explained that the rice stalk might be visvo-elastic material. In the creep test along the stalk portion with compressive force and bending force, the intermediate portion showed greatest values and also the lower portion showed the least values, which implied that the intermediate portions of rice stalk were very weak. The steady state creep behavior occured at the intermediate portion and the upper portion in the rice stalk at the compressive force larger than 25.0N, which showed the possibility of injury due to external forces.

• The Journal of Korean Academy of Prosthodontics
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• v.46 no.5
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• pp.528-534
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• 2008

Purpose: Marginal fit is one of the important components for the successful prosthodontic restoration. Poor fitting margin of the restoration causes hypersensitivity, secondary caries, and plaque accumulation, which later result in prosthodontic failure. CAD/CAM zirconia all-ceramic restorations, such as $LAVA^{(R)}$ (3M ESPE, St.Paul, MN) and $EVEREST^{(R)}$ (KaVo Dental GmbH, Biberach, Germany) systems were recently introduced in Korea. It is clinically meaningful to evaluate the changes of the marginal fit of the CAD/CAM zirconia systems before and after build-up. The purposes of this study are to compare the marginal fit of the two CAD/CAM all-ceramic systems with that of the ceramometal restoration, before and after porcelain build-up Material and methods: A maxillary first premolar dentiform tooth was prepared with 2.0 mm occlusal reduction, 1.0 mm axial reduction, chamfer margin, and 6 degree taperness in the axial wall. The prepared dentiform die was duplicated into the metal abutment die. The metal die was placed in the dental study model, and the full arch impressions of the model were made. Twenty four copings of 3 groups which were $LAVA^{(R)}$, $EVEREST^{(R)}$, and ceramometal restorations were fabricated. Each coping was cemented on the metal die with color-mixed Fit-checker $II^{(R)}$ (GC Cor., Tokyo, Japan). The marginal opening of each coping was measured with $Microhiscope^{(R)}$ system (HIROX KH-1000 ING-Plus, Seoul, Korea. X300 magnification). After porcelain build-up, the marginal openings of $LAVA^{(R)}$, $EVEREST^{(R)}$,and ceramometal restorations were also evaluated in the same method. Statistical analysis was done with paired t-test and one-way ANOVA test. Results: In coping states, the mean marginal opening for $EVEREST^{(R)}$ restorations was $52.00{\pm}11.94\;{\mu}m$ for $LAVA^{(R)}$ restorations $56.97{\pm}10.00\;{\mu}m$, and for ceramometal restorations $97.38{\pm}18.54\;{\mu}m$. After porcelain build-up, the mean marginal opening for $EVEREST^{(R)}$ restorations was $61.69{\pm}19.33\;{\mu}m$, for $LAVA^{(R)}$ restorations $70.81{\pm}12.99\;{\mu}m$, and for ceramometal restorations $1115.25{\pm}23.86\;{\mu}m$. Conclusion: 1. $LAVA^{(R)}$ and $EVEREST^{(R)}$ restorations in comparison with ceramometal restorations showed better marginal fit, which had significant differences (P < 0.05) in coping state and also after porcelain build-up . 2. The mean marginal opening values between $LAVA^{(R)}$ and $EVEREST^{(R)}$ restorations did not showed significant differences after porcelain build-up as well as in coping state (P > .05). 3. $EVEREST^{(R)}$, $LAVA^{(R)}$ and ceramometal restorations showed a little increased marginal opening after porcelain build-up, but did not show any statistical significance (P > .05).

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.1-17
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• 2017

The deep learning framework is software designed to help develop deep learning models. Some of its important functions include "automatic differentiation" and "utilization of GPU". The list of popular deep learning framework includes Caffe (BVLC) and Theano (University of Montreal). And recently, Microsoft's deep learning framework, Microsoft Cognitive Toolkit, was released as open-source license, following Google's Tensorflow a year earlier. The early deep learning frameworks have been developed mainly for research at universities. Beginning with the inception of Tensorflow, however, it seems that companies such as Microsoft and Facebook have started to join the competition of framework development. Given the trend, Google and other companies are expected to continue investing in the deep learning framework to bring forward the initiative in the artificial intelligence business. From this point of view, we think it is a good time to compare some of deep learning frameworks. So we compare three deep learning frameworks which can be used as a Python library. Those are Google's Tensorflow, Microsoft's CNTK, and Theano which is sort of a predecessor of the preceding two. The most common and important function of deep learning frameworks is the ability to perform automatic differentiation. Basically all the mathematical expressions of deep learning models can be represented as computational graphs, which consist of nodes and edges. Partial derivatives on each edge of a computational graph can then be obtained. With the partial derivatives, we can let software compute differentiation of any node with respect to any variable by utilizing chain rule of Calculus. First of all, the convenience of coding is in the order of CNTK, Tensorflow, and Theano. The criterion is simply based on the lengths of the codes and the learning curve and the ease of coding are not the main concern. According to the criteria, Theano was the most difficult to implement with, and CNTK and Tensorflow were somewhat easier. With Tensorflow, we need to define weight variables and biases explicitly. The reason that CNTK and Tensorflow are easier to implement with is that those frameworks provide us with more abstraction than Theano. We, however, need to mention that low-level coding is not always bad. It gives us flexibility of coding. With the low-level coding such as in Theano, we can implement and test any new deep learning models or any new search methods that we can think of. The assessment of the execution speed of each framework is that there is not meaningful difference. According to the experiment, execution speeds of Theano and Tensorflow are very similar, although the experiment was limited to a CNN model. In the case of CNTK, the experimental environment was not maintained as the same. The code written in CNTK has to be run in PC environment without GPU where codes execute as much as 50 times slower than with GPU. But we concluded that the difference of execution speed was within the range of variation caused by the different hardware setup. In this study, we compared three types of deep learning framework: Theano, Tensorflow, and CNTK. According to Wikipedia, there are 12 available deep learning frameworks. And 15 different attributes differentiate each framework. Some of the important attributes would include interface language (Python, C ++, Java, etc.) and the availability of libraries on various deep learning models such as CNN, RNN, DBN, and etc. And if a user implements a large scale deep learning model, it will also be important to support multiple GPU or multiple servers. Also, if you are learning the deep learning model, it would also be important if there are enough examples and references.

• Journal of Distribution Research
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• v.13 no.1
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• pp.1-33
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• 2008

As the interest in the business-to-business(B2B) electronic commerce is increasing, many companies are participating in the B2B e-Marketplaces. The e-Marketplace is defined as the virtual market that many players take part in to transact. The e-Marketplace has an influenced on the manner in which organizational buyers and sellers interact. As a result, it is important to develop an understanding of the behaviors of firms that use these electronic marketplaces. The purpose of this study is to develop a comprehensive model for trust and commitment of B2B e-Marketplace and empirically to examine their structural relationships. Drawing from trust and commitment theory in the interorganizational relationship and B2B electronic commerce context, this study identifies network externality, interactivity, justice, quality of information sharing, institutional assurance as the determinants of trust and commitment of e-Marketplace. The proposed model hypothesized that (1) trust is a function of network externality, interactivity, justice, quality of information sharing, institutional assurance, (2) attitudinal and behavioral commitment is a function of trust, (3) behavioral commitment is a function of attitudinal commitment. The proposed model is tested using organizational-level survey data from 187 buying organizations that conduct business in MRO e-Marketplaces. The data were tested by reliability test, correlation analysis, exploratory factor analysis, confirmatory factor analysis and covariance structure analysis. The results indicate that (1) trust is influenced by network externality, interactivity, justice, institutional assurance, (2) attitudinal commitment and behavioral commitment is influenced by trust (3) behavioral commitment is influenced by attitudinal commitment. Also, the empirical results confirmed that trust play a strong, central role in determinging e-Marketplace commitment. The key theoretical contribution of this research is that it begins to extend interorganizational information system literature in areas such as B2B Internet e-Marketplace. Managerially, this study contributes tn the understanding of the role of B2B e-Markeplace providers in Internet situation. And Limitations of this study and guidelines for future researches are also discussed.

• Journal of Distribution Research
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• v.15 no.1
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• pp.73-101
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• 2010

Using data collected from franchisees from Busan, we empirically examined the relationship both structural (tie strength), relational (trust), and cognitive (shared value) of social capital and between those dimensions and the patterns of economic performance and noneconomic performance (relationship continuity intention). So we established 9 hypotheses to test the structural relationship among dimensions of social capital and performances like below. H1: A franchisee's perceived tie strength with its franchisor will positively influence its trust in the franchisor. H2: A franchisee's perceived shared value with its franchisor will positively influence its trust in the franchisor. H3: A franchisee's perceived tie strength with its franchisor will positively influence its economic performance. H4: A franchisee's perceived shared value with its franchisor will positively influence its economic performance. H5: A franchisee's perceived trust in its franchisor will positively influence its economic performance. H6: A franchisee's perceived tie strength with its franchisor will positively influence its relationship continuity intention with the franchisor. H7: A franchisee's perceived shared value with its franchisor will positively influence its relationship continuity intention with the franchisor. H8: A franchisee's perceived trust in its franchisor will positively influence its relationship continuity intention with the franchisor. H9: A franchisee's perceived economic performance will positively influence its relationship continuity intention with the franchisor. The conceptual model specifying the relationship among dimensions of social capital and performances is presented in Fig. 1. Tests of the hypotheses were performed using a structural equation model. This model also reflected a good fit to the data ($\chi^2$=101.12 df=62 p=0.004, RMSEA=0.050 GFI=0.936 AGFI=0.895 NFI=0.959 CFI=0.986). The standardized solution estimated by the AMOS 7 program was for interpreting the structural results (Table 1). As was expected, tie strength and shared value were founded to be significant predictors of trust (H1 supported; H2 supported). Tie strength and trust have a significant positive effect on economic performance (H3 supported; H5 supported). But shared value have not a significant effect on economic performance (H4 Rejected). Tie strength were not associated with relationship continuity intention (H6 Rejected). While on the other higher shared value, trust, and economic performance have a significant effect on the relationship continuity intention (H7 supported; H8 supported; H9 supported). The results show integratedly that, first, tie strength does not affect directly but affects indirectly on relationship continuity intention via trust and economic performance. Second, shared goals affect directly and do indirectly via trust on relationship continuity intention. But shared goals does not affect via economic performance on relationship continuity intention. Finally, the study suggests important implications for both research and practice for franchise system especially.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.46 no.6
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• pp.453-458
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• 2001

The Rural Development Administration (RDA) of Korea now operates a system called Rice Variety Selection Tests (RVST), which are now being implemented in eight Agricultural Research and Extension Services located in eight province RVST's objective is to provide accurate yield estimates and to select well-adapted varieties to each province. Systematic evaluation of entries included in RVST is a highly important task to select the best-adapted varieties to specific location and to observe the performance of entries across a wide range of test sites within a region. The rice yield data in RVST for ordinary transplanting in Kangwon province during 1997-2000 were analyzed. The experiments were carried out in three replications of a random complete block design with eleven entries across five locations. Additive Main effects and Multiplicative Interaction (AMMI) model was employed to examine the interaction between genotype and environment (G$\times$E) in the biplot form. It was found that genotype variability was as high as 66％, followed by G$\times$E interaction variability, 21％, and variability by environment, 13％. G$\times$E interaction was partitioned into two significant (P＜0.05) principal components. Pattern analysis was used for interpretation on G$\times$E interaction and adaptibility. Major determinants among the meteorological factors on G$\times$E matrix were canopy minimum temperature, minimum relative humidity, sunshine hours, precipitation and mean cloud amount. Odaebyeo, Obongbyeo and Jinbubyeo were relatively stable varieties in all the regions. Furthermore, the most adapted varieties in each region, in terms of productivity, were evaluated.

• Asia pacific journal of information systems
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• v.23 no.2
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• pp.21-39
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• 2013

As the utilization of information technology and the turbulence of technological change increase in organizations, the adoption of IT outsourcing also grows to manage IT resource more effectively and efficiently. In this new way of IT management technique, service level management(SLM) process becomes critical to derive success from the outsourcing in the view of end users in organization. Even though much of the research on service level management or agreement have been done during last decades, the performance of the service level management process have not been evaluated in terms of final objectives of the management efforts or success from the view of end-users. This study explores the relationship between SLM maturity and IT outsourcing success from the users' point of view by a analytical case study in four client organizations under an IT outsourcing vendor, which is a member company of a major Korean conglomerate. For setting up a model for the analysis, previous researches on service level management process maturity and information systems success are reviewed. In particular, information systems success from users' point of view are reviewed based the DeLone and McLean's study, which is argued and accepted as a comprehensively tested model of information systems success currently. The model proposed in this study argues that SLM process maturity influences information systems success, which is evaluated in terms of information quality, systems quality, service quality, and net effect proposed by DeLone and McLean. SLM process maturity can be measured in planning process, implementation process and operation and evaluation process. Instruments for measuring the factors in the proposed constructs of information systems success and SL management process maturity were collected from previous researches and evaluated for securing reliability and validity, utilizing appropriate statistical methods and pilot tests before exploring the case study. Four cases from four different companies under one vendor company were utilized for the analysis. All of the cases had been contracted in SLA(Service Level Agreement) and had implemented ITIL(IT Infrastructure Library), Six Sigma and BSC(Balanced Scored Card) methods since last several years, which means that all the client organizations pursued concerted efforts to acquire quality services from IT outsourcing from the organization and users' point of view. For comparing the differences among the four organizations in IT out-sourcing sucess, T-test and non-parametric analysis have been applied on the data set collected from the organization using survey instruments. The process maturities of planning and implementation phases of SLM are found not to influence on any dimensions of information systems success from users' point of view. It was found that the SLM maturity in the phase of operations and evaluation could influence systems quality only from users' view. This result seems to be quite against the arguments in IT outsourcing practices in the fields, which emphasize usually the importance of planning and implementation processes upfront in IT outsourcing projects. According to after-the-fact observation by an expert in an organization participating in the study, their needs and motivations for outsourcing contracts had been quite familiar already to the vendors as long-term partners under a same conglomerate, so that the maturity in the phases of planning and implementation seems not to be differentiating factors for the success of IT outsourcing. This study will be the foundation for the future research in the area of IT outsourcing management and success, in particular in the service level management. And also, it could guide managers in practice in IT outsourcing management to focus on service level management process in operation and evaluation stage especially for long-term outsourcing contracts under very unique context like Korean IT outsourcing projects. This study has some limitations in generalization because the sample size is small and the context itself is confined in an unique environment. For future exploration, survey based research could be designed and implemented.

• Korean Journal of Plant Resources
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• v.27 no.5
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• pp.546-555
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• 2014

The final aim of this study is to develop a biofiltration system integrated with plant vegetation for improving indoor air quality effectively depending on indoor space and characteristics. However, to approach this final goal, several requirements such as constant pressure drops (PDs) and soil moisture contents (SMCs), which influence the capacity design for a proper ventilation rate of biofiltration system, should be satisfied. Thus, this fundamental experiment was carried out to adjust a proper wind speed and to ensure a stabilization of initial SMCs within biofilter for uniform distribution of SMCs and PDs, and for normal plant growth, especially avoiding root stress by wind. Therefore, we designed horizontal biofliter models and manufactured them, and then calculated the ventilation rate, air residence time, and air-liquid ration based on the biofilter depending on three levels of wind speed (1, 2, and $3cm{\cdot}s^{-1}$). The relative humidity (RH) and PD of the humidified air coming out through the soil within the biofilter, and SMC of the soil and plant growth parameters of lettuce and duffy fern grown within biofilter were measured depending on the three levels of wind speed. As a result of wind speed test, $3{\cdot}sec^{-1}$ was suitable to keep up a proper RH, SMC, and plant growth. Thus, the next experiment was set up to be two levels of initial SMCs (low and high initial SMC, 18.5 and 28.7%) within each biofilter operated and a non-biofiltered control (initial SMC, 29.7%) on the same wind speed ($3cm{\cdot}sec^{-1}$), and measured on the RH and PD of the air coming out through the soil within the biofilter, and SMC of the soil and plant growth parameters of Humata tyermani grown within biofilter. This result was similar to the first results on RHs, SMCs, and PDs keeping up with constant levels, and three SMCs did not show any significant difference on plant growth parameters. However, two biofiltered SMCs enhanced dry weights of the plants slightly than non-biofiltered SMC. Thus, the stability of this biofiler system keeping up major physical factors (SMC and PD) deserved to be adopted for designing an advanced integrated biofilter model in the near future.