• Information Systems Review
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• v.22 no.1
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• pp.167-182
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• 2020

Ambidexterity in organizations, in general, is interpreted as flexibility that enables organizational innovation, which is important for survival in a competitive market. It applies to individual workers as well since the ambidexterity of explorational and exploitational IS use will enable the flexible transition between dynamic and operational work, and hence, increase the work performance. The current study will therefore investigate the individual levels of exploratory and exploitative IS use, as well as the complementary relationship between exploratory and exploitative IS use. In a third step, the differential influence of IS on work performance will be evaluated. The current study validated that complementary fit of IS use exploration and IS use exploitation increases performance. Polynomial regression and surface analysis are used to validate the incongruence of IS use pattern. They showed that the incongruence of ambidexterity is composed of two types of divergent vs. convergent ambidexterity which depends on the type of work that need dynamic or operational capability.

• Korean Journal of Plant Resources
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• v.23 no.2
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• pp.172-178
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• 2010

This study was carried out to investigate abiotic and biotic environmental factors affecting homoharringtonine (HHT) contents of Cephalotaxus koreana, whereby, to provide basic information of high value-added industry production of HHT as a promising anti-cancer agent. For correlation between abiotic environmental factors (soil moisture, soil pH, habitat density and temperature) and HHT contents, the contents were highly correlated with soil moisture (0.77) and soil pH (-0.68). For multiple regression analysis of relationship between abiotic environmental factors (soil moisture and soil pH) and HHT contents, soil moisture appeared to be strongly affecting the contents relatively due to being significant at only its regression coefficient ($26.48^{***}$). For the effect of biotic environmental factors (damage index) affecting HHT contents, the contents was quadratic with equation of $H=278.23+1242D-398.87D^2$, also, damage index had strong effect on the contents. Finally, for the result of the most influencing an environmental factor on HHT contents, both damage index and soil moisture were suitable in second polynomial regression, also, damage index ($R^2=0.73^{***}$) was turned out to be more influencing factor than soil moisture ($R^2=0.67^{**}$) on HHT contents relatively. Therefore, we predict that HHT contents in the trees of Cephalotaxus koreana is produced as a chemical defense mechanism triggered by a stress-related damage of fungi or insects.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.3 s.309
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• pp.25-33
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• 2006

This paper proposed device-independent color matching algorithm based on the 3D RGB lookup table (LUT) between mobile camera and mobile LCD (Liquid Crystal Display) to improve the color-fidelity. Proposed algorithm is composed of thee steps, which is device characterization, gamut mapping, 3D RGB-LUT design. First, the characterization of mobile LCD is executed using the sigmoidal function, different from conventional method such as GOG (Gain Offset Gamma) and S-curve modeling, based on the observation of electro-optical transfer function of mobile LCD. Next, mobile camera characterization is conducted by fitting the digital value of GretagColor chart captured under the daylight environment (D65) and tristimulus values (CIELAB) using the polynomial regression. However, the CIELAB values estimated by polynomial regression exceed the maximum boundary of the CIELAB color space. Therefore, these values are corrected by linear compression of the lightness and chroma. Finally, gamut mapping is used to overcome the gamut difference between mobile camera and moible LCD. To implement the real-time processing, 3D RGB-LUT is designed based on the 3D RGB-LUT and its performance is evaluated and compared with conventional method.

• The Journal of the Korea Contents Association
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• v.22 no.4
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• pp.433-444
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• 2022

This study aimed to identify the change trajectories and clusters of Korean women's family values and depression levels, and the factors affecting depression, to use balanced panel data from the 1st to 7th rounds of the Korea Longitudinal Survey of Women and Families(KLSWF). The subjects of this study were 5,048 female panelists who participated in the KLSWF, and LSTM analysis was conducted using Python to divide the clusters of Korean women suffering from depression. In addition, descriptive statistical analysis, ANOVA, multinomial logistic regression analysis, and hierarchical regression analysis were analyzed using SPSS 23.0. Results, It was confirmed that women's depression increased with age, and family values had a significant impact on depression. It was found that the more open the marriage values of women in the married group, the higher the level of depression. The family values trajectory and depression level of the analyzed subjects were not a single pattern, but included four clusters. To prevent depression among Korean women and provide more concrete interventions, a humanities and sociological system that can identify depression groups should be prepared.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.41 no.2
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• pp.123-131
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• 2021

The buffer is a key component of an engineered barrier system that safeguards the disposal of high-level radioactive waste. Buffers are located between disposal canisters and host rock, and they can restrain the release of radionuclides and protect canisters from the inflow of ground water. Since considerable heat is released from a disposal canister to the surrounding buffer, the thermal conductivity of the buffer is a very important parameter in the entire disposal safety. For this reason, a lot of research has been conducted on thermal conductivity prediction models that consider various factors. In this study, the thermal conductivity of a buffer is estimated using the machine learning methods of: linear regression, decision tree, support vector machine (SVM), ensemble, Gaussian process regression (GPR), neural network, deep belief network, and genetic programming. In the results, the machine learning methods such as ensemble, genetic programming, SVM with cubic parameter, and GPR showed better performance compared with the regression model, with the ensemble with XGBoost and Gaussian process regression models showing best performance.

• Journal of Korean Society of Transportation
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• v.32 no.5
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• pp.544-553
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• 2014

Activity-based models analyze individuals' various daily activities that are identified as a decision-making unit for transportation planning. In other words, it is the model that determines the types of activities according to the social, economic and situational characteristics of the groups with the same activity patterns and predicts individuals' activity time, distance, spatial movement and transportation mode. The activity-based model is a method of estimating more efficient and realistic demand in transportation forecasting because traffic is regarded as a complex decision-making process that an individual and other people participate in. In this paper, we grasp the factors affecting choice behavior of activity pattern and analyze choice behavior of activity pattern based on multi-dimensional characteristic of each person. First, we classify activity types of reviewing the trip chain and activity purpose. Next, we identified preferable activity types using complicated characteristics of main agent of activity. We concluded that choice behavior of activity pattern is dependent on complex characteristics of each agent, and further multi-dimensional characteristics of each person are affected over the whole decision process of activity schedule.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.11
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• pp.2238-2249
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• 2015

The purpose of this study is to analyze the relations of innovation and productivity following the introduction of ICT and the effects in the process of innovative investments activity-innovation-productivity, not only by finding causes and effects. For this purpose we conducted surveys of SMEs classified into 7 categories by type of business. To put it concretely, this study was performed to find out the foactors which allow companies to secure competitiveness by enhancing of innovative measures through ICT, and to further analyze the political implications for the development of small and medium-size business by conducting an empirical analysis of the process, from the determination of innovative investments all the way through to production. Analysis model used CDM model using econometric methods such as multiple regression analysis and multinominal logit analysis to produce results. Also we established and analyzed models of innovation investment determinants, innovation determinants and productivity determinants to analyze specifically the relations between ICT and productivity.

• Journal of Embryo Transfer
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• v.18 no.3
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• pp.215-225
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• 2003

This study was carried out to investigate the change of blood compositions by age in Hanwoo, and a total of 866 of Hanwoo, which consisted with 638 of steer and 228 of bulls, were used to measure serum concentrations. A multiple regression equation was estimated with collection age and blood composition as independent and dependent variables, respectively. Complicated regression equations for blood compositions in steer and bulls were IGF-I(cubic), calcium (linear), and IP(linear). Linear and cubic equations were fitted to testosterone in steer and creatinine in bulls, respectively. A cubic equation in steer and linear equation in bulls were fitted to HDLC. Equations of quadratic in steer and cubic in bulls were fitted to concentration of triglyceride, globulin, and A/G ratio. BUN was fitted by equations of cubic in steer and quadratic in bulls. TP and albumin were fitted by equations of quadratic in steer and linear in bulls. A cubic regression equation did not explain the change of cortisol by age in steer and bulls. A cubic regression equation did explain the change of glucose by age in steer, but not in bulls. Higher R-square values (R-SQUARE>0.1) were estimated to IGF-1, albumin, creatinine, Inorganic phosphorous(IP) and HDLC in steer, and testosterone, IGF-I, TP, albumin, glucose, creatinine, IP, and HDLC in bulls for the fitted regression equations of blood compositions. Therefore, IGF-I, albumin, creatinine, IP, and HDLC were regarded as comparatively large variation by age in steer and bulls.

• Journal of the Korean Data and Information Science Society
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• v.20 no.5
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• pp.819-827
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• 2009

This study was conducted to investigate the relationship between the sociodemographic factors and the Korean consumers palatability evaluation grades with Hanwoo sensory evaluation data. The dichotomy logistic regression model and the multinomial logistic regression model are fitted with the independent variables such as the consumer living location, age, gender, occupation, monthly income, and beef cut and the the palatability grade as the dependent variable. Stepwise variable selection procedure is incorporated to find the final model and odds ratios are calculated to find the associations between categories.

• Journal of Energy Engineering
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• v.23 no.4
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• pp.196-206
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• 2014

This study analyzes the technological level of Korean bioenergy firms and its determinants by using a multiple logistic regression analysis based on a survey. As the result of analysis, the technological level of Korean bioenergy firms has been positively influenced by the firm size, R&D investments and R&D manpower, but negatively influenced by the competition in domestic market and economy of scale. The policy implications of this study are related to achieve the economy of scale and coevolve between demand and supply-firms for the improvement of the technological level of Korean bioenergy firms.