• Journal of Ecology and Environment
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• v.35 no.3
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• pp.157-166
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• 2012

Many models intending to explain the latitudinal gradient of increasing species diversity from the poles to the equator are presented, which are a formalisation of the species-energy hypothesis. The model predictions are consistent with patterns of increasing species number with increasing mean air or water temperatures for plants and animals. An increase in species richness is also correlated with net primary production or the Normalised Difference Vegetation Index. This implies that increased availability of resources favours increased diversity capacity. The explanatory variables included in the biodiversity prediction models represent measures of water, energy, water-energy, habitat, history/evolution and biological responses. Water variables tend to be the best predictors when the geographic scope of the data is restricted to tropical and subtropical areas, whereas water-energy variables dominate when colder areas are included. In major models, about 20-35% of species in the various global regions (European, Africa, etc.) will disappear from each grid cell by 2050 and >50% could be vulnerable or threatened by 2080. This study provides good explanations for predictive models and future changes in biodiversity depending on various scenarios.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.4 no.4
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• pp.63-69
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• 1981

As enterprises are getting bigger and bigger and more competecious, an engineering economy for the maximization of profit based on basic theory must be considered. This thesis present dynamic computer model for the decision which controls complicated and various man- machine system optimally. This model occur in general stage can be adaptable to every kind of enterprises. So, any one who has no expert knowledge is able to get the optimal solution. And decision tree used in this paper can be applied in every kinds of academic circles as well as whole the industrial world. This paper studied optimal management of engineering project based upon basic theory of engineering economy. It introduces and functionizes the variables which generalize every possible elements, set up a model in order to find out the variable which maximize the calculated value among many other variables. And the selected values ate used as decision- marking variables for the optimal management of engineering projects. It found out some problem of this model. They are : 1. In some kinds of man-machine system it refers to Probability, but other case, it depends on only experimental probability. 2. Unless decision making process (decision tree) goes on, this model can not be applied. So these cases, this paper says, can be solved by adapting finite decision tree which is analyzed by using the same technic as those in product introduction problem. And this paper set up the computer model in order to control every procedure quickly and optimally, using Fortran IV.

• International Journal of Korean Welding Society
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• v.1 no.2
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• pp.36-44
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• 2001

To get the appropriate welding process variables, mathematical modeling in conjunction with many experiments is necessary to predict the magnitude of weld bead shape. Even though the experimental results are reliable, it has a difficulty in accurately predicting welding process variables for the desired weld bead shape because of nonlinear and complex characteristics of welding processes. The welding condition determined for the desired weld bead shape may cause the weld defect if the welding current/voltage/speed combination is improperly selected. In this study, the $2^{n-1}$ fractional factorial design method and correlation parameter were used to investigate the effect of the welding process variables on the fillet joint shape, and the multiple non-linear regression analysis was used for modeling the gas metal arc welding(GMAW）parameters of the fillet joint. Finally, a fuzzy rule-based method and a neural network method were proposed so that the complexity and non-linearity of arc welding phenomena could be effectively overcome. The performance of the proposed neuro-fuzzy system was evaluated through various experiments. The experimental results showed that the proposed neuro-fuzzy system could effectively check the welding conditions as to whether or not weld defects would occur, and also adjust the welding conditions to avoid these weld defects.

• Journal of Soil and Groundwater Environment
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• v.23 no.1
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• pp.14-24
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• 2018

In soil washing, there are many variables including types of reagent and contaminant, washing time, soil-liquid ratio, washing cycles, washing agent concentrations, and etc. To identify the most influencing factors on soil washing process, regression analysis was performed for eight single variables and five combined variables. A quantitative model that employs W/H (molar ratio of washing agent to heavy metal) as a major variable was established based on the regression. The validity of the model was demonstrated by conducting lab experiments with Cu, Pb, Zn, Ni and As-contaminated soils, and various washing reagents including acetic acid, citric acid, malic acid, oxalic acid, ethylenediamine tetraacetic acid (EDTA) and nitriloacetic acid (NTA). The washing efficiencies were compared with the EDTA washing data reported in the literature. The correlation between W/H and removal efficiency was analyzed after dividing data into two groups according to the heavy metal mobility.

• The Korean Journal of Applied Statistics
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• v.20 no.1
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• pp.23-38
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• 2007

Corporations adopt a segmentation depends on the existence of target variables, in general. In this paper, for the case of no target variables, a strategy through segmentation is proposed for corporations having a special status based on the management index. In case of segmentation using cluster analysis, however, if one classify according to many variables then he will be in face of difficulties in characterizing. Therefore, after extracting representative factors by factor analysis, a segmentation method through 2 step cluster analysis is employed on the basis of these representative factors. As a result, six segmentation groups are found and the resulting strategy is proposed which strengthens prominent factors and makes up defective factors for each group.

• Journal of Korean Society on Water Environment
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• v.30 no.1
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• pp.8-15
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• 2014

In this study, regression equation was analyzed to estimate non-point source (NPS) pollutant loads in orchard area. Many factors affecting the runoff of NPS pollutant as precipitation, storm duration time, antecedent dry weather period, total runoff density, average storm intensity and average runoff intensity were used as independent variables, NPS pollutant was used as a dependent variable to estimate multiple regression equation. Based on the real measurement data from 2008 to 2012, we performed correlation analysis among the environmental variables related to the rainfall NPS pollutant runoff. Significance test was confirmed that T-P ($R^2=0.89$) and BOD ($R^2=0.79$) showed the highest similarity with the estimated regression equations according to the NPS pollutant followed by SS and T-N with good similarity ($R^2$ >0.5). In the case of regression equation to estimate the NPS pollutant loads, regression equations of multiplied independent variables by exponential function and the logarithmic function model represented optimum with the experimented value.

• International Journal of Aeronautical and Space Sciences
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• v.17 no.2
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• pp.268-283
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• 2016

Aircraft manufacturing companies have to consider multiple derivatives to satisfy various market requirements. They modify or extend an existing aircraft to meet new market demands while keeping the development time and cost to a minimum. Many researchers have studied the derivative design process, but these research efforts consider baseline and derivative designs together, while using the whole set of design variables. Therefore, an efficient process that can reduce cost and time for aircraft derivative design is needed. In this research, a more efficient design process is proposed which obtains global changes from local changes in aircraft design in order to develop aircraft derivatives efficiently. Sensitivity analysis was introduced to remove unnecessary design variables that have a low impact on the objective function. This prevented wasting computational effort and time on low priority variables for design requirements and objectives. Additionally, uncertainty from the fidelity of analysis tools was considered in design optimization to increase the probability of optimization results. The Reliability Based Design Optimization (RBDO) and Possibility Based Design Optimization (PBDO) methods were proposed to handle the uncertainty in aircraft conceptual design optimization. In this paper, Collaborative Optimization (CO) based framework with RBDO and PBDO was implemented to consider uncertainty. The proposed method was applied for civil jet aircraft derivative design that increases cruise range and the number of passengers. The proposed process provided deterministic design optimization, RBDO, and PBDO results for given requirements.

• Geomechanics and Engineering
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• v.10 no.3
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• pp.269-284
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• 2016

Simplified techniques based on in situ testing methods are commonly used to assess seismic liquefaction potential. Many of these simplified methods were developed by analyzing liquefaction case histories from which the liquefaction boundary (limit state) separating two categories (the occurrence or non-occurrence of liquefaction) is determined. As the liquefaction classification problem is highly nonlinear in nature, it is difficult to develop a comprehensive model using conventional modeling techniques that take into consideration all the independent variables, such as the seismic and soil properties. In this study, a modification of the Multivariate Adaptive Regression Splines (MARS) approach based on Logistic Regression (LR) LR_MARS is used to evaluate seismic liquefaction potential based on actual field records. Three different LR_MARS models were used to analyze three different field liquefaction databases and the results are compared with the neural network approaches. The developed spline functions and the limit state functions obtained reveal that the LR_MARS models can capture and describe the intrinsic, complex relationship between seismic parameters, soil parameters, and the liquefaction potential without having to make any assumptions about the underlying relationship between the various variables. Considering its computational efficiency, simplicity of interpretation, predictive accuracy, its data-driven and adaptive nature and its ability to map the interaction between variables, the use of LR_MARS model in assessing seismic liquefaction potential is promising.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.8
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• pp.461-472
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• 2020

In recent decades, the research field of entrepreneurship phenomenon has significantly increased in both quantity and sophistication. In Vietnam, paradoxically, while creating a new business venture has become a tendency, the interest in studying entrepreneurs seems not to be thoroughly investigated. This research aims to evaluate the factors that affect the entrepreneurial intention of information technology (IT) students in Vietnam. The authors make use of mixed methods including both quantitative research method and qualitative research method. The qualitative research method is employed to identify meanings, confirmations, adjustments, and compliments for concept-measurement variables in the conceptual model. Quantitative research is conducted from a sample of 424 IT senior students across many universities in Vietnam. Questionnaires have been sent to students to evaluate the measurement scale and appropriateness of the research model. Results from multiple regression highlighted five independent variables affecting the dependent variable, the entrepreneurial intention, in a descending order as following: entrepreneurial educational environment, personal characteristics, perception of feasibility, entrepreneurial supports, and financial accessibility. In addition, this research has proved that the variable attitudes towards entrepreneurship partially mediated among the interrelationship of the aforementioned variables. From this research, the authors make some recommendations to enhance entrepreneurial intentions of IT students in Vietnam.

• Publications of The Korean Astronomical Society
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• v.32 no.3
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• pp.421-438
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• 2017

Through the short-period variability survey program, we obtained time-series BV CCD images for $1.5^{\circ}{\times}1.0^{\circ}$ region around the young open cluster NGC 457. As a result, we have detected 61 variable stars including 31 new ones after checking light curves of all stars by eyes. The 61 variable stars were included 14 ${\delta}$ Scuti variable stars, a ${\beta}$ Cephei variable star, 10 variable Be and slowly pulsating B stars, 13 eclipsing binary stars, 21 semi-long periodic or slow irregular variables and an RR Lyrae variable star, respectively. Many variable B-type stars were known through a well-defined zero-age main sequence to the ${\beta}$ Cepheid region of NGC 457. Most of the variable B-type stars found this paper were known variable stars. But, 11 out of 14 ${\delta}$ Scuti variable stars were newly discovered. The new variable stars except for ${\delta}$ Scuti stars were 4 variable B-type stars, 5 eclipsing binaries and 11 semi-long periodic or slow irregular variables. We have performed frequency analysis for all ${\delta}$ Scuti stars, a ${\beta}$ Cepheid star and an RR Lyrae star.