• Journal of Digital Convergence
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• v.17 no.11
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• pp.213-223
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• 2019

This study aims to prove the relationship between a TPB(theory of planned behavior) variables (subjective norms, attitudes, and self-efficacy), need to belong and personal growth initiatives to explain the reasons for users' shared behavior. 959 participants who had shared online video were collected as a sample through an online survey and the collected data were analyzed through structural equation modeling. The study found that need to belong affected attitudes to online video sharing and subjective norms, and that personal growth initiative also affected attitudes to online video sharing and self-efficacy. In addition, all three variables of TPB were affect the intend of online video sharing, and attitudes to online video sharing were affecting subjective norms and self-efficacy. This study is meaningful in that it demonstrated the user's intention to share online video through variables of TPB along with their need to belong and personal growth initiatives.

• Nuclear Engineering and Technology
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• v.54 no.6
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• pp.2077-2083
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• 2022

In the unlikely event of core disruptive accident in sodium cooled fast reactors, the reactor containment building would be bottled up with sodium and fission product aerosols. The behavior of these aerosols is crucial to estimate the in-containment source term as a part of nuclear reactor safety analysis. In this work, the evolution of sodium aerosol characteristics (mass concentration and size) is simulated using HAARM-S code. The code is based on the method of moments to solve the integro-differential equation. The code is updated to FORTRAN-77 and run in Microsoft FORTRAN PowerStation 4.0 (on Desktop). The sodium aerosol characteristics simulated by HAARM-S code are compared with the measured values at Aerosol Test Facility. The maximum deviation between measured and simulated mass concentrations is 30% at initial period (up to 60 min) and around 50% in the later period. In addition, the influence of humidity on aerosol size growth for two different aerosol mass concentrations is studied. The measured and simulated growth factors of aerosol size (ratio of saturated size to initial size) are found to be matched at reasonable extent. Since sodium is highly reactive with atmospheric constituents, the aerosol growth factor depends on the hygroscopic growth, chemical transformation and density variations besides coagulation. Further, there is a scope for the improvement of the code to estimate the aerosol dynamics in confined environment.

• International Journal of Computer Science & Network Security
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• v.22 no.3
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• pp.67-76
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• 2022

COVID-19 struck labor markets around the world, exposing and exacerbating the gender inequalities within the human capital structure. The last, in its turn, jeopardizes the return of the national economies to the growth trajectory undermined by pandemic impact. The authors assume that COVID-19 disproportionately affected the employment rates of women and men, which led to increased gender inequality in the labor market, which, in turn, affected GDP growth rates in the EU. To prove this hypothesis two research questions are discovered: 1) whether there was a different correlation between the number of COVID-19 cases in the EU and indicators of the labor market for women and men; and 2) whether there was a link between the growth of gender inequality in the EU labor market and the GDP dynamics in these countries. The analysis of the correlation between the number of cases of COVID-19 and indicators of the labor market in the EU revealed faster growth of women's unemployment rates compared to men's ones as the COVID-19 incidence unfolded. Multiple linear regression and factor analysis have been used to investigate the influence of gender inequality in the labor market on GDP dynamics. Despite the methodological limitations, the proposed model is both a sound argument and an analytical basis in favor of gender-responsive economic recovery backed by the systematic and consistent gender equality policy of a government.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.116-116
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• 2020

Gilgit-Baltistan (GB) is a highly mountainous and remote region covering 45% of Upper Indus Basin (UIB) with around 1.8 million population is vulnerable to climate change and socio-economic growth makes water resources management and planning more complex. To understand the water scarcity in the region this study is carried out to project water supply and demand for agricultural and domestic sector under various climate-socio-economic scenarios in five sub catchments of GB i.e., Astore, Gilgit, Hunza, Shigar and Shyok for a period of 2015 to 2050 using Water Evaluation and Planning (WEAP) model. For climate change scenario ensembled mean of three global climate models (GCMs) was used under three different Representative Concentration Pathway (RCP) scenarios (RCP2.6, RCP6.0 and RCP8.5). The Shared Socioeconomic Pathways (SSPs) and agricultural Land Development (LD) scenarios were combined with climate scenarios to develop climate-socio-economic scenario. Our results indicate that the climate change and socio-economic growth would create a gap between supply and demand of water in the region, with socio-economic growth (e.g. agricultural and population) as dominant external factor that would reduce food production and increase poverty level in the region. Among five catchments only Astore and Gilgit will face shortfall of water while Shyoke would face shortfall of water only under agricultural growth scenarios. We also observed that the shortfall of water in response to climate-socio-economic scenarios is totally different over two water deficient catchments due to its demography and geography. Finally, to help policy makers in developing regional water resources and management policies we classified five sub catchments of UIB according to its water deficiency level.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.4B
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• pp.433-437
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• 2006

Recently, mathematical modeling for the activated sludge process is important to design and control of wastewater treatment plant. Nevertheless, there is a lack of information regarding the pathway of substrate utilization between external and internal substrates in biological nutrient removal (BNR). In this research, a new activated sludge model (step growth model) is proposed and compare with ASM No.3. This model structure is consist of five processes; aerobic storage, growth on external substrate and stored intercellular storage compounds (ISCs), endogenous respiration and aerobic respiration of ISCs. The predicted results by the step growth model were more good accordance with the results of oxygen utilization rate (OUR) and TCOD experiment than that of the ASM No.3.

• Proceedings of the Korean Society of Crop Science Conference
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• 2017.06a
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• pp.308-308
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• 2017

The low and unstable yield of soybean has been a major problem in Japan. Excess soil moisture conditions are one of the major factors to restrict soybean productivity. More than 80 % of soybean crops are cultivated in converted paddy fields which often have poor drainage. In central and eastern regions of Japan, the early vegetative growth of soybean tends to be restricted by the flooding damage because the early growth period is overlapped with the rainy season. Field observation shows that induced excess water stress in early vegetative stage reduces dry matter production by decreasing intercepted radiation by leaf and radiation use efficiency (RUE) (Bajgain et al., 2015). Therefore, it is necessary to evaluate the responses of soybean growth for excess water conditions to assess these effects on soybean productions. In this study, we aim to modify the soybean crop model (Sinclair et al., 2003) by adding the components of the restriction of leaf area development and RUE for adaptable to excess water conditions. This model was consist of five components, phenological model, leaf area development model, dry matter production model, plant nitrogen model and soil water balance model. The model structures and parameters were estimated from the data obtained from the field experiment in Tsukuba. The excess water effects on the leaf area development were modeled with consideration of decrease of blanch emergence and individual leaf expansion as a function of temperature and ground water level from pot experiments. The nitrogen fixation and nitrogen absorption from soil were assumed to be inhibited by excess water stress and the RUE was assumed to be decreasing according to the decline of leaf nitrogen concentration. The results of the modified model were better agreement with the field observations of the induced excess water stress in paddy field. By coupling the crop model and the ground water level model, it may be possible to assess the impact of excess water conditions for soybean production quantitatively.

• Journal of Internet Computing and Services
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• v.24 no.1
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• pp.61-69
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• 2023

Recently, as the fishery resources are depleted, expectations for productivity improvement by 'rearing fishery' in land farms are greatly rising. In the case of land farms, unlike ocean environments, it is easy to control and manage environmental and breeding factors, and has the advantage of being able to adjust production according to the production plan. On the other hand, unlike in the natural environment, there is a disadvantage in that operation costs may significantly increase due to the artificial management for fish growth. Therefore, profit maximization can be pursued by efficiently operating the farm in accordance with the planned target shipment. In order to operate such an efficient farm and nurture fish, an accurate growth prediction model according to the target fish species is absolutely required. Most of the growth prediction models are mainly numerical results based on statistical analysis using farm data. In this paper, we present a growth prediction model from a stochastic point of view to overcome the difficulties in securing data and the difficulty in providing quantitative expected values for inaccuracies that existing growth prediction models from a statistical point of view may have. For a stochastic approach, modeling is performed by introducing a Gaussian process regression method based on water temperature, which is the most important factor in positive growth. From the corresponding results, it is expected that it will be able to provide reference values for more efficient farm operation by simultaneously providing the average value of the predicted growth value at a specific point in time and the confidence interval for that value.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.11 no.2
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• pp.49-62
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• 2016

Technology-based start-ups have great economic ripple effect such as economic growth and job creation. Therefore, a strategic approach is required in order for such start-ups to continuously grow. However, many technology-based start-ups do not survive the Death-Valley and are being eliminated from the market. This is an empirical study on influencing variables that have impact on their performance. This study presents growth intention and influencing variables that have impact on performance (financial performance, technological performance) based on previous research on technology-based start-up. Also, this study examines the relationship between entrepreneurial competence, team commitment and growth intention, and finds the effect of controlling business-network. Structural equation modeling was performed in order to test the research hypothesis. Survey was conducted on the firms that have been certified by Youth Startup Academy of Small and Medium Business Corporation. A total of 306 samples were collected from the survey. An empirical test was conducted on the research hypothesis using SPSS 21.0 and Amos 22.0. The result of hypothesis test shows that growth intention has positive influence on both financial and technological performance, and entrepreneurial competence (technological competence, strategic management competence, creative competence and team commitment) has positive influence on growth intention. Also, the research proved that business-network has regulation effect between human resource trait and growth intention. The result of our study will provide practical insight to future start-ups for continuous growth and successful running of their firm.

• Korean Journal of Poultry Science
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• v.43 no.1
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• pp.1-14
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• 2016

Prediction of growth patterns of commercial chicken strains is important. It can provide visual assessment of growth as function of time and prediction body weight (BW) at a specific age. The aim of current study is to compare the three nonlinear functions (i.e., Logistic, Gompertz, and von Betalanffy) for modeling the growth of twenty five commercial Korean native chicken (KNC) strains reared under a battery cage system until 32 weeks of age and to evaluate the three models with regard to their ability to describe the relationship between BW and age. A clear difference in growth pattern among 25 strains were observed and classified in to the groups according to their growth patterns. The highest and lowest estimated values for asymptotic body weight (C) for 3H and 5W were given by von Bertalanffy and Logistic model 4629.7 g for 2197.8 g respectively. The highest estimated parameter for maturating rate (b) was given by Logistic model 0.249 corresponds to the 2F and lowest in von Bertalanffy model 0.094 for 4Y. According to the coefficient of determination ($R^2$) and mean square of error (MSE), Gompertz and von Bertalanffy models were suitable to describe the growth of Korean native chicken. Moreover, von Bertalannfy model was well described the most of KNC growth with biologically meaningful parameter compared to Gompertz model.

• Journal of Energy Engineering
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• v.23 no.1
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• pp.75-80
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• 2014

The past several years have seen a substantial growth in mathematical modeling activities whose interests are to describe the performance, efficiency and emissions characteristics of various types of internal combustion engines. The key element in these simulations of various aspects of engine operation is the model of the engine combustion process. Combustion models are then classified into three categories: zero-dimensional, quasi-dimensional and multidimensional models. zero-dimensional models are built around the first law of thermodynamics, and time is the only independent variable. This paper presents a introduction to the combustion characteristics of a spark ignition combustion modeling by zero-dimensional model.