• Journal of Food Hygiene and Safety
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• v.16 no.2
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• pp.103-110
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• 2001

Predictive food microbiology(PFM) is an emerging area of food microbiology since the later 1980’s. It does apply mathematical models to predict the responses of microorganism to specified environmental variables. Although, at present, PFM models do not completely developed, models can provide very useful information for microbiological responses in HACCP(Hazard Analysis Critical Control Point) system and Risk Assessment. This study illustrates the possible use of PFM models(PMP: Pathogen Modeling Program win5.1) with milk in several elements in the HACCP system, such as conduction of hazard analysis and determination of CCP(Critical Control Points) and CL(Critical Limits). The factors likely to affect the growth of the pathogens in milk involved storage fixed factors were pH 6.7, Aw 0.993 and NaCl 1.3%. PMPwin5.1 calculated generation time, lag phase duration, time to level of infective dose for pathogens across a range of storage (Critical Control Points) and CL(Critical Limits). The factors likely to affect the growth of the pathogens in milk involved storage temperature, pH, Aw and NaCl content. The factors likely to affect the growth of the pathogens in milk involved storage temperature, pH, Aw and NaCl content. The variable factor was storage temperature at the range of 4~15$^{\circ}C$ and the fixed factors were pH 6.7, Aw 0.993 and NaC 1.3%. PMPwin5.1 calculated generation time, lag phase duration, time to level of infective dose for pathogens across a range of storage temperature.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.12 no.5
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• pp.13-28
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• 2017

Entrepreneurship is an important factor not only for start-ups, but also for scale-up of businesses. In other words, the two aspects of establishment and growth of businesses must be balanced through entrepreneurship. However, it is true that entrepreneurship has been biased toward the former in previous researches and government policies. Here in this research, the causal relationships between the entrepreneurial characteristics of Korean firms and the performance of the company, which is measured by proposal, activity, and business performance are examined as a growth perspective. Based on these relationships, a model describing the operating mechanism of corporate entrepreneurship is derived and policy implications are provided. In conducting research, the hypotheses on the interrelationship of variables are builded using '2016 Entrepreneurship Situation Survey(Corporate)' data from Korea Entrepreneurship Foundation and analyzed by structural equation modeling. In addition, the moderating effect according to the firm size and the mediating effect between entrepreneurship and business performance are analyzed. As a result of this research, the fact that entrepreneurship affects business performance is identified and it is necessary to prioritize corporate vision and strategy for enhancement of entrepreneurship. In particular, necessity of operating system for SMEs is confirmed considering SMEs' entrepreneurship level. The implications of this research are expected to be applied by the government in establishing policy direction to enhance corporate entrepreneurship of SMEs in the future.

• Journal of the Korean Association of Geographic Information Studies
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• v.9 no.2
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• pp.20-29
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• 2006

Modeling urban climate caused by land use conversion is critical for human welfare and sustainable development, but has hampered because detailed information on urban characteristics is hard to obtain. With the advantage of satellite observations and the new statistical boundary system, this paper measures the economic and environmental effects of green area loss due to land use conversion in urban areas. To perform this purpose, data were collected from the various sources basic statistical unit data from the National Statistical Office, digital maps from the National Geographic Information Institute, satellite images, and field surveys when necessary. All data (maps and attributes) are built into the geographic information system (GIS). This paper also utilizes Landsat TM 5 imagery of Daegu city to derive vegetation index and to measure average surface temperature. The satellite data were examined using standard image processing software, ERDAS IMAGINE, and the results of the digital processing were presented with ARCVIEW(v.3.3). SAS package was used to perform statistical analyses. This study presents that there exists a strong relationship between land use change and climatic change as well as land price change. Based on results of the analysis, this paper suggests that planners should implement effective tools and policies of urban growth management to detect environmental quality and to make right decisions on policies concerning smart urban growth.

• International Commerce and Information Review
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• v.16 no.3
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• pp.331-355
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• 2014

With the rapid growth of Chinese economy, environmental issues also became a serious problem that public and private sector have to take under consideration. For the sustainable growth of Chinese economy scholars and policy makers agree to the stronger regulation for protection of natural environment, but at the same time worry about its negative effect on economic growth. This paper primarily focus on the relationship between the factors that have the effect on green product purchasing intention and purchasing behavior. Purchasing intention was considered as mediating variable in our model and state-action orientation - as moderating variable. We set 8 hypotheses and tested with structural equation modeling. The result shows that governmental regulation and subsidy, social environment related with green product purchase, and consumer perception on the benefit of green product have positive relationship with purchasing intention, but environmental concern does not show relationship with it. We also proved that state-action orientation has moderating effect between purchasing intention and purchasing behavior. Purchasing intention with action orientation show positive and statistically significant effect on purchasing behavior. This result supports the hypothesis that the attitude of customers has the effect on ones purchasing behavior.

• Asian-Australasian Journal of Animal Sciences
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• v.13 no.8
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• pp.1147-1153
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• 2000

A total of 9,540 pigs were evaluated for their growth performance to provide information on the development of different feeding strategies to support maximum rate of protein deposition (PD). Large variations in growth performance and protein deposition rate were found in the population used in this study (ADG from 701 to 974 g/day; ADFI from 1,726 to 2,498 g/day; Feed/gain from 2.10 to 2.90; Backfat thickness from 12.4 to 20.5 mm and PD rate from 103 to 153 g/day). It was found that ADG was positively correlated to PD ($R^2=0.9362$, p<0.0001) while FCR was negatively correlated to PD ($R^2=0.4031$, p<0.0001). Backfat thickness was negatively correlated to PD ($R^2=0.7024$, p<0.0001) and to ADG ($R^2=0.5096$, p<0.0001). The estimated lysine requirement based on PD rate also showed large variation (12.37 to 18.38 g/day true ileal digestible lysine on average between 25 and 100 kg), thus strongly indicated the need of separate feeding strategies for each group of pigs. When pigs were divided into three categories according to estimated whole body PD rate, the group of pigs with the highest PD rate grew faster by 6.3 and 13.9% than pigs with intermediate and low PD rate, respectively. Feed utilization was also more efficient in pigs with a high PD rate. It appeared that pigs with high PD rate maintained higher PD rate especially in the later stage of their life. Pigs with high PD rate require an extra amount of 1.2 and 2.4 g/true digestible lysine per day and 0.4 and 0.8% more lysine in the diet than pigs with intermediate and low PD rate during the growing-finishing period respectively. Results of this study suggest that there is a need for separate feeding strategies for individual group of pigs with different PD rate. It should be noted that average value for each group presented in this report is not the adequate amount for an animals potential for maximum PD rate. With recent development in growth modeling and access to computer technologies to facilitate computation, pork producers can easily estimate pigs protein deposition rate and thus can make their own feeding strategies.

• Korean Journal of Agricultural and Forest Meteorology
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• v.20 no.2
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• pp.228-232
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• 2018

Process-based crop models have been used to assess the impact of climate change on crop production. These models are implemented in procedural or object oriented computer programming languages including FORTRAN, C++, Delphi, Java, which have a stiff learning curve. The requirement for a high level of computer programming is one of barriers for efforts to develop and improve crop models based on biophysical process. In this study, we attempted to develop a Chinese cabbage model using Microsoft Excel with Visual Basic for Application (VBA), which would be easy enough for most agricultural scientists to develop a simple model for crop growth simulation. Results from Soil-Plant-Atmosphere-Research (SPAR) experiments under six temperature conditions were used to determine parameters of the Chinese cabbage model. During a plant growing season in SPAR chambers, numbers of leaves, leaf areas, growth rate of plants were measured six times. Leaf photosynthesis was also measured using LI-6400 Potable Photosynthesis System. Farquhar, von Caemmerer, and Berry (FvCB) model was used to simulate a leaf-level photosynthesis process. A sun/shade model was used to scale up to canopy-level photosynthesis. An Excel add-in, which is a small VBA program to assist crop modeling, was used to implement a Chinese cabbage model under the environment of Excel organizing all of equations into a single set of crop model. The model was able to simulate hourly changes in photosynthesis, growth rate, and other physiological variables using meteorological input data. Estimates and measurements of dry weight obtained from six SPAR chambers were linearly related ($R^2=0.985$). This result indicated that the Excel/VBA can be widely used for many crop scientists to develop crop models.

• Journal of Internet Computing and Services
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• v.10 no.5
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• pp.65-78
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• 2009

The most commonly adopted approach to find valuable information from tree data is to extract frequently occurring subtree patterns from them. Because mining frequent tree patterns has a wide range of applications such as xml mining, web usage mining, bioinformatics, and network multicast routing, many algorithms have been recently proposed to find the patterns. However, existing tree mining algorithms suffer from several serious pitfalls in finding frequent tree patterns from massive tree datasets. Some of the major problems are due to (1) modeling data as hierarchical tree structure, (2) the computationally high cost of the candidate maintenance, (3) the repetitious input dataset scans, and (4) the high memory dependency. These problems stem from that most of these algorithms are based on the well-known apriori algorithm and have used anti-monotone property for candidate generation and frequency counting in their algorithms. To solve the problems, we base a pattern-growth approach rather than the apriori approach, and choose to extract maximal frequent subtree patterns instead of frequent subtree patterns. The proposed method not only gets rid of the process for infrequent subtrees pruning, but also totally eliminates the problem of generating candidate subtrees. Hence, it significantly improves the whole mining process.

• Journal of Digital Convergence
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• v.14 no.12
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• pp.293-302
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• 2016

The study explores how academic strain, unhappiness, and mobile phone dependency among adolescents have changed over time. And we conducted the longitudinal and complex analysis on the influence of academic strain on unhappiness and mobile phone dependency in order to search the ways to prevent a vicious circle among them. We used general strain theory as a conceptual research frame and analysed the data of 1,589 respondents of the 2nd~4th Korean Children and Youth Panel with latent growth modeling. It was found that the levels of academic strain, unhappiness, and mobile phone dependency among adolescents were linearly increased across time. Academic strain initial status positively affected unhappiness initial status and both the initial status and change rate of mobile phone dependency. The change rate of unhappiness positively affected that of mobile phone dependency. Academic strain change rate positively influenced that of mobile phone dependency mediated by unhappiness change rate. We provided useful implications to academic activities, negative emotions, and mobile phone dependency for adolescents and suggested future studies about reasons of the changes of those variables.

• Journal of Korea Water Resources Association
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• v.51 no.9
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• pp.747-759
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• 2018

Multivariate regional frequency analysis has advantages of regional and multivariate framework as adopting a large number of regional dataset and modeling phenomena that cannot be considered in the univariate frequency analysis. To the best of our knowledge, the multivariate regional frequency analysis has not been employed for hydrological variables in South Korea. Applicability of the multivariate regional frequency analysis should be investigated for the hydrological variable in South Korea in order to improve our capacity to model the hydrological variables. The current study focused on estimating parameters of regional copula and regional marginal models, selecting the most appropriate distribution models, and estimating regional multivariate growth curve in the multivariate regional frequency analysis. Annual maximum rainfall and duration data observed at 71 stations were used for the analysis. The results of the current study indicate that Frank and Gumbel copula models were selected as the most appropriate regional copula models for the employed regions. Several distributions, e.g. Gumbel and log-normal, were the representative regional marginal models. Based on relative root mean square error of the quantile growth curves, the multivariate regional frequency analysis provided more stable and accurate quantiles than the multivariate at-site frequency analysis, especially for long return periods. Application of regional frequency analysis in bivariate rainfall-duration analysis can provide more stable quantile estimation for hydraulic infrastructure design criteria and accurate modelling of rainfall-duration relationship.

• Journal of Korean Society of Environmental Engineers
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• v.22 no.1
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• pp.11-19
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• 2000

In order to predict the performance of biological wastewater treatment plant, the kinetic parameters and stoichiometric coefficient must be known. The theories and experimental procedures for determining the biological kinetic parameters were discussed in this study. Respirometric analysis in the batch reactor was carried out for the experimental assessment of kinetic parameters. A simple procedure to estimate kinetic parameters of heterotrophs and autotrophs under aerobic condition was presented. The difficulties in the interpretation of COD and VSS measurements encouraged the conversion of respirometric data to growth data. Maximum specific growth rate, yield coefficient, half saturation constant and decay rate of heterotrophic biomass were obtained from OUR(Oxygen Uptake Rate) data. Maximum specific growth rate of autotrophic biomass was obtained from the increase of nitrate concentration. The aim of this paper is to estimate the kinetic parameters of heterotrophic and autotrophic biomass by means of the respirometric analysis of activated sludge behavior in the batch reactors. These procedures may be used for the activated sludge modeling with complex kinetic parameters.