• 한국해양학회지
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• v.30 no.5
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• pp.403-412
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• 1995

The present study was performed to determine th growth and production of Mactra veneriformis on the Songdo tidal flat off Inchon. west coast of Korea. Monthly samples were collected from Marc 1989 to September 1990. The size distributions of shell length showed unimodal patterns from March to August 1989. The binodal pattern after September 1989 indicated a recruitment of young clams during this period. The density fluctuated irregularly, but showed a decreasing pattern over time on the whole. The density of the year class 1989 increased markedly after February 1990. The growth in shell length showed three phases during a year, a fast growth phase in spring, a slow growth phase in summer and autumn, and a lag phase in winter. The annual increment in shell length reduced with age. The flesh dry weight showed a peak in late spring just before the spawning period, and another peak in autumn. The length of annuli and the back-calculated flesh dry weight were used to describe the annual growth. The growth in shell length fitted to the von Bertalanffy model and the flesh dry weight to the Gompertz model. The absolute growth rate of the shell length reduced gradually with age. The year class 1985 had the highest L, and the yeat class 1986 the lowest L. The annual growth in weight showed a typical sigmoid curve. The growth rate was maximum at the age of 2 to 3. Year classes of 1984 and 1985 had higher values of W and higher absolute growth rates than those of 1986 and 1987. Maximum absolute growth rates of 1986 and 1987 year classes were recorded at younger ages than 1984 and 1985 year classes. The annual relative growth rates of length and weight decreased exponentially with age. Biomass in flesh dry weight increased till spring and thereafter decreased progressively. Maximum biomass was 134.6g m/SUP -2/ in August 1990. The biomass of 1989 yeat class occupied highest proportion in total biomass. Annual production in flesh dry weight from March 1989 to March 1990 was 67.9 g m/SUP -2/ year/SUP -1/. Cumulative production of 1989 year class was highest among all year classes, and that of year class 1984 was lowest. The production is high in spring and autumn, and very low in summer and winter.

• Journal of Animal Science and Technology
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• v.44 no.2
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• pp.165-170
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• 2002

Mature weight (A) and rate of maturing (k) estimated by nonlinear regression were studied to determine the optimum age range over which the estimate of growth curve parameters can be estimated. The weight-age data from 1,133 Hanwoo bulls at Hanwoo Improvement Center of N.A.C.F. were used to fit the growth curve using Gompertz model. All available weight data from birth to the specific age of months were used for the estimation of parameters: the six specific ages used were 12, 14, 16, 18, 20 22 and 24 months of age. The mean estimates of mature weight (A) were 966.5, 1,255.9, 1,126.2, 916.5, 842.2, 780.9 and 767.0kg for ages 12 through 24 months, respectively. The mean estimates of mature weight (A) to 22 and 24 months of age were not different from each other. However, they were different from the estimates based on the data to other ages. Mean estimates of rate of maturing (k) were 3.362, 3.595, 3.536, 3.421, 3.403, 3.409 and 3.411 for ages 12 through 24 months, respectively. The mean estimates of maturing rate (k) for ages 18 through 24 months of age were not significantly different from each other. However, they were different from the estimates based on the data to other ages. Correlations among estimates of A at various ages showed the highest value of 0.93 between 22 and 24 months. Correlations among estimates of k at various ages were highest ranging from 0.91 to 0.99 among 18 to 24 months. The correlations between A and k were positive and tended to decrease with the increase of the age from 0.84 for the age of 12 months to 0.10 for the age of 24 months. Thus, the estimates of growth curve parameters, A and k, suitable for genetic studies can be derived from accumulated Hanwoo bulls after 22 months of age.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.2 no.1
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• pp.21-30
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• 1997

The present study reports the density, growth and production of a razor clam, Sinollovacula constricta, which is known to be one of the important fishreies catches from the Korean tidal flat. The annual yield reached to about 6,000 metric tons per year till 1994. The study was conducted on the Hwaseong tidal flat located on the central west coast, 40 kilometers south-west from Seoul. The annual yield of the razor clam in this area reached to about 50% of the total catch from the whole Korean coast. Samples were colleted monthly at 14 occasions from May 1992 to August 1993. Density of S. constricta ranged from 92~165 individuals per square meter during the study period. General trend of decreasing density was observed when the animal became older, but an exception was the year class of 1991 whose density was lower than that of 1990. The size of the shell was clearly separated into two classes during fall and winter (from September to February), however, the maximum frequency of the length of small size classes moved to right after February. It indicates a fast growth of young clams from spring to summer. Fast growth of the shell could also be examined by the growth curve. The shell growth of the whole life span was described by the von Bertalanffy equation of $L_t=89.3{\times}[1{\exp}\{-0.58{\times}(t+0.73\}]$. The growth in flesh dry weight was well fitted to the Gompertz growth model with the equation, $W_t=5.00{\times}{\exp}\{-4.31{\times}{\exp}(-0.043{\times}t)\}$. The clam lost about 30% of the body weight during spawning in August. The annual production calculated based on the data from September 1992 to August 1993 amounted to 150 g $DW{\cdot}m^{-2}{\cdot}yr^{-1}$ which was 2~50 fold higher than those of other bivalves occurred in Korea. This estimate was patitioned by each year classes; 87.5 by 1992, 53.4 by 1991, 59.0 by 1990 and -30.0 g $DW{\cdot}m^{-2}{\cdot}yr^{-1}$ by 1989 year class.

• Journal of Microbiology and Biotechnology
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• v.15 no.6
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• pp.1323-1329
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• 2005

A mathematical model was developed for predicting the growth kinetics of Listeria monocytogenes in tryptic soy broth (TSB) as a function of combined effects of temperature, pH, and NaCl. The TSB containing four different concentrations of NaCl (2, 4, 5, and $10\%$) was initially adjusted to six different pH levels (pH 5, 6, 7, 8, 9, and 10) and incubated at 4, 10, 25, or 37$^{circ}C$. In all experimental variables, the primary growth curves were well fitted ($r^{2}$=0.982 to 0.998) to a Gompertz equation to obtain the lag time (LT) and specific growth rate (SGR). Surface response models were identified as appropriate secondary models for LT and SGR on the basis of coefficient determination ($r^{2}$=0.907 for LT, 0.964 for SGR), mean square error (MSE=3.389 for LT, 0.018 for SGR), bias factor ($B_{1}$B,=0.706 for LT, 0.836 for SGR), and accuracy factor ($A_{f}$=1.567 for LT, 1.213 for SGR). Therefore, the developed secondary model proved reliable predictions of the combined effect of temperature, NaCl, and pH on both LT and SGR for L. monocytogenes in TSB.

• Asian-Australasian Journal of Animal Sciences
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• v.30 no.3
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• pp.432-438
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• 2017

Objective: The objective of this study was to evaluate the effect of combinations of $NaNO_2$ and NaCl concentrations on Listeria monocytogenes (L. monocytogenes) growth in emulsion-type sausage. Methods: Emulsion-type sausages formulated with different combinations of $NaNO_2$ (0 and 10 ppm) and NaCl (1.00%, 1.25%, and 1.50%) were inoculated with a five-strain L. monocytogenes mixture, and stored at $4^{\circ}C$, $10^{\circ}C$, and $15^{\circ}C$, under aerobic or vacuum conditions. L. monocytogenes cell counts were measured at appropriate intervals, and kinetic parameters such as growth rate and lag phase duration (LPD) were calculated using the modified Gompertz model. Results: Growth rates increased (0.004 to 0.079 Log colony-forming unit [CFU]/g/h) as storage temperature increased, but LPD decreased (445.11 to 8.35 h) as storage temperature and NaCl concentration increased. The effect of combinations of NaCl and low-$NaNO_2$ on L. monocytogenes growth was not observed at $4^{\circ}C$ and $10^{\circ}C$, but it was observed at $15^{\circ}C$, regardless of atmospheric conditions. Conclusion: These results indicate that low concentrations of $NaNO_2$ and NaCl in emulsion-type sausage may not be sufficient to prevent L. monocytogenes growth, regardless of whether they are vacuum-packaged and stored at low temperatures. Therefore, additional techniques are necessary for L. monocytogenes control in the product.

• Journal of Animal Science and Technology
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• v.46 no.4
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• pp.503-508
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• 2004

This study was conducted to estimate the growth curve parameters of crossbreds between Korean native boars and Landrace sows and their relationships with meat qualities. The data used were weight-age data and carcass data from 131 males and 122 females raised at N.L.R.I in Korea. Growth curve parameters were estimated from nonlinear regression using Gompertz model individually. Average mature weight(A), average maturing rate(k), and average inflection point(u) showing maximum growth rate estimated were 179.54${\pm}$6.06kg, 0.3154${\pm}$0.0059, and 5.50${\pm}$0.11 months in females, and 179.84${\pm}$6.33kg, 0.3049${\pm}$0.0061, and 5.24${\pm}$0.13 months in males, respectively. For the growth curve parameters and derived statistics, the phenotypic correlations of maturing rate with gain rate at inflection, mature weight, and inflection point were - .30, - .77, and - .93 in male, and - .31, - .78 and - .94 in female, respectively. Matrure weight was positively correlated to the inflection point as + .89 in both male and female, indicating that late maturing pigs with lower k had longer maturing period with increasing gain rate and reached point of inflection later than early maturing pigs with higher k, and grew to larger mature weight. Backfat thickness and erode fat contents were correlated with mature weight positively in male and negatively in female, and correlated with gain rate at inflection point positively in both male and female, of which coefficients were as high as .42 and .50 in male, respectively.

• Korea journal of population studies
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• v.10 no.2
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• pp.17-45
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• 1987

This study contributes to understanding women's labor market behavior by focusing on a particular set of labor force transitions - labor force withdrawal and entry during the period surrounding the first birth of a child. In particular, this study provides a dynamic analyses, using longitudinal data and event history analysis, to conceptualize labor force behaviors in a straightforward way. The main research question addresses which factors increase or decrease the hazard rates of leaving and entering the labor market. This study used piecewise Gompertz model, following the guide of the non-parametric analysis on the hazard rates, which allowed relatively detailed description on the distribution of timing of leave and entry to the labor market as parameters of interest. The results show that preferences and structural variables, as well as economic considerations, are very important factors to explain the labor market behavior of women in the period surrounding childbirth.

• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.17-35
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• 2015

Demand forecasting is the activity of estimating the quantity of a product or service that consumers will purchase for a certain period of time. Developing precise forecasting models are considered important since corporates can make strategic decisions on new markets based on future demand estimated by the models. Many studies have developed market growth curve models, such as Bass, Logistic, Gompertz models, which estimate future demand when a market is in its early stage. Among the models, Bass model, which explains the demand from two types of adopters, innovators and imitators, has been widely used in forecasting. Such models require sufficient demand observations to ensure qualified results. In the beginning of a new market, however, observations are not sufficient for the models to precisely estimate the market's future demand. For this reason, as an alternative, demands guessed from those of most adjacent markets are often used as references in such cases. Reference markets can be those whose products are developed with the same categorical technologies. A market's demand may be expected to have the similar pattern with that of a reference market in case the adoption pattern of a product in the market is determined mainly by the technology related to the product. However, such processes may not always ensure pleasing results because the similarity between markets depends on intuition and/or experience. There are two major drawbacks that human experts cannot effectively handle in this approach. One is the abundance of candidate reference markets to consider, and the other is the difficulty in calculating the similarity between markets. First, there can be too many markets to consider in selecting reference markets. Mostly, markets in the same category in an industrial hierarchy can be reference markets because they are usually based on the similar technologies. However, markets can be classified into different categories even if they are based on the same generic technologies. Therefore, markets in other categories also need to be considered as potential candidates. Next, even domain experts cannot consistently calculate the similarity between markets with their own qualitative standards. The inconsistency implies missing adjacent reference markets, which may lead to the imprecise estimation of future demand. Even though there are no missing reference markets, the new market's parameters can be hardly estimated from the reference markets without quantitative standards. For this reason, this study proposes a case-based expert system that helps experts overcome the drawbacks in discovering referential markets. First, this study proposes the use of Euclidean distance measure to calculate the similarity between markets. Based on their similarities, markets are grouped into clusters. Then, missing markets with the characteristics of the cluster are searched for. Potential candidate reference markets are extracted and recommended to users. After the iteration of these steps, definite reference markets are determined according to the user's selection among those candidates. Then, finally, the new market's parameters are estimated from the reference markets. For this procedure, two techniques are used in the model. One is clustering data mining technique, and the other content-based filtering of recommender systems. The proposed system implemented with those techniques can determine the most adjacent markets based on whether a user accepts candidate markets. Experiments were conducted to validate the usefulness of the system with five ICT experts involved. In the experiments, the experts were given the list of 16 ICT markets whose parameters to be estimated. For each of the markets, the experts estimated its parameters of growth curve models with intuition at first, and then with the system. The comparison of the experiments results show that the estimated parameters are closer when they use the system in comparison with the results when they guessed them without the system.