• Journal of Bio-Environment Control
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• v.32 no.4
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• pp.384-395
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• 2023

Since transpiration plays a key role in optimal irrigation management, knowledge of the irrigation demand of crops like tomatoes, which are highly susceptible to water stress, is necessary. One way to determine irrigation demand is to measure transpiration, which is affected by environmental factor or growth stage. This study aimed to estimate the transpiration amount of tomatoes and find a suitable model using mathematical and deep learning models using minute-by-minute data. Pearson correlation revealed that observed environmental variables significantly correlate with crop transpiration. Inside air temperature and outside radiation positively correlated with transpiration, while humidity showed a negative correlation. Multiple Linear Regression (MLR), Polynomial Regression model, Artificial Neural Network (ANN), Long short-term Memory (LSTM), and Gated Recurrent Unit (GRU) models were built and compared their accuracies. All models showed potential in estimating transpiration with R² values ranging from 0.770 to 0.948 and RMSE of 0.495 mm/min to 1.038 mm/min in the test dataset. Deep learning models outperformed the mathematical models; the GRU demonstrated the best performance in the test data with 0.948 R² and 0.495 mm/min RMSE. The LSTM and ANN closely followed with R² values of 0.946 and 0.944, respectively, and RMSE of 0.504 m/min and 0.511, respectively. The GRU model exhibited superior performance in short-term forecasts while LSTM for long-term but requires verification using a large dataset. Compared to the FAO56 Penman-Monteith (PM) equation, PM has a lower RMSE of 0.598 mm/min than MLR and Polynomial models degrees 2 and 3 but performed least among all models in capturing variability in transpiration. Therefore, this study recommended GRU and LSTM models for short-term estimation of tomato transpiration in greenhouses.

• Korean Journal of Health Education and Promotion
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• v.13 no.2
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• pp.130-166
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• 1996

As compared with body height and body weight by ages and sexes, by means of the data reported under other researchers from 1967 to 1994 for 33 years, this study obtained the estimate value of body height and body weight by ages and sexes for the same period, and figured out prediction value of body height and body weight in the ages of between 6 and 14 from 1995 to 2000. These surveys and measurements took for one year from October 1st 1994 to September 30th. As shown in the 〈Table 1〉, in order to calculate the establishment, estimate value and prediction value of the chronological regression model of body height and body weight, by well-grounded 17 representative research papers, this research statistically tested propriety of liner regression model by the residual analysis in advance of being reconciled to simple liner regression model by the autonomous variable-year and the subordinate variable-body weight and measured prediction value, theoretical value from 1962 to 1994 by means of 2nd or 3rd polynomial regression model, with this redult did prediction value from 1995 to 2000. 1. Chronological Change of Body Height and Body Weight The analysis result from regression model of the chronological body height and body weight for the aged 6 - 16 in both sexes ranging from 1962 to 1994, corned from the 〈Table 2-20〉. On the one hand, the measurement value of respective researchers had a bit changes by ages with age growing, but the other hand, theoretical value, prediction value showed the regular increase by the stages and all values indicated a straight line on growth and development with age growing. That is, in case of the aged 6, males had 109.93cm in 1962 and females 108.93cm, but we found the increase that males had 1I8.0cm, females 1I3.9cm. In theoretical value, prediction value, males showed the increase from 109.88cm to 1I7.89cm and females from 109.27cm to 1I5.64cm respectively. There was the same inclination toward all ages. 2. Comparision to Measurement Value and Prediction Value of Body Height and Body Weight in 1994 As shown in the 〈Table 21〉, in case of body height, measurement value and prediction value of body height and body weight by ages and sexes almost showed the similiar inclination and poor grade, in case of body weight, prediction value in males had a bit low value by all ages, and prediction value in females had a high value in adolescence, to the contrary, a low value in adult. 3. Prediction Value of Body Height and Body Weight from 1995 to 2000 This research showed that body height and body weight remarkably increased in adolescence but slowly in adult. This study represented that Korean physique was on the increase and must be measured continually hereafter.

• Food Science of Animal Resources
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• v.40 no.6
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• pp.938-945
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• 2020

A dynamic model was developed to predict the Escherichia coli cell counts in pig trotters at changing temperatures. Five-strain mixture of pathogenic E. coli at 4 Log CFU/g were inoculated to cooked pig trotter samples. The samples were stored at 10℃, 20℃, and 25℃. The cell count data was analyzed with the Baranyi model to compute the maximum specific growth rate (μ_max) (Log CFU/g/h) and lag phase duration (LPD) (h). The kinetic parameters were analyzed using a polynomial equation, and a dynamic model was developed using the kinetic models. The model performance was evaluated using the accuracy factor (A_f), bias factor (B_f), and root mean square error (RMSE). E. coli cell counts increased (p<0.05) in pig trotter samples at all storage temperatures (10℃-25℃). LPD decreased (p<0.05) and μ_max increased (p<0.05) as storage temperature increased. In addition, the value of h₀ was similar at 10℃ and 20℃, implying that the physiological state was similar between 10℃ and 20℃. The secondary models used were appropriate to evaluate the effect of storage temperature on LPD and μ_max. The developed kinetic models showed good performance with RMSE of 0.618, B_f of 1.02, and A_f of 1.08. Also, performance of the dynamic model was appropriate. Thus, the developed dynamic model in this study can be applied to describe the kinetic behavior of E. coli in cooked pig trotters during storage.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.4
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• pp.149-156
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• 2021

OTT service, which allows video content to be viewed as a streaming service on the Internet network, has recently attracted a lot of attention, and the number of users is also increasing rapidly. It would be a natural strategy for OTT companies to acquire more content to gain a competitive advantage in relations with traditional media companies and other OTT companies. However, there are research results to show that the investment in facilities by Internet service providers who must transport the increasing Internet traffic from OTT provider to end users should increase as the amount of Internet traffic originated by OTT services also increases. This study empirically analyzed how content investment by Netflix, a leading OTT company, affects its revenue growth and network investment by Internet service providers through a polynomial distributed lag model. And the analysis results show that Netflix's content investment contributes to the company's increase in revenue, and also has an effect on the increase in network investment by Internet service providers. This result confirms that OTT operators' content acquisition strategy is a valid management strategy, and empirically supports the study results that OTT operators need to share the cost of Internet network facility investment.

• The Journal of the Convergence on Culture Technology
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• v.9 no.1
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• pp.685-690
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• 2023

It was analyzed that the volume of deep excavation works adjacent to existing underground structures is increasing according to the population growth and density of cities. Currently, many underground structures and tracks are damaged by external factors, and the cause is analyzed based on the measurement results in the tunnel, and measurements are being made for post-processing, not for prevention. The purpose of this study is to analyze the effect on the deformation of the structure due to the excavation work adjacent to the urban railway track in use. In addition, the safety of structures is evaluated through machine learning techniques for displacement of structures before damage and destruction of underground structures and tracks due to external factors. As a result of the analysis, it was analyzed that the model suitable for predicting the structure management standard value time in the analyzed dataset was a polynomial regression machine. Since it may be limited to the data applied in this study, future research is needed to increase the diversity of structural conditions and the amount of data.

• Journal of Aquaculture
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• v.6 no.1
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• pp.13-27
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• 1993

In order to determine the protein requirements of the Korean rockfish Sebastes schlegeli six isocaloric diets containing crude protein level from 20\%\;to\;60\%$ were fed to two groups of fish, small and large size, with the initial average body weight of 8 g and 220 g respectively. White fish meal was used as a sole protein source. Daily weight gain, daily protein retention. daily energy retention, feed efficiency, protein retention efficiency and energy retention efficiency were significantly affected by the dietary protein content (p< 0.05). The growth parameters (that is, daily weight gain, daily protein retention and daily energy retention) increased up to $44\%$ protein level with no additional response above this point. The protein requirements were determined from daily weight gain using two different mathematical models. Second order polynomial regression analysis showed that maximum daily weight gain occurred at $56.7\%\;and\;50.6\%$ protein levels for the small size group and the large size group, respectively. However the protein requirements, determined by the broken line model, appeared to be about $40\%$ for both groups. Nutrient utilization also suggested that the protein requirements of both groups were close to $40\%$. When daily protein intake was considered, daily protein requirements per 100g of fish, estimated by the broken line model, were 0.99g and 0.35g for the small and large size groups respectively. Based on these results, a $40\%$ dietary crude protein level could be recommended for the optimum growth and efficient nutrient utilization of the Korean rockfish weighing between 8g and 300g.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.29 no.4
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• pp.464-473
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• 1996

Two-month feeding experiment was conducted to investigate the optimum dietary protein level and energy to protein ratio in fat cod (Hexagrammos otakii Jordan et STARKS). The fish averaging 29 g were fed with one of the isocaloric diets containing 30, 40, 50 or $60\%$ of protein, or with one of the isoproteic diets containing 9, 10, 11 or 12 of available energy/protein (E/P) ratio. Weight gain and feed efficiency increased significantly with dietary protein level up to $50\%$, then decreased with $60\%$ protein diet (P<0.05). Daily protein intake increased significantly with dietary protein level, whereas protein efficiency ratio decreased with dietary protein level (P<0.05). Second order polynomial regression analyses of percent weight gain and daily protein intake may indicate that the adequate dietary protein level is $45\%$ and daily protein requirement per 100g fish is 1.5g for maximal growth. Weight gain, feed efficiency and protein efficiency from fish led the diet containing 12 of E/P ratio were significantly higher than those from fish fed the other diets (P<0.05). Daily feed or protein intake from fish fed the diet containing 12 of E/P ratio was significantly lower than those from fish fed the other diets (P<0.05). Daily lipid intake increased significantly with dietary E/P ratio (P<0.05).

• Journal of Bio-Environment Control
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• v.31 no.4
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• pp.409-415
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• 2022

Plant growth and development are also affected by root-zone environment. Therefore, it is important to consider the variables of the root-zone environment when establishing an irrigation strategy. The purpose of this study is to analyze the relationship between the volumetric moisture content (VWC), Bulk EC (ECb), and Pore EC (ECp) used by plant roots using FDR sensors in two types of rockwool media with different water transmission characteristics, using the method above this was used to establish a method for collecting and correcting available root-zone environmental data. For the experiment, two types of rockwool medium (RW1, RW2) with different physical characteristics were used. The moisture content (MC) and ECb were measured using an FDR sensor, ECp was measured after extracting the residual nutrient solution from the medium using a disposable syringe in the center of the medium at a volumetric moisture content (VWC) of 10-100%. Then, ECb and ECp are measured by supplying nutrient solution having different concentration (distilled water, 0.5-5.0) to two types of media (RW1, RW2) in each volume water content range (0 to 100%). The relationship between ECb and ECp in RW1 and RW2 media is best suited for cubic polynomial. The relationship between ECb and ECp according to volume moisture content (VWC) range showed a large error rate in the low volume moisture content (VWC) range of 10-60%. The correlation between the sensor measured value (ECb) and the ECp used by plant roots according to the volumetric water content (VWC) range was the most suitable for the Paraboloid equation in both media (RW1, RW2). The coefficient of determination the calibration equation for RW1 and RW2 media were 0.936, 0.947, respectively.