• Journal of Korean Institute of Industrial Engineers
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• v.33 no.4
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• pp.487-493
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• 2007

In this paper, we deal with an optimal software-release problem of determining the time to stop testing and release the software system to the user. The optimal release time problem is considered from maintenance like the periodic distribution of service packs and the unpredictable distribution of patches after the release. Moreover, the environment of software error-detection during operation differs from the environment during testing. This paper proposes the software reliability growth model which incorporates periodic service packs, unpredictable patches and operational environment. Based on the proposed model, we derive optimal release time to minimize total cost composed of fixing an error, testing and maintenance. Using numerical examples, optimal release time is determined and illustrated.

• Korean Journal of Soil Science and Fertilizer
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• v.50 no.5
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• pp.409-421
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• 2017

Recently Unmanned Aerial Vehicle (UAV) technology offers new opportunities for assessing crop growth condition using UAV imagery. The objective of this study was to select optimal vegetation indices and regression model for estimating of rice growth using UAV images. This study was conducted using a fixed-wing UAV (Model : Ebee) with Cannon S110 and Cannon IXUS camera during farming season in 2016 on the experiment field of National Institute of Crop Science. Before heading stage of rice, there were strong relationships between rice growth parameters (plant height, dry weight and LAI (Leaf Area Index)) and NDVI (Normalized Difference Vegetation Index) using natural exponential function ($R{\geq}0.97$). After heading stage, there were strong relationships between rice dry weight and NDVI, gNDVI (green NDVI), RVI (Ratio Vegetation Index), CI-G (Chlorophyll Index-Green) using quadratic function ($R{\leq}-0.98$). There were no apparent relationships between rice growth parameters and vegetation indices using only Red-Green-Blue band images.

• Journal of People, Plants, and Environment
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• v.23 no.5
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• pp.545-554
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• 2020

Background and objective: Moth orchids in the vegetative stage are suitable for a multi-layer growing environment in a closed-type plant factory which can be a good alternative that can reduce production costs by reducing cultivation time and energy cost per plant. This study was conducted to find out the optimal rhizospheric environment for different irrigation methods without a potting medium and rhizospheric ventilation for the vegetative growth of young Phalaenopsis hybrid 'Blanc Rouge' (P. KV600 × P. Kang 1) and Phalaenopsis Queen Beer 'Mantefon' in a closed-type plant factory system. Methods: The one-month-old clonal micropropagules with bare roots rapped with a sponges were fixed on the holes of styrofoam plates above growth beds, and were watered using the ebb-and-flow (EBB) and aeroponic (AER) methods with Ichihashi solution (0.5 strength) once a day at 06:00 (P) or 18:00 (S), and both (PS). Rhizospheric ventilation (V) was also applied to change the temperature, relative humidity, and CO₂ concentration of the beds. Plants potted into sphagnum moss and watered once a week were used as the control group. Results: After 12 months of treatment, the growth characteristics of the EBB groups were the best among the treatment groups without a medium, but no effect of irrigation timing was observed. V reduced the temperature, relative humidity and CO₂ concentration of the beds. Whereas, EBB+V (ebb-and-flow with ventilation) improved plant growth and reduced the occurrence of disorders and withering. Especially, EBB+V showed a similar performance to the control group. Conclusion: The results indicated that the optimal irrigation method without a potting medium for producing middle-aged potted moth orchids was the EBB system with forced rhizospheric ventilation. Therefore, further studies on the optimal ventilation method and moisture control of the crown need to be carried out to develop the irrigation system without a potting medium for vertical farming in closed-type plant factories.

• Journal of Korean Society on Water Environment
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• v.29 no.2
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• pp.155-164
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• 2013

To confirm the relationship between climate change and Stephanodiscus in Mulgeum station of Nakdong River, Korea, this study was conducted. The temperature in crease by climate change was observed in the study site, where the temperature was gradually increased in most seasons, except for summer season. The mass proliferation of Stephanodiscus constantly appeared in every year, especially between November and March, and when Stephanodiscus abundance was above 90% in phytoplankton biomass. Among this period, phytoplankton biomass was high related with water temperature ($r^2$=0.249, P<0.01) than nutrient factors such as nitrogen and phosphorus in the study site. Finally, temperature by climate change can be regarded as the affecting factor for chl. a variation, because temperature was strongly related with water temperature ($r^2$=0.748, P<0.01). From 1997 to 2010, the annual maximum phytoplankton biomass was recorded in the range of temperature from $4.8^{\circ}C$ to $8.4^{\circ}C$, and the range was regarded as the temperature condition for the optimal growth of Stephanodiscus in the study site. On the optimal growth temperature, the trend of monthly average temperature corresponded to the trend of chl. a variation from November to March. In future, the increase of temperature by climate change can prolong Stephanodiscus blooming period in winter and spring seasons.

• Journal of Biosystems Engineering
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• v.24 no.5
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• pp.445-452
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• 1999

This study was conducted to develop a searching algorithm for optimal daily temperature setpoint greenhouse. An algorithm using crop growth and energy models was developed to determine optimum crop growth environment. The results of this study were as follows: 1. Mathematical models for crop growth and energy consumption were derived to define optimal daily temperature setpoint. 2. Optimum temperature setpoint, which could maximize performance criterion, was determined by using Pontryagin maximum principle. 3. Dynamic control of daily temperature using the developed algorithm showed higher performance criterion than static control with fixed temperature setpoint. Performance criteria for dynamic control models were with simulated periodic weather data and with real weather data, increased by 48% and 60%, respectively.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.2
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• pp.144-156
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• 2023

Smart agriculture is a rapidly growing field that seeks to optimize crop yields and reduce risk through the use of advanced technology. A key challenge in this field is the need to create a comprehensive smart farm system that can effectively monitor and control the growth environment of crops, particularly when cultivating new varieties. This is where fuzzy theory comes in, enabling the collection and analysis of external environmental factors to generate a rule-based system that considers the specific needs of each crop variety. By doing so, the system can easily set the optimal growth environment, reducing trial and error and the user's risk burden. This is in contrast to existing systems where parameters need to be changed for each breed and various factors considered. Additionally, the type of house used affects the environmental control factors for crops, making it necessary to adapt the system accordingly. While developing such a framework requires a significant investment of labour and time, the benefits are numerous and can lead to increased productivity and profitability in the field of smart agriculture. We developed an AI platform for optimal control of facility houses by integrating data from mushroom crops and environmental factors, and analysing the correlation between optimal control conditions and yield. Our experiments demonstrated significant performance improvement compared to the existing system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.27 no.1
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• pp.27-33
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• 2023

Demands for eco-friendly food materials are increasing rapidly because of increased interest in well-being and health care, deterioration of air quality due to fine dust, and various soil and water pollution. Aquaponics is a system that can solve various problems such as economic activities, environmental problems, and safe food provision of the elderly population. However, techniques for deriving the optimal growth environment should be preceded. In this paper, we intend to design an intelligent plant growth measurement system that considers the characteristics of existing aquaponics. In particular, we would like to propose a module configuration plan for learning data and judgment systems when providing a uniform growth environment, focusing on designing systems suitable for production sites that do not have high-performance processing resources among intelligent aquaponics production management modules. It is believed that the proposed system can effectively perform deep learning with small analysis resources.

• Korean Journal of Environmental Agriculture
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• v.26 no.4
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• pp.332-336
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• 2007

Pseudomonas stutzeri strain KCCM 34719 was used in this experiment to determine the effects of increasing Pb(II) concentrations on its growth rate. To obtain optimum growth conditions, strain KCCM 34719 was cultivated in nutrient broth under various conditions, such as temperature, pH, and NaCl concentration. Optimal conditions for cell growth were $30^{\circ}C$ of temperature, 8.0 of pH, and 3% of NaCl concentration, respectively. Growth response of bacterial cell to Pb(II) showed tolerance to concentrations ranging from 10 to 100 mg ${\ell}^{-1}$ in liquid culture, following a growth pattern similar to the control. Growth rate was greatly inhibited at 200 mg ${\ell}^{-1}$ of Pb(II).

• Korean Journal of Medicinal Crop Science
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• v.23 no.4
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• pp.311-318
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• 2015

This study had been conducted to investigate the effect of some plant growth regulators inducing fruit enlargement and optimal harvest time in Sageretia thea. Two hundred fifty $mg/{\ell}$ mepiquat chloride treatment, $1mg/{\ell}$ thidiazuron treatment on full bloom, and $200mg/{\ell}$ gibberellic acid treatment on 7 days before full bloom resulted in the increase of 21.7% in weight, and $200mg/{\ell}$ gibberellic acid treatment 7 days before full bloom, 10$mg/{\ell}$ forchlorfenuron treatment 14 days after full bloom, and $1mg/{\ell}$ thidiazuron treatment on full bloom also brought about positive effects on the enlargement of the fruit, increasing 6.3%, 6.3% and 8.1% in its transverse diameter, respectively. Furthermore, the effects of the plant growth regulator treatments on the harvest time of Sageretia thea were determined as follows: the increase in the optimal harvest time of 57.2 - 75.4%, shorter maturation period, by the treatments with $500mg/{\ell}$ mepiquat chloride 7 days after full bloom, $100mg/{\ell}$ gibberellic acid treatment on full bloom, $2.5mg/{\ell}$ forchlorofenuron 7 days after full bloom and $2mg/{\ell}$ thidiazuron treatment 7 days before full bloom; and the greater effects of plant growth regulator treatments on the fruit maturation in the following order, gibberellic acid > thidiazuron > forchlorofenuron > mepiquat chloride. The results of this study are expected to be used as a reference data to develop Sageretia thea as a new local specific crop for Jeju island.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.26 no.4
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• pp.217-224
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• 2014

Cochlodinium polykrikoides is a typical harmful algal species which generates the red-tide in the coastal zone, southern Korea. Accurate algal growth model can be established and then the prediction of the red-tide occurrence using this model is possible if the information on the optimal growth model parameters are available because it is directly related between the red-tide occurrence and the rapid algal bloom. However, the limitation factors on the algal growth, such as light intensity, water temperature, salinity, and nutrient concentrations, are so diverse and also the limitation function types are diverse. Thus, the study on the algal growth model development using the available laboratory data set on the growth rate change due to the limitation factors are relatively very poor in the perspective of the model. In this study, the growth model on the C. polykrikoides are developed and suggested as the optimal model which can be used as the element model in the red-tide or ecological models. The optimal parameter estimation and an error analysis are carried out using the available previous research results and data sets. This model can be used for the difference analysis between the lab. condition and in-situ state because it is an optimal model for the lab. condition. The parameter values and ranges also can be used for the model calibration and validation using the in-situ monitoring environmental and algal bloom data sets.