• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.3 no.4
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• pp.83-90
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• 2010

The demands of analysis for the physical errors of systems and prediction system using this has increased steadily with computing environment growth linking real system just like IT Convergence. The physical errors are unpredictable because of relations of various elements such as natural phenomenon and mechanical errors. Especially, the elevator system occurs various problems because of the complexity of system so that we need to efficient approach for this. In this paper, we propose the analysis and management system for elevator based on data minining that predict the error to gather information about physical or natural phenomenon. This helps actively responding in early stage and saving lives through prediction of error and an early warning for just such an eventuality.

• Journal of Environmental Impact Assessment
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• v.21 no.1
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• pp.105-117
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• 2012

Future climate according to land-use change was simulated by regional climate model. The goal of study was to predict the distribution of meteorological elements using the Weather Research & Forecasting Model (WRF). The KME (Korea Ministry of Environment) medium-category land-use classification was used as dominant vegetation types. Meteorological modeling requires higher and more sophisticated land-use and initialization data. The WRF model simulations with HyTAG land-use indicated certain change in potential vegetation distribution in the future (2086-2088). Compared to the past (1986-1988) distribution, coniferous forest area was decreased in metropolitan and areas with complex terrain. The research shows a possibility to simulate regional climate with high resolution. As a result, the future climate was predicted to $4.5^{\circ}$ which was $0.5^{\circ}$ higher than prediction by Meteorological Administration. To improve future prediction of regional area, regional climate model with HyTAG as well as high resolution initial values such as urban growth and CO2 flux simulation would be desirable.

• 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.

• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.861-866
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• 2023

Unlike conventional smart farms that require chemical fertilizers and large spaces, aquaponics farming, which utilizes the symbiotic relationship between aquatic organisms and crops to grow crops even in abnormal environments such as environmental pollution and climate change, is being actively researched. Different crops require different environments and nutrients for growth, so it is necessary to configure the ratio of aquatic organisms optimized for crop growth. This study proposes a method to measure the degree of growth based on area and volume using image processing techniques in an aquaponics environment. Tilapia, carp, catfish, and lettuce crops, which are aquatic organisms that produce organic matter through excrement, were tested in an aquaponics environment. Through 2D and 3D image analysis of lettuce and real-time data analysis, the growth degree was evaluated using the area and volume information of lettuce. The results of the experiment proved that it is possible to manage cultivation by utilizing the area and volume information of lettuce. It is expected that it will be possible to provide production prediction services to farmers by utilizing aquatic life and growth information. It will also be a starting point for solving problems in the changing agricultural environment.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.198-198
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• 2016

The Citarum River Basin is the biggest river basin in West Java Province, Indonesia and it plays strategic roles in providing water for irrigation, domestic and industrial uses, and power generation, besides controlling the flood during rainy season. Flowing through seven major cities makes the river flow and water demand are vulnerable to land use change around the river. The present water resources management has involved the regulator, operator, and users in deciding an appropriate water management plan for the entire basin. The plan includes an operation plan for three reservoirs, construction or maintenance of the river channel, and water allocation for all users along the river. Following this plan, a smaller operation group will execute and evaluates the plan based on the actual flow condition. Recently, a deforestation, environment degradation, river sedimentation, a rapid growth of population and industry, also public health become new issues that should be considered in water basin planning. Facing these arising issues, a new development program named ICWRMIP was established to advance the existing management system. This program includes actions to strengthen institutional collaboration, do the restoration and conservation of the river environment, improve water quality and public health, also advance the water allocation system. At present, the water allocation plan is created annually based on a forecasted flow data and water usage prediction report. Sometimes this method causes a difficulty for the operator when the actual flow condition is not the same as the prediction. Improving existing system, a lot of water allocation studies, including a development of the database and water allocation simulation model have been placed to help stakeholders decide the suitable planning schemes. In the future, this study also tries to contribute in advancing water allocation planning by creating an optimization model which ease stakeholders discover a suitable water allocation plan for individual users.

• Nuclear Engineering and Technology
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• v.55 no.12
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• pp.4527-4542
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• 2023

The present microbial reinforcement of rock and soil exhibits limitations, such as uneven reinforcement effectiveness and low calcium carbonate generation rate, resulting in limited solidification strength. This study introduces electroosmosis as a standard microbial grouting reinforcement technique and investigates its solidification effects on microbial-reinforced uranium tailings. The most effective electroosmosis effect on uranium tailings occurs under a potential gradient of 1.25 V/cm. The findings indicate that a weak electric field can effectively promote microbial growth and biological activity and accelerate bacterial metabolism. The largest calcium carbonate production occurred under the gradient of 0.5 V/cm, featuring a good crystal combination and the best cementation effect. Staged electroosmosis and electrode conversion efficiently drive the migration of anions and cations. Under electroosmosis, the cohesion of uranium tailings reinforced by microorganisms increased by 37.3% and 64.8% compared to those reinforced by common microorganisms and undisturbed uranium tailings, respectively. The internal friction angle is also improved, significantly enhancing the uniformity of reinforcement and a denser and stronger microscopic structure. This research demonstrates that MICP technology enhances the solidification effects and uniformity of uranium tailings, providing a novel approach to maintaining the safety and stability of uranium tailings dams.

• Journal of Climate Change Research
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• v.5 no.2
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• pp.109-125
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• 2014

Suitable climate condition is essential for stable growth of crops which directly leads to an increase in crop production. Preceding domestic researches mostly used crop models to predict grain or crop yield in relation to climate change. However, the use of various models and input data based on foreign background lowered the reliability for result. Therefore in this study, we evaluated domestic applicability by comparing and analyzing various crop models developed abroad. In addition, we selected models based on the possibility of acquiring input data and suggested domestic applicability.

• Smart Media Journal
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• v.11 no.5
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• pp.9-16
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• 2022

Recently, agricultural sites are automating into digital agricultural smart farms by applying technologies such as big data and Internet of Things (IoT). These smart farms aim to increase production and improve crop quality by measuring the environment of crops, investigating and processing data. Production prediction is an important study in smart farm digital agriculture, which is a high-tech agriculture, and it is necessary to analyze environmental data using big data and further standardized research to manage the quality of growth information data. In this paper, environmental and production data collected from smart farm strawberry farms were analyzed and studied. Based on regression analysis, crop production prediction models were analyzed using Ridge Regression, LightGBM, and XGBoost. Among the three models, the optimal model was XGBoost, and R2 showed 82.5 percent explanatory power. As a result of the study, the correlation between the amount of positive fluid absorption and environmental data was confirmed, and significant results were obtained for the production prediction study. In the future, it is expected to contribute to the prevention of environmental pollution and reduction of sheep through the management of sheep by studying the amount of sheep absorption, such as information on the growing environment of crops and the ingredients of sheep.

• Smart Structures and Systems
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• v.22 no.2
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• pp.193-200
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• 2018

From the viewpoint of engineering applications, the prediction of the failure of bogies plays an important role in preventing the occurrence of fatigue. Fatigue is a complex phenomenon affected by many uncertainties (such as load, environment, geometrical and material properties, and so on). The key to predict fatigue damage accurately is how to quantify these uncertainties. A Bayesian model is used to account for the uncertainty of various sources when predicting fatigue damage of structural components. In spite of improvements in the design of fatigue-sensitive structures, periodic non-destructive inspections are required for components. With the help of modern nondestructive inspection techniques, the fatigue flaws can be detected for bogie structures, and fatigue reliability can be updated by using Bayesian theorem with inspection data. A practical fatigue analysis of welded bogies is utilized to testify the effectiveness of the proposed methods.

• Journal of Bio-Environment Control
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• v.10 no.3
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• pp.133-140
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• 2001

This study was conducted to develop a nutrient uptake model in cucumnber (Cucumis sativus L. cv. Eunsung Backdadagi) plants for prediction of the amount of nutrients in drainage solution in a closed perlite culture system. Electrical conductivity (EC) of the nutrient solution was adjusted to 1.5, 1.8, 2.1, 2.4, and 2.7 dS. $m^{-1}$ . The amount of nutrient solution absorbed in different EC treatments was not different until the mid stage of growth. However, after the mid growth stage, a high EC treatment resulted in less solution absorption. The absorption rates of K, N $O_3$$^{[-10]}$ -N, Mg, and P increased continuously for a whole growing period in all treatments, while those of Ca decreased slightly. For S, the decrease was significant after th mid stage of growth. although the amounts of absorbed inorganic ions in different EC treatments were not significantly different at the first stage of growth, they were significantly different after the mid stage of growth and decreased slightly at the end of growth stage. Models for predicting the amounts of each inorganic ion absorbed were developed by using EC and the amount of nutrient solution absorbed per unit radiation(mg.M $J^{-1}$), which proved to be practical with a positive correlation at 1 percent probability between the developed model and practical values..