• Journal of the Korean Society of Marine Environment & Safety
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• v.20 no.6
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• pp.619-626
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• 2014

In this paper, it was constructed the halophyte Mesocosm experimental which was used tidal flat and dredged sediment as a substrate material. Depending on the vegetation and substrate material of Mesocosm, Mesocosm A(tidal flat sediment + Salicornia herbacea), Mesocosm B (only dredged sediment), Mesocosm C(dredged sediment + Salicornia herbacea). Monitoring was carried out of Warter quality factots(Chemical Oxygen Demand(COD), Total Nitrogen(T-N), Total Phosphorus(T-P), water temperature, salinity), Sediment factors(Chemical Oxygen Demand(COD), Total Nitrogen(T-N), Total Phosphorus(T-P)) and growth of Salricornia herbacea. Habitat Stability Index of vegetation was calculating by using the monitoring results. HSI of Mesocosm C was calculated from 0.87 to 0.95 as compared to the relatively high HSI in Mesocosm A, it was evaluated to be able to be used in the restoration and construction of the coastal salt marsh with dredged sediment.

• Journal of Environmental Health Sciences
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• v.49 no.6
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• pp.295-304
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• 2023

Background: Adolescents are relatively more sensitive than adults to exposure to indoor pollutants. The indoor air quality in classrooms where students spend time together must therefore be managed at a safe level because it can affect the health of students. Objectives: In this study, three types of green-wall models were applied to classrooms where students spend a long time in a limited space, and the resulting effects on reducing PM were evaluated. Methods: In the middle school classrooms which were selected as the experimental subjects, IoT-based indoor air quality monitoring equipment was installed for real-time monitoring. Three types of plant models (passive, active, and active+light) were installed in each classroom to evaluate the effects on improving indoor air quality. Results: The concentration of PM in the classroom is influenced by outdoor air quality, but repeated increases and decreases in concentration were observed due to the influence of students' activities. There was a PM reduction effect by applying the green-wall model. There was a difference in PM reduction efficiency depending on the type of green-wall model, and the reduction efficiency of the active model was higher than the passive model. Conclusions: The active green-wall model can be used as an efficient method of improving indoor air quality. Additionally, more research is needed to increase the efficiency of improving indoor air quality by setting conditions that can stimulate the growth of each type of plant.

• Journal of Internet of Things and Convergence
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• v.10 no.2
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• pp.61-67
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• 2024

In order to monitor the growth environment of new varieties of crops, it is necessary to build the agricultural production infrastructure and strengthen the agricultural resource management system using popular smart sensor tag technology. In addition, the infrastructure for improving high-quality new varieties of crops using IoT technology and the monitoring system must be strengthened. In other words, widespread smart sensor (RFID UHF Sensor Tag) technology for environmental monitoring required for improving new crop varieties is desperately needed in the smart farm environment. Therefore, in this paper, we implemented an integrated sensor that can implement smart tag functions based on heterogeneous integrated sensors. In addition, we developed a technology that can manage crops in real time through the implemented smart integrated tag and smartphone linkage. For this purpose, an integrated antenna capable of RFID and Bluetooth communication was constructed. In addition, a communication method that allows information to be collected directly from the smartphone through the Bluetooth function was used.

• Korean Journal of Environmental Agriculture
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• v.35 no.2
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• pp.148-151
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• 2016

BACKGROUND: There are few studies on the impacts of hydrophytes on water quality, so there is a need to research the effects of death of hydrophytes on the worsening of water quality. This study aimed to monitor the effects of Trapa japonica death on reservoir water quality.METHODS AND RESULTS: T.japonica shows the life cycle that highest growth in summer and rapid death in fall decomposing their body in general. T.japonica contains comparatively large portion of nutrients and minerals. Through the field survey using Mesocosm to identify the effects of excessive population of T.japonica on water quality, the water quality of plots planted T.japonica is gradually worse compared with the control plot. And the result of Wilcoxon-test also shows that the negative effect of T.japonica on water quality with significant (p<0.05).CONCLUSION: It is necessary to control the population growth of T.japonica in order to prevention of water pollution in fall.

• The Journal of Asian Finance, Economics and Business
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• v.4 no.4
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• pp.61-66
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• 2017

Environmental awareness and its relation to the development of economy has garnered increased attention in recent years. Researchers, over the years, have argued that sustainable development warrants for minimizing environmental degradation since one depends on the other. This study analyzes the relationship between environmental degradation (carbon emission taken as proxy for degradation), economic growth, total energy consumption and industrial production index growth in Bangladesh from year 1998 to 2013. This study uses Vector Autoregression (VAR) Model and variance decomposition of VAR to analyze the effect of these variables on carbon emission and vice-versa. The findings of VAR model suggest that industrial production and GDP per capita has significant relationship with carbon emission. Further analysis through variance decomposition shows carbon emission has consistent impact on industrial production over time, whereas, industrial production has high impact on emission in the short run which fades in the long run which is consistent with Environmental Kuznets Curve (EKC) hypothesis. Carbon emission rising along with GDP per capita and at the same time having low impact in the long run on industrial index indicates there may be other sources of pollution introduced with the rise in income of the economy over time.

• Journal of information and communication convergence engineering
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• v.22 no.3
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• pp.221-230
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• 2024

The aim of this study is to investigate the automatic recognition and analysis of Jeju marine-life images using artificial intelligence (AI) technology. The dataset of marine-life images was prepared using tools such as Python, TensorFlow, and Google Colab (Google Colaboratory). We also developed models by training deep learning AI in image recognition to automatically recognize the species found in these images and extract their associated information, such as taxonomy, characteristics, and distribution. This study is innovative in that it uses deep learning technology combined with imagerecognition technology for marine biodiversity research. In addition, these results will lead to the development of the marine-life industry in Jeju by supporting marine environment monitoring and marine resource conservation. Furthermore, this study is anticipated to contribute to academic advancement, specifically in the study of marine species diversity.

• Korean Journal of Environment and Ecology
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• v.24 no.3
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• pp.302-317
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• 2010

In this study, not only to present the management plan but also to verify the effectiveness for a area of improving the landscape and the area of creating the base of bio-inhabitation in Tancheon stream concrete embankment where were practised the vegetation-mat measures for greening via monitoring i.e. restoration progress. The results of monitoring, there were a total of 41 taxa, 18 families, 38 species, 3 varieties in 2006, moreover in the 2007, there were a total of 59 taxa, 19 families, 56 species, 3 varieties and in the period 2008, 64 taxa, 29 families, 59 species, 8 varieties. Therefore, these site has increased the plant spaces year by year. The distribution of vegetation characteristics shows that Miscanthus sacchariflorus and Pennisetum alopecuroides expands their influence in the area of applying the construction method. Those area appears a diversity of native species by the stream deposition at the flood. Thus, its condition is very soundly ecological health and eco-friend. At present, native species have been dominant, however, disturbed species and invasive species can be expected to increase dramatically in the future. Therefore, it is necessary to a long-range monitoring and management for maintaining an environmentally sound aquatic ecosystem. On this area refer to mix the river vegetation of primary succession and disturbed vegetation. For that reason, the method of constructing the vegetation-mat measures for greening in embankment does not need to remove the concrete and can install a coir-mat on the top. It leads to improve the landscape, moreover, it was analysed the such dramatic changes in the vegetation species richness by providing continuous the plant growth basis have a impact on in bio-diversity.

• Journal of Korean Society on Water Environment
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• v.31 no.2
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• pp.181-195
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• 2015

Algal blooms in lakes are one of major environmental issues in Korea. A three-dimensional, hydrodynamic and water quality model was developed and tested in Lake Euiam to assess the performance and limitations of numerical modeling with multiple algal groups using field data commonly collected for algal management. In this study, EFDC was adopted as the basic model framework. Simulated vertical profiles of water temperature, dissolved oxygen and nutrients monitored at five water quality monitoring stations from March to October 2013, which are closely related to algal dynamics simulation, showed good agreement with those of observed data. The overall spatio-temporal variations of three algal groups were reasonably simulated against the chlorophyll-a levels of those estimated from the limited monitoring data (chlorophyll-a level and cell numbers of algal species) with the RMSEs ranging from 2.6 to $17.5mg/m^3$. Also, note that $PO_4-P$ level in the water column was a key limiting factor controlling the growth of three algal groups during most of simulation period. However, the algal modeling results were not fully attainable to the levels of observation during short periods of time showing abrupt increase in algae throughout the lake. In particular, the green algae/cyanobacteria and diatom simulations were underestimated in late June to early July and early October, respectively. The results shows that better understanding of internal algal processes, neglected in most algal modeling studies, is necessary to predict the sudden algal blooms more accurately because the concentrations of external $PO_4-P$ and specific algal groups originated from the tributaries (mainly, dam water releases) during the periods were too low to fully capture the sharp rise of internal algal levels. In this respect, this study suggests that future modeling efforts should be focused on the quantification of internal cycling processes including vertical movement of algal species with respect to changes in environmental conditions to enhance the modeling performance on complex algal dynamics.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.5
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• pp.563-569
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• 2018

This paper is on the implementation of a system for automatically monitoring window farm hydroponics based on Arduino (utilizing Arduino's open source code) emerging as the icon of the Fourth Industrial Revolution. A window farm, which means window-type hydroponics, is offered as an alternative to fulfill the desires of people who want to grow plants aside from the busy daily life in the city. The system proposed in this paper was developed to automatically monitor a window farm hydroponics cultivation environment using the Arduino UNO board, a four-charmel motor shield, temperature and humidity sensors, illumination sensors, and a real-time clock module. Modules for hydroponics have been developed in various forms, but power consumption is high because most of them use general power and motors. Since it is not a system that is monitored automatically, there is a disadvantage in that an administrator always has to manage its operational state. The system is equipped with a water supply that is most suitable for a plant growth environment by utilizing temperature, humidity, and light sensors, which function as Internet of Things sensors. In addition, the real-time clock module can be used to provide a more appropriate water supply. The system was implemented with sketch code in a Linux environment using Raspberry Pi 3 and Arduino UNO.

• Journal of Mushroom
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• v.15 no.3
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• pp.118-123
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• 2017

This study was carried out to develop the technology to manage the growth of mushrooms, which were cultivated based on long-term information obtained from quantified data. In this study, hardware that monitored and controlled the growth environment of the mushroom cultivation house was developed. An algorithm was also developed to grow mushrooms automatically. Environmental management for the growth of mushrooms was carried out using cultivation sites, computers, and smart phones. To manage the environment of the mushroom cultivation house, the environmental management data from farmers cultivating the highest quality mushrooms in Korea were collected and a growth management database was created. On the basis of the database value, the management environment for the test cultivar (hukthali) was controlled at $0.5^{\circ}C$ with 3-7% relative humidity and 10% carbon dioxide concentration. As a result, it was possible to produce mushrooms that were almost similar to those cultivated in farms with the best available technology.