• Journal of Wetlands Research
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• v.21 no.1
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• pp.57-65
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• 2019

LID(Low Impact Development) facility classified as a social infrastructure can maintain landscape sustainability and functional sustainability through continuous maintenance and management. Since LID is a natural-based solution, the sustainability can be secured through the management of weeds, wastes and vegetation. The LID facility is distributed in the city and is an infrastructure that can be managed through citizen participation because of simple maintenance. Therefore, this study was conducted to investigate the maintenance factors affecting the sustainability of the LID facilities and to suggest measures for maintenance by investigating the participation of the peoples. The factors for landscape sustainability were derived to waste and weed management. Also the factors for functional sustainability were assessed to identification and management of dead bodies and selection of applicable soil and plant species. The citizens showed high agreement of more than 80% in the questionnaires on expanding and managing LID facilities, enacting LID ordinances, and participating in the national movement. The intention to participate in LID management linked to jobs was about 64%, indicating that LID could become a job for the vulnerable. Maintenance of the LID can easily be carried out by non-specialists, which can lead to citizen participation with low cost for each facility. The maintenance cost for citizen participation can be allocated from the social infrastructure management cost reduced by LID application of the local government and the social welfare budget of the central government.

• Journal of Bio-Environment Control
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• v.28 no.4
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• pp.311-321
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• 2019

Greenhouse farmers often use thermal screens to reduce greenhouse heating expenses during the winter, and for shade during hot, sunny days in the summer, as it is an inexpensive solution to temperature control relative to other available options. However, accurate measurements of their emitted and absorbed radiations are important for the selection of suitable screens that offer maximum performance. Material's ability to save energy is highly dependent on these properties. Limited studies have investigated the measurement of these properties under natural conditions, but they are only applicable to materials having partial porosities. In this work, we describe a new radiation balance method for determining emissive power and absorptive capacity, as well as reflectivity, transmissivity and emissivity of materials having complete and partial transparency by using pyrgeometer and net radiometer. In this study, four materials with zero porosity, were tested. The emissivity value of PE, LD-13, LD-15 and PH-20 was $0.439{\pm}0.020$, $0.460{\pm}0.010$, $0.454{\pm}0.004$, and $0.499{\pm}0.006$, respectively. All tested samples showed high emitted radiation as compared to absorbed radiation.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.24 no.6
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• pp.1-13
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• 2021

This study was performed to investigate the ecosystem service patterns in relation to climate change acceleration utilizing big data analysis. This study aimed to use big data analysis as one of the network of views to identify convergent thinking in two fields: climate change and ecosystem service. The keywords were analysed to ascertain if there were any differences in the perceiving problems, policy direction, climate change implications, and regional differences. In addition, we examined the research keywords of each continent, the centre of ecosystem service research, and the topics to be referred to in domestic research. The results of the analysis are as follows: First, the keyword centrality of climate change is similar to the detailed indicators of The Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES) regulations, content, and non-material ecosystem services. Second, the cross-analysis of terms in two journals showed a difference in value-oriented point; the Ecosystem Service Journal identified green infrastructure as having economic value, whereas the Climate Change Journal perceives water, forest, carbon, and biodiversity as management topics. The Climate Change Journal, but not the former, focuses on future predictions. Third, the analysis of the research topics according to continents showed that water and soil are closely related to the economy, and thus, play an important role in policy formulation. This disparity is due to differences in each continent's environmental characteristics, as well as economic and policy issues. This fact can be used to refer to the direction of research on ecosystem services in Korea. Consistent with the recent trend of expanding research regarding the impacts of climate change, it is necessary to study strategies to scientifically predict and respond to the negative effects of climate change.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.3
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• pp.830-860
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• 2022

[Introduction] Nowadays, many companies are shifting their businesses online due to the growing trend among customers to buy and shop online, as people prefer online purchasing products. [Problem] Users share a vast amount of information about products, making it difficult and challenging for the end-users to make certain decisions. [Motivation] Therefore, we need a mechanism to automatically analyze end-user opinions, thoughts, or feelings in the social media platform about the products that might be useful for the customers to make or change their decisions about buying or purchasing specific products. [Proposed Solution] For this purpose, we proposed an automated SentiDecpective approach, which classifies end-user reviews into negative, positive, and neutral sentiments and identifies deceptive crowd-users rating information in the social media platform to help the user in decision-making. [Methodology] For this purpose, we first collected 11781 end-users comments from the Amazon store and Flipkart web application covering distant products, such as watches, mobile, shoes, clothes, and perfumes. Next, we develop a coding guideline used as a base for the comments annotation process. We then applied the content analysis approach and existing VADER library to annotate the end-user comments in the data set with the identified codes, which results in a labelled data set used as an input to the machine learning classifiers. Finally, we applied the sentiment analysis approach to identify the end-users opinions and overcome the deceptive rating information in the social media platforms by first preprocessing the input data to remove the irrelevant (stop words, special characters, etc.) data from the dataset, employing two standard resampling approaches to balance the data set, i-e, oversampling, and under-sampling, extract different features (TF-IDF and BOW) from the textual data in the data set and then train & test the machine learning algorithms by applying a standard cross-validation approach (KFold and Shuffle Split). [Results/Outcomes] Furthermore, to support our research study, we developed an automated tool that automatically analyzes each customer feedback and displays the collective sentiments of customers about a specific product with the help of a graph, which helps customers to make certain decisions. In a nutshell, our proposed sentiments approach produces good results when identifying the customer sentiments from the online user feedbacks, i-e, obtained an average 94.01% precision, 93.69% recall, and 93.81% F-measure value for classifying positive sentiments.

• Korean Journal of Remote Sensing
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• v.38 no.6_2
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• pp.1633-1641
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• 2022

Urban population concentration and indiscriminate development are causing various environmental problems such as air pollution and heat island phenomena, and causing human resources to deteriorate the damage caused by natural disasters. Urban trees have been proposed as a solution to these urban problems, and actually play an important role, such as providing environmental improvement functions. Accordingly, quantitative measurement and analysis of individual trees in urban trees are required to understand the effect of trees on the urban environment. However, the complexity and diversity of urban trees have a problem of lowering the accuracy of single tree detection. Therefore, we conducted a study to effectively detect trees in Dongjak-gu using high-resolution aerial images that enable effective detection of tree objects and You Only Look Once Version 5 (YOLOv5), which showed excellent performance in object detection. Labeling guidelines for the construction of tree AI learning datasets were generated, and box annotation was performed on Dongjak-gu trees based on this. We tested various scale YOLOv5 models from the constructed dataset and adopted the optimal model to perform more efficient urban tree detection, resulting in significant results of mean Average Precision (mAP) 0.663.

• Membrane Journal
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• v.32 no.2
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• pp.133-139
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• 2022

As the issue of reducing greenhouse gases is emerging due to global warming and extreme weather, research on materials capable of radiative cooling without energy consumption is being actively conducted. Among them, silk is known as a natural self-cooling material, but in the conventional mixing process using chemically powdered silk, there is a problem that the radiative cooling effect disappears by the collapses of the intrinsic crystal structure of silk fibroin, so it is difficult to manufacture it in the form of a film or coating agent for radiative cooling. In this study, various types of membranes were manufactured using silk powder that went through a physical pulverization process that does not damage the intrinsic structure of silk fibroin, and the study was conducted to examine its applicability as a coating agent. Electrospun membranes and flat sheet membranes were prepared by using silk fibroin powder for this purpose, and it was observed that the viscosity of the solution had a significant effect on the membrane fabrication and its properties.

• Journal of Korea Water Resources Association
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• v.55 no.11
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• pp.903-911
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• 2022

Groundwater, one of the resources for supplying water, fluctuates in water level due to various natural factors. Recently, research has been conducted to predict fluctuations in groundwater levels using Artificial Neural Network (ANN). Previously, among operators in ANN, Gradient Descent (GD)-based Optimizers were used as Optimizer that affect learning. GD-based Optimizers have disadvantages of initial correlation dependence and absence of solution comparison and storage structure. This study developed Gradient Descent combined with Harmony Search (GDHS), a new Optimizer that combined GD and Harmony Search (HS) to improve the shortcomings of GD-based Optimizers. To evaluate the performance of GDHS, groundwater level at Icheon Yullhyeon observation station were learned and predicted using Multi Layer Perceptron (MLP). Mean Squared Error (MSE) and Mean Absolute Error (MAE) were used to compare the performance of MLP using GD and GDHS. Comparing the learning results, GDHS had lower maximum, minimum, average and Standard Deviation (SD) of MSE than GD. Comparing the prediction results, GDHS was evaluated to have a lower error in all of the evaluation index than GD.

• The Journal of the Convergence on Culture Technology
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• v.8 no.5
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• pp.497-502
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• 2022

Information delivery among young generation has a distinct tendency to prefer visual to text as means of information distribution and sharing recently, and it is natural to distribute information through Youtube or one-man broadcasting on Internet. That is, young generation usually get their information through this kind of distribution procedure. Many young generation are also drastic and more aggressive for decorating themselves very uniquely. It tends to create personal characteristics freely through drastic expression and attempt of face makeup, hair styling and fashion coordination without distinction of sex. Especially, face makeup becomes an object of major concern among males nowadays, and female of course, then it is the major means to express their personality. In this study, to meet the demands of the times, we design and implement the intellectual smart mirror application that efficiently retrieves and recommends the related videos among Youtube or one-man broadcastings produced by famous professional makeup artists to implement the face makeup congruous with our face shape, hair color & style, skin tone, fashion color & style in order to create the face makeup that represent our characteristics. We also introduce the AI technique to provide optimal solution based on the learning of user's search patterns and facial features, and finally provide the detailed makeup face images to give the chance to get the makeup skill stage by stage.

• Clean Technology
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• v.15 no.1
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• pp.60-66
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• 2009

Adsorptive removal of tetrahydrothiophene (THT) and tert-butylmercaptan (TBM) that were widely used sulfur odorants in pipeline natural gas was studied using various ion-exchanged NaY zeolites at ambient temperature and atmospheric pressure. In order to improve the adsorption ability, ion exchange was performed on NaY zeolites with alkali metal cations of $Li^+,\;Na^+,\;K^+$ and transition metal cations of $Cu^{2+},\;Ni^{2+},\;Co^{2+},\;Ag^+$. Among the adsorbents tested, Cu-NaY and Ag-NaY showed good adsorption capacities for THT and TBM. These good behaviors of removal of sulfur compound for Cu-NaY and Ag-NaY zeolites probably was influenced by their acidity. The adsorption capacity for THT and TBM on the best adsorbent Cu-NaY-0.5, which was ion exchanged with 0.5 M copper nitrate solution, was 1.85 and 0.78 mmol-S/g at breakthrough, respectively. It was the best sulfur capacity so far in removing organic sulfur compounds from fuel gas by adsorption on zeolites. While the desorption activation energy of TBM on the Cu-NaY-0.5 was higher than NaY zeolite, the difference of THT desorption activation energy between two zeolites was comparatively small.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.5B
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• pp.429-439
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• 2009

When Catastrophic extreme flood occurs due to dam break, the response time for flood warning is much shorter than for natural floods. Numerical models can be powerful tools to predict behaviors in flood wave propagation and to provide the information about the flooded area, wave front arrival time and water depth and so on. But flood wave propagation due to dam break can be a process of difficult mathematical characterization since the flood wave includes discontinuous flow and dry bed propagation. Nevertheless, a lot of numerical models using finite volume method have been recently developed to simulate flood inundation due to dam break. As Finite volume methods are based on the integral form of the conservation equations, finite volume model can easily capture discontinuous flows and shock wave. In this study the numerical model using Riemann approximate solvers and finite volume method applied to the conservative form for two-dimensional shallow water equation was developed. The MUSCL scheme with surface gradient method for reconstruction of conservation variables in continuity and momentum equations is used in the predictor-corrector procedure and the scheme is second order accurate both in space and time. The developed finite volume model is applied to 2D partial dam break flows and dam break flows with triangular bump and validated by comparing numerical solution with laboratory measurements data and other researcher's data.