• Journal of Aerospace System Engineering
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• v.17 no.4
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• pp.133-143
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• 2023

As drones (also known as UAV) become popular with advanced information and communication technology (ICT), they have been utilized for various fields (agriculture, architecture, and so on). However, malicious attackers with advanced drones may pose a threat to critical national infrastructures. Thus, anti-drone systems have been developed to respond to drone threats. In particular, remote identification data (R-ID)-based UAV detection and identification systems that detect and identify illegal drones with R-ID broadcasted by drones have been developed, and are widely employed worldwide. However, this R-ID-based UAV detection/identification system is vulnerable to security due to wireless broadcast characteristics. In this paper, we analyze the security vulnerabilities of DJI Aeroscope, a representative example of the R-ID-based UAV detection and identification system, and propose a replay-attack-based neutralization method using the analyzed vulnerabilities. To validate the proposed method, it is implemented as a software program, and verified against four types of attacks in real test environments. The results demonstrate that the proposed neutralization method is an effective neutralization method for R-ID-based UAV detection and identification systems.

• Journal of Practical Agriculture & Fisheries Research
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• v.20 no.1
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• pp.107-123
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• 2018

The global impact of climate change on agriculture is now increasing. The purpose of this study was to investigate the effect of climate change on livestock productivity. The variables that have the greatest influence on climate change factors were examined through previous studies and expert surveys. We also used the actual productivity data of livestock farmers to investigate the relationship with climate change. In order to evaluate the climate for changes in livestock productivity, national representative data (such as bullocks, dairy, pigs, laying hens, and broilers) were surveyed in Korea. Also, to select and classify evaluation indexes, we selected climate change factor variables as prior studies and studied the weighting factor of climate variable factors. In this study, the researchers of industry, academia, and farmers in the livestock sector conducted questionnaires on the indicators of vulnerability to climate change using experts, and then weighed the selected indicators using the hierarchical analysis process (AHP). In order to verify the validity of the evaluation index, was examined using domestic climate data (temperature, precipitation, humidity, etc.). Correlation and regression analysis were performed. The empirical relationship between climate change and livestock productivity was examined through this study. As a result, we used data with high reliability of statistical analysis and found that there are significant variables.

• Research in Plant Disease
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• v.28 no.3
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• pp.113-121
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• 2022

Rice blast is a major plant disease that occurs worldwide and significantly reduces rice yields. Rice blast disease occurs periodically in Korea, causing significant socio-economic damage due to the unique status of rice as a major staple crop. A disease outbreak prediction system is required for preventing rice blast disease. Epidemiological investigations of disease outbreaks can aid in decision-making for plant disease management. Currently, plant disease prediction and epidemiological investigations are mainly based on quantitatively measurable, structured data such as crop growth and damage, weather, and other environmental factors. On the other hand, text data related to the occurrence of plant diseases are accumulated along with the structured data. However, epidemiological investigations using these unstructured data have not been conducted. The useful information extracted using unstructured data can be used for more effective plant disease management. This study analyzed news articles related to the rice blast disease through text mining to investigate the years and provinces where rice blast disease occurred most in Korea. Moreover, the average temperature, total precipitation, sunshine hours, and supplied rice varieties in the regions were also analyzed. Through these data, it was estimated that the primary causes of the nationwide outbreak in 2020 and the major outbreak in Jeonbuk region in 2021 were meteorological factors. These results obtained through text mining can be combined with deep learning technology to be used as a tool to investigate the epidemiology of rice blast disease in the future.

• Korean Chemical Engineering Research
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• v.45 no.2
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• pp.133-142
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• 2007

As the environmental pollution caused by excessive uses of chemical fertilizers and pesticides is aggravated, organic farming using pasture and livestock manure is gaining an increased necessity. The application rate of the organic farming materials to the field is determined as a function of crops and soil types, weather and cultivation surroundings. When livestock manure is used for organic farming materials, the volatilization of ammonia from field-spread animal manure is a major source of atmospheric pollution and leads to a significant reduction in the fertilizer value of the manure. Therefore, an ammonia emission model should be presented to reduce the ammonia emission and to know appropriate application rate of manure. In this study, the ammonia emission rate from field-applied pig manure is predicted using an artificial neural network (ANN) method, where the Michaelis-Menten equation is employed for the ammonia emission rate model. Two model parameters (total loss of ammonia emission rate and time to reach the half of the total emission rate) of the model are predicted using a feedforward-backpropagation ANN on the basis of the ALFAM (Ammonia Loss from Field-applied Animal Manure) database in Europe. The relative importance among 15 input variables influencing ammonia loss is identified using the weight partitioning method. As a result, the ammonia emission is influenced mush by the weather and the manure state.

• Journal of Bio-Environment Control
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• v.29 no.1
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• pp.73-79
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• 2020

The objective of this study is to analyze the heat transfer loss of covering materials in a single-span plastic greenhouse under the steady-state wind environment. To achieve this objective, the following were conducted: (1) design of a small-scaled wind tunnel (SCWT) to analyze heat losses of the greenhouse and its performance; (2) determination of the overall heat transfer coefficient (OHTC) for the covering materials using a small-scaled greenhouse model. The SCWT consists of the blowing, dispersion, steady flow, reduction and testing areas. Each part of the SCWT was customized and designed to maintain air flow at steady state and to minimize the variances in the SCWT test. In this study, the OHTCs of the covering materials were calculated by separating each with the roof, side wall, front and back of the small-scaled greenhouse model. The results of this study show that the OHTC of the roof increases as wind speed increases but the zones in which the increase rate of the OHTC decreased, were distinguished by wind tunnel wing speed of 2 ms^-1. For the side wall, the increase rate of the OHTC was particularly higher in the 0-1 ms^-1 zone.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.33 no.3
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• pp.95-102
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• 2015

This study conducted the survey on the resources of traditional villages based on AHP in the subjects with the specialists in Korea and China to seek the resource evaluation standards to apply the preservation and development of traditional villages, and the differences of the importance on the resources among the specialists in both countries. We classified three levels of evaluation items to aim the deductions of the importance and priority in the resources of traditional villages. Upon the analysis results, natural resources were important in the level 1; environmental, historical, facility resources were important in the level 2; and the factors such as air, topography, traditional houses, agricultural landscape, shared community facilities, interchanges between urban and rural areas, family activities, and so on were important in the level 3. The factors that both Korean and Chinese groups evaluated as the most important ones were the same. In terms of overall importance by evaluation items, the factors such as air, water quality, noise, traditional houses, topography, shared community facilities, and so on were rated as relatively important in both Korean and Chinese groups. That is, the traditional villages have the necessity to preserve the cultural resources like their duties, however, it is required to control the natural environment with good quality preferentially. This study results can compare the importance on the resources of traditional village between Korea and China. Moreover, with calculation of the priority and scores for the preservation and management of traditional villages, they are expected to be used as the tool to apply the quantitative data in the evaluation process of traditional village resources in both countries.

• Journal of Korean Society of Environmental Engineers
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• v.33 no.1
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• pp.9-15
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• 2011

The first objective of this study was to investigate water pollution status of Meejae Reservoir, Kunsan, irregularly receiving river water for agricultural and recreational purposes. The second objective of the study was to compare nutrient pollution loads of three nutrient sources: sediment leaching, non-point sources and the receiving water. Water analysis results showed that eutrophication was a concern especially in summer and the calculated TSI (secchi depth), TSI (chlorophyll-a), and TSI (TP) were 53.6, 57.7 and 56.7, respectively. Although there was no significant difference in seasonal mean values of sediment T-N, sediment T-P and sediment organic content, mean differences were found for sampling points. However, T-N and T-P sediment release flux showed seasonal mean differences, while showing no mean difference for sampling points. Water T-N data proportionally correlated with sediment T-N and sediment organic content data, while no statistical correlation was found for water T-P data. Comparison of nutrient loads calculated from three sources showed that the highest T-N load was occurred from the receiving (pumped) water while T-P loads of the receiving water and sediment release flux were similar. The first solution would be considered for the receiving water to improve the water quality of Meejae Reservoir. Reduction of nutrient flux from the sediment would be then tried as the second alternative solution.

• Korean Journal of Environmental Agriculture
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• v.38 no.3
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• pp.154-158
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• 2019

BACKGROUND: 'Shiranuhi' mandarin is a major cultivar among all late ripening type of citrus, and is widely cultivated in Korea. However, many farmers have reported scion root problems in their orchard resulting in reduced flowering and fruiting. It is necessary that the physiology of scion-rooted 'Shiranuhi' mandarin trees is further understood. METHODS AND RESULTS: This experiment was conducted to understand the growth response and physiology of scion-rooted 'Shiranuhi' mandarin hybrids. In our study, 'Shiranuhi' mandarin trees were divided into two groups: trees without scion roots (control) and trees with scion roots. The experiment was conducted in Seogwipo of Jeju, with ten replicates for each group. Growth of trees with scion roots was more vigorous and the trees were taller than the controls. Tree height and trunk diameter of scion-rooted trees were significantly higher than those of control trees. Exposed length of rootstocks of scion-rooted trees was significantly lower (by about 2 cm) than that of control trees (8.6 cm). In terms of root nutrition, carbon contents of scion-rooted trees was significantly lower than that of control trees, but nitrogen and potassium concentrations in scion roots were significantly higher than those in control roots. CONCLUSION: Based on the results, we infer that growth of scion-rooted trees was very vigorous and the content of nitrogen in these roots was higher than that in the control tree roots. Thus, the carbon/nitrogen ratio of scion roots was significantly lower than that of the control roots.

• Journal of Korea Water Resources Association
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• v.55 no.12
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• pp.1137-1147
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• 2022

River and groundwater stages are the main elements in the hydrologic cycle. They are spatially correlated and can be used to evaluate hydrological and agricultural drought. Stochastic simulation is often performed independently on hydrological variables that are spatiotemporally correlated. In this setting, interdependency across mutual variables may not be maintained. This study proposes the Bayesian vector autoregression model (VAR) to capture the interdependency between multiple variables over time. VAR models systematically consider the lagged stages of each variable and the lagged values of the other variables. Further, an autoregressive model (AR) was built and compared with the VAR model. It was confirmed that the VAR model was more effective in reproducing observed interdependency (or cross-correlation) between river and ground stages, while the AR generally underestimated that of the observed.

• Journal of Bio-Environment Control
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• v.31 no.4
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• pp.270-278
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• 2022

This study was conducted using deep learning technology to classify for 'Mihwang' peach maturity with RGB images and fruit quality attributes during fruit development and maturation periods. The 730 images of peach were used in the training data set and validation data set at a ratio of 8:2. The remains of 170 images were used to test the deep learning models. In this study, among the fruit quality attributes, firmness, Hue value, and a^* value were adapted to the index with maturity classification, such as immature, mature, and over mature fruit. This study used the CNN (Convolutional Neural Networks) models for image classification; VGG16 and InceptionV3 of GoogLeNet. The performance results show 87.1% and 83.6% with Hue left value in VGG16 and InceptionV3, respectively. In contrast, the performance results show 72.2% and 76.9% with firmness in VGG16 and InceptionV3, respectively. The loss rate shows 54.3% and 62.1% with firmness in VGG16 and InceptionV3, respectively. It considers increasing for adapting a field utilization with firmness index in peach.