• Journal of Aerospace System Engineering
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• v.17 no.1
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• pp.33-41
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• 2023

As seen in the case of the Boeing 737 Max accident, the proportion of aircraft software is rapidly increasing. However, it is vulnerable to safety issues. In case of domestic aircraft software, to operate a Light Unmanned Aerial Vehicle (LUAV) less than an empty weight of 150 kg, safety certification is required for an Ultra-Light Vehicle (ULV). However, software certification procedure is not included. Since the use of LUAVs has increased recently, software verification is required. This paper proposed a checklist of LUAV software that could be applied to LUAV referring DO-178C, an aviation software certification standard. A case study of applying the proposed checklist to the Model-based Development-based Helicopter Flight Control Computer (FCC) project currently used by domestic and foreign advanced companies and institutions was conducted.

• The Plant Pathology Journal
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• v.39 no.2
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• pp.171-180
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• 2023

Spring black stem and leaf spot, caused by Phoma medicaginis, is an issue in annual Medicago species. Therefore, in this study, we analyzed the response to P. medicaginis infection in a collection of 46 lines of three annual Medicago species (M. truncatula, M. ciliaris, and M. polymorpha) showing different geographic distribution in Tunisia. The reaction in the host to the disease is explained by the effects based on plant species, lines nested within species, treatment, the interaction of species × treatment, and the interaction of lines nested within species × treatment. Medicago ciliaris was the least affected for aerial growth under infection. Furthermore, the largest variation within species was found for M. truncatula under both conditions. Principal component analysis and hierarchical classification showed that M. ciliaris lines formed a separate group under control treatment and P. medicaginis infection and they are the most vigorous in growth. These results indicate that M. ciliaris is the least susceptible in response to P. medicaginis infection among the three Medicago species investigated here, which can be used as a good candidate in crop rotation to reduce disease pressure in the field and as a source of P. medicaginis resistance for the improvement of forage legumes.

• The Plant Pathology Journal
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• v.39 no.3
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• pp.275-289
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• 2023

Fungal isolates from infected Chinese quince trees were found to cause black rot in Yeongcheon, Gyeongsangbuk Province, Korea. The quince leaves withered and turned reddish-brown and fruits underwent black mummification. To elucidate the cause of these symptoms, the pathogen was isolated from infected leaf and fruit tissues on potato dextrose agar and Levan media. Several fungal colonies forming a fluffy white or dark gray mycelium and two types of fungi forming an aerial white mycelium, growing widely at the edges, were isolated. Microscopic observations, investigation of fungal growth characteristics on various media, and molecular identification using an internal transcribed spacer, β-tubulin, and translation elongation factor 1-α genes were performed. The fungal pathogens were identified as Diplodia parva and Diplodia crataegicola. Pathogenicity tests revealed that the pathogen-inoculated fruits exhibited a layered pattern, turning brown rotting; leaves showed circular brown necrotic lesions. The developed symptoms were similar to those observed in the field. Fungal pathogens were reisolated to fulfill Koch's postulates. Apples were inoculated with fungal pathogens to investigate the host range. Strong pathogenicity was evident in the fruits, with browning and rotting symptoms 3 days after inoculation. To determine pathogen control, a fungicidal sensitivity test was conducted using four registered fungicides. Thiophanate-methyl, propineb, and tebuconazole inhibited the mycelial growth of pathogens. To the best of our knowledge, this is the first report on the isolation and identification of the fungal pathogens D. parva and D. crataegicola from infected fruits and leaves of Chinese quince, causing black rot disease in Korea.

• Journal of The Geomorphological Association of Korea
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• v.27 no.2
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• pp.65-80
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• 2020

This paper deals with risk assessment of life in a landslide-prone area by a GIS-based modeling method. Landslide susceptibility maps can provide a probability of landslide prone areas to mitigate or proper control this problems and to take any development plan and disaster management. A landslide inventory map of the study area was prepared based on past historical information and aerial photography analysis. A total of 550 landslides have been counted at the whole study area. The extracted landslides were randomly selected and divided into two different groups, 50% of the landslides were used for model calibration and the other were used for validation purpose. Eleven causative factors (continuous and thematic) such as slope, aspect, curvature, topographic wetness index, elevation, forest type, forest crown density, geology, land-use, soil drainage, and soil texture were used in hazard analysis. The correlation between landslides and these factors, pixels were divided into several classes and frequency ratio was also extracted. Eventually, a landslide susceptibility map was constructed using a logistic regression model based on entire events. Moreover, the landslide susceptibility map was plotted with a receiver operating characteristic (ROC) curve and calculated the area under the curve (AUC) and tried to extract a success rate curve. Based on the results, logistic regression produced an 85.18% accuracy, so we believed that the model was reliable and acceptable for the landslide susceptibility analysis on the study area. In addition, for risk assessment, vulnerability scale were added for social thematic data layer. The study area predictive landslide affected pixels 2,000 and 5,000 were also calculated for making a probability table. In final calculation, the 2,000 predictive landslide affected pixels were assumed to run. The total population causalities were estimated as 7.75 person that was relatively close to the actual number published in Korean Annual Disaster Report, 2006.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.88-88
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• 2022

Detection of stress responses in crops is important to diagnose crop growth and evaluate yield. Also, the multi-spectral sensor is effectively known to evaluate stress caused by nutrient and moisture in crops or biological agents such as weeds or diseases. Therefore, in this experiment, multispectral images were taken by an unmanned aerial vehicle(UAV) under field condition. The experiment was conducted in the long-term fertilizer field in the National Institute of Crop Science, and experiment area was divided into different status of NPK(Control, N-deficiency, P-deficiency, K-deficiency, Non-fertilizer). Total 11 vegetation indices were created with RGB and NIR reflectance values using python. Variations in nutrient content in plants affect the amount of light reflected or absorbed for each wavelength band. Therefore, the objective of this experiment was to evaluate vegetation indices derived from multispectral reflectance data as input into machine learning algorithm for the classification of nutritional deficiency in rice. RandomForest model was used as a representative ensemble model, and parameters were adjusted through hyperparameter tuning such as RandomSearchCV. As a result, training accuracy was 0.95 and test accuracy was 0.80, and IPCA, NDRE, and EVI were included in the top three indices for feature importance. Also, precision, recall, and f1-score, which are indicators for evaluating the performance of the classification model, showed a distribution of 0.7-0.9 for each class.

• Korean Journal of Remote Sensing
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• v.40 no.1
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• pp.9-18
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• 2024

Small streams, despite their rich ecosystems, face challenges in vegetation assessment due to the limitations of traditional, time-consuming methods. This study presents a groundbreaking approach, combining unmanned aerial vehicles(UAVs), convolutional neural networks(CNNs), and the vegetation differential vegetation index (VDVI), to revolutionize both assessment and management of stream vegetation. Focusing on Idong Stream in South Korea (2.7 km long, 2.34 km² basin area)with eight diverse revetment methods, we leveraged high-resolution RGB images captured by UAVs across five dates (July-December). These images trained a ResNeXt101 CNN model, achieving an impressive 89% accuracy in classifying vegetation cover(soil,water, and vegetation). This enabled detailed spatial and temporal analysis of vegetation distribution. Further, VDVI calculations on classified vegetation areas allowed assessment of vegetation vitality. Our key findings showcase the power of this approach:(a) TheCNN model generated highly accurate cover maps, facilitating precise monitoring of vegetation changes overtime and space. (b) August displayed the highest average VDVI(0.24), indicating peak vegetation growth crucial for stabilizing streambanks and resisting flow. (c) Different revetment methods impacted vegetation vitality. Fieldstone sections exhibited initial high vitality followed by decline due to leaf browning. Block-type sections and the control group showed a gradual decline after peak growth. Interestingly, the "H environment block" exhibited minimal change, suggesting potential benefits for specific ecological functions.(d) Despite initial differences, all sections converged in vegetation distribution trends after 15 years due to the influence of surrounding vegetation. This study demonstrates the immense potential of UAV-based remote sensing and CNNs for revolutionizing small-stream vegetation assessment and management. By providing high-resolution, temporally detailed data, this approach offers distinct advantages over traditional methods, ultimately benefiting both the environment and surrounding communities through informed decision-making for improved stream health and ecological conservation.

• Journal of Aerospace System Engineering
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• v.17 no.6
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• pp.9-15
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• 2023

In order to effectively prevent and respond to disasters, several techniques have been developed in which the pilot wearing a see-through Head Mounted Display (HMD) performs disaster-related rescue activities using images transmitted from an Unmanned Aerial Vehicle (UAV). However, these techniques have limitations in quickly determining and executing tasks appropriate to the on-site situation because the pilot cannot recognize the entire field in an integrated manner. In order to overcome these problems, we propose an AR based-interface technique that allows the rescuer wearing a see-through HMD to operate a UAV efficiently. Simulation results show that the proposed interface technique allows the rescuer wearing a see-through HMD to control the gimbal and flight of the UAV at a high speed based on finger gestures in a visibility situation.

• Journal of Aerospace System Engineering
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• v.18 no.3
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• pp.48-55
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• 2024

In recent years, as the commercialization of unmanned aerial vehicles (UAVs) has been actively promoted, much attention has been focused on developing a technology to ensure the safety of UAVs. In general, the UAV has the potential to enter an uncontrollable state caused by sudden maneuvers, disturbances, and pilot error. To prevent entering an uncontrolled situation, it is essential to predict the flight state of the UAV. In this paper, we propose a flight state prediction technique based on an improved CNN-LSTM hybrid mode to enhance the flight state prediction performance. Simulation results show that the proposed prediction technique offers better state prediction performance than the existing prediction technique, and can be operated in real-time in an on-board environment.

• Korean Journal of Environmental Agriculture
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• v.27 no.2
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• pp.178-184
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• 2008

This work was carried out to investigate the effect of waterlogging on the growth and nutrient contents of 'Campbell Early' and 'Kyoho' grapevines under the vinyl house condition from June 14 to July 20, 2005. For the trial, seedlings of two-year-old grapevine were transplanted to 40 L pot with a sandy loam soil. Irrigation point of non-waterlogging(control) treatment was controlled at -40 kPa of soil water tension using tensiometer and waterlogging treatments were imposed for 35 days at the water levels of above 10 cm from the soil surface using tap water. The growth of aerial(shoot length, leaf number and stem diameter) and underground(root) parts of 'Campbell Early' and 'Kyoho' grapevines tended to be wholly reduced by waterlogging, while the growth of aerial parts were more severely impaired in 'Kyoho' than in 'Campbell Early' cultivar. The different responses for waterlogging between two grapevines seem to be related with the capacity for absorbing mineral nutrients, because nitrogen content of 'Campbell Early' cultivar leaves was significantly higher than that of 'Kyoho' cultivar although the contents of phosphorus and potassium in leaves of two grapevine cultivars were similarly declined. There was no significant different of fruit quality, such as contents of soluble solid, titratable acidity and weight of berry in 'Campbell Early' between waterlogging and control. In 'Kyoho' cultivar, however, berry weight and titratable acidity were decreased and soluble solid content was increased by waterlogging. It was assumed that waterlogging stress for grapevines promotes maturation and coloring processes of berries by stimulating maturation hormone such as ethylene. In conclusion, 'Campbell Early' cultivar seems to be more tolerable than 'Kyoho' cultivar when comparing the growth responses and nutrient contents between two grapevine cultivars under waterlogging.

• Korean Journal of Medicinal Crop Science
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• v.4 no.4
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• pp.301-307
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• 1996

The experiment was conducted to clarify the effect of water stress treatment on growth character of Ligusticum chuanxiong Hort. The water stress treatment was imposed artificially on seedling, flowering and rhizome enlargement stage of the plant. The decrease ratio of leaf area compare with control decreased to 24.4% by water stress treatment at seedling stage and to 41.6% at rhizome enlargement stage. The reduction rate of chlorophyll content at the end of water stress treatment was 41.2% at the see­dling stage and no difference at the flowering stage. The chlorophyll content of water stress treatment on seedling and flowering stage was recovered to 95% at harvest time. The ratio of rootlet distribution from top soil to l0cm depth showed maximum to 90% at the seedling stage and to 20cm depth showed max­imum to 6.4% at the rhizome enlargement stage. The dry weight of rootlet was decreased to $19.3{\sim}40.3%$ by water stress treatment. Dry weight of aerial part and underground part of the plant decreased in the order of seedling, flowering, rhizome enlargement and control and the dry weight of aerial part decrease more severely than underground part.