• Korean Journal of Remote Sensing
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• 제40권1호
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• pp.93-101
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• 2024

Accurate field crop classification is essential for various agricultural applications, yet existing methods face challenges due to diverse crop types and complex field conditions. This study aimed to address these issues by combining support vector machine (SVM) models with multi-seasonal unmanned aerial vehicle (UAV) images, texture information extracted from Gray Level Co-occurrence Matrix (GLCM), and RGB spectral data. Twelve high-resolution UAV image captures spanned March-October 2021, while field surveys on three dates provided ground truth data. We focused on data from August (-A), September (-S), and October (-O) images and trained four support vector classifier (SVC) models (SVC-A, SVC-S, SVC-O, SVC-AS) using visual bands and eight GLCM features. Farm maps provided by the Ministry of Agriculture, Food and Rural Affairs proved efficient for open-field crop identification and served as a reference for accuracy comparison. Our analysis showcased the significant impact of hyperparameter tuning (C and gamma) on SVM model performance, requiring careful optimization for each scenario. Importantly, we identified models exhibiting distinct high-accuracy zones, with SVC-O trained on October data achieving the highest overall and individual crop classification accuracy. This success likely stems from its ability to capture distinct texture information from mature crops.Incorporating GLCM features proved highly effective for all models,significantly boosting classification accuracy.Among these features, homogeneity, entropy, and correlation consistently demonstrated the most impactful contribution. However, balancing accuracy with computational efficiency and feature selection remains crucial for practical application. Performance analysis revealed that SVC-O achieved exceptional results in overall and individual crop classification, while soybeans and rice were consistently classified well by all models. Challenges were encountered with cabbage due to its early growth stage and low field cover density. The study demonstrates the potential of utilizing farm maps and GLCM features in conjunction with SVM models for accurate field crop classification. Careful parameter tuning and model selection based on specific scenarios are key for optimizing performance in real-world applications.

• Advances in aircraft and spacecraft science
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• 제10권6호
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• pp.495-519
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• 2023

The drone serves the customers not served by vans. At the same time, considering the safety, policy and terrain as well as the need to replace the battery, the drone needs to be transported by truck to the identified station along with the parcel. From each such station, the drone serves a subset of customers according to a direct assignment pattern, i.e., every time the drone is launched, it serves one demand node and returns to the station to collect another parcel. Similarly, the truck is used to transport the drone and cargo between stations. This is somewhat different from the research of other scholars. In terms of the joint distribution of the drone and road vehicle, most scholars will choose the combination of two transportation tools, while we use three. The drone and vans are responsible for distribution services, and the trucks are responsible for transporting the goods and drone to the station. The goal is to optimize the total delivery cost which includes the transportation costs for the vans and the delivery cost for the drone. A fixed cost is also considered for each drone parking site corresponding to the cost of positioning the drone and using the drone station. A discrete optimization model is presented for the problem in addition to a two-phase heuristic algorithm. The results of a series of computational tests performed to assess the applicability of the model and the efficiency of the heuristic are reported. The results obtained show that nearly 10% of the cost can be saved by combining the traditional delivery mode with the use of a drone and drone stations.

• Journal of Aerospace System Engineering
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• 제18권3호
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• pp.41-47
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• 2024

Recently, as the practical application and commercialization of unmanned aerial vehicles (UAVs) is pursued, interest in ensuring the safety of the UAV is increasing. Because UAV accidents can result in property damage and loss of life, it is important to develop technology to prevent accidents. For this reason, a technique to detect the abnormal flight state of UAVs has been developed based on the AutoEncoder model. However, the existing detection technique is limited in terms of performance and real-time processing. In this paper, we propose a U-Net based abnormal flight detection technique. In the proposed technique, abnormal flight is detected based on the increasing rate of Mahalanobis distance for the reconstruction error obtained from the U-Net model. Through simulation experiments, it can be shown that the proposed detection technique has superior detection performance compared to the existing detection technique, and can operate in real-time in an on-board environment.

• Journal of The Korean Society of Agricultural Engineers
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• 제66권3호
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• pp.1-14
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• 2024

Gaining an accurate 3D stream geometry has become feasible with Unmanned Aerial Vehicle (UAV), which is crucial for better understanding stream hydrodynamic processes. The objective of this study was to investigate series of filters to remove stream vegetation and propose the best method for generating Digital Terrain Models (DTMs) using UAV-based point clouds. A stream reach approximately 500 m of the Bokha stream in Icheon city was selected as the study area. Point clouds were obtained in August 1st, 2023, using Phantom 4 multispectral and Zenmuse L1 for Structure from Motion (SfM) and Light Detection And Ranging (LiDAR) respectively. Three vegetation filters, two morphological filters, and six composite filters which combined vegetation and morphological filters were applied in this study. The Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) were used to assess each filters comparing with the two cross-sections measured by leveling survey. The vegetation filters performed better in SfM, especially for short vegetation areas, while the morphological filters demonstrated superior performance on LiDAR, particularly for taller vegetation areas. Overall, the composite filters combining advantages of two types of filters performed better than single filter application. The best method was the combination of Progressive TIN (PTIN) and Color Indicies of Vegetation Extraction (CIVE) for SfM, showing the smallest MAE of 0.169 m. The proposed method in this study can be utilized for constructing DTMs of stream and thus contribute to improving the accuracy of stream hydrodynamic simulations.

• Journal of the Institute of Convergence Signal Processing
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• 제24권4호
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• pp.241-248
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• 2023

Despite the recent short history of drones, the applying field of drones has been used for various purposes in a wide variety of areas and fields. As such, with the emergence of various types of drones over the years, in a broad sense, a remote controlled mobile object that can be controlled by wired and wireless control may be a suitable definition for drone because of various types of drones in recent years. This paper aims to help readers who want to research, develop, and use drones by examining the history, application fields, and future prospects of drones, including Unmanned Surface Vehicle(USV) and Unmanned Underwater Vehicles(UUV), as well as aerial type drones. Through this paper, it is expected that these drones will continue to be used in various fields in the future, and the prospect of future development will continue constantly. However, for the development of domestic drone technology and industry, the government's improvement in drone-related regulations should be supported.

• Journal of Korean Society of Industrial and Systems Engineering
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• 제47권2호
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• pp.176-189
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• 2024

Vertical takeoff and landing (VTOL) is a core feature of unmanned aerial vehicles (UAVs), which are commonly referred to as drones. In emerging smart logistics, drones are expected to play an increasingly important role as mobile platforms. Therefore, research on last-mile delivery using drones is on the rise. There is a growing trend toward providing drone delivery services, particularly among retailers that handle small and lightweight items. However, there is still a lack of research on a structural definition of the VTOL drone flight model for multi-point delivery service. This paper describes a VTOL drone flight route structure for a multi-drone delivery service using rotary-wing type VTOL drones. First, we briefly explore the factors to be considered when providing drone delivery services. Second, a VTOL drone flight route model is introduced using the idea of the nested graph. Based on the proposed model, we describe various time-related attributes for delivery services using drones and present corresponding calculation methods. Additionally, as an application of the drone route model and the time attributes, we comprehensively describe a simple example of the multi-drone delivery for first-come-first-served (FCFS) services.

• Korean Journal of Soil Science and Fertilizer
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• 제26권1호
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• pp.10-19
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• 1993

This study reports the influence of nitrogen application on the yield and the accumulation of $NO_3{^-}$ in edible parts of major vegetables in a pot experiment treated with five levels(0, 1, 2, 4, 8g N/pot) of nitrogen. In the $NO_3{^-}$ accumulation of chinese cabbage the outer leaf were superior to the inner leaf. The $NO_3{^-}$ contents of the midrib in outer and inner leaf were higher than those of the leaf blade. By increasing the nitrogen application, the accumulationsgap in $NO_3{^-}$ accumulation between midrib and leaf blade in a leaf, became larger. The difference ratio of $NO_3{^-}$ accumulation in the outer leaf reached 4.8:1 at 8g N/pot treatment. In theradish, the $NO_3{^-}$ accumulation in the aerial root parts is higher than those of the underground root parts, and it is higher in the leaf than in the petiole. The accumulation of $NO_3{^-}$ in sarcocarp of cucumber was increased along with the added amount of nitrogen, but contents of $NO_3{^-}$ in the core of the cucumber showed no differences in the treatment levels. The $NO_3{^-}$ accumulation differences of outer sarcocarp vs. inner core parts in cucumber was increased along with the higher nitrogen levels, and its difference ratio of $NO_3{^-}$ accumulation reached 13.1:1 at 8g N/pot treatment. The highest $NO_3{^-}$ accumulation in edible parts of chinese cabbage, radish and cucumber were found at the 8g N/pot treatment, and were 3,664ppm in the outer leaf midrib of chinese cabbage, 3,449ppm in the aerial part of root of radish, and 484ppm in sarcocarp part of cucumber. Compared with the control each 130 times, 40.8 times, 20.9 times, respectively. There are positive correlation coefficients between the amount of nitrogen fertilization, $NO_3{^-}$ accumulation in the edible parts, yield, and yield components of edible parts.

• Journal of Bio-Environment Control
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• 제32권2호
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• pp.106-114
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• 2023

With rising concerns about pesticide spray drift by aerial application, this study attempt to evaluate aerodynamic property and collection efficiency of spray drift according to the leaf area index (LAI) of crop for preventing undesirable pesticide contamination by the spray-drift tunnel experiment. The collection efficiency of the plant with 'Low' LAI was measured at 16.13% at a wind speed of 1 m·s^-1. As the wind speed increased to 2 m·s^-1, the collection efficiency of plant with the same LAI level increased 1.80 times higher to 29.06%. For the 'Medium' level LAI, the collection efficiency was 24.42% and 43.06% at wind speed of 1 m·s^-1 and 2 m·s^-1, respectively. For the 'High' level LAI, it also increased 1.24 times higher as the wind speed increased. The measured results indicated that the collection of spray droplets by leaves were increased with LAI and wind speed. This also implied that dense leaves would have more advantages for preventing the drift of airborne spray droplets. Aerodynamic properties also tended to increase as the LAI increased, and the regression analysis of quadric equation and power law equation showed high explanatory of 0.96-0.99.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• 제44권12호
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• pp.1043-1053
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• 2016

In this paper, the application of Parallel Distributed Compensation (PDC) controller for fixed pitch rotary wing system was studied. For nonlinear modeling, T-S fuzzy model was utilized to advance system control including the tilt type UAV. PDC controller was designed through the Linear Matrix Inequality (LMI). Experiments for determining the applicability and feasibility of PDC were performed using the 1 axis attitude control equipment and simulation. To verify the performance and characteristics of the controller, Mathworks Co. Simulink was used. After then, the PDC controller performance was verified and the results with developed controller using a 1 axis attitude control equipment were compared. Verification of the feasibility of PDC controller for the fixed pitch rotary wing system and identification of the overall performance and improvement analysis was conducted based on the experimental results.

• The Korean Journal of Pesticide Science
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• 제19권4호
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• pp.399-401
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• 2015

This study investigated the plant growth promoting activity of geraniol on Chinese cabbage (Brasscia campestris ssp. Pekinensis Rupr.), Pak Choi (Brassica rapa L.), Crown daisy (Chrysanthemum coronarium L.), Iceberg lettuce (Lactuca sativa L.) and Leaf perilla (Perilla frutescens Britt.). Geraniol at 0.5 to $10mg\;L^{-1}$ promoted radical growth of Chinese cabbage Pak Choi, Crown daisy, Iceberg lettuce and leaf perilla by >30%. In the pot experiments, geraniol treatment at $20mg\;L^{-1}$ by drenching increased up to 190% of the aerial part growth promotion. By comparison, foliar application showed 124% promoting activity only at $100mg\;L^{-1}$.