• Journal of the Korean GEO-environmental Society
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• v.24 no.11
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• pp.41-49
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• 2023

In this study, we analyzed the settlement characteristics of rockfill embankments mixed with soil by confirming the physical properties of soil materials mixed with silty materials and analyzing the compression characteristics of gravel materials according to the mixing ratio of soil materials. For this, we mixed silty materials into sandy soil to analyze the compression characteristics of soil materials, and we constructed a foundation by mixing various ratios of soil into rockfill materials with a particle distribution similar to that of river gravel, and conducted a one-dimensional compression experiment using a medium-sized chamber. As a result of the experiment, in the case of mixed soil materials, the Transition Fine Content (TFC) appeared in the range of 21~26% depending on the load condition, and in the case of rockfill materials mixed with soil, as the void filling ratio of soil in gravel samples increases, both total compression and creep compression decreases, but after a 50% mixing ratio, the settlement of amount increases again.

• Journal of Advanced Navigation Technology
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• v.26 no.6
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• pp.448-455
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• 2022

In this study, when establishing a UTM(UAS Traffic Management) system, a corridor must be set to separate the flight distance between unmanned aerial vehicles, and the size of the corridor was calculated in consideration of TSE(Total System Error). The flight data of the straight section and the turning section were collected using a hybrid vertical take-off and landing unmanned aerial vehicle. The flight data were derived from the TSE using the SQSM(Scalar Quantity Summation Method) method, and the impact on the straight and turning sections was analyzed by calculating in detail by NSE(Navigation System Error) and FTE(Flight Technical Error). The corridor size was calculated by referring to the TSE analysis results and PBN (Performance-based Navigation) manual.

• Journal of Advanced Navigation Technology
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• v.25 no.6
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• pp.450-455
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• 2021

In this paper, we introduce the contents of research on the establishment of an evaluation environment for autonomous cooperative driving platform for commercial vehicles based on V2X communication. For the evaluation of the autonomous cooperative driving platform based on V2X communication, various standards, standards, and guidelines for test evaluation should be developed and provided to the test subject, along with the establishment of test beds such as roads and V2X infrastructure that can apply various driving scenarios. do. In addition, based on this, various reference equipment and test equipment for actual test and evaluation should be developed. In this paper, various technologies, standards, equipment, and construction infrastructure developed to construct the evaluation environment for autonomous cooperative driving platform for commercial vehicles based on V2X communication are introduced.

• Journal of the Society of Naval Architects of Korea
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• v.61 no.1
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• pp.8-18
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• 2024

The present study concerns reduced order modeling of a marine diesel engine, which can be used for outlier detection in status monitoring and carbon intensity index calculation. Principal Component Analysis (PCA) is introduced for the reduced order modeling, focusing on the feasibility of detecting and treating nonlinear variables. By cross-correlation, it is found that there are seven non-linear data channels among 23 data channels, i.e., fuel mode, exhaust gas temperature after the turbocharger, and cylinder coolant temperatures. The dataset is handled so that the mean is located at the nominal continuous rating. Polynomial presentation of the dataset is also applied to reflect the linearity between the engine speed and other channels. The first principal mode shows strong effects of linearity of the most data channels to show the linearity of the system. The non-linear variables are effectively explained by other modes. second mode concerns the temperature of the cylinder cooling water, which shows small correlation with other variables. The third and fourth modes correlates the fuel mode and turbocharger exhaust gas temperature, which have inferior linearity to other channels. PCA is proven to be applicable to data given in binary type of fuel mode selection, as well as numerical type data.

• Journal of Advanced Navigation Technology
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• v.28 no.1
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• pp.68-76
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• 2024

With the recent rapid growth of the domestic and international unmanned aerial vehicle (UAV) market and the increasing importance of UAV operations in urban centers, such as UAMs, the safety management and regulatory framework for human life and property damage caused by UAV failures has been emphasized. In this study, we conducted a comparative analysis of risk-cost models that evaluate the risk of an operating area for safe UAM flight path planning, and identified the main limitations of each model to derive considerations for future model development. By providing a basic model for improving the safety of UAM operations, this study is expected to make an important contribution to technical improvements and policy decisions in the field of UAM flight path planning.

• Journal of Advanced Navigation Technology
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• v.28 no.1
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• pp.129-135
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• 2024

In this paper, an analytical approach for the design and analysis of an aperiodic electromagnetic bandgap (EBG)-based power distribution network (PDN) in high-speed integrated-circuit (IC) packages and printed circuit boards (PCBs) is proposed. Aperiodic EBG is an effective method to solve the noise problem of high-speed IC packages and PCBs. However, its analysis becomes challenging due to increased computation time. To overcome the problem, the proposed analytical method entails deriving impedance parameters for EBG island and the overall PDN, which includes locally placed EBG structures. To validate the proposed method, a test vehicle is fabricated, demonstrating good agreement with the measurements. Significantly, the proposed analytical method reduces computation time by 99.7 %compared to the full-wave simulation method.

• Journal of Advanced Navigation Technology
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• v.28 no.1
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• pp.15-20
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• 2024

The utilization of small unmanned aerial vehicles (UAVs) has expanded into both military and civilian domains, increasing the necessity for research to ensure operational safety and the efficient utilization of airspace. In this study, the calculation of minimum separation distances for the safe operation of small UAVs at low altitudes was conducted. The determination of minimum separation distances requires a comprehensive analysis of the total system errors associated with small UAVs, necessitating sensitivity analysis to identify key factors contributing to flight technology errors. Flight data for small UAVs were acquired by integrating the control system of an actual small UAV with a flight simulation program. Based on this data, operational scenarios for small UAVs were established, and the minimum separation distances for each scenario were calculated. This research contributes to proposing methods for utilizing calculated minimum separation distances as crucial parameters for ensuring the safe operation of small unmanned aerial vehicles in real-world scenarios.

• Journal of Advanced Navigation Technology
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• v.27 no.6
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• pp.788-797
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• 2023

In this paper, we introduced a test environment to test a vision-aided navigation system, as an alternative navigation system when global positioning system (GPS) is unavailable, for vertical take-off and landing (VTOL) unmanned aerial system. It is efficient to use a virtual environment to test and evaluate the vision-aided navigation system under development, but currently no suitable equipment has been developed in Korea. Thus, the proposed test environment is developed to evaluate the performance of the navigation system by generating input signal modeling and simulating operation environment of the system, and by monitoring output signal. This paper comprehensively describes research procedure from derivation of requirements specifications to hardware/software design according to the requirements, and production of the test environment. This test environment was used for evaluating the vision-aided navigation algorithm which we are developing, and conducting simulation based pre-flight tests.

• Journal of Advanced Navigation Technology
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• v.28 no.2
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• pp.238-245
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• 2024

In this paper, we propose a framework for improving the performance of semantic segmentation of agricultural multispectral image using feature fusion techniques. Most of the semantic segmentation models being studied in the field of smart farms are trained on RGB images and focus on increasing the depth and complexity of the model to improve performance. In this study, we go beyond the conventional approach and optimize and design a model with multispectral and attention mechanisms. The proposed method fuses features from multiple channels collected from a UAV along with a single RGB image to increase feature extraction performance and recognize complementary features to increase the learning effect. We study the model structure to focus on feature fusion and compare its performance with other models by experimenting with favorable channels and combinations for crop images. The experimental results show that the model combining RGB and NDVI performs better than combinations with other channels.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.6
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• pp.1562-1582
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• 2024

The prediction of pedestrian trajectory is conducive to reducing traffic accidents and protecting pedestrian safety, which is crucial to the task of intelligent driving. The existing methods mainly use the past pedestrian trajectory to predict the future deterministic pedestrian trajectory, ignoring pedestrian intention and trajectory diversity. This paper proposes a multi-modal trajectory prediction model that introduces pedestrian intention. Unlike previous work, our model makes multi-modal goal-conditioned trajectory pedestrian prediction based on the past pedestrian trajectory and pedestrian intention. At the same time, we propose a novel Gate Recurrent Unit (GRU) to process intention information dynamically. Compared with traditional GRU, our GRU adds an intention unit and an intention gate, in which the intention unit is used to dynamically process pedestrian intention, and the intention gate is used to control the intensity of intention information. The experimental results on two first-person traffic datasets (JAAD and PIE) show that our model is superior to the most advanced methods (Improved by 30.4% on MSE_0.5s and 9.8% on MSE_1.5s for the PIE dataset; Improved by 15.8% on MSE_0.5s and 13.5% on MSE_1.5s for the JAAD dataset). Our multi-modal trajectory prediction model combines pedestrian intention that varies at each prediction time step and can more comprehensively consider the diversity of pedestrian trajectories. Our method, validated through experiments, proves to be highly effective in pedestrian trajectory prediction tasks, contributing to improving traffic safety and the reliability of intelligent driving systems.