• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.6
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• pp.155-163
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• 2019

This paper proposes a new methodology to recognize cracks on asphalt road surfaces using the image data obtained with drones. The target section was Yuseong-daero, the main highway of Daejeon. Furthermore, two object detection algorithms, such as Tiny-YOLO-V2 and Faster-RCNN, were used to recognize cracks on road surfaces, classify the crack types, and compare the experimental results. As a result, mean average precision of Faster-RCNN and Tiny-YOLO-V2 was 71% and 33%, respectively. The Faster-RCNN algorithm, 2Stage Detection, showed better performance in identifying and separating road surface cracks than the Yolo algorithm, 1Stage Detection. In the future, it will be possible to prepare a plan for building an infrastructure asset-management system using drones and AI crack detection systems. An efficient and economical road-maintenance decision-support system will be established and an operating environment will be produced.

• Proceedings of the Korean Society of Crop Science Conference
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• 2017.06a
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• pp.14-14
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• 2017

The discipline of plant breeding is experiencing a renaissance impacting crop improvement as a result of new technologies, however fundamental questions remain for predicting the phenotype and how the environment and genetics shape it. Inexpensive DNA sequencing, genotyping, new statistical methods, high throughput phenotyping and gene-editing are revolutionizing breeding methods and strategies for improving both quantitative and qualitative traits. Genomic selection (GS) models use genome-wide markers to predict performance for both phenotyped and non-phenotyped individuals. Aerial and ground imaging systems generate data on correlated traits such as canopy temperature and normalized difference vegetative index that can be combined with genotypes in multivariate models to further increase prediction accuracy and reduce the cost of advanced trials with limited replication in time and space. Design of a GS training population is crucial to the accuracy of prediction models and can be affected by many factors including population structure and composition. Prediction models can incorporate performance over multiple environments and assess GxE effects to identify a highly predictive subset of environments. We have developed a methodology for analyzing unbalanced datasets using genome-wide marker effects to group environments and identify outlier environments. Environmental covariates can be identified using a crop model and used in a GS model to predict GxE in unobserved environments and to predict performance in climate change scenarios. These new tools and knowledge challenge the plant breeder to ask the right questions and choose the tools that are appropriate for their crop and target traits. Contemporary plant breeding requires teams of people with expertise in genetics, phenotyping and statistics to improve efficiency and increase prediction accuracy in terms of genotypes, experimental design and environment sampling.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.1
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• pp.14-19
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• 2020

This paper proposes a precise drone-positioning technique using a differential global positioning system (DGPS). The proposed system consists of a reference station for error correction data production, and a mobile station (a drone), which is the target for real-time positioning. The precise coordinates of the reference station were acquired by post-processing of received satellite data together with the reference station location data provided by government infrastructure. For the system's implementation, low-cost commercial GPS receivers were used. Furthermore, a Zigbee transmitter/receiver pair was used to wirelessly send control signals and error correction data, making the whole system affordable for personal use. To validate the system, a drone-tracking experiment was conducted. The results show that the average real-time position error is less than 0.8 m.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.3
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• pp.225-232
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• 2014

In this study, a cooperative UAV and UGV platform is proposed to obtain a wide range of visual information. The UAV recognizes a pattern marker on UGV and tracks the UGV without user control. It can provide wide range of visual information for a user in the UGV. The UGV by a user is controled equipped with an aluminum board. And the UAV can take off and land on the UGV. The UAV uses two cameras; one camera is used to recognize a pattern marker and another is used to provide a wide range of visual information to the UGV's user. It is guaranteed that the proposed visual-based approach detects and tracks the target marker on the UGV, and then lands well. The experimental results show that the proposed approach can effectively construct a cooperative UAV/UGV platform for obtaining a wide range of vision information.

• Journal of Applied Biological Chemistry
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• v.58 no.3
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• pp.281-285
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• 2015

Human neutrophil elastase (HNE) represents a good therapeutic target for the treatment of inflammatory diseases as well as invasion of microorganism. The methanol extract of a aerial part of Chelidonium majus L. showed high activity against the neutrophil elastase with an $IC_{50}$ value of $100{\mu}g/mL$. Due to its potency, subsequent bioactivity-guided fractionation of methanol extract led to six alkaloids (1-6), which were identified as dihydrosanguinarine (1), (s)-stylopine (2), arnottianamide (3), (+)-chelidonine (4), spallidamine (5), and N-trans-feruloyltyramine (6). Among of them, three alkaloids (2, 5, and 6) inhibited HNE in a dose-dependent manner with $IC_{50}$ ranging between 11.6 and $51.0{\mu}M$. Lineweaver-Burk and Dixon plots, and their secondary replots showed that alkaloids (2, 5, and 6) were mixed inhibitors of HNE. The analysis of $K_I$ and $K_{IS}$ value proved that all inhibitors (2, 5, and 6) had reversible mixed type I mechanism.

• Korean Journal of Remote Sensing
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• v.35 no.5_1
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• pp.727-736
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• 2019

In this paper, we present how to create a point cloud for a target area using multiple unmanned aerial vehicle images and to remove the gaps and overlapping points between datasets. For this purpose, first, IBA (Incremental Bundle Adjustment) technique was applied to correct the position and attitude of UAV platform. We generate a point cloud by using MDR (Multi-Dimensional Relaxation) matching technique. Next, we register point clouds based on observation vectors between stereo images by doing this we remove gaps between point clouds which are generated from different stereo pairs. Finally, we applied an occupancy grids based integration algorithm to remove duplicated points to create an integrated point cloud. The experiments were performed using UAV images, and our experiments show that it is possible to remove gaps and duplicate points between point clouds generated from different stereo pairs.

• Biomolecules & Therapeutics
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• v.29 no.6
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• pp.630-636
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• 2021

Eupafolin, a constituent of the aerial parts of Phyla nodiflora, has neuroprotective property. Because reducing the synaptic release of glutamate is crucial to achieving pharmacotherapeutic effects of neuroprotectants, we investigated the effect of eupafolin on glutamate release in rat cerebrocortical synaptosomes and explored the possible mechanism. We discovered that eupafolin depressed 4-aminopyridine (4-AP)-induced glutamate release, and this phenomenon was prevented in the absence of extracellular calcium. Eupafolin inhibition of glutamate release from synaptic vesicles was confirmed through measurement of the release of the fluorescent dye FM 1-43. Eupafolin decreased 4-AP-induced [Ca²⁺]_i elevation and had no effect on synaptosomal membrane potential. The inhibition of P/Q-type Ca²⁺ channels reduced the decrease in glutamate release that was caused by eupafolin, and docking data revealed that eupafolin interacted with P/Q-type Ca²⁺ channels. Additionally, the inhibition of calcium/calmodulin-dependent protein kinase II (CaMKII) prevented the effect of eupafolin on evoked glutamate release. Eupafolin also reduced the 4-AP-induced activation of CaMK II and the subsequent phosphorylation of synapsin I, which is the main presynaptic target of CaMKII. Therefore, eupafolin suppresses P/Q-type Ca²⁺ channels and thereby inhibits CaMKII/synapsin I pathways and the release of glutamate from rat cerebrocortical synaptosomes.

• Journal of Urban Science
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• v.7 no.2
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• pp.53-60
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• 2018

Digital Twin is a technology that creates a photocopy of real-world objects on a computer and analyzes the past and present operational status by fusing the structure, context, and operation of various physical systems with property information, and predicts the future society's countermeasures. In particular, 3D rendering technology (UAS, LiDAR, GNSS, etc.) is a core technology in digital twin. so, the research and application are actively performed in the industry in recent years. However, UAS (Unmanned Aerial System) and LiDAR (Light Detection And Ranging) have to be solved by compensating blind spot which is not reconstructed according to the object shape. In addition, the terrestrial LiDAR can acquire the point cloud of the object more precisely and quickly at a short distance, but a blind spot is generated at the upper part of the object, thereby imposing restrictions on the forward digital twin modeling. The UAS is capable of modeling a specific range of objects with high accuracy by using high resolution images at low altitudes, and has the advantage of generating a high density point group based on SfM (Structure-from-Motion) image analysis technology. However, It is relatively far from the target LiDAR than the terrestrial LiDAR, and it takes time to analyze the image. In particular, it is necessary to reduce the accuracy of the side part and compensate the blind spot. By re-optimizing it after fusion with UAS and Terrestrial LiDAR, the residual error of each modeling method was compensated and the mutual correction result was obtained. The accuracy of fusion-based 3D model is less than 1cm and it is expected to be useful for digital twin construction.

• Journal of Practical Engineering Education
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• v.9 no.1
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• pp.15-21
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• 2017

In order to satisfy the graduation requirements, the graduation work should be presented as an engineering dissertation system of the produced work and an outline of the procedure made by the major unit in accordance with the graduation thesis submission rules, and suggests necessary matters for improvement. The design content relates to a small unmanned aerial vehicle configuration for detecting personnel or objects in a disaster area. It is equipped with an infrared sensor and a GPS in the drone, the drone is control by using Blutooth communications. The drones detect the target and use the GPS to determine the location. As a result of the experiment, it was possible to detect the structure object within the range of 3~4 m, confirm the transmission of the position value in real time, and increase the communication distance by using RF communication.

• Journal of the Society of Disaster Information
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• v.15 no.1
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• pp.49-66
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• 2019

Purpose: This study aims to apply the counter terrorism policy in pertain to malicious drone abuse and the croweded public places in South Korea. And, to improve counter terrorism protection measure, this study suggests an adoptation of Anti UAV technology into counter terrorism related regulation. Method: Compared to nations' operations of counter terrorism prevention and protection activities with the South Korean gov, problems and limitations are suggested. Results: Anti UAV technology could not be applied for Multi-user facilities by any law due to the limitation, so that it is required to amend counte terrporism related policies and law. Conclusion: This study intends to identify various protection methods against UAV threats. To reduce the risk of UAV, the law of public safety and counter terrorism should be promoted and reinforced for the first.