• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.37 no.5
• /
• pp.379-388
• /
• 2019

Recently, a technique for acquiring spatial information data using UAV (Unmanned Aerial Vehicle) has been greatly developed. It is a very crucial issue of the GIS (Geographic Information System) mapping system that passes way point in the unmanned airframe and finally measures the accurate image and stable localization to the desired destination. Though positioning using DGPS (Differential Global Navigation System) or RTK-GPS (Real Time Kinematic-GPS) guarantee highly accurate, they are more expensive than the construction of a single positioning system using a single GPS. In the case of a low-priced single GPS system, the stability of the positioning data deteriorates. Therefore, it is necessary to supplement the uncertainty of the absolute position data of the UAV and to improve the accuracy of the current position data economically in the operating state of the UAV. The aim of this study was to present an algorithm enhancing the stability of position data in a single GPS mode of UAV with multiple GPS. First, the arrangement of multiple GPS receivers through the center of gravity of the UAV were examined. Next, MD (Mahalanobis Distance) is applied to detect instantaneous errors of GPS data in advance and eliminate outliers to increase the accuracy of previously collected multiple GPS data. Processing procedure for multiple GPS reception data by applying the center of the triangular method were presented to improve the position accuracy. Second, UAV navigation systems integrated multiple GPS through configuration of the UAV specifications were implemented. Using the unmanned airframe equipped with multiple GPS receivers, GPS data is measured with the TCM (Triangular Center Method). In addition, UAV equipped with multiple GPS were operated in study area and locational accuracy of multiple GPS of UAV with VRS (Virtual Reference Station) GNSS surveying were compared. The result showed that the error factors are compensated, and the error range are reduced, resulting in the reliability of the corrected value. In conclusion, the result in this paper is expected to realize high-precision position estimation at low cost in UAV using multiple low-cost GPS receivers.

• Genes and Genomics
• /
• v.40 no.12
• /
• pp.1259-1267
• /
• 2018

Litchi (Litchi chinensis Sonn.) is an important subtropical fruit crop with high commercial value due to its high nutritional values and favorable tastes. However, irregular bearing attributed to unstable flowering is a major ongoing problem for litchi producers. Previous studies indicate that low-temperature is a key factor in litchi floral induction. In order to reveal the genetic and molecular mechanisms underlying the reproductive process in litchi, we had analyzed the transcriptome of buds before and after low-temperature induction using RNA-seq technology. A key flower bud differentiation associated gene, a homologue of FLORICAULA/LEAFY, was identified and named LcLFY (GenBank Accession No. KF008435). The cDNA sequence of LcLFY encodes a putative protein of 388 amino acids. To gain insight into the role of LcLFY, the temporal expression level of this gene was measured by real-time RT-PCR. LcLFY was highly expressed in flower buds and its expression correlated with the floral developmental stage. Heterologous expression of LcLFY in transgenic tobacco plants induced precocious flowering. Meantime, we investigated the sub-cellular localization of LcLFY. The LcLFY-Green fluorescent protein (GFP) fusion protein was found in the nucleus. The results suggest that LcLFY plays a pivotal role as a transcription factor in controlling the transition to flowering and in the development of floral organs in litchi.

• Journal of Ginseng Research
• /
• v.43 no.4
• /
• pp.645-653
• /
• 2019

Background: Cytochrome P450 enzymes catalyze a wide range of reactions in plant metabolism. Besides their physiological functions on primary and secondary metabolites, P450s are also involved in herbicide detoxification via hydroxylation or dealkylation. Ginseng as a perennial plant offers more sustainable solutions to herbicide resistance. Methods: Tissue-specific gene expression and differentially modulated transcripts were monitored by quantitative real-time polymerase chain reaction. As a tool to evaluate the function of PgCYP736A12, the 35S promoter was used to overexpress the gene in Arabidopsis. Protein localization was visualized using confocal microscopy by tagging the fluorescent protein. Tolerance to herbicides was analyzed by growing seeds and seedlings on Murashige and Skoog medium containing chlorotoluron. Results: The expression of PgCYP736A12 was three-fold more in leaves compared with other tissues from two-year-old ginseng plants. Transcript levels were similarly upregulated by treatment with abscisic acid, hydrogen peroxide, and NaCl, the highest being with salicylic acid. Jasmonic acid treatment did not alter the mRNA levels of PgCYP736A12. Transgenic lines displayed slightly reduced plant height and were able to tolerate the herbicide chlorotoluron. Reduced stem elongation might be correlated with increased expression of genes involved in bioconversion of gibberellin to inactive forms. PgCYP736A12 protein localized to the cytoplasm and nucleus. Conclusion: PgCYP736A12 does not respond to the well-known secondary metabolite elicitor jasmonic acid, which suggests that it may not function in ginsenoside biosynthesis. Heterologous overexpression of PgCYP736A12 reveals that this gene is actually involved in herbicide metabolism.

• Geomechanics and Engineering
• /
• v.18 no.1
• /
• pp.11-20
• /
• 2019

The purpose of this study was to propose a new approach for quantifying in situ rock mass damage, which would include a degree-of-damage and the degraded strength of a rock mass, along with its prediction based on real-time Acoustic Emission (AE) observations. The basic approach for quantifying in-situ rock mass damage is to derive the normalized value of measured AE energy with the maximum AE energy, called the degree-of-damage in this study. With regard to estimation of the AE energy, an AE crack source location algorithm of the Wigner-Ville Distribution combined with Biot's wave dispersion model, was applied for more reliable AE crack source localization in a rock mass. In situ AE wave attenuation was also taken into account for AE energy correction in accordance with the propagation distance of an AE wave. To infer the maximum AE energy, fractal theory was used for scale-independent AE energy estimation. In addition, the Weibull model was also applied to determine statistically the AE crack size under a jointed rock mass. Subsequently, the proposed methodology was calibrated using an in situ test carried out in the Underground Research Tunnel at the Korea Atomic Energy Research Institute. This was done under a condition of controlled incremental cyclic loading, which had been performed as part of a preceding study. It was found that the inferred degree-of-damage agreed quite well with the results from the in situ test. The methodology proposed in this study can be regarded as a reasonable approach for quantifying rock mass damage.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.11
• /
• pp.4084-4104
• /
• 2021

Visual place recognition (VPR) is a fundamental yet challenging task of mobile robot navigation and localization. The existing VPR methods are usually based on some pairwise similarity of image descriptors, so they are sensitive to visual appearance change and also computationally expensive. This paper proposes a simple yet effective four-step method that achieves adaptive convolutional neural network (CNN) landmark matching for VPR. First, based on the features extracted from existing CNN models, the regions with higher significance scores are selected as landmarks. Then, according to the coordinate positions of potential landmarks, landmark matching is improved by removing mismatched landmark pairs. Finally, considering the significance scores obtained in the first step, robust image retrieval is performed based on adaptive landmark matching, and it gives more weight to the landmark matching pairs with higher significance scores. To verify the efficiency and robustness of the proposed method, evaluations are conducted on standard benchmark datasets. The experimental results indicate that the proposed method reduces the feature representation space of place images by more than 75% with negligible loss in recognition precision. Also, it achieves a fast matching speed in similarity calculation, satisfying the real-time requirement.

• Journal of Drive and Control
• /
• v.20 no.4
• /
• pp.1-8
• /
• 2023

In recent years, robots have been utilized in various industries to reduce workload and enhance work efficiency. The following mobility offers users convenience by autonomously tracking specific locations and targets without the need for additional equipment such as forklifts or carts. In this paper, deep learning techniques were employed to recognize individuals and assign each of them a unique identifier to enable the recognition of a specific person even among multiple individuals. To achieve this, the distance and angle between the robot and the targeted individual are transmitted to respective controllers. Furthermore, this study explored the control methodology for mobility that tracks a specific person, utilizing Simultaneous Localization and Mapping (SLAM) and Proportional-Integral-Derivative (PID) control techniques. In the PID control method, a genetic algorithm is employed to extract the optimal gain value, subsequently evaluating PID performance through simulation. The SLAM method involves generating a map by synchronizing data from a 2D LiDAR and a depth camera using Real-Time Appearance-Based Mapping (RTAB-MAP). Experiments are conducted to compare and analyze the performance of the two control methods, visualizing the paths of both the human and the following mobility.

• International conference on construction engineering and project management
• /
• 2024.07a
• /
• pp.1283-1283
• /
• 2024

Recently, construction sites have faced significant challenges due to arbitrary changes and poor communication between general contractors and subcontractors. This study proposes a technological solution by integrating Unmanned Ground Vehicles (UGVs) into the existing workflow of apartment construction. By analyzing current processes, we identified a scenario where UGVs, equipped with LiDAR (Light Detection and Ranging) systems, can generate and provide real-time 3D models of construction sites. These models can be linked with extended reality (XR) technology or office PCs for intuitive comparisons between digital and actual site conditions as a digital twin of the construction site. The study suggests an improved construction process that enhances contractors' understanding and on-site efficiency and enables managers to monitor progress effectively. To address challenging terrain on construction sites, a caterpillar driven UGV was developed, equipped with stereo cameras, a LiDAR sensor for scanning and gathering environmental data, and an embedded PC for data processing. Utilizing SLAM (Simultaneous Localization and Mapping) technology, the UGV autonomously navigates and scans the site at night, minimizing disruptions. Additionally, an embedded system analyzes images from stereo cameras to assess the quality of construction, mapping the findings onto 3D models. This innovation allows site managers to efficiently verify construction quality and identify issues without manual inspections, significantly improving site management efficiency.

• International conference on construction engineering and project management
• /
• 2024.07a
• /
• pp.152-159
• /
• 2024

Cracks in structural materials present a critical challenge to infrastructure safety and long-term durability. Timely and precise crack detection is essential for proactive maintenance and the prevention of catastrophic structural failures. This study introduces an innovative approach to tackle this issue using U-Net deep learning architecture. The primary objective of the intended research is to explore the potential of U-Net in enhancing the precision and efficiency of crack detection across various concrete crack detection under various environmental conditions. Commencing with the assembling by a comprehensive dataset featuring diverse images of concrete cracks, optimizing crack visibility and facilitating feature extraction through advanced image processing techniques. A wide range of concrete crack images were collected and used advanced techniques to enhance their visibility. The U-Net model, well recognized for its proficiency in image segmentation tasks, is implemented to achieve precise segmentation and localization of concrete cracks. In terms of accuracy, our research attests to a substantial advancement in automated of 95% across all tested concrete materials, surpassing traditional manual inspection methods. The accuracy extends to detecting cracks of varying sizes, orientations, and challenging lighting conditions, underlining the systems robustness and reliability. The reliability of the proposed model is measured using performance metrics such as, precision(93%), Recall(96%), and F1-score(94%). For validation, the model was tested on a different set of data and confirmed an accuracy of 94%. The results shows that the system consistently performs well, even with different concrete types and lighting conditions. With real-time monitoring capabilities, the system ensures the prompt detection of cracks as they emerge, holding significant potential for reducing risks associated with structural damage and achieving substantial cost savings.

• Progress in Medical Physics
• /
• v.24 no.2
• /
• pp.127-132
• /
• 2013

The position of the internal organs can change continually and periodically inside the body due to the respiration. To reduce the respiration induced uncertainty of dose localization, one can use a respiratory gated radiotherapy where a radiation beam is exposed during the specific time of period. The main disadvantage of this method is that it usually requests a long treatment time, the massive effort during the treatment and the limitation of the patient selection. In this sense, the combination of the real-time position management (RPM) system and the volumetric intensity modulated radiotherapy (RapidArc) is promising since it provides a short treatment time compared with the conventional respiratory gated treatments. In this study, we evaluated the accuracy of the respiratory gated RapidArc treatment. Total sic patient cases were used for this study and each case was planned by RapidArc technique using varian ECLIPSE v8.6 planning machine. For the Quality Assurance (QA), a MatriXX detector and I'mRT software were used. The results show that more than 97% of area gives the gamma value less than one with 3% dose and 3 mm distance to agreement condition, which indicates the measured dose is well matched with the treatment plan's dose distribution for the gated RapidArc treatment cases.

• Science of Emotion and Sensibility
• /
• v.20 no.3
• /
• pp.13-22
• /
• 2017

Emotion has a direct influence such as decision-making, perception, etc. and plays an important role in human life. For the convenient and accurate recognition of high-arousal negative emotion, the purpose of this paper is to design an algorithm for analysis using the bio-signal. In this study, after two emotional induction using the 'normal' / 'fear' emotion types of videos, we measured the Galvanic Skin Response (GSR) signal which is the simple of bio-signals. Then, by decomposing Tonic component and Phasic component in the measured GSR and decomposing Skin Conductance Very Slow Response (SCVSR) and Skin Conductance Slow Response (SCSR) in the Phasic component associated with emotional stimulation, extracting the major features of the components for an accurate analysis, we used a discrete wavelet transform with excellent time-frequency localization characteristics, not the method used previously. The extracted features are maximum value of Phasic component, amplitude of Phasic component, zero crossing rate of SCVSR and zero crossing rate of SCSR for distinguishing high-arousal negative emotion. As results, the case of high-arousal negative emotion exhibited higher value than the case of low-arousal normal emotion in all 4 of the features, and the more significant difference between the two emotion was found statistically than the previous analysis method. Accordingly, the results of this study indicate that the GSR may be a useful indicator for a high-arousal negative emotion measurement and contribute to the development of the emotional real-time rating system using the GSR.