• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.11
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• pp.3991-4010
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• 2021

The Question Similarity Measurement of Chinese Crop Diseases and Insect Pests (QSM-CCD&IP) aims to judge the user's tendency to ask questions regarding input problems. The measurement is the basis of the Agricultural Knowledge Question and Answering (Q & A) system, information retrieval, and other tasks. However, the corpus and measurement methods available in this field have some deficiencies. In addition, error propagation may occur when the word boundary features and local context information are ignored when the general method embeds sentences. Hence, these factors make the task challenging. To solve the above problems and tackle the Question Similarity Measurement task in this work, a corpus on Chinese crop diseases and insect pests(CCDIP), which contains 13 categories, was established. Then, taking the CCDIP as the research object, this study proposes a Chinese agricultural text similarity matching model, namely, the AgrCQS. This model is based on mixed information extraction. Specifically, the hybrid embedding layer can enrich character information and improve the recognition ability of the model on the word boundary. The multi-scale local information can be extracted by multi-core convolutional neural network based on multi-weight (MM-CNN). The self-attention mechanism can enhance the fusion ability of the model on global information. In this research, the performance of the AgrCQS on the CCDIP is verified, and three benchmark datasets, namely, AFQMC, LCQMC, and BQ, are used. The accuracy rates are 93.92%, 74.42%, 86.35%, and 83.05%, respectively, which are higher than that of baseline systems without using any external knowledge. Additionally, the proposed method module can be extracted separately and applied to other models, thus providing reference for related research.

• Geophysics and Geophysical Exploration
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• v.25 no.1
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• pp.1-13
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• 2022

For surveying shallow gas reservoirs in the Pohang basin, we proposed a seismic exploration method applicable to the transition zone in which land and marine areas are connected. We designed the seismic acquisition geometry considering both environments. We installed land nodal receivers on the ground and employed vibroseis and airgun sources in both land and marine areas. For seismic exploration in the transition zone, specific acquisition and processing techniques are required to ensure precise matching of reflectors at the boundary between the onshore and offshore regions. To enhance the continuity of reflection events on the seismic section, we performed amplitude and phase corrections with respect to the source types and applied a static correction. Following these processing steps, we obtained a seismic section showing connected reflectors around the boundary in the transition zone. We anticipate that our proposed seismic exploration method can also be used for fault detection in the transition zone.

• Journal of KIBIM
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• v.13 no.4
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• pp.96-105
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• 2023

This study focuses on developing a building object recognition technology for efficient use in the remodeling of buildings constructed without drawings. In the era of the 4th industrial revolution, smart technologies are being developed. This research contributes to the architectural field by introducing a deep learning-based method for automatic object classification and recognition, utilizing point cloud data. We use a TD3D network with voxels, optimizing its performance through adjustments in voxel size and number of blocks. This technology enables the classification of building objects such as walls, floors, and roofs from 3D scanning data, labeling them in polygonal forms to minimize boundary ambiguities. However, challenges in object boundary classifications were observed. The model facilitates the automatic classification of non-building objects, thereby reducing manual effort in data matching processes. It also distinguishes between elements to be demolished or retained during remodeling. The study minimized data set loss space by labeling using the extremities of the x, y, and z coordinates. The research aims to enhance the efficiency of building object classification and improve the quality of architectural plans by reducing manpower and time during remodeling. The study aligns with its goal of developing an efficient classification technology. Future work can extend to creating classified objects using parametric tools with polygon-labeled datasets, offering meaningful numerical analysis for remodeling processes. Continued research in this direction is anticipated to significantly advance the efficiency of building remodeling techniques.

• Tunnel and Underground Space
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• v.33 no.4
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• pp.281-298
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• 2023

Continuous research efforts are being devoted to unmanned mobile platforms for lunar exploration. There is an ongoing demand for real-time information processing to accurately determine the positioning and mapping of areas of interest on the lunar surface. To apply deep learning processing and analysis techniques to practical rovers, research on software integration and optimization is imperative. In this study, a foundational investigation has been conducted on real-time analysis of virtual lunar base construction site images, aimed at automatically quantifying spatial information of key objects. This study involved transitioning from an existing region-based object recognition algorithm to a boundary box-based algorithm, thus enhancing object recognition accuracy and inference speed. To facilitate extensive data-based object matching training, the Batch Hard Triplet Mining technique was introduced, and research was conducted to optimize both training and inference processes. Furthermore, an improved software system for object recognition and identical object matching was integrated, accompanied by the development of visualization software for the automatic matching of identical objects within input images. Leveraging satellite simulative captured video data for training objects and moving object-captured video data for inference, training and inference for identical object matching were successfully executed. The outcomes of this research suggest the feasibility of implementing 3D spatial information based on continuous-capture video data of mobile platforms and utilizing it for positioning objects within regions of interest. As a result, these findings are expected to contribute to the integration of an automated on-site system for video-based construction monitoring and control of significant target objects within future lunar base construction sites.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.37 no.2
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• pp.445-449
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• 2017

Most studies using drone is confined utilization on the ground and regulation. The drone in the water is rarely used in hydrographic surveying because of the limit of flight time and image matching. This paper is the basic research for drone hydrographic photogrammetry. The accuracy of hydrographic photogrammetry, using buoys for water reference point, was evaluated. The accuracy is influenced by the accuracy of the water reference points like the photogrammetry. The position of water reference points set up on water, keep on changing due to various environmental factors such as wind speed and water velocity. The position continuously changed of the water reference points were measured 3 times using Total Station and VRS. Experiments were conducted at two reservoirs in Gimhae City, and the accuracy of the manual image matching using the water reference points is 40 cm and 80 cm. Allowable accuracy of the ocean boundary survey is ${\pm}2m$, the results of this study are fully available. The maximum position error of the water reference point for ensuring accuracy within ${\pm}2m$ is 1.8 m.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.3 s.309
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• pp.25-33
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• 2006

This paper proposed device-independent color matching algorithm based on the 3D RGB lookup table (LUT) between mobile camera and mobile LCD (Liquid Crystal Display) to improve the color-fidelity. Proposed algorithm is composed of thee steps, which is device characterization, gamut mapping, 3D RGB-LUT design. First, the characterization of mobile LCD is executed using the sigmoidal function, different from conventional method such as GOG (Gain Offset Gamma) and S-curve modeling, based on the observation of electro-optical transfer function of mobile LCD. Next, mobile camera characterization is conducted by fitting the digital value of GretagColor chart captured under the daylight environment (D65) and tristimulus values (CIELAB) using the polynomial regression. However, the CIELAB values estimated by polynomial regression exceed the maximum boundary of the CIELAB color space. Therefore, these values are corrected by linear compression of the lightness and chroma. Finally, gamut mapping is used to overcome the gamut difference between mobile camera and moible LCD. To implement the real-time processing, 3D RGB-LUT is designed based on the 3D RGB-LUT and its performance is evaluated and compared with conventional method.

• Journal of Broadcast Engineering
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• v.26 no.1
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• pp.26-38
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• 2021

In this paper, DLKF (Deep Learning Keypoint Filtering), the deep learning-based keypoint filtering method for the rapidization of the image registration method for remote sensing images is proposed. The complexity of the conventional feature-based image registration method arises during the feature matching step. To reduce this complexity, this paper proposes to filter only the keypoints detected in the artificial structure among the keypoints detected in the keypoint detector by ensuring that the feature matching is matched with the keypoints detected in the artificial structure of the image. For reducing the number of keypoints points as preserving essential keypoints, we preserve keypoints adjacent to the boundaries of the artificial structure, and use reduced images, and crop image patches overlapping to eliminate noise from the patch boundary as a result of the image segmentation method. the proposed method improves the speed and accuracy of registration. To verify the performance of DLKF, the speed and accuracy of the conventional keypoints extraction method were compared using the remote sensing image of KOMPSAT-3 satellite. Based on the SIFT-based registration method, which is commonly used in households, the SURF-based registration method, which improved the speed of the SIFT method, improved the speed by 2.6 times while reducing the number of keypoints by about 18%, but the accuracy decreased from 3.42 to 5.43. Became. However, when the proposed method, DLKF, was used, the number of keypoints was reduced by about 82%, improving the speed by about 20.5 times, while reducing the accuracy to 4.51.

• Journal of Ocean Engineering and Technology
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• v.32 no.2
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• pp.106-115
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• 2018

The forward and afterward parts of ships and offshore structures are designed to improve the fuel consumption performance. These are made of curved plates with a large thickness. If a fabricated curved plate has some dimensional errors, a lot of additional cost is incurred in the assembly process. Thus, an accurate dimensional assessment is very important for fabrication. In this paper, we propose an assessment method for the dimensional quality management of curved plates. This can be applied to data measured using a variety of three-dimensional instruments, with boundary measurement points automatically classified and sorted to create a measurement surface. The assessment is evaluated after matching the CAD surface and the measured surface considering constrained conditions. The fabrication assessment is evaluated as a probability of how much the tolerance is satisfied.

• Journal of Ocean Engineering and Technology
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• v.16 no.3
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• pp.19-27
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• 2002

The motion of a floating OWC chamber in waves is studied taking account of fluctuating air pressure in the air chamber. An atmospheric pressure drop occurs across the upper opening of the chamber which causes not only hydrodynamic but also pneumatic added mass and damping forces to the floating chamber. A velocity potential in the water due to the free surface oscillating pressure patch is added to the conventional radiation-diffraction potential problem. the potential problem inside the chamber is formulated by making use of the Green integral equation associated with the Rankine Green function wile the outer problem with the Kelvin Green function. The two integral equations are solved simultaneously by making use of a matching boundary condition at the lower opening of the chamber to the outer water region. The chamber motion in the frequency domain is calculated for various values of parameters related to the atmospheric pressure drop. The present methods can also be sued for the analysis of air-cushion vehicle motion as well as for the design of a floating OWC wave energy absorber.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2002.05a
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• pp.191-197
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• 2002

The motion of a floating OWC chamber in waves is studied taking account of fluctuating.air pressure in the air chamber. An atmospheric pressure drop occurs across the upper opening of the chamber which causes not only hydrodynamic but also pneumatic added mass and damping forces to the floating chamber. A velocity potential in the water due to the free surface oscillating pressure patch is added to the conventional radiation-diffraction potential problem. The potential problem inside the chamber is formulated by making use of the Green integral equation associated with the Rankine Green function while the outer problem with the Kelvin Green function. The two integral equations are solved simultaneously by making use of a matching boundary condition at the lower opening of the chamber to the outer water region. The chamber motion in the frequency domain is calculated for various values of parameters related to the atmospheric pressure drop. The present methods can also be used for the analysis of air-cushion vehicle motion as well as for the design oj a floating owe wave energy absorber.