• Title/Summary/Keyword: reconstruction Model

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Mandibular Reconstruction using Simulation Surgery after Segmental Mandibulectomy

  • Hwang, Jong-Hyun;Kim, Ji-Wan;Ahn, Kang-Min
    • Journal of International Society for Simulation Surgery
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    • v.3 no.1
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    • pp.12-15
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    • 2016
  • Functional and esthetic reconstruction after segmental mandibulectomy is one of the most challenging surgeries in microsurgical reconstruction field. Simulation surgery before free flap reconstruction has been performed for efficient surgery and successful results. Fibula free flap is the flap of the choice for reconstruction of the segmental mandibular defect. Straight nature of the fibula bone requires multiple segmentations to fit into mandible. 3D rapid prototype (RP) model gives a lot of information for mandibular reconstruction. The purpose of this study was to report mandibular reconstruction with free fibular flap using simulation surgery. A total of 30 consecutive patients were included for functional and esthetic evaluation. Among 30 patients, two flaps showed necrosis after radiotherapy. The other flaps were all survived and showed successful reconstruction in both function and esthetics.

An Integrated Environment and Economic Evaluation Model for Building Reconstruction and Remodeling Projects (재건축과 리모델링 사업의 환경성${\cdot}$경제성 통합평가모델)

  • Lee Ju-Heon;Park Chan-Sik
    • Proceedings of the Korean Institute Of Construction Engineering and Management
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    • autumn
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    • pp.327-330
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    • 2002
  • Recently, the environmental sustainability has showed up one of the important considerations in the construction industry. However, the effective evaluation method for the decision-making on either reconstruction or remodeling of a project has not been developed so far. This paper presents an integrated evaluation model considering both environment and economic factors of a building project for which the decision making on either remodeling or reconstruction is needed. In order to develop the model, the characteristics of both types of projects were investigated and analyzed through the related literature review, and then appropriate evaluation criteria and analysis methodology to be used in the model were developed.

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Time Reversa1 Reconstruction of Ultrasonic Waves in Anisotropic Media

  • Jeong, Hyun-Jo
    • Journal of the Korean Society for Nondestructive Testing
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    • v.28 no.1
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    • pp.54-58
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    • 2008
  • Time reversal (TR) of body waves in fluids and isotropic solids has been used in many applications including ultrasonic NDE. However, the study of the TR method for anisotropic materials is not well established. In this paper, the full reconstruction of the input signal is investigated for anisotropic media using an analytical formulation, called a modular Gaussian beam (MGB) model. The time reversal operation of this model in the frequency domain is done by taking the complex conjugate of the Gaussian amplitude and phase received at the TR mirror position. A narrowband reference signal having a particular frequency and number of cycles is then multiplied and the whole signal is inverse Fourier transformed. The original input signal is seen to be fully restored by the TR process of MGB model and this model can be more generalized to simulate the spatial and temporal focusing effects due to TR process in anisotropic materials.

Comparison of 3D Reconstruction Methods to Create 3D Indoor Models with Different LODs

  • Hong, Sungchul;Choi, Hyunsang
    • International conference on construction engineering and project management
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    • 2015.10a
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    • pp.674-675
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    • 2015
  • A 3D indoor model becomes an indiscernible component of BIM (Building Information Modeling) and GIS (Geographic Information System). However, a huge amount of time and human resources are inevitable for collecting spatial measurements and creating such a 3D indoor model. Also, a varied forms of 3D indoor models exist depending on their purpose of use. Thus, in this study, three different 3D indoor models are defined as 1) omnidirectional images, 2) a 3D realistic model, and 3) 3D indoor as-built model. A series of reconstruction methods is then introduced to construct each type of 3D indoor models: they are an omnidirectional image acquisition method, a hybrid surveying method, and a terrestrial LiDAR-based method. The reconstruction methods are applied to a large and complex atrium, and their 3D modeling results are compared and analyzed.

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Geometry Reconstruction Using Dictionary Learning of 3D Shape Features (3차원 형태 특징의 사전 학습을 이용한 기하 복원)

  • Hwang, Jung-Min;Yoon, Yeo-Jin;Choi, Soo-Mi
    • Journal of the Korea Computer Graphics Society
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    • v.23 no.1
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    • pp.57-65
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    • 2017
  • In this paper, we present a dictionary learning method for reducing errors in point cloud models and reconstructing their geometry. For this, 3D feature information is extracted from the models which have a similar shape characteristic as the target model. Then a dictionary is constructed and the geometry is reconstructed using the dictionary. The presented method in this paper consists of the following three steps. First, a geometric patch is constructed from a similar model. Second, a morphological 3D feature of the acquired patch is learned. Third, a geometry reconstruction is performed using the learned dictionary. Finally, the error between the original model and the reconstruction result is calculated, and the accuracy of the reconstruction result is checked.

Image Reconstruction Method for Photonic Integrated Interferometric Imaging Based on Deep Learning

  • Qianchen Xu;Weijie Chang;Feng Huang;Wang Zhang
    • Current Optics and Photonics
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    • v.8 no.4
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    • pp.391-398
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    • 2024
  • An image reconstruction algorithm is vital for the image quality of a photonic integrated interferometric imaging (PIII) system. However, image reconstruction algorithms have limitations that always lead to degraded image reconstruction. In this paper, a novel image reconstruction algorithm based on deep learning is proposed. Firstly, the principle of optical signal transmission through the PIII system is investigated. A dataset suitable for image reconstruction of the PIII system is constructed. Key aspects such as model and loss functions are compared and constructed to solve the problem of image blurring and noise influence. By comparing it with other algorithms, the proposed algorithm is verified to have good reconstruction results not only qualitatively but also quantitatively.

A deep learning framework for wind pressure super-resolution reconstruction

  • Xiao Chen;Xinhui Dong;Pengfei Lin;Fei Ding;Bubryur Kim;Jie Song;Yiqing Xiao;Gang Hu
    • Wind and Structures
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    • v.36 no.6
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    • pp.405-421
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    • 2023
  • Strong wind is the main factors of wind-damage of high-rise buildings, which often creates largely economical losses and casualties. Wind pressure plays a critical role in wind effects on buildings. To obtain the high-resolution wind pressure field, it often requires massive pressure taps. In this study, two traditional methods, including bilinear and bicubic interpolation, and two deep learning techniques including Residual Networks (ResNet) and Generative Adversarial Networks (GANs), are employed to reconstruct wind pressure filed from limited pressure taps on the surface of an ideal building from TPU database. It was found that the GANs model exhibits the best performance in reconstructing the wind pressure field. Meanwhile, it was confirmed that k-means clustering based retained pressure taps as model input can significantly improve the reconstruction ability of GANs model. Finally, the generalization ability of k-means clustering based GANs model in reconstructing wind pressure field is verified by an actual engineering structure. Importantly, the k-means clustering based GANs model can achieve satisfactory reconstruction in wind pressure field under the inputs processing by k-means clustering, even the 20% of pressure taps. Therefore, it is expected to save a huge number of pressure taps under the field reconstruction and achieve timely and accurately reconstruction of wind pressure field under k-means clustering based GANs model.

A Study on the Side Collision Accident Reconstruction Using Database of Crush Test of Model Cars (모형자동차 충돌시험의 데이터베이스를 이용한 측면 충돌사고 재구성)

  • Sohn, Jeong-Hyun;Park, Seok-Cheon;Kim, Kwang-Suk
    • Transactions of the Korean Society of Automotive Engineers
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    • v.17 no.2
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    • pp.49-56
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    • 2009
  • In this study, a side collision accident reconstruction using database based on the deformed shape information from the collision test using model cars is suggested. A deformation index and angle index related to the deformed shape is developed to set the database for the collision accident reconstruction algorithm. Two small size RC cars are developed to carry out the side collision test. Several side collision tests according to the velocity and collision angles are performed for establishing the side collision database. A high speed camera with 1000fps is used to capture the motion of the car. A side collision accident reconstruction algorithm is developed and applied to find the collision conditions before the accident occurs. Two collision cases are tested to validate the database and the algorithm. The results obtained by the reconstruction algorithm show good match with original conditions with regard to the velocity and angle.

Generation of the Structural Analysis Model Through the Reconstruction of the Topological Information of the Hull Structural Model (선체 구조 모델의 위상 정보 재구성을 통한 구조 해석 모델 생성)

  • Roh, Myung-Il;Yoo, Seong-Jin;Lee, Kyu-Yeul
    • Journal of the Society of Naval Architects of Korea
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    • v.43 no.2 s.146
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    • pp.246-257
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    • 2006
  • In the ship building industry, the generation of a structural analysis model, that is, a finite element model of a hull structure, has been manually performed by a designer and thus has required lots of time as compared with that of a mechanical part, because of many constraints, the complexity, and the huge size of the hull structure. To make this task automatic, a generation method of the structural analysis model is proposed through the reconstruction of the topological information of a hull structural model in this study. The applicability of the proposed method is demonstrated by applying it to the generation of the structural analysis model of a deadweight 300,000ton VLCC(Very Large Crude oil Carrier).

2D Design Feature Recognition using Expert System (전문가 시스템을 이용한 2차원 설계 특징형상의 인식)

  • 이한민;한순흥
    • Korean Journal of Computational Design and Engineering
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    • v.6 no.2
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    • pp.133-139
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    • 2001
  • Since a great number of 2D engineering drawings are being used in industry and at the same time 3D CAD becomes popular in recent years, we need to reconstruct 3D CAD models from 2D legacy drawings. In this thesis, a combination of a feature recognition method and an expert system is suggested for the 3D solid model reconstruction. Modeling primitives of 3D CAD systems are recognized and constructed by using the pattern matching technique of the features modeling. Additional information for the 3D model reconstruction can be generated by extracting symbols or text entities which are related to form entities. For complex and indefinite cases which cannot be solved by the process of feature recognition, an expert system with a rule base has been used for decision-making. A 3D reconstruction system which recognizes 2D DXF drawing files has been implemented where models composed with protrusions, holes, and cutouts can be handled.

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