Статті в журналах: "3D data analysi"

1

Browning, Paul. "MACSPIN: 3D DATA ANALYSIS SOFTWARE." Terra Nova 4, no. 6 (November 1992): 701–4. http://dx.doi.org/10.1111/j.1365-3121.1992.tb00620.x.

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2

Wu, Youping, and Zhihui Zhou. "Intelligent City 3D Modeling Model Based on Multisource Data Point Cloud Algorithm." Journal of Function Spaces 2022 (July 21, 2022): 1–10. http://dx.doi.org/10.1155/2022/6135829.

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With the rapid development of smart cities, intelligent navigation, and autonomous driving, how to quickly obtain 3D spatial information of urban buildings and build a high-precision 3D fine model has become a key problem to be solved. As the two-dimensional mapping results have constrained various needs in people’s social life, coupled with the concept of digital city and advocacy, making three-dimensional, virtualization and actualization become the common pursuit of people’s goals. However, the original point cloud obtained is always incomplete due to reasons such as occlusion during acquisition and data density decreasing with distance, resulting in extracted boundaries that are often incomplete as well. In this paper, based on the study of current mainstream 3D model data organization methods, geographic grids and map service specifications, and other related technologies, an intelligent urban 3D modeling model based on multisource data point cloud algorithm is designed for the two problems of unified organization and expression of urban multisource 3D model data. A point cloud preprocessing process is also designed: point cloud noise reduction and downsampling to ensure the original point cloud geometry structure remain unchanged, while improving the point cloud quality and reducing the number of point clouds. By outputting to a common 3D format, the 3D model constructed in this paper can be applied to many fields such as urban planning and design, architectural landscape design, urban management, emergency disaster relief, environmental protection, and virtual tourism.

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3

Wang, Cuixia. "Optimization of Three-Dimensional Model of Landscape Space Based on Big Data Analysis." Journal of Function Spaces 2022 (August 17, 2022): 1–11. http://dx.doi.org/10.1155/2022/7002983.

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Based on virtual reality technology, landscape 3D modeling provides users with the possibility to construct a simulated garden landscape environment design effect online, so it has high requirements for accuracy. With the continuous improvement of precision requirements, the number of people involved in the construction of 3D models is also increasing, which puts forward higher requirements for modeling. Based on this, this paper studies the optimization strategy of landscape space 3D model based on big data analysis. Based on the analysis of the establishment of the 3D model and the related algorithm research, this paper analyzes the optimal design of the 3D model under the background of big data. In the 3D modeling of the edge folded area, it is based on the traditional quadratic error measurement grid simplification algorithm, combined with the vertex error matrix to simplify, so as to shorten the modeling time. Based on an efficient search algorithm, an adaptive nonsearch fractal image compression and decoding method is proposed in the image compression and decoding stage of 3D modeling. The search is performed by specifying the defined area block. Finally, an experiment is designed to analyze the performance of the optimization algorithm. The results show that the improved edge folding region algorithm can reduce errors on the basis of ensuring image quality, and the adaptive search algorithm can shorten the search time and improve the compression rate. This method provides a technical reference for the visualization experience and simulation system of garden landscape design and improves the presentation quality of virtual garden landscape design scenes.

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4

Deighton, M., and M. Petrou. "Data mining for large scale 3D seismic data analysis." Machine Vision and Applications 20, no. 1 (November 15, 2007): 11–22. http://dx.doi.org/10.1007/s00138-007-0101-3.

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5

Li, W., S. Zlatanova, and B. Gorte. "VOXEL DATA MANAGEMENT AND ANALYSIS IN POSTGRESQL/POSTGIS UNDER DIFFERENT DATA LAYOUTS." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences VI-3/W1-2020 (November 17, 2020): 35–42. http://dx.doi.org/10.5194/isprs-annals-vi-3-w1-2020-35-2020.

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Abstract. Three-dimensional (3D) raster data (also named voxel) is important sources for 3D geo-information applications, which have long been used for modelling continuous phenomena such as geological and medical objects. Our world can be represented in voxels by gridding the 3D space and specifying what each grid represents by attaching every voxel to a real-world object. Nature-triggered disasters can also be modelled in volumetric representation. Unlike point cloud, it is still a lack of wide research on how to efficiently store and manage such semantic 3D raster data. In this work, we would like to investigate four different data layouts for voxel management in open-source (spatial) DBMS - PostgreSQL/PostGIS, which is suitable for efficiently retrieving and quick querying. Besides, a benchmark has been developed to compare various voxel data management solutions concerning functionality and performance. The main test dataset is the groups of buildings of UNSW Kensington Campus, with 10cm resolution. The obtained storage and query results suggest that the presented approach can be successfully used to handle voxel management, semantic and range queries on large voxel dataset.

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6

Gautier, J., S. Christophe, and M. Brédif. "VISUALIZING 3D CLIMATE DATA IN URBAN 3D MODELS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B4-2020 (August 25, 2020): 781–89. http://dx.doi.org/10.5194/isprs-archives-xliii-b4-2020-781-2020.

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Abstract. In order to understand and explain urban climate, the visual analysis of urban climate data and their relationships with the urban morphology is at stake. This involves partly to co-visualize 3D field climate data, obtained from simulation, with urban 3D models. We propose two ways to visualize and navigate into simulated climate data in urban 3D models, using series of horizontal 2D planes and 3D point clouds. We then explore different parameters regarding transparency, 3D semiologic rules, filtering and animation functions in order to improve the visual analysis of climate data 3D distribution. To achieve this, we apply our propositions to the co-visualization of air temperature data with a 3D urban city model.

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7

Barbu, Viorel, and Michael Röckner. "Global solutions to random 3D vorticity equations for small initial data." Journal of Differential Equations 263, no. 9 (November 2017): 5395–411. http://dx.doi.org/10.1016/j.jde.2017.06.020.

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8

Papatheodorou, Theodore, John Giannatsis, and Vassilis Dedoussis. "Evaluating 3D Printers Using Data Envelopment Analysis." Applied Sciences 11, no. 9 (May 5, 2021): 4209. http://dx.doi.org/10.3390/app11094209.

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Data Envelopment Analysis (DEA) is an established powerful mathematical programming technique, which has been employed quite extensively for assessing the efficiency/performance of various physical or virtual and simple or complex production systems, as well as of consumer and industrial products and technologies. The purpose of the present study is to investigate whether DEA may be employed for evaluating the technical efficiency/performance of 3D printers, an advanced manufacturing technology of increasing importance for the manufacturing sector. For this purpose, a representative sample of 3D printers based on Fused Deposition Modeling technology is examined. The technical factors/parameters of 3D printers, which are incorporated in the DEA, are investigated and discussed in detail. DEA evaluation results compare favorably with relevant benchmarks from experts, indicating that the suggested DEA technique in conjunction with technical and expert evaluation could be employed for evaluating the performance of a highly technological system, such as the 3D printer.

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9

Mery, Francisco, Carolina Méndez-Orellana, Javier Torres, Francisco Aranda, Iván Caro, José Pesenti, Ricardo Rojas, Pablo Villanueva, and Isabelle Germano. "3D simulation of aneurysm clipping: Data analysis." Data in Brief 37 (August 2021): 107258. http://dx.doi.org/10.1016/j.dib.2021.107258.

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10

Plyusnin, Ilya, Alistair R. Evans, Aleksis Karme, Aristides Gionis, and Jukka Jernvall. "Automated 3D Phenotype Analysis Using Data Mining." PLoS ONE 3, no. 3 (March 5, 2008): e1742. http://dx.doi.org/10.1371/journal.pone.0001742.

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11

Simon, József, and Attila Felinger. "Correlation analysis on 3D data – Introducing the alteration analysis." Chemometrics and Intelligent Laboratory Systems 158 (November 2016): 54–60. http://dx.doi.org/10.1016/j.chemolab.2016.08.016.

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12

Ramm, A. G. "Stability of the inversion of 3D fixed-frequency scattering data." Journal of Mathematical Analysis and Applications 169, no. 2 (September 1992): 329–49. http://dx.doi.org/10.1016/0022-247x(92)90082-o.

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13

Shang, Jian, and Ru-liang Yang. "Data Processing and Typhoon 3D Data Analysis of TRMM Precipitation Radar." Journal of Electronics & Information Technology 30, no. 11 (April 15, 2011): 2724–27. http://dx.doi.org/10.3724/sp.j.1146.2007.00670.

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14

Li, Ou. "TDA 3D Data Model and Feature Simplification Analysis." Journal of Physics: Conference Series 1883, no. 1 (April 1, 2021): 012023. http://dx.doi.org/10.1088/1742-6596/1883/1/012023.

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15

Kovesi, Peter, Ben Richardson, Eun-Jung Holden, and Jeffrey Shragge. "Phase-Based Image Analysis of 3D Seismic Data." ASEG Extended Abstracts 2012, no. 1 (December 2012): 1–4. http://dx.doi.org/10.1071/aseg2012ab183.

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16

Fujishiro, I., Y. Takeshima, T. Azuma, and S. Takahashi. "Volume data mining using 3D field topology analysis." IEEE Computer Graphics and Applications 20, no. 5 (2000): 46–51. http://dx.doi.org/10.1109/38.865879.

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17

Salleh, S., U. Ujang, S. Azri, and T. L. Choon. "SPATIAL ADJACENCY ANALYSIS OF CITYGML BUILDINGS VIA 3D TOPOLOGICAL DATA STRUCTURE." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-4/W16 (October 1, 2019): 573–79. http://dx.doi.org/10.5194/isprs-archives-xlii-4-w16-573-2019.

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Abstract. Adjacencies between objects provides the most basic connectivity information of objects. This connectivity information provides support for more complex 3D spatial analysis such as 3D navigation, nearest neighbour and others. In 3D models, the connectivity information is maintained by building a comprehensive 3D topology. As the international standard for 3D city models, CityGML employs a simple XML links mechanism that references related entities to each other as a means of maintaining topological information. This method fulfils the purpose of relating connected entities but, it does not describe how the entities are related or in other words its adjacencies. In this study, a 3D topological data structure was utilised to preserve topological primitives and maintain connectivity information for CityGML datasets of buildings in LoD2. The adjacencies tested in this study were based on the topological links maintained by the Compact Abstract Cell Complexes 3D topological data structure. Four types of adjacencies were tested which are Point-to-Line, Line-to-Surface, Surface-to-Surface and Volume-to-Volume adjacency. As a result, all adjacencies were able to be executed for both datasets which consisted of two connected buildings and disjointed buildings. It was found that the ability of the 3D topological data structure to preserve topological primitives and build topological links supported the maintenance of connectivity information between buildings. The maintenance of connectivity information was also not limited to objects of the same dimension and could extend to connectivity between building elements in different dimensions.

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18

Wang, Jiangning, Jing Ren, Tianyu Xi, Siqin Ge, and Liqiang Ji. "Specifications and Standards for Insect 3D Data." Biodiversity Information Science and Standards 2 (May 21, 2018): e26561. http://dx.doi.org/10.3897/biss.2.26561.

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With the continuous development of imaging technology, the amount of insect 3D data is increasing, but research on data management is still virtually non-existent. This paper will discuss the specifications and standards relevant to the process of insect 3D data acquisition, processing and analysis. The collection of 3D data of insects includes specimen collection, sample preparation, image scanning specifications and 3D model specification. The specimen collection information uses existing biodiversity information standards such as Darwin Core. However, the 3D scanning process contains unique specifications for specimen preparation, depending on the scanning equipment, to achieve the best imaging results. Data processing of 3D images includes 3D reconstruction, tagging morphological structures (such as muscle and skeleton), and 3D model building. There are different algorithms in the 3D reconstruction process, but the processing results generally follow DICOM (Digital Imaging and Communications in Medicine) standards. There is no available standard for marking morphological structures, because this process is currently executed by individual researchers who create operational specifications according to their own needs. 3D models have specific file specifications, such as object files (https://en.wikipedia.org/wiki/Wavefront_.obj_file) and 3D max format (https://en.wikipedia.org/wiki/.3ds), which are widely used at present. There are only some simple tools for analysis of three-dimensional data and there are no specific standards or specifications in Audubon Core (https://terms.tdwg.org/wiki/Audubon_Core), the TDWG standard for biodiversity-related multi-media. There are very few 3D databases of animals at this time. Most of insect 3D data are created by individual entomologists and are not even stored in databases. Specifications for the management of insect 3D data need to be established step-by-step. Based on our attempt to construct a database of 3D insect data, we preliminarily discuss the necessary specifications.

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19

Bussetta, Philippe, Romain Boman, and Jean-Philippe Ponthot. "Efficient 3D data transfer operators based on numerical integration." International Journal for Numerical Methods in Engineering 102, no. 3-4 (November 25, 2014): 892–929. http://dx.doi.org/10.1002/nme.4821.

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20

Bornik, Alexander, and Wolfgang Neubauer. "3D Visualization Techniques for Analysis and Archaeological Interpretation of GPR Data." Remote Sensing 14, no. 7 (April 1, 2022): 1709. http://dx.doi.org/10.3390/rs14071709.

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The non-invasive detection and digital documentation of buried archaeological heritage by means of geophysical prospection is increasingly gaining importance in modern field archaeology and archaeological heritage management. It frequently provides the detailed information required for heritage protection or targeted further archaeological research. High-resolution magnetometry and ground-penetrating radar (GPR) became invaluable tools for the efficient and comprehensive non-invasive exploration of complete archaeological sites and archaeological landscapes. The analysis and detailed archaeological interpretation of the resulting large 2D and 3D datasets, and related data from aerial archaeology or airborne remote sensing, etc., is a time-consuming and complex process, which requires the integration of all data at hand, respective three-dimensional imagination, and a broad understanding of the archaeological problem; therefore, informative 3D visualizations supporting the exploration of complex 3D datasets and supporting the interpretative process are in great demand. This paper presents a novel integrated 3D GPR interpretation approach, centered around the flexible 3D visualization of heterogeneous data, which supports conjoint visualization of scenes composed of GPR volumes, 2D prospection imagery, and 3D interpretative models. We found that the flexible visual combination of the original 3D GPR datasets and images derived from the data applying post-processing techniques inspired by medical image analysis and seismic data processing contribute to the perceptibility of archaeologically relevant features and their respective context within a stratified volume. Moreover, such visualizations support the interpreting archaeologists in their development of a deeper understanding of the complex datasets as a starting point for and throughout the implemented interactive interpretative process.

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21

Darrah, Marjorie, Matthew Richardson, Bradley DeRoos, and Mitchell Wathen. "Optimal LiDAR Data Resolution Analysis for Object Classification." Sensors 22, no. 14 (July 9, 2022): 5152. http://dx.doi.org/10.3390/s22145152.

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When classifying objects in 3D LiDAR data, it is important to use efficient collection methods and processing algorithms. This paper considers the resolution needed to classify 3D objects accurately and discusses how this resolution is accomplished for the RedTail RTL-450 LiDAR System. We employ VoxNet, a convolutional neural network, to classify the 3D data and test the accuracy using different data resolution levels. The results show that for our data set, if the neural network is trained using higher resolution data, then the accuracy of the classification is above 97%, even for the very sparse testing set (10% of original test data set point density). When the training is done on lower resolution data sets, the classification accuracy remains good but drops off at around 3% of the original test data set point density. These results have implications for determining flight altitude and speed for an unmanned aerial vehicle (UAV) to achieve high accuracy classification. The findings point to the value of high-resolution point clouds for both the training of the convolutional neural network and in data collected from a LiDAR sensor.

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22

Wang, Qing Guo. "A 3D Surface Data Model for Fast Visualization of 3DCM." Advanced Materials Research 594-597 (November 2012): 2351–55. http://dx.doi.org/10.4028/www.scientific.net/amr.594-597.2351.

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3D data model is an indispensable component to any 3D GIS, and forms the basis of 3D spatial analysis and representation. At present, plenty of representative 3D data models are proposed. However, existing models neglect the display result and the consumption of storage space. Based on the analysis of existing 3D GIS data model, a 3D surface model is proposed for fast visualization in this paper, which is composed of node, segment and triangle. The data structure and formal representation of the proposed 3D surface model is developed to organize and store data of 3D model. Finally, an experiment is made to compare this 3D surface model with other 3D data model, and the result demonstrates that the 3D surface model proposed in this paper is superior to the existing data model in terms of data volume, moreover, it can acquire fast visualization speed.

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23

Andronov, Leonid, Jonathan Michalon, Khalid Ouararhni, Igor Orlov, Ali Hamiche, Jean-Luc Vonesch, and Bruno P. Klaholz. "3DClusterViSu: 3D clustering analysis of super-resolution microscopy data by 3D Voronoi tessellations." Bioinformatics 34, no. 17 (April 4, 2018): 3004–12. http://dx.doi.org/10.1093/bioinformatics/bty200.

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24

Ridzuan, N., U. Ujang, S. Azri, I. Mohamad Yusoff, and T. L. Choon. "VOXELIZATION TECHNIQUES: DATA SEGMENTATION AND DATA MODELLING FOR 3D BUILDING MODELS." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVIII-4/W3-2022 (December 2, 2022): 149–55. http://dx.doi.org/10.5194/isprs-archives-xlviii-4-w3-2022-149-2022.

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Abstract. Voxelization of data is discretizing the 3D space, in which the simplest form is a single voxel. There is a large number of publications that are related to voxelization. However, this paper focuses on the voxelization technique implemented in 3D building modelling. This paper aims to get the development idea of the voxelization technique throughout these past years to determine the suitable technique and method for including a 3D voxelized building model in Computational Fluid Dynamics (CFD). From the search and analysis, it is found that this technique is not only related to data modelling of the 3D voxelized model; the voxelization technique can also be utilized in the data segmentation process. First, for the data segmentation, the voxelization technique is implemented to manage the large amount of point cloud data that were obtained from the 3D scanner and sensors, which is done by reducing the number of data to avoid data redundancy and unused data using each of the voxels that exist in that environment. Second, for data modelling, popular input data to generate the 3D voxelized model is also in the form of a point cloud. However, there are still other forms, such as line and surface. Nevertheless, this paper reviews the voxelized technique in building modelling despite some data segmentation. The review shows various input data, applications, and techniques associated with the voxelization process based on building model generation. However, there is still room for improvement that allows the 3D model to be modelled in the voxelized form in the CFD domain.

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25

Holland, Stephen, Chevonne McInnis, Rafael Radkowski, and Adarsh Krishnamurthy. "NDE Data Analysis and Modeling in 3D CAD Context." Materials Evaluation 78, no. 1 (January 1, 2020): 95–103. http://dx.doi.org/10.32548/2020.me-04095.

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26

Knyaz, V., and A. Gaboutchian. "Automated Morphometric Analysis of 3D Data in Paleoanthropological Research." Nanobiotechnology Reports 16, no. 5 (September 2021): 668–75. http://dx.doi.org/10.1134/s2635167621050098.

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27

Klemm, Paul, Kai Lawonn, Sylvia Glaber, Uli Niemann, Katrin Hegenscheid, Henry Volzke, and Bernhard Preim. "3D Regression Heat Map Analysis of Population Study Data." IEEE Transactions on Visualization and Computer Graphics 22, no. 1 (January 31, 2016): 81–90. http://dx.doi.org/10.1109/tvcg.2015.2468291.

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28

INOUE, Ryo, Naotaka SAKAI, and Satoshi SHIMAWAKI. "3D body image generation using ASCII motion analysis data." Proceedings of the JSME Conference on Frontiers in Bioengineering 2003.14 (2003): 143–44. http://dx.doi.org/10.1299/jsmebiofro.2003.14.143.

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29

Chopra, Satinder, and Vladimir Alexeev. "Applications of texture attribute analysis to 3D seismic data." Leading Edge 25, no. 8 (August 2006): 934–40. http://dx.doi.org/10.1190/1.2335155.

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30

Jung, Jaehoon, Michael J. Olsen, David S. Hurwitz, Alireza G. Kashani, and Kamilah Buker. "3D virtual intersection sight distance analysis using lidar data." Transportation Research Part C: Emerging Technologies 86 (January 2018): 563–79. http://dx.doi.org/10.1016/j.trc.2017.12.004.

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31

Sheng, Ya-Nan, Zhi-Chuan Guan, and Kai Wei. "Analysis of 3D formation pressure based on logging data." Journal of Petroleum Exploration and Production Technology 7, no. 2 (July 2, 2016): 471–77. http://dx.doi.org/10.1007/s13202-016-0266-2.

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Fang, Daoyuan, and Bin Han. "GLOBAL SOLUTION FOR THE GENERALIZED ANISOTROPIC NAVIER–STOKES EQUATIONS WITH LARGE DATA." Mathematical Modelling and Analysis 20, no. 2 (March 30, 2015): 205–31. http://dx.doi.org/10.3846/13926292.2015.1020894.

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We are concerned with 3D incompressible generalized anisotropic Navier– Stokes equations with hyperdissipative term in horizontal variables. We prove that there exists a unique global solution for it with large initial data in anisotropic Besov space.

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Mezghani, Neila, Rayan Soltana, Youssef Ouakrim, Alix Cagnin, Alexandre Fuentes, Nicola Hagemeister, and Pascal-André Vendittoli. "Healthy Knee Kinematic Phenotypes Identification Based on a Clustering Data Analysis." Applied Sciences 11, no. 24 (December 17, 2021): 12054. http://dx.doi.org/10.3390/app112412054.

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The purpose of this study is to identify healthy phenotypes in knee kinematics based on clustering data analysis. Our analysis uses the 3D knee kinematics curves, namely, flexion/extension, abduction/adduction, and tibial internal/external rotation, measured via a KneeKG™ system during a gait task. We investigated two data representation approaches that are based on the joint analysis of the three dimensions. The first is a global approach that is considered a concatenation of the kinematic data without any dimensionality reduction. The second is a local approach that is considered a set of 69 biomechanical parameters of interest extracted from the 3D kinematic curves. The data representations are followed by a clustering process, based on the BIRCH (balanced iterative reducing and clustering using hierarchies) discriminant model, to separate 3D knee kinematics into homogeneous groups or clusters. Phenotypes were obtained by averaging those groups. We validated the clusters using inter-cluster correlation and statistical hypothesis tests. The simulation results showed that the global approach is more efficient, and it allows the identification of three descriptive 3D kinematic phenotypes within a healthy knee population.

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Khayyal, Heba K., Zaki M. Zeidan, and Ashraf A. A. Beshr. "Creation and Spatial Analysis of 3D City Modeling based on GIS Data." Civil Engineering Journal 8, no. 1 (January 1, 2022): 105–23. http://dx.doi.org/10.28991/cej-2022-08-01-08.

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The 3D city model is one of the crucial topics that are still under analysis by many engineers and programmers because of the great advancements in data acquisition technologies and 3D computer graphics programming. It is one of the best visualization methods for representing reality. This paper presents different techniques for the creation and spatial analysis of 3D city modeling based on Geographical Information System (GIS) technology using free data sources. To achieve that goal, the Mansoura University campus, located in Mansoura city, Egypt, was chosen as a case study. The minimum data requirements to generate a 3D city model are the terrain, 2D spatial features such as buildings, landscape area and street networks. Moreover, building height is an important attribute in the 3D extrusion process. The main challenge during the creation process is the dearth of accurate free datasets, and the time-consuming editing. Therefore, different data sources are used in this study to evaluate their accuracy and find suitable applications which can use the generated 3D model. Meanwhile, an accurate data source obtained using the traditional survey methods is used for the validation purpose. First, the terrain was obtained from a digital elevation model (DEM) and compared with grid leveling measurements. Second, 2D data were obtained from: the manual digitization from (30 cm) high-resolution imagery, and deep learning structure algorithms to detect the 2D features automatically using an object instance segmentation model and compared the results with the total station survey observations. Different techniques are used to investigate and evaluate the accuracy of these data sources. The procedural modeling technique is applied to generate the 3D city model. TensorFlow & Keras frameworks (Python APIs) were used in this paper; moreover, global mapper, ArcGIS Pro, QGIS and CityEngine software were used. The precision metrics from the trained deep learning model were 0.78 for buildings, 0.62 for streets and 0.89 for landscape areas. Despite, the manual digitizing results are better than the results from deep learning, but the extracted features accuracy is accepted and can be used in the creation process in the cases not require a highly accurate 3D model. The flood impact scenario is simulated as an application of spatial analysis on the generated 3D city model. Doi: 10.28991/CEJ-2022-08-01-08 Full Text: PDF

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35

Rubel, O., G. H. Weber, Min-Yu Huang, E. W. Bethel, M. D. Biggin, C. C. Fowlkes, C. L. Luengo Hendriks, et al. "Integrating Data Clustering and Visualization for the Analysis of 3D Gene Expression Data." IEEE/ACM Transactions on Computational Biology and Bioinformatics 7, no. 1 (January 2010): 64–79. http://dx.doi.org/10.1109/tcbb.2008.49.

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36

Hou, Thomas Y., Zhen Lei, and Congming Li. "Global Regularity of the 3D Axi-Symmetric Navier–Stokes Equations with Anisotropic Data." Communications in Partial Differential Equations 33, no. 9 (August 13, 2008): 1622–37. http://dx.doi.org/10.1080/03605300802108057.

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37

Brabant, Loes, Jelle Vlassenbroeck, Yoni De Witte, Veerle Cnudde, Matthieu N. Boone, Jan Dewanckele, and Luc Van Hoorebeke. "Three-Dimensional Analysis of High-Resolution X-Ray Computed Tomography Data with Morpho+." Microscopy and Microanalysis 17, no. 2 (January 31, 2011): 252–63. http://dx.doi.org/10.1017/s1431927610094389.

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AbstractThree-dimensional (3D) analysis is an essential tool to obtain quantitative results from 3D datasets. Considerable progress has been made in 3D imaging techniques, resulting in a growing need for more flexible, complete analysis packages containing advanced algorithms. At the Centre for X-ray Tomography of the Ghent University (UGCT), research is being done on the improvement of both hardware and software for high-resolution X-ray computed tomography (CT). UGCT collaborates with research groups from different disciplines, each having specific needs. To meet these requirements the analysis software package, Morpho+, was developed in-house. Morpho+ contains an extensive set of high-performance 3D operations to obtain object segmentation, separation, and parameterization (orientation, maximum opening, equivalent diameter, sphericity, connectivity, etc.), or to extract a 3D geometrical representation (surface mesh or skeleton) for further modeling. These algorithms have a relatively short processing time when analyzing large datasets. Additionally, Morpho+ is equipped with an interactive and intuitive user interface in which the results are visualized. The package allows scientists from various fields to obtain the necessary quantitative results when applying high-resolution X-ray CT as a research tool to the nondestructive investigation of the microstructure of materials.

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38

Wang, Yongxin, Fan Geng, and Shu Wang. "On the 3D Incompressible Boussinesq Equations in a Class of Variant Spherical Coordinates." Journal of Function Spaces 2022 (May 28, 2022): 1–12. http://dx.doi.org/10.1155/2022/9121813.

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This paper investigates the global stabilizing effects of the geometry of the domain at which the flow locates and of the geometric structure of the solution to the incompressible flows by studying the three-dimensional (3D) incompressible, viscosity, and diffusivity Boussinesq system in spherical coordinates. We establish the global existence and uniqueness of the smooth solution to the Cauchy problem for a full 3D incompressible Boussinesq system in a class of variant spherical coordinates for a class of smooth large initial data. We also construct one class of nonempty bounded domains in the three-dimensional space ℝ 3 , in which the initial boundary value problem for the full 3D Boussinesq system in a class of variant spherical coordinates with a class of large smooth initial data with swirl has a unique global strong or smooth solution with exponential decay rate in time.

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39

Prieto, Iñaki, Jose Luis Izkara, and Elena Usobiaga. "The Application of LiDAR Data for the Solar Potential Analysis Based on Urban 3D Model." Remote Sensing 11, no. 20 (October 10, 2019): 2348. http://dx.doi.org/10.3390/rs11202348.

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Solar maps are becoming a popular resource and are available via the web to help plan investments for the benefits of renewable energy. These maps are especially useful when the results have high accuracy. LiDAR technology currently offers high-resolution data sources that are very suitable for obtaining an urban 3D geometry with high precision. Three-dimensional visualization also offers a more accurate and intuitive perspective of reality than 2D maps. This paper presents a new method for the calculation and visualization of the solar potential of building roofs on an urban 3D model, based on LiDAR data. The paper describes the proposed methodology to (1) calculate the solar potential, (2) generate an urban 3D model, (3) semantize the urban 3D model with different existing and calculated data, and (4) visualize the urban 3D model in a 3D web environment. The urban 3D model is based on the CityGML standard, which offers the ability to consistently combine geometry and semantics and enable the integration of different levels (building and city) in a continuous model. The paper presents the workflow and results of application to the city of Vitoria-Gasteiz in Spain. This paper also shows the potential use of LiDAR data in different domains that can be connected using different technologies and different scales.

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40

Cheng, Xiao Min, Zi Qing Ye, and Jian Jian Zhang. "Analysis and Reconstruct of Complex Data Based on 3D Laser Scanner." Advanced Materials Research 479-481 (February 2012): 2231–34. http://dx.doi.org/10.4028/www.scientific.net/amr.479-481.2231.

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Solve the problem of simplifying, aligning, and restoring while rebuilding a large number of point group data. First, scanning art work by using 3DFAMILY laser scanner and obtain the 3D data of its surface, then removing the desultory points on the boundary, using curvature simplification and point position alignment to revise data. Finally, fixing the loophole and modify the convex block partially and finishing up 3D reconstruction. We transform the reconstruction result into STL format file, and build the prototype of art work in Rapid Prototyping System.

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41

Madan, Christopher R. "Creating 3D visualizations of MRI data: A brief guide." F1000Research 4 (August 4, 2015): 466. http://dx.doi.org/10.12688/f1000research.6838.1.

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While magnetic resonance imaging (MRI) data is itself 3D, it is often difficult to adequately present the results papers and slides in 3D. As a result, findings of MRI studies are often presented in 2D instead. A solution is to create figures that include perspective and can convey 3D information; such figures can sometimes be produced by standard functional magnetic resonance imaging (fMRI) analysis packages and related specialty programs. However, many options cannot provide functionality such as visualizing activation clusters that are both cortical and subcortical (i.e., a 3D glass brain), the production of several statistical maps with an identical perspective in the 3D rendering, or animated renderings. Here I detail an approach for creating 3D visualizations of MRI data that satisfies all of these criteria. Though a 3D ‘glass brain’ rendering can sometimes be difficult to interpret, they are useful in showing a more overall representation of the results, whereas the traditional slices show a more local view. Combined, presenting both 2D and 3D representations of MR images can provide a more comprehensive view of the study’s findings.

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42

Abdulkadhim Hameedi, Balsam, Muna Majeed Laftah, and Anwar Abbas Hattab. "Data Hiding in 3D-Medical Image." International Journal of Online and Biomedical Engineering (iJOE) 18, no. 03 (March 8, 2022): 72–88. http://dx.doi.org/10.3991/ijoe.v18i03.28007.

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Information hiding strategies have recently gained popularity in a variety of fields. Digital audio, video, and images are increasingly being labelled with distinct but undetectable marks that may contain a hidden copyright notice or serial number, or even directly help to prevent unauthorized duplication. This approach is extended to medical images by hiding secret information in them using the structure of a different file format. The hidden information may be related to the patient. In this paper, a method for hiding secret information in DICOM images is proposed based on Discrete Wavelet Transform (DWT). Firstly. segmented all slices of a 3D-image into a specific block size and collecting the host image depend on a generated key, secondly selected the block number and slice number, thirdly, the low-high band used for embedding after adding the generated number, fourthly, used the Hessenberg transform on the blocks that portioned the band (low-high) in a specific size. The secret information (image or text) is a binary value. It was embedded by setting the positive value in the diagonal to odd values if the embedded is one and setting it to even if the secret bit is zero. Several tests were applied, such as applying mean square error, peak signal to noise ratio PSNR, and structural similarity index measure SSIM. Some analyses such as adding noise, scaling, and rotation analysis are applied to test the efficiency. The results of the tests showed the strength of the proposed method.

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43

Prasertsuk, Santirak, and Chawee Busayarat. "3D Data Visualization and Analysis Tools for AI Ready City: Space Syntax and Social Media Data." Nakhara : Journal of Environmental Design and Planning 21, no. 2 (November 22, 2022): 214. http://dx.doi.org/10.54028/nj202221214.

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Space syntax is now widely accepted as a set of techniques that can be used to efficiently analyze spatial morphological structure at the city or community level. Segment analysis, a type of space syntax that is typically rendered through two-dimensional vector lines, can show the effectiveness of pedestrian and vehicular accesses to parts of a city. However, analysis of a city’s condition is far too diverse and complex for the use of space syntax alone. Other types of information, such as data from social media, can be integrated to determine and locate problems in the city, or to search for areas with potential for development. These types of data help in analyzing the quality of experience for those using the urban spaces, and they can be obtained by compiling the judgements of actual city dwellers, or by using advanced technologies to create a more realistic virtual reality and letting system users be the judges. The purpose of this research is to develop a 3D model and a virtual reality system capable of displaying the results of 3D urban morphological analysis, using space syntax segment analysis and social media data from urban space users to support the collaboration and communication among architects, designers, urban planners, city policy makers, or other city stakeholders. The virtual 3D model was created by using photogrammetry from aerial photographs, as well as a low polygon model built with referenced data from the photogrammetry model for faster rendering. The area of Thammasat University, Rangsit Center, was used as the prototype area for the AI Ready City.

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44

Abellera, Lourdes V. "K. Heather Kennedy: Introduction to 3D Data: Modeling with ArcGIS 3D Analyst and Google Earth." Mathematical Geosciences 44, no. 3 (January 25, 2012): 375–77. http://dx.doi.org/10.1007/s11004-011-9381-2.

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45

Almac, Umut, Isıl Polat Pekmezci, and Metin Ahunbay. "Numerical Analysis of Historic Structural Elements Using 3D Point Cloud Data." Open Construction and Building Technology Journal 10, no. 1 (May 31, 2016): 233–45. http://dx.doi.org/10.2174/1874836801610010233.

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The 3D laser scanner has become a common instrument in numerous field applications such as structural health monitoring, assessment and documentation of structural damages, volume and dimension control of excavations, geometrical recording of built environment, and construction progress monitoring in different fields. It enables capture of millions of points from the surface of objects with high accuracy and in a very short time. These points can be employed to extrapolate the shape of the elements. In this way, the collected data can be developed to construct three-dimensional digital models that can be used in structural FEM analysis. This paper presents structural evaluation of a historic building through FE models with the help of a 3D point cloud. The main focus of the study is on the stone columns of a historic cistern. These deteriorated load bearing elements have severe non-uniform erosion, which leads to formation of significant stress concentrations. At this point, the 3D geometric data becomes crucial in revealing the stress distribution of severely eroded columns due to material deterioration. According to the results of static analysis using real geometry, maximum stress in compression increased remarkably on the columns in comparison with the geometrically idealized models. These values seem to approach the compressive strength of the material, which was obtained from the point load test results. Moreover, the stress distribution of the analysis draws attention to the section between columns and their capitals. According to the detailed 3D documentation, there is a reduced contact surface between columns and capitals to transfer loads.

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46

Gamey, T. J. "Collection and Analysis of 3D Magnetic Data for UXO Discrimination." Journal of Environmental & Engineering Geophysics 11, no. 3 (September 1, 2006): 185–96. http://dx.doi.org/10.2113/jeeg11.3.185.

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47

Egurnov, D. A., and D. I. Ignatov. "Triclusters of Close Values for the Analysis of 3D Data." Automation and Remote Control 83, no. 6 (June 2022): 894–902. http://dx.doi.org/10.1134/s0005117922060078.

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48

Ferrando, L., I. Epifanio, and N. Ventura-Campos. "Ordinal classification of 3D brain structures by functional data analysis." Statistics & Probability Letters 179 (December 2021): 109227. http://dx.doi.org/10.1016/j.spl.2021.109227.

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49

Bouksim, Mohcine, Fatima Zakani, Khadija Arhid, Mohamed Aboulfatah, and Taoufiq Gadi. "New Approach for 3D Mesh Retrieval Using Data Envelopment Analysis." International Journal of Intelligent Engineering and Systems 11, no. 1 (February 28, 2018): 1–10. http://dx.doi.org/10.22266/ijies2018.0228.01.

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50

Henderson, J., G. Paton, B. Froner, J. Lowell, and M. Ackers. "Integrating interpretation expertise and objective data analysis in 3D interpretation." Leading Edge 31, no. 11 (November 2012): 1374–81. http://dx.doi.org/10.1190/tle31111374.1.

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