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Добірка наукової літератури з теми "3D Networks"

Автор: Grafiati

Опубліковано: 11 березня 2023

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Статті в журналах з теми "3D Networks"

1

Liang, Long, Christopher Jones, Shaohua Chen, Bo Sun, and Yang Jiao. "Heterogeneous force network in 3D cellularized collagen networks." Physical Biology 13, no. 6 (2016): 066001. http://dx.doi.org/10.1088/1478-3975/13/6/066001.

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2

Gou, Pingzhang, Baoyong Guo, Miao Guo, and Shun Mao. "VKECE-3D: Energy-Efficient Coverage Enhancement in Three-Dimensional Heterogeneous Wireless Sensor Networks Based on 3D-Voronoi and K-Means Algorithm." Sensors 23, no. 2 (2023): 573. http://dx.doi.org/10.3390/s23020573.

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During these years, the 3D node coverage of heterogeneous wireless sensor networks that are closer to the actual application environment has become a strong focus of research. However, the direct application of traditional two-dimensional planar coverage methods to three-dimensional space suffers from high application complexity, a low coverage rate, and a short life cycle. Most methods ignore the network life cycle when considering coverage. The network coverage and life cycle determine the quality of service (QoS) in heterogeneous wireless sensor networks. Thus, energy-efficient coverage enh

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3

Leng, Biao, Yu Liu, Kai Yu, Xiangyang Zhang, and Zhang Xiong. "3D object understanding with 3D Convolutional Neural Networks." Information Sciences 366 (October 2016): 188–201. http://dx.doi.org/10.1016/j.ins.2015.08.007.

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4

Chaaban, Fadi, Hanan Darwishe, and Jamal El Khattabi. "A Semi-Automatic Approach in GIS for 3D Modeling and Visualization of Utility Networks: Application for Sewer & Stormwater networks." MATEC Web of Conferences 295 (2019): 02003. http://dx.doi.org/10.1051/matecconf/201929502003.

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This paper presents a semi-automatic methodology proposed for 3D modeling of utility networks in GIS environment. The ModelBuilder in ArcGIS (ESRI) software is used for implementing this methodology, by developing two tools to automate the construction processes of 3D networks. The first presents a tool to create a 3D Manhole layer from points layer, and the second is a tool to create a 3D pipe layer. For both tools, a work algorithm has been built, in addition to designing user interfaces elements. These tools are stored in a Toolbox called “3D Manhole & Pipe.tbx”. The two previous tools

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5

Wang, Shaohua, Yeran Sun, Yinle Sun, et al. "A Hybrid Framework for High-Performance Modeling of Three-Dimensional Pipe Networks." ISPRS International Journal of Geo-Information 8, no. 10 (2019): 441. http://dx.doi.org/10.3390/ijgi8100441.

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Three-dimensional (3D) pipe network modeling plays an essential part in high performance-based smart city applications. Given that massive 3D pipe networks tend to be difficult to manage and to visualize, we propose in this study a hybrid framework for high-performance modeling of a 3D pipe network, including pipe network data model and high-performance modeling. The pipe network data model is devoted to three-dimensional pipe network construction based on network topology and building information models (BIMs). According to the topological relationships of the pipe point pipelines, the pipe n

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6

HUANG, MING, JINGJING YANG, ZHE XIAO, JUN SUN, and JINHUI PENG. "MODELING THE DIELECTRIC RESPONSE IN HETEROGENEOUS MATERIALS USING 3D RC NETWORKS." Modern Physics Letters B 23, no. 25 (2009): 3023–33. http://dx.doi.org/10.1142/s0217984909021090.

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A model of 3D RC networks was developed to describe the dielectric response of heterogeneous materials and was compared with the results of the 2D RC network model. We show that the "universal dielectric response" (UDR) of heterogeneous materials is a common feature of both 2D and 3D very large networks with randomly positioned resistors and capacitors, and that the percolation threshold of the 2D and 3D bond network are close to 0.5 and 0.25, respectively. In addition, it was found that the percolation threshold of the 3D network is in good agreement with the result of the coherent potential

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7

Fries, David, and Geran Barton. "3D MICROSENSOR IMAGING ARRAYS NETWORKS." Additional Conferences (Device Packaging, HiTEC, HiTEN, and CICMT) 2015, DPC (2015): 000348–78. http://dx.doi.org/10.4071/2015dpc-ta33.

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2D microsensor arrays can permit spatial distribution measurements of the sensed parameter and enable high resolution sensing visualizations. Measuring constituents in a flowing media, such as air or liquid could benefit from such flow through or flow across imaging systems. These flow imagers can have applications in mobile robotics and non-visible imagery, and alternate mechanical systems of perception, process control and environmental observations. In order to create rigid-conformal, large area imaging systems we have in the past merged flexible PCB substrates with rigid constructions from

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8

Jeong, Cheol, and Won-Yong Shin. "Capacity of 3D Erasure Networks." IEEE Transactions on Communications 64, no. 7 (2016): 2900–2912. http://dx.doi.org/10.1109/tcomm.2016.2569580.

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Berber, Mustafa, Petr Vaníček, and Peter Dare. "Robustness analysis of 3D networks." Journal of Geodynamics 47, no. 1 (2009): 1–8. http://dx.doi.org/10.1016/j.jog.2008.02.001.

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Thomas, Edwin L. "Nanoscale 3D ordered polymer networks." Science China Chemistry 61, no. 1 (2017): 25–32. http://dx.doi.org/10.1007/s11426-017-9138-5.

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Дисертації з теми "3D Networks"

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Stigeborn, Patrik. "Generating 3D-objects using neural networks." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-230668.

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Enabling a 2D- to 3D-reconstruction is an interesting future service for Mutate AB, where this thesis is conducted. Convolutional neural networks (CNNs) is examined in different aspects, in order to give a realistic perception of what this technology is capable of. The task conducted, is the creation of a CNN that can be used to predict how an object from a 2D image would look in 3D. The main areas that this CNN is optimized for are Quality, Speed, and Simplicity. Where Quality is the output resolution of the 3D object, Speed is measured by the number of seconds it takes to complete a reconstr

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2

Costa, Breno Jacinto Duarte da. "3D Routing with Context Awareness." Universidade Federal de Pernambuco, 2009. https://repositorio.ufpe.br/handle/123456789/1771.

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Made available in DSpace on 2014-06-12T15:52:15Z (GMT). No. of bitstreams: 1 license.txt: 1748 bytes, checksum: 8a4605be74aa9ea9d79846c1fba20a33 (MD5) Previous issue date: 2009<br>Conselho Nacional de Desenvolvimento Científico e Tecnológico<br>O surgimento de interfaces de rede sem-fio de baixo custo no mercado e o crescimento na demanda por dispositivos móveis (como Smartphones, PDAs, Internet Tablets e Laptops) permitiram a criação de cenários onde serviços de rede para usuários móveis possam existir sem nenhuma infra-estrutrutura pré-configurada. No entanto, a interoperabilidade ent

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3

Zhao, Yao. "Autonomous Localization in 3D Surface Wireless Sensor Networks." Thesis, University of Louisiana at Lafayette, 2014. http://pqdtopen.proquest.com/#viewpdf?dispub=3622968.

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<p> Location awareness is imperative for a variety of sensing applications and network operations. Although a diversity of GPS-less and GPS-free solutions have been developed recently for autonomous localization in wireless sensor networks, they primarily target at 2D planar or 3D volumetric settings. There exists unique and fundamental hardness to extend them to 3D surfaces.</p><p> The contributions of this work are twofold. First, it proposes a theoretically-proven algorithm for the 3D surface localization problem. Seeing the challenges to localize general 3D surface networks and the solva

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4

Cronje, Frans. "Human action recognition with 3D convolutional neural networks." Master's thesis, University of Cape Town, 2015. http://hdl.handle.net/11427/15482.

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Convolutional neural networks (CNNs) adapt the regular fully-connected neural network (NN) algorithm to facilitate image classification. Recently, CNNs have been demonstrated to provide superior performance across numerous image classification databases including large natural images (Krizhevsky et al., 2012). Furthermore, CNNs are more readily transferable between different image classification problems when compared to common alternatives. The extension of CNNs to video classification is simple and the rationale behind the components of the model are still applicable due to the similarity be

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5

Nihlén, Ramström Max. "Sketch to 3D Model using Generative Query Networks." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-251507.

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For digital artists and animators, translating an idea from a rough sketch to a 3D model is a time consuming process requiring a plethora of different software. In this work, a Generative Model which can directly generate images of 3D models from arbitrary view points by observing sketched 2D images is presented. The model is based on Generative Query Networks and two different generative models were tested for generating new images, the first a Variational Auto Encoder and the second a Generative Adversarial Network. The model learns to produce new images from any queried view point allowing

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6

Mohib, Hamdullah. "End-to-end 3D video communication over heterogeneous networks." Thesis, Brunel University, 2014. http://bura.brunel.ac.uk/handle/2438/8293.

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Three-dimensional technology, more commonly referred to as 3D technology, has revolutionised many fields including entertainment, medicine, and communications to name a few. In addition to 3D films, games, and sports channels, 3D perception has made tele-medicine a reality. By the year 2015, 30% of the all HD panels at home will be 3D enabled, predicted by consumer electronics manufacturers. Stereoscopic cameras, a comparatively mature technology compared to other 3D systems, are now being used by ordinary citizens to produce 3D content and share at a click of a button just like they do with t

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Birgersson, Anna, and Klara Hellgren. "Texture Enhancement in 3D Maps using Generative Adversarial Networks." Thesis, Linköpings universitet, Datorseende, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-162446.

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In this thesis we investigate the use of GANs for texture enhancement. To achievethis, we have studied if synthetic satellite images generated by GANs will improvethe texture in satellite-based 3D maps. We investigate two GANs; SRGAN and pix2pix. SRGAN increases the pixelresolution of the satellite images by generating upsampled images from low resolutionimages. As for pip2pix, the GAN performs image-to-image translation bytranslating a source image to a target image, without changing the pixel resolution. We trained the GANs in two different approaches, named SAT-to-AER andSAT-to-AER-3D, wher

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8

Nguyen, Thu Duc. "System support for distributed 3D real-time rendering on commodity clusters /." Thesis, Connect to this title online; UW restricted, 1999. http://hdl.handle.net/1773/7018.

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9

Ahmad, Waqar. "Core Switching Noise for On-Chip 3D Power Distribution Networks." Doctoral thesis, KTH, Elektroniksystem, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-103566.

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Reducing the interconnect size with each technology node and increasing speed with each generation increases IR-drop and Ldi/dt noise. In addition to this, the drive for more integration increases the average current requirement for modern ULSI design. Simultaneous switching of core logic blocks and I/O drivers produces large current transients due to power distribution network parasitics at high clock frequency. The current transients are injected into the power distribution planes thereby inducing noise in the supply voltage. The part of the noise that is caused by switching of the internal

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10

Nordhus, Lars Espen Strand. "Ray Tracing for Simulation of Wireless Networks in 3D Scenes." Thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for datateknikk og informasjonsvitenskap, 2013. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-23002.

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Simulating WIFI and other similar radio waves in real-time environments has a tremendous potential, and is a hot topic in modern computer science. The Norwegian Road Authority in Trondheim (Norway) has created a physical test road for simulating future road to vehicle communications in a realistic setting. By doing so they get an excellent physical simulator for realistic small scale testing which can be used to verify a computational simulator. IEEE has created a vehicle-to-vehicle communication standard called IEEE 802.11p: Wireless Access for the Vehicular Environment (WAVE) [Wireless Acces

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Книги з теми "3D Networks"

1

1966-, O'Driscoll Tony, ed. Learning in 3D: Adding a new dimension to enterprise learning and collaboration. Pfeiffer, 2010.

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2

Kapp, Karl M. Learning in 3D: Adding a new dimension to enterprise learning and collaboration. Pfeiffer, 2010.

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3

Kapp, Karl M. Learning in 3D: Adding a new dimension to enterprise learning and collaboration. Jossey-Bass, 2010.

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4

Brath, Richard Karl. Effective information visualization guidelines and metrics for 3D interactive representations of business data. Brath, 1999.

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5

International, Workshop on Laser and Fiber-optical Networks Modeling (3rd 2001 Kharkiv Ukraine). LFNM'2001: Proceedings of 3d International Workshop on Laser and Fiber-optical Networks Modeling : Kharkiv State University of Radio Electronics : Ukraine, May 23, 2000. IEEE, 2001.

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6

Cappellini, Vito, ed. Electronic Imaging & the Visual Arts. EVA 2013 Florence. Firenze University Press, 2013. http://dx.doi.org/10.36253/978-88-6655-372-4.

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Important Information Technology topics are presented: multimedia systems, data-bases, protection of data, access to the content. Particular reference is reserved to digital images (2D, 3D) regarding Cultural Institutions (Museums, Libraries, Palace – Monuments, Archaeological Sites). The main parts of the Conference Proceedings regard: Strategic Issues, EC Projects and Related Networks & Initiatives, International Forum on “Culture & Technology”, 2D – 3D Technologies & Applications, Virtual Galleries – Museums and Related Initiatives, Access to the Culture Information. Three Works

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7

Kim, Moon S. Defense and security 2008: Special sessions on food safety, visual analytics, resource restricted embedded and sensor networks, and 3D imaging and display : 17-18 March 2008, Orlando, Florida, USA. Edited by Society of Photo-optical Instrumentation Engineers. SPIE, 2008.

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8

Tatas, Konstantinos, Kostas Siozios, Dimitrios Soudris, and Axel Jantsch. Designing 2D and 3D Network-on-Chip Architectures. Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4614-4274-5.

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Cappellini, Vito, ed. Electronic Imaging & the Visual Arts. EVA 2014 Florence. Firenze University Press, 2014. http://dx.doi.org/10.36253/978-88-6655-573-5.

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Information Technologies of interest for Culture Heritage are presented: multimedia systems, data-bases, data protection, access to digital content, Virtual Galleries. Particular reference is reserved to digital images (Electronic Imaging & the Visual Arts), regarding Cultural Institutions (Museums, Libraries, Palace - Monuments, Archaeological Sites). The International Conference includes the following Sessions: Strategic Issues; EC Projects and Related Networks & Initiatives; 2D - 3D Technologies and Applications; Virtual Galleries - Museums and Related Initiatives; Access to the Cul

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10

Frega, Monica. Neuronal Network Dynamics in 2D and 3D in vitro Neuroengineered Systems. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-30237-9.

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Частини книг з теми "3D Networks"

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Bellocchio, Francesco, N. Alberto Borghese, Stefano Ferrari, and Vincenzo Piuri. "Hierarchical Radial Basis Functions Networks." In 3D Surface Reconstruction. Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4614-5632-2_5.

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2

Jagtap, Yash, Hitesh Shewale, Dinesh Bhadane, and M. V. Rao. "3D Smart Map." In Lecture Notes in Networks and Systems. Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-3812-9_54.

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3

Jiang, Hao, and Guan Gui. "3D Scattering Channel Modeling for Microcell Communication Environments." In Wireless Networks. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-32869-6_3.

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4

Akdere, Mert, Uğur Çetintemel, Daniel Crispell, John Jannotti, Jie Mao, and Gabriel Taubin. "Data-Centric Visual Sensor Networks for 3D Sensing." In GeoSensor Networks. Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-79996-2_8.

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5

Borzemski, Leszek, and Anna Kamińska-Chuchmała. "3D Web Performance Forecasting Using Turning Bands Method." In Computer Networks. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-21771-5_12.

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Gardikis, Georgios, Evangelos Pallis, and Michael Grafl. "Media-Aware Networks in Future Internet Media." In 3D Future Internet Media. Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-8373-1_7.

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Mensing, Glennys, and David J. Beebe. "Liquid Phase 3D Channel Networks." In Micro Total Analysis Systems 2002. Springer Netherlands, 2002. http://dx.doi.org/10.1007/978-94-010-0295-0_137.

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Tigadoli, Rishabh, Ramesh Ashok Tabib, Adarsh Jamadandi, and Uma Mudenagudi. "3D-GCNN - 3D Object Classification Using 3D Grid Convolutional Neural Networks." In Lecture Notes in Computer Science. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-34869-4_30.

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Piorkowski, Adam, Lukasz Jajesnica, and Kamil Szostek. "Creating 3D Web-Based Viewing Services for DICOM Images." In Computer Networks. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02671-3_26.

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Skabek, Krzysztof, and Łukasz Ząbik. "Network Transmission of 3D Mesh Data Using Progressive Representation." In Computer Networks. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02671-3_38.

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Тези доповідей конференцій з теми "3D Networks"

1

Marquez, Alejandra, and Alex Cuadros. "3D Medical Image Segmentation based on 3D Convolutional Neural Networks." In LatinX in AI at Neural Information Processing Systems Conference 2018. Journal of LatinX in AI Research, 2018. http://dx.doi.org/10.52591/lxai201812031.

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A neural network is a mathematical model that is able to perform a task automatically or semi-automatically after learning the human knowledge that we provided. Moreover, a Convolutional Neural Network (CNN) is a type of sophisticated neural network that has shown to efficiently learn tasks related to the area of image analysis (among other areas). One example of these tasks is image segmentation, which aims to find regions or separable objects within an image. A more specific type of segmentation called semantic segmentation, makes sure that each region has a semantic meaning by giving it a l

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2

An, Dong, Tianxu Xu, Yiwen Zhang, and Yang Yue. "Hand Gesture Recognition Using ToF Camera and 3D Point Cloud Networks." In Frontiers in Optics. Optica Publishing Group, 2022. http://dx.doi.org/10.1364/fio.2022.jw4b.56.

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Gesture recognition is achieved by using ToF camera and deep neural networks based on 3D point cloud. An average recognition accuracy of the networks is >99%. PointNet++ (MSG) network demonstrates better performance than other networks.

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3

Dulikravich, George S., and Thomas J. Martin. "Optimization of 3D Branching Networks of Microchannels for Microelectronic Device Cooling." In 2010 14th International Heat Transfer Conference. ASMEDC, 2010. http://dx.doi.org/10.1115/ihtc14-22719.

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The aim of this work is to present a methodology to develop cost-effective thermal management solutions for microelectronic devices, capable of removing maximum amount of heat and delivering maximally uniform surface temperature distributions. The topological and geometrical characteristics of multiple-story three-dimensional branching networks of microchannels were developed using multi-objective optimization. The design variables which will be subject to optimization in this analysis are the geometric parameters of the microchannel network, i.e. the number of network floors in a 3D network,

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4

Berhan, L., C. W. Wang, and A. M. Sastry. "Damage Initiation in Bonded Particulate Networks: 3D Simulations." In ASME 2001 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2001. http://dx.doi.org/10.1115/imece2001/ad-25304.

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Abstract Several promising Li-ion technologies incorporate micro- and nanoarchitectured carbon networks, typically in the form of whisker/particle blends bonded with thermoplastic binders, in the electrodes. Degradation of these battery electrode materials is currently a persistent problem, with damage presenting as blistering and/or delamination. We are investigating bonding in micro- and nanostructured materials in order to predict onset of this degradation of these stochastic materials. Here, we describe a general methodology in modeling the small junctures in these porous network materials

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Zhao, Yongheng, Tolga Birdal, Haowen Deng, and Federico Tombari. "3D Point Capsule Networks." In 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2019. http://dx.doi.org/10.1109/cvpr.2019.00110.

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Cha, Geonho, Minsik Lee, and Songhwai Oh. "Unsupervised 3D Reconstruction Networks." In 2019 IEEE/CVF International Conference on Computer Vision (ICCV). IEEE, 2019. http://dx.doi.org/10.1109/iccv.2019.00395.

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Qamar, Isabel P. S., and Richard S. Trask. "Development of Multi-Dimensional 3D Printed Vascular Networks for Self-Healing Materials." In ASME 2017 Conference on Smart Materials, Adaptive Structures and Intelligent Systems. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/smasis2017-3829.

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Self-healing materials have emerged as an alternative solution to the repair of damage in fibre-reinforced composites. Recent developments have largely focused on a vascular approach, due to the ability to transport healing agents over long distances and continually replenish from an external source. However fracture of the vascular network is required to enable the healing agents to infiltrate the crack plane, ceasing its primary function in transporting fluid and preventing the repair of any further damage events. Here we present a novel approach to vascular self-healing through the developm

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Göhnert, Tilman, Sabrina Ziebarth, Henrik Detjen, Tobias Hecking, and H. Ulrich Hoppe. "3D DynNetVis." In ASONAM '15: Advances in Social Networks Analysis and Mining 2015. ACM, 2015. http://dx.doi.org/10.1145/2808797.2808798.

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Graham, Ben. "Sparse 3D convolutional neural networks." In British Machine Vision Conference 2015. British Machine Vision Association, 2015. http://dx.doi.org/10.5244/c.29.150.

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Jin, Shengmin, and Reza Zafarani. "Representing Networks with 3D Shapes." In 2018 IEEE International Conference on Data Mining (ICDM). IEEE, 2018. http://dx.doi.org/10.1109/icdm.2018.00033.

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Звіти організацій з теми "3D Networks"

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Santoyo, C., M. R. Ceron, and M. M. Biener. Integration of Fullerenes as Electron-Acceptors in 3D Graphene Networks. Office of Scientific and Technical Information (OSTI), 2019. http://dx.doi.org/10.2172/1567989.

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De Crescenzi, Maurizio. 3D Carbon Nanotube Networks as Mechanical, Electrical and Photovoltaic Transducer and Superhydrophobic Filter. Defense Technical Information Center, 2015. http://dx.doi.org/10.21236/ada621229.

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Wang, Shiren. Proof-of-Concept: Assembling Carbon Nanocrystals for Ordered 3D Network. Defense Technical Information Center, 2011. http://dx.doi.org/10.21236/ada566278.

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Huang, Haohang, Erol Tutumluer, Jiayi Luo, Kelin Ding, Issam Qamhia, and John Hart. 3D Image Analysis Using Deep Learning for Size and Shape Characterization of Stockpile Riprap Aggregates—Phase 2. Illinois Center for Transportation, 2022. http://dx.doi.org/10.36501/0197-9191/22-017.

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Riprap rock and aggregates are extensively used in structural, transportation, geotechnical, and hydraulic engineering applications. Field determination of morphological properties of aggregates such as size and shape can greatly facilitate the quality assurance/quality control (QA/QC) process for proper aggregate material selection and engineering use. Many aggregate imaging approaches have been developed to characterize the size and morphology of individual aggregates by computer vision. However, 3D field characterization of aggregate particle morphology is challenging both during the quarry

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KHVOENKOVA, Nina, and Matthieu DELORME. An Optimal Method to Model Transient Flows in 3D Discrete Fracture Network. Cogeo@oeaw-giscience, 2011. http://dx.doi.org/10.5242/iamg.2011.0088.

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Kompaniets, Alla, Hanna Chemerys, and Iryna Krasheninnik. Using 3D modelling in design training simulator with augmented reality. [б. в.], 2020. http://dx.doi.org/10.31812/123456789/3740.

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The article is devoted to the theoretical consideration of the problem and the use of innovative technologies in the educational process in the educational establishment of secondary education in the process of studying the school course of computer science. The main advantages of using educational simulators in the educational process are considered, based on the new state standard of basic and complete general secondary education. Based on the analysis of scientific and methodological literature and network sources, the features of the development of simulators for educational purposes are d

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Muto, Kazuo. Trend of 3D CAD/CAE/CAM/CAT/Network Systems and PLM System in Advance Technology for Manufacturing Engineering Development. SAE International, 2005. http://dx.doi.org/10.4271/2005-08-0137.

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Habib, Ayman, Darcy M. Bullock, Yi-Chun Lin, and Raja Manish. Road Ditch Line Mapping with Mobile LiDAR. Purdue University, 2021. http://dx.doi.org/10.5703/1288284317354.

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Maintenance of roadside ditches is important to avoid localized flooding and premature failure of pavements. Scheduling effective preventative maintenance requires mapping of the ditch profile to identify areas requiring excavation of long-term sediment accumulation. High-resolution, high-quality point clouds collected by mobile LiDAR mapping systems (MLMS) provide an opportunity for effective monitoring of roadside ditches and performing hydrological analyses. This study evaluated the applicability of mobile LiDAR for mapping roadside ditches for slope and drainage analyses. The performance o

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Kirchhoff, Helmut, and Ziv Reich. Protection of the photosynthetic apparatus during desiccation in resurrection plants. United States Department of Agriculture, 2014. http://dx.doi.org/10.32747/2014.7699861.bard.

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In this project, we studied the photosynthetic apparatus during dehydration and rehydration of the homoiochlorophyllous resurrection plant Craterostigmapumilum (retains most of the photosynthetic components during desiccation). Resurrection plants have the remarkable capability to withstand desiccation, being able to revive after prolonged severe water deficit in a few days upon rehydration. Homoiochlorophyllous resurrection plants are very efficient in protecting the photosynthetic machinery against damage by reactive oxygen production under drought. The main purpose of this BARD project was

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