scholarly journals Material feature representation and identification with composite surfacelets

2016 ◽  
Vol 3 (4) ◽  
pp. 370-384 ◽  
Author(s):  
Wei Huang ◽  
Yan Wang ◽  
David W. Rosen
Keyword(s):  
Reverse Engineering ◽  
Multiple Scales ◽  
Three Dimensional ◽  
Parametric Representation ◽  
Feature Representation ◽  
Fine Grained ◽  
Modeling Material ◽  
Material Feature ◽  
Surfacelet Transform ◽  
Edge Features

Abstract Computer-aided materials design requires new modeling approaches to characterize and represent fine-grained geometric structures and material compositions at multiple scales. Recently, a dual-Rep approach was developed to model materials microstructures based on a new basis function, called surfacelet. As a combination of implicit surface and wavelets, surfacelets can efficiently identify and represent planar, cylindrical, and ellipsoidal geometries in material microstructures and describe the distribution of compositions and properties. In this paper, these primitive surfacelets are extended and composite surfacelets are proposed to model more complex geometries. Composite surfacelets are constructed by Boolean operations on the primitives. The surfacelet transform is applied to match geometric features in three-dimensional images. The composition of the material near the identified features can then be modeled. A cubic surfacelet and a v-joint surfacelet are developed to demonstrate the reverse engineering process of retrieving material compositions from material images. Highlights Modeling material distribution and edge singularity with composition of implicit surfaces. Identifying edge features in images with surface integrals and surfacelet transform. Enabling reverse engineering of materials with parametric representation.

Reliable Part Guided Multiple Level Attention Learning for Person Re-Identification

2021 ◽  
pp. 2150246
Author(s):  
Yanbing Geng ◽  
Yongjian Lian ◽  
Shunmin Yang ◽  
Mingliang Zhou ◽  
Jingchao Cao
Keyword(s):  
Multiple Scales ◽  
State Of The Art ◽  
Feature Representation ◽  
Late Fusion ◽  
Fine Grained ◽  
Background Clutter ◽  
Multiple Levels ◽  
Body Components ◽  
Point Detection ◽  
Multiple Task

Person Re-ID is challenged by background clutter, body misalignment and part missing. In this paper, we propose a reliable part-based multiple levels attention deep network to learn multiple scales salience representation. In particular, person alignment and key point detection are sequentially carried out to locate three relative stable body components, then fused attention (FA) mode is designed to capture the fine-grained salient features from effective spatial of valuable channels of each part, regional attention mode is succeeded to weight the importance of different parts for highlighting the representative parts while suppressing the valueless ones. A late fusion-based multiple-task loss is finally adopted to further optimize the valuable feature representation. Experimental results demonstrate that the proposed method achieves state-of-the-art performances on three challenging benchmarks: Market-1501, DukeMTMC-reID and CUHK03.

scholarly journals Increase in Total Elongation Caused by Pure Shear Deformation in Ultra-Fine-Grained Cu Processed by Equal-Channel Angular Pressing

Metals ◽  
2020 ◽  
Vol 10 (5) ◽  
pp. 654
Author(s):  
Ryosuke Matsutani ◽  
Nobuo Nakada ◽  
Susumu Onaka
Keyword(s):  
Shear Deformation ◽  
Equal Channel Angular Pressing ◽  
Pure Shear ◽  
Three Dimensional ◽  
Tensile Tests ◽  
Total Elongation ◽  
Local Deformation ◽  
Image Correlation ◽  
Fine Grained ◽  
Angular Pressing

Ultra-fine-grained (UFG) Cu shows little total elongation in tensile tests because simple shear deformation is concentrated in narrow regions during the initial stage of plastic deformation. Here, we attempted to improve the total elongation of UFG Cu obtained by equal-channel angular pressing. By making shallow dents on the side surfaces of the plate-like specimens, this induced pure shear deformation and increased their total elongation. During the tensile tests, we observed the overall and local deformation of the dented and undented UFG Cu specimens. Using three-dimensional digital image correlation, we found that the dented specimens showed suppression of thickness reduction and delay in fracture by enhancement of pure shear deformation. However, the dented and undented specimens had the same ultimate tensile strength. These results provide us a new concept to increase total elongation of UFG materials.

scholarly journals Impact of Position and Orientation of RFID Tags on Real Time Asset Tracking in a Supply Chain

2008 ◽  
Vol 3 (1) ◽  
pp. 1-12
Author(s):  
Sidney D’Mello ◽  
Eric Mathews ◽  
Lee McCauley ◽  
James Markham
Keyword(s):  
Supply Chain ◽  
Real World ◽  
Three Dimensional ◽  
Three Dimensions ◽  
Rfid Tags ◽  
Vertical Orientation ◽  
Fine Grained ◽  
Asset Tracking ◽  
Transverse Electromagnetic ◽  
World Environment

We studied the characteristics of four commercially available RFID tags such as their orientation on an asset and their position in a three dimensional real world environment to obtain comprehensive data to substantiate a baseline for the use of RFID technology in a diverse supply chain management setting. Using RFID tags manufactured by four different vendors and a GHz Transverse Electromagnetic (GTEM) cell, in which an approximately constant electromagnetic (EM) field was maintained, we characterized the tags based on horizontal and vertical orientation on a simulated asset. With these baseline characteristics determined, we moved two of the four tags through a real world environment in three dimensions using an industrial robotic system to determine the effect of asset position in relation to the reader on tag readability. Combining the data collected over these two studies, we provide a rich analysis of the feasibility of asset tracking in a real world supply chain, where there would likely be multiple tag types. We offer fine grained analyses of the tag types and make recommendations for diverse supply chain asset tracking.

scholarly journals Collisionless Dynamics and the Cosmic Web

2014 ◽  
Vol 11 (S308) ◽  
pp. 87-96
Author(s):  
Oliver Hahn
Keyword(s):  
Dark Matter ◽  
Structure Formation ◽  
Large Scale ◽  
Velocity Potential ◽  
Three Dimensional ◽  
Maximum Amount ◽  
Lagrangian Manifold ◽  
Linear Regime ◽  
Fine Grained ◽  
Simulation Techniques

AbstractI review the nature of three-dimensional collapse in the Zeldovich approximation, how it relates to the underlying nature of the three-dimensional Lagrangian manifold and naturally gives rise to a hierarchical structure formation scenario that progresses through collapse from voids to pancakes, filaments and then halos. I then discuss how variations of the Zeldovich approximation (based on the gravitational or the velocity potential) have been used to define classifications of the cosmic large-scale structure into dynamically distinct parts. Finally, I turn to recent efforts to devise new approaches relying on tessellations of the Lagrangian manifold to follow the fine-grained dynamics of the dark matter fluid into the highly non-linear regime and both extract the maximum amount of information from existing simulations as well as devise new simulation techniques for cold collisionless dynamics.

scholarly journals The pre-Late Wisconsin stratigraphy of southern Simcoe County, Ontario: implications for ice sheet buildup, decay, and Great Lakes drainage evolution

2018 ◽  
Vol 55 (7) ◽  
pp. 709-729 ◽  
Author(s):  
Riley P.M. Mulligan ◽  
Andy F. Bajc
Keyword(s):  
Great Lakes ◽  
Three Dimensional ◽  
Coarse Grained ◽  
Framework Analysis ◽  
Glacial Cycles ◽  
Fine Grained ◽  
Three Dimensional Mapping ◽  
Stratigraphic Framework ◽  
Reference Sections ◽  
Groundwater Supply

Recent three-dimensional mapping investigations in southern Simcoe County, Ontario, allow refinement of the existing regional stratigraphic framework. Analysis of 25 continuously cored boreholes has revealed a complex but consistent sediment succession that provides a record of the last two glacial cycles (Marine Isotope Stages 1–6). Five stratigraphic units (SU1–SU5) comprise the pre-Late Wisconsin record. The stratigraphy is floored by a presumed Illinoian glacial complex consisting of a lower, coarse-grained till (SU1), locally overlain by stratified glaciolacustrine and glaciofluvial sediments (SU2), but more commonly capped by a stone-poor, fine-grained till (SU3) of the Georgian Bay lobe. A widespread subaerial unconformity developed on the upper surface of SU3 contains organic-bearing, nonglacial deposits (SU4) ranging between 54 800 ± 3000 years BP (considered beyond the limits of radiocarbon dating) and 37 450 ± 590 14C years BP. SU4 is abruptly overlain by a thick succession of rhythmically laminated lacustrine muds graded upwards into glaciolacustrine silts and clays interrupted by regionally continuous sand bodies (SU5). The succession is capped (and locally truncated) by Late Wisconsin Newmarket Till. The sedimentary record of southern Simcoe County is correlated with other well-studied reference sections in southern Ontario and contains information that informs reconstructions of former ice extents in the lower Great Lakes region following the Illinoian glaciation. Several sediment units host aquifers, but limited thickness and spatial extent, as well as issues with naturally occurring dissolved gases and solids, restrict their use for groundwater supply.

scholarly journals Synchrotron radiation X-ray tomographic microscopy (SRXTM) of brachiopod shell interiors for taxonomy: Preliminary report

2010 ◽  
pp. 109-117 ◽  
Author(s):  
Neda Motchurova-Dekova ◽  
David Harper
Keyword(s):  
Synchrotron Radiation ◽  
Three Dimensional ◽  
X Rays ◽  
X Ray ◽  
Fine Grained ◽  
Internal Structures ◽  
Efficient Alternative ◽  
Micro Tomography ◽  
Light Beams ◽  
Non Destructive

Synchrotron radiation X-ray tomographic microscopy (SRXTM) is a non-destructive technique for the investigation and visualization of the internal features of solid opaque objects, which allows reconstruction of a complete three-dimensional image of internal structures by recording of the differences in the effects on the passage of waves of energy reacting with those structures. Contrary to X-rays, produced in a conventional X-ray tube, the intense synchrotron light beams are sharply focused like a laser beam. We report encouraging results from the use of SRXTM for purely taxonomic purposes in brachiopods: an attempt to find a non-destructive and more efficient alternative to serial sectioning and several other methods of dissection together with the non-destructive method of X-ray computerised micro-tomography. Two brachiopod samples were investigated using SRXTM. In ?Rhynchonella? flustracea it was possible to visualise the 3D shape of the crura and dental plates. In Terebratulina imbricata it was possible to reveal the form of the brachidium. It is encouraging that we have obtained such promising results using SRXTM with our very first two fortuitous samples, which had respectively fine-grained limestone and marl as infilling sediment, in contrast to the discouraging results communicated to us by some colleagues who have tested specimens with such infillings using X-ray micro-tomography. In future the holotypes, rare museum specimens or delicate Recent material may be preferentially subjected to this mode of analysis.

The nuclear pore complex: three-dimensional surface structure revealed by field emission, in-lens scanning electron microscopy, with underlying structure uncovered by proteolysis

1993 ◽  
Vol 106 (1) ◽  
pp. 261-274 ◽  
Author(s):  
M.W. Goldberg ◽  
T.D. Allen
Keyword(s):  
Nuclear Pore Complex ◽  
Three Dimensional ◽  
Underlying Structure ◽  
Nuclear Pore ◽  
Electron Microscopic ◽  
Biologically Relevant ◽  
Fine Grained ◽  
Outer Periphery ◽  
Electron Microscopes ◽  
Scanning Electron

The structure of the nuclear pore complex (NPC) has been previously studied by many different electron microscopic techniques. Recently, scanning electron microscopes have been developed that can visualise biologically relevant structural detail at the same level of resolution as transmission electron microscopes and have been used to study NPC structure. We have used such an instrument to visualise directly the structure of both cytoplasmic and nucleoplasmic surfaces of the NPC of manually isolated amphibian oocyte nuclear envelopes that have been spread, fixed, critical point dried and coated with a thin fine-grained film of chromium or tantalum. We present images that directly show features of the NPC that are visible at each surface, including coaxial rings, cytoplasmic particles, plug/spoke complexes and the nucleoplasmic basket or fishtrap. Some cytoplasmic particles are rod-shaped or possibly “T”-shaped, can be quite long structures extending into the cytoplasm and may be joined to the coaxial ring at a position between each subunit. Both coaxial rings, which are proud of the membranes, can be exposed by light proteolytic digestion, revealing eight equal subunits each of which may be bipartite. We have determined that the nucleoplasmic filaments that make up the baskets are attached to the outer periphery of the coaxial ring at a position between each of its subunits. These filaments extend into the nucleoplasm and insert at the distal end to the smaller basket ring. The space left between adjacent basket filaments would exclude particles bigger than about 25 nm, which is consistent with the exclusion limit previously found for NPC-transported molecules.

scholarly journals Latent 3D Volume for Joint Depth Estimation and Semantic Segmentation from a Single Image

Sensors ◽  
2020 ◽  
Vol 20 (20) ◽  
pp. 5765 ◽  
Author(s):  
Seiya Ito ◽  
Naoshi Kaneko ◽  
Kazuhiko Sumi
Keyword(s):  
3D Structure ◽  
Three Dimensional ◽  
Semantic Segmentation ◽  
Depth Estimation ◽  
Image Features ◽  
Feature Representation ◽  
Single Image ◽  
Feature Vectors ◽  
3D Space ◽  
3D Volume

This paper proposes a novel 3D representation, namely, a latent 3D volume, for joint depth estimation and semantic segmentation. Most previous studies encoded an input scene (typically given as a 2D image) into a set of feature vectors arranged over a 2D plane. However, considering the real world is three-dimensional, this 2D arrangement reduces one dimension and may limit the capacity of feature representation. In contrast, we examine the idea of arranging the feature vectors in 3D space rather than in a 2D plane. We refer to this 3D volumetric arrangement as a latent 3D volume. We will show that the latent 3D volume is beneficial to the tasks of depth estimation and semantic segmentation because these tasks require an understanding of the 3D structure of the scene. Our network first constructs an initial 3D volume using image features and then generates latent 3D volume by passing the initial 3D volume through several 3D convolutional layers. We apply depth regression and semantic segmentation by projecting the latent 3D volume onto a 2D plane. The evaluation results show that our method outperforms previous approaches on the NYU Depth v2 dataset.

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