A Global Geometric Framework for Nonlinear Dimensionality Reduction.Data from two different airborne hyperspectral sensors, AISA Eagle and Hawk, are used to evaluate transferability of band selection when using different sensors.By matching structural relatedness along all dimensions, the algorithm builds up vector paths for every voxel in the image volume representing its structural neighborhood.
The method is relatively simple and inexpensive, has a high throughput, provides nanoscale sensitivity for 3D measurements and could enable significant savings and yield improvements in nanometrology and nanomanufacturing.When the pairwise RMSD is employed as the local distance metric, implicit representations are used for the protein conformation space, leading to no direct correspondence to a Euclidean set.We compared the scaling trends of two key outputs of dimensionality reduction—shared dimensionality and percent shared variance—with neuron and trial count.We demonstrate a drastic improvement in dimensionality reduction with the use of nonlinear methods.
Software was developed for extracting target spatial coordinates in real time based on two- dimensional image feature recognition.Measurements are performed with superconducting quantum interference devices inductively coupled to magnetometer or gradiometer coils, and the resulting signals are converted to digital form in the data acquisition system.In the present paper, a new method for solving three- dimensional topology optimization problem is proposed.These results suggest that the selected SNP combination of the SCD1 gene and superior genotype groups can provide useful inferences for the improvement of the fatty acid composition in Korean native cattle.Specifically, our method explores the correlations within each view independently, and maximizes the dependence among different views with kernel matching jointly.Reduced basis ANOVA methods for partial differential equations with high- dimensional random inputs.We apply this approach in an analysis of temporal bones of diverse but related primate species, Gorilla gorilla, Pan troglodytes, Homo sapiens, and Papio hamadryas anubis, to illustrate the potential of these methods.Decentralized Dimensionality Reduction for Distributed Tensor Data Across Sensor Networks.
A number of methods currently exist for accomplishing this reduction.Optimal channel selection without eigenanalysis makes the J-CQO on large- dimensional image data feasible.In addition, the RVC-CAL library is an excellent tool to simplify the implementation process of HI algorithms.The automatically obtained sensitivity information is required to set up the method.Direct Linear Transformation Method for Three- Dimensional Cinematography.The proposed method is generic and can be applied to any snake robot represented as a set of control vertices.Methods and devices for fabricating three- dimensional nanoscale structures.
Introduction Stability and retention of the denture becomes at stake with the increase in weight of the denture prosthesis.The speckle index, mean square error, and signal-to-noise ratio are used as performance metrics and are shown to have been significantly improved by the proposed method to reduce speckle noise in the 3D object reconstruction. 3D reconstruction experiments of objects with reduced speckle noise are presented.This paper presents progress on swimming hydrodynamics using a boundary integral equation method (or boundary element method ) based on potential flow model.Multifactor dimensionality reduction (MDR) was developed as a method for detecting statistical patterns of epistasis.A second contribution of this work is a local method of species reconstruction, called ICE-PIC, which is based on the ICE manifold and uses preimage curves (PICs).The performance of the proposed method is estimated in terms of degrees of freedom downsizing, computational time enhancement, as well as matrix sparsity of the reduced system.Volumetric images of a region of the human hand are obtained by moving an ultrasound linear array along its elevation direction and one by one acquiring a number of B-mode images, which are then grouped in a 3-D matrix.The optimum for A has the best overall performance over a wide range of speed.
The proposed algorithm is based on multiresolution techniques for local inversion of the 3-D Radon transform in confined subvolumes within the entire object space.The objective of this program is to produce a series of new computer codes that permit more accurate and efficient three- dimensional inelastic structural analysis of combustor liners, turbine blades, and turbine vanes.Complex thermal processes are usually modelled by sophisticated numerical programs, but the execution delays are often long and the required memory spaces generally large.The elasticity solution for the stress distribution due to concentrated forces and a moment applied at an arbitrary point in a cracked infinite plate are used as the fundamental solution.One consequence of this mathematical approach to the singularities in General Relativity is a special, (geo)metric type of dimensional reduction: at singularities, the metric tensor becomes degenerate in certain spacetime directions, and some properties of the fields become independent of those directions.Another important contribution of the research is the application of advanced binarization techniques for identifying metal-corrupted areas on projection images.
Since noise is amplified and characteristic of noise varies while the image sensor signal undergoes several image processing steps, it is better to remove noise in earlier stage on imaging pipeline of ISP.Much information that can be exploited for 3-D palmprint recognition is extracted from the ultrasound volumetric images, including palm curvature and other under-skin information as the depth of the various traits.
Assuming that metals are completely opaque to X-ray, MEM reconstructs metals and other materials separately, then combines them afterward. 3D-MEM is not only more efficient but performs better than the repetition of MEM, because it identifies metals more precisely by utilizing the continuity of metals in the third dimension.Furthermore, we demonstrate that machine learning techniques are helpful in inspecting ligand diffusion landscapes and provide useful tools to examine structural changes accompanying rare events.The methods are illustrated and tested with Monte Carlo particle simulation data of plasma collisional relaxation and guiding-center transport with collisions in a magnetically confined plasma in toroidal geometry.A series of old and recent theoretical observations suggests that the quantization of gravity would be feasible, and some problems of Quantum Field Theory would go away if, somehow, the spacetime would undergo a dimensional reduction at high energy scales.There has been much interest in the dimensional properties of double-stranded DNA (dsDNA) confined to nanoscale environments as a problem of fundamental importance in both biological and technological fields.
Complex diseases are defined to be determined by multiple genetic and environmental factors alone as well as in interactions.A second layer of photoresist then can be placed onto the first photoresist layer and a second image pattern mask may be placed on the second layer of photoresist.The experimental results demonstrate the effectiveness of the proposed method for supervised, unsupervised, and semisupervised scenarios.