Warp Parameters Research Articles

Method for Prediction of Motion Based on Recursive Least Squares Method with Time Warp Parameter and its Application to Physical Therapy

Method for Prediction of Motion Based on Recursive Least Squares Method with Time Warp Parameter and its Application to Physical Therapy

FabricNET: A Microscopic Image Dataset of Woven Fabrics for Predicting Texture and Weaving Parameters through Machine Learning

This research presents an approach aimed at enhancing texture recognition and weaving parameter estimation in the textile industry to align with sustainability goals and improve product quality. By utilizing low-cost handheld microscopy and machine learning, this method offers the potential for more precise production outcomes. In this study, textile images were manually labeled for texture, specific mass, weft, and warp parameters, followed by the extraction of various texture features, resulting in a comprehensive dataset comprising four hundred and fifty-eight inputs and four outputs. Prominent machine learning algorithms, including XGBoost, RF, and MLP, were applied, resulting in noteworthy achievements. Specifically, XGBoost demonstrated an impressive texture classification accuracy of 0.987, while RF yielded the lowest MAE (5.121 g/cm) in specific mass prediction. Additionally, weft and warp estimations displayed superior accuracy compared to manual measurements. This research emphasizes the crucial role of AI in improving efficiency and sustainability within the textile industry, potentially reducing resource wastage, enhancing worker safety, and increasing productivity. These advancements hold the promise of significant positive environmental and social impacts, marking a substantial step forward in the industry’s pursuit of its objectives.

Kinematics analysis of the transient Milky Way warp using RGB stars from Gaia DR2

The perturbations to the Milky Way cause the disk to have bending or breathing wave, flare, and warp. Both spatial analyses from stellar and gas show the Milky Way warp can be approached with sinusoidal function to the Galactocentric longitude. In this research, we aim to find evidence of the transient Milky Way warp using kinematics data of the Red Giant Branch (RGB) stars from Gaia Data Release 2. We only use RGB stars with positive parallaxes and small parallax uncertainties where ϖ > 0 and ϖ/σϖ > 5, respectively. Using the linear warp model, we find the Milky Way warp starts on Rw = 10.72 kpc, with the amplitude (γw ) of 0.39 and the Line of Node lies on ϕw = −5.26°. Assumed the warp is a static long-lived feature on kinematics distribution, where all of the warp parameters are constant by the time, the observed vertical velocity (Vz ) is less than the expected one. The maximum Vz is not exceeded to 12.5 km/s rather 20 km/s derived from the proposed model. It infers that the warp drive on the Milky Way is a transient feature. One of the possible reasons is the recent interaction with satellite galaxies in perturbing the outer disk of the Milky Way.

The time traveler\u2019s guide to the quantization of zero modes

We study the relationship between the quantization of a massless scalar field on the two-dimensional Einstein cylinder and in a spacetime with a time machine. We find that the latter picks out a unique prescription for the state of the zero mode in the Einstein cylinder. We show how this choice arises from the computation of the vacuum Wightman function and the vacuum renormalized stress-energy tensor in the time-machine geometry. Finally, we relate the previously proposed regularization of the zero mode state as a squeezed state with the time-machine warp parameter, thus demonstrating that the quantization in the latter regularizes the quantization in an Einstein cylinder.

A Case against a Significant Detection of Precession in the Galactic Warp

Abstract Recent studies of warp kinematics using Gaia DR2 data have produced detections of warp precession for the first time, which greatly exceeds theoretical predictions of models. However, this detection assumes a warp model derived for a young population (few tens of megayears) to fit velocities of an average older stellar population of the thin disk (several gigayears) in Gaia-DR2 observations, which may lead to unaccounted systematic errors. Here, we recalculate the warp precession with the same approach and Gaia DR2 kinematic data, but using different warp parameters based on the fit of star counts of the Gaia DR2 sample, which has a much lower warp amplitude than the young population. When we take into account this variation of the warp amplitude with the age of the population, we find that there is no need for precession. We find the value of warp precession β = 4 − 4 + 6 km s−1 kpc−1, which does not exclude nonprecessing warp.

Investigation of the mechanical and forming behaviour of 3D warp interlock carbon woven fabrics for complex shape of composite material

Composite materials which are reinforced with 3D warp interlock fabrics have outstanding mechanical properties such as higher delamination resistance, ballistic damage resistance and impact damage tolerance by means of their improved structural properties. Textile reinforcements are exposed to large deformations in the production stage of composite materials which have complex shape. Although good formability properties of 3D warp interlock fabrics in forming process were already proven by recent studies, further information is needed to elucidate forming behaviours of multi-layer fabrics which is produced with high stiffness yarns like carbon. In this study, 3D warp interlock carbon fabrics were produced on a prototype weaving loom and the same carbon yarn was used in two fabric directions with equal number of yarn densities. Fabrics were differentiated with regard to the presence of stuffer warp yarn, weave pattern and parameters of binding warp yarn which are angle and depth. Therefore, the effect of fabric architecture on the mechanical and formability properties of 3D warp interlock carbon fabrics could be clarified. Three different breaking behaviours of fabrics were detected and they were correlated with crimp percentages of yarn groups. In addition, the bending and shear deformations were analysed in view of parameters of fabric architectures. Two distinct forming behaviours of fabrics were determined according to the distribution of deformation areas on fabrics. Moreover, the optimal structure was identified for forming process considering the fabric architecture.

Transformation guided representation GAN for pose invariant face recognition

Face recognition is an important topic in the field of computer vision and has been a vital biometric technique for identity authentication. It is widely used in areas such as public security, military, and daily life. However, face recognition is inherently a challenging problem due to variations in poses, facial expressions, age, and occlusion. In this work, we propose a generative adversarial network (GAN) architecture that disentangles identity and pose variations to learn generative and discriminative representations for pose-invariant face recognition. We use an iterative warping scheme that achieves better results than with the use of a single generator. The features from the encoder are considered pose-invariant features for face recognition, and evaluations on databases demonstrate the usefulness of this approach over prior methods. For example, we report 97.0% (+ 12.7%) and 90.5% (+ 8.4%) accuracy on the Feret and Caspeal datasets compared to 78.2% achieved by the best method without warping. In particular, there are two notable novelties. First, the disentangled architecture GAN (D-GAN) performs frontal face synthesis via an encoder-decoder structure in the generator with the pose variations provided to the decoder and discriminator. Second, we utilize the generator encoder as a spatial transformer network that seeks realistic image synthesis in the geometric warp parameter space.

Hotelling trace criterion as a figure of merit for the optimization of chromatogram alignment

We present a methodology for optimization of chromatogram alignment using a class separability measure called the Hotelling trace criterion (HTC). This metric is a multi‐class distance measure that accounts for within‐class and between‐class variation. We chose the correlation optimized warping algorithm as our alignment method and used the HTC to judge the effectiveness of the alignment based on algorithm parameters called segment length and max warp.Biodiesel feedstock samples representing classes of soy, canola, tallow, waste grease, and hybrid were used in our experiments. Fatty acid methyl esters in each biodiesel were separated using gas chromatography‐mass spectroscopy. The entire data set was baseline corrected, aligned, normalized, and mean‐centered prior to principal components (PCs) analysis. The aligned, baseline corrected data sets were used to compute a figure of merit called warping effect, while the PC‐transformed data sets were used to evaluate the HTC. The segment length and max warp parameters that maximized the warping effect and/or HTC were then determined. Scores plots of pairs of PCs, along with 95% confidence ellipses, were created and analyzed.The results demonstrated that the parameters derived from maximizing the HTC more effectively aligned the data, as evidenced by better clustering of the biodiesels in the scores plots. This behavior was robust to the number of PCs used in the computation of the HTC. We conclude that the HTC is an objective measure of alignment quality that allows for optimal class separability and can be applied to optimize other methods of chromatogram alignment. Copyright © 2015 John Wiley & Sons, Ltd.

Characterizing the Galactic warp with Gaia – I. The tilted ring model with a twist

We explore the possibility of detecting and characterizing the warp of the stellar disc of our Galaxy using synthetic Gaia data. The availability of proper motions and, for the brightest stars radial velocities, adds a new dimension to this study. A family of Great Circle Cell Counts (GC3) methods is used. They are ideally suited to find the tilt and twist of a collection of rings, which allow us to detect and measure the warp parameters. To test them, we use random realizations of test particles which evolve in a realistic Galactic potential warped adiabatically to various final configurations. In some cases a twist is introduced additionally. The Gaia selection function, its errors model and a realistic 3D extinction map are applied to mimic three tracer populations: OB, A and Red Clump stars. We show how the use of kinematics improves the accuracy in the recovery of the warp parameters. The OB stars are demonstrated to be the best tracers determining the tilt angle with accuracy better than $\sim0.5$ up to Galactocentric distance of $\sim16$ kpc. Using data with good astrometric quality, the same accuracy is obtained for A type stars up to $\sim13$ kpc and for Red Clump up to the expected stellar cut-off. Using OB stars the twist angle is recovered to within $< 3^\circ$ for all distances.

On the characterization of the Galactic warp in the Gaia era

We explore the possibility of detecting and characterising the warp of the stellar disc of our Galaxy using the synthetic Gaia data and the UCAC4 proper motion catalogue. We develop a new kinematic model for the galactic warp. We generate random realisations of test particles which evolve in a realistic Galactic potential warped adiabatically to various final configurations. The Gaia selection function, its errors model and a realistic 3D extinction map are applied to mimic three tracer populations: OB, A and Red Clump stars. A family of Great Circle Cell Counts (GC3) methods is used. They are ideally suited to find the tilt and twist of a collection of rings, which allow us to detect and measure the warp parameters. Moreover, We look for the kinematic signature of the warp in the μb proper motions of stars as a function of galactic longitude. Using the UCAC4 proper motions, we do not obtain a similar trend as the one we expect from our warp model. We explore a possible source of this discrepancy in terms of systematics caused by a residual spin of the Hipparcos celestial reference frame (HCRF) with respect to the extra-galactic inertial one.

New boundary conditions for AdS3

New chiral boundary conditions are found for quantum gravity with matter on AdS3. The associated asymptotic symmetry group is generated by a single right-moving U(1) Kac-Moody-Virasoro algebra with c_R = 3l/2G. The Kac-Moody zero mode generates global left-moving translations and equals, for a BTZ black hole, the sum of the total mass and spin. The level is positive about the global vacuum and negative in the black hole sector, corresponding to ergosphere formation. Realizations arising in Chern-Simons gravity and string theory are analyzed. The new boundary conditions are shown to naturally arise for warped AdS3 in the limit that the warp parameter is taken to zero.

REGION BASED MEDICAL IMAGE REGISTRATION APPROACH USING A MODIFIED ARTIFICIAL IMMUNE SYSTEM

A high accuracy medical image registration is needed to achieve an efficient medical diagnosis and computer aided surgeries, so that a novel region based medical image registration approach is presented in this paper. This approach consists of four sequential steps, image segmentation, point correspondence using a modified artificial immune system, point selection and finally LMS technique is used to estimate the warp parameters. The proposed approach provides a high accuracy and it doesn’t require any additional treatment or feature extraction as some other methods do. To demonstrate the effectiveness of the proposed approach it tested for many image pairs and it is compared with many registration algorithms such aspoint-based image registration using an artificial immune system (AIS),ICP and RANSAC algorithms.

Transfusive image manipulation

We present a method for consistent automatic transfer of edits applied to one image to many other images of the same object or scene. By introducing novel, content-adaptive weight functions we enhance the non-rigid alignment framework of Lucas-Kanade to robustly handle changes of view point, illumination and non-rigid deformations of the subjects. Our weight functions are content-aware and possess high-order smoothness, enabling to define high-quality image warping with a low number of parameters using spatially-varying weighted combinations of affine deformations. Optimizing the warp parameters leads to subpixel-accurate alignment while maintaining computation efficiency. Our method allows users to perform precise, localized edits such as simultaneous painting on multiple images in real-time, relieving them from tedious and repetitive manual reapplication to each individual image.

Feature-Based Deformable Surface Detection with Self-Occlusion Reasoning

This paper presents a method for detecting a textured deformed surface in an image. It uses (wide-baseline) point matches between a template and the input image. The main contribution of the paper is twofold. First, we propose a robust method based on local surface smoothness capable of discarding outliers from the set of point matches. Our method handles large proportions of outliers (beyond 70% with less than 15% of false positives) even when the surface self-occludes. Second, we propose a method to estimate a self-occlusion resistant warp from point matches. Our method allows us to realistically retexture the input image. A pixel-based (direct) registration approach is also proposed. Bootstrapped by our robust point-based method, it finely tunes the warp parameters using the value (intensity or color) of all the visible surface pixels. The proposed framework was tested with simulated and real data. Convincing results are shown for the detection and retexturing of deformed surfaces in challenging images.

Near-infrared and optical observations of galactic warps: a common, unexplained feature of most discs

<i>Context. <i/>Warps occurring in galactic discs have been studied extensively in HI and in the optical, but rarely in the near-infrared (NIR) bands that trace the older stellar populations.<i>Aims. <i/>We provide NIR data of nearby edge-on galaxies, combined with optical observations, for direct comparison of the properties of galactic warps as a function of wavelength, and calculate warp curves for each galaxy and obtain the characteristic warp parameters. We discuss these properties as possible constraints to the different mechanisms that have been proposed for the development and persistence of galactic warps.<i>Methods. <i/>We observed 20 galaxies that were selected from a statistically complete diameter-limited subsample of edge-on disc galaxies. We used the Cerro Tololo Infrared Imager (CIRIM) at the CTIO 1.5 m Ritchey-Chretien telescope to acquire the NIR data. We used the 1.54 m Danish and 0.92 m Dutch telescopes at the European Southern Observatory's La Silla site for our optical observations.<i>Results. <i/>Our results show that 13 of our 20 sample galaxies are warped, with the warp more pronounced in the optical than at NIR wavelengths. In the remaining seven galaxies, no warp is apparent within the limitations of our automated detection method. The transition between the unperturbed inner disc and the outer, warped region is rather abrupt. S0 galaxies exhibit very small or no warps. The magnetic model remains one of a number of interesting formation scenarios.

Casimir energy of the universe and new regularization of higher dimensional quantum field theories

Casimir energy is calculated for the 5D electromagnetism and 5D scalar theory in the warped geometry. It is compared with the flat case. A new regularization, called sphere lattice regularization, is taken. In the integration over the 5D space, we introduce two boundary curves (IR-surface and UV-surface) based on the minimal area principle. It is a direct realization of the geometrical approach to the renormalization group. The regularized configuration is closed-string like. We do not take the KK-expansion approach. Instead, the position/momentum propagator is exploited, combined with the heat-kernel method. All expressions are closed-form (not KK-expanded form). The generalized P/M propagators are introduced. We numerically evaluate Λ(4D UV-cutoff), ω(5D bulk curvature, warp parameter) and T(extra space IR parameter) dependence of the Casimir energy. We present two new ideas in order to define the 5D QFT: 1) the summation (integral) region over the 5D space is restricted by two minimal surfaces (IR-surface, UV-surface); or 2) we introduce a weight function and require the dominant contribution, in the summation, is given by the minimal surface. Based on these, 5D Casimir energy is finitely obtained after the proper renormalization procedure. The warp parameter ω suffers from the renormalization effect. The IR parameter T does not. We examine the meaning of the weight function and finally reach a new definition of the Casimir energy where the 4D momenta (or coordinates) are quantized with the extra coordinate as the Euclidean time (inverse temperature). We examine the cosmological constant problem and present an answer at the end. Dirac's large number naturally appears.

CASIMIR ENERGY OF AdS5 ELECTROMAGNETISM AND COSMOLOGICAL CONSTANT PROBLEM

Casimir energy is calculated for the 5D electromagnetism in the warped geometry. It is compared with the flat case(arXiv:0801.3064). A new regularization, called sphere lattice regularization, is taken. It is based on the minimal area principle and is a direct realization of the geometrical approach to the renormalization group. The properly regularized form of Casimir energy, is expressed in a closed form. We numerically evaluate Λ(4D UV-cutoff), ω(5D bulk curvature, warp parameter) and T(extra space IR parameter) dependence of the Casimir energy. The warp parameter ω suffers from the renormalization effect. We examine the meaning of the weight function and finally reach a new definition of the Casimir energy where the 4D momenta( or coordinates) are quantized with the extra coordinate as the Euclidean time. We comment on the cosmological term at the end.

Generalizing Inverse Compositional and ESM Image Alignment

Inverse compositional (IC) image alignment (Baker and Matthews in Int. J. Comput. Vis. 56(3):221---255, 2004) uses the symmetry between the roles of the fixed and moving images for faster processing. However, it requires implementation of compositional optimizer update steps. The IC approach can be viewed as an efficient way of computing the similarity measure derivative relative to the fixed image warp parameters. Since the mapping between the fixed and moving warp parameters is continuous and differentiable, this derivative can be converted into the moving warp space using the chain rule. This avoids the need for compositional update steps. Our generalization also allows the efficient second order method (ESM) (Malis in Proceedings of the 2004 IEEE International Conference on Robotics and Automation (ICRA04), pp. 1843---1848, 2004; Benhimane and Malis in IEEE/RSJ International Conference on Intelligent Robots and Systems, 2004; Malis and Benhimane in Robot. Auton. Syst. 52(1):39---52, 2005) to be applied to general parameterizations of the transformation. Experiments using multiple similarity measures and optimizers show that our generalized IC method equals or exceeds the performance of the original IC approach. The generalized ESM approach is more reliable than the classic approach as it increases the capture radius of the optimization.

Kaluza–Klein towers in warped spaces with metric singularities

The version of the warp model that we proposed to explain the mass scale hierarchy has been extended by the introduction of one or more singularities in the metric. We restricted ourselves to a real massless scalar field supposed to propagate in a five-dimensional bulk with the extra dimension being compactified on a strip or on a circle. With the same emphasis on the hermiticity and commutativity properties of the Kaluza–Klein operators, we have established all the allowed boundary conditions to be imposed on the fields. From them, for given positions of the singularities, one can deduce either mass eigenvalues building up a Kaluza–Klein tower, or a tachyon, or a zero mass state. Assuming the Planck mass to be the high mass scale and by a choice, unique for all boundary conditions, of the major warp parameters, the low lying mass eigenvalues are of the order of the TeV, in this way explaining the mass scale hierarchy. In our model, the physical masses are related to the Kaluza–Klein eigenvalues, depending on the location of the physical brane which is an arbitrary parameter of the model. Illustrative numerical calculations are given to visualize the structure of Kaluza–Klein mass eigenvalue towers. Observation at high energy colliders like LHC of a mass tower with its characteristic structure would be the fingerprint of the model.

Parametric Image Alignment Using Enhanced Correlation Coefficient Maximization

In this work we propose the use of a modified version of the correlation coefficient as a performance criterion for the image alignment problem. The proposed modification has the desirable characteristic of being invariant with respect to photometric distortions. Since the resulting similarity measure is a nonlinear function of the warp parameters, we develop two iterative schemes for its maximization, one based on the forward additive approach and the second on the inverse compositional method. As it is customary in iterative optimization, in each iteration, the nonlinear objective function is approximated by an alternative expression for which the corresponding optimization is simple. In our case we propose an efficient approximation that leads to a closed-form solution (per iteration) which is of low computational complexity, the latter property being particularly strong in our inverse version. The proposed schemes are tested against the Forward Additive Lucas-Kanade and the Simultaneous Inverse Compositional (SIC) algorithm through simulations. Under noisy conditions and photometric distortions, our forward version achieves more accurate alignments and exhibits faster convergence whereas our inverse version has similar performance as the SIC algorithm but at a lower computational complexity.