Shape-based Method Research Articles

Shape-based method for low-thrust transfers between periodic orbits in cislunar space

Low-thrust trajectory design in the context of the three-body problem, particularly in the vicinity of liberation points, is addressed in this paper with a focus on efficiency and accuracy. The Fourier series, previously successful in approximating near-coplanar low-thrust trajectories within two-body dynamics, is applied to the challenging landscape of the three-body problem, marked by instability and nonlinearity. This paper introduces a novel approach for constructing an initial guess trajectory, that combines coast arcs from periodic orbits and intermediate trajectory arcs from other natural dynamical structures. The resulting initial guess trajectory is instrumental in generating efficient initial estimates for the coefficients of the Fourier series. The study encompasses the analysis of homoclinic and heteroclinic transfers in both two-dimensional and three-dimensional scenarios. The approximated trajectories derived from this methodology serve as invaluable starting points for high-fidelity optimization solvers, offering promise for enhancing the precision and efficiency of low-thrust transfers in cislunar space.

Improved alpha shape-based continuum method for long-term density propagation

Improved alpha shape-based continuum method for long-term density propagation

A multi-segment alpha shape-based continuum method for long-term density propagation with bifurcation

A multi-segment alpha shape-based continuum method for long-term density propagation with bifurcation

A Shape-Based Monitoring Method for Variable Trajectories of Finishing Mill Processes

As the most critical procedure in the hot strip mill process (HSMP), the performance of the finishing mill process (FMP) has a significant influence on the key performance indicators (KPIs). Considering that the multivariate statistical process monitoring (MSPM) methods and batch alignment methods (which are implemented in a point-to-point manner) cannot effectively handle the uneven-length and multiphase characteristics of FMP data, we propose a method to monitor the shape of the variable trajectories that are closely associated with KPIs. First, the historical FMP data characterized by different grades and thickness is utilized to build monitoring models based on the Shape-Based Distance (SBD) to obtain two statistics, i.e. the SBDs and the corresponding offsets when aligned with the central trajectories. Then, by comparing the statistics of the new coming trajectories with the control limits obtained from the training set, the new coming batches can be monitored. In the end, the proposed method is tested on the real FMP dataset to validate its effectiveness.

Novel Imperfection Method for Post-Buckling Strength of C-Sectioned CFS Members

The overall behavior of cold-formed steel (CFS) members is significantly affected from existing geometric imperfections. In this work, a mode shape-based imperfection coefficient computation method is developed to investigate the effects of initial geometric imperfections on member behavior. The point clouds of CFS members are collected and used to extract imperfection distributions and coefficients. The computed coefficients are integrated into the numerical model for analysis. Finally, axial loading tests are conducted to compare the numerical and experimental results. The results obtained using mode shape-based imperfection coefficients are generally closer to the experimental results than the common method used in practice.

A pseudoequinoctial shaping method with fourier approximation for low-thrust trajectory optimization

Shape-based methods are commonly used in solving the low-thrust trajectory optimization problem. Designing a shape trajectory by maximizing a given performance index has been widely researched in recent years. The main contribution of this paper is to present a new pseudoequinoctial shaping method with parameter optimization to solve general low-thrust spacecraft rendezvous problems. The shaping method can solve the rendezvous problem with a large inclination difference between the initial and target orbits and greatly improve the performance index of the trajectory while meeting the thrust constraints. At the same time, the shape can provide a better feasible solution for solving the low-thrust trajectory optimization problem by direct methods. Another contribution is to introduce a general adjoint estimation for indirect methods. By linearizing the equation of motion near the proposed shape-based trajectory and constructing the Hamiltonian function, the initial guess of the adjoint variables can be obtained in a closed form. The general linearization formulations applicable to all coordinate systems are presented, and three numerical examples are given, in which the first example verifies the superiority of the proposed shape-based method, the second example tests the feasibility of the shape as the initial value for a direct method, and the last example compares the convergence rates of the initial adjoint variables generated by the proposed method under different coordinate systems for an indirect method.

A particle shape-based segmentation method to characterize spray dried materials by X-Ray microtomography

For accurate description of particle structure, single particle properties are required so that the properties of interest can be expressed as distributed parameters. X-Ray microtomography of the powder bed with subsequent particle separation can be used for this purpose. In this paper, a new algorithm for X-Ray microtomography images of spray dried particles was introduced since standard methods tend to fail if the particle size distribution is broad. The algorithm is based on 2D shape classification and subsequent 3D reconstitution of the particle using only a shape classifier as free parameter. The proposed algorithm was validated successfully. Using the algorithm, single particle porosities were obtained, which ranged from 0 to 70%. Prerequisites for the application of the algorithm are that a shape classifier can be set and that the 3D shape is regular.

Robust shape-based template matching algorithm for target localization under SEM.

A novel acceleration algorithm for geometric template matching is proposed based on the Cauchy-Schwartz inequality (C-S inequality) in this paper. The proposed approach is validated under a scanning electron microscope (SEM), and its effectiveness is demonstrated. In this approach, the object shape features are represented as column vectors with complex elements. Then, a threshold is determined to exclude the sliding windows without any matched objects. Finally, surface fitting is employed to obtain the subpixel positions of the targets, and least squares adjustment is utilized to fine-tune the obtained results. The experimental results demonstrate that the proposed method can significantly reduce the matching time by 59% - 96% compared with the traditional shape-based method. Furthermore, the strong robustness and high accuracy are verified under different disturbances. Additionally, the approach is shown to be robust and accurate under different types of disturbances, thus confirming its suitability for real-time targets tracking on SEM with high accuracy.

Shape-based proximity effect correction method for throughput, fidelity, and contrast enhancement of electron-beam writer

Conventional shape-based proximity effect correction (PEC) methods can only improve pattern fidelity and present a risk to correction effectiveness under severe resist-contour distortions for electron-beam writers. Herein, a shape-based PEC method for effectively improving both the pattern fidelity and energy slope without the risk in realizing high throughput, fidelity, and contrast is presented. An extra-framed pattern added to the target pattern is optimized to achieve better trade-off between contrast improvement and writing-time reduction. The proposed method demonstrated significant improvements in lithographic performance compared with the conventional and dose-based PEC methods for high-numerical-aperture extreme-ultraviolet mask and aggressive patterns.

Risk-Based Constraints for the Optimal Operation of an Energy Community

This paper formulates an energy community’s centralized optimal bidding and scheduling problem as a time-series scenario-driven stochastic optimization model, building on real-life measurement data. In the presented model, a surrogate battery storage system with uncertain state-of-charge (SoC) bounds approximates the portfolio’s aggregated flexibility. First, it is emphasized in a stylized analysis that risk-based energy constraints are highly beneficial (compared to chance-constraints) in coordinating distributed assets with unknown costs of constraint violation, as they limit both violation magnitude and probability. The presented research extends state-of-the-art models by implementing a worst-case conditional value at risk (WCVaR) based constraint for the storage SoC bounds. Then, an extensive numerical comparison is conducted to analyze the trade-off between out-of-sample violations and expected objective values, revealing that the proposed WCVaR based constraint shields significantly better against extreme out-of-sample outcomes than the conditional value at risk based equivalent. To bypass the non-trivial task of capturing the underlying time and asset-dependent uncertain processes, real-life measurement data is directly leveraged for both imbalance market uncertainty and load forecast errors. For this purpose, a shape-based clustering method is implemented to capture the input scenarios’ temporal characteristics.

Improved Monte Carlo Tree Search-based approach to low-thrust multiple gravity-assist trajectory design

In the preliminary design of low-thrust trajectories with multiple gravity-assist phases, the selection of the celestial bodies to be considered and the sequence of optimal maneuvers have a significant impact on the overall mission performance. This aspect makes the preliminary transfer trajectory analysis a very complex task. This Short Communication presents a novel method to design heliocentric multiple gravity-assist transfer trajectories for a spacecraft with a low-thrust propulsion system, where the total velocity variation is minimized. In this context, a Bézier shape-based method is used to describe the generic arc of a propelled trajectory, while an extension of the Monte Carlo Tree Search algorithm is used for a rapid analysis of the gravity-assist maneuver sequence. In particular, the proposed approach effectively solves the problem of selecting a suitable balance parameter in the Monte Carlo Tree Search-based routines, which makes the method especially useful in a preliminary mission phase. The effectiveness of the proposed approach is shown by simulating an interplanetary transfer towards the outer regions of the Solar System.

Fast cooperative obstacle-avoidance path planning for multiple space manipulators

For a space manipulator with multiple links, joints, and degrees of freedom, it is necessary to comprehensively consider the motion state of each link to make the manipulator reach the target position. In this regard, this study proposes a fast cooperative obstacle-avoidance path planning method for multiple space manipulators. The proposed method can quickly determine the obstacle-avoidance path of each link in multiple space manipulators with multiple degrees of freedom. In this method, first, the geometric relationship between the space manipulator and the target is used to constrain the range of motion of each link in the space manipulator. Thereafter, the Bezier shape-based (SB) method is used to generate the obstacle-avoidance motion path of each of these links. By comparing the results of the Bezier SB method, the finite Fourier series (FFS) SB method, and the Gauss pseudospectral method (GPM), the effectiveness and superiority of the proposed method are verified. The simulation results show that the Bezier SB method yields better results with shorter computation time than the FFS SB method. The results obtained using the Bezier SB method are employed as the initial values for the GPM. And the computation time for the Bezier SB method is less than 2.5% that of the GPM, while yielding results with a performance index difference of approximately 2%. Thus, the proposed method is proved to be considerably effective for quickly determining the cooperative obstacle-avoidance path of multiple manipulators in complex on-orbit service tasks.

Texture-less surface reconstruction using shape-based image augmentation

The development of intelligent Robot-Assisted Minimally Invasive Surgery demands geometric reconstruction from endoscopic images. However, images of human tissue surfaces are commonly texture-less. Obtaining the dense depth map of a texture-less scene is very difficult because traditional feature-based 3D reconstruction methods cannot detect enough features to build dense correspondences for depth computation. Given this problem, this study proposes a novel reconstruction method based on our shape-based image augmentation method. The main contribution of this method is the provision of a novel means to resolve the texture-less problem mainly on the input data level. In our method, we first calculate two shape gradient maps using Shape-From-Shading (SFS) method and we build Fast Point Feature Histogram (FPFH) 3D descriptor map according to the shape. Second, a series of augmented images can be computed by combining shape gradient maps, FPFH map, and the original image with different weights. Finally, we detect features on the new augmented images. Based on feature calculated sparse depth information and SFS calculated dense shape information, we further integrate a rectified dense depth map. Experiments show that our method can reconstruct texture-less surfaces with good accuracy.

Taxonomic classification of seabird long bones using 3D shape: A method with wider potential in zooarchaeology

Identifications from isolated bones using molecular methods are not always possible (e.g. fossils and older sub-fossils), and specialist taxonomic expertise is not always available. Shape-based, geometric morphometric methods for identifying taxa from a single bone can provide a potential solution for faunal studies requiring taxonomic information about isolated bones. We present a generalisable method for taxonomic classification using 3D shape analyses combined with partial least squares discriminant analysis (PLSDA). Our classification protocol uses both well-established landmark-based techniques and novel landmark-free (i.e. pseudolandmark-based) shape analysis methods. Landmark-free methods can improve the automation of the classification method. We demonstrate with three case studies that 3D shape-based PLSDA can accurately predict taxonomic identities for seabird long bones to at least family-level. Landmark-based PLSDA assigned femora from penguins and tubenosed birds to the correct order and family with 100% accuracy, sensitivity and specificity. Pseudolandmark-based PLSDA assigned humeri from penguins and tubenosed birds to the correct family with 100% accuracy, sensitivity and specificity. Our 3D shape-based classification method could reliably contribute to the identification of bone remains when only isolated or typically nondiagnostic bones (i.e. elements with comparatively little variation in discrete character states or measurement proportions when comparing between closely-related taxa) are available, and when molecular methods are not possible or feasible. We provide a framework for applying this method to 1) much larger datasets which may allow finer-level classifications (genus or species), and 2) groups beyond seabirds.

Brain tumor visualization for magnetic resonance images using modified shape-based interpolation method

<span>3D visualization plays an essential role in medical diagnosis and setting treatment plans especially for brain cancer. There have been many attempts for brain tumor reconstruction and visualization using various techniques. However, this problem is still considered unsolved as more accurate results are needed in this critical field. In this paper, a sequence of 2D slices of brain magnetic resonance Images was used to reconstruct a 3D model for the brain tumor. The images were automatically segmented using a wavelet multi-resolution expectation maximization algorithm. Then, the inter-slice gaps were interpolated using the proposed modified shape-based interpolation method. The method involves three main steps; transferring the binary tumor images to distance images using a suitable distance function, interpolating the distance images using cubic spline interpolation and thresholding the interpolated values to get the reconstructed slices. The final tumor is then visualized as a 3D isosurface. We evaluated the proposed method by removing an original slice from the input images and interpolating it, the results outperform the original shape-based interpolation method by an average of 3% reaching 99% of accuracy for some slice images.</span>

Correlation between corneal dynamic responses and keratoconus topographic parameters.

ObjectiveTo investigate the correlation between corneal biomechanical properties and topographic parameters using machine learning networks for automatic severity diagnosis and reference benchmark construction.MethodsThis was a retrospective study involving 31 eyes from 31 patients with keratonus. Two clustering approaches were used (i.e., shape-based and feature-based). The shape-based method used a keratoconus benchmark validated for indicating the severity of keratoconus. The feature-based method extracted imperative features for clustering analysis.ResultsThere were strong correlations between the symmetric modes and the keratoconus severity and between the asymmetric modes and the location of the weak centroid. The Pearson product-moment correlation coefficient (PPMC) between the symmetric mode and normality was 0.92 and between the asymmetric mode and the weak centroid value was 0.75.ConclusionThis study confirmed that there is a relationship between the keratoconus signs obtained from topography and the corneal dynamic behaviour captured by the Corvis ST device. Further studies are required to gather more patient data to establish a more extensive database for validation.

Analytical solution to logarithmic spiral trajectories with circumferential thrust and mission applications

This study made use of a shape-based method to analyze the orbital dynamics of a spacecraft subject to a continuous propulsive acceleration acting along the circumferential direction. Under the assumption of a logarithmic spiral trajectory, an exact solution to the equations of motion exists, which allows the spacecraft state variables and flight time to be expressed as a function of the angular coordinate. There is also a case characterized by specific initial conditions in which the time evolution of the state variables may be analytically determined. In this context, the presented solution is used to analyze circle-to-circle trajectories, where the combination of two impulsive maneuvers and a logarithmic spiral path are used to accomplish the transfer. The determined results are then applied to the achievement of the Earth—Mars and the Earth—Venus transfers using actual data from a recent thruster developed by NASA.

An Optimal Sensor Layout Using the Frequency Response Function Data within a Wide Range of Frequencies.

This study presents iterative optimal sensor placement (OSP) techniques using the modal assurance criterion (MAC) and the effective independence (EI) algorithm. The algorithms use the proper orthogonal mode (POM) extracted from the frequency response functions (FRFs) of dynamic systems within a wide range of frequencies. The FRF-based OSP method proposed in this study has the merit of reflecting dynamic characteristics, unlike the mode shape-based method. Evaluating the MAC values and the EI indices at each iteration, the DOFs of low contribution to the objective function of candidate sensor DOFs are deleted from master DOFs and moved to slave DOFs. This process is repeated until the sensor number corresponds with the master DOFs. The validity of the proposed methods is illustrated in an example, the sensor layouts by the proposed methods are compared, and the layout inconsistency between the MAC and the EI techniques is analyzed.

Fast costate estimation for indirect trajectory optimization using Bezier-curve-based shaping approach

In this study, a fast costate estimation method derived from the Bezier-curve-based shaping approach is proposed for indirect low-thrust transfer trajectory optimization. The trajectory is designed rapidly by means of the shape-based method, which can be discretized on the Gauss points and substituted into the discrete first-order optimal condition equation for costate estimation. The estimated costate at the starting point is substituted into the indirect method to solve the optimal control problem. The costate estimation performance for two interplanetary rendezvous missions from Earth to Mars and Earth to Dionysus is compared via random initialization and Newton's iteration method. The initial guesses for the transfer time are given by the Hohmann transfer and the Lambert two-pulse traversal search. The results show that the Lambert traversal search can provide a more accurate launch time estimation in the Bezier-curve-based shaping approach, which can estimate the costate for indirect trajectory optimization in an order of magnitude less time than that required by random initialization.

Discovery of Small-Molecule VapC1 Nuclease Inhibitors by Virtual Screening and Scaffold Hopping from an Atomic Structure Revealing Protein-Protein Interactions with a Native VapB1 Inhibitor.

Nontypeable Haemophilus influenzae (NTHi) are clinically important Gram-negative bacteria that are responsible for various human mucosal diseases, including otitis media (OM). Recurrent OM caused by NTHi is common, and infections that recur less than 2 weeks following antimicrobial therapy are largely attributable to the recurrence of the same strain of bacteria. Toxin-antitoxin (TA) modules encoded by bacteria enable rapid responses to environmental stresses and are thought to facilitate growth arrest, persistence, and tolerance to antibiotics. The vapBC-1 locus of NTHi encodes a type II TA system, comprising the ribonuclease toxin VapC1 and its cognate antitoxin VapB1. The activity of VapC1 has been linked to the survival of NTHi during antibiotic treatment both in vivo and ex vivo. Therefore, inhibitors of VapC1 might serve as adjuvants to antibiotics, preventing NTHi from entering growth arrest and surviving; however, none have been reported to date. A truncated VapB1 peptide from a crystal structure of the VapBC-1 complex was used to generate pharmacophore queries to facilitate a scaffold hopping approach for the identification of small-molecule VapC1 inhibitors. The National Center for Advancing Translational Sciences small-molecule library was virtually screened using the shape-based method rapid overlay of chemical structures (ROCS), and the top-ranking hits were docked into the VapB1 binding pocket of VapC1. Two hundred virtual screening hits with the best docking scores were selected and tested in a biochemical VapC1 activity assay, which confirmed eight compounds as VapC1 inhibitors. An additional 60 compounds were selected with structural similarities to the confirmed VapC1 inhibitors, of which 20 inhibited VapC1 activity. Intracellular target engagement of five inhibitors was indicated by the destabilization of VapC1 within bacterial cells from a cellular thermal shift assay; however, no impact on bacterial growth was observed. Thus, this virtual screening and scaffold hopping approach enabled the discovery of VapC1 ribonuclease inhibitors that might serve as starting points for preclinical development.