Entire Shape Research Articles

Design and Analysis of Automatic Pruning Machine Electrical Control System for Hedgerows on Highway

It is difficult for workers to achieve the pruning effect when pruning the fence with hedgerow on the highway, which is heavy in workload and high in costs. Meanwhile, workers are not safe when working on a high-speed road. To solve these problems, a full-automatic pruning machine and its control system are designed. The machine kinematics and work processes are analysed. Then the control system is designed and the actual work is simulated under the monitoring environment for system debugging. Results show that the machine is universal and multifunctional. The equipment has a high degree of automation and low work intensity. The machine does not require workers to have the high operating skills, and has low normative requirement for the planting method. The adaptability is strong, which means that the equipment could cut not only the plan but also the entire geometrical shape, and it can be used normally in the complicated environment. The machine is especially suitable to prune hedgerows on a highway with good safety performance.

Calcaneal shape variation in humans, nonhuman primates, and early hominins

The foot has played a prominent role in evaluating early hominin locomotion. The calcaneus, in particular, plays an important role in weight-bearing. Although the calcanei of early hominins have been previously scrutinized, a three-dimensional analysis of the entire calcaneal shape has not been conducted. Here, we investigate the relationship between external calcaneal shape and locomotion in modern Homo sapiens (n = 130), Gorilla (n = 86), Pan (n = 112), Pongo (n = 31), Papio (n = 28), and hylobatids (Hylobates, Symphalangus; n = 32). We use these results to place the calcanei attributed to Australopithecus sediba, A. africanus, A. afarensis, H. naledi, and Homo habilis/Paranthropus boisei into a locomotor context. Calcanei were scanned using either surface scanning or micro-CT and their external shape analyzed using a three-dimensional geometric morphometric sliding semilandmark analysis. Blomberg's K statistic was used to estimate phylogenetic signal in the shape data. Shape variation was summarized using a principal components analysis. Procrustes distances between all taxa as well as distances between each fossil and the average of each taxon were calculated. Blomberg's K statistic was small (K = 0.1651), indicating weak phylogenetic effects, suggesting variation is driven by factors other than phylogeny (e.g., locomotion or body size). Modern humans have a large calcaneus relative to body size and display a uniquely convex cuboid facet, facilitating a rigid midfoot for bipedalism. More arboreal great apes display relatively deeper cuboid facet pivot regions for increased midfoot mobility. Australopithecus afarensis demonstrates the most human-like calcaneus, consistent with obligate bipedalism. Homo naledi is primarily modern human-like, but with some intermediate traits, suggesting a different form of bipedalism than modern humans. Australopithecus africanus, A. sediba, and H. habilis/P. boisei calcanei all possess unique combinations of human and nonhuman ape-like morphologies, suggesting a combination of bipedal and arboreal behaviors.

Magnetic Reconnection in a Sheared Magnetic Flux Tube: Slippage Versus Tearing

AbstractThe process of magnetic reconnection in a flux tube can occur in a time‐stationary fashion as slippage reconnection or in a time‐dependent manner based on, for example, the tearing instability. However, it is not well known under which conditions a system can sustain slippage reconnection. Likewise, it is unclear whether systems can exhibit slippage reconnection and time‐dependent reconnection simultaneously. In order to investigate these questions, we employ a set of 3D magnetohydrodynamic simulation. Using these simulations, we model a twisted flux tube with a spatially localized resistive region in the center of the simulation box, and an applied driver on one end plane of the simulation box. As a result, the Poynting flux injected at the boundary propagates to the resistive region and dissipates there. If the driver is nearly circular, we find a predominance of slippage reconnection, which decouples the applied driver entirely from one half of the flux tube. Second, a tearing‐like instability occurs with slippage reconnection in the resistive region when the resistivity is strong enough and the cross section of the flux tube, as defined by the shape of the applied velocity perturbation, is elliptical enough. In this case we find the surprising feature that magnetic field perturbation generated by the tearing‐like instability radiates away from the resistive region to influence the entire flux tube shape.

Augmented Reality Application Development for Elementary School Purpose

The world is being hit by a pandemic due to the COVID-19 virus outbreak. The changes brought by this virus are huge, one of which is school activities that are transformed into online learning. Online learning causes students to not do their own classroom learning. This causes students to become un familiar with their school properly, such as the layout of classrooms and school facilities. By using Augmented Reality the problem can be solved. Augmented Reality (AR) is the merging of real and virtual objects in a real environment with interactive results and presented in real time. AR can be used to modeling the entire shape of the school, making it easier for users to get information about the building from the school instead of walking manually. Users only need to install the app on their smarthphone and scan the specified QR code in order to be able to bring up the building object along with the information. The result of this research is an AR application which can provide information about the rooms and buildings at SDN 1 Padangsambian.

Decision tree pairwise metric learning against adversarial attacks

Distance Metric Learning has been used or paired with SoftMax Cross-Entropy loss to increase the discriminative power of deep learning classifiers against adversarial attacks. Most distance metric learning-based methods for adversarial detection adopt the standard Mahalanobis distance which only encodes the relative position information and therefore cannot capture the entire shape of complex data. In this research, we propose an alternative metric learning approach for adversarial sample classification. This approach integrates relative information as well as absolute pairwise information into a differentiable decision tree representation to guarantee a more robust classifier. We term this metric learning approach as differentiable decision tree pairwise metric learning (DTML). We demonstrate that DTML is more robust even under strong adversarial untargeted attacks compared with the single Mahalanobis distance-based defending methods on MNIST, CIFAR-10, and KDDCUP99 datasets.

Human assist control considering shape of target system

AbstractHuman operational errors, especially those that result in car crashes, are recognized as a significant issue in modern society. Recently, assistance with control systems operated by humans has generated interest in its detailed investigation. Previously, to avoid collisions with obstacles as a result of arbitrary human input, control barrier function‐based collision avoidance methods have been utilized. However, safety can only be guaranteed in the condition that a target system is a point. In this paper, we propose a new control barrier function that can guarantee the safety of the entire shape of the control target. We design a lane‐keeping assistance system that considers the shape of a target system for a rear‐wheel‐drive car with a control barrier function. The effectiveness of the proposed method is confirmed by computer simulation.

CentroidReg: A Global-to-Local Framework for Partial Point Cloud Registration

Point cloud registration is a key problem for robotics, computer vision, and other applications. Previous global registration algorithms are sensitive to noises or partial occlusion, while local registration algorithms are highly dependent on initial angles. To solve these problems, we propose CentroidReg, a global-to-local framework for partial point cloud registration, desensitizing noises and initial angles. The partial point clouds have consistent global information (the centroid of the complete 3D shape) and local surface structures, which motivates us to combine rotation-invariant global and local information for correspondence generating. To estimate the centroid of the complete 3D shape for partial point clouds, we propose the CentroidNet with centroid voting and maximum likelihood estimation (MLE) aggregation. Then, we use the proposed RegistrationNet to extract hybrid rotation-invariant features (HRIF) combining global information of the entire 3D shape and local structures in the local area to describe each point. Furthermore, we propose the Reliable Correspondence Generating (RCG) module to generate correspondences in the overlapping area. Finally, a weighted differentiable singular value decomposition (SVD) step is performed to estimate the final rigid transformation. The proposed framework presents state-of-the-art performance on partial point cloud registration. Experiments show that our method is robust to initial angles and noises.

Multiplicity of Inertial Self-Similar Conical Shapes in an Electrified Liquid Metal

Liquid metal ion sources (LMIS) are widely used in applications ranging from local ion implantation in semiconductors, to focused ion beam systems for milling and nanolithography, to space micropropulsion devices being developed by NASA. Above a critically large field strength, an electrically stressed liquid metal develops one or more cuspidal protrusions which undergo accelerated conic tip sharpening with runaway field self-enhancement. Zubarev (2001) first predicted from an inviscid model that the electric stresses at the liquid apex undergo self-similar divergent growth in finite time. The inviscid assumption is appropriate to liquid metals since the viscous boundary layer extends only a few tens of nanometers from the moving interface. In this work, we examine in more depth a two-parameter family of far-field self-similar solutions incorporating inertial, electrical and capillary effects, which to leading order describe electric and velocity potential fields corresponding to a rapidly accelerating \textit{dynamic} Taylor cone. These far field solutions are incorporated self-consistently into boundary integral simulations which reveal the entire liquid shape in the near field. By invoking time reversal symmetry inherent to inviscid flow, we unmask an entire family of novel self-similar conic modes exhibiting features such as inertial recoil, tip bulging from accelerated advance and tip counter-current flow as well as multiple interface stagnation points. These dynamic configurations help explain for the first time the origin of decades old experimental observations that have reported phenomena such as tip oscillation, pulsation and breakup during operation. The various liquid tip shapes accessible to such systems should help correct persistent misconceptions of pre- and post-emission behavior in LMIS systems and related technologies.

A facile approach to fabricate shape memory polyvinyl alcohol/short carbon fibre composites with self-folding properties

In this article, electroactive shape memory polyvinyl alcohol (PVA)/short carbon fibres (SCFs) composites were prepared by simple solution casting method. The self-folding properties of PVA/SCF composites were achieved by shape programming procedure and multilayer assembly technology. The design concept was a three-layer self-folding structure, which utilized three easily obtainable materials; namely, PVA/SCF composite films (shape change layer), polyimide tape (structural layer) and copper wire. The reliability of spontaneous shape recovery of self-folding samples was studied by electrical and shape memory performance tests. The results showed that with the appropriate increase of the applied voltage, the deformation time of the samples decreased and shape memory performance improved. A sample completed the entire shape recovery process within 48 s under a low triggered voltage of 35 V, and shape recovery ratio ( $$R_{\text{r}}$$ ) reached 95%. In addition, shape memory cycle tests showed that the samples had good cycle stability. After 15 consecutive times of unfolding/self-folding cycles, the $$R_{\text{r}}$$ and the shape fixity ratio ( $$R_{\text{f}}$$ ) of the samples were all greater than 93%. A 2D self-folding component was fabricated by properly assigned PVA/SCF composites in a plane, which could complete shape changing at 35 V. This showed the feasibility of self-folding samples in actuating the conversion of 2D framework to 3D structure. The study provides a unique strategy to expand the application of shape memory PVA/SCF composites in smart 3D structures with self-folding properties.

Application of a Simple, Spiking, Locally Competitive Algorithm to Radionuclide Identification

Many radionuclide identification algorithms use statistical inference to collect a variety of features from gamma-ray spectra to deduce the presence of particular radionuclides. More modern algorithms require large amounts of data to learn and use latent features from spectra for classification. Both approaches are computationally expensive, which is reflected in their power consumption, and require large amounts of user intervention to prepare. In this article, we introduce a low-power, neuromorphic algorithm for the real-time identification of radionuclides which simultaneously considers the entire shape of a gamma-ray spectrum. Utilizing the output of a traditional gamma-ray detector, our spiking, locally competitive algorithm uses sparse coding optimization to compare global patterns in a gamma-ray spectrum with a dictionary of radionuclide templates. This approach allows us to model informative global features resulting from both photoelectric absorption and Compton scattering. For the purpose of radiation threat reduction, the dictionary consists of data from the Nuclear Wallet Cards, a list of radionuclides and their properties compiled by the National Nuclear Data Center. To test our algorithm, we use a variety of gamma-ray spectra created using radionuclides measured under laboratory conditions with varying durations, distances, activity levels, and backgrounds, resulting in a wide range of signal-to-noise ratios. We have created test sets for three different gamma-ray detector types, with <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">57</sup> Co, <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">137</sup> Cs, <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">152</sup> Eu, <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">60</sup> Co, <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">239</sup> Pu, and <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">235</sup> U sources, to quantify the effect of resolution, efficiency, and background on the accuracy of the algorithm. We demonstrate a true positive accuracy of 91% with a high-resolution detector and 89% with a low-resolution detector on the corresponding test sets. Experimenting with the same radionuclides included in the test sets in a variety of special nuclear material (SNM) masking configurations, we show that our algorithm is capable of correctly identifying both SNM and mask even when the activity level of the mask is several times higher than that of the SNM. We also determine that our algorithm achieves over a 99% reduction in power consumption over other radionuclide identification software applications, which is critical for long-term, independent monitoring and is the goal of this research.

HEMlets PoSh: Learning Part-Centric Heatmap Triplets for 3D Human Pose and Shape Estimation.

Estimating 3D human pose from a single image is a challenging task. This work attempts to address the uncertainty of lifting the detected 2D joints to the 3D space by introducing an intermediate state - Part-Centric Heatmap Triplets (HEMlets), which shortens the gap between the 2D observation and the 3D interpretation. The HEMlets utilize three joint-heatmaps to represent the relative depth information of the end-joints for each skeletal body part. In our approach, a Convolutional Network (ConvNet) is first trained to predict HEMlets from the input image, followed by a volumetric joint-heatmap regression. We leverage on the integral operation to extract the joint locations from the volumetric heatmaps, guaranteeing end-to-end learning. Despite the simplicity of the network design, the quantitative comparisons show a significant performance improvement over the best-of-grade methods (e.g., 20 percent on Human3.6M). The proposed method naturally supports training with "in-the-wild" images, where only weakly-annotated relative depth information of skeletal joints is available. This further improves the generalization ability of our model, as validated by qualitative comparisons on outdoor images. Leveraging the strength of the HEMlets pose estimation, we further design and append a shallow yet effective network module to regress the SMPL parameters of the body pose and shape. We term the entire HEMlets-based human pose and shape recovery pipeline HEMlets PoSh. Extensive quantitative and qualitative experiments on the existing human body recovery benchmarks justify the state-of-the-art results obtained with our HEMlets PoSh approach.

Shape Estimation of Soft Manipulator Using Stretchable Sensor.

The soft robot manipulator is attracting attention in the surgical fields with its intrinsic softness, lightness in its weight, and safety toward the human organ. However, it cannot be used widely because of its difficulty of control. To control a soft robot manipulator accurately, shape sensing is essential. This paper presents a method of estimating the shape of a soft robot manipulator by using a skin-type stretchable sensor composed of a multiwalled carbon nanotube (MWCNT) and silicone (p7670). The sensor can be easily fabricated and applied by simply attaching it to the surface of the soft manipulator. In its fabrication, MWCNT is sprayed on a teflon sheet, and liquid-state silicone is poured on it. After curing, we turn it over and cover it with another silicone layer. The sensor is fabricated with a sandwich structure to decrease the hysteresis of the sensor. After calibration and determining the relationship between the resistance of the sensor and the strain, three sensors are attached at 120° intervals. Using the obtained data, the curvature of the manipulator is calculated, and the entire shape is reconstructed. To validate its accuracy, the estimated shape is compared with the camera data. We experiment with three, six, and nine sensors attached, and the result of the error of shape estimation is compared. As a result, the minimum tip position error is approximately 8.9 mm, which corresponded to 4.45% of the total length of the manipulator when using nine sensors.

Free-to-bound emission from interstitial carbon and oxygen defects (CiOi) in electron-irradiated Si

We determined the entire spectral shape of a broad band around 0.8 eV, previously termed the C08-band, which was observed commonly in Si by room-temperature photoluminescence after electron irradiation. The band has a peak at 0.77 ± 0.01 eV with long tails on both sides. We identified that the C08-band has the same origin as the C-line and occurs as a result of the recombination between a free electron and a hole bound by the deep trap due to the interstitial C and O defects (CiOi). The long tails were explained by the superposition of phonon sidebands.

Infrared Thermography Measurement for Vibration-Based Structural Health Monitoring in Low-Visibility Harsh Environments.

In this study, infrared thermography is used for vibration-based structural health monitoring (SHM). Heat sources are employed as sensors. An acrylic frame structure was experimentally investigated using the heat sources as structural marker points to record the vibration response. The effectiveness of the infrared thermography measurement system was verified by comparing the results obtained using an infrared thermal imager with those obtained using accelerometers. The average error in natural frequency was between only 0.64% and 3.84%. To guarantee the applicability of the system, this study employed the mode shape curvature method to locate damage on a structure under harsh environments, for instance, in dark, hindered, and hazy conditions. Moreover, we propose the mode shape recombination method (MSRM) to realize large-scale structural measurement. The partial mode shapes of the 3D frame structure are combined using the MSRM to obtain the entire mode shape with a satisfactory model assurance criterion. Experimental results confirmed the feasibility of using heat sources as sensors and indicated that the proposed methods are suitable for overcoming the numerous inherent limitations associated with SHM in harsh or remote environments as well as the limitations associated with the SHM of large-scale structures.

Opening and closing surfaces

We propose a new type of curvature flow for curves in 2D and surfaces in 3D. The flow is inspired by the mathematical morphology opening and closing operations. These operations are classically defined by composition of dilation and erosion operations. In practice, existing methods implemented this way will result in re-discretizing the entire shape, even if some parts of the surface do not change. Instead, our surface-only curvature-based flow moves the surface selectively in areas that should be repositioned. In our triangle mesh discretization, vertices in regions unaffected by the opening or closing will remain exactly in place and do not affect our method's complexity, which is output-sensitive.

Scalar and vector crossed breather-pair and their controlling excitations of a coupled nonlinear Schrödinger equation with partially nonlocal property in an external potential

We study a nonautonomous (2+1)-dimensional coupled partially nonlocal nonlinear Schrödinger equation under a linear and parabolic potential, and find a mapping expression between nonautonomous and autonomous equations. Via this mapping equation with the Darboux method, we find diversified exact solutions, such as scalar and vector crossed breather-pair. By changing values of phase chirp and diffraction parameters to alter value of maximal cumulative time and compare with values of top position, we investigate the controlling excitation of scalar and vector crossed breathers including the early shape, top shape, entire shape and periodical reproduction excitations in different external potentials.

Mathematical model of shaping toothed products using volumetric tool with one motion parameter

Introduction. The development of a mathematical model of one-parameter shaping of a toothed product is considered. As an example, shaping of the side surface of the teeth of the Novikov gearing is studied; the mode and magnitude of the change in the shaping error heightwise the wheel tooth are shown. The work objective was to develop a mathematical model of the surface of the product teeth as a generating surface envelope of the tool. A computational and experimental study is carried out. The mathematical models obtained can be used in devices with copiers when shaping the side surface of the teeth of the Novikov gear. As an example, we consider the deviation behavior of the teeth profile of the Novikov gear with the original profile of DLZ 0.7-0.15 Materials and Methods. When building the model and studying its characteristics, the mathematical tools of the gearing theory, calculation procedure for cylindrical gears (A.A. Silich’s author development) were used. The paper proposes new mathematical models of the equations of the lateral surface of the gear teeth formed with a tool whose axial profile coincides with the original one. In the model under consideration, the tool moves along the axis of the product while the latter rotates on its axis. In the course of the study, numerical modeling was carried out to determine the error value in shaping the product profile using the tool. Results. New mathematical models and software have been developed for numerical simulation of the shaping of a toothed product using a tool with one independent motion parameter. An algorithm has also been developed to determine the deviation error of the real profile from the nominal one for the tooth of the Novikov gear. Solutions to accurately reproduce the tooth profile are provided. Discussion and Conclusions. The parametric method of analytical description of the surface used in the work simplifies the calculation of the cutting tool displacements in the problems of numerical control. Solving the problem of synthesizing the technology of workpiece surface treatment on metal-cutting machines provides the development of a description of the entire shaping process and requires the representation of the workpiece surface in the form of a mathematical model. The results obtained can be used under creating finishing methods for processing teeth when improving the quality of gear wheels and gear drives, as well as production efficiency.

Contactless reversible 4D-printing for 3D-to-3D shape morphing

ABSTRACT 4D printing provides a means to create dynamic structures for self-actuating devices fabricated by additive manufacturing techniques. Most existing 4D printing processes are only capable of one-way shape morphing using a single mechanism for stimulation. In the limited successful reversible 4D-printing studies, most only demonstrate 2D-to-3D shape morphing. This study introduces a contactless shape setting mechanism to empower reversible 4D printing using a combination of stimuli. The forward shape programming is realised by asymmetric swelling with heated ethanol, and the shape recovery is accomplished by dry heating. The shape morphing can be predicted using a simulation model. Several designs are 4D-printed to achieve different forms of morphing to obtain 3D-to-3D shape morphing. The entire shape morphing cycle could be completed within as short as 3 min. The capability of 3D-to-3D shape morphing and reversibility of our 4D-printing process promise great potential for different applications such as biomimetics and soft robotics.

Practical Applications of Adaptive Portfolios and the Power of Diversification

<h3>Practical Applications Summary</h3> In <b>Adaptive Portfolios and the Power of Diversification</b>, in the August 2019 edition of <b><i>The Journal of Investing</i>, Jürgen Vandenbroucke</b> of <b>KBC Asset Management NV</b> describes a discretionary method for portfolio management that addresses investor emotions at the individual, investment-product, and portfolio levels. By adding “a behavioral component to the prevailing risk-based paradigm,” he subscribes to the adaptive market hypothesis (Lo 2004), which concerns how individuals’ emotions may negate rational investment decision-making. Vandenbroucke highlights the common consequences of emotion-driven investing. He then proposes remedies in the areas of investor profiling, product positioning, and portfolio construction. He distinguishes between investor attitudes toward “risk,” as measured by the variance of returns, and “loss,” as measured in terms of an investment’s potential gain versus its potential losses. This amounts to operating beyond the confines of a classical mean–variance framework and considering the entire shape of the distribution of future returns (which may be non-normal). He differentiates among investment products along spectrums of mean versus variance and upside potential versus downside hazard. Finally, he shows how to weight selected investment products to align investors’ loss aversion with a balance between upside potential and downside risk in a portfolio. This weighting allows a portfolio to inhabit an investor’s “comfort zone” by adjusting its allocations as market conditions change. A customer-centered adaptive portfolio of this kind enhances diversification and can temper emotionally driven trading activity that would otherwise be a drag on performance. <b>TOPICS:</b>Wealth management, portfolio construction, statistical methods

Gorilla calcaneal morphological variation and ecological divergence.

The primate foot has been extensively investigated because of its role in weight-bearing; however, the calcaneus has been relatively understudied. Here we examine entire gorilla calcaneal external shape to understand its relationship with locomotor behavior. Calcanei of Gorilla gorilla gorilla (n = 43), Gorilla beringei graueri (n = 20), and Gorilla beringei beringei (n = 15) were surface or micro-CT scanned. External shape was analyzed through a three-dimensional geometric morphometric sliding semilandmark analysis. Semilandmarks were slid relative to an updated Procrustes average in order to minimize the bending energy of the thin plate spline interpolation function. Shape variation was summarized using principal components analysis of shape coordinates. Procrustes distances between taxa averages were calculated and resampling statistics run to test pairwise differences. Linear measures were collected and regressed against estimated body mass. All three taxa exhibit statistically different morphologies (p < .001 for pairwise comparisons). G. g. gorilla demonstrates an anteroposteriorly elongated calcaneus with a deeper cuboid pivot region and mediolaterally flatter posterior talar facet. G. b. beringei possesses the flattest cuboid and most medially-angled posterior talar facets. G. b. graueri demonstrates intermediate articular facet morphology, a medially-angled tuberosity, and an elongated peroneal trochlea. Articular facet differences separate gorillas along a locomotor gradient. G. g. gorilla is adapted for arboreality with greater joint mobility, while G. b. beringei is adapted for more stereotypical loads associated with terrestriality. G. b. graueri's unique posterolateral morphology may be due to a secondary transition to greater arboreality from a more terrestrial ancestor.