Offset Parameters Research Articles

Visualization of band offsets at few-layer MoS2/Ge heterojunction

The visualization of band alignment for designing heterostructures between transition metal dichalcogenides and germanium plays a vital role in a deeper understanding of carrier dynamics at the heterointerface. Here, to study the band alignment across the MoS2/Ge heterojunction, we have deposited a wafer-scale highly crystalline few atomic layers MoS2 film via a highly controllable and scalable sputtering technique coupled with a post sulfurization process in a sulfur-rich environment. The Raman and XRD spectra of as-fabricated MoS2/Ge heterojunction expose the presence of highly crystalline few atomic layer MoS2 on top of Ge substrate. Interestingly, we found a type-II band alignment at the MoS2/Ge heterointerface having valence band, and conduction band offset values of 0.88 and 0.21 eV, which can provide very efficient recombination through spatially confining charge carriers. The calculation of band offset parameters offers a promising way for device engineering across the MoS2/Ge heterojunction interface. Moreover, to demonstrate the practicability of the fabricated heterostructure, we explored the suitability of our device for broadband photodetection applications.

FAGNet: Multi-Scale Object Detection Method in Remote Sensing Images by Combining MAFPN and GVR

<p indent=0mm>Remote sensing images of large scenes are complex, and have the characteristics of many categories of objects, different scales and changeable directions, which lead to the problem of multi-class, multi-scale and multi-oriented of objects in remote sensing images. A remote sensing image object detection method based on multi-scale attention feature pyramid network (MAFPN) and gliding vertex regression (GVR) mechanism is proposed. Firstly, multi-layer feature maps are extracted from backbone network as input of MAFPN, which combines feature fusion and attention mechanism. On the basis of fusing feature maps of multi-scale, channel attention and spatial attention mechanisms are used to suppress noise, enhance effective feature reuse, and improve the network’s adaptability to object multi-scale features. The fusion feature map output by MAFPN is input to the region proposal network to generate the regions of interest, and then they will be sent to the classification regression network. The GVR mechanism is used in the object classification regression network and the four vertex offset ratio parameters and rotation factors are added on the basis of predicting the horizontal boxes, which converts the horizontal boxes into a rotating box to reduce the redundant area in the bounding boxes, makes the predicted rotating bounding boxes fit the object more closely. The experimental results on the DOTA public dataset, compared with many classical detection algorithms based on convolutional neural networks, show that the average detection accuracy of the proposed method is significantly improved, which can detect objects of multi-scales and multi-oriented more accurately, and achieve the robust detection of multi-scale objects.

Application of AsiaSat-3S satellite in CAPS system

CAPS is an integrated system of navigation and communication. The orbit position of AsiaSat-3S satellite has been pushed from 105.5E to 147.5E. It has become a SIGSO satellite, which plays a certain role in improving the constellation DOP of CAPS navigation system. According to the characteristic parameters of AsiaSat-3S satellite (mainly including orbit parameters, polarization parameters, frequency offset parameters, etc.), this paper expounds the changes of azimuth, elevation angle and polarization angle of 16-meter paraboloid antenna in Tianjin pointing and tracking AsiaSat-3S satellite in CAPS ground system, and analyzes the dynamic changes of frequency offset of AsiaSat-3S satellite transponder through the spontaneous receiving of navigation signals The parameter model prediction of CAPS repeater navigation system has a good reference value.

Residual stress reduction of LPBF-processed CM247LC samples via multi laser beam strategies

Based on SLM parameters from previous works, which guarantee fully dense and crack free CM247LC samples, multi laser beam strategies have been pursued to reduce residual stresses or rather distortion during LPBF processing. By using a second post heating and non-melting laser source with a defocused laser beam and lateral offset, cantilever distortion is reduced more than 7.5%, compared to the reference. Based on pre-tests with 9 different offset parameters, the optimum offset has been identified. Also, an upper limit for the laser power of 65 W is identified for the second heat laser beam with a spot diameter of 380 μm, to avoid re-melting and creating new defects. A theoretical “two bar model,” to explain the residual stress behavior and reduction with multi laser beam offset strategy during the LPBF process, is presented. Furthermore, re-melting cracks, defects, and microstructure are analyzed in conjunction with the second defocused offset laser, in case of a 200 W laser power, an increased scan speed of 1300 mms/s, and a reduced hatch distance. Secondary electron signal (SE) images of re-melting cracks are analyzed and compared to SE-image of hot cracks (solidification cracks). Based on electron backscatter diffraction (EBSD), the results of the microstructure from the last mentioned multi laser beam approach, which creates re-melting cracks, are presented and analyzed.

Slant type taper profiling and prediction of profiling speed for a circular profile during in wire electric discharge machining using Hastelloy-X

Hastelloy-X a nickel-based alloy used in nozzles, flame holders, turbine blades, turbocharges, jet engine tailpipes, afterburner components etc. having complex tapering profiles. Wire electric discharge machining proves to be the most beneficial machining technique as it provides required accuracy for the components. In the present research, a slant type taper fixture is employed for achieving taper angles as convention tapering have many hindrances like wire bend, angular inaccuracy, guide wear, insufficient flushing and wire breakage etc. and machining a simple circular profile on Hastelloy-X. The behaviour of different output parameters like profiling speed, surface roughness, profile areas, microhardness and recast layer were investigated for various input parameters for machined taper components at 0°, 15° and 30°. The cutting speed override parameter influenced most on the profiling speed and surface roughness. The wire offset parameter was found to be the most significant factor in the case of circular profile areas that were machined. The variation of different output parameters to profiling/cutting speed and taper angle was also highlighted. It is found the recast layer decreased which indicated lesser thermal degradation at higher taper angles at different profiling parameters. This is also validated by the microhardness where the machined surface hardness of taper angular profiles was found to be greater than the 0° profiles. The artificial neural networks and adaptive neuro-fuzzy interference system were used for the prediction of profiling speed. The adaptive neuro-fuzzy interference system was found better in prediction as the percentage error varies between 0–5 per cent. In conclusion, the profiling speed influences both on the accuracy and surface of machined taper circular profiles.

Chameleonic Noise in GPS Position Time Series

AbstractIt has been a standard practice for about 2 decades to compute global positioning system (GPS)‐based station velocity uncertainties using the apparent noise statistics of the non‐linear position residuals rather than assume white noise (WN) behavior. The latter choice would yield unrealistic velocity uncertainties. The most common noise types used are power‐law, usually close to flicker noise (FN), over most frequencies mixed with WN at the shortest periods. The complicating impact of offsets in the position time series, mostly caused by equipment changes or tectonic events, has not been fully appreciated. These are far less benign than recently suggested. In addition to contributing a pseudo‐random walk noise (RW) component to the velocity errors, estimating offset parameters changes the apparent noise color toward whiter. Spectral power is effectively drained by offsets at periods longer than roughly the mean span between them. This consequently favors a Gauss‐Markov process as the apparently preferred noise model and, importantly, obscures the presence of RW and long‐period Earth deformation in the series. Both effects can lead to potentially under‐estimated velocity uncertainties. The full value of decadal‐long GPS time series for geodynamical applications is thereby greatly eroded by recurring offsets, especially when they occur quasi‐regularly. In addition, contrary to common assumption, the noise color is generally not fixed with time, but clearly becomes whiter in more recent data. The origin of the colored noise and its whitening over time remain elusive.

A Novel Airborne Dual-Antenna InSAR Calibration Method for Backprojection Imaging Model

The interferometric synthetic aperture radar (InSAR) elevation inversion method based on the backprojection (BP) imaging model simplifies the interferometric processing chain where image registration and phase unwrapping are not required. Meanwhile, BP algorithm is suitable for radar with different imaging modes and geometry. However, the existing calibration methods are all aimed at traditional InSAR which adopts frequency domain imaging algorithm, but the calibration method for backprojection InSAR elevation inversion model has not been published. In this paper, we propose a novel InSAR calibration method which combines Fast Fourier Transform (FFT) estimation method with sensitivity equation method based on backprojection imaging model. FFT is used to process the interferometric phase which has removed the terrain phase of external digital elevation model (DEM) under BP imaging, and the estimation of interferometric parameters is realized through the phase fringe frequency. In the calibration method based on sensitivity equations, the deviations of interferometric parameters are calculated by solving sensitivity equations according to the three-dimensional information of ground control points. FFT estimation method not only generates the initial baseline parameters for sensitivity equation method, which is conducive to obtaining the global optimal solution, but also separates the calibration of phase offset and baseline parameters, which makes it possible to minimize the condition number of sensitivity matrix in sensitivity equation method. Finally, we obtain the calibrated interferometric parameters through iteration of sensitivity equation method and realize high accuracy DEM inversion. Both simulation experiment and airborne dual-antenna InSAR data processing are performed to verify the effectiveness of this method.

Current Sensors Offset Fault Online Estimation in Permanent Magnet Synchronous Generator (PMSG) Drives for Offshore Wind Turbines

Offshore wind power generation system’s reliability is always a challenging task. To solve the current sensor offset fault problem in the electric powertrain for the offshore wind power generation system, in this paper, a current-detection based sensor offset fault diagnosis method is proposed. The proposed method adopts four fixed measuring points for the estimation of the offset values, which does not require any modifications to the traditional PWM generating strategy. Therefore, the total harmonic distortion (THD) of the drive is not increased by using the proposed offset fault estimation method. The offset fault parameters of the powertrain system are obtained by analyzing the detected current sensors in the aforementioned four sampling points directly. No complex observers nor filters are needed for the signal processing, resulting in computational burden reduction. Experimental results on a 1 kW PMSG system demonstrated the effectiveness of the proposed strategy, which show that the current sensor offset faults can be estimated accurately, and the adverse effects can be eliminated.

Full-sky photon simulation of clusters and active galactic nuclei in the soft X-rays for eROSITA

The eROSITA X-ray telescope on board the Spectrum-Roentgen-Gamma (SRG) mission will measure the position and properties of about 100,000 clusters of galaxies and 3 million active galactic nuclei over the full sky. To study the statistical properties of this ongoing survey, it is key to estimate the selection function accurately. We create a set of full sky light-cones using the MultiDark and UNIT dark matter only N-body simulations. We present a novel method to predict the X-ray emission of galaxy clusters. Given a set of dark matter halo properties (mass, redshift, ellipticity, offset parameter), we construct an X-ray emissivity profile and image for each halo in the light-cone. We follow the eROSITA scanning strategy to produce a list of X-ray photons on the full sky. We predict scaling relations for the model clusters, which are in good agreement with the literature. The predicted number density of clusters as a function of flux also agrees with previous measurements. Finally, we obtain a scatter of 0.21 (0.07, 0.25) for the X-ray luminosity -- mass (temperature -- mass, luminosity -- temperature) model scaling relations. We provide catalogues with the model photons emitted by clusters and active galactic nuclei. These catalogues will aid the eROSITA end to end simulation flow analysis and in particular the source detection process and cataloguing methods.

Horizontal Correction of Scoliotic Deformity with High-Density Pedicle Screw Constructs: A Retrospective Analysis of 40 Patients

Purpose: To report radiologic outcomes in the horizontal plane after scoliosis correction with high-density pedicle screw constructs through a sterEOS®-3D analysis. Methods: We conducted a retrospective monocentric study on scoliotic patients who underwent a surgical correction with high-density constructs. SterEOS®-3D reconstructions were modelled from pre and postoperative EOS® acquisitions. Amplitude of surgical correction and residual deformity were analysed for rotational parameters (vertebrae vectors coordinates, apical vertebral rotation (AVR), intervertebral rotations, Torsion Index) and transversal offset parameters (Spread of Coronal Offsets (SCO), mean of coronal offsets (CO), T9 and L3 to Gravity Line (GL) CO, T9/L3 Transverse Gravitational Deviation Index (TGDI), T9/L3 TGDI θ categories). Results: 80 sterEOS®3D reconstructions were analysed. Paired t-test comparisons between pre and postoperative values showed a significant reduction for Cobb angles (p&lt;0.0001) and AVR (p = 0.0024) but not for TI (p = 0.69). 51% of the curves with a preoperative AVR &gt; 10° were corrected at a segmental level with an average de-rotation amplitude of 19.3° +/- 8° and 56% at a global level with an average de-torsion index of 54% +/- 30%. Correction of SCO was effective for 95% of patients with a mean amplitude of 30mm +/- 10mm and was associated with a significant reduction in T9 and L3 to GL CO (34mm ± 24mm and 7.6mm +/-10mm respectively). Conclusion: Horizontal corrections achieved with high-density constructs in scoliosis surgery are more significant on translation than rotation at a segmental and global level.

Adaptive Convolution Neural Networks for Electrical Resistivity Inversion

Electrical Resistivity Inversion is an inverse problem that intends to infer the resistivity model from apparent resistivity data. The input and output have the format as the image but are with some unique characteristics that differ from the common natural images. The patterns in resistivity data are no longer spatial invariant. In this case, though the vanilla convolutional neural networks could build the mapping between images, their weight sharing kernels may cause ambiguous situations when coping with the resistivity data. To address this problem, in this work, we directly adapt convolutional kernels to fit for the electrical resistivity inversion task. By analyzing the resistivity data, we found the data patterns corresponding to the same abnormal body will vary with the vertical position change, correspondingly we learn extra offset and amplitude parameters for each vertical position the convolutional kernels applied, to make convolutional kernels transformed to capture the varying patterns. Unlike active convolution and deformable convolution, our learned offsets and amplitudes are sharing at each vertical position, which is neither too free nor too rigid. More importantly, it obeys the inherent characteristics of resistivity data. Finally, through adversarial training, the inversion results are more realistic as the resistivity model. From comprehensive comparisons and studies, our adaptive convolutional neural networks (ACN) outperform the baselines consistently, verifying our assumption and the effectiveness of our proposed method.

The Kinematics of Massive Quiescent Galaxies at 1.4 &lt; z &lt; 2.1: Dark Matter Fractions, IMF Variation, and the Relation to Local Early-type Galaxies*

Abstract We study the dynamical properties of massive quiescent galaxies at 1.4 &lt; z &lt; 2.1 using deep Hubble Space Telescope WFC3/F160W imaging and a combination of literature stellar velocity dispersion measurements and new near-infrared spectra obtained using the K-band Multi Object Spectrograph (KMOS) on the ESO Very Large Telescope. We use these data to show that the typical dynamical-to-stellar mass ratio has increased by ∼0.2 dex from z = 2 to the present day, and we investigate this evolution in the context of possible changes in the stellar initial mass function (IMF) and/or fraction of dark matter contained within the galaxy effective radius, f DM[&lt;r e]. Comparing our high-redshift sample to their likely descendants at low redshift, we find that f DM[&lt;r e] has increased by a factor of more than 4 since z ≈ 1.8, from f DM[&lt;r e] = 6.6% ± 1.0% to ∼24%. The observed increase appears robust to changes in the methods used to estimate dynamical masses or match progenitors and descendants. We quantify possible variation of the stellar IMF through the offset parameter α, defined as the ratio of dynamical mass in stars to the stellar mass estimated using a Chabrier IMF. We demonstrate that the correlation between stellar velocity dispersion and α reported among quiescent galaxies at low redshift is already in place at z = 2, and we argue that subsequent evolution through (mostly minor) merging should act to preserve this relation while contributing significantly to galaxies’ overall growth in size and stellar mass.

Different types of band alignment at MoS2/(Al, Ga, In)N heterointerfaces

Heterojunction band offset parameters are critical for designing and fabricating junction-based devices as these parameters play a crucial role in determining the optical and electronic properties of a device. Herein, we report the band discontinuities at the MoS2/III-nitride (InN, GaN, and AlN) heterointerfaces. Few-layer MoS2 thin films are deposited by pulsed laser deposition on III-nitrides/c-sapphire substrates. Band offsets [valence band offset (VBO) and conduction band offset (CBO)] at the heterojunctions are determined by high-resolution x-ray photoelectron spectroscopy. The estimated band alignments are found to be type-I (VBO: 2.34 eV, CBO: 2.59 eV), type-II (VBO: 2.38 eV, CBO: 0.32 eV), and type-III (VBO: 2.23 eV, CBO: 2.87 eV) for MoS2/AlN, MoS2/GaN, and MoS2/InN, respectively. Such determination of the band offsets of 2D/3D heterojunctions paves a way to understand and design the futuristic photonic and electronic devices using these material systems.

Channel prediction based temporal multiple sparse bayesian learning for channel estimation in fast time-varying underwater acoustic OFDM communications

In recent years, the multi-blocks joint channel estimation methods for underwater acoustic (UWA) OFDM systems have been proposed to improve the performance by using time correlation across consecutive OFDM blocks. However, the assumption of common sparse support (multi-path delays are invariant across consecutive blocks) in these methods is difficult to be met in fast time-varying channels. Therefore, we propose a channel prediction based joint channel estimation method for UWA fast time-varying channels, where multi-path delays and gains change significantly across consecutive OFDM blocks. Firstly we define a channel offset parameters model by the clustering property of UWA channels, and adopt Orthogonal Matching Pursuit (OMP) algorithm to estimate the channel offset parameters. Then we reconstruct a virtual current received signal based on the prediction method. Finally we combine the virtual received signal and the actual one into a joint estimation model, and utilize temporal multiple sparse Bayesian learning (TMSBL) method to jointly estimate the channel. Results of simulations and sea trial demonstrate the effectiveness of the proposed method in fast time-varying UWA channels, which achieves better performance than both the TMSBL method which is based on the joint processing of multi-blocks, and the OMP method which is based on block-by-block processing.

Distributed non‐linear robust consensus‐based sensor calibration for networked control systems

In this study a new algorithm is proposed for distributed blind sensor macro-calibration in networked control systems robust to noise. The proposed distributed algorithm for estimation of gain and offset correction parameters is of stochastic approximation type, with local non-linear transformations of residuals. Convergence of the algorithm in mean-square and with probability one to consensus is proved for a large class of non-linear transformations, network properties and communication and measurement noise characteristics. The choice of the introduced non-linear transformations in accordance with the theory of robust statistics leads to the proposal of new calibration algorithms robustified w.r.t. noise. It is demonstrated by Monte Carlo simulation that the proposed algorithms are very efficient in the presence of large outliers from the point of view of both achievement of high convergence rate and adequate values of convergence points, outperforming the existing linear algorithms.

Position analysis and nonlinear phenomena of flexible manipulator with generic payload mounted on a moving base

The investigation of the end-point trajectory and the nonlinear oscillation of elastic manipulator with offset payload mounted on moving base has been carried out by demonstrating the modal parameters and dynamic responses of a bi-directionally deflected rotating flexible link manipulator. A large deflection model of a flexible rotating manipulator considering both transverse and axial deformation, dynamics of rotating hub, generic payload, and rigid motion of platform has been derived. Initially, modal analysis has been studied to graphically illustrate the eigenfrequencies and corresponding eigenspectrums, while it has been noted that the system possesses distinct and different vibration characteristics as compared to that of a system without offset payload. A smooth sinusoidal input torque has been imparted to the joint to assess the time dependency factors and parameters, which describe its position inaccuracy over time. Finally, the investigation of influence of essential system attributes on the nonlinear behavior and system instabilities under resonance conditions by analyzing the steady-state solutions has been accomplished. The effect of payload parameters such as mass, inertia, and offset, along with the inertia and stiffness of actuator on the frequency response curves has been demonstrated graphically. This work exhibits that the system’s dynamics diversely evolve with a change of offset parameters while system loses its stability due to saddle-node bifurcations. The present result offers specific guidelines towards the design and control aspects of flexible manipulators based on the selection of offset parameters.

Statistically driven model for efficient analysis of few-photon transport in waveguide quantum electrodynamics

Understanding transport properties in quantum nanophotonics plays a central role in designing few-photon devices, yet it suffers from a longstanding extensive computational burden. In this work, we propose a statistically driven model with a tremendously eased computational burden, which is based on the deep understanding of the few-photon spontaneous emission process. By utilizing phenomenological, statistically driven inter-photon offset parameters, the proposed model expedites the transport calculation with a three-order-of-magnitude enhancement of speed in contrast to conventional numerical approaches. We showcase the two-photon transport computation benchmarked by the rigorous analytical approach. Our work provides an efficient tool for designing few-photon nano-devices, and it significantly deepens the understanding of correlated quantum many-body physics.

Clonal selection based intelligent parameter inversion algorithm for prestack seismic data

Amplitude variation with offset (AVO) elastic parameter inversion is an approach of oil exploration that employs seismic information, and it is a problem of non-linear optimization. When using a quasi-linear or linear approach to solve the problem, the inversion result is unreliable or inaccurate. Metaheuristic search methods, e.g., bio-inspired optimization algorithms such as genetic algorithms, are capable of handling highly non-linear optimization problems and thus provide a promising approach for oil and gas exploration. As one of the metaheuristic search approaches, the immune clone selection algorithm exhibits the property of fast convergence and strong global search capability. In this paper, the immune clone selection algorithm is used to address the problem of AVO elastic parameter inversion. This algorithm employs the specific initialization strategy of Aki as well as the approximation equation of Rechard, which is utilized in the elastic parameter inversion process to smooth the initialization parameter curve. Additionally, the genetic operation in the algorithm is improved in accordance. The results of multiple experiments demonstrate that the approach could significantly improve the inversion accuracy, and the correlation coefficient of the elastic parameters acquired via inversion is specifically high.

Waveform Design and Accurate Channel Estimation for Frequency-Hopping MIMO Radar-Based Communications

Frequency-hopping (FH) MIMO radar-based dual-function radar communication (FH-MIMO DFRC) enables communication symbol rate to exceed radar pulse repetition frequency, which requires accurate estimations of timing offset and channel parameters. The estimations, however, are challenging due to unknown, fast-changing hopping frequencies and the multiplicative coupling between timing offset and channel parameters. In this article, we develop accurate methods for a single-antenna communication receiver to estimate timing offset and channel for FH-MIMO DFRC. First, we design a novel FH-MIMO radar waveform, which enables a communication receiver to estimate the hopping frequency sequence (HFS) used by radar, instead of acquiring it from radar. Importantly, the novel waveform incurs no degradation to radar ranging performance. Then, via capturing distinct HFS features, we develop two estimators for timing offset and derive mean squared error lower bound of each estimator. Using the bounds, we design an HFS that renders both estimators applicable. Furthermore, we develop an accurate channel estimation method, reusing the single hop for timing offset estimation. Validated by simulations, the accurate channel estimates attained by the proposed methods enable the communication performance of DFRC to approach that achieved based on perfect timing and ideal knowledge of channel.

Experimental Study on the Effect of Offset Notch on Fracture Properties of Rock under Three‐Point Bending Beam

To investigate the effects of offset notch on the fracture properties of rock beam under bending load, granite beam specimens with “one single offset notch” and “central and offset double notches” are made. A series of three‐point bending beam tests on the specimens are carried out by controlling the displacement rate of central notch. The whole load‐displacement (P‐CMOD) curves are obtained. Experimental results show that the larger the distance between the offset notch and beam central is, the larger are the peak load and nominal strength of the specimen. The peak load and nominal strength for the “central and offset double notches” specimens are both larger than those for the “single central notch” specimen. A fracture model considering the effect of offset notch is developed, and the relationship between the offset notch parameter, tensile strength, and fracture toughness is established.