Inverse Scheme Research Articles

Inverse computational ghost imaging for image encryption.

Computer-generated random patterns and bucket detection are two key characteristics of computational ghost imaging (GI), which offer it a potential application in optical encryption. Here, we propose an inverse computational GI scheme, in which bucket signals are firstly selected and then random patterns are calculated correspondingly. Different GI reconstruction algorithms are used to test the inverse computational GI, and the relationship between imaging quality and error ratio factor is discussed as well. Compared with computational GI, our inverse one not only has disguised bucket signals but also provides an opportunity to combine with other cryptographies, both of which enrich the GI-based encryption process and enhance the security simultaneously.

Enhanced Protection by Recombinant Newcastle Disease Virus Expressing Infectious Bronchitis Virus Spike Ectodomain and Chicken Granulocyte-Macrophage Colony-Stimulating Factor.

We previously reported that recombinant Newcastle disease virus LaSota (rLS) expressing infectious bronchitis virus (IBV) Arkansas (Ark)-type trimeric spike (S) ectodomain (Se; rLS/ArkSe) provides suboptimal protection against IBV challenge. We have now developed rLS expressing chicken granulocyte-macrophage colony-stimulating factor (GMCSF) and IBV Ark Se in an attempt to enhance vaccine effectiveness. In the current study, we first compared protection conferred by vaccination with rLS/ArkSe and rLS/ArkSe.GMCSF. Vaccinated chickens were challenged with virulent Ark, and protection was determined by clinical signs, viral load, and tracheal histomorphometry. Results showed that coexpression of GMCSF and the Se from rLS significantly reduced tracheal viral load and tracheal lesions compared with chickens vaccinated with rLS/ArkSe. In a second experiment, we evaluated enhancement of cross-protection of a Massachusetts (Mass) attenuated vaccine by priming or boosting with rLS/ArkSe.GMCSF. Vaccinated chickens were challenged with Ark, and protection was evaluated. Results show that priming or boosting with the recombinant virus significantly increased cross-protection conferred by Mass against Ark virulent challenge. Greater reductions of viral loads in both trachea and lachrymal fluids were observed in chickens primed with rLS/ArkSe.GMCSF and boosted with Mass. Consistently, Ark Se antibody levels measured with recombinant Ark Se protein-coated ELISA plates 14 days after boost were significantly higher in these chickens. Unexpectedly, the inverse vaccination scheme, that is, priming with Mass and boosting with the recombinant vaccine, proved somewhat less effective. We concluded that a prime and boost strategy by using rLS/ArkSe.GMCSF and the worldwide ubiquitous Mass attenuated vaccine provides enhanced cross-protection. Thus, rLS/GMCSF coexpressing the Se of regionally relevant IBV serotypes could be used in combination with live Mass to protect against regionally circulating IBV variant strains.

Inferring Morphology of a Neuron from In Vivo LFP Data.

We propose a computational pipeline that uses biophysical modeling and sequential neural posterior estimation algorithm to infer the position and morphology of single neurons using multi-electrode in vivo extracellular voltage recordings. In this inverse modeling scheme, we designed a generic biophysical single neuron model with stylized morphology that had adjustable parameters for the dimensions of the soma, basal and apical dendrites, and their location and orientations relative to the multi-electrode probe. Preliminary results indicate that the proposed methodology can infer up to eight neuronal parameters well. We highlight the issues involved in the development of the novel pipeline and areas for further improvement.

Two-dimensional meshless modelling and TE-mode inversion of magnetotelluric data

SUMMARY We present a new 2-D forward modelling and inversion scheme to interpret magnetotelluric/radio-magnetotelluric data by utilizing a novel meshless forward operator. We use this discretization technique within an inverse scheme to recover conductivity structures from given magnetotelluric data. To approximate solutions of the partial differential equations that describe the magnetotelluric experiment, we discretize the subsurface only in terms of nodes. These node sets, which are simple to generate, are used to derive the differential operators’ approximations in a generalized meshless framework. First, we study and compare forward modelling calculations to an analytical and known solution from the literature. Several example calculations are given, which validate the proposed meshless forward operator. We then formulate our inverse scheme for TE-mode data, which uses only subsets of the nodal subsurface parametrization to generate conductivity structures from this given data. The inverse scheme consists of a Gauss–Newton algorithm combined with the generalized meshless framework. To validate the algorithm, we present inversion results from synthetic and field data. We compare our results to conductivity models calculated by established, well-known inversion schemes and literature results. We report that our algorithm can accurately model magnetotelluric responses and recover meaningful conductivity models, explaining given magnetotelluric data.

Logarithmic confidence intervals for the cross-product ratio of binomial proportions under different sampling schemes

We consider the problem of logarithmic interval estimation for a cross-product ratio with data from two independent Bernoulli samples. Each sample may be obtained in the framework of direct or inverse Binomial sampling schemes. Asymptotic logarithmic confidence intervals are constructed under different types of sampling schemes, with parameter estimators demonstrating exponentially decreasing bias. Our goal is to investigate the cases when the relatively simple normal approximations for estimators of the cross-product ratio are reliable for constructing logarithmic confidence intervals. We use the closeness of the confidence coefficient to the nominal confidence level as our main evaluation criterion, and use the Monte-Carlo method to investigate the key probability characteristics of intervals corresponding to all possible combinations of sampling schemes. We present estimations of the coverage probability, expectation and standard deviation of interval widths in tables. Also, we provide some recommendations for applying each logarithmic interval obtained.

PERICLIMv1.0: a model deriving palaeo-air temperatures from thaw depth in past permafrost regions

Abstract. Periglacial features, such as various kinds of patterned ground, cryoturbations, frost wedges, solifluction structures, and blockfields, are among the most common relics of cold climate periods, which repetitively occurred throughout the Quaternary. As such, they are widespread archives of past environmental conditions. Climate controls on the development of most periglacial features, however, remain poorly known, and thus empirical palaeo-climate reconstructions based on them have limited validity. This study presents and evaluates a simple new inverse modelling scheme called PERICLIMv1.0 (PERIglacial CLIMate) that derives palaeo-air temperature characteristics related to the palaeo-active-layer thickness, which can be recognized using many relict periglacial features found in past permafrost regions. The evaluation against modern temperature records showed that the model reproduces air temperature characteristics with average errors ≤1.3 ∘C. The past mean annual air temperature modelled experimentally for two sites in the Czech Republic hosting relict cryoturbation structures was between -7.0±1.9 and -3.2±1.5 ∘C, which is well in line with earlier reconstructions utilizing various palaeo-archives. These initial results are promising and suggest that the model could become a useful tool for reconstructing Quaternary palaeo-environments across vast areas of mid-latitudes and low latitudes where relict periglacial assemblages frequently occur, but their full potential remains to be exploited.

Reconstruction scheme for excitatory and inhibitory dynamics with quenched disorder: application to zebrafish imaging

An inverse procedure is developed and tested to recover functional and structural information from global signals of brains activity. The method assumes a leaky-integrate and fire model with excitatory and inhibitory neurons, coupled via a directed network. Neurons are endowed with a heterogenous current value, which sets their associated dynamical regime. By making use of a heterogenous mean-field approximation, the method seeks to reconstructing from global activity patterns the distribution of in-coming degrees, for both excitatory and inhibitory neurons, as well as the distribution of the assigned currents. The proposed inverse scheme is first validated against synthetic data. Then, time-lapse acquisitions of a zebrafish larva recorded with a two-photon light sheet microscope are used as an input to the reconstruction algorithm. A power law distribution of the in-coming connectivity of the excitatory neurons is found. Local degree distributions are also computed by segmenting the whole brain in sub-regions traced from annotated atlas.

Sound source localization \u2013 state of the art and new inverse scheme

Acoustic source localization techniques in combination with microphone array measurements have become an important tool for noise reduction tasks. A common technique for this purpose is acoustic beamforming, which can be used to determine the source locations and source distribution. Advantages are that common algorithms such as conventional beamforming, functional beamforming or deconvolution techniques (e.g., Clean-SC) are robust and fast. In most cases, however, a simple source model is applied and the Green’s function for free radiation is used as transfer function between source and microphone. Additionally, without any further signal processing, only stationary sound sources are covered. To overcome the limitation of stationary sound sources, two approaches of beamforming for rotating sound sources are presented, e.g., in an axial fan.Regarding the restrictions concerning source model and boundary conditions, an inverse method is proposed in which the wave equation in the frequency domain (Helmholtz equation) is solved with the corresponding boundary conditions using the finite element method. The inverse scheme is based on minimizing a Tikhonov functional matching measured microphone signals with simulated ones. This method identifies the amplitude and phase information of the acoustic sources so that the prevailing sound field can be with a high degree of accuracy.

Tomographic reconstruction of refractive index fields based on laser beam deflection measurement

Refractive index as one of the most important optical properties of materials is the key to utilize refractive index elements. However, it is very difficult to measure or estimate refractive index of media, especially for multi-dimensional inhomogeneous refractive index distribution. Therefore, an inverse scheme is presented for reconstructing refractive index field in rectangular gradient index medium based on ray deflection measurement in this work. A collection of rays from given positions along given directions transit the semitransparent medium and all exit boundary positions are recorded to construct the objective function of inverse problem. Runge–Kutta ray tracing technique is employed to simulate the curved ray path determined by Fermat principle in gradient-index medium. Conjugate gradient method as an inverse algorithm is used to reconstruct refractive index field. A series of simulation experiments are done to show the performance of the inverse strategy we developed. The results indicate that this inverse strategy for reconstructing refractive index field is accurate and effective.

Preisach-model-based position control of a shape-memory alloy linear actuator in the presence of time-varying stress

Tensioned shape-memory alloy (SMA) wires can repeatedly contract and extend, according to hysteretic loops defined by the shape-memory effect (SME), when subject to cyclic heating and cooling. Empirical evidence shows that these periodic hysteretic deformations are also a function of the loading stress applied to the tested wire. Therefore, to achieve accurate position control of an SMA wire-actuator, the SME hysteretic phenomenon in the presence of time-varying loading stress must be explicitly modeled in order to be compensated. To this end, we use a Preisach-model-based forward mapping that relates the time-varying exciting temperature and stress signals as inputs with the produced strain signal as the output, and whose parameters are experimentally estimated a priori through a series of steps in a nonlinear system identification process. Then, the identified parameters are employed by a Preisach-model-based inversion algorithm that is integrated into a feedforward inverse control scheme designed to mitigate the effects of hysteresis affecting the tested SMA wire. In the proposed scheme, the inverse controller reads two time-varying inputs, a strain reference and the known stress signal exciting the controlled SMA wire-actuator, and then it computes the corresponding temperature reference that, once enforced on the SMA material of the wire, generates the desired strain output. This approach to position tracking control can be realized using lightweight sensors and, as demonstrated in this paper through experimental results, is computationally efficient, which are the two most essential features required for the implementation of controllers on centimeter-scale autonomous robots. Using data obtained through real-time experiments, we demonstrate that the introduced position control scheme is highly effective and suitable to be used in future microrobotic applications. Furthermore, we show that the proposed methods for the system identification of the nonlinear hysteretic dynamics of SMA wires and for the synthesis of inverse controllers can be easily modified to be applied to the tracking control of SMA actuators thermally excited by means other than Joule heating.

On the unit Burr-XII distribution with the quantile regression modeling and applications

In this paper, we modify the Burr-XII distribution through the inverse exponential scheme to obtain a new two-parameter distribution on the unit interval called the unit Burr-XII distribution. The basic statistical properties of the newly defined distribution are studied. Parameters estimation is dealt and different estimation methods are assessed through two simulation studies. A new quantile regression model based on the proposed distribution is introduced. Applications of the proposed distribution and its regression model to real data sets show that the proposed models have better modeling capabilities than competing models.

Adaptive Pseudo Inverse Control for a Class of Nonlinear Asymmetric and Saturated Nonlinear Hysteretic Systems

This paper aims at eliminating the asymmetric and saturated hysteresis nonlinearities by designing hysteresis pseudo inverse compensator and robust adaptive dynamic surface control (DSC) scheme. The “pseudo inverse” means that an on-line calculation mechanism of approximate control signal is developed by applying a searching method to the designed temporary control signal where the true control signal is included. The main contributions are summarized as: 1) to our best knowledge, it is the first time to compensate the asymmetric and saturated hysteresis by using hysteresis pseudo inverse compensator because the construction of the true saturated-type hysteresis inverse model is very difficult; 2) by designing the saturated-type hysteresis pseudo inverse compensator, the construction of true explicit hysteresis inverse and the identifications of its corresponding unknown parameters are not required when dealing with the saturated-type hysteresis; 3) by combining DSC technique with the tracking error transformed function, the “explosion of complexity” problem in backstepping method is overcome and the prespecified tracking performance is achieved. Analysis of stability and experimental results on the hardware-in-loop platform illustrate the effectiveness of the proposed adaptive pseudo inverse control scheme.

Non-linear dynamic analysis of reinforced concrete structures with hybrid mixed stress finite elements

This paper presents and discusses a hybrid-mixed stress (HMS) finite element model for the static and dynamic analysis of 2D reinforced concrete frame structures. It is assumed a physically non-linear behaviour for both concrete and steel. In this model, both the stress and the displacement fields are approximated in the domain of each element. Complete sets of orthonormal Legendre polynomials are used as approximation functions. The use of these functions makes possible the definition of analytical closed form solutions for the computation of all structural operators when a physically linear behaviour is assumed and leads to the development of very effective p- refinement procedures. Due to the nature of the HMS formulation, it is possible to consider the use of both inverse and direct integration schemes at the cross-section level. The time integration procedure uses classical step-by-step techniques, such as Newmark and α-HHT method. The latter is used in order to supress some numerical noise that may occur in the iterative procedure involved in the solution of dynamic non-linear problems. Three different types of damage models, with and without permanent strains, are used to model concrete behaviour. To validate the model, to illustrate its potential and to assess its accuracy and efficiency, several numerical examples are discussed, and comparisons are made with solutions provided by other numerical techniques.

Capabilities of inverse scheme for acoustic source localization at low frequencies

We present the capabilities of a recently developed inverse scheme for source localization at low frequencies within an arbitrary acoustic environment. The inverse scheme is based on minimizing a Tikhonov functional matching measured microphone signals with simulated ones. We discuss the sensitivity of all involved parameters, the precision of geometry and physical boundary modeling for the numerical simulation using the finite element (FE) method, and the automatic determination of the positions of the recording microphones being distributed around the object of investigation. Finally, we apply the inverse scheme to a real-world scenario and compare the obtained results to state-of-the-art signal processing approaches, e.g. Clean-SC.

On Computer Implementation for Comparison of Inverse Numerical Schemes for Non-Linear Equations

In this research article, we interrogate two new modifications in inverse Weierstrass iterative method for estimating all roots of non-linear equation simultaneously. These modifications enables us to accelerate the convergence order of inverse Weierstrass method from 2 to 3. Convergence analysis proves that the orders of convergence of the two newly constructed inverse methods are 3. Using computer algebra system Mathematica, we find the lower bound of the convergence order and verify it theoretically. Dynamical planes of the inverse simultaneous methods and classical iterative methods are generated using MATLAB (R2011b), to present the global convergence properties of inverse simultaneous iterative methods as compared to classical methods. Some non-linear models are taken from Physics, Chemistry and engineering to demonstrate the performance and efficiency of the newly constructed methods. Computational CPU time, and residual graphs of the methods are provided to present the dominance behavior of our newly constructed methods as compared to existing inverse and classical simultaneous iterative methods in the literature.

Structural analysis of two-dimensional statically indeterminate structure problem with crack by transfer matrix method

A digital twin technique is regarded as the advanced maintenance technology for the aged facilities such as power plant, although it includes some difficulty for the practical usage. In this study, fundamental formulation for transfer matrix method (TMM) is conducted for the cracked structural problem as the first step to realize this technique. Furthermore, the inverse scheme based upon TMM theory formulated here is developed to identify crack depth and position.

Shear Stress Hardening Curves of AISI 4130 Steel at Ultra-high Strain Rates with Taylor Impact Tests

This paper is concerned with shear properties of AISI 4130 steel at various strain rates from the quasi-static state to ultra-high strain rates using a Taylor impact testing machine. Shear properties of metallic materials are known to be sensitive to the strain rate especially at high strain rates. In order to investigate hardening behavior under shear loading, in-plane shear tests are carried out at a wide range of strain rates from 10–3 s–1 to 103 s–1 with an INSTRON 5583 and a High Speed Material Testing Machine with a novel procedure to obtain hardening curves from shear tests. To induce shear deformation at ultra-high strain rates, a novel shear specimen applicable to Taylor impact tests is designed and then shear tests are conducted with a Taylor impact testing machine. Hardening curves are extrapolated by a dynamic hardening model and then calibrated by an experimental–numerical hybrid method with an inverse optimization scheme so that finite element analysis results match to shear tests results at ultra-high strain rates with the Taylor impact test. Shear fracture strains at ultra-high strain rates are also calibrated in the same manner. Calibrated flow stresses are higher than the extrapolated ones before calibration and calibrated shear fracture strains decrease more rapidly than the extrapolated ones before calibration at the ultra-high strain rate region.

Inverse kinematics solution and motion simulation of seven-degree-of-freedom ascending platform based on neural network

A pseudoinverse-based inverse kinetic solving scheme for 7-degree-of-freedom redundant aerial platform robotic arm, the scheme combines Minimum Velocity Norm scheme and damped least-square method, a close-loop damped minimum velocity norm scheme is set up which allows to avoid the joints’ limitation and to ensure the solution’s stability near the singularity position. Further, a genetic algorithm optimized BP neural network is built. Genetic algorithm can improve the training efficiency and avoid trapping in local optimal solution. The application of neural network can ensure the real-time of solution.

Real time uncertainty estimation in filling stage of resin transfer molding process

AbstractThis paper addresses the development of a digital twin, based on an inversion procedure, integrating process monitoring with simulation of composites manufacturing to provide a real time probabilistic estimation of process outcomes. A computationally efficient surrogate model was developed based on Kriging. The surrogate model reduces the computational time allowing inversion in real time. The tool was implemented in the filling stage of an resin transfer molding processing of a carbon fiber reinforced part resulting in the probabilistic prediction of unknown parameters. Flow monitoring data were acquired using dielectric sensors. The inverse scheme based on Markov Chain Monte Carlo uses input parameters, such as permeability and viscosity, as unknown stochastic variables. The scheme enhances the model by reducing model parameter uncertainty yielding an accurate on line estimation of process outcomes and critical events such as racetracking. The inverse scheme provides a prediction of filling duration with an error of about 5% using information obtained within the first 30% of the process.

Experimental Study on Inverse Model-Based Force Tracking Control of MR Damper

An explicit inverse model of a magnetorheological (MR) damper is established to track the desired force in real time through experimental analysis and mathematical modeling. An algebraic hyperbolic tangent model is used to present the nonlinear behavior of MR dampers to avoid dynamic evolution due to effortless invertibility. A characteristic method is utilized to obtain the initial parameters of this algebraic hyperbolic tangent model; subsequently, the main parameters of the algebraic model are selected as quadratic functions of the applied current such that the closed-form expressions of the inverse model can be obtained. Then, the response time including communication and electromagnetic interactions in the experiment is investigated and modeled. By combining the force-current and electromagnetic models, an inverse model-based force tracking scheme is proposed. A series of validated tests are performed to study the force tracking performance. The proposed model exhibits high fidelity for tracking variable desired forces in experiments. Further analysis on force tracking errors demonstrates the mitigation of errors in various current fluctuating methods.