Class Of Schemes Research Articles

Tools and Techniques to Accelerate Crop Breeding.

As climate changes and a growing global population continue to escalate the need for greater production capabilities of food crops, technological advances in agricultural and crop research will remain a necessity. While great advances in crop improvement over the past century have contributed to massive increases in yield, classic breeding schemes lack the rate of genetic gain needed to meet future demands. In the past decade, new breeding techniques and tools have been developed to aid in crop improvement. One such advancement is the use of speed breeding. Speed breeding is known as the application of methods that significantly reduce the time between crop generations, thereby streamlining breeding and research efforts. These rapid-generation advancement tactics help to accelerate the pace of crop improvement efforts to sustain food security and meet the food, feed, and fiber demands of the world's growing population. Speed breeding may be achieved through a variety of techniques, including environmental optimization, genomic selection, CRISPR-Cas9 technology, and epigenomic tools. This review aims to discuss these prominent advances in crop breeding technologies and techniques that have the potential to greatly improve plant breeders' ability to rapidly produce vital cultivars.

Topology optimization of incompressible structures subject to fluid–structure interaction

In this work, an algorithm for topology optimization of incompressible structures is proposed, in both small and finite strain assumptions and in which the loads come from the interaction with a surrounding fluid. The algorithm considers a classical block-iterative scheme, in which the solid and the fluid mechanics problems are solved sequentially to simulate the interaction between them. Several stabilized mixed finite element formulations based on the Variational Multi-Scale approach are considered to be capable of tackling the incompressible limit for the numerical approximation of the solid. The fluid is considered as an incompressible Newtonian fluid flow which is combined with an Arbitrary-Lagrangian Eulerian formulation to account for the moving part of the domain. Several numerical examples are presented and discussed to assess the robustness of the proposed algorithm and its applicability to the topology optimization of incompressible elastic solids subjected to Newtonian incompressible fluid loads.

Positioning dynamic polymeric materials within the modern polymer economy: From application to recycling and circularity

AbstractInnovations in dynamic polymeric materials offer prospects to improve the circularity and lower the environmental impact of the modern polymer economy. These materials are also beginning to blur the distinction between re‐use and recycling methods since the bulk material properties of the material may be rationally changed after applying a stimulus or performing a controlled chemical reaction. In this Perspective, we propose that dynamic polymers denote a unique class of versatile post‐consumer polymer waste, which shares similarities to emergent upcycling approaches while also offering additional opportunities within more classical recycling schemes. A brief overview of stimuli‐responsive polymers is presented where illustrative examples are discussed within the context of developing practical materials. Dynamic covalent polymeric materials are then highlighted, along with emerging techniques such as polymer editing, with a focus on recent reports demonstrating rational manipulation of bulk material properties. Finally, we discuss these examples alongside modern recycling methods and explore how dynamic polymers could perform in this sphere.

Robust biometric identity authentication scheme using quantum voice encryption and quantum secure direct communications for cybersecurity

A significant problem facing cybersecurity is that most client/server identity authentication schemes depend on computational complexity which is recently challenged by the super exponential computational abilities of quantum computers. Quantum cryptography with its quantum mechanics principles solves this problem and provides mathematically un-hackable secure communication for the quantum computers epoch. Biometric authentication has a big challenge related to its protection as it has to be submitted and stored in encrypted form. Unfortunately, most existing biometric cryptosystems rely on classical cryptography, so they are insecure in quantum era. This problem is solved in this paper by introducing a novel three-factor biometric quantum identity authentication scheme combining something you know (password), something you produce (client’s voice), and something you are (client’s face image) is proposed. The scheme consists of two phases: client enrollment and client login/authentication. The methodology is to use in the enrollment phase, two layers of quantum encryption for the client’s voice signal. Each layer consists of two simple quantum circuits of SWAP and C-NOT quantum gates respectively using a different pseudorandom key obtained from a cellular automata (CA) pseudorandom generator. The proposed scheme has many merits. Firstly, it introduces a new design of muti-factors quantum biometric authentication scheme as the biometric voice data is processed, transmitted, and stored at the server database in an encrypted unconditionally secure quantum form which provides parallel processing, real-time communications, inherent level of security against attacks, tamper-proof security and exponential powerful storage capability due to the quantum properties. Secondly, the proposed scheme achieves double-layers security by combing quantum voice encryption and quantum secure direct communication in one process such that the quantum channel eavesdropper cannot obtain any valuable information in case of information leakage. Thirdly, the distribution and management of encryption key problem is solved as there is no need for key exchange prior to communication. Fourthly, it achieves high communication efficiency as although it is a three-factor biometric identity authentication, only one biometric data is sent in quantum encrypted form to the server. Fifthly, the numerical simulations showed that the proposed scheme has large key space, high key sensitivity and more robust performance against different types of attacks compared to other existing classical and quantum voice encryption schemes. Finally, as an identity authentication method, the proposed scheme achieves identification accuracy of 100% with zero False Rejection Rate (FRR) and zero False acceptance rate (FAR) which is perfect.

A new high-order shock-capturing TENO scheme combined with skew-symmetric-splitting method for compressible gas dynamics and turbulence simulation

The high-order shock-capturing scheme is one of the main building blocks for the simulation of the compressible fluid characterized by strong shockwaves and broadband length scales. However, the classical shock-capturing scheme fails to perform long-time stable and non-dissipative simulations since the quadratic invariants associated with the conservation equations cannot be conserved as a result of the inherent numerical dissipation. Additionally, the overall computational cost for classical shock-capturing schemes is quite expensive as a result of the time-consuming local characteristic decomposition and the nonlinear-weights computing process. In this work, based on a new efficient discontinuity indicator, which distinguishes the non-smooth high-wavenumber fluctuations and discontinuities from smooth scales in the wavenumber space, a paradigm of high-order shock-capturing scheme by recasting the non-dissipative skew-symmetric-splitting method with newly optimized dispersion property for smooth flow scales and invoking the nonlinear targeted ENO (TENO) schemes for non-smooth discontinuities is proposed. The resulting TENO-S scheme not only successfully performs long-time stable computations for smooth flows without numerical dissipation, but also recovers the robust shock-capturing capabilities with adaptive numerical dissipation. Without the necessity of parameter tuning case by case, extensive benchmark simulations involving a wide range of flow length scales and strong discontinuities demonstrate that the proposed TENO-S scheme performs significantly better than the straightforward deployment of WENO/TENO-family schemes with better spectral property and higher computational efficiency.

A POD based extrapolation DG time stepping space-time FE method for parabolic problems

Based on the proper orthogonal decomposition technique, a new reduced-order discontinuous time stepping space-time finite element extrapolation iterative scheme is constructed to solve two-dimensional parabolic problems, which includes very few degrees of freedom but holds sufficiently high accuracy. A reduced space-time projection operator is defined, and its related error estimations are discussed. Then, the error estimate between the classical scheme solution and the reduced-basis scheme solution, and the a priori error estimate for the reduced-basis scheme are derived, respectively. These error estimates are analyzed by using the technique of combining Radau quadrature rule with finite element method, without considering any dual problems. The algorithm implementation of the reduced-order extrapolation iterative scheme is also provided. Finally, a numerical example is presented. The numerical results are consistent with theoretical ones. Moreover, it is shown that the new reduced-order extrapolation iterative scheme, by comparing to the standard approach, can reduce CPU time without loss of accuracy. Therefore, it is feasible and efficient for solving parabolic problems.

A secure and lightweight cloud data deduplication scheme with efficient access control and key management

Data deduplication technology is extensively employed to enhance the storage efficiency of cloud servers by eliminating redundant files. Cloud users commonly encrypt their data prior to uploading it to the server. Conventional encryption algorithms, however, lead to the encryption of duplicated data from different users into distinct ciphertexts. Consequently, these ciphertexts must be stored in the cloud since the cloud server cannot identify such duplicated data. In this paper, we introduce a hybrid cloud-based secure deduplication scheme tailored for implementation on large-scale data systems. Specifically, our approach leverages ciphertext-policy attribute-based encryption (CP-ABE), which enables us to establish access control and key management via a private cloud server. Simultaneously, we leverage a public cloud server to cater to enterprises and groups seeking secure data storage. Notably, our approach ensures mutual zero-interaction verification between both public and private cloud servers through ElGamal encryption, thereby guaranteeing data unforgeability. The security assessment illustrates that our proposed approach ensures both data privacy and integrity. We also show that the approach resists brute-force attacks on the dictionary, prevents malicious users from deceiving cloud servers to return incorrect ciphertext, and achieves secure and efficient access control and key management. Furthermore, functional and performance evaluation underscores the superiority of our method over five other classical data deduplication schemes. Under the premise of having more comprehensive security settings, the performance of the scheme still maintains a good level at every stage.

Approximately well-balanced Discontinuous Galerkin methods using bases enriched with Physics-Informed Neural Networks

This work concerns the enrichment of Discontinuous Galerkin (DG) bases, so that the resulting scheme provides a much better approximation of steady solutions to hyperbolic systems of balance laws. The basis enrichment leverages a prior – an approximation of the steady solution – which we propose to compute using a Physics-Informed Neural Network (PINN). To that end, after presenting the classical DG scheme, we show how to enrich its basis with a prior. Convergence results and error estimates follow, in which we prove that the basis with prior does not change the order of convergence, and that the error constant is improved. To construct the prior, we elect to use parametric PINNs, which we introduce, as well as the algorithms to construct a prior from PINNs. We finally perform several validation experiments on four different hyperbolic balance laws to highlight the properties of the scheme. Namely, we show that the DG scheme with prior is much more accurate on steady solutions than the DG scheme without prior, while retaining the same approximation quality on unsteady solutions.

Faith Renewed: Validation of the LTA_Classic Conceptual Complexity Coding Scheme

Abstract Following the creation of the LTA_Classic automated coding schemes for Margaret Hermann’s approach to leadership analysis, LTA_Classic has become a widely used tool for researching the individual differences between leaders and their policies in the last two decades. However, there has been no prior published assessment of the validity of the LTA_Classic coding scheme. The result of this validity assessment is a revised coding scheme (CC_2023) with roughly double the accuracy of the LTA_Classic CC coding scheme and a corresponding increase in statistical power. At the same time, correlation by document (N = 44,173) for LTA_Classic CC and CC_2023 is r = 0.7305 with a 95 percent confidence interval of 0.7261 ⇐ r ⇐ 0.7348 and p < 0.0000, indicating that the CC_2023 coding scheme is convergent with the LTA_Classic coding scheme and prior results are likely to be replicable using CC_2023.

Non-Polynomial Collocation Spectral Scheme for Systems of Nonlinear Caputo–Hadamard Differential Equations

In this paper, we provide a collocation spectral scheme for systems of nonlinear Caputo–Hadamard differential equations. Since the Caputo–Hadamard operators contain logarithmic kernels, their solutions can not be well approximated using the usual spectral methods that are classical polynomial-based schemes. Hence, we construct a non-polynomial spectral collocation scheme, describe its effective implementation, and derive its convergence analysis in both L2 and L∞. In addition, we provide numerical results to support our theoretical analysis.

Non-Commutative Classical and Quantum Fractionary Cosmology: FRW Case

In this work, we will explore the effects of non-commutativity in fractional classical and quantum schemes using the flat Friedmann–Robertson–Walker (FRW) cosmological model coupled to a scalar field in the K-essence formalism. In previous work, we have obtained the commutative solutions in both regimes in the fractional framework. Here, we introduce non-commutative variables, considering that all minisuperspace variables qnci do not commute, so the symplectic structure was modified. In the quantum regime, the probability density presents a new structure in the scalar field corresponding to the value of the non-commutative parameter, in the sense that this probability density undergoes a shift back to the direction of the scale factor, causing classical evolution to arise earlier than in the commutative world.

Enhancing DC microgrid performance through machine learning‐optimized droop control

AbstractA machine learning‐based optimized droop method is suggested here to simultaneously reduce the production cost (PC) and power line losses (PLL) for a class of direct current (DC) microgrids (MGs). Traditionally, a communication‐less technique known as the hybrid droop method has been employed to decrease PC and PLL in DC MGs. However, achieving the desired reduction in either PC or PLL requires arbitrary adjustments of weighting coefficients for each distributed generator in the conventional hybrid droop method. To address this challenge, this paper introduces a systematic approach that capitalizes on the benefits of artificial intelligence to accurately predict both the PC and PLL in a DC MG. Furthermore, an optimization technique relying on the gradient descendent method is employed to independently optimize both PC and PLL for each scenario. The effectiveness of the proposed method is confirmed through a comparative study with classical and hybrid droop coordination schemes under various scenarios such as rapid load changes.

Advanced Gyrotron Concepts for Spectroscopic Applications

Background: Currently, some modern spectroscopic applications require sub-terahertz and terahertz continuous-wave electromagnetic radiation sources with power levels from 0.1 to 100 W. Gyrotron, a powerful high-frequency vacuum electronics device, is considered one of the promising sources for these aims. Methods: Modification of the gyrotron design promotes the widespread use of these devices for DNP/NMR spectroscopy. Results: Promising non-canonical concepts are presented, the features of which compare favorably with the classical gyrotron scheme. Conclusion: The gyrotron concepts we considered allow us to master the terahertz range and develop a unique gyrotron installation for each scientific group, considering the specifics of their scientific research.

A pragma based C++ framework for hybrid quantum/classical computation

Quantum computers promise exponential speed ups over classical computers for various tasks. This emerging technology is expected to have its first huge impact in High Performance Computing (HPC), as it can solve problems beyond the reach of HPC. To that end, HPC will require quantum accelerators, which will enable applications to run on both classical and quantum devices, via hybrid quantum-classical nodes. Hybrid quantum-HPC applications should be scalable, executable on Quantum Error Corrected (QEC) devices, and could use quantum-classical primitives. However, the lack of scalability, poor performances, and inability to insert classical schemes within quantum applications has prevented current quantum frameworks from being adopted by the HPC community.This paper specifies the requirements of a hybrid quantum-classical framework compatible with HPC environments, and introduces a novel hardware-agnostic framework called Q-Pragma. This framework extends the classical programming language C++ heavily used in HPC via the addition of pragma directives to manage quantum computations.

A new compact scheme-based Lax–Wendroff method for high fidelity simulations

The classical Lax–Wendroff (LW) method employs explicit second order central difference schemes to solve partial differential equations. Recently, the authors in Sengupta et al. (2023) have identified numerical parameter ranges in performing large eddy simulation (LES) using this classical LW method. In a bid to improve these numerical parameter ranges for high fidelity computations, a new non-uniform grid based compact scheme for LW method (NUCLW) is developed here. This new method uses sixth order non-uniform compact scheme (NUC6) for the first and higher order derivatives. Reported global spectral analysis confirms substantial improvement in the resolution and accuracy of NUCLW scheme over the classical LW scheme. A significant advantage of the present scheme is its ability to compute solutions for non-uniform, structured grids, and that does not suffer degradation in accuracy. The potential of the NUCLW scheme for high accuracy computations is demonstrated by solving 2D incompressible Navier–Stokes equations for the benchmark unsteady flow inside a square lid driven cavity problem for a subcritical Reynolds number of 3200 and a post-critical Reynolds number of 10,000 and simulating the instability of the Taylor–Green vortex problem. These demonstrate the ability of the NUCLW scheme to solve the Navier–Stokes equations for high fidelity simulations such as LES/DNS with enhanced ranges of numerical parameters with respect to enhanced accuracy and faster computations.

Research of cognitive data processing in radio communication systems with permutation decoding

Background. The need to use permutation decoding tools in radio communication systems is explained by the increased error correction capabilities of this method. In this case, complex matrix calculations during the search for equivalent codes according to the classical scheme of permutation decoding are replaced by a list of ready-made solutions. These solutions are calculated a priori and entered into the cognitive cards of the decoder processor, which makes the method a convenient tool in the procedure for ensuring information reliability when controlling, for example, unmanned vehicles via radio channels. In fact, matrix calculations on board are replaced by searching the list of cognitive maps for the right solution corresponding in real time to the current permutation of reliable character numerators. However, data processing in the decoder’s cognitive map requires a special description.
 Aim. The study of methods for identifying permutations of character numerators of code vectors in order to effectively transform them in a system of cognitive maps of a permutation decoder.
 Methods. The paper reveals the subtle structure of cognitive maps of productive and unproductive permutations of numerators, which allows on a regular basis to obtain an alternative solution for switching to a set of productive permutations when the receiver receives an unproductive permutation, thereby excluding the use of trial and error.
 Results. The efficiency of the permutation decoder increases due to the implementation of permutations that were originally included in a set of solutions introduced into the cognitive map of unproductive permutations.
 Conclusion. A family of microcontrollers is proposed to implement the principle of interaction of cognitive maps with a system of alternative solutions.

Fuzzy Modeling Framework Using Sector Non-Linearity Techniques for Fixed-Wing Aircrafts

This paper presents a mathematical modeling approach utilizing a fuzzy modeling framework for fixed-wing aircraft systems with the goal of creating a highly desirable mathematical representation for model-based control design applications. The starting point is a mathematical model comprising fifteen non-linear ordinary differential equations representing the dynamic and kinematic behavior applicable to a wide range of fixed-wing aircraft systems. Here, the proposed mathematical modeling framework is applied to the AIRBUS A310 model developed by ONERA. The proposed fuzzy modeling framework takes advantage of sector non-linearity red techniques to recast all the non-linear terms from the original model to a set of combined fuzzy rules. The result of this fuzzification is a more suitable mathematical description from the control system design point of view. Therefore, the combination of this fuzzy model and the wide range of control techniques available in the literature for such kind of models, like parallel and non-parallel distributed compensation control laws using linear matrix inequality optimization, enables the development of control algorithms that guarantee stability conditions for a wide range of operations points, avoiding the classical gain scheduling schemes, where the stability issues can be extremely challenging.

3D numerical simulation of frequency-domain elastic wave equation with a compact second-order scheme

Finite-difference frequency-domain (FDFD) modeling has gained popularity in recent years. However, its main drawback lies in the need to solve large sparse linear systems, which is computationally expensive, especially for 3D elastic wave simulations. The existing elastic wave optimal schemes improve the simulation accuracy at the cost of using large-sized stencils or high-order finite-difference (FD) operators, and most of them only consider equal grid spacing and solid media. To address these issues, we have proposed a compact second-order scheme for simulating 3D elastic wave propagation. Starting from the second-order FD discretization of the first-order velocity-stress expression, the compact discrete scheme of the second-order elastic wave equation is obtained by using a parsimonious staggered-grid strategy to eliminate the stress variables. In this way, the scheme preserves the ability to handle high-contrast velocity and liquid-solid media, and has a more compact and sparse impedance matrix than existing schemes, which helps save computational costs. We also use an antilumped mass strategy to further improve the modeling accuracy. Dispersion analysis indicates that our compact second-order scheme has better accuracy than the classic second-order scheme, and even better accuracy than the average derivative 27-point scheme at large Poisson's ratio. Compared with the existing 3D elastic wave schemes, the compact second-order scheme has advantages in computational cost for the same grid. Finally, we employ these schemes to implement 3D numerical simulations, validating the effectiveness of our proposed scheme.

Explicit P1 Finite Element Solution of the Maxwell-Wave Equation Coupling Problem with Absorbing b. c.

In this paper, we address the approximation of the coupling problem for the wave equation and Maxwell’s equations of electromagnetism in the time domain in terms of electric field by means of a nodal linear finite element discretization in space, combined with a classical explicit finite difference scheme for time discretization. Our study applies to a particular case where the dielectric permittivity has a constant value outside a subdomain, whose closure does not intersect the boundary of the domain where the problem is defined. Inside this subdomain, Maxwell’s equations hold. Outside this subdomain, the wave equation holds, which may correspond to Maxwell’s equations with a constant permittivity under certain conditions. We consider as a model the case of first-order absorbing boundary conditions. First-order error estimates are proven in the sense of two norms involving first-order time and space derivatives under reasonable assumptions, among which lies a CFL condition for hyperbolic equations. The theoretical estimates are validated by numerical computations, which also show that the scheme is globally of the second order in the maximum norm in time and in the least-squares norm in space.

High-order finite volume multi-resolution WENO schemes with adaptive linear weights on triangular meshes

This paper presents high-order finite volume multi-resolution weighted essentially non-oscillatory schemes with adaptive linear weights to solve hyperbolic conservation laws on triangular meshes. They are abbreviated as the ALW-MR-WENO schemes. The novel third-order, fourth-order, and fifth-order ALW-MR-WENO schemes are designed by applying two unequal-sized hierarchical central stencils in comparison to the classical WENO schemes which utilize many equal-sized upwind biased/central stencils. With the application of one simple condition, only two linear weights are automatically adjusted to be positive values on condition that their summation is one. The novel finite volume ALW-MR-WENO schemes could maintain the designed order of accuracy in smooth areas and reduce to the first-order accuracy so as to keep essentially non-oscillatory properties around strong discontinuities. So it is the first time that any high-order WENO schemes with the application of only two unequal-sized stencils are obtained on triangular meshes. And the major benefits are their efficiency, compactness, and simplicity in large scale engineering applications on unstructured meshes. Finally, several tests are used to indicate the effectiveness of these new finite volume WENO schemes.