Advances in Science and Technology Vol. 144

Abstract: The Dirac contour representation functions fk(z) and fb(z) are employed to represent theket states |f ⟩ and bra states ⟨f |, respectively, in quantum systems with a finite-dimensional Hilbertspace H_2j+1. The scalar product within these quantum systems is defined using a contour integral.Moreover, a numerical approach is utilized to examine the time evolution of both periodic and non-periodic systems, utilizing several Hamiltonian matrices. Furthermore, the stability of periodic systemsis investigated. In addition to these aspects, we study the most significant application of the Dirac con-tour representation, which is its capability to handle an extended Hilbert space, suitable for describingquantum physics at negative temperatures.

Abstract: Two-dimensional Poisson and convection-diffusion problems are solved by using three localization schemes implemented in the context of a Radial Basis Function (RBFs) collocation method. The first scheme uses the traditional RBF superpositions to approximate the problem variable in a defined stencil. The second scheme is the Partition of Unity strategy and it is used to obtain a representation of governing equations as a linear combination of RBFs local superpositions evaluated at neighbouring stencils. Weight functions are designed to capture the convection term effect on the solution. In the third scheme, an upwind strategy is included in the Partition of Unity scheme for solving the convection-diffusion problem by moving and deforming stencils based on velocity. For all schemes, stencils in the form of crosses, circles, and squares are considered, and Root mean square (RMS) is obtained as a function of shape parameter, nodal distribution size and stencil size. In the case of Poisson problems, the use of Partition of unity in circular configuration with no more than 37 nodes per stencil is recommended as far as a $c$ suitable range is obtained for each nodal distribution employed to avoid ill-conditioning issues.

Abstract: To perform the Hilbert transform H_il of a non-integrable function φ, such as φ(x) = 1, x, in a numerical calculation-friendly way, we propose a method of rewriting H_il in terms of the resolvent for a differential operator R whose eigenfunctions satisfy the orthogonality and the completeness, so that the resolvent kernel 〈x|R^-1y〉can be given by the eigenfunction expansion. We deal with two cases for the choice of R: one is the harmonic oscillator Hamiltonian, which is commutative with the Fourier transform F; and the other is such that is commutative with H_il itself. We show how the calculation of H_ilφ is made in a numerical calculation-friendly way, to find that Π_k=0,1 H_ilf_k (f_k (x) = x^k) satisfies quite a simple relation.

Abstract: Collaboration on knowledge is an essential channel for fostering the production and integration of knowledge. Knowledge collaboration user interactions can evolve into a network for knowledge collaboration. The "resources" variable has a significant effect on knowledge diffusion in the actual world. This paper examines the impact of resource production and consumption processes on the knowledge diffusion. We construct the knowledge diffusion model and determine the threshold for knowledge diffusion's propagation. We analyze the existing collaboration network dataset, Erdos Collaboration Network (ERDOS), and demonstrate that it exhibits clustering and small-world behavior. Using ERDOS data, we investigate the effect of resource generation and consumption processes on knowledge diffusion, as well as the role of self-learning and review mechanisms in this process. In addition, we find that the steady-state density of informed users is insensitive to both the benchmark knowledge diffusion rate and the maximum resource-mediated knowledge diffusion rate. In the actual world, managers can set the cost at the threshold, creating a win-win situation between the degree of knowledge diffusion and the benefits.

Abstract: Let C be a right submodule of a free finite right module F over a finite Frobenius ring R. In order to facilitate the decoding of C, one can replace F by the minimal projective submodule P of F, containing C. Once R is Frobenius, P coincides with the injective envelope E(C) of C in F and can be constructed as the maximal essential extension of C in F. The work describes the injective envelope E(C) of an arbitrary module C over a residue ring Zm modulo a natural number m. Any choice of a basis of F is associated with an inner product on F and allows to describe the relations of C in F by its left orthogonal group (⊥C, +) < (F, +). Bearing in mind that the relations (⊥P, +) of P = E(C) in F are contained in (⊥C, +), one realizes the relations of C in P by the quotient group (⊥C, +)/(⊥P, +). The decoding of C in P = E(C) makes use of a generating set of (⊥C, +)/(⊥P, +), which is obviously smaller than a generating set of (⊥C, +), needed for a decoding of C in F.The present note discusses also Mac Williams Extension Theorem for codes C in finite right projective modules P over a finite Frobenius ring R. It establishes that any Hamming isometry of C in P lifts to a monomial transformation g of a free cover F of P. Moreover, if the kernel of the epimorphism F onto P is invariant under g then the Hamming isometry of C in P extends to a Hamming isometry of P with itself.

Abstract: A method to extract lithologic interfaces and identify lithofacies based on the continuous wavelet transform (CWT), principal component analysis (PCA) and K-means clustering is proposed. Well-logs which can reflect lithofacies are selected by correlation analysis of multiple well-logs and their principal components are determined by PCA of them. The CWT of the 1st principal component (PC) based on the Gaussian wavelet at a fixed scale is used to detect temporary interfaces which include lithologic interfaces as well as those reflecting intra-bed variations. Interval signal is formed by averaging the 1st PC values between adjacent interfaces. Accurate and practical lithologic interfaces are reset by considering variances of the interval signal to select interfaces using the difference moduli of the interval signal. The K-means clustering in the main PC space is effectively employed to classify and identify sedimentary lithofacies from well log data. The application to well log data indicates that the method is useful and practical in detecting lithological interfaces and identifying lithofacies.

Abstract: The aim of this study was to assess the efficacy of an unmanned aerial vehicle-based remote sensing system for quantifying Bambara groundnut canopy state variables. Remotely sensed color infrared images and in-situ canopy state variables were collected during Malaysia's 2018/19 Bambara growing season at vegetative, flowering, podding, podfilling, maturity, and senescence stages. Five common vegetation indices (VIs) were derived from the images, yielding to single stage and cumulative VIs (∑VIs). The relationship between canopy state variables and single stage VIs/∑VIs was investigated using Pearson’s correlation. Linear parametric and non-linear non-parametric machine learning (ML) regressions were employed to estimate canopy state variables by using VIs/ ∑VIs as input features. The best correlation were observed at flowering stage. The ∑VIs from vegetative to senescence stage exhibited the most robust relationship with canopy state variables. CatBoostRegressor (CBR) excelled in training for all canopy state variables, however, it showed potential overfitting in testing. In contrast, Huber regression (HR) models provided consistent results in both training and testing. HR performance was comparable to that of the top-performing ML algorithms in estimation of groundnut crop variables.

Abstract: Building change detection is critical for urban management. Deep learning methods are more discriminatory and learnable than traditional change detection methods. But in complicated backdrop environments, it is still difficult to precisely pinpoint change zones of interest. Most change detection networks suffer from inaccurate feature characterization during feature extraction and fusion. As a solution to these problems, we propose the use of multilevel feature fusion in conjunction with aware networks to detect building changes. To obtain multi-scale change characteristics, our Context-awareness network employs multi-scale patch embedding. Followed by multi-path Transformers to enhance learning and extract more suitable features. The multi-scale fusion module can ensure semantic consistency of change features, making detected change regions more accurate. Visual comparisons and quantitative evaluations of our method showed that it outperformed seven popular change detection methods on the LEVIR-CD dataset.

Abstract: Hybrid Electric Propulsion Systems (HEPS) have grown to be a promising topic of research for Unmanned Aerial Vehicles (UAVs) applications as they combine the complimentary benefits of internal combustion engine and electric propulsion systems while reducing pollutant emissions. Controlling UAVs in any flight condition is essential for its successful application in practical missions. In general, hybrid-electric UAVs exhibit three flight modes: vertical flight mode, fixed-wing mode and transition mode. The transition control design from vertical and hover flights to fixed-wing flight mode or vice versa still remains a challenge due to the multiple nonlinearities in the model and the optimal design results have a strong effect on mission performance. In the present study, a numerical model was developed to enhance the flight performance and the transition control of a hybrid electric multi-rotor UAV during a specific flight mission. This model is based on the control of forward thrust, lift thrust, and pitch angle to achieve the speed, altitude, and position defined in the mission profile of the flight simulation. The simulation results show that, of the two applied control strategies, the one that separates the segment into one below stall speed and another above stall speed provides better performance and faster response during transition from vertical flight mode (VTOL) to horizontal fight mode (fixed-wing) and vice versa, where significant changes in speed and pitching angle occur.