Abstract Block ciphers, which serve as primary components of network security systems, play a crucial role in securely exchanging and communicating confidential information. Substitution boxes (S-boxes) are the most significant components of contemporary block ciphers. Inherently, the security strength of such cryptosystems relies on the quality of the S-box employed. The cryptographically strong S-boxes provide robustness and assurance of the security competency to block ciphers. To generate the strong S-boxes, a number of chaos-based methods have been investigated in the past decade. However, chaos-based methods are random approaches which are computationally intensive and don’t guarantee the generation of strong S-boxes. To meet the challenges of strong and fast S-box generation, a novel coset graphs based algebraic method is proposed to evolve robust and efficient S-box. Firstly, an initial S-box of decent cryptographic strength is generated by using the vertices of coset graphs for two Galois fields and a bijective function. After that, the initial S-box's robustness is improved by rearranging its columns in a particular manner, which yields the strong proposed S-box. The effectiveness of the proposed method is validated by comparing various attributes of our S-box against some recently investigated S-boxes. Additionally, the generated S-box is applied for image encryption and analyzed using the MLC criterions. The results show the suitability of the proposed S-box for secure multimedia applications.
Abstract In this article, the higher-order Haar wavelet collocation method (HCMHW) is investigated to solve linear and nonlinear integro-differential equations (IDEs) with two types of conditions: simple initial condition and the point integral condition. We reproduce and compare the numerical results of the conventional Haar wavelet collocation method (CMHW) with those of HCMHW, demonstrating the superior performance of HCMHW across various conditions. Both methods effectively handle different types of given conditions. However, numerical results reveal that HCMHW exhibits a faster convergence rate than CMHW. To address nonlinear IDEs, we employ the quasi-linearization technique. The computational stability of both methods is evaluated through various experiments. Additionally, the article provides examples to illustrate the overall performance and accuracy of HCMHW compared to CMHW for both linear and nonlinear IDEs.
In this study, we implemented the well-known Crank–Nicolson scheme for the numerical solution of Schrödinger equation. The numerical results converge to the exact solution because the Crank–Nicolson scheme is unconditionally stable and accurate. We have compared the results for different parameters with analytical solution, and it is found that the Crank–Nicolson scheme is suitable for the numerical solution of Schrödinger equations. Three different problems are included to verify the accuracy, stability, and capability of the Crank–Nicolson scheme.
Objectives: To determine the awareness and beliefs of medical students towards Corona disease and the COVID-19 vaccine and to assess the willingness to get vaccinated against COVID-19.
Methods: This was a cross sectional study conducted on undergraduate medical students at University College of Medicine and dentistry, University of Lahore (UOL). A self-developed questionnaire containing demographic information, 8 knowledge and attitude items and 11 items for perceptions and willingness to get COVID-19 vaccine was completed by 410 participants.
Results: More than ninety five percent of participants were aware of the cause, mode of transmission and mortality associated with corona disease; however, a handful of them knew about the purpose of using vaccine. Majority of the participants believed that COVID-19 vaccine will be effective and a good way to get protected from the disease. Regarding willingness to get cocid-19 vaccine, more than half of the participants wanted to be the first to get vaccinated but majority were concerned about the safety of COVID-19 vaccine.
Conclusion: The medical students of University College of Medicine and dentistry, University of Lahore (UOL) displayed an adequate level of knowledge and awareness towards COVID-19 and a positive attitude about COVID-19 vaccine. Our study noted a high level of COVID-19 vaccine acceptance among medical students, yet there were significant concerns about the safety of vaccine.
Data mining is mainly used to get information from a large amount of data. Process it to convert this information into understanding form predictions. Data minings algorithms have immense importance and chore in predictions. The data mining methods can uncover the unseen patterns (unsupervised), associations, and oddity from collected data. This information can enhance the decision-making processes for predictions. Data mining can be considered as a most suitable technology for predictions especially in predictions of students performance. The primary aim of this paper is to give a precise review on Applications of algorithms of data mining for prediction of students performance. In this paper, we presented a methodology in which we applied pre-processing on data to select best attributes in order to increase its accuracy then we applied different Algorithms to measure its accuracy and found out that Random Forest algorithm gives best results.
In this article, a hybrid numerical method based on Haar wavelets and finite differences is proposed for shock ridden evolutionary nonlinear time‐dependent partial differential equations (PDEs). A linear procedure using Taylor expansions is adopted to linearize the nonlinearity. The Euler difference scheme is used to discretize the time derivative part of the PDE. The PDE is converted into full algebraic form, once the space derivatives are replaced by finite Haar series. Convergence analysis is performed both in space and time, and computational stability of the proposed method is also discussed. Different benchmark cases related to 1‐D and 2‐D Burgers' type equations are considered to verify the theory. The proposed method is also compared numerically with existing methods in the literature.
In this paper, a local meshless method (LMM) based on radial basis functions (RBFs) is utilized for the numerical solution of various types of PDEs. This local approach has flexibility with respect to geometry along with high order of convergence rate. In case of global meshless methods, the two major deficiencies are the computational cost and the optimum value of shape parameter. Therefore, research is currently focused towards localized RBFs approximations, as proposed here. The proposed local meshless procedure is used for spatial discretization, whereas for temporal discretization, different time integrators are employed. The proposed local meshless method is testified in terms of efficiency, accuracy and ease of implementation on regular and irregular domains.
This study delves into the nonlocal inverse boundary-value problem for a second-order, two-dimensional parabolic equation within a rectangular domain.The primary focus is to identify the unknown coefficient and propose a resolution to the problem.The second-order, two-dimensional convection equation is addressed through the direct application of the alternating direction explicit (ADE) finite difference scheme.An adaptation of the ADE scheme is formulated to accommodate mixed boundary conditions, utilizing suitable expressions at the boundaries.Furthermore, unconditional stability is scrutinized through a series of examples.Each ADE scheme typically comprises two substeps, known as upward and downward sweeps, during which values computed at the new time level are incorporated into the discretization template.The inverse problem is restructured into a nonlinear regularized least-square optimization problem, with a defined boundary for the unknown factor, and is effectively resolved using the MATLAB subroutine lsqnonlin from the optimization toolbox.Given the typically ill-posed nature of the problem under investigation, where minor errors in the input data can significantly affect the output, Tikhonov's regularization technique is employed to produce stable and regularized results.
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