Lorestan University
Mathematical Analysis and Convex Optimization
2717-0624
1
MODULE CONNES AMENABILITY FOR PROJECTIVE TENSOR PRODUCT AND Θ-LAU PRODUT OF BANACH ALGEBRAS
0
0
EN
Ebrahim
Tamimi
Velayat University
Ali
Ghaffari
Semnan University
Let A and B be Banach algebras with preduals A∗ and B∗ respectively, and
Θ : B → A be an algebraic homomorphism. In this paper, we derive some specific results
concerning the characterizations of module Connes amenability of certain Banach algebras.
Indeed, we investigate and give necessary and sufficient conditions for module Connes
amenability of projective tensor product Ab⊗B. Moreover, we characterize the module (ψ, θ)-
Connes amenability of Θ-Lau product A×Θ B, which ψ and θ are homomorphisms in A∗ and
B∗, respectively.
Lorestan University
Mathematical Analysis and Convex Optimization
2717-0624
1
Duality and $alpha$-duality of g-frames and fusion frames in Hilbert spaces
0
0
EN
Morteza
Mirzaee Azandaryani
University of Qom
Mahmood
Pourgholamhossein
University of Qom
In this paper, we get some results about $alpha$-duals of g-frames and fusion frames
in Hilbert spaces. Especially, the direct sums and tensor products for $alpha$-duals of g-frames and fusion
frames are considered and some of the obtained results for duals are generalized to $alpha$-duals.
Lorestan University
Mathematical Analysis and Convex Optimization
2717-0624
1
Infinitely many solutions for a class of nonlinear fractional equations with impulsive effects
0
0
EN
Mohammad
Abolghasemi
Razi University
The existence of infinitely many solutions for a class of impulsive
fractional boundary value problems is established.
Our approach is based on recent variational methods for smooth
functionals defined on reflexive Banach spaces. Some recent results are extended and improved. One example is
given in this paper to illustrate the main results.
Lorestan University
Mathematical Analysis and Convex Optimization
2717-0624
1
The Curvatures of R-quadratic Finsler Metrics
0
0
EN
Nasrin
Sadeghzadeh
University of Qom
Najmeh
SAJJADI MOGHADAM
University of Qom
This paper presents a study of $R$-quadratic Finsler spaces and a new class of Finsler metrics called $bar{D}$-metrics. The non-Riemannian curvatures of $R$-quadratic Finsler spaces and their special case, the $R$-quadratic generalized $(alpha, beta)$-metrics, are analyzed to gain insights into their behavior. The paper then introduces the $bar{D}$-metrics, which are shown to be a proper subset of the class of $GDW$-metrics and contain the class of Douglas metrics. This paper contributes to the understanding of $R$-quadratic Finsler spaces and their properties, and presents a novel class of Finsler metrics with potential applications in the field.
Lorestan University
Mathematical Analysis and Convex Optimization
2717-0624
1
Some Properties of 4-Dimensional Finsler Manifolds
0
0
EN
Akbar
Tayebi
In this paper, we study Cartan torsion, mean Cartan torsion and mean Landsberg
curvature of 4-dimensional Finsler metrics. First, we find the necessary and sufficient
condition under which a 4-dimensional Finsler manifold has bounded Cartan torsion and
mean Cartan torsion. Then, we show that a 4-dimensional Finsler manifold has relatively
isotropic mean Landsberg curvature if and only if it is Riemannian or the main scalars of
Finsler metric satisfy the certain conditions.
Lorestan University
Mathematical Analysis and Convex Optimization
2717-0624
1
Adjointations of Operator Inequalities for Sector Matrices
0
0
EN
Somayeh
Malekinejad
Payme Noor University
Hamideh
Mohammadzadehkan
Payme Noor University
In this paper, we first extend the well-known inequalities to the case of sector matrices. We also explore the adjointness of operator inequalities with binary operations for sector matrices. As a result of our exploration, we establish four distinct inequalities: a matrix inequality, a unitarily invariant norm inequality, a singular value inequality, and a determinant inequality. For example, we demonstrate that if $sigma_{1}$ and $ sigma_{2} $ are non-zero connections, and if $A$, $B$, and $C$ belong to $mathcal{S}_{alpha}$, such that
begin{equation*}
mathcal{R}left(A sigma_{1} (B sigma_{2} C)right) leq cos^{4}(alpha) mathcal{R}left((A sigma_{1} B) sigma_{2} (A sigma_{1} C)right),
end{equation*}
then
begin{equation*}
mathcal{R}left(A sigma_{1}^* (B sigma_{2}^* C)right)geq cos^{4}(alpha) mathcal{R}left((A sigma_{1}^* B) sigma_{2}^* (A sigma_{1}^* C)right).
end{equation*}
Lorestan University
Mathematical Analysis and Convex Optimization
2717-0624
1
Direct Product of IFMSN(G)
61
79
EN
Rasul
Rasuli
In this paper we introduced direct product of intuitionistic fuzzy multigroups of G under norms(IFMSN(G)) and we prove that it will be also IFMSN(G). Next we shall study some important properties and theorems for them. On the other hand we shall give the definition of the identity element, strong upper- lower and weak upper- lowerof them and study the main theorem for this. We shall also give new results on this subject. Also we define the concepts of conjugate and commutative of IFMSN(G) and investigate them under direct product. Finally, we organize them under group homomorphisms and we prove that the image and preimage of direct product of IFMSN(G) will be also IFMSN(G).
Lorestan University
Mathematical Analysis and Convex Optimization
2717-0624
1
A Watermarking Technique Using Finite Ridgelet Transform and Bidiagonal SVD
81
90
EN
Farzaneh
Salari
Department of Mathematics, Faculty of Sciences, Razi University
The ease with which digital images can be manipulated with readily available editing tools highlights the critical need for robust copyright protection mechanisms. Digital watermarking tackles this challenge by embedding imperceptible ownership information within images. However, striking a balance between transparency (invisibility of the watermark) and robustness against attacks remains a significant hurdle. This paper proposes a watermarking method that uses the combined strengths of Finite Ridgelet Transform (FRIT) and Bidiagonal Singular Value Decomposition (BSVD). Our approach first pre-processes the image using FRIT to extract prominent features. Subsequently, the watermark is imperceptibly embedded into the singular values obtained from the FRIT coefficients. Our evaluation using standard sample images confirms high visual quality and robustness to attacks for the proposed method.