arXiv subjects

Maryam Saadati

Publications and source records attributed to Maryam Saadati.

6 recordsLinked to original sources

arXiv2024

Robust optimality and duality for composite uncertain multiobjective optimization in Asplund spaces with its applications

This article is devoted to investigate a nonsmooth/nonconvex uncertain multiobjective optimization problem with composition fields (CUP) for brevity) over arbitrary Asplund spaces. Employing some advanced techniques of variational analysis and generalized differentiation, we establish necessary optimality conditions for weakly robust efficient solutions of (CUP) in terms of the limiting subdifferential. Sufficient conditions for the existence of (weakly) robust efficient solutions to such a problem are also driven under the new concept of pseudo-quasi convexity for composite functions. We formulate a Mond-Weir-type robust dual problem to the primal problem (CUP), and explore weak, strong, and converse duality properties. In addition, the obtained results are applied to an approximate uncertain multiobjective problem and a composite uncertain multiobjective problem with linear operators.

math.OC↗

arXiv2023

Unveiling the Complexity of Neural Populations: Evaluating the Validity and Limitations of the Wilson-Cowan Model

The population model of Wilson-Cowan is perhaps the most popular in the history of computational neuroscience. It embraces the nonlinear mean field dynamics of excitatory and inhibitory neuronal populations provided via a temporal coarse-graining technique. The traditional Wilson-Cowan equations exhibit either steady-state regimes or else limit cycle competitions for an appropriate range of parameters. As these equations lower the resolution of the neural system and obscure vital information, we assess the validity of mass-type model approximations for complex neural behaviors. Using a large-scale network of Hodgkin-Huxley style neurons, we derive implicit average population dynamics based on mean field assumptions. Our comparison of the microscopic neural activity with the macroscopic temporal profiles reveals dependency on the binary state of interacting subpopulations and the random property of the structural network at the Hopf bifurcation points when different synaptic weights are considered. For substantial configurations of stimulus intensity, our model provides further estimates of the neural population's dynamics official, ranging from simple periodic to quasi-periodic and aperiodic patterns, as well as phase transition regimes. While this shows its great potential for studying the collective behavior of individual neurons particularly concentrating on the occurrence of bifurcation phenomena, we must accept a quite limited accuracy of the Wilson-Cowan approximations-at least in some parameter regimes. Additionally, we report that the complexity and temporal diversity of neural dynamics, especially in terms of limit cycle trajectory, and synchronization can be induced by either small heterogeneity in the degree of various types of local excitatory connectivity or considerable diversity in the external drive to the excitatory pool.

q-bio.NC↗

arXiv2022

Approximate solutions for robust multiobjective optimization programming in Asplund spaces

In this paper, we study a nonsmooth/nonconvex multiobjective optimization problem with uncertain constraints in arbitrary Asplund spaces. We first provide necessary optimality condition in a fuzzy form for approximate weakly robust efficient solutions and then establish necessary optimality theorem for approximate weakly robust quasi-efficient solutions of the problem in the sense of the limiting subdifferential by exploiting a fuzzy optimality condition in terms of the Frechet subdifferential. Sufficient conditions for approximate (weakly) robust quasi-efficient solutions to such a problem are also driven under the new concept of generalized pseudo convex functions. Finally, we address an approximate Mond-Weir-type dual robust problem to the reference problem and explore weak, strong, and converse duality properties under assumptions of pseudo convexity.

math.OC↗

arXiv2022

Optimality conditions for robust nonsmooth multiobjective optimization problems in Asplund spaces

We employ a fuzzy optimality condition for the Frechet subdifferential and some advanced techniques of variational analysis such as formulae for the subdifferentials of an infinite family of nonsmooth functions and the coderivative scalarization to investigate robust optimality condition and robust duality for a nonsmooth/nonconvex multiobjective optimization problem dealing with uncertain constraints in arbitrary Asplund spaces. We establish necessary optimality conditions for weakly and properly robust efficient solutions of the problem in terms of the Mordukhovich subdifferentials of the related functions. Further, sufficient conditions for weakly and properly robust efficient solutions as well as for robust efficient solutions of the problem are provided by presenting new concepts of generalized convexity. Finally we formulate a Mond-Weir-type robust dual problem to the reference problem, and examine weak, strong, and converse duality relations between them under the pseudo convexity assumptions.

math.OC↗

arXiv2021

An Enterprise Architecture Framework for E-learning

With a trend toward becoming more and more information and communication based, learning services and processes were also evolved. E-learning comprises all forms of electronically supported learning and teaching. The information and communication systems serve as a fundamental role to implement these learning processes. In the typical information-driven organizations, the E-learning is part of a much larger platform for applications and data that extends across the Internet and intranet/extranet. In this respect, E-learning has brought about an inevitable tendency to lunge towards organizing their information based activities in a comprehensive way. Building an Enterprise Architecture (EA) undoubtedly serves as a fundamental concept to accomplish this goal. In this paper, we propose an EA for E-learning information systems. The presented framework helps developers to design and justify completely integrated learning and teaching processes and information systems which results in improved pedagogical success rate.

cs.CY↗

arXiv2021

The effects of beta-cell mass and function, intercellular coupling, and islet synchrony on $\textrm{Ca}^{2+}$ dynamics

Type 2 diabetes (T2D) is a challenging metabolic disorder characterized by a substantial loss of $β$-cell mass and alteration of $β$-cell function in the islets of Langerhans, disrupting insulin secretion and glucose homeostasis. The mechanisms for deficiency in $β$-cell mass and function during the hyperglycemia development and T2D pathogenesis are complex. To study the relative contribution of $β$-cell mass to $β$-cell function in T2D, we make use of a comprehensive electrophysiological model of human $β$-cell clusters. We find that defect in $β$-cell mass causes a functional decline in single $β$-cell, impairment in intra-islet synchrony, and changes in the form of oscillatory patterns of membrane potential and intracellular $\textrm{Ca}^{2+}$ concentration, which can lead to changes in insulin secretion dynamics and in insulin levels. The model demonstrates a good correspondence between suppression of synchronizing electrical activity and published experimental measurements. We then compare the role of gap junction-mediated electrical coupling with both $β$-cell synchronization and metabolic coupling in the behavior of $\textrm{Ca}^{2+}$ concentration dynamics within human islets. Our results indicate that inter-$β$-cellular electrical coupling depicts a more important factor in shaping the physiological regulation of islet function and in human T2D. We further predict that varying the whole-cell conductance of delayed rectifier $\textrm{K}^{+}$ channels modifies oscillatory activity patterns of $β$-cell population lacking intercellular coupling, which significantly affect $\textrm{Ca}^{2+}$ concentration and insulin secretion.

physics.bio-ph↗