Search results

In structural mechanics, systems with damping factor get converted to nonlinear eigenvalue problems (NEPs), namely, quadratic eigenvalue problems. Generally, the parameters of NEPs are considered as crisp values but because of errors in measurement, observation or maintenance-induced errors, the parameters may have uncertain bounds of values, and such uncertain bounds may be considered in terms of closed intervals. As such, this paper aims to deal with solving nonlinear interval eigenvalue problems (NIEPs) with respect to damped spring-mass systems having interval parameters.

Two methods, namely, linear sufficient regularity perturbation (LSRP) and direct sufficient regularity perturbation (DSRP), have been proposed for solving NIEPs based on sufficient regularity perturbation method for intervals. LSRP may be used for solving NIEPs by linearizing the eigenvalue problems into generalized interval eigenvalue problems, and DSRP may be considered as a direct solution procedure for solving NIEPs.

LSRP and DSRP methods help in computing the lower and upper eigenvalue and eigenvector bounds for NIEPs which contain the crisp eigenvalues. Further, the DSRP method is computationally efficient compared to LSRP.

The efficiency of the proposed methods has been validated by example problems of NIEPs. Moreover, the procedures may be extended for other nonlinear interval eigenvalue application problems.

Aims to solve Fredholm and Volterra non‐linear integral equations of the first kind. Uses the Adomian method, but since these equations are not under the canonical form u‐Nu = f, proposes some transformations for reducing the integral equations to integral equations of the second kind, much more appropriate. Uses a perturbation method for Fredholm equations. Concerning Volterra equations, uses a differentiation of the original equation, under sufficient regularity conditions, for obtaining a canonical form of Adomian.

Science of systems requires a specific and constructive mathematical model and language, which describe jointly such systemic categories as adaptation, self‐organization, complexity, evolution, and bring the applied tools for building a system model for each specific object of a diverse nature. This formalism should be connected directly with a world of information and computer applications of systemic model, developed for a particular object. The considered information systems theory (IST) is aimed at building a bridge between the mathematical systemic formalism and information technologies to develop a constructive systemic model of revealing information regularities and specific information code for each object.

To fulfill this goal and the considered systems' definition, the IST joins two main concepts: unified information description of interacted flows, initiated by the sources of different nature, with common information language and systems modeling methodology, applied to distinct interdisciplinary objects; general system's information formalism for building the model, which allows expressing mathematically the system's regularities and main systemic mechanisms.

The formalism of informational macrodynamics (IMD), based of the minimax variational principle, reveals the system model's main layers: microlevel stochastics, macrolevel dynamics, hierarchical dynamic network (IN) of information structures, its minimal logic, and optimal code of communication language, generated by the IN hierarchy, dynamics, and geometry. The system's complex dynamics originate information geometry and evolution with the functional information mechanisms of ordering, cooperation, mutation, stability, diversity, adaptation, self‐organization, and the double helix's genetic code.

The developed IMD's theoretical computer‐based methodology and the software has been applied to such areas as technology, communications, computer science, intelligent processes, biology, economy, management, and other nonphysical and physical subjects.

The IMD's macrodynamics of uncertainties connect randomness and regularities, stochastic and determinism, reversibility and irreversibility, symmetry and asymmetry, stability and instability, structurization and stochastization, order and disorder, as a result of micro‐macrolevel's interactions for an open system, when the external environment can change the model's structure.

We present an abstract mathematical and numerical analysis for Drift‐Diffusion equation of heterojunction semiconductor devices with Fermi‐Dirac statistic. For the approximation, a mixed finite element method is considered. This can be profitably used in the investigation of the current through the device structure. A peculiar feature of this mixed formulation is that the electric displacement D and the current densities jn and jp for electrons and holes, are taken as unknowns, together with the potential φ and quas‐Fermi levels φn and φp. This enably D, jn and jp to be determined directly and accurately. For decoupled system, existence, uniqueness, regularity and stability results of the approximate solution are given. A priori and a posteriori error estimates are also presented. A nonlinear implicit scheme with local time steps is used. This algorithm appears to be efficient and gives satisfactory results. Numerical results for an heterojunction bipolar transistor, In two dimension, are presented.

Business cycle theory is normally described as having evolved out of a previous tradition of writers focusing exclusively on crises. In this account, the turning point is seen as residing in Clément Juglar's contribution on commercial crises and their periodicity. It is well known that the champion of this view is Schumpeter, who propagated it on several occasions. The same author, however, pointed to a number of other writers who, before and at the same time as Juglar, stressed one or another of the aspects for which Juglar is credited primacy, including the recognition of periodicity and the identification of endogenous elements enabling the recognition of crises as a self-generating phenomenon. There is indeed a vast literature, both primary and secondary, relating to the debates on crises and fluctuations around the middle of the nineteenth century, from which it is apparent that Juglar's book Des Crises Commerciales et de leur Retour Périodique en France, en Angleterre et aux États-Unis (originally published in 1862 and very much revised and enlarged in 1889) did not come out of the blue but was one of the products of an intellectual climate inducing the thinking of crises not as unrelated events but as part of a more complex phenomenon consisting of recurring crises related to the development of the commercial world – an interpretation corroborated by the almost regular occurrence of crises at about 10-year intervals.

The purpose of this paper is to frame organisational cybersecurity through a strategic lens, as a function of an interplay of pragmatism, inference, holism and adaptation. The authors address the hostile epistemic climate for intellectual capital management presented by the dynamics of cybersecurity as a phenomenon. The drivers of this hostility are identified and their implications for research and practice are discussed.

The philosophical foundations of cybersecurity in its relation with strategy, knowledge and intellectual capital are explored through a review of the literature as a mechanism to contribute to the emerging theoretical underpinnings of the cybersecurity domain.

This conceptual paper argues that a knowledge-based perspective can serve as the necessary platform for a phenomenon-based view of organisational cybersecurity, given its multi-disciplinary nature.

By recognising the knowledge-related vectors, mechanisms and tendencies at play, a novel perspective on the topic can be developed: cybersecurity as a “knowledge problem”. In order to facilitate such a perspective, the paper proposes an emergent epistemology, rooted in systems thinking and pragmatism.

In practice, the knowledge-problem narrative can underpin the development of new organisational support constructs and systems. These can address the distinctiveness of the strategic challenges that cybersecurity poses for the growing operational reliance on intellectual capital.

The research narrative presents a novel knowledge-based analysis of organisational cybersecurity, with significant implications for both interdisciplinary research in the field, and practice.

Gaussian copula is by far the most popular copula used in the financial industry in default dependency modeling. However, it has a major drawback – it does not exhibit tail dependence, a very important property for copula. The essence of tail dependence is the interdependence when extreme events occur, say, defaults of corporate bonds. In this paper, we show that some tail dependence can be restored by introducing stochastic volatility on a Gaussian copula. Using perturbation methods we then derive an approximate copula – called perturbed Gaussian copula in this paper.

In this paper the authors review the recent numerical techniques proposed to solve the forward and inverse problems concerning the electromagnetic casting and electromagnetic levitation techniques of the metallurgical industry. In addition, the authors present a new topology optimization method to solve the inverse axisymmetric electromagnetic levitation problem.

The proposed method is based on an exact second-order topological expansion of a Kohn–Vogelius-like functional specially devised for this problem.

Through some examples the authors show that it can find suitable solutions efficiently.

The new method completes the set of efficient methods available to solve the inverse electromagnetic casting and the inverse axisymmetric electromagnetic levitation problems.

Weak separability is an important concept in many fields of economic theory. This chapter uses Monte Carlo experiments to investigate the performance of newly developed nonparametric revealed preference tests for weak separability. A main finding is that the bias of the sequentially implemented test for weak separability proposed by Fleissig and Whitney (2003) is low. The theoretically unbiased Swofford and Whitney test (1994) is found to perform better than all sequentially implemented test procedures but is found to suffer from an empirical bias, most likely because of the complexity in executing the test procedure. As a further source of information, we also perform sensitivity analyses on the nonparametric revealed preference tests. It is found that the Fleissig and Whitney test seems to be sensitive to measurement errors in the data.