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Many analysis and design problems in engineering and science involve uncertainty to varying degrees. This paper is concerned with the structural vibration problem involving uncertain material or geometric parameters, specified as fuzzy parameters. The requirement is to propagate the parameter uncertainty to the eigenvalues of the structure, specified as fuzzy eigenvalues. However, the usual approach is to transform the fuzzy problem into several interval eigenvalue problems by using the α-cuts method. Solving the interval problem as a generalized interval eigenvalue problem in interval mathematics will produce conservative bounds on the eigenvalues. The purpose of this paper is to investigate strategies to efficiently solve the fuzzy eigenvalue problem.

Based on the fundamental perturbation principle and vertex theory, an efficient perturbation method is proposed, that gives the exact extrema of the first-order deviation of the structural eigenvalue. The fuzzy eigenvalue approach has also been improved by reusing the interval analysis results from previous α-cuts.

The proposed method was demonstrated on a simple cantilever beam with a pinned support, and produced very accurate fuzzy eigenvalues. The approach was also demonstrated on the model of a highway bridge with a large number of degrees of freedom.

This proposed Vertex-Perturbation method is more efficient than the standard perturbation method, and more general than interval arithmetic methods requiring the non-negative decomposition of the mass and stiffness matrices. The new increment method produces highly accurate solutions, even when the membership function for the fuzzy eigenvalues is complex.

The purpose of this paper is to propose the generalized integral transform technique (GITT) to the solution of convection-diffusion problems with nonlinear boundary conditions by employing the corresponding nonlinear eigenvalue problem in the construction of the expansion basis.

The original nonlinear boundary condition coefficients in the problem formulation are all incorporated into the adopted eigenvalue problem, which may be itself integral transformed through a representative linear auxiliary problem, yielding a nonlinear algebraic eigenvalue problem for the associated eigenvalues and eigenvectors, to be solved along with the transformed ordinary differential system. The nonlinear eigenvalues computation may also be accomplished by rewriting the corresponding transcendental equation as an ordinary differential system for the eigenvalues, which is then simultaneously solved with the transformed potentials.

An application on one-dimensional transient diffusion with nonlinear boundary condition coefficients is selected for illustrating some important computational aspects and the convergence behavior of the proposed eigenfunction expansions. For comparison purposes, an alternative solution with a linear eigenvalue problem basis is also presented and implemented.

This novel approach can be further extended to various classes of nonlinear convection-diffusion problems, either already solved by the GITT with a linear coefficients basis, or new challenging applications with more involved nonlinearities.

Adverse situations negatively impact project stakeholders’ engagement. Past research has sporadically investigated adverse situations affecting stakeholder engagement but lacks a thorough empirical investigation. The paper aims to discuss this issue.

A web survey was designed to address the knowledge gap of the identification of the impactful adverse situations during multi-stakeholder engagement. The research yielded 144 completed responses from multi-stakeholders engaged in globally distributed ICT projects.

Exploratory factor analysis revealed eight factors that underpin 26 adverse situations. The top factors, ranked in terms of importance according to their Relative Importance Index (RII) are: dysfunctional conflicts, dearth of reasoning, glitches in project governance, clash of personalities.

This research reveals the factors that can impact engagement in the form of meaningful clusters and dimensions and opens-up a future research agenda toward causation and mitigation studies related to adversarial stakeholder engagement. The study focuses on globally distributed ICT projects and has not explored generalizability in other sectors.

This research enables project managers and stakeholder analysts to get an understanding on the importance of different dimensions of adverse situations in the way stakeholders think, act and emote.

Awareness on the potential adversarial stakeholder engagement helps in effectively managing the sustained stakeholder relationships and mental well-being of project stakeholders.

This research contributes to project management practice, as it reveals the underlying factors of adverse situations occurring during multi-stakeholders’ engagement, provides clarity on their components and ranks them in terms of importance for their overall effect on stakeholders’ engagement.

The study aims to find the synchronization between foreign agriculture investment (FAI) and Sustainable Development Goals (SDGs) related to agriculture as classified by the Food and Agriculture Organization (FAO). The study tries to find such an association in India over 2 decades from 2001.

The Toda-Yamamoto Granger using the M-Wald test for the non-causality procedure is applied to find the synchronization. Stationarity is tested using the Augmented Dickey-Fuller, Phillips-Perron and Kwiatkowski, Phillips, Schmidt and Shin (KPSS) tests. The Johanson methodology with MacKinnon-Haug-Michelis P-value is employed for the Cointegration test.

The empirical results indicate that the FAI Granger cause SDG2 “Zero hunger” and “Overall sustainability”, but SDG13 “Climate Change”, SDG6 “Clean water and sanitation”, SDG12 “Responsible production and consumption” and SDG15 “Life on Land” granger cause global investments. Notwithstanding, SDG5 “Gender equality” and SDG14 “Life below water” found no-way causality with FAI.

Host governments should prioritize sector-level sustainable development, notably agricultural SDGs, to attract global investments. Foreign agriculture investment is influenced differently by various SDGs; thus, policymakers should concentrate on specific agricultural SDGs to enhance the flow of capital into the agriculture sector. Global investors should take sustainability into account while framing foreign investment plans, and the supra-national organization may consider global agricultural investments while addressing the problems related to global food security.

The distinguishing feature of the study is that SDGs classified by the FAO from a global investment perspective have not been studied so far.

Without reliance on results obtained from applying a cell formation method, this paper aims to describe a simple quantitative approach to testing whether an underlying pattern of relationships exists between machines of a given system, such that the machines may be rearranged into manufacturing cells. It also aims to support the approach by an index for measuring the clustering tendency.

The eigenvalues of the similarity coefficient matrix and Kaiser's rule are used to: detect the number of clusters existing in the part‐machine matrix, and derive an index for predicting the goodness of the best possible obtainable cell formation.

The results of applying the proposed approach and the clustering tendency index to problems of different sizes taken from the literature have proven that both the approach and the clustering tendency index are powerful in performing the feasibility assessment and in predicting the right number of manufacturing cell to be formed.

This study is of considerable value to practitioners because it provides them with a powerful yet very easy to apply approach for assessing the feasibility of adopting cellular manufacturing in early stages of design. Another characteristic of this approach is the possibility of using it as a decision support tool for practitioners who opt to use a cell formation method which requires specifying the number of cells in advance. Moreover, the approach does not require any special software package, since it can be easily performed using several available software packages such as MATLAB and Mathematica.

A methodology for evaluating the adaptability of a system to cellular manufacturing has been proposed in a previous study. However, the methodology used is complex and uses a certain degree of subjectivity. In contrast, the proposed approach is simple and completely quantitative. Furthermore, a new index for measuring the clustering tendency is presented.

The purpose of this paper is to describe reduced order modelling based on dynamic flexibility approximation and applied to transient analyses.

This work is based on a recently proposed flexibility‐based component modes synthesis (CMS) approach which was shown to be very efficient for solving large eigenvalue problems. The model reduction approach is based on partionning via the localized Lagrange multipliers method, which makes it very appropriate to handle coupled problems.

In particular, it is demonstrated in this paper how the utilised model reduction method can be applied only to one part of the structure and efficiently coupled to a full finite element model. The performance of the method is investigated on numerical examples of plate and 3D problems.

The proposed flexibility‐based CMS approach can be used as a very efficient tool for complex engineering structures under dynamic load where the mode superposition method applies. The efficiency of the computations is brought about by the model reduction.

The dynamics of coupling between spectrum and resolvent under ε‐perturbations of operator and matrix spectra are studied both theoretically and numerically. The phenomenon of non‐trivial pseudospectra encountered in these dynamics is treated by relating information in the complex plane to the behaviour of operators and matrices. On a number of numerical results we show how an intrinsic blend of theory with symbolic and numerical computations can be used effectively for the analysis of spectral problems arising from engineering applications.

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.

Analytical or hybrid numerical‐analytical solutions of multidimensional diffusion problems involve the evaluation of nested multiple infinite summations, which require the computation of eigenvalues and related quantities, from associated auxiliary eigenvalue‐type problems. A substantial reduction of the total computational effort in the construction of the final solution for the original potential can be achieved through the proper reorganization of the multiple summations into a single series representation. Such reordering of terms should be carefully accomplished, in order to account for the most significant contributions to the final numerical result, up to a truncated finite order that meets the user prescribed tolerance for the relative error. Presents an algorithm for an optimized scheme with consequent reduction on the number of eigenquantities to be evaluated. This approach is illustrated through representative two and three‐dimensional transient heat conduction problems.