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The purpose is to reduce round-off errors in numerical simulations. In the numerical simulation, different kinds of errors may be created during analysis. Round-off error is one of the sources of errors. In numerical analysis, sometimes handling numerical errors is challenging. However, by applying appropriate algorithms, these errors are manageable and can be reduced. In this study, five novel topological algorithms were proposed in setting up a structural flexibility matrix, and five different examples were used in applying the proposed algorithms. In doing so round-off errors were reduced remarkably.

Five new algorithms were proposed in order to optimize the conditioning of structural matrices. Along with decreasing the size and duration of analyses, minimizing analytical errors is a critical factor in the optimal computer analysis of skeletal structures. Appropriate matrices with a greater number of zeros (sparse), a well structure and a well condition are advantageous for this objective. As a result, a problem of optimization with various goals will be addressed. This study seeks to minimize analytical errors such as rounding errors in skeletal structural flexibility matrixes via the use of more consistent and appropriate mathematical methods. These errors become more pronounced in particular designs with ill-suited flexibility matrixes; structures with varying stiffness are a frequent example of this. Due to the usage of weak elements, the flexibility matrix has a large number of non-diagonal terms, resulting in analytical errors. In numerical analysis, the ill-condition of a matrix may be resolved by moving or substituting rows; this study examined the definition and execution of these modifications prior to creating the flexibility matrix. Simple topological and algebraic features have been mostly utilized in this study to find fundamental cycle bases with particular characteristics. In conclusion, appropriately conditioned flexibility matrices are obtained, and analytical errors are reduced accordingly.

(1) Five new algorithms were proposed in order to optimize the conditioning of structural flexibility matrices. (2) A JAVA programming language was written for all five algorithms and a friendly GUI software tool is developed to visualize sub-optimal cycle bases. (3) Topological and algebraic features of the structures were utilized in this study.

This is a multi-objective optimization problem which means that sparsity and well conditioning of a matrix cannot be optimized simultaneously. In conclusion, well-conditioned flexibility matrices are obtained, and analytical errors are reduced accordingly.

Engineers always finding mathematical modeling of real-world problems and make them as simple as possible. In doing so, lots of errors will be created and these errors could cause the mathematical models useless. Applying decent algorithms could make the mathematical model as precise as possible.

Errors in numerical simulations should reduce due to the fact that they are toxic for real-world applications and problems.

This is an original research. This paper proposes five novel topological mathematical algorithms in order to optimize the structural flexibility matrix.

Matrix structures are complex and conflict prone, so multinational enterprises (MNEs) would utilize them only if they conferred some advantage over less complex organizational structures. Based upon the information-processing view, a theory of matrix advantage is proposed. It is supported by a secondary analysis of data from a major study of German MNEs. Matrix structures are shown to have an advantage over the elementary structural types. Specifically, the matrix structures fit higher levels of transnational strategy than elementary structures. Transnational strategy is assessed by two concepts: firm internationalization (involvement in foreign sales, manufacturing, and research and development (R&D)) and corporate integration (intracompany transfers). Moreover, three-dimensional matrices are associated with higher levels of transnational strategy than are two-dimensional matrices, confirming the gains from having additional structural dimensions. Matrix structures arise because of the need to simultaneously fit high levels of both firm internationalization and corporate integration. Matrices fit the transnational strategy type of Bartlett and Ghoshal. Implications are drawn for the relationship between the head office and the subsidiary. The matrix often subjects the subsidiary to conflicting expectations from the head office, which it can attempt to manage. Similarly, the head office is challenged by the task of integrating the information that comes from different dimensions of the matrix.

The purpose of this paper is to focus on studying the concept of “Smart Organization” and providing a comprehensive framework for the various factors as barriers for the smart organization, identifying and classifying the key criterion of these factors based on their direct and indirect relationships.

In this paper an extensive literature survey and experts’ opinion have been used to identify major barriers of smart organization. These barriers are then modeled using interpretative structural modeling (ISM) methodology. The model so developed has been further improved and an integrated model has been developed using fuzzy-MICMAC.

Various barriers of smart organization have been identified and a structural model has been developed for barriers using the ISM methodology. The critical barriers have been found out by fuzzy-MICMAC analysis. The driver power and dependence graph has been plotted for barriers. The barriers are classified into four categories which are, autonomous, linkage, dependent and independent according to their driver power and dependence. From the ISM model and the integrated model, and from further discussions with the experts, it has been found that the barriers “(B1) organizational structure” and “(B6) Managerial actions” are the two most important barriers, every other barrier is directly or indirectly driven by these.

The basis of developing the ISM model, i.e, the structural self-interaction matrix is based on experts’ opinion, therefore the result may get influenced if there is any biasing in judging the barriers. The future research scope for this paper will be to test the model generated in this paper. The testing of the model can be done by applying structural equation modeling technique, it has the capability of testing the hypothetical model. Further a framework of smart organizations can be created to find out the smartness of different organizations.

The paper can be used by organizations in understanding the barriers in becoming “smart” on the basis of their inter-relationships. This model can help manufacturing organization of North India in understanding the barriers which needs to be worked upon and the inter-relationship among these factors. This model-based study may be helpful in understanding and implementing the practices of smart organization by removing the possible critical barriers.

This is the first study to identify the barriers of smart organizations and to develop a model of these barriers using ISM and fuzzy-MICMAC.

Identification of shocks of interest is a central problem in structural vector autoregressive (SVAR) modeling. Identification is often achieved by imposing restrictions on the impact or long-run effects of shocks or by considering sign restrictions for the impulse responses. In a number of articles changes in the volatility of the shocks have also been used for identification. The present study focuses on the latter device. Some possible setups for identification via heteroskedasticity are reviewed and their potential and limitations are discussed. Two detailed examples are considered to illustrate the approach.

The purpose of this paper is to develop a comprehensive framework to identify and classify key medical tourism enablers (MTEs) and to study the direct and indirect effects of each enabler on the growth of medical tourism in India.

In this paper, an integrated approach using interpretive structural modeling (ISM) and Fuzzy Matrice d'Impacts Croisés Multiplication Appliquée á un Classement (FMICMAC) analysis has been developed to identify and classify the key MTEs, typically identified by a comprehensive review of literature and expert opinion. The key enablers are also modeled to find their role and mutual influence.

The key finding of this modeling helps to identify and classify the enablers which may be useful for medical tourism decision makers to employ this model for formulating strategies in order to overcome challenges and to become a preferred medical tourism destination. Integrated model reveals enablers such as medicine insurance coverage, international healthcare collaboration, and efficient information system as dependent enablers. No enabler is found to be autonomous enablers. The important enablers like healthcare infrastructure facilities and global competition are found as the linkage enablers. Research in medicine and pharmaceutical science, medical tourism market, transplantation law, top management commitment, national healthcare policy, competent medical and para-medical staffs are found as the independent enablers. Integrated model also establishes the direct and indirect relationship among various enablers.

The research provides an integrated model using ISM and FMICMAC to identify and classify various key enablers of medical tourism in India. In conventional cross-impact matrix multiplication applied to classification analysis, binary relationship of various enablers is considered. FMICMAC analysis helps to establish possibility of relationship among various enablers so that low-key hidden factors can be identified. The low-key hidden factors may initially exhibit marginal influence but they may show significant influence later on during analysis. The uncertainty and fuzziness of relationship among various enablers can be conveniently handled by FMICMAC and expert opinions can easily be captured. This research will help medical tourism decision makers to select right enablers for the growth of medical tourism in India.

International projects very commonly experience failure due to various factors at the global level. Especially, large projects at the international level virtually have no chance of meeting scope, time, cost and quality. This fact has been underlined by most of the international surveys and published literature. Effective risk management plays a vital role in preventing projects from failure by implementing appropriate risk response strategies. The success of risk management will be based on the understanding of various risk categories which specifically affect international projects, analysis of their interdependence, prioritize them according to their importance and develop strategies for risk management based on the prioritization. The paper aims to discuss these issues.

This paper represents typical eight risk categories frequently observed in the international projects through literature survey and feedback from project professionals. Interpretive structural modeling (ISM) and Matrice d’Impacts croises-multiplication applique´ an classment (MICMAC) analysis have been used to analyze the interactions among the risk categories and prioritize them. The strategy management tool threats, opportunities, weaknesses and strengths (TOWS) matrix has been used to develop the strategies for effective project risk management.

The analysis represents political risks, contractual and legal risks, cultural risks, and financial and economic risks as the highest priority risk categories, the mitigation of which should be paid the highest attention. The strengths-threats strategy has been applied to develop the strategies by identifying the various internal strengths of project organization to overcome the various threats caused by the eight risk categories observed in international projects.

This paper tries to represent the prioritization of international project risk categories which are generic in nature. For any specific international project, the risk categories as well as their prioritization may be slightly varying. The tool used for prioritization; Interpretive structural modeling (ISM) is more suitable for few numbers of variables as it becomes complex as the number of variables increases. The strengths and threats considered for developing strategies using TOWS matrix are based on the feedback from project professionals and may vary according to the nature of project.

This paper uses ISM and MICMAC for risk prioritization in international projects and TOWS matrix for developing risk management strategies. This may trigger new opportunities for in-depth research in the risk management strategy development for international projects.

Considering the randomness of physical parameters of structural material, dynamic characteristic topology optimization mathematical model based on reliability of planar continuum structures is built in this paper. In which topology information variables of the structure are taken as design variables, minimizing the mean value of total structural weight as objective function and satisfying the reliability requirement of structural dynamic characteristic as constraints. In the process of optimization, the ESO method based on probability is adopted as solution strategy. At the same time, distribution function method is utilized to convert the reliability constraints into conventional constraints formally. A square thin plate with four sides fixed is used as an example to demonstrate the rationality and validity of the presented model.

The paper aims to analyse the contextual relationship and dependency amongst enablers for lean manufacturing implementation in Bulgarian small and medium-sized enterprises (SMEs).

In this study, the interpretive structural modelling (ISM) technique was used to develop a hierarchical structural model for enablers. Also, the interpretive ranking process (IRP) was used to analyse and rank enablers with reference to performance variables. For the ISM approach, a structural self- integration matrix was developed with the help of experts’ suggestions and opinions. Cross-impact matrix multiplication applied to classification (MICMAC) analysis was used to analyse the relationship amongst enablers. A total of nine experts were chosen for collecting the primary data in which seven experts belong to the industry and two experts were academicians. The dominant relationship amongst the enablers was analysed through IRP modelling.

A total of 11 enablers were identified for the purpose of this study. The model shows that “leadership and commitment by management”, “human resource management”, “customer relation management”, “supplier relation management” and “information technology system” are the most significant enablers for lean implementation in Bulgarian SMEs as these are positioned at the bottom levels in ISM model. MICMAC analysis shows that five enablers fall in the independent factor, two enablers in linkage factor and four enablers in the dependant factor while there is no enabler in the autonomous factor. ISM and IRP models show that “continuous improvement” is an essential enabler for the successful implementation of lean in Bulgarian SMEs. This study also helps to explain the comparative analysis of ISM and IRP, which indicates that IRP is a more robust modelling approach than ISM, as it incorporates the relationship of enablers with performance variables.

ISM and IRP modelling approaches are based solely on expert opinions and responses. This limitation can be overcome with the help of empirical study.

This study supports the professionals/experts to prioritise and manage enablers at strategic and tactical levels while implementing lean manufacturing practices in Bulgarian SMEs. The models developed in the study will be helpful for practitioners to understand and analyse the interdependence of enablers for lean manufacturing implementation.

This study helps to identify and prioritise enablers that affect lean manufacturing adoption using ISM and IRP approaches. Literature shows that numerous authors have used the ISM approach but the use of IRP approach is limited. The models were developed in the study, totally dependent on data collected from the experts to ensure their real-life validity.

The purpose of this paper is to analyze the stability of aeroelastic systems using aeroelastic frequency response function (FRF).

The proposed technique determines the instability boundary of an aeroelastic system based on condition number (CN) of aeroelastic FRF matrix or directly from FRFs data.

Stability margins of typical section and hingeless helicopter rotor blade in the subsonic flow regimes (quasi‐steady and unsteady models) are determined using proposed techniques as two case studies.

The paper introduces a technique which is applicable not only when aerodynamic and structure analytical models are available but also when there are experimental models for structure and/or aerodynamics, such as impulse response functions data or FRFs data. In other words, the main advantage of the proposed method, besides its simplicity and low memory requirement, is its ability to utilize experimental data.

The purpose of this paper is to identify and analyze the interactions among different enablers of total quality management (TQM) and its outcome variables in service sector specific to Indian domestic airline industry. No study has been done regarding the implementation of TQM in Indian domestic aviation sector. To fill this gap interpretive structural modeling (ISM) and total interpretive structural modeling (TISM) based quality framework model has been developed to understand the mutual interactions among the variables and to identify the driving and dependence power of these variables.

An ISM and TISM based approach have been used to study and analyze the interactions between identified variables.

In this research work, a total of 14 variables have been identified based on extensive literature review, brainstorming and experts opining from the Indian airline industry and academia. The result showed that top management commitment, training, continuous improvement, benchmarking, employee involvement and commitment have strong driving power and weak dependence power and are at the lowest level in hierarchy in the ISM and TISM model, while the outcome variables of TQM have low driving power but have high dependence power.

Top management must stress on variables having strong driving power for efficient implementation of TQM. By implementation of TISM model in the Indian airline industry, organizations would become more productive, competitive and would eventually become more profitable.

In this research work, ISM and TISM based quality framework structural model have been proposed for Indian domestic aviation industry which is a new effort in the area of TQM implementation in this sector.