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The definition of modeling languages is a key‐prerequisite for model‐driven engineering. In this respect, Domain‐Specific Modeling Languages (DSMLs) defined from scratch in terms of metamodels and the extension of Unified Modeling Language (UML) by profiles are the proposed options. For interoperability reasons, however, the need arises to bridge modeling languages originally defined as DSMLs to UML. Therefore, the paper aims to propose a semi‐automatic approach for bridging DSMLs and UML by employing model‐driven techniques.

The paper discusses problems of the ad hoc integration of DSMLs and UML and from this discussion a systematic and semi‐automatic integration approach consisting of two phases is derived. In the first phase, the correspondences between the modeling concepts of the DSML and UML are defined manually. In the second phase, these correspondences are used for automatically producing UML profiles to represent the domain‐specific modeling concepts in UML and model transformations for transforming DSML models to UML models and vice versa. The paper presents the ideas within a case study for bridging ComputerAssociate's DSML of the AllFusion Gen CASE tool with IBM's Rational Software Modeler for UML.

The ad hoc definition of UML profiles and model transformations for achieving interoperability is typically a tedious and error‐prone task. By employing a semi‐automatic approach one gains several advantages. First, the integrator only has to deal with the correspondences between the DSML and UML on a conceptual level. Second, all repetitive integration tasks are automated by using model transformations. Third, well‐defined guidelines support the systematic and comprehensible integration.

The paper focuses on the integrating direction DSMLs to UML, but not on how to derive a DSML defined in terms of a metamodel from a UML profile.

Although, DSMLs defined as metamodels and UML profiles are frequently applied in practice, only few attempts have been made to provide interoperability between these two worlds. The contribution of this paper is to integrate the so far competing worlds of DSMLs and UML by proposing a semi‐automatic approach, which allows exchanging models between these two worlds without loss of information.

The purpose of this paper is to address a classic problem – pattern formation identified by researchers in the area of swarm robotic systems – and is also motivated by the need for mathematical foundations in swarm systems.

The work is separated out as inspirations, applications, definitions, challenges and classifications of pattern formation in swarm systems based on recent literature. Further, the work proposes a mathematical model for swarm pattern formation and transformation.

A swarm pattern formation model based on mathematical foundations and macroscopic primitives is proposed. A formal definition for swarm pattern transformation and four special cases of transformation are introduced. Two general methods for transforming patterns are investigated and a comparison of the two methods is presented. The validity of the proposed models, and the feasibility of the methods investigated are confirmed on the Traer Physics and Processing environment.

This paper helps in understanding the limitations of existing research in pattern formation and the lack of mathematical foundations for swarm systems. The mathematical model and transformation methods introduce two key concepts, namely macroscopic primitives and a mathematical model. The exercise of implementing the proposed models on physics simulator is novel.

This study aims to examine the relationship between the influence of technological disruption and the transformation of business models mediated by adaptive organization and organization learning.

In total, 116 top management teams from the member of the Indonesian Advertising Association (P3I) were recruited for this study. The data was obtained through an online survey and analyzed using the PLS-structural equation modeling (SEM) technique.

This study revealed the importance of organizational learning and adaptive organization in minimizing technology disruption and enabler of the business model transformation. In an always-changing environment, the adaptive organization is the core element and catalyst of firm transformation. The acceleration of business model transformation is empowered through establishing an organization's learning system by exploiting existing knowledge, exploring new knowledge and cultivating a learning culture.

In today’s fast-paced digital world and a constant state of flux, advertising agencies need to build a sustainable business model and structure that allows them to be flexible, adaptive to changes and efficient.

To the best of the authors’ knowledge, this study was the first to develop a model to mitigate technology disruption and enable necessary elements to create a transformation business model.

Some functional properties of engineering materials, i.e. physical, mechanical and thermal ones, depend directly on the microstructure, which is a result of processes occurring in the material during the forming and thermomechanical processing. The proper microstructure can be obtained in many cases by the phase transformation. This phenomenon is one of the most important processes during hot forming and heat treatment. The purpose of this paper is to develop a new comprehensive hybrid model for modeling diffusion phase transformations. A problem has been divided into several tasks and is carried out on several stages. The purpose of this stage is a development of the structure of a hybrid model, development of an algorithm used in the diffusion module and one-dimensional heat flow and diffusion modeling. Generally, the processes of phase transformations are studied well enough but there are not many tools for their complex simulations. The problems of phase transformation simulation are related to the proper consideration of diffusion, movement of phase boundaries and kinetics of transformation. The proposed new model at the final stage of development will take into account the varying grain growth rate, different shape of growing grains and will allow for proper modeling of heat flow and carbon diffusion during the transformation in many processes, where heating, annealing and cooling can be considered (e.g. homogenizing and normalizing).

One of the most suitable methods for modeling of microstructure evolution during the phase transformation is cellular automata (CA), while lattice Boltzmann method (LBM) suits for modeling of diffusion and heat flow. Then, the proposed new hybrid model is based on CA and LBM methods and uses high performing parallel computations.

The first simulation results obtained for one-dimensional modeling confirm the correctness of interaction between LBM and CA in common numerical solution and the possibility of using these methods for modeling of phase transformations. The advantages of the LBM method can be used for the simulation of heat flow and diffusion during the transformation taking into account the results obtained from the simulations. LBM creates completely new possibilities for modeling of phase transformations in combination with CA.

The studies are focused on diffusion phase transformations in solid state in condition of low cooling rate (e.g. transformation of austenite into ferrite and pearlite) and during the heating and annealing (e.g. transformation of the ferrite-pearlite structure into austenite, the alignment of carbon concentration in austenite and growth of austenite grains) in carbon steels within a wide range of carbon content. The paper presents the comprehensive modeling system, which can operate with the technological processes with phase transformation during heating, annealing or cooling.

A brief review of the modeling of phase transformations and a description of the structure of a new CA and LBM hybrid model and its modules are presented in the paper. In the first stage of model implementation, the one-dimensional LBM model of diffusion and heat flow was developed. The examples of simulation results for several variants of modeling with different boundary conditions are shown.

Security requirements play an important role in software development. These can be specified both in enterprise architecture models and in business processes. Enterprises increasingly carry out larger amounts of business processes where security plays a major role. Business processes including security can be automatically obtained from enterprise architecture models by applying a model-driven architecture approach, through a CIM to CIM transformation. The aim of this article is to present the specification of transformation rules for the correspondence between enterprise architecture and business process model elements focusing on security.

This work utilizes motivational aspects of the ArchiMate language to model security in the business layer of enterprise architectures. Next, a set of transformation rules defined with the Atlas Transformation Language are utilized to obtain the correspondence of the enterprise architecture elements in a business process, modelled with a security extension of BPMN.

A total of 19 transformation rules have been defined. These rules are more complex than element to element relations, as they take into consideration the context of the elements for establishing the correspondence. Additionally, the prototype of a tool that allows the automatic transformation between both models has been developed.

The results of this work demonstrate the possibility to tackle complex transformations between both models, as previous literature focuses on semantic correspondences. Moreover, the obtained models can be of use for software developers applying the model-driven approach.

Industry 4.0 is a promising concept that allows industries to meet customers’ demands with flexible and resilient processes, and highly personalised products. This concept is made up of different dimensions. For a long time, innovative digital technology has been thought of as the only dimension to succeed in digital transformation projects. Other dimensions have been identified such as organisation, strategy, and human resources as key while rolling out digital technology in factories. From these findings, researchers have designed industry 4.0 theoretical models and then built readiness models that allow for analysing the gap between the company initial situation and the theoretical model. Nevertheless, this purely deductive approach does not take into consideration a company’s background and context, and eventually favours one single digital transformation model. This article aims at analysing four actual digital transformation projects and demonstrating that the digital transformation’s success or failure depends on the combination of two variables related to a company’s background and context. This research is based on a double approach: deductive and inductive. First, a literature review has been carried out to define industry 4.0 concept and its main dimensions and digital transformation success factors, as well as barriers, have been investigated. Second, a qualitative survey has been designed to study in-depth four actual industry digital transformation projects, their genesis as well as their execution, to analyse the key variables in succeeding or failing. 46 semi-structured interviews were carried out with projects’ members; interviews have been analysed with thematic content analysis. Then, each digital transformation project has been modelled regarding the key variables and analysed with regards to succeeding or failing. Investigated projects have consolidated the models of digital transformation. Finally, nine digital transformation types have been identified.

The purpose of this work is to apply a recently proposed constitutive model for mechanically induced martensitic transformations to the prediction of transformation loci. Additionally, this study aims to elucidate if a stress-assisted criterion can account for transformations in the so-called strain-induced regime.

The model is derived by generalising the stress-based criterion of Patel and Cohen (1953), relying on lattice information obtained using the Phenomenological Theory of Martensite Crystallography. Transformation multipliers (cf. plastic multipliers) are introduced, from which the martensite volume fraction evolution ensues. The associated transformation functions provide a variant selection mechanism. Austenite plasticity follows a classical single crystal formulation, to account for transformations in the strain-induced regime. The resulting model is incorporated into a fully implicit RVE-based computational homogenisation finite element code.

Results show good agreement with experimental data for a meta-stable austenitic stainless steel. In particular, the transformation locus is well reproduced, even in a material with considerable slip plasticity at the martensite onset, corroborating the hypothesis that an energy-based criterion can account for transformations in both stress-assisted and strain-induced regimes.

A recently developed constitutive model for mechanically induced martensitic transformations is further assessed and validated. Its formulation is fundamentally based on a physical metallurgical mechanism and derived in a thermodynamically consistent way, inheriting a consistent mechanical dissipation. This model draws on a reduced number of phenomenological elements and is a step towards the fully predictive modelling of materials that exhibit such phenomena.

This paper aims to present how iterative round‐trip modelling between two different business process modelling tools can be enabled on a conceptual level. Iterative round‐trip modelling addresses model transformations between high‐level business and executable process models, and how to maintain these transformations in change time. Currently, the development of these process models is supported by different tools. To the authors' best knowledge, no coherent collaborative tool environment exists that supports iterative round‐trip modelling.

This paper is primarily based on a literature review of state‐of‐the‐art business to IT transformations regarding business process modelling. The architecture of integrated information systems (ARIS) and Cordys tools are used as an example case in this research. ARIS is a business process analysis (BPA) tool suited for analyzing and designing business processes, while the execution and monitoring of these processes is allowed by Cordys, a business process management suite (BPMS). The theory is used for transforming between ARIS event‐driven process chains from the business perspective and business process modelling notation in Cordys from the IT perspective.

A conceptual framework is proposed to couple a BPA and BPMS tool for round‐trip business process modelling. The framework utilizes concepts from the model‐driven architecture for structurally addressing interoperability and model transformations. Ensuring iterative development with two tools requires traceability of model transformations.

In many organizations, BPA and BPMS tools are used for business process modelling. These are in practice often two different worlds, while they concern around the same business processes. Maintaining multiple versions of the same process models across two tools is a considerable task, as they often are subject to design changes. Interoperability between a BPA and BPMS tool will minimize redundant activities, and reduce business to IT deployment time.

This research provides a theoretical base for coupling a BPA and BPMS tool regarding iterative round‐trip modelling. It provides an overview of the current state‐of‐the‐art literature of business process modelling transformations, and what is necessary for maintaining interoperability between tools. The findings indicate what is expected in tool support for iterative development in business process modelling from analysis and design to execution.

This study aims to analyze and synthesize the design features of existing digital transformation maturity models with a developed classification scheme and propose a generic maturity model development wireframe based on design science research.

A systematic literature review is conducted on digital transformation maturity models in peer-reviewed journals, including the Emerald Insight, Science Direct, Scopus, Taylor & Francis and Web of Science databases, which resulted in 21 studies. A concept-centric tabular approach is used to analyze the studies, and intersectional demonstrations are used to synthesize the findings regarding the design features.

The classification scheme derived from the tabular concept-centric approach and iteratively evolved results in three main and 25 subcategories related to the design features. Analysis and synthesis of the studies reveal the granularity of the existing digital transformation maturity models concerning the design features. Furthermore, considering the design features in the classification scheme, a generic maturity model development wireframe is proposed to guide the researchers.

The generic maturity model development wireframe and the classification scheme that represents the design features of existing maturity models guide the researchers for the maturity model development roadmap.

The existing literature review studies do not focus on the design feature of digital transformation maturity models within a systematic literature review perspective. A unique classification scheme derived from the tabular concept-centric approach aims to analyze the granularity level of the existing models. Furthermore, the generic maturity model development wireframe includes the guidelines and recommendations of design science studies and presents a roadmap for maturity model researchers.

This study aims to focus on numerical simulation investigations of phase transformation during cooling of 55SiMnMo steel, which is commonly applied to improve mechanical properties.

A mathematical model based on the finite element method (FEM) and the phase transformation kinetics model has been proposed to predict microstructure changes during continuous cooling of 55SiMnMo steel. This model can be employed to analyze the variation of austenite, special upper bainite and lump-like composite structure with cooling time at different cooling rates.

According to the continuous cooling experiments, when the cooling rate is lower than 0.1°C/s, the special upper bainite is the only transformation product which decreases with increasing cooling rate; when the cooling rate is above 0.5°C/s, the transformation products include special upper bainite and lump-like composite structure. Meanwhile, the results of continuous cooling experiment verified the correctness of this finite element model.

This model has a great value for proper controlling of the cooling process which can improve the quality of hollow drill steel and increase the service life of the final product.