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This paper investigates the regression statistics of the size-effect method to obtain fracture parameters of quasi-brittle materials. The correct nonlinear regression model and assumptions are established and verified using a large dataset of size-effect tests extracted from the literature. The effect of model transformation on the change in error structure is then investigated. Three different transformations are considered, including the one leading to the linear regression recommended by RILEM (Mater Struct 23:461–465, 1990). The behavior of the nonlinear least squares estimators of the fracture parameters corresponding to the untransformed space, i.e., peak load P versus specimen size D, and to each of the three transformations are discussed. Monte Carlo simulations on generated data show that the transformations lead to the violation of model assumptions and to highly skewed error distributions prone to artificial outliers. The paper also shows that the estimator corresponding to the RILEM recommendation is asymptotically biased. The estimators corresponding to the other transformations are found either asymptotically biased or do not possess the minimum variance property. Finally, simulations show that the least squares point estimates of the unknown fracture parameters differ when a model transformation is used, and that the difference is statically significant. The fitting of the fracture parameters through the size-effect method should only be obtained in the space (P vs. D) for which the nonlinear least squares estimator is asymptotically unbiased, mean square consistent, and has minimum variance. The linear regression plot suggested by RILEM should be avoided for the statistical inverse problem of the size-effect method. [ABSTRACT FROM AUTHOR]

Modern organizations are process-oriented. To remain competitive in the digital transformation era, these organizations design and implement Information Systems (IS) to support their business processes. The emergence of the Service-Oriented Architecture (SOA) style made it possible to design IS architectural models that meet software quality criteria and are aligned with the organizations’ business models. However, designing such SOA services is a complex task that requires extensive knowledge and skills in software architecture and the business domain. Researchers and practitioners have proposed several methods to derive SOA services from business models during the last two decades. However, SOA design initiatives from business models still fail. Existing methods and processes to design process-aware IS have limitations related to their usability and implementation complexity. These limitations triggered the necessity for a survey that extracts more information about how to design SOA architectural models from business models. This work proposes a systematic literature review (SLR) to establish the state of the knowledge about the existing methods that derive service models from business models. This SLR provides practitioners, such as solutions architects, business architects, and application architects, a comprehensive overview of available methods to derive SOA architectural models from business models, helping them design SOA services and build effective software solutions. We selected forty-one primary studies published between 2006 and 2023. We compared selected methods according to seven specific criteria, namely: design life cycle coverage, detailed specification support, SoaML support, service granularity, the use of patterns, automation, and tool support. The results confirm that SOA is an established architectural style for building effective ISs that support organizations’ business processes. As far as we observed from comparing selected methods according to the selected criteria, our findings explain the need for a new method that provides organizations with an easy-to-use and comprehensive process to derive quality SOA models from business models.

A multi-agent organizational model represents a coordination mechanism that allows tasks to be shared among agents to perform complex tasks. While the Agent-Group-Role organizational model (AGR) provides a concise methodological framework for designing multi-agent systems, it is expressed in informal language and lacks formal semantics. Consequently, designers of multi-agent systems have been unable to exploit this model for analysing and checking the behaviour of their systems. Some works propose investigating the issue of model transformation; unfortunately, no effort has been made to transform AGR models using a formal language defined on the semantics of true concurrency. The DD-LOTOS Language is one of the promising alternatives to this problem, as it is based on true concurrency semantics and supports the distributed aspect of the system. This paper proposes a formal approach that generates DD-LOTOS specifications from AGR models. This formalization permits the analysis, verification, and validation of the important properties of an organization. Model-to-text (M2T) transformation uses the Xpand tools to implement the approach. The e-commerce case study is used to illustrate our approach. [ABSTRACT FROM AUTHOR]

The reasonableness and accuracy of engineering design are often assessed through the use of a variety of structural design analysis software, which are then compared and verified. However, it is challenging for a single analysis software to meet the diverse and complex design requirements. In order to meet the specific engineering requirements, it is necessary to convert the MIDAS result model into an ANSYS structural model and conduct a nonlinear analysis and simulation in ANSYS. Nevertheless, the existing interface is unable to facilitate direct conversion of the model. Accordingly, this paper presents a Python-based ANSYS APDL program that enables the complete conversion of MIDAS GEN structural models to ANSYS finite element models. The program is capable of converting a range of data, including material, section, element, connection, load, node mass, constraint, time history function, and so forth. The program is capable of converting specific connection units, including elastic and general connection units. Additionally, the beam-column section direction, beam end freedom release, rigid element, and special anti-rocking structure of the structure can be considered. Ultimately, the theatre model is transformed. Following a comparison of the analysis results, it was found that the mass and mode of the model before and after the transformation were essentially identical. The maximum error of the first six orders of the structure is 2.95%, with the structural displacement under gravity load remaining essentially unchanged. The research and analysis demonstrate the accuracy and reliability of the MIDAS GEN conversion ANSYS program. The conversion program significantly reduces the time required for direct modeling in ANSYS, enhancing work efficiency. The study has considerable practical significance for the seismic sway design and analysis of buildings based on vibration isolation design. [ABSTRACT FROM AUTHOR]

Many complex embedded systems are Mixed-Criticality Systems (MCSs). MCSs are often required to operate with the specified criticality level, but they may be subject to hazards that can induce random errors and burst errors, which may result in the abortion of an executing thread or even system failures. Current research only concentrates on schedulability analysis for MCSs and fails to further analyze system safety and consider the dependency relationship among threads. Taking random errors and burst errors as the research objects, we propose an architecture-basedMCSsafety analysis method with the integration of fault propagation analysis. Meanwhile, Architecture Analysis and Design Language (AADL) is employed to characterize the dependency relations among components. To compensate for the shortcomings of AADL, we create new AADL properties (AADL burst error properties) and propose new thread state machine (burst error-based thread state machine) semantics to describe the thread execution process with burst errors. Additionally, model transformation rules and assembly methods are proposed to apply probabilistic model checking for safety analysis, and PRISM models are derived from AADL models. Two formulae are also formulated to obtain quantitative safety properties for verifying occurrence probabilities of failures, and qualitative safety properties for generating corresponding witnesses to figure out propagation paths for fault propagation analysis respectively. Finally, the effectiveness of the proposed method is verified by adopting a Power Boat Autopilot (PBA) system. [ABSTRACT FROM AUTHOR]

Although Unified Modeling Language (UML) state machines constitute a convenient modeling formalism that is widely used in many applications, the lack of formal semantics impedes carrying out automatic processing, such as formal verification. In this article, we aim to achieve a proven translation from a subset of UML state machines to timed automata. A generic abstract syntax is defined for state machines that allows us to specify state machines as a tree-like structure, explicitly illustrating the hierarchical relationships within the model. Based on this syntax, a formal asynchronous semantics for state machines and systems of state machines is established. Additionally, the semantics of timed automata is specified. Then, a translation relation from the considered set of state machines to timed automata is defined and a strong equivalence relation — namely, a timed bisimulation between the source and target models — is formally proven. The proof is carried out inductively while considering continuous (time) and discrete transitions separately. This proof allows us to demonstrate a strong similitude between these models. [ABSTRACT FROM AUTHOR]

The paper describes elements of an original approach that uses the principles of model-driven development and transformation to create prototypes of virtual assistants. Models of all levels of abstraction (concretization) are presented, with special attention paid to computational-independent and platform-independent models in the form of ontologies. Fragments of transformation of model elements are shown. A description of the main stages of the proposed approach is given in the context of solving the problem of diagnosing the aircraft power supply system. [ABSTRACT FROM AUTHOR]

Model transformation, which is a program targeting at transforming an input model to an output model, has been a critical basis for Model-Driven Engineering (MDE). The quality of model transformation programs directly affects the quality of software products built with MDE activities. Therefore, debugging model transformation programs has been crucial from the quality assurance point of view. One of the key impediments to the model transformation debugging is the high complexity and scale of the input models. In order to ameliorate the burden on model transformation debugging, this study proposes an effective approach to systematically reduce input models of model transformation programs. By combining the advantages of input simplification approaches for traditional programs and also the characteristics of model transformation, our approach leverages and adapts the delta debugging technique to model simplification. We conduct experiments to evaluate the proposed approach from two aspects: its effectiveness in model simplification, and its effects on model transformation debugging. Our experimental results confirm the positive contributions of the approach in both aspects. It delivers promising reduction effectiveness, and it can also well support the fault localization in model transformations. [ABSTRACT FROM AUTHOR]

As Internet-based technology spreads to most areas of life, it becomes a challenge to grasp opportunities arising from enormous amounts of data being generated from various sources such as smart homes, smart cities, health care systems and industries. Efficient utilization of these data can enable us to improve many human practices, including those connected to health care. In the present study, we focus on the health care sector, as it consists of large-scale organizations that rely on the processing of big data and complex processing of information. Due to the dynamic nature and complexity of this domain, it is essential to develop sophisticated technologies for the efficient processing of vast amounts of information. There is, for example, a need for interactive tools that can visualise actual care processes being executed in the hospital. A tool visualising real-time data could give a dynamic view of the processes, with accurate quantitative information, which can be used to improve the quality and efficiency of health care provision. These tools should be built on the requirements of practitioners needs and requirements, to ensure their relevance and practical utility. In this paper, we present a user-driven design process for developing therapy data visualisation components of guided Internet-based cognitive behaviour therapy (iCBT) and their evaluation. In order to ensure the reusability of the visual components, we propose to utilise a model-based approach which allows data analysts to adapt domain models by means of model transformation and transform them into visualization. [ABSTRACT FROM AUTHOR]

Many powerful metamodeling platforms enabling model-driven software engineering (MDSE) exist, each with its strengths, weaknesses, functionalities, programming language(s), and developer community. Platform interoperability would enable users to exploit their mutual benefits. Such interoperability would allow the transformation of metamodels and models created in one platform into equivalent metamodels and models in other platforms. Language engineers could then freely choose the metamodeling platform without risking a lock-in effect. Two well-documented and publicly available metamodeling platforms are the eclipse modeling framework (EMF) and the modeling SDK for visual studio (MSDKVS). In this paper, we propose an M3-level-bridge (M3B) that establishes interoperability between EMF and MSDKVS on the abstract syntax level and on the graphical concrete syntax level. To establish such interoperability we (i) compare the two platforms, (ii) present a conceptual mapping between them, and (iii) implement a bidirectional transformation bridge including both the metamodel and model layer. We evaluate our approach by transforming a collection of publicly available metamodels and automatically generated or manually created models thereof. The transformation outcomes are then used to quantitatively and qualitatively evaluate the transformation's validity, executability, and expressiveness. [ABSTRACT FROM AUTHOR]

Both the SysML and Modelica standards are used in the field of Systems Engineering (SE) to model systems from different perspectives, on different abstraction levels. SysML is strong when modeling systems on a functional level because it provides different views. With the capabilities of other simulation specifications, the engineers can simulate the system architecture. On the other hand, an open standard, such as Modelica is a key enabler for representing multi‐physical systems described by differential, algebraic, and discrete equations. With the symbolic manipulation, the dynamics of the systems are represented in state space form, and solved by the numerical integration methods fixed or variable step. However, it is clear that the connection between systems engineering and system simulation, with their respective domain knowledge of the actual equipment in their system, is missing. By seeing these complementary values, the authors demonstrate language interaction to integrate SysML and Modelica to achieve complimentary values through bi‐directional transformation and simulation. [ABSTRACT FROM AUTHOR]

The paper emphasizes the critical importance of the initial phase in IT project development to avoid implementation errors. It argues that minimizing these errors can be achieved by developing project artifacts at the early stage using a model-driven engineering-based approach. Model transformation plays a basic role in that context. The goal of this paper is to survey publications in which the authors propose generating initial project elements through model-driven engineering and to analyze the level of model transformations offered in their solutions. As a result, the authors would highlight the necessity of understanding which elements of a project can be obtained through automatic transformations and which still require manual manipulation. This distinction is crucial, as it can significantly influence the efficiency and accuracy of the project’s early phases. In general, identifying the project components that can be reliably generated through model transformations helps streamline the project inception and elaboration process performed before IT product implementation.

This study presents the development of an adaptive fuzzy control strategy for double-star PMSM-PWM inverters used in ship electrical propulsion. The approach addresses the current and speed tracking challenges of double-star permanent magnet synchronous motors (DSPMSMs) in the presence of parametric uncertainties. Initially, a modeling technique employing a matrix transformation method is introduced, generating decoupled and independent star windings to eliminate inductive couplings, while maintaining model consistency and torque control. The precise DSPMSM model serves as the foundation for an unknown nonlinear backstepping controller, approximated directly using an adaptive fuzzy controller. Through the Lyapunov direct method, system stability is demonstrated. All signals in the closed-loop system are ensured to be uniformly ultimately bounded (UUB). The proposed control system aims for low tracking errors, while also mitigating the impact of parametric uncertainties. The effectiveness of the adaptive fuzzy nonlinear control system is validated through tests conducted in hardware-in-the-loop (HIL) simulations, utilizing the OPAL-RT platform, OP4510. [ABSTRACT FROM AUTHOR]

In order to fully utilize the control degrees of freedom of a multi-three-phase-star smooth-pole permanent magnet synchronous motor (PMSM), this paper first develops a modeling approach using a new matrix transformation method. The proposed transformation produces decoupled and independent star windings, removing the inductive couplings and preserving the model and torque control's consistency as the number of phases increases. The model, together with a new vector control scheme, is superior for studying the effect of the winding phase angle shift on motor performance. Based on a numerical simulation, this paper focuses on the quality analysis of phase currents, non-sequential currents, and torque ripple with different phase angles for double- and triple-star PMSM drives. The control of a triple-star PMSM is validated, and the behavior analysis is investigated by OPAL-RT. [ABSTRACT FROM AUTHOR]

To apply the interference alignment (IA) technology to practical communication networks effectively, the low complexity IA design problem still needs to be solved well. In this paper, we study the low complexity closed-form IA design method, for the multiple-cell multiple-user multiple-input multiple-output (MIMO) cellular interference network. To eliminate the complex interference conveniently, the multiple-cell multiple-user cellular network model is transformed into several relatively simple network models. Based on the model transformation of the cellular network, the IA precoding is divided into two parts. Then the two-stage IA design scheme is proposed, which includes the outer IA design and inter one. The former is to eliminate the inter-cell interference, while the latter is to eliminate the inter-user interference. Simulation results show the higher system sum-rate performance and low computational complexity of the proposed IA design scheme. [ABSTRACT FROM AUTHOR]

Model Driven Engineering (MDE) adoption in the industry suffers from many technical and non-technical problems. One of the significant technical problems lies in the difficulty of building complex transformations from the composition of small and reusable transformations. Another problem resides in developing transformations from scratch in case they are missing. In this paper, we present an approach to how to handle these issues. The approach allows composing reusable transformations to build more complex ones by providing a catalog of prebuilt transformations targeting common architectures, frameworks, and design patterns. To give guidance and simplify the task of developing new transformations, we describe a platform description model of an entire system or a part of it in two views: a UML profile and a set of transformations. We also present three transformation types, each of which handles different abstraction design concerns. Generic transformations are small and reusable to build complex transformations, system-independent transformations are reusable and implement high-level design decisions, and system-specific transformations are not reusable and implement all design decisions needed for a given system. The approach is implemented as a plugin for a UML modeling tool and validated by developing a system that simulates the behavior of a gas station through model transformations built from the composition of reusable transformations.

Model-driven development (MDD) in the Artificial Intelligence of Things (AIoT) domain faces significant challenges in ensuring the consistency and preservation of model properties during transformations, often leading to system inconsistencies. This research introduces the Property Preservation Framework (PPF), a novel approach fortified with a Markov chain methodology, specifically designed to address these challenges. The PPF integrates formal procedures and constraint-checking methods to systematically validate and preserve model properties, thereby enhancing the reliability of AIoT systems. Through empirical evaluations, the framework has demonstrated its ability to efficiently determine and verify model characteristics at various transformation stages, significantly reducing the incidence of property violations. The results indicate that the PPF not only ensures overall consistency and reliability but also optimizes resource allocation, thereby enhancing data efficiency during the property validation and preservation processes. These advancements make a substantial contribution to the domain of MDD, providing developers with the methodology to execute model transformations that accurately reflect system requirements and behaviors in AIoT ecosystems. The findings underscore the potential of the PPF to revolutionize AIoT development by ensuring high-quality, dependable, and efficient modeling outcomes.

The reasonableness and accuracy of engineering design are often assessed through the use of a variety of structural design analysis software, which are then compared and verified. However, it is challenging for a single analysis software to meet the diverse and complex design requirements. In order to meet the specific engineering requirements, it is necessary to convert the MIDAS result model into an ANSYS structural model and conduct a nonlinear analysis and simulation in ANSYS. Nevertheless, the existing interface is unable to facilitate direct conversion of the model. Accordingly, this paper presents a Python-based ANSYS APDL program that enables the complete conversion of MIDAS GEN structural models to ANSYS finite element models. The program is capable of converting a range of data, including material, section, element, connection, load, node mass, constraint, time history function, and so forth. The program is capable of converting specific connection units, including elastic and general connection units. Additionally, the beam-column section direction, beam end freedom release, rigid element, and special anti-rocking structure of the structure can be considered. Ultimately, the theatre model is transformed. Following a comparison of the analysis results, it was found that the mass and mode of the model before and after the transformation were essentially identical. The maximum error of the first six orders of the structure is 2.95%, with the structural displacement under gravity load remaining essentially unchanged. The research and analysis demonstrate the accuracy and reliability of the MIDAS GEN conversion ANSYS program. The conversion program significantly reduces the time required for direct modeling in ANSYS, enhancing work efficiency. The study has considerable practical significance for the seismic sway design and analysis of buildings based on vibration isolation design.

The 38th issue of CSIMQ comprises four articles selected by guest issue editors on topics related to novel decision support methods or model-based frameworks for evolving or evaluating information systems. Design-oriented research is the dominant approach in these works, balancing technical design decisions insights with empirical evaluation cases. Three of the selected articles contribute with decision-support methods or frameworks – for ESG (Environment-Social-Governance) accounting, for democratized decision services, and for information security management. The fourth article revisits UML-based model-driven software development from a new perspective.

Architecture-Driven Modernization (ADM) is a special kind of reengineering that employs models along the process. The main ADM metamodel is the Knowledge Discovery Metamodel (KDM), which is a platform-independent metamodel able to represent several views of a system. Although a lot of research is currently focused on the reverse engineering phase of ADM, little has been devoted to the forward engineering one, mainly on the generation of Platform-Specific Models (PSMs) from KDM. The forward engineering phase is essential because it belongs to the end of the horseshoe model, completing the reengineering process. Besides, the lack of research and the absence of tooling support in this phase hinder the industrial adoption of ADM. Therefore, in this paper, we present a process for creating Transformation Engines (TEs) capable of transforming KDM instances in a chosen PSM. We highlight two main contributions in this work. The first is a process that software engineers can follow for building TEs capable of generating PSM instances (e.g., Java model, Python model, etc.) from KDM instances. Having that on their hands, modernization engineers can then use generators for generating language-specific source code from the PSM. The second is delivering a specific TE called RUTE-K2J, which is able to generate Java models from KDM models. The transformation rules of RUTE-K2J have been tested considering sets of common code structures that normally appear when modernizing systems. The test cases have shown that in this version of RUTE the transformation rules are able to correctly generate 92% of the source code submitted to the transformation. [ABSTRACT FROM AUTHOR]

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With digital patient data increasing due to new diagnostic methods and technology, showing the right data in the context of decision support at the point of care becomes an even greater challenge. Standard operating procedures (SOPs) modeled in BPMN (Business Process Model and Notation) contain evidence-based treatment guidance for all phases of a certain diagnosis, while physicians need the parts relevant to a specific patient at a specific point in the clinical process. Therefore, integration of patient data from electronic health records (EHRs) providing context to clinicians is needed, which is stored and communicated in HL7 (Health Level Seven) FHIR (Fast Healthcare Interoperability Resources). To address this issue, we propose a method combining an integration of stored data into BPMN and a loss-free transformation from BPMN into FHIR, and vice versa. Based on that method, an identification of the next necessary decision point in a specific patient context is possible. We verified the method for treatment of malignant melanoma by using an extract of a formalized SOP document with predefined decision points and validated FHIR references with real EHR data. The patient data could be stored and integrated into the BPMN element 'DataStoreReference'. Our loss-free transformation process therefore is the foundation for combining evidence-based knowledge from formalized clinical guidelines or SOPs and patient data from EHRs stored in FHIR. Processing the SOP with the available patient data can then lead to the next upcoming decision point, which will be displayed to the physician integrated with the corresponding data. [ABSTRACT FROM AUTHOR]

Context: This paper engages with the question of how one can arrive at more coherent explanations of social behavior in coupled socio-ecological systems. Objectives: The paper aims to give a counterargument to the assumption that social theory in coupled socio-ecological systems can only be developed in one way, as such showing that the premise of the special issue deserves further scrutiny. Methods: Current issues are identified and categorized based on a literature survey; likewise, the solutions derive from methodological literature, in particular from the realm of critical realism. Results: The paper shows how a set of assumptions about the nature of socio-ecological systems and about the nature of theory derived from observations prohibit a deeper understanding of how social theory may be developed at the nexus of coupled socio-ecological systems. Researchers should engage more clearly with movements between theories, models and data, and movements between ontology, epistemology and data. Conclusions: Landscape ecology can—and should—accommodate social theory in its analysis but from a different premise than is currently often the case. The proposed operations will contribute to a complexity-informed understanding of human behavior in coupled socio-ecological systems. [ABSTRACT FROM AUTHOR]