Abstract: Since the process of transforming user requirements to modeling constructs are not very well supported by domain-specific frameworks, it became necessary to integrate domain requirements with the specific architectures to achieve an integrated customizable solutions space via artifact orientation. Domain-specific modeling language specifications of model-driven engineering technologies focus more on requirements within a particular domain, which can be tailored to aid the domain expert in expressing domain concepts effectively. Modeling processes through domain-specific language formalisms are highly volatile due to dependencies on domain concepts or used process models. A capable solution is given by artifact orientation that stresses on the results rather than expressing a strict dependence on complicated platforms for model creation and development. Based on this premise, domain-specific methods for producing artifacts without having to take into account the complexity and variability of platforms for model definitions can be integrated to support customizable development. In this paper, we discuss methods for the integration capabilities and necessities within a common structure and semantics that contribute a metamodel for artifact-orientation, which leads to a reusable software layer with concrete syntax capable of determining design intents from domain expert. These concepts forming the language formalism are established from models explained within the oil and gas pipelines industry.
Abstract: As a process of developing a service system, the term ‘service engineering’ evolves in scope and definition. To achieve an integrated understanding of the process, a general framework and an ontology are required. This paper extends a previously built service engineering framework by exploring metamodels for the framework artefacts based on a foundational ontology and a metamodel landscape. The first part of this paper presents a correlation map between the proposed framework with the ontology as a form of evaluation for the conceptual coverage of the framework. The mapping also serves to characterize the artefacts to be produced for each activity in the framework. The second part describes potential metamodels to be used, from the metamodel landscape, as alternative formats of the framework artefacts. The results suggest that the framework sufficiently covers the ontological concepts, both from general service context and software service context. The metamodel exploration enriches the suggested artefact format from the original eighteen formats to thirty metamodel alternatives.
Abstract: The aeronautics sector is currently living an unprecedented growth largely due to innovative projects. In several cases, such innovative developments are being carried out by Small and Medium sized-Enterprises (SMEs). For instance, in Europe, a handful of SMEs are leading projects like airships, large civil drones, or flying cars. These SMEs have all limited resources, must make strategic decisions, take considerable financial risks and in the same time must take into account the constraints of safety, cost, time and performance as any commercial organization in this industry. Moreover, today, no international regulations fully exist for the development and certification of this kind of projects. The absence of such a precise and sufficiently detailed regulatory framework requires a very close contact with regulatory instances. But, SMEs do not always have sufficient resources and internal knowledge to handle this complexity and to discuss these issues. This poses additional challenges for those SMEs that have system integration responsibilities and that must provide all the necessary means of compliance to demonstrate their ability to design, produce, and operate airships with the expected level of safety and reliability. The final objective of our research is thus to provide a methodological framework supporting SMEs in their development taking into account recent innovation and institutional rules of the sector. We aim to provide a contribution to the problematic by developing a specific Model-Based Systems Engineering (MBSE) approach. Airspace regulation, aeronautics standards and international norms on systems engineering are taken on board to be formalized in a set of models. This paper presents the on-going research project combining Systems Engineering and Project Management process modeling and taking into account the metamodeling problematic.
Abstract: Wireless Sensor Networks (WSNs) have always been characterized for application-specific sensing, relaying and collection of information for further analysis. However, software development was not considered as a separate entity in this process of data collection which has posed severe limitations on the software development for WSN. Software development for WSN is a complex process since the components involved are data-driven, network-driven and application-driven in nature. This implies that there is a tremendous need for the separation of concern from the software development perspective. A layered approach for developing data acquisition design based on Model Driven Development (MDD) has been proposed as the sensed data collection process itself varies depending upon the application taken into consideration. This work focuses on the layered view of the data acquisition process so as to ease the software point of development. A metamodel has been proposed that enables reusability and realization of the software development as an adaptable component for WSN systems. Further, observing users perception indicates that proposed model helps in improving the programmer's productivity by realizing the collaborative system involved.
Abstract: The trend of digitization significantly changes the role of data for enterprises. Data turn from an enabler to an intangible organizational asset that requires management and qualifies as a tradeable good. The idea of a networked economy has gained momentum in the data domain as collaborative approaches for data management emerge. Traditional organizational knowledge consequently needs to be extended by comprehensive knowledge about data. The knowledge about data is vital for organizations to ensure that data quality requirements are met and data can be effectively utilized and sovereignly governed. As this specific knowledge has been paid little attention to so far by academics, the aim of the research presented in this paper is to conceptualize it by proposing a “data knowledge model”. Relevant model entities have been identified based on a design science research (DSR) approach that iteratively integrates insights of various industry case studies and literature research.
Abstract: Surrogate model has received increasing attention for use in detecting damage of structures based on vibration modal parameters. However, uncertainties existing in the measured vibration data may lead to false or unreliable output result from such model. In this study, an efficient approach based on Monte Carlo simulation is proposed to take into account the effect of uncertainties in developing a surrogate model. The probability of damage existence (PDE) is calculated based on the probability density function of the existence of undamaged and damaged states. The kriging technique allows one to genuinely quantify the surrogate error, therefore it is chosen as metamodeling technique. Enhanced version of ideal gas molecular movement (EIGMM) algorithm is used as main algorithm for model updating. The developed approach is applied to detect simulated damage in numerical models of 72-bar space truss and 120-bar dome truss. The simulation results show the proposed method can perform well in probability-based damage detection of structures with less computational effort compared to direct finite element model.
Abstract: In the present case study we examined the development and testing methods of systems that contain safety-critical elements in different industrial fields. Consequentially, we observed the classical object-oriented development and testing environment, as both medical technology and automobile industry approaches the development of safety critical elements that way. Subsequently, we examined model-based development. We introduce the quality parameters that define development and testing. While taking modern agile methodology (scrum) into consideration, we examined whether and to what extent the methodologies we found fit into this environment.
Abstract: This paper presents an approach for the model-driven
generating of Rich Internet Application (RIA) focusing on the
graphical aspect. We used well known Model-Driven Engineering
(MDE) frameworks and technologies, such as Eclipse Modeling
Framework (EMF), Graphical Modeling Framework (GMF), Query
View Transformation (QVTo) and Acceleo to enable the design and
the code automatic generation of the RIA. During the development of
the approach, we focused on the graphical aspect of the application
in terms of interfaces while opting for the Model View Presenter
pattern that is designed for graphics interfaces. The paper describes
the process followed to define the approach, the supporting tool and
presents the results from a case study.
Abstract: Average temperatures worldwide are expected to
continue to rise. At the same time, major cities in developing
countries are becoming increasingly populated and polluted.
Governments are tasked with the problem of overheating and air
quality in residential buildings. This paper presents the development
of a model, which is able to estimate the occupant exposure
to extreme temperatures and high air pollution within domestic
buildings. Building physics simulations were performed using the
EnergyPlus building physics software. An accurate metamodel is
then formed by randomly sampling building input parameters and
training on the outputs of EnergyPlus simulations. Metamodels are
used to vastly reduce the amount of computation time required when
performing optimisation and sensitivity analyses. Neural Networks
(NNs) have been compared to a Radial Basis Function (RBF)
algorithm when forming a metamodel. These techniques were
implemented using the PyBrain and scikit-learn python libraries,
respectively. NNs are shown to perform around 15% better than RBFs
when estimating overheating and air pollution metrics modelled by
EnergyPlus.
Abstract: The access to relevant information that is adapted to
user’s needs, preferences and environment is a challenge in many
applications running. That causes an appearance of context-aware
systems. To facilitate the development of this class of applications, it
is necessary that these applications share a common context
metamodel. In this article, we will present our context metamodel
that is defined using the OMG Meta Object facility (MOF).This
metamodel is based on the analysis and synthesis of context concepts
proposed in literature.
Abstract: We evaluate the performance of a numerical method
for global optimization of expensive functions. The method is using a
response surface to guide the search for the global optimum. This
metamodel could be based on radial basis functions, kriging, or a
combination of different models. We discuss how to set the cyclic
parameters of the optimization method to get a balance between local
and global search. We also discuss the eventual problem with Runge
oscillations in the response surface.
Abstract: The paper follows a discourse on computer-assisted
language learning. We examine problems of foreign language
teaching and learning and introduce a metamodel that can be used to
define learning models of language grammar structures in order to
support teacher/student interaction. Special attention is paid to the
concept of a virtual language lab. Our approach to language
education assumes to encourage learners to experiment with a
language and to learn by discovering patterns of grammatically
correct structures created and managed by a language expert.
Abstract: Global approximation using metamodel for complex
mathematical function or computer model over a large variable
domain is often needed in sensibility analysis, computer simulation,
optimal control, and global design optimization of complex, multiphysics
systems. To overcome the limitations of the existing
response surface (RS), surrogate or metamodel modeling methods for
complex models over large variable domain, a new adaptive and
regressive RS modeling method using quadratic functions and local
area model improvement schemes is introduced. The method applies
an iterative and Latin hypercube sampling based RS update process,
divides the entire domain of design variables into multiple cells,
identifies rougher cells with large modeling error, and further divides
these cells along the roughest dimension direction. A small number
of additional sampling points from the original, expensive model are
added over the small and isolated rough cells to improve the RS
model locally until the model accuracy criteria are satisfied. The
method then combines local RS cells to regenerate the global RS
model with satisfactory accuracy. An effective RS cells sorting
algorithm is also introduced to improve the efficiency of model
evaluation. Benchmark tests are presented and use of the new
metamodeling method to replace complex hybrid electrical vehicle
powertrain performance model in vehicle design optimization and
optimal control are discussed.
Abstract: Ontology-based modelling of multi-formatted
software application content is a challenging area in content
management. When the number of software content unit is huge and
in continuous process of change, content change management is
important. The management of content in this context requires
targeted access and manipulation methods. We present a novel
approach to deal with model-driven content-centric information
systems and access to their content. At the core of our approach is an
ontology-based semantic annotation technique for diversely
formatted content that can improve the accuracy of access and
systems evolution. Domain ontologies represent domain-specific
concepts and conform to metamodels. Different ontologies - from
application domain ontologies to software ontologies - capture and
model the different properties and perspectives on a software content
unit. Interdependencies between domain ontologies, the artifacts and
the content are captured through a trace model. The annotation traces
are formalised and a graph-based system is selected for the
representation of the annotation traces.
Abstract: Graph rewriting-based visual model processing is a
widely used technique for model transformation. Visual model
transformations often need to follow an algorithm that requires a
strict control over the execution sequence of the transformation steps.
Therefore, in Visual Model Processors (VMPs) the execution order
of the transformation steps is crucial. This paper presents the visual
control flow support of Visual Modeling and Transformation System
(VMTS), which facilitates composing complex model
transformations of simple transformation steps and executing them.
The VMTS Visual Control Flow Language (VCFL) uses stereotyped
activity diagrams to specify control flow structures and OCL
constraints to choose between different control flow branches. This
paper introduces VCFL, discusses its termination properties and
provides an algorithm to support the termination analysis of VCFL
transformations.
Abstract: Software organizations are constantly looking for
better solutions when designing and using well-defined software
processes for the development of their products and services.
However, while the technical aspects are virtually easier to arrange,
many software development processes lack more support on project
management issues. When adopting such processes, an organization
needs to apply good project management skills along with technical
views provided by those models. This research proposes the
definition of a new model that integrates the concepts of PMBOK
and those available on the OPEN metamodel, helping not only
process integration but also building the steps towards a more
comprehensive and automatable model.
Abstract: Modern managements of water distribution system
(WDS) need water quality models that are able to accurately predict
the dynamics of water quality variations within the distribution system
environment. Before water quality models can be applied to solve
system problems, they should be calibrated. Although former
researchers use GA solver to calibrate relative parameters, it is
difficult to apply on the large-scale or medium-scale real system for
long computational time. In this paper a new method is designed
which combines both macro and detailed model to optimize the water
quality parameters. This new combinational algorithm uses radial
basis function (RBF) metamodeling as a surrogate to be optimized for
the purpose of decreasing the times of time-consuming water quality
simulation and can realize rapidly the calibration of pipe wall reaction
coefficients of chlorine model of large-scaled WDS. After two cases
study this method is testified to be more efficient and promising, and
deserve to generalize in the future.
Abstract: Real-time embedded systems should benefit from
component-based software engineering to handle complexity and
deal with dependability. In these systems, applications should not
only be logically correct but also behave within time windows.
However, in the current component based software engineering
approaches, a few of component models handles time properties in
a manner that allows efficient analysis and checking at the
architectural level. In this paper, we present a meta-model for
component-based software description that integrates timing
issues. To achieve a complete functional model of software
components, our meta-model focuses on four functional aspects:
interface, static behavior, dynamic behavior, and interaction
protocol. With each aspect we have explicitly associated a time
model. Such a time model can be used to check a component-s
design against certain properties and to compute the timing
properties of component assemblies.
Abstract: CIM is the standard formalism for modeling management
information developed by the Distributed Management Task
Force (DMTF) in the context of its WBEM proposal, designed to
provide a conceptual view of the managed environment. In this
paper, we propose the inclusion of formal knowledge representation
techniques, based on Description Logics (DLs) and the Web Ontology
Language (OWL), in CIM-based conceptual modeling, and then we
examine the benefits of such a decision. The proposal is specified as a
CIM metamodel level mapping to a highly expressive subset of DLs
capable of capturing all the semantics of the models. The paper shows
how the proposed mapping can be used for automatic reasoning
about the management information models, as a design aid, by means
of new-generation CASE tools, thanks to the use of state-of-the-art
automatic reasoning systems that support the proposed logic and use
algorithms that are sound and complete with respect to the semantics.
Such a CASE tool framework has been developed by the authors and
its architecture is also introduced. The proposed formalization is not
only useful at design time, but also at run time through the use of
rational autonomous agents, in response to a need recently recognized
by the DMTF.
Abstract: CIM is the standard formalism for modeling management
information developed by the Distributed Management Task
Force (DMTF) in the context of its WBEM proposal, designed to
provide a conceptual view of the managed environment. In this
paper, we propose the inclusion of formal knowledge representation
techniques, based on Description Logics (DLs) and the Web Ontology
Language (OWL), in CIM-based conceptual modeling, and then we
examine the benefits of such a decision. The proposal is specified
as a CIM metamodel level mapping to a highly expressive subset
of DLs capable of capturing all the semantics of the models. The
paper shows how the proposed mapping provides CIM diagrams with
precise semantics and can be used for automatic reasoning about the
management information models, as a design aid, by means of newgeneration
CASE tools, thanks to the use of state-of-the-art automatic
reasoning systems that support the proposed logic and use algorithms
that are sound and complete with respect to the semantics. Such a
CASE tool framework has been developed by the authors and its
architecture is also introduced. The proposed formalization is not
only useful at design time, but also at run time through the use of
rational autonomous agents, in response to a need recently recognized
by the DMTF.