ABSTRACT As the size and the complexity of business process models are an important driver of error probability, it is recommended to split large models into smaller models. Hence, we propose, in this paper, to develop business process models by refinement. A refinement is a transformation of a source model to a target model expressed in the same modeling language. This transformation should preserve the semantics of the source model to provide semantically correct target model. Thus, we propose, in this paper, a domain specific language based on Business Process Model and Notation (BPMN) language for developing by refinement business process models correct‐by‐construction. Hence, we propose (i) a formal syntax throughout a context‐free grammar , (ii) axiomatic semantics to ensure the refinement correction when building business process models, (iii) operational semantics in terms of Kripke structure permitting formal verification of provided models to check their reliability. The Kripke structure supports the verification of behavioral requirements represented by the Computational Tree Logic (CTL) temporal logic and verified by NuSMV model checker. Based on these semantics, we prove the validity of the compiler that we have developed to assist developers when building their correct models and to transform these models to NuSMV code to prove their reliability.

The existence of various representations of the same ontology poses a challenge in terms of manipulating knowledge across different computational domains. To address this issue, it would be prudent to harmonise similar ontologies by reducing their level of heterogeneity. This proposed solution involves aligning comparable ontologies through the utilisation of established ontology schema-matching techniques. In this paper, we introduce an approach for ontology alignment that leverages these techniques along with machine learning algorithms. To accomplish this, we propose a method for constructing a matrix based on ontology matching techniques, specifically employing element matching and structure matching techniques facilitated by elementary matchers. Subsequently, once the matrix is constructed, we use a composite matcher as a classifier to determine the degree of similarity between the two ontologies. Since these matchers are not readily available, we put forth the idea of implementing them in this paper using various supervised machine learning algorithms such as Neural Network and Logistic Regression. To validate our approach, we conducted an empirical assessment using the Conference track and the benchmark track of the reference ontologies provided by the Ontology Alignment Evaluation Initiative (OAEI 1).

With the evolution of mobile devices such as laptops, tablets, smartphones, etc., the number of users has also increased, but it is difficult for some people due to their limited abilities. The Internet of Things (IoT) can make people's lives more convenient, and especially important for people with disabilities. This paper presents an approach to semantic representation using ontology. This approach is based on IoT to facilitate the real-time populating of the ontology in the context of adapting User Interfaces (UI) to people with disabilities such as sensory impairments (hearing and vision). IoT technology offers a great service to gain more autonomy and independence for people with disabilities.

In this paper, we present a reactive system for running flexible business process. We define two flexibility patterns based on BPMN (Business Process Model Notation) that deals with changes of resource requirements for business process. The business processes are built on an abstract level, using a BPMN model for the specification of the cloud service business process structure based on flexibility patterns, and the state-chart diagram for the specification of the cloud service business process behaviour. In fact, our approach is based on model driven engineering to facilitate the business process design for developers and free them from the lower cloud details during the running time of such applications. Moreover, the use of flexibility actions ensures the capacity of making a compromise between adapting rapidly and easily business process when running errors occur and keeping the effectiveness of these updated application models. This update is controlled by the real time system which is based on a machine learning algorithm to depict the appropriate cloud service to involve in the business process model using the right flexibility action. Finally, we present some results of our system.

Adaptive User Interfaces (AUI) have to exploit Artificial Intelligence powerful to adapt User Interfaces (UI)s to People With Disabilities (PWD). Thus, Machine Learning methods could master disabilities problems and barriers. In this paper, we propose a Reinforcement Learning (RL) based approach for resolving and surmounting PWD-UI interactions barriers since RL is good for learning good behavior. Hence, we have called the approach as RL-AUIAC as Reinforcement Learning of Adaptive User Interfaces for Accessibility Context. RL-AUIAC is based on three Knowledge Layers (KL)s depending on the kind of adaptation and the resolved problem at each layer. KL uses the Exploration-Exploitation dilemma to respond to the question: what to learn from each planned-adaptation sequences? In fact, Disability Knowledge Layer (DKL)learns UI structure behavior depending on the disability profile. Modality Knowledge Layer(MKL) learns facilities of adaptation on the basis of the couple. Platform Knowledge Layer (PKL) explores-exploits platform-knowledge to learn adaptation facilities on the basis of.

In this paper, we present a real time interactive system for running flexible workflow applications. This system facilitates the execution of these applications in terms of time execution complexity as it is based on flexibility mechanism. These workflows are built on an abstract level, through BPMN models using flexibility patterns. We define two flexibility patterns based on BPMN (Business Process Model Notation) that deals with changes of resource requirements for workflows. The provided models specify the functional view of workflows, whereas, their behavioral view is described using state-chart diagrams. A state-chart diagram represents the model specifying our real time system which controls the execution of workflow applications by making decisions on the use of flexibility actions. This execution is supported by the BPEL4WS engine that we have amended to execute flexible workflows and to be controlled by our real time system. Finally, we present some results of evaluations of our system.

In this paper we introduce a description mechanism for specifying the refinement approach for Business Process Modeling and Notations(BPMN). We present at each level of abstraction the syntax of this BPMN models by a context-free grammar. After that, for each refined BPMN, we analyze, automatically the change impact using NuSMV model checker. The change impact concerns the semantic preservation of BPMN models during the refinement process.

The BPMN2 language suffers from the absence of a precise formal semantics of the various notations used, which often leads to ambiguities. In addition, this language does not have a proof system that validates a BPMN2 specification. Consequently, the use of a formal method, such as Event B, is a solution for dealing with the shortcomings found in the BPMN2 language. We propose in this paper a model-driven approach based on meta-model and meta-model transformation implemented in KerMeta to specify and formally verify workflows.

Modeling complex workflow systems, using BPMN (Business Process Modeling Notation), is quite a hard task that cannot be done in one step. The step-wise refinement technique facilitates the understanding of complex systems by dealing with the major issues before getting involved in the details. The proposed approach allows an incrementally developing of more and more detailed models with preserving the correctness of BPMN refined models at each step. Hence, we provide a formal semantics for BPMN models based on Kripke structure and BPMN refinement patterns to provide formal verification of this correctness. This verification is ensured automatically by NuSMV model Checker based on a BPMN language to NuSMV language transformation. The refinement correctness are expressed as refinement safety properties specified with LTL (Linear Temporal Logic).

Cloud computing is a new model for deploying and executing flexible workflow composed of cloud services. One of the expected facilities of Cloud environments is flexibility at different levels. In this paper, we propose a Model-Driven Approach (MDA) for the specification and the execution of cloud service flexible workflow applications. We define two flexibility patterns based on BPMN(Business Process Model and Notation) that deals with changes of resource requirements for workflow. The workflows are built on an abstract level, using a BPMN model for the specification of the cloud service workflow structure based on flexibility patterns, and the state-chart diagram for the specification of the cloud service workflow behavior. The execution process is supervised by a control system which is responsible for making decisions on the execution of the workflow based on the behavior of the engine defined by the state-chart diagram.

In this paper we propose an model driven approach for the specification and the execution of flexible workflows composed from cloud services. Flexibility of workflow means fast reactivity to internal and external changes. The basic challenge for workflow now is the ability to respond dynamic changes. To fulfill, we define functional and behavioral views of the flexible workflow. The first view is modeling by BPMN language and the other by a the statechart model. Besides, we describe how the workflow reacts to dynamic changes. To be executed, workflow models should be translated into BPEL4WS language which will be executed by the BPEL4WS engine, the later is driven by the behavior described by the statechart model. In addition, we present an execution infrastructure suitable for the execution of flexible workflows.

In this paper, we present an approach to adapt the e-assessment workflow by considering learner's profiles. We have started by creating a learner profile ontology based on extraction data from e-assessment activities, file log and personal information. Then, we have defined three adaptation actions: Add Activity, Edit Activity and Delete Activity, applied on the workflow assessment and using information extracted from learner profile ontology instances. Each action is applied according to conditions. After that, we present some results of the empirical evaluation of our system.

This paper presents a meta-model transformation based approach to reasoning about sequence diagrams using B event. We present an approach for the specification and the verification of flexible Workflow applications of cloud services. Our approach is based on the semiformal notation of UML sequence diagrams, and the formal method B event. We have developed a tool called SD2EventB supporting the proposed approach. This tool allows the specification of flexible Cloud service Workflow application models using predefined flexibility patterns generated automatically by this tool. Once the model is specified, it is transformed to an event B model to be verified. In order to ensure this verification, we have used the platform Rodin supporting the event B method. This platform has been integrated into our tool. The transformation, as well, has been developed as a function of our tool using the meta-model transformation environment KerMeta.

We apply the Model-Driven Engineering for adapting User Interfaces (UI) in order to improve their accessibility into interactive system (IS). The solution that we propose has to be generic to be applicable in any context and with any type of UI. Therefore, we have developed a model driven approach based on meta-model transformations. This approach generates modality-based UI models adapted to each kind of disability. Hence, we have developed an accessibility context described with the type of disability, the used platform, the user identity, his/her situation and the surrounded environment. This context is defined with an ontology which will be used in the adaptation process. To generate Platform Independent and Specific UI Models, we have proposed a set of metamodel transformation rules.

Using Cloud Computing environment, the e-assessment process becomes an orchestration of a set of dedicated cloud services. In this paper, we propose an architecture for an e-assessment environment based on cloud services. This environment implements an approach that we have proposed to develop a generic e-assessment process which will be adapted to a learner profile. The e-assessment process activities and the adaptation process are implemented as Cloud services. Furthermore, they could be invoked from any existing Learning Management System (LMS).

Nowadays, there are many problems related to the e-learning in the development of E-assessment such as the difficulty to use the assessment object from a platform to another one. As the domain model reuse rate is very low in various e-learning systems and hardness to guarantee the consistency between designs and codes. Therefore, we need an approach aiming to generate a general process of the e-assessment. The present study describes an approach for integrating e-assessment functionalities of learning management systems (LMS) candidates into a generalized e-assessment process. To attempt these goals, we have studied different existing LMSs to depict their various e-assessment activities from which we have generated a set of generic e-assessment activities using the reverse engineering. Then, we have integrated these activities into a workflow model to specify a generic e-assessment process based on pedagogical scenarios. We have defined these scenarios using workflow to provide an abstract e-assessment process. Finally, we have implemented this generic e-assessment workflow as a cloud computing service to be invoked from any LMS.

Currently, there are many problems in the domain of the development of the e-Assessment process such as the difficulty to use a same e-assessment process by different e-learning platforms, the low rate of the e-assessment model reuse by various e-learning systems and the hardness to guarantee the consistency between designs and codes. Therefore, to resolve these problems, we need an approach aiming to develop a generic e-assessment process model which will be adapted automatically to any e-learning system. Hence, we propose a model driven approach for design flexible E-assessment process. We use an abstract description provided by UML activity diagram language and coupled with LTSA standards.

Currently, there are many problems of the application development of E-Assessment such as the difficulty to use the assessment object from a platform to another one. In addition, the domain model reuse rate is very low in various application systems, and hardness to guarantee the consistency between designs and codes. Therefore, to resolve these problems, we need an approach aiming to automate the modeling and coding processes in e-assessment system. The present study describes an approach, based on service cloud computing, for integrating e-assessment functionalities of candidate LMS systems into a generalized e-assessment process.

In order to ensure accessibility of user interface, it is highly recommended to elaborate a generic solution which is compliant to disable user requirements and best accommodates their particular needs. Therefore, we propose, in this paper, a generic MDA-based solution of adapting application's interface to accessibility context. It consists of generating, automatically, accessible adapted User Interfaces. Hence, we propose a multimodel approach by incorporating the modality of interaction into adaptation process. Consequently, based on MDA principals, we develop different meta-model transformations to provide an adapted User Interface model according to recent accessibility context information and a given non adapted User Interface.

We propose a workflow application constructive approach in which Event B models are built incrementally from UML AD models. Following our proposed approach, to be verified, workflow activity diagram models should be translated into Event B models which will be proved using the RODIN tool. To reach this objective, we propose, in this paper, a meta-model based transformation from UML AD to Event B models. To ensure the correctness and the completion of the transformation we propose a graph homomorphic mapping between the activity diagram and Event B models elements. By an example of workflow application we illustrate the proposed technique.

This paper focuses on how to model and compose workflow applications of Grid services without considering lower level description of the Grid environment. To reach this objective, we propose a model-driven approach (MDA) for developing workflow applications from existing Grid services. The workflows are built on an abstract level with semantic and syntactic descriptions of services available on the Grid using UML activity diagram language. As there are particular needs for modeling composed workflows of Grid services, we propose to extend the UML activity diagram notation. These extensions deal with additional information allowing a systematic composition of workflows and containing appropriate data to describe a Grid service. These data are useful for the execution of the resulting workflow.