A semantic web services-based infrastructure for context-adaptive process support

Current technologies aimed at supporting processes whether it is a business or learning process - primarily follow a metadata- and data-centric paradigm. Whereas process metadata is usually based on a specific standard specification - such as the Business Process Modeling Notation (BPMN) or the IMS Learning Design Standard - the allocation of resources is done manually at design-time, and the used data is often specific to one process context only. These facts limit the reusability of process models across different standards and contexts. To overcome these issues, we introduce an innovative Semantic Web Service-based framework aimed at changing the current paradigm to a context-adaptive service-oriented approach. Following the idea of layered semantic abstractions, our approach supports the development of abstract semantic process model - reusable across different contexts and standards - that enables a dynamic adaptation to specific actor needs and objectives. To illustrate the application of our framework and establish its feasibility, we describe a prototypical application in the E-Learning domain

Minimum Information About a Simulation Experiment (MIASE)

Reproducibility of experiments is a basic requirement for science. Minimum Information (MI) guidelines have proved a helpful means of enabling reuse of existing work in modern biology. The Minimum Information Required in the Annotation of Models (MIRIAM) guidelines promote the exchange and reuse of biochemical computational models. However, information about a model alone is not sufficient to enable its efficient reuse in a computational setting. Advanced numerical algorithms and complex modeling workflows used in modern computational biology make reproduction of simulations difficult. It is therefore essential to define the core information necessary to perform simulations of those models. The Minimum Information About a Simulation Experiment (MIASE, Glossary in Box 1) describes the minimal set of information that must be provided to make the description of a simulation experiment available to others. It includes the list of models to use and their modifications, all the simulation procedures to apply and in which order, the processing of the raw numerical results, and the description of the final output. MIASE allows for the reproduction of any simulation experiment. The provision of this information, along with a set of required models, guarantees that the simulation experiment represents the intention of the original authors. Following MIASE guidelines will thus improve the quality of scientific reporting, and will also allow collaborative, more distributed efforts in computational modeling and simulation of biological processes

Adressing context-awareness and standards interoperability in e-learning: a service-oriented framework based on IRS III

Current technologies aimed at supporting learning goals primarily follow a data and metadata-centric paradigm. They provide the learner with appropriate learning content packages containing the learning process description as well as the learning resources. Whereas process metadata is usually based on a certain standard specification – such as ADL SCORM or the IMS Learning Design – the used learning resources – data or services - are specific to pre-defined learning contexts, and they are allocated manually at design-time. Therefore, a content package cannot consider the actual learning context, since this is only known at runtime of a learning process. These facts limit the reusability of a content package across different standards and contexts. To overcome these issues, this paper proposes an innovative Semantic Web Service-based approach that changes this data- and metadata-based paradigm to a context-adaptive service-oriented approach. In this approach, the learning process is semantically described as a standard-independent process model decomposed into several learning goals. These goals are accomplished at runtime, based on the automatic allocation of the most appropriate service. As a result, we address the dynamic adaptation to specific context and - providing the appropriate mappings to established metadata standards - we enable the reuse of the defined semantic learning process model across different standards. To illustrate the application of our approach and to prove its feasibility, a prototypical application based on an initial use case scenario is proposed

Bringing the OpenMI to LIFE Progress Report No. 4 - 31st March 2008 – 30th September 2008

The Water Framework Directive demands an integrated approach to water management. This requires the ability to predict how catchment processes will behave and interact in response to the activities of water managers and others. In most contexts, it is not feasible to build a single predictive model that adequately represents all the processes; therefore a means of linking models of individual processes is required. This is met by the FP5 HarmonIT project’s Open Modelling Interface and Environment (the OpenMI). The purpose of this project is to transform the OpenMI from a research output to a sustainable operational Standard. It will build the capacity to use the OpenMI and will demonstrate it under operational conditions. It will also develop, test and demonstrate the future support organisation for the OpenMI. Finally, information about the OpenMI will be disseminated to users

Real-Time Distributed Aircraft Simulation through HLA

This paper presents some ongoing researches carried out in the context of the PRISE (Research Platform for Embedded Systems Engineering) Project. This platform has been designed to evaluate and validate new embedded system concepts and techniques through a special hardware and software environment. Since many actual embedded equipments are not available, their corresponding behavior is simulated using the HLA architecture, an IEEE standard for distributed simulation, and a Run-time infrastructure called CERTI and developed at ONERA. HLA is currently largely used in many simulation applications, but the limited performances of the RTIs raises doubts over the feasibility of HLA federations with real-time requirements. This paper addresses the problem of achieving real-time performances with HLA. Several experiments are discussed using well-known aircraft simulators such as the Microsoft Flight Simulator, FlightGear, and X-plane connected with the CERTI Run-time Infrastructure. The added value of these activities is to demonstrate that according to a set of innovative solutions, HLA is well suited to achieve hard real time constraints

Towards adaptive e-learning applications based on Semantic Web Services

The current state of the art in supporting E-Learning objectives is primarily based on providing a learner with learning content by using metadata standards like ADL SCORM 2004 or IMS Learning Design. By following this approach, several issues can be observed including high development costs due to a limited reusability across different standards and learning contexts. To overcome these issues, our approach changes this data-centric paradigm to a highly dynamic service-oriented approach. By following this approach, learning objectives are supported based on a automatic allocation of services instead of a manual composition of learning data. Our approach is fundamentally based on current Semantic Web Service (SWS) technology and considers mappings between different learning metadata standards as well as ontological concepts for E-Learning. Since our approach is based on a dynamic selection and invocation of SWS appropriate to achieve a given learning objective within a specific learning context, it enables the dynamic adaptation to specific learning needs as well as a high level of reusability across different learning contexts

Teaching old sensors New tricks: archetypes of intelligence

In this paper a generic intelligent sensor software architecture is described which builds upon the basic requirements of related industry standards (IEEE 1451 and SEVA BS- 7986). It incorporates specific functionalities such as real-time fault detection, drift compensation, adaptation to environmental changes and autonomous reconfiguration. The modular based structure of the intelligent sensor architecture provides enhanced flexibility in regard to the choice of specific algorithmic realizations. In this context, the particular aspects of fault detection and drift estimation are discussed. A mixed indicative/corrective fault detection approach is proposed while it is demonstrated that reversible/irreversible state dependent drift can be estimated using generic algorithms such as the EKF or on-line density estimators. Finally, a parsimonious density estimator is presented and validated through simulated and real data for use in an operating regime dependent fault detection framework

HLA high performance and real-time simulation studies with CERTI

Our work takes place in the context of the HLA standard and its application in real-time systems context. Indeed, current HLA standard is inadequate for taking into consideration the different constraints involved in real-time computer systems. Many works have been invested in order to provide real-time capabilities to Run Time Infrastructures (RTI). This paper describes our approach focusing on achieving hard real-time properties for HLA federations through a complete state of the art on the related domain. Our paper also proposes a global bottom up approach from basic hardware and software basic requirements to experimental tests for validation of distributed real-time simulation with CERTI