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Since the emergence of Service Oriented Architecture and its implementation with the Web services technology, combining several Web services to response to a complex request presented a hard challenge. This is an area that has attracted the interest of many research organizations and manufactories. This paper firstly describes the developed approach of web services composition based on Model Driven Approach, and using different languages and systems, like Multi-Agent Reactive Decisional system for the modeling task and Business Process Execution language for the implementation task. Secondly, the paper seeks to presents the application of this approach in the online learning domain. In brief, this document proposes the design and implementation of an e-learning platform based on Web services composition.

There are many tasks in the oil and gas industry in which the individual's health may pose a risk on the individual's and others’ safety. In addition, some tasks may negatively impact the health of individuals with pre-existing health conditions. Fitness to Work (FTW) assures that individuals are able to complete tasks safely without unacceptable risk to themselves, their employing company or a third party. This is done through the objective assessment of health of employees in relation to their specific jobs. There is currently no standardized approach for FTW in the oil and gas industry, resulting in a wide variety of practices among operators. The proposed risk-based FTW design process includes 5 key steps: Health risk assessment, Control options, Legal assessment, Implementation, and Review. Each step is discussed with best practice examples, lessons from real-world implementation, and common pitfalls. Outcomes and consequences of FTW assessments are also discussed. Based on 6 years of global implementation, this approach represents an effective model of systematic identification, assessment and management of the risks associated with tasks that place specific physical or psychological demands on employees.

Web services are a way for businesses to offer their services over the Web. The concept of semantic Web services, is the fruit of the convergence of Web services field with the Semantic Web, indeed its main objective is to make web services more accessible to the machine by automating the various tasks of their life cycle such as discovery, selection, invocation and composition. In this work, we study the problem of semantic discovery of services by exposing a state of the art on the discovery approaches achieved, and proposing a method that is based on Multi-Agent Reactive Decisional Systems (MARDS) and ontologies. The use of a multi-agent system ensures great flexibility in our proposed approach.

The main objective of today's companies is to cope with rapid changes in the environment. For this, they must ensure the integration and interoperability of their applications. To manage and automate the life cycle of these applications, companies are adopting web services technology. The current problem is that the content of these web services cannot be processed automatically. Only humans can interpret its contents. The semantic web is a new vision of the web that promises to overcome this difficulty. The goal of this technology is to automate the retrieval, assembly, and selection of web services. In this post, we are interested in semantic detection of web services. The main problem is automatically discovering web services on request from clients. Against this background, we first describe the principle of the proposed detection mechanism and then present the designed matchmaking algorithm. Finally, we implement our proposed method. To verify our work, we run tests against various user requests and web service panels. As part of a case study, we consider an online hospital problem. This problem is a typical web service discovery scenario to which the concepts of our method are applied.