Motion Rail: A Virtual Reality Level Crossing Training Application

This paper presents the development and usability testing of a Virtual Reality (VR) based system named 'Motion Rail' for training children on railway crossing safety. The children are to use a VR head mounted device and a controller to navigate the VR environment to perform a level crossing task and they will receive instant feedback on pass or failure on a display in the VR environment. Five participants consisting of two male and three females were considered for the usability test. The outcomes of the test was promising, as the children were very engaging and will like to adopt this training approach in future safety training

Integration of DFDs into a UML - based model-driven engineering approach

The main aim of this article is to discuss how the functional and the object-oriented views can be inter-played to represent the various modeling perspectives of embedded systems.We discuss whether the object-oriented modeling paradigm, the predominant one to develop software at the present time, is also adequate for modeling embedded software and how it can be used with the functional paradigm.More specifically, we present how the main modeling tool of the traditional structured methods, data flow diagrams, can be integrated in an object-oriented development strategy based on the unified modeling language. The rationale behind the approach is that both views are important for modeling purposes in embedded systems environments, and thus a combined and integrated model is not only useful, but also fundamental for developing complex systems. The approach was integrated in amodel-driven engineering process, where tool support for the models used was provided. In addition, model transformations have been specified and implemented to automate the process.We exemplify the approach with an IPv6 router case study.FEDER -Fundação para a Ciência e a Tecnologia(HH-02-383

Developing Ontologies withing Decentralized Settings

This chapter addresses two research questions: “How should a well-engineered methodology facilitate the development of ontologies within communities of practice?” and “What methodology should be used?” If ontologies are to be developed by communities then the ontology development life cycle should be better understood within this context. This chapter presents the Melting Point (MP), a proposed new methodology for developing ontologies within decentralised settings. It describes how MP was developed by taking best practices from other methodologies, provides details on recommended steps and recommended processes, and compares MP with alternatives. The methodology presented here is the product of direct first-hand experience and observation of biological communities of practice in which some of the authors have been involved. The Melting Point is a methodology engineered for decentralised communities of practice for which the designers of technology and the users may be the same group. As such, MP provides a potential foundation for the establishment of standard practices for ontology engineering

Conversational Interfaces for Explainable AI: A Human-Centered Approach

One major goal of Explainable Artificial Intelligence (XAI), in order to enhance trust in technology, is to enable the user to enquire information and explanation about its functionality directly from an intelligent agent. We propose conversational interfaces (CI) to be the perfect setting, since they are intuitive for humans and computationally processible. While there are many approaches addressing technical issues of this human-agent communication problem, the user perspective appears to be widely neglected. With the purpose of better requirement understanding and identification of implicit expectations from a human-centered view, a Wizard of Oz experiment was conducted, where participants tried to elicit basic information from a pretended artificial agent (What are your capabilities?). The hypothesis that users pursue fundamentally different strategies could be verified with the help of Conversation Analysis. Results illustrate the vast variety in human communication and disclose both requirements of users and obstacles in the implementation of protocols for interacting agents. Finally, we infer essential indications for the implementation of such a CI

Towards Declarative Programming of Conceptual Models

This article introduces some basic functions and architectural issues, that help to build a tool for programming conceptual models, and that is not specific for a particular problem class or problem solving method. Our work is based on the KADS-method, that had to be modified in some points, to enable declarative programming of inference knowledge as well as domain knowledge. It is shown, how knowledge sources can be described as semantic network modules. Knowledge sources are instantiated from generic descriptions. All resulting semantic networks are part of a modular knowledge base, each module representing the knowledge on its own right level of granularity. Functions are introduced, that define views between semantic networks. They help connecting declarative representation of knowledge sources on the inference layer to parts of the domain layer network. We only contemplate the interconnection of domain and inference layer. 1. Introduction 1.1. Notions First, to avoid misconception..