Virtual integration platform for computational fluid dynamics

Computational Fluid Dynamics (CFD) tools used in shipbuilding industry involve multiple disciplines, such as resistance, manoeuvring, and cavitation. Traditionally, the analysis was performed separately and sequentially in each discipline, which often resulted in conflict and inconsistency of hydrodynamic prediction. In an effort to solve such problems for future CFD computations, a Virtual Integration Platform (VIP) has been developed in the University of Strathclyde within two EU FP6 projects - VIRTUE and SAFEDOR1. The VIP provides a holistic collaborative environment for designers with features such as Project/Process Management, Distributed Tools Integration, Global Optimisation, Version Management, and Knowledge Management. These features enhance collaboration among customers, ship design companies, shipyards, and consultancies not least because they bring together the best expertise and resources around the world. The platform has been tested in seven European ship design companies including consultancies. Its main functionalities along with advances are presented in this paper with two industrial applications

Piloting Multimodal Learning Analytics using Mobile Mixed Reality in Health Education

© 2019 IEEE. Mobile mixed reality has been shown to increase higher achievement and lower cognitive load within spatial disciplines. However, traditional methods of assessment restrict examiners ability to holistically assess spatial understanding. Multimodal learning analytics seeks to investigate how combinations of data types such as spatial data and traditional assessment can be combined to better understand both the learner and learning environment. This paper explores the pedagogical possibilities of a smartphone enabled mixed reality multimodal learning analytics case study for health education, focused on learning the anatomy of the heart. The context for this study is the first loop of a design based research study exploring the acquisition and retention of knowledge by piloting the proposed system with practicing health experts. Outcomes from the pilot study showed engagement and enthusiasm of the method among the experts, but also demonstrated problems to overcome in the pedagogical method before deployment with learners

The snowflake effect: the future of mashups and learning

Emerging technologies for learning report - Article exploring web mashups and their potential for educatio

VPOET: Using a Distributed Collaborative Platform for Semantic Web Applications

This paper describes a distributed collaborative wiki-based platform that has been designed to facilitate the development of Semantic Web applications. The applications designed using this platform are able to build semantic data through the cooperation of different developers and to exploit that semantic data. The paper shows a practical case study on the application VPOET, and how an application based on Google Gadgets has been designed to test VPOET and let human users exploit the semantic data created. This practical example can be used to show how different Semantic Web technologies can be integrated into a particular Web application, and how the knowledge can be cooperatively improved.Comment: accepted for the 2nd International Symposium on Intelligent Distributed Computing - IDC'2008. September 18-20, 2008, Catania, Ital

Using learning design as a framework for supporting the design and reuse of OER

The paper will argue that adopting a learning design methodology may provide a vehicle for enabling better design and reuse of Open Educational Resources (OERs). It will describe a learning design methodology, which is being developed and implemented at the Open University in the UK. The aim is to develop a 'pick and mix' learning design toolbox of different resources and tools to help designers/teachers make informed decisions about creating new or adapting existing learning activities. The methodology is applicable for designers/teachers designing in a traditional context – such as creation of materials as part of a formal curriculum, but also has value for those wanting to create OERs or adapt and repurpose existing OERs. With the increasing range of OERs now available through initiatives as part of the Open Courseware movement, we believe that methodologies, such as the one we describe in this paper, which can help guide reuse and adaptation will become increasingly important and arguably are an important aspect of ensuring longer term sustainability and uptake of OERs. Our approach adopts an empirically based approach to understanding and representing the design process. This includes a range of evaluation studies (capturing of case studies, interviews with designers/teachers, in-depth course evaluation and focus groups/workshops), which are helping to develop our understanding of how designers/teachers go about creating new learning activities. Alongside this we are collating an extensive set of tools and resources to support the design process, as well as developing a new Learning Design tool that helps teachers articulate and represent their design ideas. The paper will describe how we have adapted a mind mapping and argumentation tool, Compendium, for this purpose and how it is being used to help designers and teachers create and share learning activities. It will consider how initial evaluation of the use of the tool for learning design has been positive; users report that the tool is easy to use and helps them organise and articulate their learning designs. Importantly the tool also enables them to share and discuss their thinking about the design process. However it is also clear that visualising the design process is only one aspect of design, which is complex and multi-faceted

Using learning design as a framework for supporting the design and reuse of OER

The paper will argue that adopting a learning design methodology may provide a vehicle for enabling better design and reuse of Open Educational Resources (OERs). It will describe a learning design methodology, which is being developed and implemented at the Open University in the UK. The aim is to develop a 'pick and mix' learning design toolbox of different resources and tools to help designers/teachers make informed decisions about creating new or adapting existing learning activities. The methodology is applicable for designers/teachers designing in a traditional context – such as creation of materials as part of a formal curriculum, but also has value for those wanting to create OERs or adapt and repurpose existing OERs. With the increasing range of OERs now available through initiatives as part of the Open Courseware movement, we believe that methodologies, such as the one we describe in this paper, which can help guide reuse and adaptation will become increasingly important and arguably are an important aspect of ensuring longer term sustainability and uptake of OERs. Our approach adopts an empirically based approach to understanding and representing the design process. This includes a range of evaluation studies (capturing of case studies, interviews with designers/teachers, in-depth course evaluation and focus groups/workshops), which are helping to develop our understanding of how designers/teachers go about creating new learning activities. Alongside this we are collating an extensive set of tools and resources to support the design process, as well as developing a new Learning Design tool that helps teachers articulate and represent their design ideas. The paper will describe how we have adapted a mind mapping and argumentation tool, Compendium, for this purpose and how it is being used to help designers and teachers create and share learning activities. It will consider how initial evaluation of the use of the tool for learning design has been positive; users report that the tool is easy to use and helps them organise and articulate their learning designs. Importantly the tool also enables them to share and discuss their thinking about the design process. However it is also clear that visualising the design process is only one aspect of design, which is complex and multi-faceted

Knowledge creation and visualisation by using trade-off curves to enable set-based concurrent engineering

The increased international competition forces companies to sustain and improve market share through the production of a high quality product in a cost effective manner and in a shorter time. Set‑based concurrent engineering (SBCE), which is a core element of lean product development approach, has got the potential to decrease time‑to‑market as well as enhance product innovation to be produced in good quality and cost effective manner. A knowledge‑based environment is one of the important requ irements for a successful SBCE implementation. One way to provide this environment is the use of trade‑off curves (ToC). ToC is a tool to create and visualise knowledge in the way to understand the relationships between various conflicting design parame ters to each other. This paper presents an overview of different types of ToCs and the role of knowledge‑based ToCs in SBCE by employing an extensive literature review and industrial field study. It then proposes a process of generating and using knowledg e‑based ToCs in order to create and visualise knowledge to enable the following key SBCE activities: (1) Identify the feasible design space, (2) Generate set of conceptual design solutions, (3) Compare design solutions, (4) Narrow down the design sets, (5) Achieve final optimal design solution. Finally a hypothetical example of a car seat structure is presented in order to provide a better understanding of using ToCs. This example shows that ToCs are effective tools to be used as a knowledge sou rce at the early stages of product development process

Structuring visual exploratory analysis of skill demand

The analysis of increasingly large and diverse data for meaningful interpretation and question answering is handicapped by human cognitive limitations. Consequently, semi-automatic abstraction of complex data within structured information spaces becomes increasingly important, if its knowledge content is to support intuitive, exploratory discovery. Exploration of skill demand is an area where regularly updated, multi-dimensional data may be exploited to assess capability within the workforce to manage the demands of the modern, technology- and data-driven economy. The knowledge derived may be employed by skilled practitioners in defining career pathways, to identify where, when and how to update their skillsets in line with advancing technology and changing work demands. This same knowledge may also be used to identify the combination of skills essential in recruiting for new roles. To address the challenges inherent in exploring the complex, heterogeneous, dynamic data that feeds into such applications, we investigate the use of an ontology to guide structuring of the information space, to allow individuals and institutions to interactively explore and interpret the dynamic skill demand landscape for their specific needs. As a test case we consider the relatively new and highly dynamic field of Data Science, where insightful, exploratory data analysis and knowledge discovery are critical. We employ context-driven and task-centred scenarios to explore our research questions and guide iterative design, development and formative evaluation of our ontology-driven, visual exploratory discovery and analysis approach, to measure where it adds value to users’ analytical activity. Our findings reinforce the potential in our approach, and point us to future paths to build on

Interactive Visual Analysis of Networked Systems: Workflows for Two Industrial Domains

We report on a first study of interactive visual analysis of networked systems. Working with ABB Corporate Research and Ericsson Research, we have created workflows which demonstrate the potential of visualization in the domains of industrial automation and telecommunications. By a workflow in this context, we mean a sequence of visualizations and the actions for generating them. Visualizations can be any images that represent properties of the data sets analyzed, and actions typically either change the selection of data visualized or change the visualization by choice of technique or change of parameters