An ontology framework for developing platform-independent knowledge-based engineering systems in the aerospace industry

This paper presents the development of a novel knowledge-based engineering (KBE) framework for implementing platform-independent knowledge-enabled product design systems within the aerospace industry. The aim of the KBE framework is to strengthen the structure, reuse and portability of knowledge consumed within KBE systems in view of supporting the cost-effective and long-term preservation of knowledge within such systems. The proposed KBE framework uses an ontology-based approach for semantic knowledge management and adopts a model-driven architecture style from the software engineering discipline. Its phases are mainly (1) Capture knowledge required for KBE system; (2) Ontology model construct of KBE system; (3) Platform-independent model (PIM) technology selection and implementation and (4) Integration of PIM KBE knowledge with computer-aided design system. A rigorous methodology is employed which is comprised of five qualitative phases namely, requirement analysis for the KBE framework, identifying software and ontological engineering elements, integration of both elements, proof of concept prototype demonstrator and finally experts validation. A case study investigating four primitive three-dimensional geometry shapes is used to quantify the applicability of the KBE framework in the aerospace industry. Additionally, experts within the aerospace and software engineering sector validated the strengths/benefits and limitations of the KBE framework. The major benefits of the developed approach are in the reduction of man-hours required for developing KBE systems within the aerospace industry and the maintainability and abstraction of the knowledge required for developing KBE systems. This approach strengthens knowledge reuse and eliminates platform-specific approaches to developing KBE systems ensuring the preservation of KBE knowledge for the long term

Evaluating the implicit feedback models for adaptive video retrieval

Interactive video retrieval systems are becoming popular. On the one hand, these systems try to reduce the effect of the semantic gap, an issue currently being addressed by the multimedia retrieval community. On the other hand, such systems enhance the quality of information seeking for the user by supporting query formulation and reformulation. Interactive systems are very popular in the textual retrieval domain. However, they are relatively unexplored in the case of multimedia retrieval. The main problem in the development of interactive retrieval systems is the evaluation cost.The traditional evaluation methodology, as used in the information retrieval domain, is not applicable. An alternative is to use a user-centred evaluation methodology. However, such schemes are expensive in terms of effort, cost and are not scalable. This problem gets exacerbated by the use of implicit indicators, which are useful and increasingly used in predicting user intentions. In this paper, we explore the effectiveness of a number of interfaces and feedback mechanisms and compare their relative performance using a simulated evaluation methodology. The results show the relatively better performance of a search interface with the combination of explicit and implicit features

Is Evaluating Visual Search Interfaces in Digital Libraries Still an Issue?

Although various visual interfaces for digital libraries have been developed in prototypical systems, very few of these visual approaches have been integrated into today's digital libraries. In this position paper we argue that this is most likely due to the fact that the evaluation results of most visual systems lack comparability. There is no fix standard on how to evaluate visual interactive user interfaces. Therefore it is not possible to identify which approach is more suitable for a certain context. We feel that the comparability of evaluation results could be improved by building a common evaluation setup consisting of a reference system, based on a standardized corpus with fixed tasks and a panel for possible participants.Comment: 10 pages, 2 figures, LWA Workshop 201

Development of a simple information pump.

The Information Pump (IP) is a methodology that aims to counter the problems arising from traditional subjective product data collection. The IP is a game theory based process that aims to maximise information extracted from a panel of subjects, while maintaining their interest in the process through a continuous panelist scoring method. The challenge with implementing this arises from the difficulty in executing the 'game'. In its original format, there is an assumption that the game is played with each player using their own PC to interact with the process. While this in theory allows information and scores to flow in a controlled manner between the players, it actually provides a major barrier to the wider adoption of the IP method. This barrier is two-fold: it is costly and complex, and it is not a natural manner for exchanging information. The core objective is to develop a low cost version of the IP method. This will use the game theory approach to maintain interest among participants and maximise information extraction, but remove the need for each participant to have their own PC interface to the game. This will require replacing both the inter-player communication method and the score keeping/reporting

Adaptation of the Electric Machines Learning Process to the European Higher, Education Area

In this paper the basic lines of a complete teaching methodology that has been developed to adaptthe electric machines learning process to the European Higher Education Area (EHEA) arepresented. New teaching materials that are specific to Electric Machines have been created(textbooks, self-learning e-books, guidelines for achieving teamwork research, etc.). Working ingroups has been promoted, as well as problem solving and self-learning exercises, all of which areevaluated in a way that encourages students' participation. Finally, the students' learning process inthe lab has been improved by the development both of a new methodology to follow in the lab andnew workbenches with industrial machines that are easier to use and also enable the labexperiments to be automated. Finally, the first results obtained as a result of applying the proposedmethodology are presented

Linking design and manufacturing domains via web-based and enterprise integration technologies

The manufacturing industry faces many challenges such as reducing time-to-market and cutting costs. In order to meet these increasing demands, effective methods are need to support the early product development stages by bridging the gap of communicating early design ideas and the evaluation of manufacturing performance. This paper introduces methods of linking design and manufacturing domains using disparate technologies. The combined technologies include knowledge management supporting for product lifecycle management (PLM) systems, enterprise resource planning (ERP) systems, aggregate process planning systems, workflow management and data exchange formats. A case study has been used to demonstrate the use of these technologies, illustrated by adding manufacturing knowledge to generate alternative early process plan which are in turn used by an ERP system to obtain and optimise a rough-cut capacity plan

Exploration of applying a theory-based user classification model to inform personalised content-based image retrieval system design

© ACM, 2016. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published at http://dl.acm.org/citation.cfm?id=2903636To better understand users and create more personalised search experiences, a number of user models have been developed, usually based on different theories or empirical data study. After developing the user models, it is important to effectively utilise them in the design, development and evaluation of search systems to improve users’ overall search experiences. However there is a lack of research has been done on the utilisation of the user models especially theory-based models, because of the challenges on the utilization methodologies when applying the model to different search systems. This paper explores and states how to apply an Information Foraging Theory (IFT) based user classification model called ISE to effectively identify user’s search characteristics and create user groups, based on an empirically-driven methodology for content-based image retrieval (CBIR) systems and how the preferences of different user types inform the personalized design of the CBIR systems