Applying semantic web technologies to knowledge sharing in aerospace engineering

This paper details an integrated methodology to optimise Knowledge reuse and sharing, illustrated with a use case in the aeronautics domain. It uses Ontologies as a central modelling strategy for the Capture of Knowledge from legacy docu-ments via automated means, or directly in systems interfacing with Knowledge workers, via user-defined, web-based forms. The domain ontologies used for Knowledge Capture also guide the retrieval of the Knowledge extracted from the data using a Semantic Search System that provides support for multiple modalities during search. This approach has been applied and evaluated successfully within the aerospace domain, and is currently being extended for use in other domains on an increasingly large scale

Reconfigurable Manufacturing Potential in Small and Medium Enterprises with Low Volume and High Variety:Pre-design Evaluation of RMS

AbstractGlobal competition forces companies to respond to fast changing market conditions by introducing new and innovative products rapidly and more often at competitive prices. Meeting these challenges sets strict requirements in order to cope with the variety of products during both ramp-up and production. The Reconfigurable Manufacturing System meets these challenges of high variety by adapting to the capacity and functionality needed when needed. Thus, implementing reconfigurable manufacturing affects the performance during both ramp-up and production. Still, the evaluation of the reconfigurable manufacturing potential has only received limited attention even though it is highly related to justifying its investment. One practical case based example of investigating the potential in reconfigurable manufacturing has though been carried out in high volume manufacturing. However, quantifying and investigating the potential in reconfigurable manufacturing for low volume manufacturing has to our knowledge not been carried out. Thus, the purpose of this paper is to measure the potential of reconfigurable manufacturing in low volume industry, carried out by use of a case-study in Danish industry. Thus, this paper presents an approach for decision support that can be applied by low volume manufacturing companies

Computational Dynamic Features Extraction from Anonymized Medical Images

Images depict clearer meaning than written words and this is reason they are used in a variety of human endeavors, including but not limited to medicine. Medical image datasets are used in medical environment to diagnose and confirm medical disorders for which physical examination may not be sufficient. However, the medical profession's ethics of patient confidentiality policy creates barrier to availability of medical datasets for research; thus, this research work was able to solve the above stated barrier through anonymization of sensitive identity information. Furthermore, the Content Based Image Retrieval (CBIR) using texture as the content was developed to overcome the challenge of information overloading associated with data retrieval systems. Images acquired from various imaging modalities and placed into Digital Imaging and Communications in Medicine (DICOM) formats were obtained from several hospitals in Nigeria. The database of these images was created and consequently anonymized, then a new anonymized database was created. On anonymized images, feature extraction was done using textures as content and the content was considered for the implementation of retrieval system. The anonymized images were tested in DICOM view to see if all files were successfully anonymized; the result obtained was 100%. A texture retrieval test was performed, and the number of precisely returned search images using the Similarity Distance Measure formulae resulted in a significant reduction in image overload. Thus, this research work solved the problem of non-availability of datasets for researchers in medical imaging field by providing datasets that can be used without violating law of patient confidentiality by the interested parties. It also solves the problem of hackers obtaining useful information about patients’ datasets. The CBIR using texture as content also enhances and solves the problem of information overloading