DC3K 2013 Abstracts

Short Papers

Paper Nr:	5
Title:	Bridging the Semantic Gap between Sensor Data and High Level Knowledge
Authors:	Marjan Alirezaie and Amy Loutfi
Abstract:	The advance of modeling knowledge in different domains along with the promotion in sensor technology that causes the emergence of data streams are addressing a new problem, namely the semantic gap. The objective of this research is bridging the semantic gap between qualitative knowledge and quantitative raw data, specifically electronic nose data coming from chemical sensors that sniff the gas (odour) in the environment. More precisely, the gap bridging in this research is defined as the process of data stream annotation with high level concepts. We introduce three frameworks implemented or under studies for the task of sensor data annotation for which the effectiveness in the sense of the time complexity and the expressiveness of final explanations are examined. The paper outlines the main contributions of the work, details the progress so far after two year of the thesis work, and provides an outline of planned activities.
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Paper Nr:	3
Title:	Development and Implementation of a Methodological Approach to Support MDO by Means of Knowledge based Technologies
Authors:	M. F. M. Hoogreef and G. La Rocca
Abstract:	Multidisciplinary Design Optimization (MDO) can provide designers with the methods to further improve the performance of already mature solutions, and to support the exploration of innovative complex engineering products. The best design of a complex system can only be found when the interactions between the system’s disciplines are fully considered. MDO provides the structured approach and the mathematical formulations to capture such interactions. Although the very first MDO implementations have been presented about 50 years ago, at date, such a discipline is not yet fully exploited at industrial level, apart from limited application. This seems a missed chance to improve product quality and cut design cycle time and cost. The main purpose of this PhD research is the development of an methodological approach, with knowledge based technologies to support MDO, by formalizing knowledge and making MDO more accessible.
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Paper Nr:	4
Title:	BIOscrabble - Extraction of Biological Analogies out of Large Text Sources
Authors:	Maria Katharina Kaiser, Helena Hashemi Farzaneh and Udo Lindemann
Abstract:	How to identify a promising biological solution for developing an innovative technical product? To answer this question, approaches have been developed that support engineers in scanning biological texts for relevant biological analogies. However, existing approaches underutilize biological research articles as a text source, because the enormous amount of biological information contained in these articles is difficult to manage. Nevertheless, this search source is very comprehensive and represents the current state of biological research. Hence, it is worth further consideration. In this research, a search support for bio-inspired design called BIOscrabble is illustrated. It addresses the issue of extracting promising biological analogies out of huge biological text sources. Besides supporting the selection of useful search terms, it proposes different graph-based representations of the search to divide the biological information that is obtained in manageable "packages".
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Paper Nr:	7
Title:	Know-Cap: A Method for Knowledge Capitalization in Software Engineering
Authors:	Gislaine Camila Lapasini Leal, Paulo Cezar Stadzisz and Elisa Huzita
Abstract:	This paper presents a method for knowledge capitalization in Software Engineering. We describe the goals, state of the art, methodology and expected results. It also presents an initial version of the proposed method, named as Know-Cap.
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Paper Nr:	8
Title:	Acquiring Diagnostic Assembly Knowledge from Documents - For the Domain of Assembly of Aircraft Structures
Authors:	Madhusudanan N., Gurumoorthy B. and Amaresh Chakrabarti
Abstract:	The research being proposed in this paper is knowledge acquisition from documents for diagnosis of potential issues. The application domain is that of manual assembly of aircraft structures. The research challenge is to understand and acquire the necessary knowledge from natural language texts. The first step is the segregation of relevant portions of text from documents, possibly using ontologies. The next task is to acquire necessary pieces of knowledge and translate them into a knowledge based system. The final step is to validate the acquired knowledge on example assemblies.
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