Knowledge engineering for modelling reasoning in a diagnosis task: application to search and rescue

Schvartz, Stéphane; Abi‐Zeid, Irène; Tourigny, Nicole

doi:10.1002/cjas.24

Cited by 4 publications

(3 citation statements)

References 6 publications

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“…By following this modeling approach, we were reproducing, albeit in a structured manner, the reasoning followed by the coordinator who tries to get a mental picture of what the pilot saw during his flight, and to guess what might have been his reactions. A full description of the knowledge model can be found in [12] and in [11].…”

Section: Figure 7: the Reasoning Modelmentioning

confidence: 99%

Towards a knowledge-based system prototype for aeronautical Search and Rescue operations

Abi‐Zeid

Nilo

Schvartz

et al. 2010

2010 13th International Conference on Information Fusion

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The long-term objective of our project is to develop a knowledge-based tool for Search and Rescue (SAR) operations to support a Canadian search mission coordinator in determining the likely location of a missing aircraft overland. In order to attain this objective, we used a knowledge engineering approach to acquire, structure and model SAR experts' knowledge. This knowledge was modeled and implemented in a knowledge-based system prototype. The input to the interactive prototype consists of the known information regarding a given SAR case. Its main output is a set of scenarios describing the various hypotheses on what might have happened to the missing aircraft, why and where, the plausible routes followed, as well as the possibility area, defined as the region most likely to contain the missing aircraft. In this paper, we introduce the knowledge model, present an application example and briefly describe the prototype.

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Section: Figure 7: the Reasoning Modelmentioning

confidence: 99%

Towards a knowledge-based system prototype for aeronautical Search and Rescue operations

Abi‐Zeid

Nilo

Schvartz

et al. 2010

2010 13th International Conference on Information Fusion

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“…Among the several ways to initialize this location probability distribution [1], one of them consists in defining a Gaussian function centered on the last known point (LKP). Some methods have been proposed to generate complex probability of containment distributions, which use several scenarii to define possibility areas [19]. The conditional probability of detecting (P OD) the search object provided that it is in a given cell c (P OD (c)) depends on several parameters such as the environment, the amount of search effort, the kind of search object and the type of sensors.…”

Section: Classical Approach Of Search Problemmentioning

confidence: 99%

Belief functions induced by multimodal probability density functions, an application to the search and rescue problem

et al. 2010

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In this paper, we propose a new method to generate a continuous belief functions from a multimodal probability distribution function defined over a continuous domain. We generalize Smets' approach in the sense that focal elements of the resulting continuous belief function can be disjoint sets of the extended real space of dimension n. We then derive the continuous belief function from multimodal probability density functions using the least commitment principle. We illustrate the approach on two examples of probability density functions (unimodal and multimodal). On a case study of Search And Rescue (SAR), we extend the traditional probabilistic framework of search theory to continuous belief functions theory. We propose a new optimization criterion to allocate the search effort as well as a new rule to update the information about the lost object location in this latter framework. We finally compare the allocation of the search effort using this alternative uncertainty representation to the traditional probabilistic representation.

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“…The academic literature describes knowledge creation as a combination and exchange of knowledge inputs through interactions with others (McFadyen & Cannella, 2004;Tsai, Hsu & Fang, 2012). The organization is usually treated as the unit of analysis when investigating the importance of knowledge acquisition and integration within and between firms (Ditillo, 2004;Schvartz, Abi-Zeid & Tourigny, 2003;Sullivan & Marvel, 2011). The actual process of creating new knowledge, however, has received much less attention.…”

Section: Introductionmentioning

confidence: 99%

Impact of Network Position and Knowledge Diversity on Knowledge Creation: The Empirical Setting of Research Communities

Chen

Liu

2012

Can J Adm Sci

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We examined the role of network position and knowledge diversity as related to new knowledge creation within a network of 239 academics from business administration departments at four universities. Analyses of their 1,827 publications involving 1,541 coauthors between 1986 and 2008 revealed an inverse U-shaped relationship between network centrality and knowledge creation. Moreover, knowledge diversity positively moderated the association between centrality and the quality of the knowledge created, but negatively moderated the centrality-knowledge quantity relationship. RésuméCet article examine le rôle de la position du réseau et de la diversité des connaissances dans la création des nouvelles connaissances à l'intérieur d'un réseau de 239 universitaires issus des départements d'administration des affaires de quatre universités. Les analyses des 1827 publications dont 1541 cosignés entre 1986 et 2008 révèlent une relation en forme de U inverse entre la centralité du réseau et la création du savoir. Bien plus, la diversité du savoir modère positivement l'association entre la centralité et la qualité du savoir créé, mais modère négativement la relation centralité-quantité du savoir.

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Knowledge engineering for modelling reasoning in a diagnosis task: application to search and rescue

Abstract: This paper pertains to the application of knowledge engineering methods to aeronautical search and rescue in

Cited by 4 publications

References 6 publications

Towards a knowledge-based system prototype for aeronautical Search and Rescue operations

Towards a knowledge-based system prototype for aeronautical Search and Rescue operations

Belief functions induced by multimodal probability density functions, an application to the search and rescue problem

Impact of Network Position and Knowledge Diversity on Knowledge Creation: The Empirical Setting of Research Communities

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