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An Approach Toward a Prediction of the Presence of Asbestos in Buildings Based on Incomplete Temporal Descriptions of Marketed Products

Authors:

Thamer Mecharnia,

Lydia Chibout Khelifa,

Nathalie Pernelle, and

Fayçal HamdiAuthors Info & Claims

K-CAP '19: Proceedings of the 10th International Conference on Knowledge Capture

September 2019

Pages 239 - 242

https://doi.org/10.1145/3360901.3364428

Published: 23 September 2019 Publication History

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Abstract

Since 1997, the production, import and sale of asbestos\footnoteNaturally occurring mineral fibres which were used due to their insulating properties. have been banned in France. However, there are still millions of tons scattered in factories, buildings, or hospitals. In this paper we propose a method for predicting the presence of asbestos products in buildings based on temporal data that describes the probability of the presence of asbestos in marketed products.

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Cited By

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Wu PMjörnell KMangold MSandels CJohansson T(2021)A Data-Driven Approach to Assess the Risk of Encountering Hazardous Materials in the Building Stock Based on Environmental InventoriesSustainability10.3390/su1314783613:14(7836)Online publication date: 13-Jul-2021
https://doi.org/10.3390/su13147836

Index Terms

An Approach Toward a Prediction of the Presence of Asbestos in Buildings Based on Incomplete Temporal Descriptions of Marketed Products
1. Information systems

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Information

Published In

K-CAP '19: Proceedings of the 10th International Conference on Knowledge Capture

September 2019

281 pages

ISBN:9781450370080

DOI:10.1145/3360901

General Chairs:
Mayank Kejriwal
University of Southern California Information Sciences Institute, USA
,
Pedro Szekely
University of Southern California Information Sciences Institute, USA
,
Program Chair:
Raphaël Troncy
EURECOM, France

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 23 September 2019

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K-CAP '19

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SIGAI

K-CAP '19: Knowledge Capture Conference

November 19 - 21, 2019

CA, Marina Del Rey, USA

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Overall Acceptance Rate 55 of 198 submissions, 28%

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Wu PMjörnell KMangold MSandels CJohansson T(2021)A Data-Driven Approach to Assess the Risk of Encountering Hazardous Materials in the Building Stock Based on Environmental InventoriesSustainability10.3390/su1314783613:14(7836)Online publication date: 13-Jul-2021
https://doi.org/10.3390/su13147836

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Mining Contextual Rules to Predict Asbestos in Buildings

Policy management and decentralized debugging in the asbestos operating system