M-Tahar Kechadi

Prof. Dr. M-Tahar Kechadi

Insight Centre for Data Analytics, University College Dublin, Belfield, Dublin04, Ireland
orcid

Research Focus & Metrics

Academic Career Length

35Years (1992-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 January 2012 in Expert Systems with Applications
Verified
Journal Article
Closed access
BHBingquan Huang
Bingquan Huang
M-Tahar KechadiM-Tahar Kechadi
M-Tahar Kechadi
BBBrian Buckley
Brian Buckley

26 April 2013 in The European Physical Journal C
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Journal Article
Open access
PDF file
TCThe LHCb Collaboration
The LHCb Collaboration
ABA. Bharucha
A. Bharucha
IBI. I. Bigi
I. I. Bigi
CBC. Bobeth
C. Bobeth
MBM. Bobrowski
M. Bobrowski
AZA. Zwart
A. Zwart
During 2011 the LHCb experiment at CERN collected 1.0 fb−1 of [equation] ppcollisions. Due to the large heavy quark production cross-sections, these data provide unprecedented samples of heavy...

1 January 2011
Verified
Book Chapter
Open access
PDF file
KRKeyun Ruan
Keyun Ruan
JCJoe Carthy
Joe Carthy
M-Tahar KechadiM-Tahar Kechadi
M-Tahar Kechadi
MCMark Crosbie
Mark Crosbie
Cloud computing may well become one of the most transformative technologies in the history of computing. Cloud service providers and customers have yet to establish adequate forensic capabilities that could support investigations of criminal activities in the cloud. This paper discusses the emerging area of cloud forensics, and highlights its challenges and opportunities.

1 June 2013 in Digital Investigation
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Journal Article
Closed access
KRKeyun Ruan
Keyun Ruan
JCJoe Carthy
Joe Carthy
M-Tahar KechadiM-Tahar Kechadi
M-Tahar Kechadi
IBIbrahim Baggili
Ibrahim Baggili

1 June 2007 in Journal of Visual Languages & Computing
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Journal Article
Closed access
PCP. Compieta
P. Compieta
Sergio Di MartinoSergio Di Martino
Sergio Di Martino
MBMichela Bertolotto
Michela Bertolotto
FFF. Ferrucci
F. Ferrucci
M-Tahar KechadiM-Tahar Kechadi
M-Tahar Kechadi

23 December 2022 in Journal of Big Data
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Journal Article
Open access
PDF file
NCNabila Chergui
Nabila Chergui
M-Tahar KechadiM-Tahar Kechadi
M-Tahar Kechadi
Recent advances in Information and Communication Technologies have a significant impact on all sectors of the economy worldwide. Digital Agriculture appeared as a consequence of the democratisation of digital devices and advances in artificial intelligence and data science. Digital agriculture created new processes for making farming more productive and efficient while respecting the environment. Recent and sophisticated digital devices and data science allowed the collection and analysis of vast amounts of agricultural datasets to help farmers, agronomists, and professionals understand better farming tasks and make better decisions. In this paper, we present a systematic review of the application of data mining techniques to digital agriculture. We introduce the crop yield management process and its components while limiting this study to crop yield and monitoring. After identifying the main categories of data mining techniques for crop yield monitoring, we discuss a panoply of existing works on the use of data analytics. This is followed by a general analysis and discussion on the impact of big data on agriculture.