Rostand Tayong Boumda

Prof. Rostand Tayong Boumda

University of Bedfordshire
orcid
Senior Lecturer at the University of Bedfordshire

Research Focus & Metrics

Academic Career Length

6Years (2021-Present)

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

Representative Publications

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27 January 2021 in Remote Sensing
Verified
Journal Article
Open access
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Ole GrønOle Grøn
Ole Grøn
LBLars O. Boldreel
Lars O. Boldreel
MSMorgan F. Smith
Morgan F. Smith
SJShawn Joy
Shawn Joy
RBRostand Tayong Boumda
Rostand Tayong Boumda
ADAntonio Dell’Anno
Antonio Dell’Anno
Acoustic response from lithics knapped by humans has been demonstrated to facilitate effective detection of submerged Stone Age sites exposed on the seafloor or embedded within its sediments. This phenomenon has recently enabled the non-invasive detection of several hitherto unknown submerged Stone Age sites, as well as the registration of acoustic responses from already known localities. Investigation of the acoustic-response characteristics of knapped lithics, which appear not to be replicated in naturally cracked lithic pieces (geofacts), is presently on-going through laboratory experiments and finite element (FE) modelling of high-resolution 3D-scanned pieces. Experimental work is also being undertaken, employing chirp sub-bottom systems (reflection seismic) on known sites in marine areas and inland water bodies. Fieldwork has already yielded positive results in this initial stage of development of an optimised Human-Altered Lithic Detection (HALD) method for mapping submerged Stone Age sites. This paper reviews the maritime archaeological perspectives of this promising approach, which potentially facilitates new and improved practice, summarizes existing data, and reports on the present state of development. Its focus is not reflection seismics as such, but a useful resonance phenomenon induced by the use of high-resolution reflection seismic systems.

21 May 2025 in Applied Composite Materials
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Journal Article
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MVMihai M. Vasilache
Mihai M. Vasilache
RBRostand Tayong Boumda
Rostand Tayong Boumda
VVVladan Velisavljevic
Vladan Velisavljevic
Carbon fibre reinforced polymers (CFRP) are increasingly being used in different industries, including the automotive and aerospace sectors. One important reason for this is because they have interesting structural and mechanical properties compared to metallic materials. Their high strength-to-weight ratio makes them a preferred choice for high-stress applications. However, CFRPs are often subjected to various defects during their manufacturing that can significantly alter their structural integrity and durability. Amongst these defects, the occurrence of void formation (known as porosity) is the most common. Many methods have been developed for the characterisation of porosity including the ones based on the use of ultrasound data. The present work aims at providing a comprehensive review of the application of machine learning (ML) techniques to the mapping and characterisation of porosity across CFRP composites. The types of ML used, and their potentials for improving the accuracy of porosity detection are presented and discussed. It is particularly noted that ML techniques can extract unique features from CFRP complex ultrasound data with a relatively good level of accuracy. This result suggests that these techniques, particularly the convolutional neural network (CNN), would overcome the limitations of traditional signal processing techniques.

28 April 2023 in Results in Engineering
Verified
Journal Article
Open access
MSMosopefoluwa Samuel
Mosopefoluwa Samuel
RBRostand Tayong Boumda
Rostand Tayong Boumda

2 June 2025 in Results in Engineering
Verified
Journal Article
Open access
MVMihai-Mircea Vasilache
Mihai-Mircea Vasilache
ITIryna Tretiak
Iryna Tretiak
RBRostand Tayong Boumda
Rostand Tayong Boumda
VVVladan Velisavljevic
Vladan Velisavljevic

18 October 2023 in Results in Engineering
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Journal Article
Open access
RBRostand Tayong Boumda
Rostand Tayong Boumda
DHDave Henderson
Dave Henderson
AMAlex Murray
Alex Murray

25 January 2025 in Remote Sensing
Verified
Journal Article
Open access
PDF file
LBLars O. Boldreel
Lars O. Boldreel
Ole GrønOle Grøn
Ole Grøn
RBRostand Tayong Boumda
Rostand Tayong Boumda
BMBo Madsen
Bo Madsen
Ole BennikeOle Bennike
Ole Bennike
MAMorten Sparre Andersen
Morten Sparre Andersen
Teledyne Chirp III high-resolution seismic data were acquired over a three-year period at a water depth of 6.0–9.0 m, with a clear concentration of acoustic “haystack” features, in the dredged Svanemøllen Harbor, Copenhagen. The recordings show haystacks related to preserved shallow basins and rivers in the paleo-coastal setting. Eleven short vibrocores were retrieved below these pronounced haystacks and a sandy interval, underlain by clayey till and overlain by harbor mud, which represent the basin configuration. Two cores contained four pieces of knapped flint in the sandy interval (statistical density of around 230 pieces per square meter), while the remaining cores did not reach the desired depth. Finite Element (FE) modeling revealed that the small pieces of knapped flint were resonant and that the acoustic impedance of the flint was high. The Svanemøllen Harbor site is a hitherto unknown buried Stone Age site, and this is the first time ever that an unknown submerged, buried Stone Age site has been acoustically detected (using Teledyne Chirp III), verified by means of coring and modeled using FE modeling. The Innomar and Geopulse data acquired at the site did not register any haystacks. Due to the global sea level rise after the Last Glacial Maximum, a significant part of the world’s submerged Stone Age sites must be expected to be buried in seafloor sediments.