2019
Imen C, Fouad DJAIZ, Mabrouk B.
Reconsideration of the Cenomanian-Turonian stratigraphics units in the Tebessa region (Algero-TunisienConfines): Petroleum implications. The 1st National Seminar in Geosciences and Environment (SGSE 2019) [Internet]. 2019.
Publisher's VersionAbstract
The Algero-Tunisian confines (Tebessa region) is partially composed of Cenomano- Turonian carbonate outcrops; therefore, it presents a good example to highlight the black shale levels reported over a short period, around the Cenomanian-Turonian boundary. The lithostratigraphic study made it possible to specify the paleoenvironment during the Cenomano-Turonian in the Tebessa region. At that time, the depositional environment emphasized a relatively deep, calm and often confined ocean environment that was significantly shalloweron the north part of the study area. The lithology and the distribution of the facies in the Constantine domain allow us to underline the pelagic influences during the Upper Cretaceous and neritic during the lower Cretaceous period. We note a maximum thickness of the Cenomano- Turonian in the southern zones and a minimum (100m) appears further north. This Palaeogeographic organization continue laterally in Tunisia on the extension of the Constantine mole.
Imen C, Fouad DJAIZ, Mabrouk B.
Reconsideration of the Cenomanian-Turonian stratigraphics units in the Tebessa region (Algero-TunisienConfines): Petroleum implications. The 1st National Seminar in Geosciences and Environment (SGSE 2019) [Internet]. 2019.
Publisher's VersionAbstract
The Algero-Tunisian confines (Tebessa region) is partially composed of Cenomano- Turonian carbonate outcrops; therefore, it presents a good example to highlight the black shale levels reported over a short period, around the Cenomanian-Turonian boundary. The lithostratigraphic study made it possible to specify the paleoenvironment during the Cenomano-Turonian in the Tebessa region. At that time, the depositional environment emphasized a relatively deep, calm and often confined ocean environment that was significantly shalloweron the north part of the study area. The lithology and the distribution of the facies in the Constantine domain allow us to underline the pelagic influences during the Upper Cretaceous and neritic during the lower Cretaceous period. We note a maximum thickness of the Cenomano- Turonian in the southern zones and a minimum (100m) appears further north. This Palaeogeographic organization continue laterally in Tunisia on the extension of the Constantine mole.
Imen C, Fouad DJAIZ, Mabrouk B.
Reconsideration of the Cenomanian-Turonian stratigraphics units in the Tebessa region (Algero-TunisienConfines): Petroleum implications. The 1st National Seminar in Geosciences and Environment (SGSE 2019) [Internet]. 2019.
Publisher's VersionAbstract
The Algero-Tunisian confines (Tebessa region) is partially composed of Cenomano- Turonian carbonate outcrops; therefore, it presents a good example to highlight the black shale levels reported over a short period, around the Cenomanian-Turonian boundary. The lithostratigraphic study made it possible to specify the paleoenvironment during the Cenomano-Turonian in the Tebessa region. At that time, the depositional environment emphasized a relatively deep, calm and often confined ocean environment that was significantly shalloweron the north part of the study area. The lithology and the distribution of the facies in the Constantine domain allow us to underline the pelagic influences during the Upper Cretaceous and neritic during the lower Cretaceous period. We note a maximum thickness of the Cenomano- Turonian in the southern zones and a minimum (100m) appears further north. This Palaeogeographic organization continue laterally in Tunisia on the extension of the Constantine mole.
Benbouza N, Benfarhi L, Azoui B.
Reduction of the Low Voltage Substation Constraints by Inserting Photovoltaic Systems in Underserved Areas. Recent Advances in Electrical & Electronic Engineering, DOI : 10.2174/2352096511666180523095219Recent Advances in Electrical & Electronic Engineering, DOI : 10.2174/2352096511666180523095219. 2019;12 :102-107.
Naima B, Louiza B, Boubekeur A.
Reduction of the Low Voltage Substation Constraints by Inserting Photovoltaic Systems in Underserved Areas. Recent Advances in Electrical & Electronic Engineering (Formerly Recent Patents on Electrical & Electronic Engineering)Recent Advances in Electrical & Electronic Engineering (Formerly Recent Patents on Electrical & Electronic Engineering). 2019;12 :105-112.
Benbouza N, Benfarhi L, Azoui B.
Reduction of the Low Voltage Substation Constraints by Inserting Photovoltaic Systems in Underserved Areas. Recent Advances in Electrical & Electronic Engineering, DOI : 10.2174/2352096511666180523095219Recent Advances in Electrical & Electronic Engineering, DOI : 10.2174/2352096511666180523095219. 2019;12 :102-107.
Naima B, Louiza B, Boubekeur A.
Reduction of the Low Voltage Substation Constraints by Inserting Photovoltaic Systems in Underserved Areas. Recent Advances in Electrical & Electronic Engineering (Formerly Recent Patents on Electrical & Electronic Engineering)Recent Advances in Electrical & Electronic Engineering (Formerly Recent Patents on Electrical & Electronic Engineering). 2019;12 :105-112.
Benbouza N, Benfarhi L, Azoui B.
Reduction of the Low Voltage Substation Constraints by Inserting Photovoltaic Systems in Underserved Areas. Recent Advances in Electrical & Electronic Engineering, DOI : 10.2174/2352096511666180523095219Recent Advances in Electrical & Electronic Engineering, DOI : 10.2174/2352096511666180523095219. 2019;12 :102-107.
Naima B, Louiza B, Boubekeur A.
Reduction of the Low Voltage Substation Constraints by Inserting Photovoltaic Systems in Underserved Areas. Recent Advances in Electrical & Electronic Engineering (Formerly Recent Patents on Electrical & Electronic Engineering)Recent Advances in Electrical & Electronic Engineering (Formerly Recent Patents on Electrical & Electronic Engineering). 2019;12 :105-112.
Hafdaoui H, Benatia D.
Regrouping of acoustics microwaves in piezoelectric material (ZnO) by SVM classifier. International Journal of Digital Signals and Smart SystemsInternational Journal of Digital Signals and Smart Systems. 2019;3 :110-120.
Hichem H, Djamel B.
Regrouping of acoustics microwaves in piezoelectric material (ZnO) by SVM classifier, ISSN / e-ISSN 2398-0311 / 2398-032X. International Journal of Digital Signals and Smart SystemsInternational Journal of Digital Signals and Smart Systems. 2019;Volume 3 :pp 110 - 120.
AbstractIn this paper, we propose a new numerical method for acoustics microwaves detection of an acoustics microwaves signal during the propagation of acoustics microwaves in a piezoelectric substrate zinc oxide (ZnO). We have used support vector machines (SVMs), the originality of this method is the accurate values that provides this technique help to identify undetectable waves that we can not identify with the classical methods. We classify all the values of the real part and the imaginary part of the coefficient attenuation with the acoustic velocity in order to build a model from which we note the types of microwaves acoustics (bulk waves or surface waves or leaky waves). We obtain accurate values for each of the coefficient attenuation and acoustic velocity. This study will be very interesting in modelling and realisation of acoustics microwaves devices (ultrasound, radiating structures, filter SAW…) based on the propagation of acoustics microwaves.
Hichem H, Djamel B.
Regrouping of acoustics microwaves in piezoelectric material (ZnO) by SVM classifier, ISSN / e-ISSN 2398-0311 / 2398-032X. International Journal of Digital Signals and Smart SystemsInternational Journal of Digital Signals and Smart Systems. 2019;Volume 3 :pp 110 - 120.
AbstractIn this paper, we propose a new numerical method for acoustics microwaves detection of an acoustics microwaves signal during the propagation of acoustics microwaves in a piezoelectric substrate zinc oxide (ZnO). We have used support vector machines (SVMs), the originality of this method is the accurate values that provides this technique help to identify undetectable waves that we can not identify with the classical methods. We classify all the values of the real part and the imaginary part of the coefficient attenuation with the acoustic velocity in order to build a model from which we note the types of microwaves acoustics (bulk waves or surface waves or leaky waves). We obtain accurate values for each of the coefficient attenuation and acoustic velocity. This study will be very interesting in modelling and realisation of acoustics microwaves devices (ultrasound, radiating structures, filter SAW…) based on the propagation of acoustics microwaves.
Hafdaoui H, Benatia D.
Regrouping of acoustics microwaves in piezoelectric material (ZnO) by SVM classifier. International Journal of Digital Signals and Smart SystemsInternational Journal of Digital Signals and Smart Systems. 2019;3 :110-120.
Hamza Z, Hacene S.
Reliability and safety analysis using fault tree and Bayesian networks. International Journal of Computer Aided Engineering and TechnologyInternational Journal of Computer Aided Engineering and Technology. 2019;11 :73-86.
Hamza Z, Hacene S.
Reliability and safety analysis using fault tree and Bayesian networks. International Journal of Computer Aided Engineering and TechnologyInternational Journal of Computer Aided Engineering and Technology. 2019;11 :73-86.
Ari AAA, Gueroui A, Titouna C, Thiare O, Aliouat Z.
Resource allocation scheme for 5G C-RAN: A Swarm Intelligence based approach. Computer NetworksComputer Networks. 2019;165 :106957.
Ari AAA, Gueroui A, Titouna C, Thiare O, Aliouat Z.
Resource allocation scheme for 5G C-RAN: A Swarm Intelligence based approach. Computer NetworksComputer Networks. 2019;165 :106957.
Ari AAA, Gueroui A, Titouna C, Thiare O, Aliouat Z.
Resource allocation scheme for 5G C-RAN: A Swarm Intelligence based approach. Computer NetworksComputer Networks. 2019;165 :106957.
Ari AAA, Gueroui A, Titouna C, Thiare O, Aliouat Z.
Resource allocation scheme for 5G C-RAN: A Swarm Intelligence based approach. Computer NetworksComputer Networks. 2019;165 :106957.
Ari AAA, Gueroui A, Titouna C, Thiare O, Aliouat Z.
Resource allocation scheme for 5G C-RAN: A Swarm Intelligence based approach. Computer NetworksComputer Networks. 2019;165 :106957.