Publications

2019
Rafika S. Mise en Evidence de l&⋕39;évènement anoxique océanique 2 (EAO-2) dans la région de Batna (NE, Algérie). 2019.Abstract
RésuméRésumé:La présente étude s’intéresse aux dépôts cénomano-turoniens, observables dans la région de Batna,afin de définir la mise en évidence de l’évènement anoxique océanique 2 (EAO-2). Cette région couvre deux domaines paléogéographiques et structuraux : le préatlasique(Monts de Bellezma-Batna) au NOet l’atlasique (Monts de l’Aurès) au SE. Pour le faire,une analyse sédimentologique, biostratigraphique et géochimique est réalisée sur deux coupes Thénièt El Manchar et Firmet Riche «Dj Bou Arif». Basées sur les ammonites et les foraminifères planctoniques, deux formations ont été définies: (1) la Formation des Marnes de Smail, subdivisée en quatre unités litho-stratigraphiques (IA, IB, IC, ID), datée du Cénomanien et (2) la base de la Formation des Dolomies de l’Oued Skhoun (unité, IIA) datée du Turonien inférieur. L’analyse qualitative et quantitative des foraminifères (planctoniques et/ou benthiques), des ostracodes, l’étude du microfaciès et des marqueurs géochimiques, permet de reconstituer l’évolution du paléo-environnement et les variations paléo-bathymétriques au cours de l’intervalle stratigraphique concerné. Ainsi, les unités IA-IB-IC et la partie inférieure de l’unité ID (Cénomanien) sont dominées par des associations de fora-minifères benthiques agglutinés et des carapaces entières d’ostracodes, témoignant d’un milieu de plate-forme et d’un faible hydrodynamisme. Les calcaires supérieurs de l’unité IC et inférieurs de l’unité ID sont marqués par la présence de rudistes traduisant une reductiondu milieu de sédimentation et une augmentation de l’hydrodynamisme. Dans ces dépôts, les associations montrent une diversité spécifique faible à moyenne et une abondance plus ou moins élevée de foraminifères benthiques, témoignant de conditions trophiques et d’oxygénation considérées comme normales. Les termes sommitaux de l’unité ID (sommet du Cénomanien)et l’unité IIA (base du Turonien) marquent, quant à eux, une évolution vers des conditions plus profondes, comme le montre la succession standard des événements déjà reconnus en Afrique du nord, à savoir : l’abondance de foraminifères planctoniques, la présence de ‘filaments’ et une réduction drastique de la faune d’ostracodes. D’une manière générale, la sédimentation des deux formations dans les deux domaines représente une séquence qui évolue d’un environnement de plate-forme externe distale à celui d’une plate-forme moyenne, avec une phase régressive. Cette séquence s’achève avec le retour aux conditions profondes concomitantes d’une hausse eustatique et dépôt de sédiments pélagiques caractérisant un intervalle transgressif (IT) et s’inscrit dans le cycle eustatique majeur téthysien de troisième ordre. L’évolution séquentielle et paléogéographique des dépôts cénomaniens et turoniens inférieurs de la région de Batna dépendent intimement du contexte structural de la région.En outre, les courbes isotopiques du, carbone (Δ13C) et de l’oxygène (Δ18O) des carbonates mettent en évidence des anomalies isotopiques relatives aux modifications paléo-environnementales. Les données du Δ13C et celles du COT indiquent une productivité primaire faible. Les données duΔ18O, quant à elles, indiquent une augmentation des paléo-températures, cause principale du déclenchement de l’EAO 2. Ces interprétations paléo-environnementales s’accordent avec les données connues du contexte paléogéographique régional et mettent en exergue les spécificités téthysiennes.
Boubiche DE, Imran M, Maqsood A, Shoaib M. Mobile crowd sensing – Taxonomy, applications, challenges, and solutions. Computers in Human BehaviorComputers in Human Behavior. 2019;101 :352-370.Abstract
Recently, mobile crowd sensing (MCS) is captivating growing attention because of their suitability for enormous range of new types of context-aware applications and services. This is attributed to the fact that modern smartphones are equipped with unprecedented sensing, computing, and communication capabilities that allow them to perform more complex tasks besides their inherent calling features. Despite a number of merits, MCS confronts new challenges due to network dynamics, the huge volume of data, sensing task coordination, and the user privacy problems. In this paper, a comprehensive review of MCS is presented. First, we highlight the distinguishing features and potential advantages of MCS compared to conventional sensor networks. Then, a taxonomy of MCS is devised based on sensing scale, level of user involvement and responsiveness, sampling rate, and underlying network infrastructure. Afterward, we categorize and classify prominent applications of MCS in environmental, infrastructure, social, and behavioral domains. The core architecture of MCS is also described. Finally, we describe the potential advantages, determine and reiterate the open research challenges of MCS and illustrate possible solutions.
Boubiche DE, Imran M, Maqsood A, Shoaib M. Mobile crowd sensing – Taxonomy, applications, challenges, and solutions. Computers in Human BehaviorComputers in Human Behavior. 2019;101 :352-370.Abstract
Recently, mobile crowd sensing (MCS) is captivating growing attention because of their suitability for enormous range of new types of context-aware applications and services. This is attributed to the fact that modern smartphones are equipped with unprecedented sensing, computing, and communication capabilities that allow them to perform more complex tasks besides their inherent calling features. Despite a number of merits, MCS confronts new challenges due to network dynamics, the huge volume of data, sensing task coordination, and the user privacy problems. In this paper, a comprehensive review of MCS is presented. First, we highlight the distinguishing features and potential advantages of MCS compared to conventional sensor networks. Then, a taxonomy of MCS is devised based on sensing scale, level of user involvement and responsiveness, sampling rate, and underlying network infrastructure. Afterward, we categorize and classify prominent applications of MCS in environmental, infrastructure, social, and behavioral domains. The core architecture of MCS is also described. Finally, we describe the potential advantages, determine and reiterate the open research challenges of MCS and illustrate possible solutions.
Boubiche DE, Imran M, Maqsood A, Shoaib M. Mobile crowd sensing – Taxonomy, applications, challenges, and solutions. Computers in Human BehaviorComputers in Human Behavior. 2019;101 :352-370.Abstract
Recently, mobile crowd sensing (MCS) is captivating growing attention because of their suitability for enormous range of new types of context-aware applications and services. This is attributed to the fact that modern smartphones are equipped with unprecedented sensing, computing, and communication capabilities that allow them to perform more complex tasks besides their inherent calling features. Despite a number of merits, MCS confronts new challenges due to network dynamics, the huge volume of data, sensing task coordination, and the user privacy problems. In this paper, a comprehensive review of MCS is presented. First, we highlight the distinguishing features and potential advantages of MCS compared to conventional sensor networks. Then, a taxonomy of MCS is devised based on sensing scale, level of user involvement and responsiveness, sampling rate, and underlying network infrastructure. Afterward, we categorize and classify prominent applications of MCS in environmental, infrastructure, social, and behavioral domains. The core architecture of MCS is also described. Finally, we describe the potential advantages, determine and reiterate the open research challenges of MCS and illustrate possible solutions.
Boubiche DE, Imran M, Maqsood A, Shoaib M. Mobile crowd sensing – Taxonomy, applications, challenges, and solutions. Computers in Human BehaviorComputers in Human Behavior. 2019;101 :352-370.Abstract
Recently, mobile crowd sensing (MCS) is captivating growing attention because of their suitability for enormous range of new types of context-aware applications and services. This is attributed to the fact that modern smartphones are equipped with unprecedented sensing, computing, and communication capabilities that allow them to perform more complex tasks besides their inherent calling features. Despite a number of merits, MCS confronts new challenges due to network dynamics, the huge volume of data, sensing task coordination, and the user privacy problems. In this paper, a comprehensive review of MCS is presented. First, we highlight the distinguishing features and potential advantages of MCS compared to conventional sensor networks. Then, a taxonomy of MCS is devised based on sensing scale, level of user involvement and responsiveness, sampling rate, and underlying network infrastructure. Afterward, we categorize and classify prominent applications of MCS in environmental, infrastructure, social, and behavioral domains. The core architecture of MCS is also described. Finally, we describe the potential advantages, determine and reiterate the open research challenges of MCS and illustrate possible solutions.
Boubiche DE, Imran M, Maqsood A, Shoaib M. Mobile crowd sensing–taxonomy, applications, challenges, and solutions. Computers in Human BehaviorComputers in Human Behavior. 2019;101 :352-370.
Boubiche DE, Imran M, Maqsood A, Shoaib M. Mobile crowd sensing–taxonomy, applications, challenges, and solutions. Computers in Human BehaviorComputers in Human Behavior. 2019;101 :352-370.
Boubiche DE, Imran M, Maqsood A, Shoaib M. Mobile crowd sensing–taxonomy, applications, challenges, and solutions. Computers in Human BehaviorComputers in Human Behavior. 2019;101 :352-370.
Boubiche DE, Imran M, Maqsood A, Shoaib M. Mobile crowd sensing–taxonomy, applications, challenges, and solutions. Computers in Human BehaviorComputers in Human Behavior. 2019;101 :352-370.
Nianga J-M, Mejni F, Kanit T, Imad A, Li J. Mode I stress intensity factor and T-stress by exponential matrix method. Theoretical and Applied Fracture MechanicsTheoretical and Applied Fracture Mechanics. 2019;103 :102287.
Nianga J-M, Mejni F, Kanit T, Imad A, Li J. Mode I stress intensity factor and T-stress by exponential matrix method. Theoretical and Applied Fracture MechanicsTheoretical and Applied Fracture Mechanics. 2019;103 :102287.
Nianga J-M, Mejni F, Kanit T, Imad A, Li J. Mode I stress intensity factor and T-stress by exponential matrix method. Theoretical and Applied Fracture MechanicsTheoretical and Applied Fracture Mechanics. 2019;103 :102287.
Nianga J-M, Mejni F, Kanit T, Imad A, Li J. Mode I stress intensity factor and T-stress by exponential matrix method. Theoretical and Applied Fracture MechanicsTheoretical and Applied Fracture Mechanics. 2019;103 :102287.
Nianga J-M, Mejni F, Kanit T, Imad A, Li J. Mode I stress intensity factor and T-stress by exponential matrix method. Theoretical and Applied Fracture MechanicsTheoretical and Applied Fracture Mechanics. 2019;103 :102287.
Slimane W, Benchouia MT, Golea A, Ait-Mohamed-Said I, Drid S, Chrifi-Alaoui L. Modeling and simulation of the DFIG using in the wind energy conversion system for an isolated site. 2019 International Conference on Control, Automation and Diagnosis (ICCAD). 2019 :1-5.
Slimane W, Benchouia MT, Golea A, Ait-Mohamed-Said I, Drid S, Chrifi-Alaoui L. Modeling and simulation of the DFIG using in the wind energy conversion system for an isolated site. 2019 International Conference on Control, Automation and Diagnosis (ICCAD). 2019 :1-5.
Slimane W, Benchouia MT, Golea A, Ait-Mohamed-Said I, Drid S, Chrifi-Alaoui L. Modeling and simulation of the DFIG using in the wind energy conversion system for an isolated site. 2019 International Conference on Control, Automation and Diagnosis (ICCAD). 2019 :1-5.
Slimane W, Benchouia MT, Golea A, Ait-Mohamed-Said I, Drid S, Chrifi-Alaoui L. Modeling and simulation of the DFIG using in the wind energy conversion system for an isolated site. 2019 International Conference on Control, Automation and Diagnosis (ICCAD). 2019 :1-5.
Slimane W, Benchouia MT, Golea A, Ait-Mohamed-Said I, Drid S, Chrifi-Alaoui L. Modeling and simulation of the DFIG using in the wind energy conversion system for an isolated site. 2019 International Conference on Control, Automation and Diagnosis (ICCAD). 2019 :1-5.
Slimane W, Benchouia MT, Golea A, Ait-Mohamed-Said I, Drid S, Chrifi-Alaoui L. Modeling and simulation of the DFIG using in the wind energy conversion system for an isolated site. 2019 International Conference on Control, Automation and Diagnosis (ICCAD). 2019 :1-5.

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