1. R. Bouziane, L. S. Terrissa, S. Ayad, and J.-F. Brethé, “Towards an architecture for cloud robotic services,” International Journal of Computers and Applications, vol. 44, no. 9, pp. 863–874, 2022.

2. R. Bouziane, L. S. Terrissa, and A. Soheyb, “Semantic web services for ros: A robot as a service approach,” Automated Software Engineering, vol. 29, no. 2, pp. 29–49, 2022.

3. I. REMADNA, L. TERRISSA, Z. ALMASRI, and N. ZERHOUNI, “Rul prediction using a fusion of attention-based convolutional variational autoencoder and ensemble learning classifier,” IEEE Transactions on Reliability, IEEE, 2022.

4. I. Remadna, L. Terrissa, M. Sayah, S. Ayad, and N. Zerhouni, “Boosting rul prediction using a hybrid deep cnn-blstm architecture,” Automatic Control and Computer Sciences, vol. 56, no. 4, pp. 300–310, 2022.

5. S. Zroug, I. Remadna, L. Kahloul, L. Terrissa, and S. Benharzallah, “Towards performance evaluation prediction in wsns using artificial neural network multi-perceptron,” Cluster Computing, 2022.

6. A. Belaala, L. S. Terrissa, N. Zerhouni, and C. Devalland, “Computer-aided diagnosis for spitzoid lesions classification using artificial intelligence techniques,” International Journal of Healthcare Information Systems and Informatics (IJHISI), vol. 16, no. 1, pp. 16–36, 2021.

7. I. remadna, L. S. Terrissa, S. Ayad, and N. Zerhouni, “Rul estimation enhancement using hybrid deep learning methods,” International Journal of Prognostics and Health Management, vol. 12, no. 1, 2021.

8. A. Belaala, Y. Bourezane, L. S. Terrissa, Z. A. Masry, and N. Zerhouni, “Skin cancer and deep learning for dermoscopic images classification: A pilot study,” Journal of Clinical Oncology, vol. 38, no. 15_suppl, e22018, 2020.

9. Z. Bouzidi, L. S. Terrissa, N. Zerhouni, and S. Ayad, “Qos of cloud prognostic system application to aircraft engines fleet,” European Journal of Industrial Engineering, vol. 14, no. 01, pp. 34–57, 2020.

10. S. Meraghni, L. Terrissa, M. Yue, J. Ma, S. Jemei, and N. Zerhouni, “A data-driven digital-twin prognostics method for proton exchange membrane fuel cell remaining useful life prediction,” International Journal of Hydrogen Energy, 2020.

11. S. Ayad and L. S. Terrissa, “A generic architecture for intelligent systems based on iot technology,” Internet of Things Journal, DOI : 10.21494/ISTE.OP.2019.0326, vol. 3, no. 01, 2019.

12. F. Bekkari, S. Terrissa, and I. Hamlaoui, “Taboo techniques to resolve the dominance problem in semantic image retrieval,” 2019.

13. Z. Laiadi, L. Terrissa, Z. Lakhrif, and M. M. Bentchikou, “Simultaneous morphological measurements comparison and automated analysis of two algerian grapevine collections,” REVUE AGRICULTURE, vol. 6, pp. 4–13, 2019.

14. Z. Bouzidi, L. S. Terrissa, N. Zerhouni, and S. Ayad, “An efficient cloud prognostic approach for aircraft engines fleet trending,” International Journal of Computers and Applications, https://doi.org/10.1080/1206212X.2018.1488024, pp. 1–16, 2018.

15. L. S. Terrissa, “Robotics as a service. est-il l avenir de la robotique?” JDN, 2018.

16. S. Ayad, O. Kazar, A.-N. Benharkat, and S.-L. Terrissa, “An optimised semantic web services discovery in manet,” International journal of communication networks and distributed systems, vol. 19, no. 3, pp. 270–287, 2017.

17. L. S. Terrissa, R. Bouziane, and J.-F. Brethé, “Soa-based approach of robot as a service (raas) in the cloud,” 2017.

18. S. Ayad, O. Kazar, N.-A. Benharkat, and L.-S. Terrissa, “Cross-layer routing based on semantic web services discovery with energy evaluation and optimization in manet,” International Journal of Communication Networks and Information Security, vol. 8, no. 1, p. 47, 2016.

19. l. TERRISSA, N. ZERHOUNI, and R. GOURIVEAU, “Neuro-fuzzy model for prognostic as a service in private cloud computing,” networks, vol. 4, no. 7, p. 9, 2016.

20. R. Bouziane, L. S. Terrissa, S. Ayad, and J.-F. Breth, “A ros-based approach for robot as a service (web services based solution),” University of Biskra, 2015.

21. A. Zerroug, L. Terrissa, and A. Faure, “Chaotic dynamical behavior of recurrent neural network,” Annu. Rev. Chaos Theory Bifurc. Dyn. Syst, vol. 4, pp. 55–66, 2013.

22. L. S. Terrissa and A. Zerroug, “Models of growth heterogeneous cancer cells with chains markoviens and estimation of their fractal dimension,” International Journal of Computer Science Issues (IJCSI), vol. 8, no. 5, p. 274, 2011.

S. Attache, L. Terrissa, I. Remadna, S. Ayad, F. Madaci, and N. Zerhouni, “Predicting covid-19 outbreak in algeria using long short-term memory networks,” in ISPA2022: THE 7th International Conference on the Image and Signal Processing and their Applications, 2022.

S. Attache, I. Remadna, L. S. Terrissa, I. Maouche, and N. Zerhouni, “Iot based prediction of active and passive earth pressure coefficients using artificial neural networks,” in International Conference on Networked Systems (LNCS), Springer, Cham, 2022, pp. 252–262.

I. MAOUCHE, L. S. TERRISSA, S. BOUDAIRA, K. BENMOHAMED, and Z. Noureddine., “Identification of factors related to covid-19 mortality in diabetic patients using log binomial regression: Algerian study.,” in The 11th WORKSHOP "AMINA 2022" Monastir, Tunisia, 2022.

Z. Siham, R. Ikram, L. Kahloul, and T. Sadek Labib, “Simulation and formal verification in wsns empowered by machine learning: A review,” in 4th International Conference on Pattern Analysis and Intelligent Systems, 2022.

T. E. C. Ainou, S. Ayad, and L. S. Terrissa, “A survey on sdn based energy-efficiency approaches in iot: systematic survey on energy conservation methods in iot.,” in NISS (ACM), 2021, pp. 8–1.

S. Ayad, A. Telli, and L. S. Terrissa, “Toward agriculture 4.0: Smart farming environment based on robotic and iot,” in The 4 th International Symposium on Advanced Electrical & Communication Technologies, ISAECT 2021, 2021.

S. Ayad, L. S. Terrissa, and A. Telli, “Energy consumption optimization in iot-based smart farming,” in The IEEE International Conference on Recent Advances in Mathematics and Informatics (ICRAMI’2021),, Tebessa, Algeria, 2021.

T. E. ChaibAinou, S. Ayad, and L. S. Terrissa, “A survey on sdn based energy-efficiency approaches in iot,” in The 4th International Conference on Networking, Information Systems & Security (NISS 2021), 2021.

I. Maouche, S. L. Terrissa, K. Benmohammed, N. Zerhouni, and S. Boudaira, “Early prediction of icu admission within covid-19 patients using machine learning techniques,” in The 6th International Conference on Smart City Applications SCA’21, 2021.

S. Zroug, I. Remadna, L. Kahloul, S. Benharzallah, and S. L. Terrissa, “Leveraging the power of machine learning for performance evaluation prediction in wireless sensor networks,” in 2021 International Conference on Information Technology (ICIT), IEEE, 2021, pp. 864–869.

A. Belaala, Z. Al Masry, L. S. Terrissa, and N. Zerhouni, “Retargeting phm tools: From industrial to medical field,” in PHM Society European Conference, vol. 5, 2020, pp. 7–7.

A. Belaala, L. S. Terrissa, N. Zerhouni, and C. Devalland, “Spitzoid lesions diagnosis based on smote-ga and stacking methods,” in AI2SD, Advanced Intelligent Systems and computing, Springer, Cham, 2020.

H. Laouz, S. Ayad, and L. S. Terrissa, “Literature review on driver’s drowsiness and fatigue detection,” in 4th International Conference on Intelligent Systems and Computer Vision (ISCV 2020), 2020.

H. Messabih, S. Ayad, and L. S. Terrissa, “Context aware for internet of things: A survey,” in 2020 International Conference on Intelligent Systems and Computer Vision (ISCV), IEEE, 2020, pp. 1–7.

I. Remadna, L. S. Terrissa, N. Zerhouni, and R. Zemouri, “Unsupervised feature reduction techniques with bidirectional gru neural network for aircraft engine rul estimation,” in AI2SD, Advanced Intelligent Systems and computing, Springer, Cham, 2020.

I. Remadna, S. L. Terrissa, R. Zemouri, S. Ayad, and N. Zerhouni, “Leveraging the power of the combination of cnn and bi-directional lstm networks for aircraft engine rul estimation,” in 2020 Prognostics and Health Management Conference (PHM-Besançon), IEEE, 2020, pp. 116–121.

L. S. TERRISSA, “A new approach of medical-phm,” in The International Pluridisciplinary PhD Meeting (IPPM’20), El Oued - Algeria, 2020.

R. Zemouri, Z. Elmasri, I. Remadna, L. Terrissa, and N. Zerhouni, “Hybrid architecture of deep convolutional variational auto-encoder for remaining useful life prediction,” in Proceedings of the 30th European Safety and Reliability Conference and the 15th Probabilistic Safety Assessment and Management Conference, 2020.

A. BELAALA, C. DEVALLAND, L. S. TERRISSA, S. V. DEGANO, and N. ZERHOUNI, “Aide à la classification des tumeurs de spitz,” in Carrefour Pathologique, Palais des Congrès Paris, 2019.

A. Belaala, L. S. Terrissa, N. Zerhouni, and C. Devalland, “Spitzoid lesions diagnosis based on ga feature selection and random forest,” in AI2SD’2019, Marrakech, Morocco, 2019.

B. Benhaya, S. Ayad, and L. S. Terrissa, “Comparative study on wireless mobile generation technologies: From 1g to 6g,” in The 8th International Conference on Innovation and New Trends in Information Technology, Tangier, Morocco, 2019.

R. Bouziane and L. S. Terrissa, “Ros-based solution for robotics services in cloud computing,” in The 1st workshop on Systems-of-Systems, Cybersecurity, Communication, Software Architecture, and Product Lines, SCAP’19, 2019.

I. Remadna, L. S. Terrissa, N. Zerhouni, S. Ayad, and R. Zemouri, “Remaining useful life estimation using principal component analysis with bidirectional lstm neural network,” in ICCAD’019, Grenoble, France, 2019.

I. Remadna and L. Terrissa, “Deep learning techniques for phm,” in The 1st Workshop on Systems-of-Systems, Cybersecurity, Communication, Software Architecture, and Product Lines, SCAP’19, 2019.

L. S. Terrissa, S. Ayad, and N. Zerhouni, “Robotics based solution for data center e-monitoring,” in 2019 International Conference on Advanced Systems and Emergent Technologies (IC_ASET), IEEE, 2019, pp. 201–208.

S. Ayad, L. S. Terrissa, O. Kazar, and B. Aıcha-Nabila, “A smart greenhouse solution based on iot and cloud computing technologies,” in IEEE - 2018 International Conference on Control, Automation and D iagnosis ( ICCAD’18 ), Mar 2018, Marrakech, Morocco, 2018, p23–35.

S. Ayad, L. S. Terrissa, and N. Zerhouni, “An iot approach for a smart maintenance,” in 2018 International Conference on Advanced Systems and Electric Technologies (IC_ASET), IEEE, 2018, pp. 210–214.

A. Belaala, L. S. Terrissa, N. Zerhouni, and C. Devalland, “Predictive big data analysis in healthcare,” in ARIMA 18, Monastir, Tunisia, 2018.

A. Lahmadi, L. S. Terrissa, and N. Zerhouni, “A data-driven method for estimating the remaining useful life of a composite drill pipe,” in 2018 International Conference on Advanced Systems and Electric Technologies (IC_ASET), IEEE, 2018, pp. 192–195.

S. Meraghni, L. S. Terrissa, S. Ayad, N. Zerhouni, and C. Varnier, “Post-prognostics decision in cyber-physical systems,” in 2018 International Conference on Advanced Systems and Electric Technologies (IC_ASET), IEEE, 2018, pp. 201–205.

I. Remadna, S. L. Terrissa, R. Zemouri, and S. Ayad, “An overview on the deep learning based prognostic,” in 2018 International Conference on Advanced Systems and Electric Technologies (IC_ASET), IEEE, 2018, pp. 196–200.

R. Bouziane, L. S. Terrissa, S. Ayad, J.-F. Brethe, and O. Kazar, “A web services based solution for the nao robot in cloud robotics environment,” in 2017 4th International Conference on Control, Decision and Information Technologies (CoDIT), IEEE, 2017, pp. 0809–0814.

Z. Bouzidi, L. S. Terrissa, A. Lahmadi, N. Zerhouni, and S. Ayad, “The performance measure of a data driven prognostic system: Application to an aircraft engine,” in 2017 4th International Conference on Control, Decision and Information Technologies (CoDIT), IEEE, 2017, pp. 0790–0796.

S. MERAGHNI, L. S. TERRISSA, N. ZERHOUNI, C. VARNIER, and S. AYAD, “An iot-based solution for post-prognostics decision in cloud computing environment,” 2017.

Z. Bouzidi, L. Terrissa, A. Lahmadi, N. Zerhouni, and R. Gouriveau, “Neuro-fuzzy model for prognostic as a service in private cloud computing,” in 2016 2nd International Conference on Cloud Computing Technologies and Applications (CloudTech), IEEE, 2016, pp. 360–367.

Z. Bouzidi, L. Terrissa, N. Zerhouni, and R. Gouriveau, “Neural network model for prognostic as a service in private cloud computing,” in Conférence Francophone de Modélisation, Optimisation et Simulation, 2016.

S. Meraghni, L. S. Terrissa, N. Zerhouni, C. Varnier, and S. Ayad, “A post-prognostics decision framework for cell site using cloud computing and internet of things,” in 2016 2nd International Conference on Cloud Computing Technologies and Applications (CloudTech), IEEE, 2016, pp. 310–315.

L. S. Terrissa, S. Meraghni, Z. Bouzidi, and N. Zerhouni, “A new approach of phm as a service in cloud computing,” in 2016 4th IEEE international colloquium on information science and technology (CiSt), IEEE, 2016, pp. 610–614.

L. S. Terrissa and S. Ayad, “Towards a new cloud robotics approach,” in 2015 10th International Symposium on Mechatronics and its Applications (ISMA), IEEE, 2015, pp. 1–5.

L. S. Terrissa, R. Bey, and J.-F. Brethé, “An overview on cloud robotics,” in 2nd cfrancophone conference on collaborative systems (SysCo 2014), 2014.

I. MAOUCHE, L. S. TERRISSA, S. BOUDAIRA, K. BENMOHAMED, and Z. Noureddine., “Identification of factors related to covid-19 mortality in diabetic patients using log binomial regression: Algerian study.,” in The 11th WORKSHOP "AMINA 2022" Monastir, Tunisia, 2022.

Abir Belaala, Labib Sadek Terrissa, Josepf Tan, Christine Duvallant, Noureddine Zerhouni : Adaptive Health Management Information Systems , Jones & Bartlett Learning , 2019.

John Francis T. Diaz, D. K. R. Babajee, S. K. Khratti, P. P. Murthy, Rashmi, Farid Messelmi, A. Zerroug, L. Terrissa, A. Faure: Annual Review of Chaos Theory, Bifurcations and Dynamical Systems. Volume 4 (http://www.arctbds.com/vomule%204.htm). 01/2013; www.arctbds.com., ISBN: 2253-0371

S. Meraghni, K. Benaggoune, Z. A. Masry, L. S. Terrissa, C. Devalland, and N. Zerhouni, “Towards digital twins driven breast cancer detection,” in Intelligent Computing, Springer, Cham, 2021, pp. 87–99