MISC Lab, Modeling and Implementation of Complex Systems laboratory, located at the University of Constantine 2, is a laboratory approved by the decree n°93 of March 25, 2010. It is a laboratory of the New Information and Communication Technologies faculty at the University of Constantine 2. Its teams work on the design of complex systems, formal methods for software engineering, computing grids and artificial life, and finally on spatial ontologies and geographic information systems.
The research axes of the laboratory cover a wide range of scientific topics of interest for scientific research and practical research for the socio-economic sector.
MISC Lab. invites you to its next scientific symposium that will be held at the University of Constantine 2 on December 10-12, 2022. This call for papers aims to open up the scientific discussion around themes that pose scientific problems and real tracks of technology transfer to the service of the socio-economic sector and society.
The objective is to gather researchers and young researchers to present their work and to confront their theoretical and practical ideas in their respective fields of expertise. Orientations and discussions will emerge from this confrontation around the following themes:
⦿ Context-sensitive ambient systems
⦿ Internet of Things architectures for smart environments
⦿ Communication and cooperation protocols in IoT systems
⦿ Fog and edge computing
⦿ Methods for the design and verification of complex systems
⦿ Learning and machine learning
⦿ Optimization and complex problem solving
⦿ Computer vision and augmented reality
⦿ Parallelism processing and distributed systems
⦿ AI applications and tools
⦿ Data mining and extraction
⦿ Data repositories and Big data
⦿ Image processing and synthesis
⦿ Complex problem-solving in GIS
⦿ Spatial knowledge bases and advanced information systems
⦿ Validation of complex systems
by Pr Abdelouahab Moussaoui
Deep learning is a machine learning technique that has dramatically improved results in many areas such as computer vision, speech recognition, machine translation, etc. Deep learning techniques make it possible, using data, to solve many problems in many areas of the economy such as health, transport, trade, finance and energy. It is a technology which imposes itself as a powerful AI approach that uses multi-layered artificial neural networks to deliver state-of-the-art accuracy in tasks such as object detection, speech recognition, and language translation. Using deep learning, computers can learn and recognize patterns from data that are considered too complex or subtle for expert-written software.
In this tutorial, you’ll learn how deep learning works through hands-on exercises in computer vision and natural language processing. You’ll train deep learning models from scratch, learning tools and tricks to achieve highly accurate results. You’ll also learn to leverage freely available, state-of-the-art pre-trained models to save time and get your deep learning application up and running quickly.
By participating in this tutorial, you’ll:
⦿ Pr Djamel Eddine Saidouni
⦿ Pr Mohammed Gharzouli
⦿ Dr Raida El-Mansouri
⦿ Hichem Talbi, University of Constantine 2, Algeria
⦿ Mohamed Chaouki Babahenini, University of Biskra, Algeria
⦿ Nabil Belala, University of Constantine 2, Algeria
⦿ Azeddine Bilami, University of Batna 2, Algeria
⦿ Abdelkrim Bouramoul, University of Constantine 2, Algeria
⦿ Mourad Bouzenada, University of Constantine 2, Algeria
⦿ Said Labed, University of Constantine 2, Algeria
⦿ Ahmed-Chawki Chaouche, University of Constantine 2, Algeria
⦿ Smaine Mazouzi, University of Skikda, Algeria
⦿ Sihem Mostefai, University of Constantine 2, Algeria
⦿ Abdelouahab Moussaoui, University of Sétif 1, Algeria
⦿ Badreddine Miles, University of Constantine 1, Algeria
⦿ Mohamed Skander Daas, University of Constantine 1, Algeria
⦿ Imene Bensalem, Ecole Supérieure de Comptabilité et de Finances, Constantine, Algeria
⦿ Akram Kout, University of Sétif 1, Algeria.
⦿ Dr Radouan Nouara
⦿ Mohamed El-Kamel Hamdane
⦿ Oussama Kamel
⦿ November 27, 2022: Deadline for submission of papers
⦿ December 03, 2022: Notification for authors
⦿ December 06, 2022: Camera ready
⦿ December 10-12, 2022: DMIS 2022 symposium
Papers should be in English and consist of no more than 15 pages in LNCS format (LaTeX Template or MS Word Template).
Submission should be made by email to email@example.com, mentioning as a subject of the email: DMIS2022_LASTNAME_FIRSTNAME.
Pr Mohamed GHERZOULI