University of Paris 13, France
Prof. Ben-Othman received his B.Sc. and M.Sc. degrees both in Computer Science from the University of Pierre et Marie Curie, (Paris 6) France in 1992, and 1994 respectively. He received his PhD degree from the University of Versailles, France, in 1998. He was an Assistant Professor at the University of Orsay (Paris 11) and University of Pierre et Marie Curie (Paris 6), in 1998 and 1999 respectively. He was an Associate Professor at the University of Versailles from 2000 to 2011. He is currently full professor at the University of Paris 13 since 2011. Dr. Ben-Othman's research interests are in the area of wireless ad hoc and sensor networks, VANETs, IoT, performance evaluation and security in wireless networks in general. He was the recipient of several best papers award (IWCMC'16, EUSPN'14, ICC'11 AHSM, ICCIT'11), the recipient of the IEEE comsoc Communication Software technical committee Recognition Award in 2016, the IEEE computer society Meritorious Service Award in 2016, and he is a Golden Core Member of IEEE Computer Society. He is currently in steering committee of IEEE Transaction on Mobile computing (IEEE TMC), an editorial board member of IEEE communications letters (IEEE COMML), IEEE comsoc Journal of Communications and Networks (JCN) and International Journal On Advances in Networks and Services IJANS. He is also an Associate Editor of Wiley International Journal of Communication Systems (wiley IJCS). He has served as general chair of the international conference on wireless networks and mobile communications (WINCOM'15), program chair of IEEE New technologies mobility and security (NTMS'15). He has also served as TPC Co-Chair for IEEE Globecom and ICC conferences for Ad hoc and Sensor Networking, wireless network and wireless communication symposiums (ICC'17, GC'16, ICC'16, GC'14, ICC'14, ICC'12, GC'11, GC'10 ), since 2011 for International Wireless Communications and Mobile Computing Conference (IWCMC) and other conferences and workshops (VTC'14, ComComAp'13, ICNC'12, WCSP'12, Q2SWinet'12, P2MNET'11, WLN'10, WLN'09....). He is the chair of the IEEE Ad Hoc and sensor networks technical committee since January 2016, he was previously the vice chair and secretary for this committee. He has been appointed as IEEE comsoc distinguished lecturer since 2015 where he did several tours all around the world. He is member of IEEE technical services board since 2016.
Speech Title: New Directions to Improve and/or to Evaluate Wireless Networks in Cyberspace
Abstract: Cyberspace is always growing up since this last decade. Wireless and mobile networks are one of the technology that make the cyberspace a real success. Wireless and mobile networks have many advantages as easy deployment, user mobility and provides network access to users regardless to their locations. The most critical issues that arise in those networks are on the resource allocations as the bandwidth is limited, the propagation (multi-path, fading, distortion) and security since communications are transmitted over radio waves. In this seminar I will present several works done to model/Improve Quality of Service in Wireless networks. Three different methods will be presented in this lecture. In the first part a new model based on Markov chains is presented to model the different service classes defined in IEEE 802.16. The second part I will present a new AC that we have defined for IEEE 802.16 and we have evaluated using Stochastic Automata Networks.
Prof. Maryline Chetto
University of Nantes, France
Maryline Chetto is a full professor at the University of Nantes (France). She is conducting her research at LS2N (Laboratoire des Sciences du Numerique de Nantes). She received the degree of Docteur de 3ieme cycle in control engineering and the degree of Habilite a Diriger des Recherches in Computer Science from the University of Nantes, France, in 1984 and 1993, respectively. From 1984 to 1985, she held the position of Assistant professor of Computer Science at the University of Rennes 1, while her research was with the Institut de Recherche en Informatique et Systemes Aleatoires, Rennes, France. Her main research interests include Scheduling, Fault-tolerance and Dynamic Power Management technologies for real time embedded applications. She is now studying energy harvesting systems that use renewable energy to power embedded devices.
Speech Title: Challenges in the Design of Embedded Energy Harvesting Computing Systems
Abstract: This keynote addresses state of the art as well as our findings in real-time scheduling and processor activity management for energy harvesting computing devices. A growing number of applications (e.g. medical, environmental) involve many wireless devices that may be deployed in wide areas and possibly unattainable places. Such systems should be designed to function perpetually without any human intervention because either costly or impractical. As a consequence, energy harvesting technology has been an area of rapid development during the last decade. Energy harvesting is a technology that permits to capture unused ambient energy. It is converted into electrical energy which is used immediately or later through a storage unit. In addition to energy limitations, these devices have to cope with real-time requirements that are expressed in terms of deadline success. As a consequence, any real-time energy harvesting system needs to be provided with specific real-time scheduling and power management facilities.
Prof. Farid Meziane
University of Salford, United Kingdom
Professor Farid Meziane obtained a PhD in Computer Science from the University of Salford on his work on producing formal specification from Natural Language requirements. He is currently holding a chair in Data and Knowledge Engineering and is the director of the informatics research centre at the University of Salford, UK. He has authored over 100 scientific papers and participated in many national and international research projects. He is the co-chair of the international conference on application of Natural Language to information systems and in the programme committee of over ten international conferences and in the editorial board of three international journals. He was awarded the Highly Commended Award from the Literati Club, 2001 for his paper on Intelligent Systems in Manufacturing: Current Development and Future Prospects. His research expertise includes Natural Language processing, semantic computing, data mining and big data and knowledge Engineering.
Speech Title: A Framework for an Adaptable And Personalised e-Learning System Based On Free Web Resources
Abstract: The talk will summarise the work undertaken in the
development of the adaptable and personalised E-learning system (APELS)
architecture that will provide a framework for the development of
comprehensive learning environments for learners who cannot follow a
conventional programme of study. The system extracts information from
freely available resources on the Web taking into consideration the
learners' background and requirements to design modules and a planner
system to organise the extracted learning material to facilitate the
learning process. The process is supported by the development of an
ontology to optimise and support the information extraction process.
Additionally, natural language processing techniques are utilised to
evaluate a topic's content against a set of learning outcomes as defined
by standard curricula. An application in the computer science field is
used to illustrate the working mechanisms of the proposed framework and
its evaluation based on the ACM/IEEE Computing Curriculum.
A variety of models are developed and techniques used to support the adaptability and personalisation features of APELS. Learning style theories were adopted as a way of identifying and categorising individual learners to improve their on-line learning experience. A knowledge extraction model is responsible for the extraction of the learning resources from the Web that would satisfy the learners' needs and learning outcomes. To support this process, an ontology was developed to retrieve the relevant information as per users' needs. A matching process is implemented to compute the similarity measure between the ontology concepts and those extracted from the learning resources. The system was validated by developing Computer Science modules based on the ACM/IEEE Computer Science Curriculum.