Dakota State University, USA
Dr. Houssain Kettani received the Bachelor's degree in Electrical and Electronic Engineering from Eastern Mediterranean University, Cyprus in 1998, and Master’s and Doctorate degrees both in Electrical Engineering from the University of Wisconsin at Madison in 2000 and 2002, respectively. Dr. Kettani served as faculty member at the University of South Alabama (2002-2003), Jackson State University (2003-2007), Polytechnic University of Puerto Rico (2007-2012), Fort Hays State University (2012-2016), Florida Polytechnic University (2016-2018) and Dakota State University since 2018. Dr. Kettani has served as Staff Research Assistant at Los Alamos National Laboratory in summer of 2000, Visiting Research Professor at Oak Ridge National Laboratory in summers of 2005 to 2011, Visiting Research Professor at the Arctic Region Supercomputing Center at the University of Alaska in summer of 2008 and Visiting Professor at the Joint Institute for Computational Sciences at the University of Tennessee at Knoxville in summer of 2010. Dr. Kettani’s research interests include computational science and engineering, high performance computing algorithms, information retrieval, network traffic characterization, number theory, robust control and optimization, and Muslim population studies. He presented his research in over sixty refereed conference and journal publications and his work received over four hundred citations by researchers all over the world. He chaired over hundred international conferences throughout the world and successfully secured external funding in millions of dollars for research and education from US federal agencies such as NSF, DOE, DOD, and NRC.
Speech Title: Advances in High Performance Computing and Impact on Cybersecurity
Abstract: In the past thirty years, advances in high performance computing have increased the performance by million times, and decreased the volume of the machine by similar order. Accordingly, the fastest computer in the world increased its performance from one Gigaflop/s in mid-1980s to a projected one Exaflop/s by 2020. In addition, current hand-held devices such as smartphones have performance that rivals those machines of the 1980s. Due to hardware limitations, parallel computing became an integral part of our lives that it is hard to imagine a device that is not using multiprocessor power, including smartphones. What started as a hardware solution to physical limitation, prompted software engineers to adopt to parallelism, which also motivates the theoretical solution to algorithms design and analysis to provide a solution that is parallel oriented rather than a serial oriented one. The increased computing power also means an increase in the efficiency of brute force attack algorithms on encryption standards, which will make the widely adopted Advanced Encryption Standard obsolete by the end of this century.
Western Michigan University, USA
Ala Al-Fuqaha (S’00-M’04-SM’09) received Ph.D. degree in Computer Engineering and Networking from the University of Missouri-Kansas City, Kansas City, MO, USA, in 2004. Currently, he is a Professor at the Information and Computing Technology (ICT) division, College of Science and Engineering (CSE) of Hamad Bin Khalifa University (HBKU). His research interests include the use of machine learning in general and deep learning in particular in support of the data-driven and self-driven management of large-scale deployments of IoT and smart city infrastructure and services, Wireless Vehicular Networks (VANETs), cooperation and spectrum access etiquette in cognitive radio networks, and management and planning of software defined networks (SDN). He is a senior member of the IEEE and an ABET Program Evaluator (PEV). He serves on editorial boards and technical program committees of multiple international journals and conferences.
Speech Title: TBA
University of Gloucestershire, UK
Dr Salah Al-Majeed,
highly experienced academic manager with successful
accomplishments records of brand technology, product innovations
and corporate communication. A proficient academic Professor
with extensive international profile and high quality of
delivering academic teaching and research. Prof Al-Majeed is the
Academic Subject Leader (Head) of Engineering and Technology at
School of Business and Technology, University of
Gloucestershire. Prior to his current position, Dr Salah was
Head of Systems Engineering School at the Military Technological
College -MTC Oman (partner with University of Portsmouth, UK).
In addition to his role as academic and manager, Salah has an extensive portfolio of Industrial, Academia and R&D works, leading the innovation of implementing technologies. Conduct research into issues and challenges in data exploration through Internet of Things (IoT) and Smart Environment (including Smart City and Biomedical and Health informatics) from a multitude of perspectives, which is driving breakthroughs and innovation in a range of areas, such as Sensor, E-Health, Telemedicine and Mobile Telemedicine, Wireless Networks (4G and 5G) for different layers and applications. Where that can be seen through his role as a lead consultant at North Caspian Operating Company - NCOC – Kazakhstan for Sensabot project and collaborating closely with Huawei, Shell and Carnegie Mellon University – CMU, USA. In addition, his research projects were supported and funded by UK, EU and International organizations and companies.
Prof Al-Majeed is an Editor-in-Chief of Computer Science Engineering: An International Journal, and Editorial Member, International Journal of Computer Science, Engineering and Applications. In addition to his recognition as a Senior Member of IEEE, he is a reviewer for many well-known journals including IEEE transections and an invited keynote speaker for many of international conferences and events. Recently, he was the Technical Activities Officer of IEEE Oman Section.
Speech Title: TBA
Mohammed V University, Morocco
Mohamed SBIHI, received PhD in automation and information processing from the Faculty of Sciences, University Ibn Tofail in Kénitra, Morocco, in 2006. His research interests include the Real-Time Image Processing, Data analysis, Embedded Systems and Robotics and E- Learning. He is Professor of Higher Education since 1996. Actually, he is Professor at the International Professions of Morocco Departement in the Superior School of Technology of Sale (ESTS), Mohammed V University In Rabat, Morroco and professor at the Abulcasis International University of Health Sciences, Rabat, Morocco. He is a Member of Laboratory of the Analysis Systems, Information Processing and Industrial Management at ESTS. He is Director of several doctoral Thesis, Author of an International Book and Multiple Journal/Conference Papers. He is a member of the Scientific Committee and Program Chair of Multiple National and International Conferences.
Speech Title: Image Processing: From Optimization to Implementation on Programmable Circuits
Abstract: Image segmentation and edge detection are key processes in classification and pattern recognition fields. The major difficulties encountered during the development of the applications related to these image processing steps reside, firstly in the adaptation of the algorithm to the application. This difficulty can be solved if we can find an optimal approximation to the characteristics of the considered images. This implies a good knowledge in advance of parameters relative to additional noise to the images, the properties of the image (format, resolution, dimensions, ...) and edges or regions of interest inherent to the application field. On the other hand, the second difficulty is to be able to obtain the best results in terms of quality, detectability of details or processing time. This presentation aims to show the accomplished improvements to algorithms, en term of optimization, for both segmentation and edge detection of digital images. In this context, the first part of the presentation focuses on the optimization of Markov algorithms for improving the quality of image segmentation results in remote sensing and industrial radiography. At first, the optimization is done in satellite imagery field, by fusing the Markovian algorithm ICM with Fuzzy C-Means (FCM) algorithm, according to the theory of evidence. Then, the improvement of the Hidden Markov Random Fields (HMRF) will be implemented in the industrial radiography related to Non Destructive Testing, by introducing the algorithm of Artificial Bee Colony (ABC). The second part of the presentation is dedicated to the optimization of image edge detection algorithms using real-time implementation on an FPGA circuit (Field- Programmable Gate Array). In time domain, the algorithms implemented are based on the variation of the intensity, first by the calculation of the gradient and, second by the calculation of Laplacian. In the frequency domain, the implemented algorithm is based on the computation of the wavelet transform. The resulting images after processing are real-time displayed on a VGA monitor. The performance of the optimization using real-time implementation of the proposed algorithms is shown through images in medical field as well as other images in other different fields.