Vikrant Bhateja is Associate Professor, Department of Electronics & Communication Engineering, Shri Ramswaroop Memorial Group of Professional Colleges (SRMGPC), Lucknow and also the Head (Academics & Quality Control) in the same college. He is doctorate in Bio-Medical Imaging & Signal Processing and has a total academic teaching experience of 15 years with around 125 publications in reputed international conferences, journals and online book chapter contributions. His areas of research include digital image and video processing, computer vision, medical imaging, machine learning, pattern analysis and recognition. Prof. Vikrant has chaired TPC and sessions from the above domain in international conferences of IEEE and Springer. He has edited 15 proceeding books/editorial volumes with Springer Nature. He is Editor-in-Chief of IGI Global--International Journal of Natural Computing and Research (IJNCR). He is also associate editor in International Journal of Synthetic Emotions (IJSE) and International Journal of Ambient Computing and Intelligence (IJACI) under IGI Global press. He is also serving in the editorial board of International Journal of Image Mining (IJIM) and International Journal of Convergence Computing (IJConvC) under Inderscience Publishers. He has also guest edited Special Issues in reputed Scopus/SCIE indexed journals under Springer-Nature. He has received the ‘Certificate of Outstanding Contribution in Reviewing’ for year 2016 and 2017 respectively in prestigious Elsevier journals like: AEUE, Measurements, Computer Methods and Programs in Bio-medicine. Presently, he is guest editor in prestigious Springer journals: “Evolutionary Intelligence” and “Arabian Journal of Science and Engineering”.
Dr. Vikrant has an h-index of 21 on Scopus and 25 on Google Scholar.https://scholar.google.co.in/citations?user=u_Mp2HwAAAAJ&hl=en
Computer aided analysis of mammograms is the most primary requisition in early detection of breast cancer. Enhancement of mammograms is constrained owing to variable nature of the surrounding breast tissues and type of lesions imaged. Non-linear filtering approaches are highlighted as suitable choice for mammogram enhancement as the response of these filters is well correlated with Human Visual System (HVS) characteristics.
Non linear polynomial filters have been an effective tool towards noise controlled contrast and edge enhancement of mammograms. The utility of these filters towards detection of variety of mammographic anomalies will be discussed and demonstrated. Applicability of these filters to other medical imaging modalities will be explored. Future directions to carry further research in this domain will be discussed.
Pr. Abdelhakim Senhaji Hafid is Full Professor at the University of Montreal. He is the director of the Network Research Lab and the Montreal Blockchain Lab. He is also research fellow at CIRRELT and IVADO, Montreal, Canada. Pr. Abelhakim Senhaji Hafid published over 230 journal and conference papers; he also holds 3 US patents. Prior to joining U. of Montreal, he spent several years, as senior research scientist, at Bell Communications Research (Bellcore), NJ, US working in the context of major research projects on the management of next generation networks. Pr. Abdelhakim Senhaji Hafid was also Assistant Professor at Western University (WU), Canada, Research director of Advance Communication Engineering Center (venture established by WU, Bell Canada and Bay Networks), Canada, researcher at CRIM, Canada, visiting scientist at GMD-Fokus, Berlin, Germany and visiting professor at University of Evry, France. Pr. Abelhakim Senhaji Hafid has extensive academic and industrial research experience in the area of the management of next generation networks. His research interests include also intelligent transport systems, Blockchain, cloud/mobile cloud, IoT, and fog computing.
Blockchain can be simply defined as a distributed digital ledger that keeps track of all the transactions that have taken place in a secure, chronological and immutable way using peer-to-peer networking technology. The most known blockchain application is bitcoin that supports transactions of bitcoin transfer. However, blockchain is finding many uses in financial and non-financial applications; indeed, it is believed that blockchain will transform how we live, work, and interact. This talk will start with an introduction to Blockchain technology. It will show how Blockchain works. It will present the concept of smart contracts, which are critical in developing blockchain applications. It will also identify industry segments where blockchain can play a key role in solving existing issues. Then, the talk will address the integration of blockchain and AI; in particular, it will show how Blockchain can help advancing and democratizing AI. The talk will conclude by briefly overviewing our work at Montreal Blockchain Lab and our view on the future of blockchain and its intersection with AI
Pr. Jamal Zbitou was born in Fes, Morocco, in June 1976. He received the Ph.D. degree in electronics from Polytech of Nantes, the University of Nantes, France, in 2005. He is currently anassociate Professor of Electronics in FST, University of Hassan 1st, Morocco. He is involved inthe design of hybrid, monolithic active and passive microwave electronic circuits.
The use of microwave waves for wireless energy transport is an attractive alternative for applications such as:
In 1967, the first studies on wireless microwave transmission were launched by Mr. Brown as part of a US Air Force-funded project for the implementation of an observation platform stationary at high altitude. Given the importance for the future of this field of research, many works have been succeeded. One of these lines of research aims to develop a device called "rectenna", composedfrom a receiving antenna followed by a rectifier system, the purpose is to optimize the conversion efficiency AC-DC. This presentation will discuss firstly the theoretical study of designing rectennas, and the different technologies used to design such circuit. The second research focus will be about Radio frequency identification (RFID) which is a non-contact automatic identification and data acquisition technology which uses radio waves. The two major components of the RFID system are the reader and the tag. This second part of this presentation will be about the design of miniature antennas for Tag.
Pr. Mohammad A. M. Abushariah is working as an Associate Professor at the Department of Computer Information Systems, King Abdullah II School of Information Technology, The University of Jordan. He obtained his bachelor degree in information technology from the International Islamic University Malaysia, Malaysia in 2005. He then obtained his Master degree in software engineering and Ph.D. in computer science and information technology specialized in Natural Language Processing (NLP) andspeech processing from University of Malaya, Malaysia in 2007 and 2012, respectively. He is a supervisor of various Ph.D. and Master research students specialized in Arabic NLP, speech processing, and software engineering. He has over 50 publications in ISI journals, IEEE international conferences, and technical reports. He was appointed as the Guest Editor of a special issue (Volume 19, No. 2) on Arabic Natural Language Processing and Speech Recognition: A study of algorithms, resources, tools, techniques, and commercial applications, which was published in 2016 by the International Journal of Speech Technology (IJST), Springer. In February 2019, he was appointed as an academic editor on the editorial board of Public Library of Science (PLOS) One journal, which is indexed in Scopus and ISI/WoS (JCR). In March 2018, he was appointed as an editorial board member of the Journal of Theoretical and Applied Information Technology (JATIT), which is indexed in Scopus.In January 2017, he was appointed as an External Associate Editor for the Malaysian Journal of Computer Science (MJCS), which is indexed by ISI/WoS (JCR). In April 2015, he was appointed as an Editorial Team Member of the International Journal of Open Information Technologies (INJOIT). He also serves as a reviewer for various specialized international journals indexed in ISI/WoS (JCR) and conferences. In April 2014, he was appointed as a Consultant of NLP and speech recognition for Samsung R&D Institute in Jordan working with a distributed team with Samsung Headquarter in South Korea. In September 2014, he was appointed as the assistant dean for student affairs at School of Graduate Studies, The University of Jordan. In September 2015, he was appointed as the assistant dean for development and quality affairs at School of Graduate Studies, The University of Jordan. Since September 2016 until September 2018, he acts as the deputy dean at King Abdullah II School of Information Technology, The University of Jordan. His research interests include: Arabic NLP, Arabic speech processing, text and speech corpora, language resources production, speaker recognition using biometrics, speech emotion recognition, Arabic sign language, sentiment analysis, and software engineering.
Automatic Speech Recognition (ASR) is gaining its importance due to the vast growth generally in relevant technology and computing in specific. From industrial perspective, computers, laptops, smartphones, and manyother smart devices nowadays have the ASR support embedded into the operating systems. From academia on the other hand, there are many research efforts being conducted addressing this technology in order to contribute to its state-of-the-art. In order for human to experience the benefits and privileges of ASR technology, ASR systems and applications must provide support to human natural languages worldwide including Arabic, English, French, Spanish, Mandarin, Dutch and various others. They should provide support to the standard forms of the language as well as their dialectal forms.Unlike English, many languages such as Arabic still need more research to achieve matured ASR technology and highly performing applications. In this keynote speech, I will elaborate on the major components of ASR systems with more emphasis on Arabic language. The required language resources including speech and text corpora, and phonetic dictionary will be discussed. In addition, I will highlight on applicable tools and techniques for Arabic ASR systems. This keynote speech will thoroughly include open challenges and a roadmap for Arabic ASR technology. Finally, I will talk about my research and industrial efforts generally in Arabic Natural Language Processing (NLP) and specifically in Arabic ASR, which will enlighten the audience of the keynote speech and graduate students about potential collaboration in the near future.
Pr. Assal A. M. Alqudah is working as a Speech Science Consultant for "Nuance Communication Services Ireland Ltd. – Dubai Branch" since March 2017, where she works on several aspects of Arabic and English Natural Language Processing (NLP). She is also working as a research assistant in The University of Jordan on research projects related to Automatic Speech Recognition (ASR) for speakers with speech disorders and Enterprise Resource Planning (ERP). She obtained her bachelor degree in computer information systems from Yarmouk University, Jordan, in 2010. She then obtained her Master degree in software engineering from University of Malaya, Malaysia, in 2011. She finally obtained her Ph.D. in Computer Science from The University of Jordan, Jordan, in 2018. She has academic and industrial experience that make her in a strong position to handle both teaching and research of many computer science aspects including and not limited to NLP, artificial intelligence, text mining, data science, Arabic speech processing, text and speech corpora, language resources production, speaker recognition using biometrics, and also software engineering.
The rapidly changing and evolving technologies in the last three decades produced another type of communication known as human-machine communication or the human-computer interaction (HCI). People today not only speak to each other, but also to systems and applications that are embedded into computers, smartphones, smart watches, and many other smart devices. This interaction is possible if users have good speech and language skills to convey clear and understandable messages. Without these skills, users may have problems with interacting with new technologies and embedded systems. However, many users suffer from speech disordersand are incapable to produce the correct speech sound when using and speaking to systems especially systems that rely on Automatic Speech Recognition (ASR) technology such as automatic query answering, automatic speech translation, speech dictation, command and control, and many more. In this keynote speech, I will elaborate on the main categories of speech disorders with more emphasis on articulation disorders such as substitution and distortion. I will also present my efforts in adapting the ASR technology to speakers with speech disorders for Modern Standard Arabic (MSA) especially the development of the Arabic disordered speech phonetic dictionary generator for ASR technology research and development purposes.
Suresh Chandra Satapathy is a PhD in Computer Science, currently working as Professor and at KIIT (Deemed to be University), Bhubaneshwar, Odisha, India. He held the position of the National Chairman Div-V (Educational and Research) of Computer Society of India and is also a senior Member of IEEE. He has been instrumental in organizing more than 20 International Conferences in India as Organizing Chair and edited more than 30 Book Volumes from Springer LNCS, AISC, LNEE and SIST Series as Corresponding Editor. He is quite active in research in the areas of Swarm Intelligence, Machine Learning, Data Mining. He has developed a new optimization algorithm known as Social Group Optimization (SGO) published in Springer Journal. He has delivered number of Keynote address and Tutorials in his areas of expertise in various events in India. He has more than 100 publications in reputed journals and conf proceedings. Dr. Suresh is in Editorial board of IGI Global, Inderscience, Growing Science journals and also Guest Editor for Arabian Journal of Science and Engg published by Springer.
Nature provides some of the efficient ways to solve problems. Nature inspired algorithms imitating processes in nature/inspired from nature for solving complex optimization problems. This talk explores the use of recently proposed new efficient optimization algorithm Social Group Optimization (SGO) which is inspired by the social behavior of human for solving complex problems. To judge the effectiveness of SGO, extensive experiments have been conducted on number of different unconstrained benchmark functions and performance comparisons are made with recently proposed state-of-art optimization techniques as well as 30 standard numerical benchmark functions taken from ICSI 2014 Competition on Single Objective Optimization and compared with the performance of six selected algorithms of that competition. It is shown that this algorithm have respected value in research world like other algorithms.