Tabrizi received his B.S. degree in Computer Science from Manchester University, UK. He then completed his M.S. and Ph.D. from Automatic Control and Systems Engineering Department, Sheffield University, UK. Tabrizi worked in Manchester University for two years prior to his appointment at East Carolina University in 1984. He is the Graduate Program Director of Computer Science and founder and director of Software Engineering graduate program at East Carolina University. His research interests are in the areas of Virtual Reality, Modeling and Simulation, Computer Vision, Signal and Image Processing, Software Engineering, Big Data, Machine Learning, Assistive Technologies, and Computer Science Education.
The transformation of our current cities into smarter cities will bring challenges in diverse areas such as the transportation system, the electricity system, and wearable systems, just to name a few. In smart cities, Information and Communication Technologies (ICT) will play a vital role for providing services in the urban environment. These services include real time monitoring and reaction in time through wireless sensor and actuator networks. Smart Grids (SGs), Intelligent Transportation Systems (ITS), Internet of Things (IoT), Electric Vehicles (EVs), and Wireless Sensor Networks (WSNs) will be the building blocks of futuristic smart cities. All these technologies will help in building smart cities. In this presentation we will address technology trends with a focus on autonomous vehicles and in particular on Connected and Autonomous Electric Vehicles (CAEVs) in smart cities. Current capabilities as well as limitations and opportunities of key enabling technologies will be reviewed, along with a discussion on the impact of such advances on society and the environment. Predictions about changes in the car-industry will be discussed, including potential industry winners and losers.
After four years of industrial experience mainly at Bell-Northern Research (BNR), Dr. Hussein T. Mouftah started his academic career as an Assistant Professor in the Department of Electrical and Computer Engineering at Queen’s University in 1979. In 1988 he became full professor there and from 1998 until 2002 he was Associate Head for the Department. Since 2002 he has been a Tier 1 Canada Research Chair at the University of Ottawa, SITE and in 2006 he was appointed Distinguished University Professor. During his sabbatical leaves, he did consulting work for BNR and Nortel Networks (1986-87; 1993-94; and 2000-01). Dr. Mouftah has published over 1000 technical papers, 7 books and 48 book chapters. To his credit he has 12 patents and 140 industrial reports. He has received research grants and contracts totalling close to $40 million and he has supervised more than 300 highly qualified personnel of which 95 are Master’s and 63 are PhD graduates and 30 are post-doctoral fellows. Dr. Mouftah has served the Institute of Electrical and Electronic Engineering (IEEE) Communications Society as Editor-in-Chief of the Communications Magazine (1995-97), Director of Magazines (1998-99), Chair of the Awards Committee (2002-03), Director of Education (2006-07), and Member of the Board of Governors (1997-99 and 2006-07). Also, he is the founding Chair of two of IEEE Communications Society’s Technical Committees (TCs): Optical Networking TC (2002-04) and Ad Hoc and Sensor Networks TC (2005-07). He has been a Distinguished Speaker of the IEEE Communications Society (2000-2008). Dr. Mouftah is the recipient of the 1989 Engineering Medal for Research and Development from the Association of Professional Engineers of Ontario and of the 2002 Ontario Distinguished Researcher Award of the Ontario Innovation Trust. He has also received 12 Outstanding/Best Paper Awards (ISMVL’1984; IEEE Communications Magazine in 1993; SPECTS’2002; HPSR’2002; CITO Innovators2004; ICC’2005; 2 at ISCC2008; CCECE2009; IST-AWSN’09; WiSense2010; and EPEC2010), the IEEE Canada Outstanding Service Award (1995), and the CSIM Distinguished Service Award of the IEEE Communications Society (2006). In 2004 Dr. Mouftah received the IEEE Communications Society Edwin Howard Armstrong Achievement Award and the George S. Glinski Award for Excellence in Research from the Faculty of Engineering, University of Ottawa. In 2006 he was honoured with the IEEE McNaughton Gold Medal and the Engineering Institute of Canada Julian Smith Medal. In 2007 he was the recipient of the Royal Society of Canada Thomas W. Eadie Medal. He has also received the 2007-2008 University of Ottawa Award for Excellence in Research, and the 2008 ORION Leadership Award of Merit. Dr. Mouftah is a Fellow of the IEEE (1990), Fellow of the Canadian Academy of Engineering (2003), Fellow of the Engineering Institute of Canada (2005), and Fellow of the Royal Society of Canada RSC Academy of Sciences (2008).
Recently, a variety of IoT and social computing services have led to the big data era where a large volume of multi-dimensional data with spatial and temporal features are widely available. In addition, advances of big data processing and AI technologies have made such spatial and temporal data as important data sources to extract knowledge on the real world such as event/trend detection and monitoring. In this talk, we will present our recent works on spatial and temporal big data processing. First, we will focus on fundamental techniques for spatial and temporal big data processing including efficient data retrieval (advanced query processing) and pattern mining (e.g. motif detection) on multi-dimensional data streams, which can be commonly used in many applications. We will also talk about techniques for big data analysis on social media (e.g. twitter). Then, our talk will move on to applications of data processing/analysis on spatial and temporal big data. In particular, we will present some of our on-going projects including knowledge extraction from social media, digital marketing, and locomotion analysis of wild life. Finally, we will summarize this talk and discuss about future directions.
Takahiro Hara received his PhD from Osaka University, Japan, in 2000. Currently, he is a full Professor of the Department of Multimedia Engineering, Osaka University. He has published more than 450 Journal and international conference papers. He served as a General Chair of IEEE SRDS'14 and Mobiquitous'16. He also served as a Program Chair of a number of international conferences including IEEE MDM'06, 10 and 18, IEEE AINA'09 and 14, Mobiquitous'13, and IEEE SRDS'12. His research interests include databases, sensor networks, social computing, and mobile computing. He is a distinguished scientist of ACM and a senior member of IEEE.
Future factories will be distinguished by Cloud computing, Internet of Things, intelligent machines, intelligent automation, human factors integration and knowledge management. While many advanced and smart factories the world over are embracing the fourth Industrial revolution, or better known as Industry 4.0, a key fundamental component has been overlooked, i.e; the notion of human intelligence and creativity and its’ integration into future smart systems that will carry us into the next phase, allowing future products to be personalized. This talk will cover the history, recent achievements, roles of modelling and computer simulation both at system and products levels from virtual reality, augmented reality to haptics and intelligent human machine interfaces and how future systems should be designed to facilitate the transition from mass production, mass customisation to mass personalisation, hence the introduction of Industry 5.0. Through a series of case studies, various elements of such a futuristic system will be showcased and the knowledge gaps that require filling to take us across the threshold.
Saeid Nahavandi received his BSc (Hons), MSc and PhD in Control Engineering from Durham University, UK in 1985, 1986 and 1991 respectively. Saeid is an Alfred Deakin Professor, Pro Vice-Chancellor and the Director for the Institute for Intelligent Systems Research and Innovation at Deakin University in Australia. Professor Nahavandi is a Fellow member of IET, IEAust and Senior Member of IEEE and has published over 800 refereed papers and been awarded several competitive grants over the past 30 years. He received the Research collaboration / initiatives award from Japan (2000) and Prince & Princess of Wales Science Award in 1994. He won the title of Young Engineer of the Year Award in 1996 and holds six patents. In 2002 Professor Nahavandi served as a consultant to the Jet Propulsion Lab (NASA) during his visit to JPL Labs. He has carried out industry based research with several major international companies such as Boeing, Bosch, Ford Motor Company, General Motors, General Dynamics, Holden, Lockheed Martin, Nissan, Thales and Vestas just to name a few. Professor Nahavandi was General Co-Chair for IEEE SMC 2011. He also holds the position of Co-Editor-in-Chief for IEEE Systems Journal, Associate Editor: IEEE/ASME Mechatronics, Associate Editor: IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS: SYSTEMS, Associate Editor: IEEE SMC Magazine.
Art & Design has been a significant area of study and practice in the world since centuries. It is ancient as well as most modern. In addition to its critical importance in the traditional fields of Painting, Sculpturing, Fashion, Textile and Archeology, more recently, it is has also proven to be indispensable in a variety of modern industries. Robotics, medical imaging, visualization, and even media and many other industries have excelled due to power of modern computing. This presentation aims to provide and enlighten on the power of computing for Art & Design. Specific concentration would be made on modeling using tool of splining. The talk is going to focus on interdisciplinary methods and affiliate research in the area. It aims to provide the audience with a variety of techniques, applications and examples necessary for various real life problems. The major goal of the talk is to stimulate views and provide a source where researchers and practitioners can find the latest developments in the field. The talk may specifically be of interest to people in the industries or academic fields including Computer Graphics, Computer Aided Geometric Design, Computer Vision, Image Processing, Virtual Reality, Information Visualization, Body Simulation, Engineering Disciplines, Mathematical Sciences, Font Industry, Art & Design, Film industry, Software Industry, Manufacturing Industry. It may also lead to applications like vector graphics, digitization of hand-drawn shapes, computer supported cartooning, pattern recognition, Computer Aided Design (CAD), Computer Aided Manufacturing (CAM), Computer Aided Geometric Design (CAGD), and various other applications.
Muhammad Sarfraz is a Professor and Director of Graduate Studies in the Department of Information Science, Kuwait University, Kuwait. His research interests include Computer Graphics, Pattern Recognition, Computer Vision, Image Processing, Soft Computing, Machine Learning, Data Science, Information Technology, Intelligent Systems and Information Systems. He is currently working on various projects related to academia and industry. Prof. Sarfraz has been keynote/invited speaker at various platforms around the globe. He has advised/supervised more than 70 students for their MSc and PhD theses. He has published more than 350 publications as journal and conference papers. His publications include around 55 Books as Author and Editor. He is also Editor of Proceeding Books of various Conferences around the globe. Prof. Sarfraz is member of various professional societies including IEEE, ACM, IVS, IFAC, INSTICC and ISOSS. He is a Chair, member of the International Advisory Committees and Organizing Committees of various international conferences, Symposiums and Workshops. He is also Editor-in-Chief, Editor and Guest Editor of various International Journals. He is the reviewer, for many international Journals, Conferences, meetings, and workshops around the world. He has achieved various awards in education, research, and administrative services.
Application modeling is important in software development projects such as safety-critical real-time systems. The Unified Modeling Language (UML) has been accepted as the de facto object-oriented modeling language for software systems, and is supported by major corporations, research, and academic institutions. In relational database development, entity-relationship models have traditionally been used for modeling such systems. It has been acknowledged that relational database management systems need a better representation of the real world than that obtained with the current tabular representation that are derived from the entity-relationship models. Object-oriented modeling is an effective mechanism for representing real world structures as it provides diagrams for modeling different aspects of the system. There are a number of techniques for extending and transforming object-oriented models to object-relational database systems. One transformation approach involves the use of formal (mathematical) techniques; the use of a formal technique transformation incorporates the use of graph-theory on UML class diagram. The main focus of this work is the transformations of UML class diagrams into a set of Data Definition Language statements in SQL:2003, by applying the methodologies to a case study class diagram. This work, demonstrated, compared, and evaluated a formal methodology for transforming UML class diagram models into object-oriented relational databases. The work identified the key activities, and determined the advantages and disadvantages of the methodologies and proposed possible improvements to the methodology.
Emanuel S. Grant received a B.Sc. from the University of the West Indies, MCS from Florida Atlantic University, and a Ph.D. from Colorado State University, all in Computer Science. Since 2008, he is an Associate Professor in the Department of Computer Science at the University of North Dakota, USA, where he started as an Assistant Professor in 2002. His research interests are in software development methodologies, formal specification techniques, domain-specific modeling languages, and model driven software development, and software engineering education. He is an adjunct professor at the Holy Angel University, Philippines, where he is conducting research in software engineering teaching with collaborators from HELP University College, Malaysia; III-Hyderabad, India; Singapore Management University, Singapore; Montclair State University, and University of North Carolina Wilmington of the USA; and the University of Technology, Jamaica. Emanuel is a member of the Association for Computing Machinery (ACM), Upsilon Pi Epsilon (UPE), and the Institute of Electrical and Electronics Engineers (IEEE).
Cloud computing is revolutionizing the way we think of data storage and core enterprise services. As a business enabler, its popularity has resulted in a rapid increase in adoption by industry and government, with it being implemented as a) Software as a Service (SaaS), b) Platform as a Service (PaaS) and c) Infrastructure as a Service (IaaS). This rapid adoption has resulted in a number of challenges related to privacy, security and investigations. NIST’s Cloud Computing Forensic Science working group has identified numerous challenges this technology has brought to the field of digital forensics (NISTIR 8006 publication). While many of these challenges have potential technical solutions, others are more properly situated in public policy, governance, and international cooperation. Even the technical issues have nuances that strike to the very heart of why cloud computing has been so embraced (e.g., resource pooling, rapid elasticity), and modifying these could result in the cloud computing model becoming unattractive to businesses and consumers. As with other rapid growth technologies, our focus on securing it has greatly lagged our focus on development and implementation. The challenges facing cloud computing forensics will require a multidisciplinary approach across the computing, engineering and technology fields, as well as cooperation with the international legal justice system.
Dr. Rogers is a Professor/Department Head, Fellow of the American Academy of Forensic Sciences (AAFS), University Faculty Scholar and Fellow - Center for Education and Research in Information Assurance and Security (CERIAS). Dr. Rogers is the Chair of the Digital and Multimedia Sciences section of the American Academy of Forensic Sciences (AAFS), past International Chair of the Law, Compliance and Investigation Domain of the Common Body of Knowledge (CBK) committee,Co-Editor Cyber crime Dept. IEEE Security & Privacy, NIST-OSAC DE Member and Chair of the Education Task Group for DE. He is a former Police officer who worked in the area of fraud and computer crime investigations. Dr. Rogers sits on the editorial board for several professional journals. He is also a member of other various national and international committees focusing on digital forensic science and digital evidence. Dr. Rogers is the author of books, book chapters, and journal publications in the field of forensic psychology, digital forensics and applied psychological analysis. His research interests include applied cyber forensics, psychological digital crime scene analysis, and cyber terrorism. He is a frequent speaker at international and national information assurance and security conferences, and guest lectures at various universities throughout the world.
The concept, backgrounds, progresses of academic research and industrial applications of digital twin (DT) are first introduced. A five dimensions mode for digital twin is proposed in order to make the DT concept widely used in product lifecycle, including product design, manufacturing and service. A new shop-floor paradigm towards smart manufacturing, named digital twin shop-floor (DTS) is proposed and discussed. The architecture, system composition, running mechanism, and enabling key technologies of DTS are investigated. Then the theories and technologies for cyber-physical fusion based on DT are discussed from four aspects, including physical fusion, model fusion, data fusion and service fusion. At last, the related practical researches of DT from the DT research group at Beihang University are briefly introduced.
Fei Tao is currently a Professor at the School of Automation Science and Electrical Engineering, Beihang University, Beijing, China, where he served as the Vice Dean from Jan. 2015 to Jun. 2018. Now he is the Director of High-Technology Office at Beihang University Since June 2018. His current research interests include service-oriented smart manufacturing, manufacturing service management and optimization, digital twin driven product design/ manufacturing/service, sustainable manufacturing and cloud manufacturing. He has authored 4 monographs and over 60 journal papers in these fields, which obtained over 8,400 citations in Google Scholar and 3,000 citations in Web of Science. Dr. Tao is currently the Editor of International Journal of Service and Computing-oriented Manufacturing (IJSCOM).
We present a few IoT-oriented networking research activities carried out at the Internet of Things (IoT) Lab of the Department of Engineering and Architecture of the University of Parma. In particular, we distinguish between: sensor networking (efficient IoT data collection with RPL in IEEE 802.15.4 networks), mesh networking (IoT-oriented WiFi and BLE mesh networking), 5G networking (data processing in the cloud), and hybrid networking (integration of multiple radio technologies).
Gianluigi Ferrari was born in Parma, Italy, on November 13, 1974. He received the "Laurea" degree (5-year program) in Electrical Engineering "summa cum laude" from the University of Parma, Parma, Italy in October 1998. He received the Ph.D. degree in "Information Technologies" from the Department of Information Engineering (Dipartimento di Ingegneria dell'Informazione, DII) of the University of Parma in January 2002. From July 2000 to December 2001 he was a Visiting Scholar at the Communication Sciences Institute, University of Southern California, Los Angeles, California, USA. Between February 2002 and August 2002, he was a Postdoc Student at the DII, University of Parma. Between September 2002 and October 2010, he was a Research Professor at the DII of the University of Parma. Since November 2010, he has been an Associate Professor at the same department (he received the Italian nation-wide habilitation from Polytechnic of Milan in August 2010): in 2017, the DII has been merged with other engineering departments and architecture and is now the Department of Engineering and Architecture (Dipartimento di Ingegneria e Architettura, DIA). During October 2002-February 2003, July-December 2003 and July-December 2004, he was a Research Associate at the Electrical and Computer Engineering Department of Carnegie Mellon University, Pittsburgh, PA, USA. Since September 2006 he has been the Coordinator of the Internet of Things (IoT) Laboratory. In Fall 2007 he visited, as a DUO-Thailand Fellow, the King Mongkut's Institute of Technology Ladkrabang (KMITL), Bangkok, Thailand. Between July 2010 and October 2010, he was a Visiting Researcher, within a "Brains (Back) to Brussels" (B2B) program, at the OPERA Department of the Université Libre de Bruxelles (ULB), Belgium. In December 2013, he received the "Abilitazione Scientifica Nazionale" (National Scientific Qualification) for Full Professorship in Telecommunications. In 2015, he has been nominated, by the Italian Ministry of Defense, as the only Italian representative (Technical Team Member) in the NATO Research Task Group (RTG) HFM-260 "Enhancing Warfighter Effectiveness with Wearable Bio Sensors and Physiologicol Models," in the period 2015-2018.
Artificial Intelligence is applied for prediction and calculations of unknown values of data or coordinates. Decision makers, academicians, researchers, advanced-level students, technology developers, and government officials will find this text useful in furthering their research exposure to pertinent topics in AI, computer science, numerical analysis or operations research and assisting in furthering their own research efforts in these fields. Proposed method, called Two-Points Smooth Interpolation (TPSI), is the method of 2D curve interpolation and extrapolation using the set of key points (knots or nodes). Nodes can be treated as characteristic points of data for modeling and analyzing. The model of data can be built by choice of probability distribution function and nodes combination. TPSI modeling via nodes combination and parameter γ as probability distribution function enables value anticipation in AI, risk analysis and decision making. Two-dimensional curve is extrapolated and interpolated via nodes combination and different functions as continuous probability distribution functions: polynomial, sine, cosine, tangent, cotangent, logarithm, exponent, arc sin, arc cos, arc tan, arc cot or power function.
Dariusz Jacek Jakóbczak was born in Koszalin, Poland, on December 30, 1965. He graduated in mathematics (numerical methods and programming) from the University of Gdansk, Poland in 1990. He received the Ph.D. degree in 2007 in computer science from the Polish – Japanese Institute of Information Technology, Warsaw, Poland. From 1991 to 1994 he was a civilian programmer in the High Military School in Koszalin. He was a teacher of mathematics and computer science in the Private Economic School in Koszalin from 1995 to 1999. Since March 1998 he has worked in the Department of Electronics and Computer Science, Koszalin University of Technology, Poland and since October 2007 he has been an Assistant Professor in the Chair of Computer Science and Management in this department. His research interests connect mathematics with computer science and include computer vision, artificial intelligence, shape representation, curve interpolation, contour reconstruction and geometric modeling, numerical methods, probabilistic methods, game theory, operational research and discrete mathematics.
Small and medium enterprises (SMEs) have proved themselves to be slow adopters of the new technology of big data analytics and are in danger of being left behind. This presentation examines the opportunity for small businesses, to take advantage of "data-driven decision-making" and to achieve significant improvement in their productivity and profitability, by disconnecting the place of operation, and receiving free high-quality advisory services, guidance and support. In this presentation we will • Identify barriers to SMEs uptake of big data analytics and recognizes their complex challenges to all stakeholders and propose a ‘big data hybrid business analytics advisory service model’ for SMEs that uses business analytics tools utilizing big data and is supported by teams of specialists. • Propose a business advisory model and discuss its digital implementation as a collection of web services should be supported by state-of-the-art analysis tools, static and real time data from multiple sources and on-site evaluation and advice, dealing with the structural problems of small business independent from the industry and the area of operation. In particular, we focus on the challenges for the: 1.Development of an innovative small business hybrid advisory web model based on big data analytics and including on line support by experts. 2.Realization of the above model as a web services that includes an “intelligent business API” on well-established open source software platforms. 3.Collection of static and real time business data from multiple sources including social media by creating a unified big data warehouse.
Prof. Vavalis has served as a faculty member at the University of Crete and at Purdue University and as a Senior Researcher at ICS of the Foundation for Research and Technology - Hellas (FORTH) and at ITI of the Centre of Research and Technology Hellas (CERTH). He authored more than 100 peer reviewed publications and supervised more than 80 students. His research has been supported by NSF, European Commission and the General Secretariat for Research and Technology – Greece. He currently focuses on Smart Energy Systems, Blockchain, Web Technologies, Information and Knowledge Management and Computational Science and Engineering.
Visual servoing is an important technique that uses visual information for the feedback control of robots. To implement a visual servo controller, an important step is to calibrate the intrinsic and extrinsic parameters of the camera. It is well known that the camera calibration is costly and tedious. The calibration accuracy of these parameters significantly affects the control errors. It is desirable to use uncalibrated visual signals directly in controller design. By directly incorporating visual feedback in the dynamic control loop, it is possible to enhance the system stability and the control performance. Dynamic visual servoing is to design the joint inputs of robot manipulators directly using visual feedback. In the design, the nonlinear dynamics of the robot manipulator is taken into account. In this talk, various visual servoing approaches will be presented to work in uncalibrated environments. These methods are also implemented in many robot systems such as manipulator, mobile robot, soft robot, quadrotor and so on.
Hesheng Wang received the Ph.D. degree in Automation & Computer-Aided Engineering from Chinese University of Hong Kong. Currently, he is a Professor of Department of Automation, Shanghai Jiao Tong University, China. He has published more than 100 papers in refereed journals and conferences. He is an associate editor of Robotics and Biomimetics, Assembly Automation, International Journal of Humanoid Robotics and IEEE Transactions on Robotics. He is the general chair of IEEE RCAR2016 and program chair of IEEE AIM2019. He was a recipient of The National Science Fund for Outstanding Young Scholars in 2017. He is a Senior Member of IEEE.