Neil Bose has been VP Research at Memorial University since November 2017. Prior to this, he served as principal of the Australian Maritime College (AMC), the national institute for maritime education, training, research and consultancy at the University of Tasmania. Dr. Bose was also a professor of maritime hydrodynamics at the AMC. From 2009 to 2011, he was director of the AMC’s National Centre for Maritime Engineering and Hydrodynamics. He joined the college in May 2007 as the manager of the Australian Maritime Hydrodynamics Research Centre. Before his move to Tasmania, Dr. Bose was a long-standing and respected member of Memorial University’s research community. He came to Memorial in May 1987 as an assistant professor in the naval architectural engineering program. In his time at Memorial, Dr. Bose served as director of the Ocean Engineering Research Centre, chair of ocean and naval architectural engineering program and, in 2003, was named a Tier 1 Canada Research Chair in Offshore and Underwater Vehicles Design in the Faculty of Engineering and Applied Science. Dr. Bose received an honorary degree from the Nikola Vaptsarov Naval Academy, the oldest technical educational institution in Bulgaria. Dr. Bose obtained his B.Sc. in Naval Architecture and Ocean Engineering from the University of Glasgow in 1978 and his PhD, also from Glasgow, in 1982. Dr. Bose was appointed to the NRC Council in June 2018.
Abstract: Marine pollution is a global problem that has severe adverse environmental and socio-economic impacts. Oil spills are one form of pollution; further chemical run-off and plastics in the ocean are others. Climate change and severe degradation of our ecosystem are some of the outcomes from this pollution. Increased risks, the Deepwater Horizon blowout in the Gulf of Mexico, the MV Wakashio in Mauritius, spills off Newfoundland in 2018 and 2019, have broadened the gap between the potential need for oil spill countermeasures and current response capabilities. Information about oil and other pollution in the water column is critical to understanding of subsurface plume behavior which in turn enables timely and effective mitigation. Following the Gulf of Mexico blowout, autonomous underwater vehicles (AUVs) were successfully used to characterize submerged oil that was trapped at a depth of approximately 1200 m and provided a comprehensive analysis of the impacted areas. In our research AUV capabilities are being advanced specifically for the understanding of marine pollution and response. An innovative adaptive mission planning approach for discontinuous patchy plumes made up of non-soluble oil droplet clouds or other potential items of interest such as micro-plastics, is being researched to improve performance of AUVs and their onboard sensors in delineating subsurface plumes. Using adaptive sampling, the AUV autonomously modifies its mission path in real-time based on features of the plumes detected by on-board sensors. Hence the AUV path is concentrated within the areas of interest and in information-rich areas identified by the sensors, optimizing the AUV response. The target community of our research includes regulators, marine pollution agencies, oil spill response organizations, the offshore petroleum industry, AUV manufacturers, operators and oceanographers.
Fabio Tosti (IEEE M’17–SM’19) received the M.Sc. and Eng. degrees (cum laude) in Infrastructure and Transportation Engineering from Roma Tre University, Rome, Italy, in 2010, and the Ph.D. degree in Civil Engineering with European Doctorate Label (excellent rating) from Roma Tre University, in 2014. A registered Chartered Engineer, he is a Professor of Civil Engineering at the School of Computing and Engineering, University of West London (UWL), London, U.K., and the Deputy Head of “The Faringdon Centre for Non-Destructive Testing and Research” at UWL. His research interests include the development of new algorithms, methodologies, and models for geoscience applications and the nondestructive and satellite remote sensing assessment, repair, and maintenance of civil infrastructure. He has authored/co-authored over 200 research publication records in international journals, conferences, and books and delivered numerous keynote and invited lectures. Prof. Tosti was a recipient of the ECSs Award by the European Geosciences Union (EGU) in 2017 and several Best Paper Awards at International Conferences, including the 2021 IEEE Asia–Pacific Conference on Geoscience, Electronics and Remote Sensing Technology (AGERS2021) and the IEEE 2020 43rd International Conference on Telecommunications and Signal Processing (TSP2020). He was the General Co-Chair of the 2nd International Workshop on Signal Processing Techniques for Ground Penetrating Radar Applications in 2020 (TSP—IEEE Conf. Record 49548), and he served as the main organiser, scientific committee member and chair of technical sessions in 50+ international conferences and workshops. He served as the managing guest editor for various journals. He is an Associate Editor of the International Journal of Pavement Engineering (IJPE), Geoscientific Instrumentation, Methods and Data Systems (GI), and the Journal of Railway Engineering, and a member of the Editorial Board of Remote Sensing (MDPI) and Frontiers in Remote Sensing..
Abstract: Effective health monitoring of railway sub-structural layers (ballast and sub-ballast) is crucial in preserving the quality of the track-bed and ensuring the safety of operations. When measuring the long-term integrity and functionality of the railway track, detection of early decay in track-bed foundation materials is vital. Increasing traffic flow on rail network systems demands more time-efficient and vigorous techniques and methodologies in terms of safety and maintenance. In this context, the ground-penetrating radar (GPR) non-destructive technology has been successfully applied for decades, reaching very high standards of data quality and accuracy. This keynote aims to review significant GPR research development for stand-alone and integrated application in railway infrastructure monitoring. Furthermore, main challenges and future perspectives are presented.
Dr. Yungcheol Byun is a full professor at the Computer Engineering Department (CE) at Jeju National University (http://www.jejunu.ac.kr). His research interests include the areas of Pattern Recognition & Image Processing, Artificial Intelligence & Machine Learning, Pattern-based Security, Home Network and Ubiquitous Computing, u-Healthcare, and RFID & IoT Middleware System. He directs the Machine Laboratory at the CE department. Recently, he studied at University of Florida as a visiting professor from 2012 to 2014. He is currently serving as a director of Information Science Technology Institute, and other academic societies. Outside of his research activities, Dr. Byun has been hosting international conferences including CNSI (Computer, Network, Systems, and Industrial Engineering), ICESI (Electric Vehicle, Smart Grid, and Information Technology), and serving as a conference and workshop chair, program chair, and session chair in various kinds of international conferences and workshops. Dr. Byun was born in Jeju, Korea, and received his Ph.D. and MS from Yonsei University (http://www.yonsei.ac.kr) in 1995 and 2001 respectively, and BS from Jeju National University in 1993. Before joining Jeju National University, he worked as a special lecturer in SAMSUNG Electronics (http://www.samsung.com) in 2000 and 2001. From 2001 to 2003, he was a senior researcher of Electronics and Telecommunications Research Institute (ETRI, https://etri.re.kr/eng/main/main.etri). He was promoted to join Jeju National University as an assistant professor in 2003.
Abstract: Despite the advancement within the last decades in the field of smart grids, energy consumption forecasting utilizing the metrological features is still challenging. This paper proposes a genetic algorithm-based adaptive error curve learning ensemble (GA-ECLE) model. The proposed technique copes with the stochastic variations of improving energy consumption forecasting using a machine learning-based ensembled approach. A modified ensemble model based on a utilizing error of model as a feature is used to improve the forecast accuracy. This approach combines three models, namely Cat- Boost (CB), Gradient Boost (GB), and Multilayer Perceptron (MLP). The ensembled CB-GB-MLP model’s inner mechanism consists of generating meta-data from Gradient Boosting and CatBoostmodels to compute the final predictions using the Multilayer Perceptron network. A genetic algorithm is used to obtain the optimal features to be used for the model. To prove the proposed model’s effectiveness, we have used a four-phase technique using Jeju island’s real energy consumption data. In the first phase, we have obtained the results by applying the CB-GB-MLP model. In the second phase, we have utilized a GA-ensembled model with optimal features. The third phase is for the comparison of the energy forecasting result with the proposed ECL-based model. The fourth stage is the final stage, where we have applied the GA-ECLE model. We obtained a mean absolute error of 3.05, and a root mean square error of 5.05. Extensive experimental results are provided, demonstrating the superiority of the proposed GA-ECLE model over traditional ensemble models.
Shigeo Akashi was certified as a Ph.D. holder by Tokyo Institute of Technology in 1987 and he is now a professor at Tokyo University of Science. He was the chair professor at the Department of Information Sciences at this university from 2015 through 2016. He was also an visiting researcher at Rome II University in 1994 and was an associate professor at Southern Illinois University in 2000. As for the academic and educational activities, he has been a member of Experts Committee Leading Scientific Education for Japanese Senior High Schools authorized by Ministry of Education, Culture, Sports, Science and Technology attached to Japanese Government since 2016. He is interested in the interdisciplinary research area ranging from applied mathematics through information sciences. As for the research activity on applied mathematics, in 2003, he solved the analytic function version of Hilbert's 13th problem, which was known as an open problem derived from the 13th problems belonging to the 23 problems which was introduced by Professor David Hilbert in 1900 and would play important roles in directing mathematics in the future. Since his research work on Hilbert's 13th problem proved to be related to the theory of data compression, he was nominated as an invited speaker in Asian Mathematical Conference 2013, which is the second largest international conference on mathematics and was held in Korea in 2013. Moreover, he was a member of Scientific Committee for Asian Conference on Nonlinear Analysis and Optimization which was officially approved as a satellite international conference of International Congress of Mathematicians 2014. As for the research activity on information science, he has been being certified as Distinguished Cisco Certified Active Instructor Approved by Cisco Networking Academy since 2012, which is administrated by Cisco Systems. Moreover, he was awarded 2018 APSCIT Fellowship by Asia Pacific Society for Computing and Information Technology. His joint research work with RKC Instruments Co. Ltd., namely the largest company in all Japanese companies producing temperature-measuring instruments, which is named as "An algorithm for discriminating the inside of a closed curve from the outside" was accepted as Patent ID.4760768 by Japan Patent Office attached to the Ministry of Economy, Trade and Industry attached to Japanese Government in 2011.
Abstract: The man-in-the-middle attack is dened as a cyber attack that an attacker can insert himself into the network routes connecting between two authenticagted network users for the purpose of collecting data commuting between them, and so far, various kinds of multiple cases which the cyber attacker can carry out as the following: Case 1. DNS spoofing. Case 2. IP spoofing. Case 3. Wi-Fi eavesdropping. Case 4. HTTPS spoofing. Case 5. SSL hijacking. Case 6. Email hijacking. Case 7. Session Hijacking. Case 8. Man in the Browser. The above table reporting examples belonging to man-in-the-middle attacks is constructed based on the Application Layer of the OSI Reference Model. In other words, this table shows that man-in-the-middle attacks can change themselves in accordance with a change of application softwares. Actually, the way of the attacker's intercepting a large number of packets commuting between the authenticated client and the authenticated server is commonly used among the attacks stated as above. In this talk, we discuss the man-in-the-middle attacks from the point of view of the Network Layer of the OSI Reference Model. Concretely speaking, we show that some of the famouse network skills, which have already been used over the Internet, can bring about another case of the man-in-the-middle attacks, and that a malicious simultaneous combined use of the dynamic routing based on EIGRP is not compatible with the static routing.
Ali Kashif Bashir is Associate Professor at the Department of Computing and Mathematics, Manchester Metropolitan University, United Kingdom. He is also with Visual Research Intelligent Center, University of Electronics Science and Technology of China (UESTC) as an Honorary Professor and Chief Adviser; with University of Science and Technology, Islamabad (NUST) as an Adjunct Professor, and with University of Guelph, Canada as Special Graduate Faculty. He is a senior member of IEEE, member of IEEE Industrial Electronic Society, member of ACM, and Distinguished Speaker of ACM. He received his Ph.D. in computer science and engineering from Korea University, South Korea. He has authored over 200 research articles; and received over 3 Million USD funding as PI and Co-PI from research bodies of South Korea, Japan, EU, UK and Middle East. His research interests include internet of things, wireless networks, distributed systems, network/cyber security, network function virtualization, machine learning, etc. He is serving as the Editor-in-chief of the IEEE FUTURE DIRECTIONS NEWSLETTER. He is also serving as area editor of KSII Transactions on Internet and Information Systems; associate editor of IEEE Internet of Things Magazine, IEEE Access, Peer J Computer Science, IET Quantum Computing, and Journal of Plant Disease and Protection. He is leading many conferences as a chair (program, publicity, and track) and had organized workshops in flagship conferences like IEEE Infocom, IEEE Globecom, IEEE Mobicom, etc.