Prof. Dr. Cengiz TAPLAMACIOĞLU, Gazi University, Turkey
Prof. Dr. M.Cengiz TAPLAMACIOGLU graduated from Gazi University, Faculty of Engineering, Department of Electrical and Electronics Engineering (Ankara, Turkey). He received the degrees of M.Sc. in Industrial Engineering from Gazi University and in Electrical and Electronics Engineering from Middle East Technical University (METU- Ankara, Turkey). He completed his Ph.D. in Electrical, Electronics and Systems Engineering from University of Wales (Cardiff, UK). He has been a full time Professor of the Electrical and Electronics Engineering since 2000. His research interests and subjects are power systems, high voltage engineering, corona discharge and modeling, electrical field computation, measurement and modeling techniques, optical hv measurement techniques, power systems optimization and control, power systems and smart grid applications, microgrid systems, renewable energy systems, protection systems , lighting technics and applications.
Speech Title: Revıew of Turkish Electric Energy System and Requirements of HVDC Systems for Connecting Neighboring Grids
Abstract: In this study, as a one of the largest electricity networks in Europe, past and recent situation of Turkish transmission network, length of transmission lines, installed capacity, annual electricity generation, annual electricity consumption, amount of electricity import and electricity export are given. Cooperation in the field of electricity, the agreement of permanent synchronization was signed on 15 April 2015 between ENTSO-E and Turkish Electricity Transmission Company (TEIAS). According to this agreement, Turkey has committed to remain the network parameters like frequency deviations and voltage changes within the standards specified. On the other hand, Turkey pursues electrical energy trade with neighbouring countries; Iran, Georgia and Nakhchivan(Azerbaijan).
The network operation which is performed in accordance with the quality standards of electrical parameters is regulated according to own electricity grid legislation of each country. Since each country has special conditions for the quality of the electricity grid, the network parameters and quality of countries vary according to each other as well. In parallel, it is not desirable that the electrical disturbances affect another side in the electricity trade between countries. For this reason, HVDC systems used to provide asynchronous parallel connection without AC interaction for international electric trade at present. In addition, the HVDC systems allow asynchronous interconnection between adjacent networks having different frequency level and prevent breakdowns between the networks due to fault isolation to the neighbouring network. Also, it is possible to eliminate electromechanical oscillations and increase grid stability by controlling power flow quickly and precisely using HVDC systems.
Assoc. Prof. Dr. Huseyin Seker The University of Northumbria at Newcastle, UK
Dr Huseyin Seker is a multi-disciplinary researcher and data scientist with a particular interest in big data mining, machine learning, and bio-medical and industrial applications. He has published over 100 peer-reviewed papers, led a number of projects, delivered keynote and invited talks at several events and organised a number of conferences and special sessions. He is currently a Reader in the Department of Computer and Information Sciences of Northumbria University in Newcastle-upon-Tyne (UK). He is also the Director of Enterprise and Engagement, and leads Bio-Health Informatics Research Team and Big Data Analytics Lab within the department. In addition to his academic duties, he is an Advisory Board Member of the North East Satellite Applications Centre of Excellence, Steering Group Member of Digital Catapult North East and Tees Valley, and a member of the CyberNorth Initiative in the UK. Further information about his projects and publications can be found at http://computing.unn.ac.uk/staff/yqqd6/home.htm
Title: The role of data and artificial intelligence in the development of next generation of services
Abstract: Data is today’s most valuable asset for businesses. In order to gain value out of the data, we need to turn the data into actionable insights, drive meaningful and cost-saving knowledge from it, and develop and deploy profitable data-driven intelligent tools. This can be achieved through advanced data analytics, artificial intelligence (AI) and machine learning as well as image, video, speech and natural language processing.
Due to the technological advances, data is becoming more available and goes beyond volume, variety, and velocity alone. In addition, industry is now becoming more data-driven and automated. Therefore, advanced data analytics methods and data-driven business modelling are now more important than ever to address the industry’s complex business challenges.
The UK government has started investing more in the collaboration between enterprise organisations and universities in order to improve the business’ (data-driven) value and gain a better place in the world of data and AI economy.
Our research team in Smart Data Analytics Lab is supporting the government's initiatives and working with industry to successfully automate business processes by developing and deploying advanced data analytics and AI-driven methods. Through a number of examples of successful academic and industrial projects that we work on within our research group, this talk will cover information about (1) the concept of data analytics and what it means for academic research and business, (2) ways of identifying business need and data capability, and (3) data-driven strategy that an industry needs to implement to develop next generation of its services.
Dr. S. A. Binselam, Senior Research Scientist at FM Global, Center for Property Risk Solutions
S. A. Binselam was born in 1970, in Çorum, Turkey. He finished his undergraduate studies at Gazi University, Ankara, Turkey, May 1992. He earned his first Master of Science degree in systems science from Louisiana State University (LSU) in 1998, and second Master of Science degree in Geography, Majoring in Mapping Science in 2001. He worked as a research scientist at LSU Hurricane Center from 2002 to 2010. In 2013, received his Ph.D. in Engineering Sciences. He is currently working as a Senior Research Scientist at FM Global, Center for Property Risk Solutions.
His research interests include Geographic Information Systems (GIS), geodatabases design and integration, costal storm surge, storm surge modeling, Database Management Systems (DBMS), data visualization, data warehousing, distributed systems, machine learning and high performance computing.
Title: Use of Machine Learning Techniques in Large Spatio-Temporal Datasets
Abstract: Massive volumes of spatio-temporal datasets have been collected daily with various data acquisition systems ranging from satellites to internet-based crowed sourcing portals. These datasets are growing rapidly. As the volume and complexity of spatio-temporal datasets increases, the effective extraction of useful information becomes challenging with traditional data analysis methods. To address these challenges, machine learning methods have implemented with promising results in Geographic Information Systems (GIS).
We briefly review the literature for promising spatio-temporal data mining techniques; in classification, prediction, and cluster analysis. The focus will be in point pattern analysis, prediction in space-time data techniques used in GIS applications.
Dr. Hüseyin Üvet, Yildiz Technical University, Turkey
Dr. Uvet holds a Bachelor of Science degree in Computer Engineering from Kultur University which he acquired in 2004. Upon completing his undergraduate studies he started his master’s degree at Osaka University, Japan in System Engineering. Following his master’s studies on “Compact Vision System Design for Single Cell Analysis and Manipulation” at the Robotic Technologies Lab, he started his doctorate on “Micro/Nano Robotics” at the very same Robotic Technologies Lab of Osaka University, Japan. In 2010, he continued his researches in Nagoya University, Micro-Nano System Engineering Department as a post-doctoral fellow. During this period, he worked on robotic micromanipulation, microassembly, MEMS (sensors and actuators), mechanical manipulation of biological cells and tissue
At the start of his academic studies as an undergraduate student, Dr. Uvet proved to be an ambitious and hardworking potential young scientist by having been deemed to full scholarship by Kultur University after becoming a top % 1 entrant to the university’s Computer Engineering Department. His academic quest for excellence was awarded full scholarship by the “Japan Student Services Organization (JASSO) and The Japan Ministry of Education (MEXT)” agency to cover his master’s and doctorate studies between 2005 and 2010. Starting October 17, 2011, Dr. Uvet, has been appointed as an Assistant Professor at the Department of Mechatronics Engineering at Yildiz Technical University, Istanbul, Turkey. After starting his career in Turkey, He has managed and co-managed multiple medium to large-scale state assessment R&D projects, valued at over $6.000.000. He was director of Science and Technology Research and Application Center in Yildiz Technical University between 2014 to 2016. Since 2016, Dr. Uvet has taken part in several senior consulting positions in worldwide companies as Deutsche Post DHL Group R&D Center and Turkish Airlines.
Dr. Uvet is an independent and prolific researcher whose research career and research potential has been approved by independent and objective pioneers of his research topic. Some of his international and noteworthy academic awards are:
Speech Title: Precise Manipulation of Untethered Microrobots