Technical University of Crete, Greece
- October 27, 2017
- 2:00 PM
- ECS 241
Yannis A. Phillis received his diploma in electrical and mechanical engineering from the National Technical University of Athens, Greece, in 1973 and the M.S., Engineer Degree, and Ph.D. degrees from the University of California at Los Angeles (UCLA) in control systems in 1978, 1979, and 1980 respectively. From 1980 to 1986, he was with Boston University, Boston, MA. Since 1986, he has been with the School of Production Engineering and Management, Technical University of Crete, Chania, Greece where he was Rector for 12 years and currently is professor and director of the CAM Laboratory. In 1992 and between 2005 and 2007 he was visiting professor at UCLA’s Chemical Engineering Department. In 2008 he was Onassis Foundation Senior Visiting Fellow in the US. In 2013-2014 he was Prometeo Senior Research Fellow in Riobamba, Ecuador. His research interests are in stochastic control, manufacturing, sustainability and climate change. Dr. Phillis is member of the editorial board of several technical journals. He is the recipient of numerous honors among which Harry Kurnitz Literary Award at UCLA, 1978 and 1979; Professor of the Year Award at Boston University, 1986; Award by the Academy of Athens for his environmental activities, 2007; Fellow of the Venizelos Research Institute in Greece, 2006; Awards by the Municipalities of Chania and Assini, Greece in 2005 and 2008 respectively for his service to society, science, and letters; Lifetime Achievement Award at the World Automation Conference 2010, Kobe, Japan; and Academic Alumni Professional Achievement Award, UCLA, 2013. He has published over 120 scientific papers and four technical books. He is an award winning writer in Greece and the US. He is a Fellow of AAAS; a Senior Member of IEEE; and Member of Sigma Xi; Poets and Writers, USA; and P.E.N. Club.
Anthropogenic climate change is causing many dangerous phenomena such as hot spells, floods, droughts, hurricanes, acidification of oceans, sea level rise, reappearance of old diseases, etc. These phenomena have direct negative effects on national security. In this talk, climate security is defined and mathematically assessed using a hierarchy of indicators that are combined using statistical methods and multistage fuzzy reasoning. At the bottom level of this hierarchy are 38 indicators and at the highest level is an overall measure of national security. The indicators are organized in seven fundamental dimensions of climate security: Water, Food, Energy, Conflict, Health, and Economy. These dimensions represent basic resources necessary for human well-being and sustainable development that are highly vulnerable to climate change. Each dimension comprises three components: Exposure, Sensitivity, and Adaptation. The inputs of the model are time series of each indicator for a given country. Each time series is filtered using exponential smoothing to generate a single value for the corresponding indicator which is then normalized on [0, 1] by interpolation between insecure and secure values or intervals of their physical domain. Normalized indicators are fuzzified and passed through a multistage inference process that generates a security index for each country. A sensitivity analysis exposes those indicators that have the highest potential for security improvement for each country. The signatory countries of the Paris Agreement are ranked according to their climate security index and their most sensitive indicators are pinpointed. In all, about 220,000 data points were used. Several European countries rank at the top while developing countries rank at the bottom, as expected. The most sensitive indicators for developed countries are aging population and renewable energy use, whereas for developing countries they are GDP, corruption, poverty, and political rights.