CEST Proceedings are published under the ISSN 2944-9820.
Multivariate Analysis of Large µ-FTIR Data Sets in Search of Microplastics
(Corresponding) Wander L., Vianello A., Vollertsen J., Braun U., Paul A.
Topic:
Microplastics in the marine environment
µ-FTIR spectroscopy is a widely used technique in microplastics research. It allows to simultaneously characterize the material of the small particles, fibers or fragments, and to specify their size distribution and shape. Modern detectors offer the possibility to perform two-dimensional imaging of...Read more
Meteorological Data Science: exploiting causality discovery in time-series for knowledge discovery and improved forecasting
Gkikas A., (Corresponding) Maragoudakis M.
Topic:
Enviornmental data analysis and modelling
Climate change and its impact on everyday life still remains one of the greatest challenge of our era. The complex nature of climate data addresses the use of data science techniques to provide predictive analytics to the task at hand. While most existing approaches exploit correlation between...Read more
Keywords:
Data Science, Causal Inference, Time-Series Analysis, Graph Analysis, Feature Selection
A Machine Learning Approach for the prediction of solid fuels consumption in Turkey
Celik N., (Corresponding) Konyalioglu A.
Topic:
Environmental data analysis and modelling
Solid fuels are very crucial energy sources as most of industries use them for obtaining heat, electricity and light. Furthermore, since solid fuels are scarce sources in Turkey, it is very important to forecast the consumption in order to effectively manage the energy policies and to conduct an...Read more
Keywords:
Solid Fuels, Environmental Data Analysis, Machine Learning
Optimization of wastewater treatment by integration of artificial intelligence techniques: recent progress and future perspectives
(Corresponding) Cairone S., Hasan S., Zarra T., Belgiorno V., Naddeo V.
Topic:
Wastewater treatment
Artificial intelligence (AI) is proving useful in optimizing the process efficiency in many sectors, including wastewater treatment. The complexity of wastewater characteristics and treatment technologies leads to uncertainties and variability in the efficiency of the processes in wastewater...Read more
