This book presents results of the combined use of microwave remote sensing, optical tools, and ecoinformatics methods under solution-applied tasks at both regional and global scales. Ecoinformatics methods are used to assess links between global climate change and the level of ocean pollution, with specific focus on the Arctic Ocean, the Sea of Okhotsk, and the South-China Sea. The theoretical and applied aspects of instrumental tools are considered in this book as a basis for the monitoring of water quality in various watersheds, with particular attention to microwave remote sensing monitoring data to determine the ecotoxicological status of hydro-ecosystems affected by climate change. The book develops new information technologies that provide solutions for hydrochemical tasks using algorithms and models based on computer technologies for big data processing. This will help to synthesize effective computer-based systems for the solution of problems arising due to anthropogenic impacts on hydrological processes and objects at various spatial scales. This book is intended for specialists in the fields of environmental monitoring, climate change, human-nature interactions, and geopolitics. The book will be useful for undergraduate and postgraduate students studying these fields of science as well.

Methodologies of Pattern Recognition is a collection of papers that deals with the two approaches to pattern recognition (geometrical and structural), the Robbins-Monro procedures, and the implications of interactive graphic computers for pattern recognition methodology. Some papers describe non-supervised learning in statistical pattern recognition, parallel computation in pattern recognition, and statistical analysis as a tool to make patterns emerge from data. One paper points out the importance of cluster processing in visual perception in which proximate points of similar brightness values form clusters. At higher levels of mental activity humans are efficient in clumping complex items into clusters. Another paper suggests a recognition method which combines versatility and an efficient noise-proofness in dealing with the two main problems in the field of recognition. These difficulties are the presence of a large variety of observed signals and the presence of interference. One paper reports on a possible feature selection for pattern recognition systems employing the minimization of population entropy. Electronic engineers, physicists, physiologists, psychologists, logicians, mathematicians, and philosophers will find great rewards in reading the above collection.

Contains Proceedings of the Canadian Mathematical Congress, 6th- 1963-