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This book provides a comprehensive introduction to the design and analysis of Learning Classifier Systems (LCS) from the perspective of machine learning. LCS are a family of methods for handling unsupervised learning, supervised learning and sequential decision tasks by decomposing larger problem spaces into easy-to-handle subproblems. Contrary to commonly approaching their design and analysis from the viewpoint of evolutionary computation, this book instead promotes a probabilistic model-based approach, based on their defining question “What is an LCS supposed to learn?”.

This book offers an up-to-date overview of the latest scientific findings in regional climate research on the Baltic Sea Basin, including climate changes in the recent past, climate projections up until 2100 using the most sophisticated regional climate models available, and an assessment of climate change impacts on terrestrial, freshwater and marine ecosystems. The authors demonstrate that the regional climate has already started to change, and will continue to do so – projections show that the region will become considerably warmer and wetter in some parts, but dryer in others. Terrestrial and aquatic ecosystems have already shown adjustments to increased temperatures, and are expected to face further changes in the near future.

The book is organized in four major areas. The first unit focuses on the terrorism informatics and data mining. The second unit discusses the intelligence and crime analysis. The third unit covers access control, infrastructure protection, and privacy. The fourth unit presents surveillance and emergency response.

Readers will find the book valuable and useful in their study or work, especially the ISI community. The researchers and practitioners in this community will continue to grow and share research findings to contribute to national safety around the world.

Major improvements in instrumentation and specimen preparation have brought SEM to the fore as a biological imaging technique. In FESEM, a field-emission cathode placed in the electron gun of a scanning electron microscope provides narrower probing beams and high electron energy. The result is improved spatial resolution and minimized sample charging and damage. Images produced are less destroyed and have a spatial resolution down to 1.5 nm, three to six times better than conventional SEM.

Although this imaging technique has undergone tremendous developments, it is still poorly represented in the literature, limited to journal articles and chapter s in books. This comprehensive volume is dedicated to the theory and practical applications of FESEM in biological samples. It provides a comprehensive explanation of instrumentation, applications, and protocols, and is intended to teach the reader how to operate such microscopes to obtain the best quality images.