Subrata Mondal – författare

This book presents the latest technological advancements in the understanding and diagnosis of neurological disorders. The chapters provide the complexities of diagnosis, understanding pathogenesis, and unveiling the latest therapeutic strategies against neurodegenerative disorders. The book also explores the transformative role of optogenetics, nanoarchitectonics, machine learning, and artificial intelligence in neurodiagnosis. Metal organic frameworks are explored for their prospective applications in neuroscience. The book continues to unfold with a focus on robotic advancements in neurotherapeutics, offering comprehensive insights into the cutting edge of neurotherapeutic interventions. The complex interplay between neurodiagnostics and psychodiagnostics is explored in the context of substance use disorders. The book concludes by examining the potential of aquaporin as a therapeutic target in neurological disorders. As such, this book is an invaluable source for neuroscientists, neurologists, and computational biologists.

Key Features

This book presents the latest technological advancements in the understanding and diagnosis of neurological disorders. The chapters provide the complexities of diagnosis, understanding pathogenesis, and unveiling the latest therapeutic strategies against neurodegenerative disorders. The book also explores the transformative role of optogenetics, nanoarchitectonics, machine learning, and artificial intelligence in neurodiagnosis. Metal organic frameworks are explored for their prospective applications in neuroscience. The book continues to unfold with a focus on robotic advancements in neurotherapeutics, offering comprehensive insights into the cutting edge of neurotherapeutic interventions. The complex interplay between neurodiagnostics and psychodiagnostics is explored in the context of substance use disorders. The book concludes by examining the potential of aquaporin as a therapeutic target in neurological disorders. As such, this book is an invaluable source for neuroscientists, neurologists, and computational biologists.

Key Features

This book discusses various statistical models and their implications for developing landslide susceptibility and risk zonation maps. It also presents a range of statistical techniques, i.e. bivariate and multivariate statistical models and machine learning models, as well as multi-criteria evaluation, pseudo-quantitative and probabilistic approaches. As such, it provides methods and techniques for RS & GIS-based models in spatial distribution for all those engaged in the preparation and development of projects, research, training courses and postgraduate studies. Further, the book offers a valuable resource for students using RS & GIS techniques in their studies. 

This book focuses on the spatial distribution of landslide hazards of the Darjeeling Himalayas. Knowledge driven methods and statistical techniques such as frequency ratio model (FRM), information value model (IVM), logistic regression model (LRM), index overlay model (IOM), certainty factor model (CFM), analytical hierarchy process (AHP), artificial neural network model (ANN), and fuzzy logic have been adopted to identify landslide susceptibility. In addition, a comparison between various statistical models were made using success rate cure (SRC) and it was found that artificial neural network model (ANN), certainty factor model (CFM) and frequency ratio based fuzzy logic approach are the most reliable statistical techniques in the assessment and prediction of landslide susceptibility in the Darjeeling Himalayas. The study identified very high, high, moderate, low and very low landslide susceptibility locations to take site-specific management options as well as to ensure developmental activities in theDarjeeling Himalayas.

Particular attention is given to the assessment of various geomorphic, geotectonic and geohydrologic attributes that help to understand the role of different factors and corresponding classes in landslides, to apply different models, and to monitor and predict landslides. The use of various statistical and physical models to estimate landslide susceptibility is also discussed. The causes, mechanisms and types of landslides and their destructive character are elaborated in the book. Researchers interested in applying statistical tools for hazard zonation purposes will find the book appealing.