This book reviews current research on the important processes involved in neurodegenerative diseases (e.g. Alzheimer's disease) and the peptides and proteins involved in the amyloidogenic processes. It covers the design and developments of anti-amyloid inhibitors, and gives readers a fundamental understanding of the underlying oligomerization and aggregation processes of these diseases from both computational and experimental points of view.
This textbook helps future data analysts comprehend aggregation function theory and methods in an accessible way, focusing on a fundamental understanding of the data and summarization tools. Offering a broad overview of recent trends in aggregation research, it complements any study in statistical or machine learning techniques. Readers will learn how to program key functions in R without obtaining an extensive programming background.
Sections of the textbook cover background information and context, aggregating data with averaging functions, power means, and weighted averages including the Borda count. It explains how to transform data using normalization or scaling and standardization, as well as log, polynomial, and rank transforms. The section on averaging with interaction introduces OWS functions and the Choquet integral, simple functions that allow the handling of non-independent inputs. The final chapters examine software analysis with an emphasis on parameter identification rather than technical aspects.
This textbook is designed for students studying computer science or business who are interested in tools for summarizing and interpreting data, without requiring a strong mathematical background. It is also suitable for those working on sophisticated data science techniques who seek a better conception of fundamental data aggregation. Solutions to the practice questions are included in the textbook.
Описание: This textbook helps future data analysts comprehend aggregation function theory and methods in an accessible way, focusing on a fundamental understanding of the data and summarization tools.
Автор: Yi Wang, Qixin Chen, Chongqing Kang Название: Smart Meter Data Analytics ISBN: 9811526230 ISBN-13(EAN): 9789811526237 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Since data management is the basis of further smart meter data analytics and its applications, three issues on data management, i.e., data compression, anomaly detection, and data generation, are subsequently studied.
Автор: Kevin Berk Название: Modeling and Forecasting Electricity Demand ISBN: 3658086688 ISBN-13(EAN): 9783658086688 Издательство: Springer Рейтинг: Цена: 11753.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The master thesis of Kevin Berk develops a stochastic model for the electricity demand of small and medium-sized companies that is flexible enough so that it can be used for various business sectors. As a consequence, forecasting electricity load and its risk is now an integral component of the risk management for all market participants.
Описание: Examines the issues involved in the field of neuromarketing, including models, technologies, and methodology. Highlighting the intricacies of neuroscience, biometrics, multimedia technology, marketing strategy, and big data management, this book is an ideal resource for researchers, neuroscientists, marketers, suppliers, customers, and investors.
Описание: The book collects contributions from experts worldwide addressing recent scholarship in social network analysis such as influence spread, link prediction, dynamic network biclustering, and delurking.
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