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Ramesh S. V. Teegavarapu
Imputation Methods for Missing Hydrometeorological Data Estimation

Missing data is a ubiquitous problem that plagues many hydrometeorological datasets. Objective and robust spatial and temporal imputation methods are needed to estimate missing data and create error-free,…

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National Academies of Sciences Engineering and Medicine, Division on Engineering and Physical Sciences, National Materials and Manufacturing Board, Board on Mathematical Sciences and Analytics
Statistical and Data-Driven Methods for Additive Manufacturing Qualification

Additive manufacturing (AM), the process in which a three-dimensional (3D) object is built by adding subsequent layers of materials, enables novel material compositions and shapes, often without the need …

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Machine Learning Methods for Multi-Omics Data Integration

The advancement of biomedical engineering has enabled the generation of multi-omics data by developing high-throughput technologies, such as next-generation sequencing, mass spectrometry, and microarrays.…

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Nature-Inspired Methods for Smart Healthcare Systems and Medical Data

This book aims to gather high-quality research papers on developing theories, frameworks, architectures, and algorithms for solving complex challenges in smart healthcare applications for real industry us…

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Recent Developments in Model-Based and Data-Driven Methods for Advanced Control and Diagnosis

The book consists of recent works on several axes either with a more theoretical nature or with a focus on applications, which will span a variety of up-to-date topics in the field of systems and control.…

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Faris
Change Point Detection: A Powerful Method for Genetic Data Analysis

The human genome holds a treasure trove of information, but how do we find the hidden patterns within this vast dataset? "Change Point Detection: A Powerful Method for Genetic Data Analysis" unl…

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Yannick Lingelbach
Application of Data Mining and Machine Learning Methods to Industrial Heat Treatment Processes for Hardness Prediction

This work presents a data mining framework applied to industrial heattreatment (bainitization and case hardening) aiming to optimize processes and reduce costs. The framework analyses factors such as mate…

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Richard Huntsinger
Business Analytics

Business analytics is about leveraging data analysis and analytical modeling methods to achieve business objectives. Suitable for senior and graduate students in business or data science, this innovative …

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Michael Hagmann, Stefan Riezler
Validity, Reliability, and Significance

This book introduces empirical methods for machine learning with a special focus on applications in natural language processing (NLP) and data science. The authors present problems of validity, reliabilit…

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