Data Science for Wind Energy provides an in-depth discussion on how data science methods can improve decision making for wind energy applications, near-ground wind field analysis and forecast, turbine power curve fitting and performance analysis, turbine reliability assessment, and maintenance optimization for wind turbines and wind farms. A broad set of data science methods covered, including time series models, spatio-temporal analysis, kernel regression, decision trees, kNN, splines, Bayesian inference, and importance sampling. More importantly, the data science methods are described in the context of wind energy applications, with specific wind energy examples and case studies. Please also visit the author’s book site at https://aml.engr.tamu.edu/book-dswe. Features Provides an integral treatment of data science methods and wind energy applications Includes specific demonstration of particular data science methods and their use in the context of addressing wind energy needs Presents real data, case studies and computer codes from wind energy research and industrial practice Covers material based on the author's ten plus years of academic research and insights
This book combines two distinctive topics: data science/image analysis and materials science. The purpose of this book is to show what type of nano material problems can be better solved by which set of data science methods. The majority of material science research is thus far carried out by domain-specific experts in material engineering, chemistry/chemical engineering, and mechanical & aerospace engineering. The book could benefit materials scientists and manufacturing engineers who were not exposed to systematic data science training while in schools, or data scientists in computer science or statistics disciplines who want to work on material image problems or contribute to materials discovery and optimization. This book provides in-depth discussions of how data science and operations research methods can help and improve nano image analysis, automating the otherwise manual and time-consuming operations for material engineering and enhancing decision making for nano material exploration. A broad set of data science methods are covered, including the representations of images, shape analysis, image pattern analysis, and analysis of streaming images, change points detection, graphical methods, and real-time dynamic modeling and object tracking. The data science methods are described in the context of nano image applications, with specific material science case studies.
At ten years old, the mother who was carrying her little brother was strangled to death right in front of her eyes. Three years later, the Han WanRong who raised her was beaten into the cold palace and burned to death. The princess of the cold palace was designed to be close to her, betraying her former lover. He was the Left Xian Prince of the Huns, but he pushed her into the arms of the Chanyu. When I first met Chanyu Tangli Gu, I had been accused of being unfaithful, and I abandoned him like a pair of old shoes. Being a widow once again, how could he endure being sent to the Chanyu's son's red silk cloth? Ninja, just for revenge, sent troops to Da Kang, to see his former lover again, but they were enemies on both sides. He had killed all of his enemies, yet now, he suddenly looked back. Where was his beauty? Where did she go?
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After leaving Special Forces, Xiao Ke, who was born with the ability to predict the future, had been living a leisurely lifestyle. A kind help from the bar instead brought him some trouble, and as the trouble grew, Xiao Ke's peaceful life was immediately broken. As more and more people entered his life, his responsibilities became greater and greater, he was entrusted by the country to search for treasures of Hua Xia, and he also had to fight everywhere because of the kidnapping of his woman. From London, to Paris, to Istanbul, all sorts of footprints were left behind.
This book constitutes the refereed proceedings of the fourth Asian Semantic Web Conference, ASWC 2009, held in Shanghai, China, in December 2009. The 35 revised full papers presented were carefully reviewed and selected from 63 submissions. These submissions cover a broad range of topics including, query languages and optimization, rule and logics, scalable reasoning, semantic content generation, database and semantics, semantic web services, eSemantics (e.g., e-Business, e-Science, e-Learning, e-Culture, e-Health), social web and semantics, semantic graph mining, security for semantic web, ontology modeling, ontology management, to name a few.
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