Download or read book Time Anomaly written by Lindsey Sparks and published by Rubus Press. This book was released on 2021-06-22 with total page 427 pages. Available in PDF, EPUB and Kindle. Book excerpt: The sequel to Echo in Time. For most people, time is a river, flowing in only one direction. Alexandra Larson isn't most people... PRESENT DAY...When Lex notices an inky presence darkening Marcus's eyes, she discovers he's no longer what he seemed. Almost too late, she realizes that the man she has entrusted with both her heart and her life is now her greatest threat. Seeking safety, Lex is forced to draw on her god-like powers and flee...to the ancient past. OLD KINGDOM EGYPT...Hiding in plain sight, Lex takes on the identity of the goddess Hathor as she struggles to blend in thousands of years before her own time. But the safety she sought proves elusive. If the body-snatching spirit of a dead god doesn't kill her, her rapidly worsening bonding withdrawals will. Can she come to an arrangement with Heru, Marcus's ancient counterpart, in time to save her life and the future? Or will the secrets she's hiding push him away for good? The past clashes with the present in this paranormal saga of ancient prophecies and warring gods. If you like Egyptian mythology, steamy romance, time-bending mysteries, and complex characters, then you'll love this sprawling time travel adventure. MORE BOOKS IN THE ECHO WORLD: ECHO TRILOGY Echo in Time Resonance (an Echo Trilogy novella) Time Anomaly Dissonance (an Echo Trilogy novella) Ricochet Through Time KAT DUBOIS CHRONICLES Ink Witch Outcast Underground Soul Eater Judgement Afterlife *** KEYWORDS: Egyptian Mythology, Paranormal Romance, Time Travel Romance, Egyptian Time Travel, Egyptian gods and goddessess, paranormal time travel, mythological paranormal, mythological pnr, ancient time travel, first in series, first in pnr series, completed series, completed paranormal series, egyptian gods fantasy, egyptian gods paranormal romance, egyptian mythology series, paranormal romance ancient mystery, time travel ancient mystery, time travel romance ancient mystery

Download or read book Echo Queen written by Lindsey Fairleigh and published by . This book was released on 2014-09-25 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: For most people, time is a river, flowing in only one direction...but Alexandra Larson isn't most people. PRESENT DAY...When Lex notices an inky presence darkening Marcus's eyes, she discovers he's no longer what he seemed. Almost too late, she realizes that the man she has entrusted with both her heart and her life is now her greatest threat. Seeking safety, Lex is forced to draw on her god-like powers and flee...to the ancient past. OLD KINGDOM EGYPT...Hiding in plain sight, Lex takes on the identity of the goddess Hathor as she struggles to blend in thousands of years before her own time. But the safety she sought proves elusive. If the body-snatching spirit of a dead god doesn't kill her, her rapidly worsening bonding withdrawals will. Can she come to an arrangement with Heru, Marcus's ancient counterpart, in time to save her life and the future? Or will the secrets she's hiding push him away for good? ***CONTAINS ADULT CONTENT***

Download or read book Anomaly Detection written by and published by BoD – Books on Demand. This book was released on 2024-01-17 with total page 170 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book The Anomaly written by Hervé Le Tellier and published by Other Press, LLC. This book was released on 2021-11-23 with total page 401 pages. Available in PDF, EPUB and Kindle. Book excerpt: A New York Times bestseller and a "Best Thriller of the Year" Winner of the Goncourt Prize and now an international phenomenon, this dizzying, whip-smart novel blends crime, fantasy, sci-fi, and thriller as it plumbs the mysteries surrounding a Paris-New York flight. Who would we be if we had made different choices? Told that secret, left that relationship, written that book? We all wonder—the passengers of Air France 006 will find out. In their own way, they were all living double lives when they boarded the plane: Blake, a respectable family man who works as a contract killer. Slimboy, a Nigerian pop star who uses his womanizing image to hide that he’s gay. Joanna, a Black American lawyer pressured to play the good old boys’ game to succeed with her Big Pharma client. Victor Miesel, a critically acclaimed yet largely obscure writer suddenly on the precipice of global fame. About to start their descent to JFK, they hit a shockingly violent patch of turbulence, emerging on the other side to a reality both perfectly familiar and utterly strange. As it charts the fallout of this logic-defying event, The Anomaly takes us on a journey from Lagos and Mumbai to the White House and a top-secret hangar. In Hervé Le Tellier’s most ambitious work yet, high literature follows the lead of a bingeable Netflix series, drawing on the best of genre fiction from “chick lit” to mystery, while also playfully critiquing their hallmarks. An ingenious, timely variation on the doppelgänger theme, it taps into the parts of ourselves that elude us most.

Download or read book Anomaly Detection Principles and Algorithms written by Kishan G. Mehrotra and published by Springer. This book was released on 2017-11-18 with total page 229 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a readable and elegant presentation of the principles of anomaly detection,providing an easy introduction for newcomers to the field. A large number of algorithms are succinctly described, along with a presentation of their strengths and weaknesses. The authors also cover algorithms that address different kinds of problems of interest with single and multiple time series data and multi-dimensional data. New ensemble anomaly detection algorithms are described, utilizing the benefits provided by diverse algorithms, each of which work well on some kinds of data. With advancements in technology and the extensive use of the internet as a medium for communications and commerce, there has been a tremendous increase in the threats faced by individuals and organizations from attackers and criminal entities. Variations in the observable behaviors of individuals (from others and from their own past behaviors) have been found to be useful in predicting potential problems of various kinds. Hence computer scientists and statisticians have been conducting research on automatically identifying anomalies in large datasets. This book will primarily target practitioners and researchers who are newcomers to the area of modern anomaly detection techniques. Advanced-level students in computer science will also find this book helpful with their studies.

Download or read book Time Anomaly written by Lindsey Fairleigh and published by . This book was released on 2021-02-10 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Network Traffic Anomaly Detection and Prevention written by Monowar H. Bhuyan and published by Springer. This book was released on 2017-09-03 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: This indispensable text/reference presents a comprehensive overview on the detection and prevention of anomalies in computer network traffic, from coverage of the fundamental theoretical concepts to in-depth analysis of systems and methods. Readers will benefit from invaluable practical guidance on how to design an intrusion detection technique and incorporate it into a system, as well as on how to analyze and correlate alerts without prior information. Topics and features: introduces the essentials of traffic management in high speed networks, detailing types of anomalies, network vulnerabilities, and a taxonomy of network attacks; describes a systematic approach to generating large network intrusion datasets, and reviews existing synthetic, benchmark, and real-life datasets; provides a detailed study of network anomaly detection techniques and systems under six different categories: statistical, classification, knowledge-base, cluster and outlier detection, soft computing, and combination learners; examines alert management and anomaly prevention techniques, including alert preprocessing, alert correlation, and alert post-processing; presents a hands-on approach to developing network traffic monitoring and analysis tools, together with a survey of existing tools; discusses various evaluation criteria and metrics, covering issues of accuracy, performance, completeness, timeliness, reliability, and quality; reviews open issues and challenges in network traffic anomaly detection and prevention. This informative work is ideal for graduate and advanced undergraduate students interested in network security and privacy, intrusion detection systems, and data mining in security. Researchers and practitioners specializing in network security will also find the book to be a useful reference.

Download or read book Practical Machine Learning A New Look at Anomaly Detection written by Ted Dunning and published by "O'Reilly Media, Inc.". This book was released on 2014-07-21 with total page 65 pages. Available in PDF, EPUB and Kindle. Book excerpt: Finding Data Anomalies You Didn't Know to Look For Anomaly detection is the detective work of machine learning: finding the unusual, catching the fraud, discovering strange activity in large and complex datasets. But, unlike Sherlock Holmes, you may not know what the puzzle is, much less what “suspects” you’re looking for. This O’Reilly report uses practical examples to explain how the underlying concepts of anomaly detection work. From banking security to natural sciences, medicine, and marketing, anomaly detection has many useful applications in this age of big data. And the search for anomalies will intensify once the Internet of Things spawns even more new types of data. The concepts described in this report will help you tackle anomaly detection in your own project. Use probabilistic models to predict what’s normal and contrast that to what you observe Set an adaptive threshold to determine which data falls outside of the normal range, using the t-digest algorithm Establish normal fluctuations in complex systems and signals (such as an EKG) with a more adaptive probablistic model Use historical data to discover anomalies in sporadic event streams, such as web traffic Learn how to use deviations in expected behavior to trigger fraud alerts

Download or read book Network Anomaly Detection written by Dhruba Kumar Bhattacharyya and published by CRC Press. This book was released on 2013-06-18 with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the rapid rise in the ubiquity and sophistication of Internet technology and the accompanying growth in the number of network attacks, network intrusion detection has become increasingly important. Anomaly-based network intrusion detection refers to finding exceptional or nonconforming patterns in network traffic data compared to normal behavi

Download or read book An Updated Global Grid Point Surface Air Temperature Anomaly Data Set written by and published by . This book was released on 1991 with total page 430 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Advanced Anomaly Detection Technologies and Applications in Energy Systems written by Tinghui Ouyang and published by Frontiers Media SA. This book was released on 2022-10-14 with total page 628 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Deep Learning and XAI Techniques for Anomaly Detection written by Cher Simon and published by Packt Publishing Ltd. This book was released on 2023-01-31 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: Create interpretable AI models for transparent and explainable anomaly detection with this hands-on guide Purchase of the print or Kindle book includes a free PDF eBook Key FeaturesBuild auditable XAI models for replicability and regulatory complianceDerive critical insights from transparent anomaly detection modelsStrike the right balance between model accuracy and interpretabilityBook Description Despite promising advances, the opaque nature of deep learning models makes it difficult to interpret them, which is a drawback in terms of their practical deployment and regulatory compliance. Deep Learning and XAI Techniques for Anomaly Detection shows you state-of-the-art methods that'll help you to understand and address these challenges. By leveraging the Explainable AI (XAI) and deep learning techniques described in this book, you'll discover how to successfully extract business-critical insights while ensuring fair and ethical analysis. This practical guide will provide you with tools and best practices to achieve transparency and interpretability with deep learning models, ultimately establishing trust in your anomaly detection applications. Throughout the chapters, you'll get equipped with XAI and anomaly detection knowledge that'll enable you to embark on a series of real-world projects. Whether you are building computer vision, natural language processing, or time series models, you'll learn how to quantify and assess their explainability. By the end of this deep learning book, you'll be able to build a variety of deep learning XAI models and perform validation to assess their explainability. What you will learnExplore deep learning frameworks for anomaly detectionMitigate bias to ensure unbiased and ethical analysisIncrease your privacy and regulatory compliance awarenessBuild deep learning anomaly detectors in several domainsCompare intrinsic and post hoc explainability methodsExamine backpropagation and perturbation methodsConduct model-agnostic and model-specific explainability techniquesEvaluate the explainability of your deep learning modelsWho this book is for This book is for anyone who aspires to explore explainable deep learning anomaly detection, tenured data scientists or ML practitioners looking for Explainable AI (XAI) best practices, or business leaders looking to make decisions on trade-off between performance and interpretability of anomaly detection applications. A basic understanding of deep learning and anomaly detection–related topics using Python is recommended to get the most out of this book.

Download or read book Beginning Anomaly Detection Using Python Based Deep Learning written by Sridhar Alla and published by Apress. This book was released on 2019-10-10 with total page 427 pages. Available in PDF, EPUB and Kindle. Book excerpt: Utilize this easy-to-follow beginner's guide to understand how deep learning can be applied to the task of anomaly detection. Using Keras and PyTorch in Python, the book focuses on how various deep learning models can be applied to semi-supervised and unsupervised anomaly detection tasks. This book begins with an explanation of what anomaly detection is, what it is used for, and its importance. After covering statistical and traditional machine learning methods for anomaly detection using Scikit-Learn in Python, the book then provides an introduction to deep learning with details on how to build and train a deep learning model in both Keras and PyTorch before shifting the focus to applications of the following deep learning models to anomaly detection: various types of Autoencoders, Restricted Boltzmann Machines, RNNs & LSTMs, and Temporal Convolutional Networks. The book explores unsupervised and semi-supervised anomaly detection along with the basics of time series-based anomaly detection. By the end of the book you will have a thorough understanding of the basic task of anomaly detection as well as an assortment of methods to approach anomaly detection, ranging from traditional methods to deep learning. Additionally, you are introduced to Scikit-Learn and are able to create deep learning models in Keras and PyTorch. What You Will LearnUnderstand what anomaly detection is and why it is important in today's world Become familiar with statistical and traditional machine learning approaches to anomaly detection using Scikit-Learn Know the basics of deep learning in Python using Keras and PyTorch Be aware of basic data science concepts for measuring a model's performance: understand what AUC is, what precision and recall mean, and more Apply deep learning to semi-supervised and unsupervised anomaly detection Who This Book Is For Data scientists and machine learning engineers interested in learning the basics of deep learning applications in anomaly detection

Download or read book Anomaly Detection and Complex Event Processing Over IoT Data Streams written by Patrick Schneider and published by Academic Press. This book was released on 2022-01-07 with total page 408 pages. Available in PDF, EPUB and Kindle. Book excerpt: Anomaly Detection and Complex Event Processing over IoT Data Streams: With Application to eHealth and Patient Data Monitoring presents advanced processing techniques for IoT data streams and the anomaly detection algorithms over them. The book brings new advances and generalized techniques for processing IoT data streams, semantic data enrichment with contextual information at Edge, Fog and Cloud as well as complex event processing in IoT applications. The book comprises fundamental models, concepts and algorithms, architectures and technological solutions as well as their application to eHealth. Case studies, such as the bio-metric signals stream processing are presented –the massive amount of raw ECG signals from the sensors are processed dynamically across the data pipeline and classified with modern machine learning approaches including the Hierarchical Temporal Memory and Deep Learning algorithms. The book discusses adaptive solutions to IoT stream processing that can be extended to different use cases from different fields of eHealth, to enable a complex analysis of patient data in a historical, predictive and even prescriptive application scenarios. The book ends with a discussion on ethics, emerging research trends, issues and challenges of IoT data stream processing. Provides the state-of-the-art in IoT Data Stream Processing, Semantic Data Enrichment, Reasoning and Knowledge Covers extraction (Anomaly Detection) Illustrates new, scalable and reliable processing techniques based on IoT stream technologies Offers applications to new, real-time anomaly detection scenarios in the health domain

Download or read book Anomaly Detection and Health Analysis Techniques for Core Router Systems written by Shi Jin and published by Springer Nature. This book was released on 2019-12-19 with total page 155 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book tackles important problems of anomaly detection and health status analysis in complex core router systems, integral to today’s Internet Protocol (IP) networks. The techniques described provide the first comprehensive set of data-driven resiliency solutions for core router systems. The authors present an anomaly detector for core router systems using correlation-based time series analysis, which monitors a set of features of a complex core router system. They also describe the design of a changepoint-based anomaly detector such that anomaly detection can be adaptive to changes in the statistical features of data streams. The presentation also includes a symbol-based health status analyzer that first encodes, as a symbol sequence, the long-term complex time series collected from a number of core routers, and then utilizes the symbol sequence for health analysis. Finally, the authors describe an iterative, self-learning procedure for assessing the health status. Enables Accurate Anomaly Detection Using Correlation-Based Time-Series Analysis; Presents the design of a changepoint-based anomaly detector; Includes Hierarchical Symbol-based Health-Status Analysis; Describes an iterative, self-learning procedure for assessing the health status.

Download or read book Path Integrals and Quantum Anomalies written by Kazuo Fujikawa and published by OUP Oxford. This book was released on 2004-04-29 with total page 297 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Feynman path integrals are becoming increasingly important in the applications of quantum mechanics and field theory. The path integral formulation of quantum anomalies, i.e. the quantum breaking of certain symmetries, can now cover all the known quantum anomalies in a coherent manner. In this book the authors provide an introduction to the path integral method in quantum field theory and its applications to the analyses of quantum anomalies. No previous knowledge of field theory beyond advanced undergraduate quantum mechanics is assumed. The book provides the first coherent introductory treatment of the path integral formulation of chiral and Weyl anomalies, with applications to gauge theory in two and four dimensions, conformal field theory and string theory. Explicit and elementary path integral calculations of most of the quantum anomalies covered are given. The conceptual basis of the path integral bosonization in two-dimensional theory, which may have applications to condensed matter theory, for example, is clarified. The book also covers the recent interesting developments in the treatment of fermions and chiral anomalies in lattice gauge theory.

Download or read book The TensorFlow Workshop written by Matthew Moocarme and published by Packt Publishing Ltd. This book was released on 2021-12-15 with total page 601 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get started with TensorFlow fundamentals to build and train deep learning models with real-world data, practical exercises, and challenging activities Key FeaturesUnderstand the fundamentals of tensors, neural networks, and deep learningDiscover how to implement and fine-tune deep learning models for real-world datasetsBuild your experience and confidence with hands-on exercises and activitiesBook Description Getting to grips with tensors, deep learning, and neural networks can be intimidating and confusing for anyone, no matter their experience level. The breadth of information out there, often written at a very high level and aimed at advanced practitioners, can make getting started even more challenging. If this sounds familiar to you, The TensorFlow Workshop is here to help. Combining clear explanations, realistic examples, and plenty of hands-on practice, it'll quickly get you up and running. You'll start off with the basics – learning how to load data into TensorFlow, perform tensor operations, and utilize common optimizers and activation functions. As you progress, you'll experiment with different TensorFlow development tools, including TensorBoard, TensorFlow Hub, and Google Colab, before moving on to solve regression and classification problems with sequential models. Building on this solid foundation, you'll learn how to tune models and work with different types of neural network, getting hands-on with real-world deep learning applications such as text encoding, temperature forecasting, image augmentation, and audio processing. By the end of this deep learning book, you'll have the skills, knowledge, and confidence to tackle your own ambitious deep learning projects with TensorFlow. What you will learnGet to grips with TensorFlow's mathematical operationsPre-process a wide variety of tabular, sequential, and image dataUnderstand the purpose and usage of different deep learning layersPerform hyperparameter-tuning to prevent overfitting of training dataUse pre-trained models to speed up the development of learning modelsGenerate new data based on existing patterns using generative modelsWho this book is for This TensorFlow book is for anyone who wants to develop their understanding of deep learning and get started building neural networks with TensorFlow. Basic knowledge of Python programming and its libraries, as well as a general understanding of the fundamentals of data science and machine learning, will help you grasp the topics covered in this book more easily.