Java Virtual Machine

Covering the evolution of machine guns from the mid-19th century to the present, Machine Guns follows both the development of small arms technology and the impact of machine guns on ground combat, mil

Managing a project can be stressful enough without the added difficulty of coordinating project members working from different sites--or even continents! Managing Virtual Projects outlines techniques,

The goal of machine learning is to program computers to use example data or past experience to solve a given problem. Many successful applications of machine learning exist already, including systems

Virtual Humans are becoming more and more popular and used in many applications such as the entertainment industry (in both film and games) and medical applications. This comprehensive book covers all

The definitive machine design handbook for mechanical engineers, product designers, project engineers, design engineers, and manufacturing engineers covers every aspect of machine construction and ope

Offers a thorough look at peer review in virtual environments.

Concurrent and Distributed Computing in Java addresses fundamental concepts in concurrent computing with Java examples. The book consists of two parts. The first part deals with techniques for program

Machine Learning: Discriminative and Generative covers the main contemporary themes and tools in machine learning ranging from Bayesian probabilistic models to discriminative support-vector machines.

Going Virtual: Distributed Communities of Practice contributes to the understanding of how more subtle kinds of knowledge can be managed in a distributed international environment. It describes academ

Virtual schools are a result of widespread changes in knowledge about learning, in available technology and in society. Virtual schooling is growing in popularity and will continue to attract students

Fifty papers from the 2003 conference report on cutting-edge technology and techniques for assessing the performance of machine tools and measuring machines. Work on the enhancement of machine perform

Glencoe’s Introduction to Computer Science Using Java provides students with a highly visual way of learning Java programming. This colorful text provides the information needed for students enrolled

Written by three experienced educators and practitioners, Machine Tool Technology Basics is sure to be a useful tool for anyone needing to learn about today's machine tool trade. Logically organized i

Professionals in library science provide a framework for the creation and maintenance of virtual or digital academic research libraries, through a case presentation of how one academic library at the

Building Virtual Communities examines how learning and cognitive change are fostered by online communities. Contributors to this volume explore this question by drawing on their different theoretical backgrounds, methodologies, and personal experience with virtual communities. Each chapter discusses the different meanings of the terms community, learning, and change. Case studies are included for further clarification. Together, these chapters describe the building out of virtual communities in terms that are relevant to theorists, researchers, and practitioners. The chapters provide a basis for thinking about the dynamics of Internet community building. This includes consideration of the role of the self or individual as a participant in virtual community, and the design and refinement of technology as the conduit for extending and enhancing the possibilities of community building in cyberspace. Building Virtual Communities will interest educators, psychologists, sociologists, and res

The book is written for professionals, students, and laymen interested in virtual clothing. It contains annexes on clothing research projects and commercial clothing systems and comes with a CD-ROM pr

The definitive, official reference to the Java 1.1 class libraries for Java programmers. The extensive class and member descriptions contain details crucial for developing professional applets and app

Oge Mora's Saturday meets Carmela Full of Wishes in this touching and whimsical picture book about a mother and child's last trip to their local laundromat before moving away. Every Sunday after cereal, Sam and Mom walk to the laundromat, wash their clothes, and see their friends. But this Sunday is different. Today, they're doing laundry so they can pack clean clothes into boxes and move away. Sam doesn't want to leave their neighborhood and friends. Maybe if they hope with all their might, they can turn a washing machine into a wishing machine! Sam's imagination turns the mundane into a series of wonders as they cope with change and learn the true meaning of home.

Dancing to the Drum Machine is a never-before-attempted history of what is perhaps the most controversial musical instrument ever invented: the drum machine. Here, author Dan LeRoy reveals the untold story of how their mechanical pulse became the new heartbeat of popular music. The pristine snap of the LinnDrum. The bottom-heavy beats of the Roland 808. The groundbreaking samples of the E-MUSP-1200. All these machines―and their weirder, wilder-sounding cousins―changed composition, recording, and performance habits forever. Their distinctive sounds and styles helped create new genres of music, like hip hop and EDM. But they altered every musical style, from mainstream pop to heavy metal to jazz. Dan LeRoy traces the drum machine from its low-tech beginnings in the Fifties and Sixties to its evolution in the Seventies and its ubiquity in the Eighties, when seemingly overnight, it infiltrated every genre of music. Drum machines put some drummers out of work, while keeping others on

This self-contained introduction to machine learning, designed from the start with engineers in mind, will equip students with everything they need to start applying machine learning principles and algorithms to real-world engineering problems. With a consistent emphasis on the connections between estimation, detection, information theory, and optimization, it includes: an accessible overview of the relationships between machine learning and signal processing, providing a solid foundation for further study; clear explanations of the differences between state-of-the-art techniques and more classical methods, equipping students with all the understanding they need to make informed technique choices; demonstration of the links between information-theoretical concepts and their practical engineering relevance; reproducible examples using Matlab, enabling hands-on student experimentation. Assuming only a basic understanding of probability and linear algebra, and accompanied by lecture slide

Fundamental theory and practical algorithms of weakly supervised classification, emphasizing an approach based on empirical risk minimization.Standard machine learning techniques require large amounts of labeled data to work well. When we apply machine learning to problems in the physical world, however, it is extremely difficult to collect such quantities of labeled data. This book presents theory and algorithms for weakly supervised learning, a paradigm of machine learning from weakly labeled data. Emphasizing an approach based on empirical risk minimization and drawing on state-of-the-art research in weakly supervised learning, the book provides both the fundamentals of the field and the advanced mathematical theories underlying them. It can be used as a reference for practitioners and researchers and in the classroom.The book first mathematically formulates classification problems, defines common notations, and reviews various algorithms for supervised binary and multiclass classif

A veteran British journalist living in Hong Kong investigates the disappearance of a student protester in this atmospheric novel from the New York Times notable author of The Forgiven―soon to be a major motion picture.“There came a sound of rubber bullets being fired along Java Road and the sad crowing of sirens as if to herald a future even more unpleasant than the present.”After twenty years as a journalist in Hong Kong, ex-pat Englishman Adrian Gyle has very little to show for it. Evenings are whiled away with soup dumplings and tea at Fung Shing, the restaurant downstairs from his home on Java Road, that “most melancholy street in the city, the street where the dead congregated.” It is through these jaded eyes that Gyle watches the city around him--once overflowing with wine dinners and private members’ clubs--erupt in violence as pro-democracy demonstrations hit ever closer to home. But just as Gyle prepares to turn his back on Hong Kong, he finds one last intrigue: the alluring R

Since the mid-2010s, virtual reality (VR) technology has advanced rapidly. This book explores the many opportunities that VR can offer for humanities and social sciences researchers. It provides a user-friendly, non-technical methods guide to using ready-made VR content and 360° video as well as creating custom materials.

By 2025, an estimated 70 percent of the workforce will work remotely at least five days each month. In The Virtual Leader, Takako Hirata, an experienced leader of large international virtual teams, shares her proven methods for thriving in the remote workplace with the help of new leadership principles. Remote work is here to stay. As a result, remote leadership is now a core competency for most executives and managers. Leaders cannot simply transfer what they've been doing in the office to the remote context. While the goals remain the same--efficiency, engagement, community--the means of achieving those are very different. In The Virtual Leader, Takako Hirata shares the proven leadership methods she has developed over nearly a decade coordinating teams across the globe as the head of international business development at ROHTO Pharmaceutical. Hirata has seen firsthand that while the remote environment presents its own set of obstacles, the opportunities for innovation far outweigh th

Every day we interact with machine learning systems offering individualized predictions for our entertainment, social connections, purchases, or health. These involve several modalities of data, from sequences of clicks to text, images, and social interactions. This book introduces common principles and methods that underpin the design of personalized predictive models for a variety of settings and modalities. The book begins by revising 'traditional' machine learning models, focusing on adapting them to settings involving user data, then presents techniques based on advanced principles such as matrix factorization, deep learning, and generative modeling, and concludes with a detailed study of the consequences and risks of deploying personalized predictive systems. A series of case studies in domains ranging from e-commerce to health plus hands-on projects and code examples will give readers understanding and experience with large-scale real-world datasets and the ability to design mod

This lucid, accessible introduction to supervised machine learning presents core concepts in a focused and logical way that is easy for beginners to follow. The author assumes basic calculus, linear algebra, probability and statistics but no prior exposure to machine learning. Coverage includes widely used traditional methods such as SVMs, boosted trees, HMMs, and LDAs, plus popular deep learning methods such as convolution neural nets, attention, transformers, and GANs. Organized in a coherent presentation framework that emphasizes the big picture, the text introduces each method clearly and concisely “from scratch” based on the fundamentals. All methods and algorithms are described by a clean and consistent style, with a minimum of unnecessary detail. Numerous case studies and concrete examples demonstrate how the methods can be applied in a variety of contexts.

This modern and self-contained book offers a clear and accessible introduction to the important topic of machine learning with neural networks. In addition to describing the mathematical principles of the topic, and its historical evolution, strong connections are drawn with underlying methods from statistical physics and current applications within science and engineering. Closely based around a well-established undergraduate course, this pedagogical text provides a solid understanding of the key aspects of modern machine learning with artificial neural networks, for students in physics, mathematics, and engineering. Numerous exercises expand and reinforce key concepts within the book and allow students to hone their programming skills. Frequent references to current research develop a detailed perspective on the state-of-the-art in machine learning research.

Explore the technology that is changing our world!Imagine a machine that can learn from experience and teach itself new things - that's AI in action! Trace the development of intelligent machines fr

Pondering the town he had invented in his novels, Anthony Trollope had 'so realised the place, and the people, and the facts' of Barset that 'the pavement of the city ways are familiar to my footsteps'. After his novels end, William Thackeray wonders where his characters now live, and misses their conversation. How can we understand the novel as a form of artificial reality? Timothy Gao proposes a history of virtual realities, stemming from the imaginary worlds created by novelists like Trollope, Thackeray, Charlotte Bronte, and Charles Dickens. Departing from established historical or didactic understandings of Victorian fiction, Virtual Play and the Victorian Novel recovers the period's fascination with imagined places, people, and facts. This text provides a short history of virtual experiences in literature, four studies of major novelists, and an innovative approach for scholars and students to interpret realist fictions and fictional realities from before the digital age. This ti

The recent pandemic has clarified the overwhelming connection between the workplace and technology. With thousands of employees suddenly forced to work at home, a large segment of the workforce quickly received crash courses in videoconferencing and other technologies, and society as a whole took a step back to redefine what employment actually means. The virtual workplace is the blending of brick-and-mortar physical places of business with the advanced technologies that now make it possible for workers to perform their duties outside of the office. Trying to regulate in this area requires the application of decades old employment laws to a context never even contemplated by the legislatures that wrote those rules. This book explores the emerging issues of virtual work―defining employment, litigating claims, aggregating cases, unionizing workers, and preventing harassment―and provides clarity to these areas, synthesizing the current case law, statutory rules, and academic literature to

The world of machine learning is changing all the time. It is so amazing the idea that we are able to take a computer and let it learn as it goes. Without having to write out all of the codes that we need for every situation out there or every input that the user may pick, we are able to write out codes in machine learning, even with Python, in order to let the computer or device learn and make decisions on its own.This guidebook is going to take a closer look at how Python machine learning is able to work, as well as how you can use some of the tools and techniques that come with this process for your own needs. When you are interested in learning more about what machine learning is all about, as well as how you can use a part of the coding from Python inside of this process, then this guidebook is the tool for you Some of the topics that we will explore when we go through this guidebook will include: Understanding some of the basics of machine learning;Some of the different parts tha

With a machine learning approach and less focus on linguistic details, this gentle introduction to natural language processing develops fundamental mathematical and deep learning models for NLP under a unified framework. NLP problems are systematically organised by their machine learning nature, including classification, sequence labelling, and sequence-to-sequence problems. Topics covered include statistical machine learning and deep learning models, text classification and structured prediction models, generative and discriminative models, supervised and unsupervised learning with latent variables, neural networks, and transition-based methods. Rich connections are drawn between concepts throughout the book, equipping students with the tools needed to establish a deep understanding of NLP solutions, adapt existing models, and confidently develop innovative models of their own. Featuring a host of examples, intuition, and end of chapter exercises, plus sample code available as an onli

Immerse yourself in 45 spectacularly imagined virtual cities, from Arkham City to Whiterun, in this beautifully illustrated unofficial guide.Spanning decades of digital history, this is the ultimate t

The second edition of a comprehensive introduction to machine learning approaches used in predictive data analytics, covering both theory and practice.Machine learning is often used to build predictiv

A jaw-dropping exploration of everything that goes wrong when we build AI systems and the movement to fix them.Today’s “machine-learning” systems, trained by data, are so effective that we’ve invited

A virtualist is a doctor who specializes in virtual medicine. She uses tools like VR headsets, spatial acoustics, haptic feedback, and even olfactory mimicry to induce reactions in patients' bodies th

Present book covers new paradigms in Blockchain, Big Data and Machine Learning concepts including applications and case studies. It explains dead fusion in realizing the privacy and security of

This book will help readers understand fundamental and advanced statistical models and deep learning models for robust speaker recognition and domain adaptation. This useful toolkit enables readers to apply machine learning techniques to address practical issues, such as robustness under adverse acoustic environments and domain mismatch, when deploying speaker recognition systems. Presenting state-of-the-art machine learning techniques for speaker recognition and featuring a range of probabilistic models, learning algorithms, case studies, and new trends and directions for speaker recognition based on modern machine learning and deep learning, this is the perfect resource for graduates, researchers, practitioners and engineers in electrical engineering, computer science and applied mathematics.

Make, mend, and customize your own wardrobe with this highly photographic beginner's guide to machine sewing.Discover how to read a pattern, use a sewing machine, and sew basic stitches, seams, and he

With this groundbreaking text, discover how wireless artificial intelligence (AI) can be used to determine position at centimeter level, sense motion and vital signs, and identify events and people. Using a highly innovative approach that employs existing wireless equipment and signal processing techniques to turn multipaths into virtual antennas, combined with the physical principle of time reversal and machine learning, it covers fundamental theory, extensive experimental results, and real practical use cases developed for products and applications. Topics explored include indoor positioning and tracking, wireless sensing and analytics, wireless power transfer and energy efficiency, 5G and next-generation communications, and the connection of large numbers of heterogeneous IoT devices of various bandwidths and capabilities. Demo videos accompanying the book online enhance understanding of these topics. Providing a unified framework for wireless AI, this is an excellent text for gradu