Next Generation Knowledge Machines

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Next Generation Knowledge Machines

Author : Syed V. Ahamed
Publisher : Elsevier
Page : 337 pages
File Size : 50,9 Mb
Release : 2013-09-13
Category : Computers
ISBN : 9780124166691

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Next Generation Knowledge Machines by Syed V. Ahamed Pdf

This book delivers the scientific and mathematical basis to treat and process knowledge as a quantifiable and dimensioned entity. It provides the units and measures for the value of information contained in a "body of knowledge" that can be measured, processed, enhanced, communicated and preserved. It provides a basis to evaluate the quantity of knowledge acquired by students at various levels and in different universities. The effect of time on the dynamics and flow of knowledge is tied to Internet knowledge banks and provides the basis for designing and building the next generation of novel machine to appear in society. This book ties the basic needs of all human beings to the modern machines that resolve such need based on Internet knowledge banks (KBs) distributed throughout nations and societies. The features of the Intelligent Internet are fully exploited to make a new generation of students and knowledge workers use the knowledge resources elegantly and optimally. It deals with topics and insight into the design and architecture of next-generation computing systems that deal with human and social problems. Processor and Internet technologies that have already revolutionized human lives form the subject matter and the focal point of this book. Information and knowledge on the Internet delivered by next-generation mobile networks form the technical core presented. Human thought processes and adjustments follow the solutions offered by machines. Extends the established practices and designs documented in computer systems to encompass the evolving knowledge processing field Provides an academic and industrial viewpoint of the concurrent dynamic changes in computer and communication industries Presents information for all perspectives, from managers, scientists and researchers Basic concepts can be applied to other disciplines and situations

Intelligent Networks

Author : Syed V. Ahamed
Publisher : Elsevier
Page : 343 pages
File Size : 45,5 Mb
Release : 2013-07-03
Category : Computers
ISBN : 9780124166707

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Intelligent Networks by Syed V. Ahamed Pdf

This textbook offers an insightful study of the intelligent Internet-driven revolutionary and fundamental forces at work in society. Readers will have access to tools and techniques to mentor and monitor these forces rather than be driven by changes in Internet technology and flow of money. These submerged social and human forces form a powerful synergistic foursome web of (a) processor technology, (b) evolving wireless networks of the next generation, (c) the intelligent Internet, and (d) the motivation that drives individuals and corporations. In unison, the technological forces can tear human lives apart for the passive or provide a cohesive set of opportunities for the knowledgeable to lead and reap the rewards in the evolved knowledge society. The book also provides in-depth coverage of the functions embedded in modern processors and intelligent communication networks. It focuses on the convergence of the design of modern processor technologies with the switching and routing methodologies of global intelligent networks. Most of the concepts that are generic to the design of terra-flop parallel processors and the terra-bit fiber-optic networks are presented. This book also highlights recent developments in computer and processor technologies into the microscopic and macroscopic medical functions in hospitals and medical centers. Examination of the latest technologies and innovations presented from academic and industrial perspectives of the concurrent dynamic changes in computer and communication industries An up-to-date and coherent perspective of the developments in the wireless and fiber optic network technologies based on the experience and developments in the older copper, cable and hybrid fiber-coaxial communication systems Provides a set of novel concepts and methodologies for the innovators in industry

Next-Generation Machine Learning with Spark

Author : Butch Quinto
Publisher : Apress
Page : 367 pages
File Size : 42,5 Mb
Release : 2020-02-22
Category : Computers
ISBN : 9781484256695

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Next-Generation Machine Learning with Spark by Butch Quinto Pdf

Access real-world documentation and examples for the Spark platform for building large-scale, enterprise-grade machine learning applications. The past decade has seen an astonishing series of advances in machine learning. These breakthroughs are disrupting our everyday life and making an impact across every industry. Next-Generation Machine Learning with Spark provides a gentle introduction to Spark and Spark MLlib and advances to more powerful, third-party machine learning algorithms and libraries beyond what is available in the standard Spark MLlib library. By the end of this book, you will be able to apply your knowledge to real-world use cases through dozens of practical examples and insightful explanations. What You Will Learn Be introduced to machine learning, Spark, and Spark MLlib 2.4.xAchieve lightning-fast gradient boosting on Spark with the XGBoost4J-Spark and LightGBM librariesDetect anomalies with the Isolation Forest algorithm for SparkUse the Spark NLP and Stanford CoreNLP libraries that support multiple languagesOptimize your ML workload with the Alluxio in-memory data accelerator for SparkUse GraphX and GraphFrames for Graph AnalysisPerform image recognition using convolutional neural networksUtilize the Keras framework and distributed deep learning libraries with Spark Who This Book Is For Data scientists and machine learning engineers who want to take their knowledge to the next level and use Spark and more powerful, next-generation algorithms and libraries beyond what is available in the standard Spark MLlib library; also serves as a primer for aspiring data scientists and engineers who need an introduction to machine learning, Spark, and Spark MLlib.

Knowledge Machines

Author : Eric T. Meyer,Ralph Schroeder
Publisher : MIT Press
Page : 285 pages
File Size : 45,7 Mb
Release : 2023-05-09
Category : Language Arts & Disciplines
ISBN : 9780262547857

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Knowledge Machines by Eric T. Meyer,Ralph Schroeder Pdf

An examination of the ways that digital and networked technologies have fundamentally changed research practices in disciplines from astronomy to literary analysis. In Knowledge Machines, Eric Meyer and Ralph Schroeder argue that digital technologies have fundamentally changed research practices in the sciences, social sciences, and humanities. Meyer and Schroeder show that digital tools and data, used collectively and in distributed mode—which they term e-research—have transformed not just the consumption of knowledge but also the production of knowledge. Digital technologies for research are reshaping how knowledge advances in disciplines that range from physics to literary analysis. Meyer and Schroeder map the rise of digital research and offer case studies from many fields, including biomedicine, social science uses of the Web, astronomy, and large-scale textual analysis in the humanities. They consider such topics as the challenges of sharing research data and of big data approaches, disciplinary differences and new forms of interdisciplinary collaboration, the shifting boundaries between researchers and their publics, and the ways that digital tools promote openness in science. This book considers the transformations of research from a number of perspectives, drawing especially on the sociology of science and technology and social informatics. It shows that the use of digital tools and data is not just a technical issue; it affects research practices, collaboration models, publishing choices, and even the kinds of research and research questions scholars choose to pursue. Knowledge Machines examines the nature and implications of these transformations for scholarly research.

Evolution of Knowledge Science

Author : Syed V. Ahamed
Publisher : Morgan Kaufmann
Page : 578 pages
File Size : 42,8 Mb
Release : 2016-10-25
Category : Computers
ISBN : 9780128093559

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Evolution of Knowledge Science by Syed V. Ahamed Pdf

Evolution of Knowledge Science: Myth to Medicine: Intelligent Internet-Based Humanist Machines explains how to design and build the next generation of intelligent machines that solve social and environmental problems in a systematic, coherent, and optimal fashion. The book brings together principles from computer and communication sciences, electrical engineering, mathematics, physics, social sciences, and more to describe computer systems that deal with knowledge, its representation, and how to deal with knowledge centric objects. Readers will learn new tools and techniques to measure, enhance, and optimize artificial intelligence strategies for efficiently searching through vast knowledge bases, as well as how to ensure the security of information in open, easily accessible, and fast digital networks. Author Syed Ahamed joins the basic concepts from various disciplines to describe a robust and coherent knowledge sciences discipline that provides readers with tools, units, and measures to evaluate the flow of knowledge during course work or their research. He offers a unique academic and industrial perspective of the concurrent dynamic changes in computer and communication industries based upon his research. The author has experience both in industry and in teaching graduate level telecommunications and network architecture courses, particularly those dealing with applications of networks in education. Presents a current perspective of developments in central, display, signal, and graphics processor-units as they apply to designing knowledge systems Offers ideas and methodologies for systematically extending data and object processing in computing into other disciplines such as economics, mathematics, and management Provides best practices and designs for engineers alongside case studies that illustrate practical implementation ideas across multiple domains

Next Generation Business Intelligence

Author : Sonar, Rajendra M.
Publisher : Vikas Publishing House
Page : 128 pages
File Size : 44,5 Mb
Release : 2024-06-14
Category : Electronic
ISBN : 9788125942566

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Next Generation Business Intelligence by Sonar, Rajendra M. Pdf

Business Intelligence (BI) has been successfully deployed by modern businesses to serve their customers and stakeholders. However, organizations increasingly look at BI to be all pervasive and realize its higher level of potential, instead of following it conventionally. The book covers the techniques, technologies and frameworks that can be used to build next generation BI.

Intelligent Internet Knowledge Networks

Author : Syed V. Ahamed
Publisher : John Wiley & Sons
Page : 520 pages
File Size : 49,8 Mb
Release : 2006-11-17
Category : Computers
ISBN : 9780470055984

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Intelligent Internet Knowledge Networks by Syed V. Ahamed Pdf

Introducing the basic concepts in total program control of the intelligent agents and machines, Intelligent Internet Knowledge Networks explores the design and architecture of information systems that include and emphasize the interactive role of modern computer/communication systems and human beings. Here, you’ll discover specific network configurations that sense environments, presented through case studies of IT platforms, electrical governments, medical networks, and educational networks.

Computing

Author : Peter Salenieks
Publisher : Unknown
Page : 240 pages
File Size : 40,6 Mb
Release : 1988
Category : Computers
ISBN : CORNELL:31924052707647

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Computing by Peter Salenieks Pdf

Next Generation Roadmapping

Author : Tugrul U. Daim,Robert Phaal,Dirk Meissner,Clive Kerr
Publisher : Springer Nature
Page : 375 pages
File Size : 45,8 Mb
Release : 2023-11-10
Category : Business & Economics
ISBN : 9783031385759

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Next Generation Roadmapping by Tugrul U. Daim,Robert Phaal,Dirk Meissner,Clive Kerr Pdf

Roadmapping is a structured visual approach for supporting strategic technology and innovation management, providing strategic navigational support (hence the “roadmap” metaphor) for technologists, designers, entrepreneurs, programme managers, executives, policy makers, other stakeholders involved in the formulation and implementation of strategy. This book brings together the latest developments in roadmapping, covering a range of practical issues and conceptual aspects. First, the book delves into the critical topic of strategic alignment within organizations, encompassing the interdependencies and synchronization of horizontal and vertical systems, connecting innovation priorities to strategic objectives, and the integration of key performance indicators. Then, the book concentrates on practical techniques and tools for roadmapping, including a template-based approach for technology venture funding. Social and digital aspects of roadmapping are explored, including workshop methods, considering how quantitative (analysis) and qualitative (expert) knowledge can be combined for improved strategic planning. Finally, a series of new case studies focusing on energy systems in Sub-Saharan Africa and Turkey illustrate the practical application of technology roadmapping and also provide useful insights. Roadmapping continues to evolve, as it is adapted to apply to new domains and strategic challenges, propagates to new sectors, and as new digital technologies such as AI emerge that radically affect strategy and innovation processes. The need for structured and engaging approaches such as roadmapping for navigating towards the future is essential.

Fundamentals of Deep Learning

Author : Nikhil Buduma,Nicholas Locascio
Publisher : "O'Reilly Media, Inc."
Page : 365 pages
File Size : 48,7 Mb
Release : 2017-05-25
Category : Computers
ISBN : 9781491925560

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Fundamentals of Deep Learning by Nikhil Buduma,Nicholas Locascio Pdf

With the reinvigoration of neural networks in the 2000s, deep learning has become an extremely active area of research, one that’s paving the way for modern machine learning. In this practical book, author Nikhil Buduma provides examples and clear explanations to guide you through major concepts of this complicated field. Companies such as Google, Microsoft, and Facebook are actively growing in-house deep-learning teams. For the rest of us, however, deep learning is still a pretty complex and difficult subject to grasp. If you’re familiar with Python, and have a background in calculus, along with a basic understanding of machine learning, this book will get you started. Examine the foundations of machine learning and neural networks Learn how to train feed-forward neural networks Use TensorFlow to implement your first neural network Manage problems that arise as you begin to make networks deeper Build neural networks that analyze complex images Perform effective dimensionality reduction using autoencoders Dive deep into sequence analysis to examine language Learn the fundamentals of reinforcement learning

Forecasting Next Generation Manufacturing

Author : Frank T. Piller,Verena Nitsch,Dirk Lüttgens,Alexander Mertens,Sebastian Pütz,Marc Van Dyck
Publisher : Springer Nature
Page : 169 pages
File Size : 46,7 Mb
Release : 2022-08-25
Category : Business & Economics
ISBN : 9783031077340

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Forecasting Next Generation Manufacturing by Frank T. Piller,Verena Nitsch,Dirk Lüttgens,Alexander Mertens,Sebastian Pütz,Marc Van Dyck Pdf

Manufacturing companies have just begun to implement the concepts of the Fourth Industrial Revolution (Industry 4.0) on a larger scale. Still, this area is characterized by a rapid pace of technological change, blurring boundaries between physical, digital, and biological systems, and a quickly changing growing political, economic, and social environment -- leading to high uncertainty in decision making and many questions about the future development in this field. To provide guidance and inspiration for managers and academics on the future of digital manufacturing systems, this book presents the results of an extensive Delphi study on next-generation manufacturing systems, with a projection period of up to 2030. We analyzed almost 2000 quantitative estimations and more than 600 qualitative arguments from a large panel of industrial and academic experts from Europe, North America, and Asia. The book describes each of the 24 projections in detail, offering current case study examples and related research, as well as implications for policymakers, firms, and individuals. The empirical results also allowed us to build scenarios for the most probable future along the dimensions of governance, organization, capabilities, and interfaces from both a company-internal and an external (network) perspective.

Reinforcement and Systemic Machine Learning for Decision Making

Author : Parag Kulkarni
Publisher : John Wiley & Sons
Page : 324 pages
File Size : 42,7 Mb
Release : 2012-07-11
Category : Technology & Engineering
ISBN : 9781118271551

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Reinforcement and Systemic Machine Learning for Decision Making by Parag Kulkarni Pdf

Reinforcement and Systemic Machine Learning for Decision Making There are always difficulties in making machines that learn from experience. Complete information is not always available—or it becomes available in bits and pieces over a period of time. With respect to systemic learning, there is a need to understand the impact of decisions and actions on a system over that period of time. This book takes a holistic approach to addressing that need and presents a new paradigm—creating new learning applications and, ultimately, more intelligent machines. The first book of its kind in this new and growing field, Reinforcement and Systemic Machine Learning for Decision Making focuses on the specialized research area of machine learning and systemic machine learning. It addresses reinforcement learning and its applications, incremental machine learning, repetitive failure-correction mechanisms, and multiperspective decision making. Chapters include: Introduction to Reinforcement and Systemic Machine Learning Fundamentals of Whole-System, Systemic, and Multiperspective Machine Learning Systemic Machine Learning and Model Inference and Information Integration Adaptive Learning Incremental Learning and Knowledge Representation Knowledge Augmentation: A Machine Learning Perspective Building a Learning System With the potential of this paradigm to become one of the more utilized in its field, professionals in the area of machine and systemic learning will find this book to be a valuable resource.

Next Generation of Data Mining

Author : Hillol Kargupta,Jiawei Han,Philip S. Yu,Rajeev Motwani,Vipin Kumar
Publisher : CRC Press
Page : 601 pages
File Size : 41,9 Mb
Release : 2008-12-24
Category : Computers
ISBN : 1420085875

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Next Generation of Data Mining by Hillol Kargupta,Jiawei Han,Philip S. Yu,Rajeev Motwani,Vipin Kumar Pdf

Drawn from the US National Science Foundation’s Symposium on Next Generation of Data Mining and Cyber-Enabled Discovery for Innovation (NGDM 07), Next Generation of Data Mining explores emerging technologies and applications in data mining as well as potential challenges faced by the field. Gathering perspectives from top experts across different disciplines, the book debates upcoming challenges and outlines computational methods. The contributors look at how ecology, astronomy, social science, medicine, finance, and more can benefit from the next generation of data mining techniques. They examine the algorithms, middleware, infrastructure, and privacy policies associated with ubiquitous, distributed, and high performance data mining. They also discuss the impact of new technologies, such as the semantic web, on data mining and provide recommendations for privacy-preserving mechanisms. The dramatic increase in the availability of massive, complex data from various sources is creating computing, storage, communication, and human-computer interaction challenges for data mining. Providing a framework to better understand these fundamental issues, this volume surveys promising approaches to data mining problems that span an array of disciplines.

Machine Learning and Knowledge Discovery in Databases. Research Track

Author : Nuria Oliver,Fernando Pérez-Cruz,Stefan Kramer,Jesse Read,Jose A. Lozano
Publisher : Springer Nature
Page : 857 pages
File Size : 51,6 Mb
Release : 2021-09-10
Category : Computers
ISBN : 9783030865238

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Machine Learning and Knowledge Discovery in Databases. Research Track by Nuria Oliver,Fernando Pérez-Cruz,Stefan Kramer,Jesse Read,Jose A. Lozano Pdf

The multi-volume set LNAI 12975 until 12979 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2021, which was held during September 13-17, 2021. The conference was originally planned to take place in Bilbao, Spain, but changed to an online event due to the COVID-19 pandemic. The 210 full papers presented in these proceedings were carefully reviewed and selected from a total of 869 submissions. The volumes are organized in topical sections as follows: Research Track: Part I: Online learning; reinforcement learning; time series, streams, and sequence models; transfer and multi-task learning; semi-supervised and few-shot learning; learning algorithms and applications. Part II: Generative models; algorithms and learning theory; graphs and networks; interpretation, explainability, transparency, safety. Part III: Generative models; search and optimization; supervised learning; text mining and natural language processing; image processing, computer vision and visual analytics. Applied Data Science Track: Part IV: Anomaly detection and malware; spatio-temporal data; e-commerce and finance; healthcare and medical applications (including Covid); mobility and transportation. Part V: Automating machine learning, optimization, and feature engineering; machine learning based simulations and knowledge discovery; recommender systems and behavior modeling; natural language processing; remote sensing, image and video processing; social media.

Knowledge Graphs: Semantics, Machine Learning, and Languages

Author : M. Acosta,S. Peroni,S. Vahdati
Publisher : IOS Press
Page : 262 pages
File Size : 46,9 Mb
Release : 2023-10-03
Category : Computers
ISBN : 9781643684253

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Knowledge Graphs: Semantics, Machine Learning, and Languages by M. Acosta,S. Peroni,S. Vahdati Pdf

Semantic computing is an integral part of modern technology, an essential component of fields as diverse as artificial intelligence, data science, knowledge discovery and management, big data analytics, e-commerce, enterprise search, technical documentation, document management, business intelligence, and enterprise vocabulary management. This book presents the proceedings of SEMANTICS 2023, the 19th International Conference on Semantic Systems, held in Leipzig, Germany, from 20 to 22 September 2023. The conference is a pivotal event for those professionals and researchers actively engaged in harnessing the power of semantic computing, an opportunity to increase their understanding of the subject’s transformative potential while confronting its practical limitations. Attendees include information managers, IT architects, software engineers, and researchers from a broad spectrum of organizations, including research facilities, non-profit entities, public administrations, and the world's largest corporations. For this year’s conference a total of 54 submissions were received in response to a call for papers. These were subjected to a rigorous, double-blind review process, with at least three independent reviews conducted for each submission. The 16 papers included here were ultimately accepted for presentation, with an acceptance rate of 29.6%. Areas covered include novel research challenges in areas such as data science, machine learning, logic programming, content engineering, social computing, and the Semantic Web. The book provides an up-to-date overview, which will be of interest to all those wishing to stay abreast of emerging trends and themes within the vast field of semantic computing.