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The unintended consequences of technology : Solutions, breakthroughs, and the restart we need
In The Unintended Consequences of Technology: Solutions, Breakthroughs and the Restart We Need, accomplished tech entrepreneur Chris Ategeka delivers an insightful and eye-opening exploration of the challenges and the opportunities at the intersection of technology, society and our planet. Detailing both positive and negative technology use cases that on one hand have made humanity better, but on the other hand pose a serious threat to individuals and groups across the world.
The semantic web : Real-world applications from industry
It offers a glimpse into the opening door of semantic technologies by means of concentrated examples of semantic applications in real business environments. For quite a while, there has been evidence from academic research and early industrial prototypes that semantic technology can help humans and machines substantially in accessing and using the unprecedented, and exponentially growing, amount of information that the World Wide Web provides. Now semantic technology is moving from academic and industrial research into real products and applications. This book provides a series of case studies which demonstrate how real benefits can be derived from the adoption of semantic technology in popular business domains, such as telecommunication, B2B integration, healthcare, education, and others.
Text Mining for Information Professionals : An Uncharted Territory
Focuses on a basic theoretical framework dealing with the problems, solutions, and applications of text mining and its various facets in a very practical form of case studies, use cases, and stories. Contains 11 chapters with 14 case studies showing 8 different text mining and visualization approaches, and 17 stories. In addition, both a website and a Github account are also maintained for the book. They contain the code, data, and notebooks for the case studies; a summary of all the stories shared by the librarians/faculty; and hyperlinks to open an interactive virtual RStudio/Jupyter Notebook environment.
Simplifying data engineering and analytics with delta : Create analytics-ready data that fuels artificial intelligence and business intelligence
Data engineers, data scientists, ML practitioners, BI analysts, or anyone in the data domain working with big data will be able to put their knowledge to work with this practical guide to executing pipelines and supporting diverse use cases using the Delta protocol. Basic knowledge of SQL, Python programming, and Spark is required to get the most out of this book.
Scenarios : Models, transformations and tools ; International Workshop, Dagstuhl Castle, Germany, September 7-12, 2003, Revised Selected Papers
Visual notations and languages continue to play a pivotal role ˆ in the design of complex software systems. In many cases visual notations are used to - scribe usage or interaction scenarios of software systems or their components. While representing scenarios using a visual notation is not the only possibility, a vast majority of scenario description languages is visual. Scenarios are used in telecommunications as Message Sequence Charts, in object-oriented system design as Sequence Diagrams, in reverse engineering as execution traces, and in requirements engineering as, for example, Use Case Maps or Life Sequence Charts. These techniques are used to capture requirements, to capture use cases in system documentation, to specify test cases, or to visualize runs of existing systems. They are often employed to represent concurrent systems that int- act via message passing or method invocation.
Mobile and Wireless Communications with Practical Use-Case Scenarios
While wireless technologies had a spectacular evolution over the past years, the present trend is to adopt a global heterogeneous network of shared standards that enables the provisioning of Quality of Service and Quality of Experience to the end-user. To this end, enabling technologies like Machine Learning, Internet of Things, Digital Twins, are seen as promising solutions for next generation networks that will enable an intelligent adaptive interconnected environment with support for prediction and decision making so that the heterogeneous applications and users requirements can be highly satisfied. The aim of this textbook is to provide the readers with a comprehensive technical foundation of the mobile communication systems and wireless network design, operations and applications of various radio access technologies. Additionally, it also introduces the reader to the latest advancements in technologies in terms of Internet of Things ecosystem, Machine Learning and Digital Twins for IoT-enabled intelligent environments. Furthermore, this textbook also includes practical use-case scenarios using Altair WinProp Software as well as Phyton, TensorFlow and Jupiter as support for practice-based laboratory sessions"
Instrumaster
Experiments with different neural network structures and algorithms in order to achieve musical note recognition as well as musical instrument recognition, all bundled in a mobile application. It also aims to create the most effective music-learning application that works completely offline, which is hard to find in modern music applications. The paper also explores why the instrument identifying AI is solely based on Multi-Layer Perceptron (MLP) and why the note-identifying AI system was chosen to be a ML system over CNN or other deep-learning trained AI. The paper presents feature extraction methods for audio signals and files and dives deep into the process, such as FFT, MFCCs, Wavelengths, sampling rates, etc. It also touches on Logistic Regression Algorithms, their limitations, and their performance with the different use cases in the application. All these techniques are then compared side by side for maximally added value, making this research paper a good reference for any future developers looking to find optimal neural networks techniques when it comes to audio processing and analysis.
Heterogeneity, high performance computing, self-organization and the cloud
Addresses the most recent developments in cloud computing such as HPC in the Cloud, heterogeneous cloud, self-organising and self-management, and discusses the business implications of cloud computing adoption. Establishing the need for a new architecture for cloud computing, it discusses a novel cloud management and delivery architecture based on the principles of self-organisation and self-management. This focus shifts the deployment and optimisation effort from the consumer to the software stack running on the cloud infrastructure. It also outlines validation challenges and introduces a novel generalised extensible simulation framework to illustrate the effectiveness, performance and scalability of self-organising and self-managing delivery models on hyperscale cloud infrastructures. It concludes with a number of potential use cases for self-organising, self-managing clouds and the impact on those businesses.
Healthcare solutions using machine learning and informatics
Covers novel and innovative solutions for the healthcare that apply machine learning and biomedical informatics technology. The healthcare sector is one of the most critical in society. This book presents a series of artificial intelligence, machine learning, intelligent IoT-based solutions for medical image analysis, medical big data processing, disease predictions. Machine learning and artificial intelligence use cases in healthcare presented in the book give researchers, practitioners, and students a wide range of practical examples of cross-domain convergence. The wide variety of topics covered include: Artificial Intelligence in healthcare Machine learning solutions for such disease as diabetes, arthritis, cardiovascular disease, and COVID-19 Big data analytics solutions for healthcare data processing Reliable biomedical applications using AI models Intelligent IoT in healthcare. The book explains fundamental concepts as well as the advanced use cases illustrating how to apply emerging technologies such as machine learning, AI models, data informatics into practice to tackle challenges in the field of healthcare with real-world scenarios. Chapters contributed by noted academicians and professionals examine various solutions, frameworks, applications, case studies, and best practices in the healthcare domain
Forensic Dentistry ; 2nd ed.
The identification of unknown individuals and the estimation of age, race, and gender are among the chief functions of forensic dentistry. Other important applications include the investigation and analysis of bitemarks and oral injuries in abuse cases and evaluating, reporting, and testifying in civil litigation cases. Twelve years after the benchmark first edition of this book explored these topics, the long-awaited Forensic Dentistry, Second Edition offers a comprehensive update and revision of the material.
Earth Observation Open Science and Innovation
The digital transformation is revolutionizing our ability to monitor our planet and transforming the way we access, process and exploit Earth Observation data from satellites.This book reviews these megatrends and their implications for the Earth Observation community as well as the wider data economy. It provides insight into new paradigms of Open Science and Innovation applied to space data, which are characterized by openness, access to large volume of complex data, wide availability of new community tools, new techniques for big data analytics such as Artificial Intelligence, unprecedented level of computing power, and new types of collaboration among researchers, innovators, entrepreneurs and citizen scientists. In addition, this book aims to provide readers with some reflections on the future of Earth Observation, highlighting through a series of use cases not just the new opportunities created by the New Space revolution, but also the new challenges that must be addressed in order to make the most of the large volume of complex and diverse data delivered by the new generation of satellites.
Digital twin : Architectures, networks, and applications
Offers comprehensive, self-contained knowledge on digital twin (DT), which is a very promising technology for achieving digital intelligence in the next-generation wireless communications and computing networks. DT is a key technology to connect physical systems and digital spaces in Metaverse. The objectives of this book are to provide the basic concepts of DT, to explore the promising applications of DT integrated with emerging technologies, and to give insights into the possible future directions of DT. For easy understanding, this book also presents several use cases for DT models and applications in different scenarios. The book starts with the basic concepts, models, and network architectures of DT. Then, we present the new opportunities when DT meets edge computing, Blockchain and Artificial Intelligence, and distributed machine learning (e.g., federated learning, multi-agent deep reinforcement learning).
Developing BIM talent : A guide to the BIM body of knowledge with Metrics, KSAs, and learning outcomes
A systematic Building Information Modeling (BIM) framework features cutting-edge use cases and competencies for students and professionals pursuing BIM careers. Offers: A solid foundation and guidelines for educators and practitioners for starting or enhancing a BIM curriculum or training program Templates, expert interviews, and case studies that provide in-depth knowledge and lessons learned that can facilitate process changes and strategic action plans Strategies for standardizing emerging BIM job tasks, descriptions, and methods for benchmarking performance
Designing machine learning systems : An iterative process for production-ready applications
Machine learning systems are both complex and unique. Each design decision--such as how to process and create training data, which features to use, how often to retrain models, and what to monitor--in the context of how it can help your system as a whole achieve its objectives. The iterative framework in this book uses actual case studies backed by ample references. The book will help you tackle scenarios such as: Engineering data and choosing the right metrics to solve a business problem Automating the process for continually developing, evaluating, deploying, and updating models Developing a monitoring system to quickly detect and address issues your models might encounter in production Architecting an ML platform that serves across use cases Developing responsible ML systems
Computational linguistics and intelligent text processing ; Vol. 3406 ; 6th International Conference, CICLing 2005, Mexico City, Mexico, February 13-19, 2005, Proceedings
This book constitutes the refereed proceedings of the 6th International Conference on Computational Linguistics and Intelligent Text Processing, CICLing 2005, held in Mexico City, Mexico in February 2005. An approach that involves natural language analysis techniques for the treatment of software system functional requirements is described in this book. This approach is used as the basis for a process developed to generate sequence diagrams automatically from the textual specification of use cases. This facility has been integrated in the Requirements Engineering Phase of OO-Method, an automatic production environment of software. For this purpose, a translator that is based on natural language parser is used. The translator provides grammatical information to each use case sentence and it identifies the corresponding interaction. The automatic transformation is conceived and specified following an orientation that is based on models and patterns. The results of the validation of the transformation patterns are presented.
Machine learning and deep learning in medical data analytics and healthcare applications
Introduces and explores a variety of schemes designed to empower, enhance, and represent multi-institutional and multi-disciplinary machine learning (ML) and deep learning (DL) research in healthcare paradigms. Serving as a unique compendium of existing and emerging ML/DL paradigms for the healthcare sector, this book demonstrates the depth, breadth, complexity, and diversity of this multi-disciplinary area. It provides a comprehensive overview of ML/DL algorithms and explores the related use cases in enterprises such as computer-aided medical diagnostics, drug discovery and development, medical imaging, automation, robotic surgery, electronic smart records creation, outbreak prediction, medical image analysis, and radiation treatments.
C# 10 in a Nutshell : The Definitive Reference
When you have questions about C# 10.0 or .NET 6, this guide has the answers you need. C# is a language of unusual flexibility and breadth, but with its continual growth, there's so much more to learn. In the tradition of O'Reilly's Nutshell guides, this thoroughly updated edition is simply the best one-volume reference to the C# language available today. Organized around concepts and use cases, this comprehensive and complete reference provides intermediate and advanced programmers with a concise map of C# and .NET that also plumbs significant depths
Beginning Database Design : From novice to professional
Beginning Database Design: From Novice to Professional provides short, easy-to-read explanations of how to get database design right the first time. Through the help of use cases and class diagrams modeled in the UML, youll learn how to discover and represent the details and scope of the problem in question.
Banking on (artificial) intelligence : Navigating the realities of ai in financial services
Provides a tailored overview of what AI specifically means for financial services, a highly regulated yet also disrupted industry. it investigates the current state of AI applications in financial services today along with the state of funding and partnerships between tech and banking industries. it also examines the key pillars of responsible AI and the importance of keeping humans in the loop. the book takes a deep dive into the use cases in the financial services industry, the challenges and opportunities, and the fragmented regulatory landscape. how can we effectively assess risks, and balance innovation and customer centricity with trust in AI in financial services? can smaller organizations reap the benefits of the technology? how can institutions deploy AI responsibly and securely, and promote a fairer and more equitable future for more people?
Agile Development with the ICONIX Process : People, Process, and Pragmatism
Describes how to apply ICONIX Process (a minimal, use case-driven modeling process) in an agile software project. It's full of practical advice for avoiding common agile pitfalls. Further, the book defines a core agile subset so those of you who want to get agile need not spend years learning to do it. Instead, you can simply read this book and apply the core subset of techniques. The book follows a real-life .NET/C# project from inception and UML modeling, to working code through several iterations. You can then go on-line to compare the finished product with the initial set of use cases. The book also introduces several extensions to the core ICONIX Process, including combining test-driven development (TDD) with up-front design to maximize both approaches (with examples using Java and JUnit). And the book incorporates persona analysis to drive the projects goals and reduce requirements churn.
