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Mezzalira Luca: Building Micro-Frontends

Building Micro-Frontends

Distributed Systems for the Frontend

Advances in Digital Technologies for Smart Applications

Medical Knowledge Paradigms for Enabling the Digital Health Ecosystems delves into the dynamic interplay between technology and healthcare, exploring the transformative potential of digital solutions in shaping the future of healthcare delivery.

Medical Knowledge Paradigms for Enabling the Digital Health Ecosystem

Advanced Topics in Biomaterials

Signal Processing Roadmap: Technologies, Applications, and Future Directions explores cutting-edge and emerging signal-processing techniques across various measurement and monitoring applications, serving as an authoritative reference for engineers, researchers, and technologists. It critically analyses key signal processing considerations like uncertainty modelling that enable more intelligent and reliable next-generation measurement systems, backed by real-world implementation examples in areas ranging from Internet of Things devices to complex biomedical equipment. The book will provide an overview of the latest research in the hybrid information system modelling field, with a particular emphasis on practical applications in various fields. This includes case studies and examples of how these models have been used to solve problems in finance, healthcare, engineering, and other related fields. Additionally, the book reviews the theories and concepts related to non-linear optimization, fuzzy sets, and rough sets. Overall, Signal Processing Roadmap: Technologies, Applications, and Future Directions deals with the dual goals of consolidating the state-of-the-art and charting the future directions across the exciting applications where signal processing will continue playing a pivotal role in building intelligent, reliable, and efficient systems of the future.

Technologies, Applications, and Future Directions

Signal Processing Roadmap

Lecture Notes in Networks and Systems

This book gathers high-quality peer-reviewed research papers presented at the International Conference on Intelligent Computing and Networking (IC-ICN 2025), organized by the Computer Engineering Department, Thakur College of Engineering and Technology, in Mumbai, Maharashtra, India, on February 21–22, 2025. This book includes innovative and novel papers in the areas of intelligent computing, artificial intelligence, machine learning, deep learning, fuzzy logic, natural language processing, human–machine interaction, big data mining, data science and mining, applications of intelligent systems in healthcare, finance, agriculture and manufacturing, high-performance computing, computer networking, sensor and wireless networks, Internet of Things (IoT), software-defined networks, cryptography, mobile computing, digital forensics, and blockchain technology.

Proceedings of IC-ICN 2025

Intelligent Computing and Networking

Comprehensive overview of recent research advancements in scheduling approaches for cloud edge computing systems Intelligent Scheduling of Tasks for Cloud-Edge-Device Computing Systems offers an in-depth collection of advanced task scheduling algorithms designed specifically for diverse cloud-edge-device computing systems. After an introductory overview, a series of intelligent scheduling approaches are presented, each specifically designed for a particular scenario within cloud-edge-device computing systems. The book then summarizes the authors' research findings in recent years, delving into topics including resource management, latency and real-time requirements, load balancing, priority constraints, algorithm design, and performance evaluation. The book enables readers to achieve efficient allocation of computing, storage, and network resources to optimize resource utilization. Real-world applications of scheduling technologies in smart cities and traffic management, industrial automation and smart factories, and healthcare monitoring systems are given in a separate chapter. Additional topics include: <ul> <li>Workload-aware scheduling of real-time independent tasks, covering how to schedule jobs in a single or multiple servers</li> <li>Mixed real-time task scheduling in automotive systems with vehicle networks, covering hybrid schedule design, offline task management, and online job assignment</li> <li>Scheduling with real-time constraint, covering task placement adjustment strategy, start time adjustment, and backwards schedule adjustment</li> <li>Energy-efficient scheduling without real-time constraint, covering energy consumption-optimal task placement plans as well as partition scheduling</li> </ul> Intelligent Scheduling of Tasks for Cloud-Edge-Device Computing Systems is an essential resource for researchers and practitioners in the field of IoT seeking to understand specific challenges and requirements associated with task scheduling in cloud-edge-device computing systems.

Intelligent Scheduling of Tasks for Cloud-Edge-Device Computing Systems

Hacking and Securing Serverless Cloud Applications on AWS, Azure, and GCP

Learning Serverless Security

Praxisleitfaden für das IT- und Software Asset Management

1x1 des Lizenzmanagements

The Big Ideas Behind Reliable, Scalable, and Maintainable Systems

Designing Data-Intensive Applications

FPGA, IoT, Microcontrollers, and Quantum Technologies

Exploring Hardware Advances

Sybex Study Guide

A fast and efficient prep handbook for the Azure AI Fundamentals certification exam In MC Microsoft Certified Azure AI Fundamentals Study Guide: Exam AI-900, experienced software engineer Adora Nwodo walks you through every technical topic you need to understand to succeed on the AI-900 certification exam and build a fundamental understanding of Azure AI features. The Study Guide uses the proven and popular Sybex approach to help you use Azure AI in the real-world, whether you're in a technical or non-technical role. Nwodo offers clear explanations, step-by-step instructions, and visual aids to guide you through essential AI concepts and shows you how to use them in the Azure cloud. You'll learn about: <ul> <li>Artificial intelligence concepts and workloads</li> <li>Responsible AI use in Azure</li> <li>Core concepts in AI models and solutions</li> <li>Introduction to machine learning concepts, including data preprocessing, training and validation, algorithms, and more</li> <li>The application of machine learning concepts on the Azure cloud platform</li> <li>Computer vision in Azure</li> <li>Natural language processing concepts</li> <li>Generative AI concepts</li> <li>The Azure OpenAI Service</li> <li>Example AI use cases and industry-specific applications</li> </ul> The MC Microsoft Certified Azure AI Fundamentals Study Guide highlights best practices for industry newcomers and veterans alike and builds the confidence you need to pass the AI-900 certification exam on your first attempt. Inside the book: <ul> <li>Intuitively organized material and additional sample questions that allow you to selectively study the areas in which you need to improve</li> <li>Carefully explained content appropriate for non-technical professionals who interact with AI technologies occasionally or on a daily basis</li> <li>Complimentary access to the superior Sybex online learning environment and test bank, including practice test questions, digital flashcards, and a glossary of key terms</li> </ul> Perfect for everyone preparing for the AI-900 certification exam, the Microsoft Certified Azure AI Fundamentals Study Guide is also a must-read for technical and non-technical professionals--especially those working in AI-impacted industries like sales and marketing--who wish to expand their AI skillset and improve their effectiveness at work.

Exam AI-900

MC Azure AI Fundamentals Study Guide

As the popularity and criticality of automation has grown within enterprise organizations, the need to automate has become just as important. This book will explain how Event-Drive Ansible, a highly scalable and flexible automation capability that works with event sources such as monitoring tools, can be deployed and configured to handle the day-to-day events created by multiple teams within your organization.

You'll learn how to build a self-healing environment using key components, and how cultural change is a requirement for this automation evolution. Understanding this will not only allow you to monitor the automated remediation of known issues, but also understand how Event-Driven Ansible can be leveraged to resolve both common and major automation headaches.

Event-Driven Ansible will show you why this technology is the next step in automation evolution.

You will:

<ul>
	<li>Review diverse use cases for Event-Driven Ansible.</li>
	<li>Build and configure your own Event-Driven Ansible environment.</li>
	<li>Design a self-healing infrastructure.</li>
	<li>Solve common problems that prevent End-to-End Automation.</li>
	<li>Examine end-to-end automation in siloed environments.</li>
</ul>

Taking Your Automation to the Next Level

Event-Driven Ansible

Proceedings of the Sixth International Conference on Real Time Intelligent Systems RTIS 2024

2024 Real-Time Intelligent Systems

Tech Today

Running Windows Server 2025 on Microsoft Azure

Building Micro-Frontends

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