5G Enabled Secure Wireless Networks

This book covers issues related to 5G network security. The authors start by providing details on network architecture and key requirements. They then outline the issues concerning security policies and various solutions that can handle these policies. Use of SDN-NFV technologies for security enhancement is also covered. The book includes intelligent solutions by utilizing the features of artificial intelligence and machine learning to improve the performance of the 5G security protocols and models. Optimization of security models is covered as a separate section with a detailed information on the security of 5G-based edge, fog, and osmotic computing. This book provides detailed guidance and reference material for academicians, professionals, and researchers.

Presents extensive information and data on research and challenges in 5G networks;

Covers basic architectures, models, security frameworks, and software-defined solutions for security issues in 5G networks;

Provides solutions that can help in the growth of new startups as well as research directions concerning the future of 5G networks.

Archive: rar

Formats: pdf, epub

File Size: 26.5 MB

Print Length: 200 pages

Publication Date: February 5, 2019

https://mega.nz/file/AKAAmTbK#tae-wgB9HA0vbl68o4lGIm_6OmSwcmxV6Ff4gGZvQcY

Artificial Intelligence Accelerates Human Learning: Discussion Data Analytics

Focusing on students’ presentations and discussions in laboratory seminars, this book presents case studies on evidence-based education using artificial intelligence (AI) technologies. It proposes a system to help users complete research activities, and a machine-learning method that makes the system suitable for long-term operation by performing data mining for discussions and automatically extracting essential tasks. By illustrating the complete process – proposal, implementation, and operation – of applying machine learning techniques to real-world situations, the book will inspire researchers and professionals to develop innovative new applications for education.

The book is divided into six chapters, the first of which provides an overview of AI research and practice in education. In turn, Chapter 2 describes a mechanism for applying data analytics to student discussions and utilizing the results for knowledge creation activities such as research. Based on discussion data analytics, Chapter 3 describes a creative activity support system that effectively utilizes the analytical results of the discussion for subsequent activities. Chapter 4 discusses the incorporation of a gamification method to evaluate and improve discussion skills while maintaining the motivation to participate in the discussion.

Chapters 5 and 6 describe an advanced learning environment for honing students’ discussion and presentation skills. Two important systems proposed here are a presentation training system using virtual reality technologies, and an interactive presentation/discussion training system using a humanoid robot. In the former, the virtual space is constructed by measuring the three-dimensional shape of the actual auditorium, presentations are performed in the same way as in the real world, and the AI as audience automatically evaluates the presentation and provides feedback. In the latter, a humanoid robot makes some remarks on and asks questions about students’ presentations, and the students practice responding to it.

Archive: rar

Formats: pdf, epub

File Size: 51.4 MB

Print Length: 151 pages

Publication Date: February 2, 2019

https://mega.nz/file/UKJkCZiI#IakwrWQMXmgjH3vGgISxXcipPuI20VPSOrlPEpKcea4

The Basic Practice of Statistics, 8th

Written by an author team of accomplished leaders in statistics education, The Basic Practice of Statistics (BPS) reflects the actual practice of statistics, where data analysis and design of data production join with probability-based inference to form a coherent science of data. The authors’ ultimate goal is to equip students to carry out common statistical procedures and to follow statistical reasoning in their fields of study and in their future employment.

The text’s long-standing renown is built on an inspired framework of balanced content, experience with data, and the importance of ideas. These themes are widely accepted by statisticians concerned about teaching and are directly connected to and reflected by the themes of the College Report of the Guidelines in Assessment and Instruction for Statistics Education (GAISE) Project.

The eighth edition of The Basic Practice of Statistics is supported in SaplingPLUS for a user experience of its own. SaplingPLUS combines Macmillan’s StatsTools, powerful multimedia resources, and text-specific exercises with the powerful targeted feedback of Sapling Learning, where every problem is a teaching and learning opportunity.

Archive: No archive

Formats: epub

File Size: 66 MB

Print Length: 654 pages

Publication Date: December 22, 2017

https://mega.nz/file/ISYAVR7a#557194Ecp8fKr8UuGAUSYjT0DJWkIusVvShXGjXfqYg

Make Your Own PC Tricks and Tips – 4th Edition 2020

Format: pdf (zip)

Size: 52Mb

http://www.solidfiles.com/v/nDMmg4W3zAx65

Online Security For Beginners – December 2020

Format: pdf (zip)

Size: 72Mb

https://mir.cr/IGNETCIS

Developing Networks using Artificial Intelligence (Wireless Networks)

This book mainly discusses the most important issues in artificial intelligence-aided future networks, such as applying different ML approaches to investigate solutions to intelligently monitor, control and optimize networking. The authors focus on four scenarios of successfully applying machine learning in network space. It also discusses the main challenge of network traffic intelligent awareness and introduces several machine learning-based traffic awareness algorithms, such as traffic classification, anomaly traffic identification and traffic prediction. The authors introduce some ML approaches like reinforcement learning to deal with network control problem in this book.

Traditional works on the control plane largely rely on a manual process in configuring forwarding, which cannot be employed for today's network conditions. To address this issue, several artificial intelligence approaches for self-learning control strategies are introduced. In addition, resource management problems are ubiquitous in the networking field, such as job scheduling, bitrate adaptation in video streaming and virtual machine placement in cloud computing. Compared with the traditional with-box approach, the authors present some ML methods to solve the complexity network resource allocation problems. Finally, semantic comprehension function is introduced to the network to understand the high-level business intent in this book.

With Software-Defined Networking (SDN), Network Function Virtualization (NFV), 5th Generation Wireless Systems (5G) development, the global network is undergoing profound restructuring and transformation. However, with the improvement of the flexibility and scalability of the networks, as well as the ever-increasing complexity of networks, makes effective monitoring, overall control, and optimization of the network extremely difficult. Recently, adding intelligence to the control plane through AI&ML become a trend and a direction of network development

This book's expected audience includes professors, researchers, scientists, practitioners, engineers, industry managers, and government research workers, who work in the fields of intelligent network. Advanced-level students studying computer science and electrical engineering will also find this book useful as a secondary textbook.

Archive: No archive

Formats: pdf

File Size: 9.90 MB

Print Length: 248 pages

Publication Date: April 26, 2019

https://mega.nz/file/db4VyIhT#Mv7mf8X9GVcv0I3FvK4JbQTfTdgOcZ6oyyDQV51KmOk

Hands-On Artificial Intelligence for Beginners

Key Features

Enter the world of AI with the help of solid concepts and real-world use cases

Explore AI components to build real-world automated intelligence

Become well versed with machine learning and deep learning concepts

Book Description

Virtual Assistants, such as Alexa and Siri, process our requests, Google's cars have started to read addresses, and Amazon's prices and Netflix's recommended videos are decided by AI. Artificial Intelligence is one of the most exciting technologies and is becoming increasingly significant in the modern world.

Hands-On Artificial Intelligence for Beginners will teach you what Artificial Intelligence is and how to design and build intelligent applications. This book will teach you to harness packages such as TensorFlow in order to create powerful AI systems. You will begin with reviewing the recent changes in AI and learning how artificial neural networks (ANNs) have enabled more intelligent AI. You'll explore feedforward, recurrent, convolutional, and generative neural networks (FFNNs, RNNs, CNNs, and GNNs), as well as reinforcement learning methods. In the concluding chapters, you'll learn how to implement these methods for a variety of tasks, such as generating text for chatbots, and playing board and video games.

By the end of this book, you will be able to understand exactly what you need to consider when optimizing ANNs and how to deploy and maintain AI applications.

What you will learn

Use TensorFlow packages to create AI systems

Build feedforward, convolutional, and recurrent neural networks

Implement generative models for text generation

Build reinforcement learning algorithms to play games

Assemble RNNs, CNNs, and decoders to create an intelligent assistant

Utilize RNNs to predict stock market behavior

Create and scale training pipelines and deployment architectures for AI systems

Who this book is for

This book is designed for beginners in AI, aspiring AI developers, as well as machine learning enthusiasts with an interest in leveraging various algorithms to build powerful AI applications.

Table of Contents

The History of AI

Machine Learning Basics

Platforms and Other Essentials

Your First Artificial Neural Networks

Convolutional Neural Networks

Recurrent Neural Networks

Generative Models

Reinforcement Learning

Deep Learning for Intelligent Agents

Deep Learning for Game Playing

Deep Learning for Finance

Deep Learning for Robotics

Deploying and Maintaining AI Applications

Archive: rar

Formats: epub, Code

File Size: 15 MB

Print Length: 364 pages

Publication Date: October 31, 2018

https://mega.nz/file/YPY3CKCJ#55QM6DL4Xmu6iFvNuO5PXrC01S20qXaJxQOOFnfjOQU

Network Automation Cookbook: Proven and actionable recipes

Key Features

Step-by-step instructions to automate network Infrastructure using Ansible

Effectively model and describe Network Infrastructure using Ansible in various environments across Cloud, Data Center and Service Provider Networks

Integrate Ansible with several 3rd party tools like NAPALM, NetBox and Batfish to deliver a robust automation framework

Book Description

Network Automation Cookbook is designed for system administrators, network engineers, or infrastructure automation engineers interested in using network automation to centrally manage the switches, routers, and other devices in their organization's network infrastructure.

The book begins by reviewing the basic Ansible concepts and then explains how to use Ansible to automate common network tasks across various vendor equipment in different environments like enterprise, data center and service providers.Then, we move to explain how to automate networks on the cloud from providers like AWS, GCP and Azure..

By the end of this book, you should be comfortable in using Ansible in automating network devices as well as using various 3rd party tools like NAPALM, NetBox and Batfish to build robust network automation solutions.

What you will learn

Understand the various components of Ansible

Using infrastructure as code concepts in the design and build of network solutions

Using Ansible in automating network devices like Cisco, Juniper, Arista and F5

Using Ansible to automate network resources in AWS, GCP and Azure cloud solutions

How to use NetBox for network inventory and how to integrate it with Ansible

How to validate network using Ansible and Batfish

Who This Book Is For

This book is ideal for network engineers and devops engineers who would like to automate common network tasks. A good amount of network and basic Linux knowledge is required.

Archive: rar

Formats: pdf, epub, mobi, Code

File Size: 95 MB

Print Length: 399 pages

Publication Date: May 11, 2020

https://mega.nz/file/ZPhhVKQY#pFCupR1fqoe2tZMtUNAobbjAgZn6KPjtJPBZeVzfV40

Embedded Programming with C++ Cookbook

Key Features

Get hands-on experience in developing a sample application for an embedded Linux-based system

Explore advanced topics such as concurrency, RTOS, and C++ utilities

Learn how to test and debug your embedded applications by using logs and profiling tools

Book Description

Developing applications for embedded systems may seem like a daunting task as developers face challenges in terms of limited memory, power consumption, and maintaining real-time responses. This book is a collection of practical examples for understanding how to develop applications for embedded boards and solve challenges that you may encounter while developing.

The book will start with an introduction to embedded systems and how to set up the development environment. By teaching you to build your first embedded application, the book will help you progress from the basics to more complex concepts such as debugging, logging and profiling. Moving ahead, you will understand the use of specialized memory and custom allocators. From here, you will delve into recipes that will teach you how to work with the C++ memory model, atomic variables, and synchronization. The book will then take you through recipes on inter-process communication, data serialization, and timers. Finally, you’ll cover topics such as error handling, and guidelines for real-time systems and safety-critical systems.

By the end of this book, you will be proficient in building robust and secure embedded applications with C++.

What you will learn

Become well-versed with how to deploy software to an embedded system

Create specialized Linux distributives for embedded systems using the Yocto Project

Understand concepts such as interrupt vector array, Separating Device Driver and interrupt controller management

Discover the importance of logging for debugging and failure root cause analysis

Understand the need for custom memory allocators for better memory management

Use toolkit implementers for code optimization

Who This Book Is For

This book is for developers, electronic hardware professionals, and software and system-on-chip engineers who want to build effective embedded programs in C++. Familiarity with the C++language is expected but no previous knowledge of embedded systems is required.

Archive: rar

Formats: pdf, epub, mobi, Code

File Size: 94 MB

Print Length: 389 pages

https://mega.nz/file/8Ph1BApZ#vR3v-AaQkai7fhF4VKU6tgGsoZMdQMPo-k5B1bnl8s8

Smarter Data Science: Succeeding with Enterprise-Grade Data and AI Projects

Enterprise data and AI projects are often scattershot, underbaked, siloed, and not adaptable to predictable business changes. As a result, the vast majority fail. These expensive quagmires can be avoided, and this book explains precisely how.

Data science is emerging as a hands-on tool for not just data scientists, but business professionals as well. Managers, directors, IT leaders, and analysts must expand their use of data science capabilities for the organization to stay competitive. Smarter Data Science helps them achieve their enterprise-grade data projects and AI goals. It serves as a guide to building a robust and comprehensive information architecture program that enables sustainable and scalable AI deployments.

When an organization manages its data effectively, its data science program becomes a fully scalable function that’s both prescriptive and repeatable. With an understanding of data science principles, practitioners are also empowered to lead their organizations in establishing and deploying viable AI. They employ the tools of machine learning, deep learning, and AI to extract greater value from data for the benefit of the enterprise.

By following a ladder framework that promotes prescriptive capabilities, organizations can make data science accessible to a range of team members, democratizing data science throughout the organization. Companies that collect, organize, and analyze data can move forward to additional data science achievements:

Improving time-to-value with infused AI models for common use cases

Optimizing knowledge work and business processes

Utilizing AI-based business intelligence and data visualization

Establishing a data topology to support general or highly specialized needs

Successfully completing AI projects in a predictable manner

Coordinating the use of AI from any compute node. From inner edges to outer edges: cloud, fog, and mist computing

When they climb the ladder presented in this book, businesspeople and data scientists alike will be able to improve and foster repeatable capabilities. They will have the knowledge to maximize their AI and data assets for the benefit of their organizations.

Archive: No archive

Formats: pdf

File Size: 4.28 MB

Print Length: 304 pages

Publication Date: May 5, 2020

https://mega.nz/file/FXwGwYYD#yCg2cyfJ98n1lk7w2ntCH_S58h99ovkTQAmBVdK0wMM

Mastering Microsoft Teams: End User Guide to Practical Usage, Collaboration, and Governance

Do you need to learn how to use Microsoft Teams? Are you questioning how to drive user adoption, govern content, and manage access for your Teams deployment? Either way, Mastering Microsoft Teams is your one-stop-shop to learning everything you need to know to find success with Microsoft Teams.

Microsoft’s new chat-based collaboration software has many rich features that enable teams to be more efficient, and save valuable time and resources. However, as with all software, there is a learning curve and pitfalls that should be avoided.

Begin by learning the core components and use cases for Teams. From there the authors guide you through ideas to create governance and adoption plans that make sense for your organization or customer. Wrap up with an understanding of features and services in progress, and a road map to the future of the product.

What You'll Learn

Implement, use, and manage Microsoft Teams

Understand how Teams drives productivity and engagement by combining the functionality of Microsoft Groups, SharePoint, OneDrive, Outlook, and other services in one location

Govern, explain, and use Teams in your organization

Know the pitfalls to avoid that may create challenges in your usage of Teams

Become familiar with the functionality and components of Teams via walkthroughs, including opportunities for automating business processes in Teams

Archive: No archive

Formats: pdf

File Size: 6 MB

Print Length: 304 pages

Publication Date: August 20, 2018

https://mega.nz/file/8WI0WT4T#bHUSNTbN_UrDbk55zj3razmYaizDqp0RLpA4g03wnco

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