Colonel Jake McCrea's mission is to get Dr. Jessie Stevens and her bioterrorism team in the air. The clock is ticking down to a thermal meltdown at the DEEP lab in Mexico. A terrorist group has attacked the facility and only Jessie knows the combination to the GP2 virus and vaccine.Jessie wanted the deadly level four virus to burn in the lab until she learned that GP2 may have been secretly cultivated in Florida. As tension flares into attraction with Jake, Jessie won't fall for another man in uniform, even if Jake is the bravest man she's ever met. Still, she's having a tough time concentrating on a killer virus, instead of Jake's killer smile.Jake doesn't want to take Jessie into a firefight, but she's the only survivor of the DEEP lab scientists with an immunity to GP2. He knows Jessie is stubborn and tough as nails, but can she pull the pin on a thermal device to destroy the virus? With his feelings getting in the way of his mission, could he allow Jessie to put her life in danger?

The Contemporary Introduction to Deep Reinforcement Learning that Combines Theory and Practice Deep reinforcement learning (deep RL) combines deep learning and reinforcement learning, in which artificial agents learn to solve sequential decision-making problems. In the past decade deep RL has achieved remarkable results on a range of problems, from single and multiplayer games—such as Go, Atari games, and DotA 2—to robotics. Foundations of Deep Reinforcement Learning is an introduction to deep RL that uniquely combines both theory and implementation. It starts with intuition, then carefully explains the theory of deep RL algorithms, discusses implementations in its companion software library SLM Lab, and finishes with the practical details of getting deep RL to work. This guide is ideal for both computer science students and software engineers who are familiar with basic machine learning concepts and have a working understanding of Python. Understand each key aspect of a deep RL problem Explore policy- and value-based algorithms, including REINFORCE, SARSA, DQN, Double DQN, and Prioritized Experience Replay (PER) Delve into combined algorithms, including Actor-Critic and Proximal Policy Optimization (PPO) Understand how algorithms can be parallelized synchronously and asynchronously Run algorithms in SLM Lab and learn the practical implementation details for getting deep RL to work Explore algorithm benchmark results with tuned hyperparameters Understand how deep RL environments are designed Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.

Laboratory Design Guide 3rd edition is a complete guide to the complex process of laboratory design and construction. With practical advice and detailed examples, it is an indispensable reference for anyone involved in building or renovating laboratories. In this working manual Brian Griffin explains how to meet the unique combination of requirements that laboratory design entails. Considerations range from safety and site considerations to instrumentation and special furniture, and accommodate the latest laboratory practices and the constant evolution of science. Case studies from around the world illustrate universal principles of good design while showing a variety of approaches. Revised throughout for this new edition, the book contains a brand new chapter on the role of the computer, covering topics such as the virtual experiment, hot desking, virtual buildings and computer-generated space relationship diagrams. There are also 10 new international case studies, including the Kadoorie Biological Sciences Building at the University of Hong Kong.

It is the year 2312, and the City covers most of the planet. Street kid David North is a “Super,” but his power – moving strings, wires, and similar things with his mind – isn’t entirely under his control. During a violent altercation with one of the City’s notorious gangs, he is saved from near death by a couple of Super teenagers who are students of an underground scientific research and training facility called Project Arete. David immediately feels a curious connection with one of his saviors—Sarah, a young woman with glowing green bionic eyes. During his recovery at Project Arete’s hospital, David is given the opportunity to join PA and, warily, he takes it. Perhaps there, finally off the City’s streets, he could learn more about his power and how to control it . . . and more about Sarah. But there is someone who doesn’t want David to get too close to her. And even though he is making lasting friendships, as David spends more time at PA, he discovers things are not exactly what they seem. An ancient mystery is slowly unfurling, and when David finds himself caught up in a 3000-year-old betrayal, he must confront impossible choices to protect the ones he loves. But will his choices doom them all to repeat the mistakes of the ancient past? The first book in the action-packed Keystone Trilogy, Return takes you deep inside a world where no choice is easy, no answer is the right one, and every step you take comes with great responsibility.

Explore the mathematical computations and algorithms for image processing using popular Python tools and frameworks. Key FeaturesPractical coverage of every image processing task with popular Python librariesIncludes topics such as pseudo-coloring, noise smoothing, computing image descriptorsCovers popular machine learning and deep learning techniques for complex image processing tasksBook Description Image processing plays an important role in our daily lives with various applications such as in social media (face detection), medical imaging (X-ray, CT-scan), security (fingerprint recognition) to robotics & space. This book will touch the core of image processing, from concepts to code using Python. The book will start from the classical image processing techniques and explore the evolution of image processing algorithms up to the recent advances in image processing or computer vision with deep learning. We will learn how to use image processing libraries such as PIL, scikit-mage, and scipy ndimage in Python. This book will enable us to write code snippets in Python 3 and quickly implement complex image processing algorithms such as image enhancement, filtering, segmentation, object detection, and classification. We will be able to use machine learning models using the scikit-learn library and later explore deep CNN, such as VGG-19 with Keras, and we will also use an end-to-end deep learning model called YOLO for object detection. We will also cover a few advanced problems, such as image inpainting, gradient blending, variational denoising, seam carving, quilting, and morphing. By the end of this book, we will have learned to implement various algorithms for efficient image processing. What you will learnPerform basic data pre-processing tasks such as image denoising and spatial filtering in PythonImplement Fast Fourier Transform (FFT) and Frequency domain filters (e.g., Weiner) in PythonDo morphological image processing and segment images with different algorithmsLearn techniques to extract features from images and match imagesWrite Python code to implement supervised / unsupervised machine learning algorithms for image processingUse deep learning models for image classification, segmentation, object detection and style transferWho this book is for This book is for Computer Vision Engineers, and machine learning developers who are good with Python programming and want to explore details and complexities of image processing. No prior knowledge of the image processing techniques is expected.

Strictly off limits to the public, Plum Island is home to virginal beaches, cliffs, forests, ponds -- and the deadliest germs that have ever roamed the planet. Lab 257 blows the lid off the stunning true nature and checkered history of Plum Island. It shows that the seemingly bucolic island in the shadow of New York City is a ticking biological time bomb that none of us can safely ignore. Based on declassified government documents, in-depth interviews, and access to Plum Island itself, this is an eye-opening, suspenseful account of a federal government germ laboratory gone terribly wrong. For the first time, Lab 257 takes you deep inside this secret world and presents startling revelations on virus outbreaks, biological meltdowns, infected workers, the periodic flushing of contaminated raw sewage into area waters, and the insidious connections between Plum Island, Lyme disease, and the deadly West Nile virus. The book also probes what's in store for Plum Island's new owner, the Department of Homeland Security, in this age of bioterrorism. Lab 257 is a call to action for those concerned with protecting present and future generations from preventable biological catastrophes.

This book includes the peer-reviewed proceedings of the 2nd International Conference on Information Control, Electrical Engineering, and Rail Transit (ICEERT 2022). This book provides the advanced research results of transportation and covers the main research fields of information control, traffic information engineering, and control, intelligent transit, logistics, etc. This book aims to promote a new green and intelligent mode of rail transit between scholars from the top universities, research centers, and high-tech enterprises around the world, which is beneficial to researchers and practitioners in mechanical engineering.