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Atkins’ physical chemistry
Widely acknowledged by both students and lecturers around the globe to be the textbook of choice for studying physical chemistry. Now in its twelfth edition, the text has been enhanced with additional learning features, and the writing style has been refreshed to resonate with the modern student.
Artificial intelligence in drug design
Looks at applications of artificial intelligence (AI), machine learning (ML), and deep learning (DL) in drug design. The chapters in this book describe how AI/ML/DL approaches can be applied to accelerate and revolutionize traditional drug design approaches such as: structure- and ligand-based, augmented and multi-objective de novo drug design, SAR and big data analysis, prediction of binding/activity, ADMET, pharmacokinetics and drug-target residence time, precision medicine and selection of favorable chemical synthetic routes. How broadly are these approaches applied and where do they maximally impact productivity today and potentially in the near future.
Antibiotics Simplified
Designed to bridge knowledge gained in basic sciences courses with clinical practice in infectious diseases. This practical text reviews basic microbiology and how to approach the pharmacotherapy of a patient with a presumed infection. It also contains concise Drug Class Reviews with an explanation of the characteristics of various classes of antibacterial drugs and antifungal drugs.
An ecological and societal approach to biological control
Biological control is among the most promising methods for control of pests (including vectors), diseases and weeds. In this book ecological and societal aspects are for the first time treated together. In an ecological approach the aim is to evaluate the significance of certain biological properties like biodiversity and natural habitats. Also, it is important to see biological control from an organic (or ecological) farming point of view. In a societal approach terms like ‘consumer’s attitude’, ‘risk perception’, ‘learning and education’ and ‘value triangle’ are recognised as significant for biological production and human welfare.
Algal Toxins : Nature, Occurrence, Effect and Detection
This volume contains the lectures and seminars given at the NATO Advanced Study Institute on “Sensor Systems for Biological Threads: The Algal Toxins Case”, held in Pisa, Italy in October, 2007. Algae can form heavy growths in ponds, lakes, reservoirs and sl- moving rivers throughout the world; algae can house toxins which are - ually released into water when the cells rupture or die. Hundreds of toxins have been identified so far. Detection methods, including rapid screening, have been developed to help us learning more about them, especially to find out which toxins are a real threat for people and what conditions encourage their production and accumulation. Early detection of algal toxins is an - portant aspect for public safety and natural environment, and significant efforts are underway to develop effective and reliable tools that can be used for this purpose.
Algal Toxins : Nature, Occurrence, Effect and Detection
This volume contains the lectures and seminars given at the NATO Advanced Study Institute on “Sensor Systems for Biological Threads: The Algal Toxins Case”, held in Pisa, Italy in October, 2007. Algae can form heavy growths in ponds, lakes, reservoirs and sl- moving rivers throughout the world; algae can house toxins which are - ually released into water when the cells rupture or die. Hundreds of toxins have been identified so far. Detection methods, including rapid screening, have been developed to help us learning more about them, especially to find out which toxins are a real threat for people and what conditions encourage their production and accumulation. Early detection of algal toxins is an - portant aspect for public safety and natural environment, and significant efforts are underway to develop effective and reliable tools that can be used for this purpose.
AI in disease detection : Advancements and applications
Discusses the integration of artificial intelligence to revolutionize disease detection approaches, with case studies of AI in disease detection as well as insight into the opportunities and challenges of AI in healthcare as a whole. The book explores a wide range of individual AI components such as computer vision, natural language processing, and machine learning as well as the development and implementation of AI systems for efficient practices in data collection, model training, and clinical validation.
Advances in cognitive neurodynamics ICCN 2007; Proceedings of the International conference on cognitive neurodynamics - 2007
Contains the Proceedings of the 1st International Conference on Cognitive Neurodynamics held in Shanghai, November 17-21, 2007. The participants were treated to an exciting and stimulating conference that left everyone with an enthusiastic vision for the future of the field. The latest important progress was covered by 13 mini-symposia including: Models of Mental Disorders; Cognitive Machines; Dynamics in learning and memory; Central nervous system synchronization; Neuroinformatics; Cognitive Computational Modeling of Human Language Processing; Cognitive Neurodynamics of Attention; Bottom-Up and Top-Down; Brain Networks; From Anatomy to Dynamics; Translational Cognitive Neuroimaging; K-sets; Theory and Applications; Advanced Signal Processing Techniques for Brain Data Analysis; Visual cortex: information processing and dynamics; Dynamics of Firing Patterns and Synchronization in Neuronal Systems.
Leveraging Data Science for Global Health
Explores ways to leverage information technology and machine learning to combat disease and promote health, especially in resource-constrained settings. It focuses on digital disease surveillance through the application of machine learning to non-traditional data sources.
501 Math Word Problems
Contains only word problems - the kinds you encounter at school and on high stakes tests. Gaining familiarity with this specific question type is a proven technique for increasing test scores. The Skill Builder in Focus method provides the targeted practice on these questions necessary to attain higher scores. Questions are divided into six chapters: algebra, geometry, fractions, percents, decimals, and miscellaneous math. Within each chapter, questions move from easy to advanced, giving test-takers the opportunity to gain confidence in each math area. Each chapter contains questions, answers, and detailed explanations to reinforce learning and understanding. Diagrams and useful terminology help clarify math rules for effective studying and retention.
Mathematical Linguistics
Mathematical Linguistics introduces the mathematical foundations of linguistics to computer scientists, engineers, and mathematicians interested in natural language processing. The book presents linguistics as a cumulative body of knowledge from the ground up, with no prior knowledge of linguistics being assumed, covering more than the average two-semester introductory course in linguistics.This comprehensive, reader-friendly volume offers readers a high-level orientation, discussing the foundations of the field and presenting both the classical work and the most recent results. It covers an extremely rich array of topics including not only syntax and semantics but also phonology and morphology, probabilistic approaches, complexity, learnability, and the analysis of speech and handwriting.
Managed Software Evolution
This open access book presents the outcomes of the “Design for Future – Managed Software Evolution” .The different lifecycles of software and hardware platforms lead to interoperability problems in such systems. Instead of separating the development, adaptation and evolution of software and its platforms, as well as aspects like operation, monitoring and maintenance, they should all be integrated into one overarching process. Accordingly, the book is split into three major parts, the first of which includes an introduction to the nature of software evolution, followed by an overview of the specific challenges and a general introduction to the case studies used in the project. The second part of the book consists of the main chapters on knowledge carrying software, and cover tacit knowledge in software evolution, continuous design decision support, model-based round-trip engineering for software product lines, performance analysis strategies, maintaining security in software evolution, learning from evolution for evolution, and formal verification of evolutionary changes. In turn, the last part of the book presents key findings and spin-offs. The individual chapters there describe various case studies, along with their benefits, deliverables and the respective lessons learned. An overview of future research topics rounds out the coverage.
Machine-learning-assisted intelligent processing and optimization of complex systems
Focuses on the most recent developments in intelligent optimization methods and their applications in various test cases. The reprint covers various topics, including distributed multiagent modeling, metaheuristic algorithms, multisource data fusion, mobile computing and mobile sensing, machine learning-based intelligent processing for modeling complex manufacturing systems, and data-driven intelligent modeling
Machine Learning Techniques and Analytics for Cloud Security
covers new methods, surveys, case studies, and policy with almost all machine learning techniques and analytics for cloud security solutions
Machine Learning Refined : Foundations, Algorithms, and Applications
Provides students with the fundamental knowledge and practical tools needed to conduct research and build data-driven products. The authors prioritize geometric intuition and algorithmic thinking, and include detail on all the essential mathematical prerequisites, to offer a fresh and accessible way to learn. Practical applications are emphasized, with examples from disciplines including computer vision, natural language processing, economics, neuroscience, recommender systems, physics, and biology.
Machine learning methods for reverse engineering of defective structured surfaces
Pascal Laube presents machine learning approaches for three key problems of reverse engineering of defective structured surfaces: parametrization of curves and surfaces, geometric primitive classification and inpainting of high-resolution textures. The proposed methods aim to improve the reconstruction quality while further automating the process. The contributions demonstrate that machine learning can be a viable part of the CAD reverse engineering pipeline.
Machine learning in healthcare : Fundamentals and recent applications
Discusses how to build various ML algorithms and how they can be applied to improve healthcare systems. Healthcare applications of AI are innumerable: medical data analysis, early detection and diagnosis of disease, providing objective-based evidence to reduce human errors, curtailing inter- and intra-observer errors, risk identification and interventions for healthcare management, real-time health monitoring, assisting clinicians and patients for selecting appropriate medications, and evaluating drug responses. Extensive demonstrations and discussion on the various principles of machine learning and its application in healthcare is provided, along with solved examples and exercises.
Machine Learning in Computer Vision
The goal of this book is to address the use of several important machine learning techniques into computer vision applications. An innovative combination of computer vision and machine learning techniques has the promise of advancing the field of computer vision, which contributes to better understanding of complex real-world applications. The effective usage of machine learning technology in real-world computer vision problems requires understanding the domain of application, abstraction of a learning problem from a given computer vision task, and the selection of appropriate representations for the learnable (input) and learned (internal) entities of the system. In this book, we address all these important aspects from a new perspective: that the key element in the current computer revolution is the use of machine learning to capture the variations in visual appearance, rather than having the designer of the model accomplish this. As a bonus, models learned from large datasets are likely to be more robust and more realistic than the brittle all-design models.
Machine Learning for Multimedia Content Analysis
Challenges in complexity and variability of multimedia data have led to revolutions in machine learning techniques. Multimedia data, such as digital images, audio streams and motion video programs, exhibit richer structures than simple, isolated data items. A number of pixels in a digital image collectively conveys certain visual content to viewers. A TV video program consists of both audio and image streams that unfold the underlying story. To recognize the visual content of a digital image, or to understand the underlying story of a video program, we may need to label sets of pixels or groups of image and audio frames jointly.
Machine learning for data streams : With practical examples in MOA
The book first offers a brief introduction to the topic, covering big data mining, basic methodologies for mining data streams, and a simple example of MOA. More detailed discussions follow, with chapters on sketching techniques, change, classification, ensemble methods, regression, clustering, and frequent pattern mining. Most of these chapters include exercises, an MOA-based lab session, or both. Finally, the book discusses the MOA software, covering the MOA graphical user interface, the command line, use of its API, and the development of new methods within MOA.
