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Obsidian
Obsidian was long valued by ancient peoples as a raw material for producing stone tools, and archaeologists have increasingly come to view obsidian studies as a crucial aid in understanding the past. Steven Shackley now shows how the geochemical and contextual analyses of archaeological obsidian can be applied to the interpretation of social and economic organization in the ancient Southwest. This book, the capstone of decades of investigation, integrates a wealth of obsidian research in one volume. It covers advances in analytical chemistry and field petrology that have enhanced our understanding of obsidian source heterogeneity, presents the most recent data on and interpretations of archa...
Explainable AI: Interpreting, Explaining and Visualizing Deep Learning
The development of “intelligent” systems that can take decisions and perform autonomously might lead to faster and more consistent decisions. A limiting factor for a broader adoption of AI technology is the inherent risks that come with giving up human control and oversight to “intelligent” machines. For sensitive tasks involving critical infrastructures and affecting human well-being or health, it is crucial to limit the possibility of improper, non-robust and unsafe decisions and actions. Before deploying an AI system, we see a strong need to validate its behavior, and thus establish guarantees that it will continue to perform as expected when deployed in a real-world environment. ...
Machine Learning Meets Quantum Physics
Designing molecules and materials with desired properties is an important prerequisite for advancing technology in our modern societies. This requires both the ability to calculate accurate microscopic properties, such as energies, forces and electrostatic multipoles of specific configurations, as well as efficient sampling of potential energy surfaces to obtain corresponding macroscopic properties. Tools that can provide this are accurate first-principles calculations rooted in quantum mechanics, and statistical mechanics, respectively. Unfortunately, they come at a high computational cost that prohibits calculations for large systems and long time-scales, thus presenting a severe bottlenec...
Computer Simulations in Molecular Biology
This book covers a range of topics in quantum mechanics and molecular dynamics simulation, including computational modeling and machine learning approaches. The book also provides a Python GUI and tutorials for simulating molecular biological systems and presents case studies of quantum mechanics simulations for predicting electronic properties. Its pedagogical formatting makes it easy for students to understand and follow and has been praised for providing clear and detailed explanations of complex topics. This book is ideal for graduate students and researchers in theoretical and computational biophysics, physics, chemistry, and materials science, as well as postgraduates in applied mathematics, computer science, and bioinformatics.
Hyperordered Structures in Materials
This book introduces characterizations of hyperordered structures using latest quantum beam technologies, the advanced theoretical methods for understanding the roles of the structures, and the state-of-the-arts materials containing the structures. In this book, the authors focus on the importance of defect complexes to improve functionality of crystals and that of orders of network structures to improve functionality of glass materials. These features can be regarded as interphases between perfect crystals and perfect amorphous, and they are the key factor for the evolution of materials science to a new dimension. The authors call such interphases "hyperordered structures" in this book. This is the first book that comprehensively summarizes glass science, defect science, and quantum beam science. It is valuable not only for active researchers in industry and academia but also graduate students.
