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Machine Learning in Biomolecular Simulations
Machine learning methods such as neural networks, non-linear dimensionality reduction techniques, random forests and others meet in this research topic with biomolecular simulations. The authors of eight articles applied these methods to analyze simulation results, accelerate simulations or to make molecular mechanics force fields more accurate.
Autonomous Vehicles and Systems
This book captures multidisciplinary research encompassing various facets of autonomous vehicle systems (AVS) research and developments. The AVS field is rapidly moving towards realization with numerous advances continually reported. The contributions to this field come from widely varying branches of knowledge, making it a truly multidisciplinary area of research and development. The topics covered in the book include: AI and deep learning for AVS Autonomous steering through deep neural networks Adversarial attacks and defenses on autonomous vehicles Gesture recognition for vehicle control Multi-sensor fusion in autonomous vehicles Teleoperation technologies for AVS Simulation and game theoretic decision making for AVS Path following control system design for AVS Hybrid cloud and edge solutions for AVS Ethics of AVS
Parallel Computing: Technology Trends
The year 2019 marked four decades of cluster computing, a history that began in 1979 when the first cluster systems using Components Off The Shelf (COTS) became operational. This achievement resulted in a rapidly growing interest in affordable parallel computing for solving compute intensive and large scale problems. It also directly lead to the founding of the Parco conference series. Starting in 1983, the International Conference on Parallel Computing, ParCo, has long been a leading venue for discussions of important developments, applications, and future trends in cluster computing, parallel computing, and high-performance computing. ParCo2019, held in Prague, Czech Republic, from 10 – ...
Digital Phenomenology
Digital Phenomenology is a report on the philosophical theory of everything. From the first principle, digital philosophy and post-Keynesian economics are proved. The report is technical and aimed toward philosophers, mathematicians, computer scientists, physicists, economists, and political scientists.
Artificial Intelligence For Science: A Deep Learning Revolution
This unique collection introduces AI, Machine Learning (ML), and deep neural network technologies leading to scientific discovery from the datasets generated both by supercomputer simulation and by modern experimental facilities.Huge quantities of experimental data come from many sources — telescopes, satellites, gene sequencers, accelerators, and electron microscopes, including international facilities such as the Large Hadron Collider (LHC) at CERN in Geneva and the ITER Tokamak in France. These sources generate many petabytes moving to exabytes of data per year. Extracting scientific insights from these data is a major challenge for scientists, for whom the latest AI developments will be essential.The timely handbook benefits professionals, researchers, academics, and students in all fields of science and engineering as well as AI, ML, and neural networks. Further, the vision evident in this book inspires all those who influence or are influenced by scientific progress.
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The Pacific Symposium on Biocomputing (PSB) 2012 is an international, multidisciplinary conference for the presentation and discussion of current research in the theory and application of computational methods in the problems of biological significance. Presentations are rigorously peer-reviewed and are published in an archival proceedings volume. PSB 2012 will be held on January 3 – 7, 2012 in Kohala Coast, Hawaii. Tutorials and workshops will be offered prior to the start of the conference. PSB 2012 will bring together top researchers from the US, the Asian Pacific nations, and countries around the world to exchange research results and address open issues in all aspects of computational...
