Super-Recursive Algorithms
New discoveries about algorithms are leading scientists beyond the Church-Turing Thesis, which governs the "algorithmic universe" and asserts the conventionality of recursive algorithms. A new paradigm for computation, the super-recursive algorithm, offers promising prospects for algorithms of much greater computing power and efficiency. Super-Recursive Algorithms provides an accessible, focused examination of the theory of super-recursive algorithms and its ramifications for the computer industry, networks, artificial intelligence, embedded systems, and the Internet. The book demonstrates how these algorithms are more appropriate as mathematical models for modern computers, and how these algorithms present a better framework for computing methods in such areas as numerical analysis, array searching, and controlling and monitoring systems. In addition, a new practically-oriented perspective on the theory of algorithms, computation, and automata, as a whole, is developed. Problems of efficiency, software development, parallel and distributed processing, pervasive and emerging computation, computer architecture, machine learning, brain modeling, knowledge discovery, and intelligent systems are addressed.
كتب مشابهة
Scalable data management for future hardware
Presents the results of the DFG priority program on scalable data management for future hardware. It details requirements and solutions of how modern and future hardware architectures can be leveraged to address the challenges in modern data management.the nine chapters of the book present a wide range of data management architectures in conjunction with current hardware developments, often related to applications in data analytics or machine learning. they cover topics such as hardware-accelerated query or event processing on FPGA, GPU, and multicore CPUs, scalable data management in data center networks or on modern memory and storage technologies, and operating system support.
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Fundamentals of manufacturing engineering using digital visualization
Offers a guide to core principles and practices of manufacturing engineering. It covers the design of, together with technological and measurement issues for, technical systems. Locating charts and setup schemes describing different machining processes are included. Concepts of product quality, with a focus on accuracy indicators, machining accuracy, roughness, and the impact of surface quality on exploitation properties are also explained. Furthermore, key machining methods, including turning, milling, hole machining, grinding, and gear machining, are analyzed in depth, covering their principles, applications, and techniques. The book is enriched by QR codes, linking to a mobile application presenting additional information about the content, for an interactive and extended learning experience. It also uses illustrations visualized with digital tools to promote a better understanding of the concepts.
AI in drug discovery
Constitutes the refereed proceedings of the First international workshop on ai in Drug Discovery, AIDD 2024, held as a part of the 33rd International Conference on Artificial Neural Networks, ICANN 2024, in Lugano, Switzerland, on September 19, 2024. These papers focus on various aspects of the rapidly evolving field of Artificial Intelligence (AI)-driven drug discovery in chemistry, including Big Data and advanced Machine Learning, eXplainable AI (XAI), Chemoinformatics, Use of deep learning to predict molecular properties, Modeling and prediction of chemical reaction data and Generative models.
