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The book explains the power, and routing optimization in underwater sensor networks, advanced cross-layer framework,... Læs mere
This book talks about science and applications of Large Language Models (LLMs). You'll discover the common thread that drives some of the most... Læs mere
Are you ready to take your programming skills to the next level? Look no further! "The Problem Solver's Guide To Coding" is the ultimate guide that will... Læs mere
This book considers the four essential cores of game design: Mechanics, Economy, Narrative, and Aesthetics. It discusses all four... Læs mere
This book begins by discussing the fundamentals of artificial intelligence, the internet of things, and their convergence. It then covers techniques, algorithms, and methods of analysing and processing data over the artificial intelligence of things.
A blockchain-based distributed framework can be used for automobiles in the smart city. This framework can include a novel miner node selection algorithm... Læs mere
This book provides a compact but comprehensive treatment that guides readers through the C programming language with Microsoft® Visual Studio®. The author uses his extensive classroom experience to guide readers toward deeper understanding of key concepts of the C language.
The ever-increasing importance of social coding platforms has made software ecosystems indispensable to software practitioners, in commercial as well as... Læs mere
This book demonstrates the metaheuristic methodologies that apply to maximum diversity problems to solve them. In... Læs mere
These include math-based challenges in chapter three, number-based challenges in chapter four, string-based challenges in chapter five, game-based challenges in chapter six, count-based challenges in chapter seven, and miscellaneous challenges in chapter eight.
This book presents recent findings and results concerning the solutions of especially finite state-space Markov decision problems and determining Nash equilibria for related stochastic games with average and total expected discounted reward payoffs.