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In den WarenkorbPaperback. Zustand: new. Paperback. In this book I have given an algorithm which works for quadratic equation, cubic equation, quartic equation, quintic equation, ., to n^th degree polynomial equation. You can solve any degree polynomial equation by this algorithm. In this book I have given an exercise depending on quadratic equation, an exercise depending on cubic equation, an exercise depending on quartic equation, an exercise depending on quintic equation and an exercise depending on higher degree polynomial equation to the practice of this algorithm. I have inserted most important questions of quadratic equation, most important questions of cubic equation, most important questions of quartic equation, most important questions of quintic equation and also most important questions of higher than five degree polynomial equation such that your practice be perfect. Polynomial equation is most important for high school student, college, university, all entrance examinations, teachers, competitions, B.A., B.Sc., B.Teck., M.A., M.Sc., M.Teck., Ph.d. I hope this book be a panacea for all the readers of this book .This book is most important for all the branches of science and mathematics.Polynomial equations are used in the following branchesAlgebra, Trigonometry, Calculus, Geometry, Number Theory, Topology, Combinatorics, Applied Mathematics, Dynamical Systems and Differential Equations, Mathematical Physics, Computation, Information Theory and Signal Processing, Probability and Statistics and more. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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In den WarenkorbPaperback. Zustand: new. Paperback. In this book I have given an algorithm which works for quadratic equation, cubic equation, quartic equation, quintic equation, ., to n^th degree polynomial equation. You can solve any degree polynomial equation by this algorithm. In this book I have given an exercise depending on quadratic equation, an exercise depending on cubic equation, an exercise depending on quartic equation, an exercise depending on quintic equation and an exercise depending on higher degree polynomial equation to the practice of this algorithm. I have inserted most important questions of quadratic equation, most important questions of cubic equation, most important questions of quartic equation, most important questions of quintic equation and also most important questions of higher than five degree polynomial equation such that your practice be perfect. Polynomial equation is most important for high school student, college, university, all entrance examinations, teachers, competitions, B.A., B.Sc., B.Teck., M.A., M.Sc., M.Teck., Ph.d. I hope this book be a panacea for all the readers of this book .This book is most important for all the branches of science and mathematics.Polynomial equations are used in the following branchesAlgebra, Trigonometry, Calculus, Geometry, Number Theory, Topology, Combinatorics, Applied Mathematics, Dynamical Systems and Differential Equations, Mathematical Physics, Computation, Information Theory and Signal Processing, Probability and Statistics and more. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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In den WarenkorbPaperback. Zustand: new. Paperback. Despite the remarkable progress witnessed in the last decade in big data utilization and parallel processing techniques, a persistent disparity exists between the capabilities of computer-aided diagnosis systems and the intricacies of practical healthcare scenarios. This disconnection is particularly evident in the complex landscape of artificial intelligence (AI) and IoT innovations within the biomedical realm. The need to bridge this gap and explore the untapped potential in healthcare and biomedical applications has never been more crucial. As we navigate through these challenges, Applications of Parallel Data Processing for Biomedical Imaging offers insights and solutions to reshape the future of biomedical research. The objective of Applications of Parallel Data Processing for Biomedical Imaging is to bring together researchers from both the computer science and biomedical research communities. By showcasing state-of-the-art deep learning and large data analysis technologies, the book provides a platform for the cross-pollination of ideas between AI-based and traditional methodologies. The collaborative effort seeks to have a substantial impact on data mining, AI, computer vision, biomedical research, healthcare engineering, and other related fields. This interdisciplinary approach positions the book as a cornerstone for scholars, professors, and professionals working in software and medical fields, catering to both graduate and undergraduate students eager to explore the evolving landscape of parallel computing, artificial intelligence, and their applications in biomedical research. The topics covered in the book span a diverse range, including heterogeneous computing, biological and molecular computing, AI applications in biomedical imaging, big data processing, and future network architectures for parallel processing. Readers will delve into the frontiers of AI and deep learning in medicine, human biology, and healthcare, exploring machine learning and deep learning-based clinical decision-making systems, biomedical imaging, medical and healthcare education, and more. The book acts as a beacon for those intrigued by the possibilities at the intersection of big data, intelligent IoT, and parallel computing in reshaping the landscape of healthcare, bioinformatics, biomechanics, and biomedical services. Bringing together researchers from the computer science and biomedical research communities, this book offers insights and solutions to reshape the future of biomedical research. The collaborative effort seeks to have a substantial impact on data mining, AI, computer vision, biomedical research, healthcare engineering, and other related fields. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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