Madhusudhan h s (112 résultats)

Etat : As New. Unread book in perfect condition.

Etat : As New. Unread book in perfect condition.

Etat : New.

Etat : New.

Etat : New.

Etat : New.

Etat : New.

PAP. Etat : New. New Book. Shipped from UK. Established seller since 2000.

PAP. Etat : New. New Book. Shipped from UK. Established seller since 2000.

PAP. Etat : New. New Book. Shipped from UK. Established seller since 2000.

Etat : As New. Unread book in perfect condition.

Etat : New.

Etat : New.

Paperback / softback. Etat : New. New copy - Usually dispatched within 4 working days.

Etat : New. 1st edition NO-PA16APR2015-KAP.

Etat : As New. Unread book in perfect condition.

Paperback / softback. Etat : New. New copy - Usually dispatched within 4 working days.

Etat : New. In English.

Etat : New.

Etat : New. 1st edition NO-PA16APR2015-KAP.

Etat : New. In English.

Etat : New.

Paperback. Etat : New. Biomedical engineering is undergoing a transformation because of AI, which is allowing creative solutions that enhance patient outcomes, diagnosis, treatment planning, and healthcare delivery. Artificial Intelligence and Cloud Computing Applications in Biomedical Engineering examines the salient characteristics of AI in biomedical engineering, highlighting its practical applications and new directions. Highlights of the book include:Genome sequence and visualizationThe role of AI and cloud in detection of diseasesNature-inspired algorithms for disease detectionFrameworks for disease classificationWith a focus on designing AI techniques for disease detection, the book explores the role of AI in biomedical engineering. It discusses how machine learning (ML) and deep learning (DL) are at the heart of AI applications in biomedical engineering. ML algorithms, particularly those based on neural networks, enable computers to learn from large datasets, identify patterns, and make predictions or decisions without explicit programming, and implementing ML algorithms is a focus of the book. Another focus is on DL, a subset of ML, and how it uses multi-layered neural networks to achieve high accuracy in such complex tasks as image and speech recognition. Biomedical engineering generates massive amounts of data from medical imaging, genomic sequencing, wearable devices, electronic health records (EHR), and other sources. This book also discusses AI-driven big data analytics, which allows researchers and clinicians to derive from data meaningful insights, aiding in early disease detection, personalized treatment plans, and patient monitoring.…

Etat : New.

Paperback. Etat : New. One of the major developments in the computing field has been cloud computing, which enables users to do complicated computations that local devices are unable to handle. The computing power and flexibility that have made the cloud so popular do not come without challenges. It is particularly challenging to decide which resources to use, even when they have the same configuration but different levels of performance because of the variable structure of the available resources. Cloud data centers can host millions of virtual machines, and where to locate these machines in the cloud is a difficult problem. Additionally, fulfilling optimization needs is a complex problem.Reliable and Intelligent Optimization in Multi-Layered Cloud Computing Architectures examines ways to meet these challenges. It discusses virtual machine placement techniques and task scheduling techniques that optimize resource utilization and minimize energy consumption of cloud data centers. Placement techniques presented can provide an optimal solution to the optimization problem using multiple objectives. The book focuses on basic design principles and analysis of virtual machine placement techniques and task allocation techniques. It also looks at virtual machine placement techniques that can improve quality-of-service (QoS) in service-oriented architecture (SOA) computing. The aims of virtual machine placement include minimizing energy usage, network traffic, economical cost, maximizing performance, and maximizing resource utilization. Other highlights of the book include:Improving QoS and resource efficiencyFault-tolerant and reliable resource optimization modelsA reactive fault tolerance method using checkpointing restartCost and network-aware metaheuristics.Virtual machine scheduling and placementElectricity consumption in cloud data centersWritten by leading experts and researchers, this book provides insights and techniques to those dedicated to improving cloud computing and its services.…

Paperback. Etat : Brand New. 264 pages. 9.18x6.12x9.21 inches. In Stock.

Paperback. Etat : Brand New. 232 pages. 9.19x6.13x9.21 inches. In Stock.

Etat : New. Dr. Madhusudhan H S is currently working as Associate Professor in the Department of computer science and Engineering at Vidyavardhaka College of Engineering, Mysuru, Karnataka, India. He has published scientific research publications in reputed I.

Paperback. Etat : New. Biomedical engineering is undergoing a transformation because of AI, which is allowing creative solutions that enhance patient outcomes, diagnosis, treatment planning, and healthcare delivery. Artificial Intelligence and Cloud Computing Applications in Biomedical Engineering examines the salient characteristics of AI in biomedical engineering, highlighting its practical applications and new directions. Highlights of the book include:Genome sequence and visualizationThe role of AI and cloud in detection of diseasesNature-inspired algorithms for disease detectionFrameworks for disease classificationWith a focus on designing AI techniques for disease detection, the book explores the role of AI in biomedical engineering. It discusses how machine learning (ML) and deep learning (DL) are at the heart of AI applications in biomedical engineering. ML algorithms, particularly those based on neural networks, enable computers to learn from large datasets, identify patterns, and make predictions or decisions without explicit programming, and implementing ML algorithms is a focus of the book. Another focus is on DL, a subset of ML, and how it uses multi-layered neural networks to achieve high accuracy in such complex tasks as image and speech recognition. Biomedical engineering generates massive amounts of data from medical imaging, genomic sequencing, wearable devices, electronic health records (EHR), and other sources. This book also discusses AI-driven big data analytics, which allows researchers and clinicians to derive from data meaningful insights, aiding in early disease detection, personalized treatment plans, and patient monitoring.…

Etat : As New. Unread book in perfect condition.