Niranjanamurthy M – författare

Blockchain is an emerging platform for developing decentralized applications and data storage, over and beyond its role as a platform for cryptocurrencies. This reference text provides a comprehensive discussion on blockchain technology from research and application perspective. Discusses different approaches for building distributed applications (DAPPS). Provides detailed listing and discussion of blockchain technology applications in solving real life problems. Covers proof of work (PoW) based blockchain consensus, and proof of stake (PoS) based blockchain consensus. Discusses blockchain algorithms including practical byzantine fault tolerance (PBFT) and simplified byzantine fault tolerance (SBFT). It comprehensively covers important topics including blockchain consensus algorithms, Ethereum, Hyperledger, blockchain scalability, smart contracts with solidity, ERC20 standards, building DApp with Golang, building DApp using Hyperledger, building PoCs with Hyperledger fabric, blockchain as a server, blockchain security and privacy. The text will serve as a useful text for senior undergraduate and graduate students in interdisciplinary areas including electronics and communications engineering, electrical engineering, computer science, and information technology.

This book provides a comprehensive discussion of deep learning (DL) in medical and healthcare applications, including the fundamentals and current advances in medical image analysis, DL methods for medical image analysis, and DL-based clinical computer-aided diagnosis systems. It further presents algorithms, models, software, and tools in the field of bioinformatics.This book:Presents mathematical principles of DL algorithms such as convolutional neural networks and recurrent neural networksDiscusses applications of DL such as hyperparameter optimization and multimodal DL for bioinformaticsShowcases how algorithms are applied to a broad range of application areas, including microscopy and pathologyCovers DL techniques such as deep feedforward networks, sequence modeling, and convolutional networksExamines the importance of deep learning in biomedical image processing and enhancing biological diagnosisIt will serve as an ideal reference text for senior undergraduates, graduate students, and academic researchers in the areas such as electrical engineering, electronics, and communications engineering, computer engineering, and information technology.

Blockchain is an emerging platform for developing decentralized applications and data storage, over and beyond its role as a platform for cryptocurrencies. This reference text provides a comprehensive discussion on blockchain technology from research and application perspective. Discusses different approaches for building distributed applications (DAPPS). Provides detailed listing and discussion of blockchain technology applications in solving real life problems. Covers proof of work (PoW) based blockchain consensus, and proof of stake (PoS) based blockchain consensus. Discusses blockchain algorithms including practical byzantine fault tolerance (PBFT) and simplified byzantine fault tolerance (SBFT). It comprehensively covers important topics including blockchain consensus algorithms, Ethereum, Hyperledger, blockchain scalability, smart contracts with solidity, ERC20 standards, building DApp with Golang, building DApp using Hyperledger, building PoCs with Hyperledger fabric, blockchain as a server, blockchain security and privacy. The text will serve as a useful text for senior undergraduate and graduate students in interdisciplinary areas including electronics and communications engineering, electrical engineering, computer science, and information technology.

The main goal of the book is to explore the idea behind data modeling in smart agriculture using information and communication technologies and tools to make agricultural practices more functional, fruitful and profitable. The research in the book looks at the likelihood and level of use of implemented technological components with regard to the adoption of different precision agricultural technologies. To identify the variables affecting farmers’ choices to embrace more precise technology, zero-inflated Poisson and negative binomial count data regression models were utilized. Outcomes from the count data analysis of a random sample of various farm operators show that various aspects, including farm dimension, farmer demographics, soil texture, urban impacts, farmer position of liabilities, and position of the farm in a state, were significantly associated with the approval severity and likelihood of precision farming technologies. Farm management information systems (FMIS) have constantly advanced in complexity as they have incorporated new technology, the most recent of which is the internet. However, few FMIS have fully tapped into the internet’s possibilities, and the newly developing idea of precision agriculture receives little or no support in the FMIS that are now being sold. FMIS for precision agriculture must meet a few more criteria beyond those of regular FMIS, which increases the technological complexity of these systems’ deployment in a number of ways. In order to construct an FMIS that meet these extra needs, the authors here evaluated various cutting-edge web-based methods. The goal was to determine the requirements that precision agriculture placed on FMIS.

This book is a vital resource for anyone looking to understand the essential role of graph theory as the unifying thread that connects and provides innovative solutions across a wide spectrum of modern computer science disciplines. Graph theory is a traditional mathematical discipline that has evolved as a basic tool for modeling and analyzing the complex relationships between different technological landscapes. Graph theory helps explain the semantic and syntactic relationships in natural language processing, a technology behind many businesses. Disciplinary and industry developments are seeing a major transition towards more interconnected and data-driven decision-making, and the application of graph theory will facilitate this transition. Disciplines such as parallel and distributive computing will gain insights into how graph theory can help with resource optimization and job scheduling, creating considerable change in the design and development of scalable systems. This book provides comprehensive coverage of how graph theory acts as the thread that connects different areas of computer science to create innovative solutions to modern technological problems. Using a multi-faceted approach, the book explores the fundamentals and role of graph theory in molding complex computational processes across a wide spectrum of computer science.