Bhuvan Unhelkar

Hari Mohan Pandey

Ankur Choudhary

Arun Prakash Agrawal

This volume comprises the select peer-reviewed proceedings of the International Conference on Advances and Applications of Artificial Intelligence and Machine Learning 2022 (ICAAAIML 2022). It aims to provide a comprehensive and broad-spectrum picture of state-of-the-art research and development in the areas of artificial intelligence, machine learning, deep learning, and their advanced applications in computer vision and blockchain. It also covers research in core concepts of computers, intelligent system design and deployment, real-time systems, WSN, sensors and sensor nodes, software engineering, image processing, and cloud computing. This volume will provide a valuable resource for those in academia and industry.

Proceedings of ICAAAIML 2022

Advances and Applications of Artificial Intelligence & Machine Learning

Keith Sherringham

Whether it is the turnaround of a sports team to win a championship, bettering a community, remediation of business, or adoption and adaption to digital business, it is having us do things differently which brings sustainable change. This was seen throughout 2020 during the COVID-19 global pandemic. People from around the world stood up and helped each other, shared their time, goods, skills, and expertise which collectively crafted and shaped our response to COVID. Our environment was changed, capacities and capabilities implemented, behaviors emerged, and outcomes were managed. Interests and values were aligned and as empowered individuals having ownership with pride in who we are and what we do, we adopted and adapted. Knowing the issue, the importance to us, what we needed to do, and where to get help, enabled us to better ourselves and those around us. For the decisions made, we empowered and supported with variations to circumstances as required of us. This book provides the hands-on of “fixing the pipes and helping people” to capacity and capability build for the crafting and shaping of the emergent behaviors needed through our aligned interest and values with the empowered emotional ownership: “I do good work, change is coming, help me with the change, and I can do more.”

Adoption and Adaption in Digital Business

The Art of Agile Practice: A Composite Approach for Projects and Organizations presents a consistent, integrated, and strategic approach to achieving "Agility" in your business. Transcending beyond Agile as a software development method, it covers the gamut of methods in an organization—including business processes, governance standards, project management, quality management, and business analysis—to show you how to use this composite approach to enhance your ability to adapt and respond to evolving business requirements. The book is divided into three parts: Introduces Agility and identifies the challenges facing organizations in terms of development and maintenance approaches Presents Composite Agile Method and Strategy (CAMS) as a carefully constructed combination of process elements and illustrates its application to development, business management, business analysis, project management, and quality Includes two Agile case studies, a comprehensive index, definitions of key acronyms, and appendices with a current list of Agile methods and interview summaries The book describes relevant metrics for the entire CAMS lifecycle and explains how to embed Agile practices within formal process-maps in projects. Filled with figures, case studies, and tables that illustrate key concepts, the text is ideal for a two- or three-day training course or workshop. It is also suitable for a 13-week education course for higher degree students that includes process discussions and consideration of Agile values at both software and business levels. The chapters are organized to correspond roughly to such lectures with an option to choose from the case study chapters.

A Composite Approach for Projects and Organizations

The Art of Agile Practice

Rajasvaran Logeswaran

The book presents a collection of peer-reviewed articles from the International Conference on Advances and Applications of Artificial Intelligence and Machine Learning - ICAAAIML 2020. The book covers research in artificial intelligence, machine learning, and deep learning applications in healthcare, agriculture, business, and security. This volume contains research papers from academicians, researchers as well as students. There are also papers on core concepts of computer networks, intelligent system design and deployment, real-time systems, wireless sensor networks, sensors and sensor nodes, software engineering, and image processing. This book will be a valuable resource for students, academics, and practitioners in the industry working on AI applications.

Select Proceedings of ICAAAIML 2020

Applications of Artificial Intelligence and Machine Learning

A practical approach to enhancing quality in software models usingUML Version 2.0 "Despite its increasing usage, many companies are not taking thebest advantage of UML and, occasionally, individuals haveexperienced frustration in applying its standards. Perhaps this isbecause they have not yet read this book!" -From the Foreword by Prof. Brian Henderson-Sellers This book presents a practical checklist approach to enhancing thequality of software models created with the Unified ModelingLanguage (UML) Version 2.0. The foundation for quality is set bythe discussion on the nature and creation of UML models. This isfollowed by a demonstration of how to apply verification andvalidation checks to these models with three foci: syntacticalcorrectness, semantic meaningfulness, and aesthetic symmetry. Thequality work is carried out within three distinct yet relatedmodeling spaces: * Model of problem space (MOPS) * Model of solution space (MOSS) * Model of background space (MOBS) Readers can then choose a specific quality approach according totheir roles in their projects. Verification and validation checks are also organized according tothese three modeling spaces, making it easier for the reader tofocus on the appropriate diagrams and quality checks correspondingto their modeling space. In addition, a major element of thispublication is the Strengths, Weaknesses, Objectives, and Traps(SWOT) analysis. This analysis is performed on each UML diagram,enabling readers to fully comprehend these diagrams, theiradvantages and limitations, and the way in which they can be usedin practical projects for modeling. A consistent case study of the Lucky Insurance System is providedthroughout the chapters to illustrate the creation of good qualityUML diagrams, followed by application of quality checks to them.With its emphasis on quality in UML-based projects, this book is anessential resource for all quality professionals, including qualityanalysts, process consultants, quality managers, test designers,and testers.

Verification and Validation for Quality of UML 2.0 Models

Agile is a set of values, principles, techniques, and frameworks for the adaptable, incremental, and efficient delivery of work. Big Data is a rapidly growing field that encompasses crucial aspects of data such as its volume, velocity, variety, and veracity. This book outlines a strategic approach to Big Data that will render a business Agile. It discusses the important competencies required to streamline and focus on the analytics and presents a roadmap for implementing such analytics in business.

Big Data Strategies for Agile Business

This book presents the analysis, design, documentation, and quality of software solutions based on the OMG UML v2.5. Notably it covers 14 different modelling constructs including use case diagrams, activity diagrams, business-level class diagrams, corresponding interaction diagrams and state machine diagrams. It presents the use of UML in creating a Model of the Problem Space (MOPS), Model of the Solution Space (MOSS) and Model of the Architectural Space (MOAS). The book touches important areas of contemporary software engineering ranging from how a software engineer needs to invariably work in an Agile development environment through to the techniques to model a Cloud-based solution.

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