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Statistical modelling of software source code
This book will focus on utilizing statistical modelling of the software source code, in order to resolve issues associated with the software development processes. Writing and maintaining software source code is a costly business; software developers need to constantly rely on large existing code bases. Statistical modelling identifies the patterns in software artifacts and utilize them for predicting the possible issues. Statistic tool for the software engineer. 2021 Walter de Gruyter GmbH, Berlin/Boston. -
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Strategic Innovation and Sustainable Customer-Centric Growth
Strategic innovation and sustainable customer-centric growth drive long-term success in today's evolving business landscape. Organizations that prioritize innovation adapt to changing market demands while ensuring they stay ahead. By placing the customer at the core of their strategies, businesses can create lasting value, build brand loyalty, and drive meaningful growth that balances profitability with long-term sustainability. This approach requires a continuous alignment of innovative efforts with customer needs, emerging technologies, and environmental and social responsibility. The convergence of strategy, innovation, and a customer-centric mindset may build resilient and future-ready organizations. Strategic Innovation and Sustainable Customer-Centric Growth explores how organizations can leverage strategic innovation to develop sustainable, customer-centric business models that drive long-term growth. It examines the integration of customer insights, technological advancements, and sustainability practices into core strategies to create competitive advantage and lasting value. This book covers topics such as business strategy, circular economics, and digital marketing, and is a useful resource for business owners, academicians, researchers, and scientists. 2026 by IGI Global Scientific Publishing. All rights reserved. -
New Business Development Strategies for Achieving Sustainable Growth
In an increasingly competitive and fast-paced global economy, sustainable business success hinges on the ability to innovate, adapt, and execute well-informed strategies. The modern entrepreneur or business leader must navigate complex challenges, from securing funding and managing teams to leveraging technology and aligning operations with long-term goals. Strategic frameworks that integrate both foundational business principles and emerging trends are essential for building resilient, scalable enterprises. By promoting agility, innovation, and sustainability, this topic directly supports economic development and empowers a new generation of leaders to create lasting, positive impact across industries and communities. New Business Development Strategies for Achieving Sustainable Growth provides a comprehensive road map to build, grow, and sustain successful businesses in an ever-changing global market. It bridges the gap between theoretical knowledge and practical application, equipping readers with actionable strategies to navigate challenges, leverage opportunities, and achieve long-term business success. Covering topics such as adaptive business, digitalization, and property management, this book is an excellent resource for entrepreneurs, business owners, managers, executives, students, consultants, educators, researchers, academicians, and more. 2026 by IGI Global Scientific Publishing. All rights reserved. -
Exploring the ethical implications of generative AI
Generative Artificial Intelligence (AI), an ever-evolving technology, holds immense promise across various industries, from healthcare to content generation. However, its rapid advancement has also given rise to profound ethical concerns. Illicit black-market industries exploit generative AI for counterfeit imagery, and in educational settings, biases and misinformation perpetuate. These issues underscore the need to grapple with the risks accompanying generative AI integration. Exploring the Ethical Implications of Generative AI emerges as a wellspring of insight for discerning academic scholars. It sets the stage by acknowledging generative AI's multifaceted potential and its capacity to reshape industries. The book addresses these complex ethical concerns, offering a comprehensive analysis and providing a roadmap for responsible AI development and usage. Its intended audience spans business leaders, policymakers, scholars, and individuals passionate about the ethical dimensions of AI. The book's objective is a twofold mission: to identify and dissect the ethical challenges inherent in generative AI while prescribing practical guidelines for its responsible development and utilization. By amalgamating the current research landscape, it aims to provide a comprehensive view of the field. Furthermore, the book introduces a set of practical guidelines that can serve as a guiding light for developers and users in diverse contexts, including workplaces, media, healthcare, education, and the military. By comprehensively addressing issues like bias, privacy, misuse, accountability, and responsibility, this book becomes the definitive guide for academic scholars navigating the ethical dilemmas of generative AI, ultimately safeguarding the responsible evolution of this groundbreaking technology. 2024 by IGI Global. All rights reserved. -
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Immersive Technologies: Navigating the Impacts, Challenges, and Opportunities
Immersive technology is going to govern the next generation in terms of education, health, military, tourism, and much more. Through its comprehensive exploration, didactic approach, and insightful analyses, this book provides an invaluable resource for understanding and harnessing the power of immersive technology. Immersive Technologies: Navigating the Impacts, Challenges, and Opportunities serves as a guiding compass through the immersive technology landscape and takes a multifaceted approach, addressing both the technical and human aspects. The book dissects the underlying methods and technologies that power immersive experiences, offering readers a clear understanding of how VR, AR, and MR function. The latest advancements, from cutting-edge hardware developments to revolutionary software applications are discussed in detail. The book also delves into the potential societal impacts and takes the reader on a journey from education to healthcare, entertainment to remote collaboration, so the reader can gain insights into the myriad of ways immersive technology is already shaping industries and human interaction. The ultimate benefit readers will derive from this book is a holistic grasp of the immersive technology landscape and they will be armed with knowledge about the challenges and opportunities presented by VR, AR, and MR. They will be well-equipped to navigate the future. This is a must-read for anyone interested in how this technology has the potential to reshape our world. Academicians will be enriched with the applications and practical perspectives. 2025 Sagaya Aurelia. -
Industry 4.0 Key Technological Advances and Design Principles in Engineering, Education, Business, and Social Applications
This book offers an in-depth look at Industry 4.0's applications and provides a conceptual framework for design principles and easy implementation. The book touches on the impact of Industry 4.0 and also examines the key technological advances and potential economic and technical benefits through case studies featuring real-world implementations. Industry 4.0 Key Technological Advances and Design Principles in Engineering, Education, Business, and Social Applications discusses the impact of Industry 4.0 and workforce transformation. The book examines the key technological advances that support Industry 4.0 and examines their potential economic and technical benefits through case studies. It covers the connection Industrial 4.0 has with IT and communication technologies and demonstrates the technological advancements and how to use their benefits towards and through examples of real-world applications. This book offers a conceptual framework and road map for those making decisions as they go through the next stage of transformation. This book mainly targets academicians, professionals, business professionals, start-up companies, and researchers at undergraduate, postgraduate, and doctoral levels. 2025 selection and editorial matter, Sagaya Aurelia and Ossama Embarak. All rights reserved. -
Internet of Medical Things: Case Studies and Applications in Healthcare
The book presents a comprehensive overview of emerging IoT technologies, IoT devices and sensors and their role in the healthcare industry. It offers recent developments in the creation, application, and impact of new IoMT data security, IoMT devices used in a variety of applications, including telemedicine, monitoring patients, and intelligence-based medical data analysis. It includes discussions on the use of medical data analysis to make various predictions and diagnoses that lead to the right treatment. The security of medical data from Internet of Things (IoT) devices, where there is a risk of data leakage during transmission from the device to the server, is also discussed. Offers Software Application Framework for Sustainable Healthcare Includes feature case studies and real-world examples of IoT devices and technologies in use in healthcare settings Provide insight into the security risks associated with connected medical devices and the measures that can be taken to mitigate these risks. Discusses various integration strategies and technologies, including data interoperability standards, application programming interfaces (APIs), and other tools Contains discussions on emerging IoT technologies, such as blockchain and edge computing, as well as their potential applications in healthcare This book is for researchers, professionals and students interested in the latest advancements on Internal of Medical Things. 2026 selection and editorial matter, Balakrishnan C, Jayapriya J, Vinay M, Sanjeev Kumar Singh, Nadarajah Manivannan individual chapters, the contributors. -
Nature-inspired Metaheuristic Algorithms: Solving Real World Engineering Problems
This comprehensive text provides practical guidance for implementing nature-inspired algorithms and metaheuristics in real-life scenarios to solve complex optimization problems. It further demonstrates how nature inspired metaheuristic algorithms have the potential to contribute to multiple United Nations sustainable development goals such as climate action, clean energy, and sustainable cities. This book: Discusses load balancing and demand response using nature-inspired optimization techniques Presents energy-efficient routing and scheduling, energy management, and optimization using metaheuristic algorithms Covers disease diagnosis, and prognosis using metaheuristic algorithms, drug discovery, and development using nature-inspired optimization techniques Explains waste reduction and recycling, image processing, and computer vision using nature-inspired optimization techniques Illustrates medical image analysis and segmentation using Ant Colony optimization, and Particle Swarm optimization techniques Nature-inspired Metaheuristic Algorithms is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, and information technology. 2025 selection and editorial matter, Sulabh Bansal, Aprna Tripathi, Shilpa Srivastava and Prem Prakash Vuppuluri; individual chapters, the contributors. -
PUNCHING UP IN STAND-UP COMEDY: Speaking Truth to Power
Punching Up in Stand-Up Comedy explores the new forms, voices and venues of stand-up comedy in different parts of the world and its potential role as a counterhegemonic tool for satire, commentary and expression of identity especially for the disempowered or marginalised. The title brings together essays and perspectives on stand-up and satire from different cultural and political contexts across the world which raise pertinent issues regarding its role in contemporary times, especially with the increased presence of OTT platforms and internet penetration that allows for easy access to this art form. It examines the theoretical understanding of the different aspects of the humour, aesthetics and politics of stand-up comedy, as well as the exploration of race, gender, politics and conflicts, urban culture and LGBTQ+ identities in countries such as Indonesia, Finland, France, Iran, Italy, Morocco, India and the USA. It also asks the question whether, along with contesting and destabilising existing discursive frameworks and identities, a stand-up comic can open up a space for envisaging a new social, cultural and political order? This book will appeal to people interested in performance studies, media, popular culture, digital culture, sociology, digital sociology and anthropology, and English literature. Chapter 9 of this book is freely available as a downloadable Open Access PDF at https://www.taylorfrancis.com under a Creative Commons (CC-BY) 4.0 license. Funded by the University of Helsinki. 2023 selection and editorial matter, Rashi Bhargava and Richa Chilana; individual chapters, the contributors. -
Recent Trends in Computational Intelligence Enabled Research: Theoretical Foundations and Applications
The field of computational intelligence has grown tremendously over that past five years, thanks to evolving soft computing and artificial intelligent methodologies, tools and techniques for envisaging the essence of intelligence embedded in real life observations. Consequently, scientists have been able to explain and understand real life processes and practices which previously often remain unexplored by virtue of their underlying imprecision, uncertainties and redundancies, and the unavailability of appropriate methods for describing the incompleteness and vagueness of information represented. With the advent of the field of computational intelligence, researchers are now able to explore and unearth the intelligence, otherwise insurmountable, embedded in the systems under consideration. Computational Intelligence is now not limited to only specific computational fields, it has made inroads in signal processing, smart manufacturing, predictive control, robot navigation, smart cities, and sensor design to name a few. Recent Trends in Computational Intelligence Enabled Research: Theoretical Foundations and Applications explores the use of this computational paradigm across a wide range of applied domains which handle meaningful information. Chapters investigate a broad spectrum of the applications of computational intelligence across different platforms and disciplines, expanding our knowledge base of various research initiatives in this direction. This volume aims to bring together researchers, engineers, developers and practitioners from academia and industry working in all major areas and interdisciplinary areas of computational intelligence, communication systems, computer networks, and soft computing. 2021 Elsevier Inc. All rights reserved. -
Intelligent Environmental Data Monitoring for Pollution Management: A volume in Intelligent Data-Centric Systems
Intelligent Environmental Data Monitoring for Pollution Management discusses evolving novel intelligent algorithms and their applications in the area of environmental data-centric systems guided by batch process-oriented data. Thus, the book ushers in a new era as far as environmental pollution management is concerned. It reviews the fundamental concepts of gathering, processing and analyzing data from batch processes, followed by a review of intelligent tools and techniques which can be used in this direction. In addition, it discusses novel intelligent algorithms for effective environmental pollution data management that are on par with standards laid down by the World Health Organization. To learn more about Elseviers Series, Intelligent Data-Centric Systems, please visit this link: https://www.elsevier.com/books-and-journals/book-series/intelligent-data-centric-systems-sensor-collected-intelligence. 2021 Elsevier Inc. All rights reserved. -
Quantum machine learning
Quantum-enhanced machine learning refers to quantum algorithms that solve tasks in machine learning, thereby improving a classical machine learning method. Such algorithms typically require one to encode the given classical dataset into a quantum computer, so as to make it accessible for quantum information processing. After this, quantum information processing routines can be applied and the result of the quantum computation is read out by measuring the quantum system. While many proposals of quantum machine learning algorithms are still purely theoretical and require a full-scale universal quantum computer to be tested, others have been implemented on small-scale or special purpose quantum devices. New trends in Machine Learning based on Quantum Computing and Quantum Algorithms Examples on real life applications Illustrative diagrams and coding examples. 2020 Walter de Gruyter GmbH, Berlin/Boston. All rights reserved. -
Deep learning: Research and applications
This book focuses on the fundamentals of deep learning along with reporting on the current state-of-art research on deep learning. In addition, it provides an insight of deep neural networks in action with illustrative coding examples. Deep learning is a new area of machine learning research which has been introduced with the objective of moving ML closer to one of its original goals, i.e. artificial intelligence. Deep learning was developed as an ML approach to deal with complex input-output mappings. While traditional methods successfully solve problems where final value is a simple function of input data, deep learning techniques are able to capture composite relations between non-immediately related fields, for example between air pressure recordings and English words, millions of pixels and textual description, brand-related news and future stock prices and almost all real world problems. Deep learning is a class of nature inspired machine learning algorithms that uses a cascade of multiple layers of nonlinear processing units for feature extraction and transformation. Each successive layer uses the output from the previous layer as input. The learning may be supervised (e.g. classification) and/or unsupervised (e.g. pattern analysis) manners. These algorithms learn multiple levels of representations that correspond to different levels of abstraction by resorting to some form of gradient descent for training via backpropagation. Layers that have been used in deep learning include hidden layers of an artificial neural network and sets of propositional formulas. They may also include latent variables organized layer-wise in deep generative models such as the nodes in deep belief networks and deep boltzmann machines. Deep learning is part of state-of-the-art systems in various disciplines, particularly computer vision, automatic speech recognition (ASR) and human action recognition. Tutorials on deep learning framework with focus on tensor flow, keras etc. Numerous worked out examples on real life applications Illustrative diagrams and coding examples. 2020 Walter de Gruyter GmbH, Berlin/Boston. All rights reserved.