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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. -
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. -
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. -
Characterization of Diesel soot from the combustion in engine by X-ray and spectroscopic techniques
International journal of Electrochemical science . Vol. 4, Issue 4, pp. 3215-3221 ISSN No. 1452-3981 -
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. -
Hybrid Computational Intelligence: Challenges and Applications
Hybrid Computational Intelligence: Challenges and Utilities is a comprehensive resource that begins with the basics and main components of computational intelligence. It brings together many different aspects of the current research on HCI technologies, such as neural networks, support vector machines, fuzzy logic and evolutionary computation, while also covering a wide range of applications and implementation issues, from pattern recognition and system modeling, to intelligent control problems and biomedical applications. The book also explores the most widely used applications of hybrid computation as well as the history of their development. Each individual methodology provides hybrid systems with complementary reasoning and searching methods which allow the use of domain knowledge and empirical data to solve complex problems. 2020 Elsevier Inc. -
Intelligent Manufacturing and Industry 4.0: Impact, Trends, and Opportunities
The use of intelligence in manufacturing has emerged as a fascinating subject for academics and businesses everywhere. This book focuses on various manufacturing operations and services which are provided to customers to achieve greater manufacturing flexibility, as well as widespread customization and improved quality with the help of advanced and smart technologies. It describes cyber-physical systems and the whole product life cycle along with a variety of smart sensors, adaptive decision models, high-end materials, smart devices, and data analytics. Intelligent Manufacturing and Industry 4.0: Impact, Trends, and Opportunities focuses on Intelligent Manufacturing and the design of smart devices and products that meet the demand of Industry 4.0, manufacturing and cyber-physical systems, along with real-time data analytics for Intelligent Manufacturing. The usage of advanced smart and sensing technologies in Intelligent Manufacturing for healthcare solutions is discussed as well. Popular use cases and case studies related to Intelligent Manufacturing are addressed to provide a better understanding of this topic. This publication is ideally designed for use by technology development practitioners, academicians, data scientists, industry professionals, researchers, and students interested in uncovering the latest innovations in the field of Intelligent Manufacturing. Features: Presents cutting-edge manufacturing technologies and information to maximise product exchanges and production Discusses the improvement in service quality, product quality, and production effectiveness Conveys how a manufacturing companys competitiveness can increase if it can manage the turbulence and changes in the global market Presents how intelligence production is essential in Industry 4.0 and how Industry 4.0 offers greater manufacturing flexibility, as well as widespread customisation, improved quality, and increased productivity Covers the ways businesses handle the challenges of generating an increasing number of customised items with quick time to market and greater quality Includes popular use cases and case studies related to intelligent manufacturing to provide a better understanding of this discipline. 2025 selection and editorial matter, Alka Chaudhary, Vandana Sharma, and Ahmed Alkhayyat individual chapters, the contributors. -
Models for Social Responsibility Action by Higher Education Institutions
This book offers 18 chapters on replicable models for social responsibility actions for universities and other academic institutions. The chapters are broadly classified under two major areas: sustainable development models and social sensitisation programmes. The chapters capture the efficient and successful models of social responsibility practiced by Indian and foreign universities. The models are proposed based on the evidence from a rigorous research process. Universities across the world can benefit from the best practices and implement the same successfully. The models will be helpful to universities in achieving the United Nations' Sustainable Development Goals (SDGs) and rank higher on the Sustainability Tracking, Assessment & Rating System (STARS). The research-based chapters will have significant benefits to researchers in expanding the domain of social responsibility of higher education institutions. As a text, this book will serve students of higher education in sustainability and social responsibility related courses. 2024 by Nova Science Publishers, Inc. All rights reserved. -
SOCIAL PSYCHOLOGY: Theories and Applications
This book examines the concept of social psychology in today's context. It analyses the theoretical concepts of social psychology and their applicationto other fields. It further explores the discipline in a cultural, historical, and philosophical context with special emphasis on religion. The volume goes beyond individual focus and directs its attention to society as the centre of influence. It advocates for a symbiotic relationship between the concepts of social psychology and their implementation in a society transitioning from being value-oriented to commerce-oriented. The book also suggests ways in which social psychology can assist in dealing with issues plaguing today's world. This book will be useful to students of psychology, applied psychology, sociology, social work, public health, gender, and women studies. It will also be indispensable to professionals working in the field of paediatrics, forensic medicine, psychiatry, and law enforcement authorities like police and judiciary. 2024 Sibnath Deb, Anjali Gireesan, Pooja Prabhavalkar and Shayana Deb. -
ICT as a driver of women's social and economic empowerment
The role of information and communication technologies as a tool for development has attracted the sustained attention of various agencies worldwide. If the gender dimensions of information and communication technologies-in terms of access and use, capacity-building opportunities, employment, and potential for empowerment-are explicitly identified and addressed, information and communication technologies can be a powerful catalyst for the political and social empowerment of women and the promotion of gender equality. ICT as a Driver of Women's Social and Economic Empowerment contributes to the growing body of literature and present state of knowledge by offering evidence on how new information and communication technologies impact women's economic and social empowerment and overall welfare creation leading to inclusive growth. Covering key topics such as economics, entrepreneurship, digital technologies, and inclusion, this premier reference source is ideal for industry professionals, policymakers, administrators, business owners, managers, researchers, academicians, scholars, practitioners, instructors, and students. 2023 by IGI Global. All rights reserved. -
Colonialism and Communalism: Religion and Changing Identities in Modern India
Christhu Doss examines how the colonial construct of communalism through the fault lines of the supposed religious neutrality, the hunger for the bread of life, the establishment of exclusive village settlements for the proselytes, the rhetoric of Victorian morality, the booby-traps of modernity, and the subversion of Indian cultural heritage resulted in a radical reorientation of religious allegiance that eventually created a perpetual detachment between proselytes and the others. Exploring the trajectories of communalism, Doss demonstrates how the multicultural Indian society, known widely for its composite culture, and secular convictions were categorized, compartmentalized, and communalized by the racialized religious pretensions. A vital read for historians, political scientists, sociologists, anthropologists, and all those who are interested in religions, cultures, identity politics, and decolonization in modern India. 2024 M. Christhu Doss. -
Data Analytics for Social Microblogging Platforms
Data Analysis for Social Microblogging Platforms explores the nature of microblog datasets, also covering the larger field which focuses on information, data and knowledge in the context of natural language processing. The book investigates a range of significant computational techniques which enable data and computer scientists to recognize patterns in these vast datasets, including machine learning, data mining algorithms, rough set and fuzzy set theory, evolutionary computations, combinatorial pattern matching, clustering, summarization and classification. Chapters focus on basic online micro blogging data analysis research methodologies, community detection, summarization application development, performance evaluation and their applications in big data. 2023 Elsevier Inc. All rights reserved. -
Advanced Applications of Python Data Structures and Algorithms
Data structures are essential principles applicable to any programming language in computer science. Data structures may be studied more easily with Python than with any other programming language because of their interpretability, interactivity, and object-oriented nature. Computers may store and process data at an extraordinary rate and with outstanding accuracy. Therefore, it is of the utmost importance that the data is efficiently stored and is able to be accessed promptly. In addition, data processing should take as little time as feasible while maintaining the highest possible level of precision. Advanced Applications of Python Data Structures and Algorithms assists in understanding and applying the fundamentals of data structures and their many implementations and discusses the advantages and disadvantages of various data structures. Covering key topics such as Python, linked lists, datatypes, and operators, this reference work is ideal for industry professionals, computer scientists, researchers, academicians, scholars, practitioners, instructors, and students. 2023 by IGI Global. All rights reserved. -
Advanced Machine Vision Paradigms for Medical Image Analysis
Computer vision and machine intelligence paradigms are prominent in the domain of medical image applications, including computer assisted diagnosis, image guided radiation therapy, landmark detection, imaging genomics, and brain connectomics. Medical image analysis and understanding are daunting tasks owing to the massive influx of multi-modal medical image data generated during routine clinal practice. Advanced computer vision and machine intelligence approaches have been employed in recent years in the field of image processing and computer vision. However, due to the unstructured nature of medical imaging data and the volume of data produced during routine clinical processes, the applicability of these meta-heuristic algorithms remains to be investigated. Advanced Machine Vision Paradigms for Medical Image Analysis presents an overview of how medical imaging data can be analyzed to provide better diagnosis and treatment of disease. Computer vision techniques can explore texture, shape, contour and prior knowledge along with contextual information, from image sequence and 3D/4D information which helps with better human understanding. Many powerful tools have been developed through image segmentation, machine learning, pattern classification, tracking, and reconstruction to surface much needed quantitative information not easily available through the analysis of trained human specialists. The aim of the book is for medical imaging professionals to acquire and interpret the data, and for computer vision professionals to learn how to provide enhanced medical information by using computer vision techniques. The ultimate objective is to benefit patients without adding to already high healthcare costs. 2020 Elsevier Inc. All rights reserved. -
Impact of Climate Change on Social and Mental Well-Being
Impact of Climate Change on Social and Mental Well-Being, increases the awareness and understanding of how global climate change, including natural disasters, loss of habitat, and displacement can affect social and mental well-being. This book provides valuable insights into the connection between environmental issues and mental health, and the long-term implications of these issues. Sections dedicated to adaptation and solutions, offer coping mechanisms and strategies for eco-anxiety and climate grief. This book also explores the social, economic, and political factors that contribute to climate change and how these factors impact human well-being. 2025 Elsevier Inc. All rights are reserved including those for text and data mining AI training and similar technologies.