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Multi-Agent-Based Simulation XXIV: 24th International Workshop, MABS 2023, London, UK, May 29 – June 2, 2023, Revised Selected Papers (Lecture Notes in Computer Science #14558)
by Luis G. Nardin Sara MehryarThis book constitutes the refereed Proceedings of the 24th International Workshop on Multi-Agent-Based Simulation XXIV, MABS 2023, held in London, UK, during May 29–June 2, 2023. The 11 regular papers presented were carefully reviewed and selected from 27 submissions. The papers are organized in subject areas as follows: MABS methodology and tools; MABS and social behavior; and MABS applications.
Accelerating Discoveries in Data Science and Artificial Intelligence II: ICDSAI 2023, LIET Vizianagaram, India, April 24–25 (Springer Proceedings in Mathematics & Statistics #438)
by Nishtha Kesswani Frank M. Lin Ashokkumar Patel Bosubabu SambanaThis edited volume on machine learning and big data analytics (Proceedings of ICDSAI 2023), that was held on April 24-25, 2023 by CSUSB USA, International Association of Academicians (IAASSE), and Lendi Institute of Engineering and Technology, Vizianagaram, India is intended to be used as a reference book for researchers and practitioners in the disciplines of AI and Data Science. With the fascinating development of technologies in several industries, there are numerous opportunities to develop innovative intelligence technologies to solve a wide range of uncertainties in various real-life problems. Researchers and academics have been drawn to building creative AI strategies by combining data science with classic mathematical methodologies. The book brings together leading researchers who wish to continue to advance the field and create a broad knowledge about the most recent research.
Type-3 Fuzzy Logic in Time Series Prediction (SpringerBriefs in Applied Sciences and Technology)
by Oscar Castillo Patricia MelinThis book focuses on the field of type-3 fuzzy logic for applications in time series prediction. The main idea is that a higher type and order of fuzzy logic can help in solving various prediction problems and find better results. In addition, neural networks and fractal theory are employed in enhancing prediction results. In this regard, several hybrid intelligent methods are offered. In this book we test the proposed methods using several prediction problems, like predicting COVID-19 and the stock market. We can notice that when Type-3 fuzzy systems are implemented to model the behavior of systems, the results in prediction are enhanced, because the management of uncertainty is better. For this reason, we consider in this book the proposed methods using type-3 fuzzy systems, neural networks and fractal theory to improve the prediction behavior of the complex nonlinear systems. This book is intended to be a reference for scientists and engineers interested in applying type-3 fuzzy logic techniques for solving complex prediction problems. This book can also be used as a reference for graduate courses like the following: soft computing, fuzzy logic, neural networks, bio-inspired algorithms, intelligent prediction, and similar ones. We consider that this book can also be used to get novel ideas for new lines of research, or to continue the lines of research proposed by the authors of the book.
Artificial Intelligence for Multimedia Information Processing: Tools and Applications
by Xavier Savarimuthu Sivakannan Subramani Alex Noel Joseph RajAdvances in artificial intelligence (AI), widespread mobile devices, internet technologies, multimedia data sources, and information processing have led to the emergence of multimedia processing. Multimedia processing is the application of signal processing tools to multimedia data—text, audio, images, and video—to allow the interpretation of these data, particularly in urban and smart city environments. This book discusses the new standards of multimedia and information processing from several technological perspectives, including analytics empowered by AI, streaming on the intelligent edge, multimedia edge caching and AI, services for edge AI, and hardware and devices for multimedia on edge intelligence.FEATURES Covers a wide spectrum of enabling technologies for AI and machine learning for multimedia and information processing Includes many applications using AI, from robotics and driverless cars to environmental, human health, and remote sensing Presents an overview of the fundamentals of AI and multimedia processing: imaging, signal, and speech Explains new models and architectures for multimedia streaming, services, and caching for AI Discusses the emerging paradigms of the deployment of hardware and devices for multimedia on edge intelligence Gives recommendations for future research in multimedia and AI This book is written for engineers and graduate students in image and signal processing, information processing, environmental engineering, medical and public health, etc., who are interested in machine learning, deep learning, and multimedia processing.
Artificial Intelligence for Multimedia Information Processing: Tools and Applications
Advances in artificial intelligence (AI), widespread mobile devices, internet technologies, multimedia data sources, and information processing have led to the emergence of multimedia processing. Multimedia processing is the application of signal processing tools to multimedia data—text, audio, images, and video—to allow the interpretation of these data, particularly in urban and smart city environments. This book discusses the new standards of multimedia and information processing from several technological perspectives, including analytics empowered by AI, streaming on the intelligent edge, multimedia edge caching and AI, services for edge AI, and hardware and devices for multimedia on edge intelligence.FEATURES Covers a wide spectrum of enabling technologies for AI and machine learning for multimedia and information processing Includes many applications using AI, from robotics and driverless cars to environmental, human health, and remote sensing Presents an overview of the fundamentals of AI and multimedia processing: imaging, signal, and speech Explains new models and architectures for multimedia streaming, services, and caching for AI Discusses the emerging paradigms of the deployment of hardware and devices for multimedia on edge intelligence Gives recommendations for future research in multimedia and AI This book is written for engineers and graduate students in image and signal processing, information processing, environmental engineering, medical and public health, etc., who are interested in machine learning, deep learning, and multimedia processing.
Future Communication Systems Using Artificial Intelligence, Internet of Things and Data Science
by Mariya Ouaissa Mariyam Ouaissa Inam Ullah Khan Inam Ullah Salma El HajjamiFuture Communication Systems Using Artificial Intelligence, Internet of Things and Data Science mainly focuses on the techniques of artificial intelligence (AI), Internet of Things (IoT) and data science for future communications systems.The goal of AI, IoT and data science for future communications systems is to create a venue for industry and academics to collaborate on the development of network and system solutions based on data science, AI and IoT. Recent breakthroughs in IoT, mobile and fixed communications and computation have paved the way for a data‑centric society of the future. New applications are increasingly reliant on machine‑to‑machine connections, resulting in unusual workloads and the need for more efficient and dependable infrastructures. Such a wide range of traffic workloads and applications will necessitate dynamic and highly adaptive network environments capable of self‑optimization for the task at hand while ensuring high dependability and ultra‑low latency.Networking devices, sensors, agents, meters and smart vehicles/systems generate massive amounts of data, necessitating new levels of security, performance and dependability. Such complications necessitate the development of new tools and approaches for providing successful services, management and operation. Predictive network analytics will play a critical role in insight generation, process automation required for adapting and scaling to new demands, resolving issues before they impact operational performance (e.g., preventing network failures and anticipating capacity requirements) and overall network decision‑making. To increase user experience and service quality, data mining and analytic techniques for inferring quality of experience (QoE) signals are required.AI, IoT, machine learning, reinforcement learning and network data analytics innovations open new possibilities in areas such as channel modeling and estimation, cognitive communications, interference alignment, mobility management, resource allocation, network control and management, network tomography, multi‑agent systems and network ultra‑broadband deployment prioritization. These new analytic platforms will aid in the transformation of our networks and user experience. Future networks will enable unparalleled automation and optimization by intelligently gathering, analyzing, learning and controlling huge volumes of information.
Future Communication Systems Using Artificial Intelligence, Internet of Things and Data Science
by Dr Inam UllahFuture Communication Systems Using Artificial Intelligence, Internet of Things and Data Science mainly focuses on the techniques of artificial intelligence (AI), Internet of Things (IoT) and data science for future communications systems.The goal of AI, IoT and data science for future communications systems is to create a venue for industry and academics to collaborate on the development of network and system solutions based on data science, AI and IoT. Recent breakthroughs in IoT, mobile and fixed communications and computation have paved the way for a data‑centric society of the future. New applications are increasingly reliant on machine‑to‑machine connections, resulting in unusual workloads and the need for more efficient and dependable infrastructures. Such a wide range of traffic workloads and applications will necessitate dynamic and highly adaptive network environments capable of self‑optimization for the task at hand while ensuring high dependability and ultra‑low latency.Networking devices, sensors, agents, meters and smart vehicles/systems generate massive amounts of data, necessitating new levels of security, performance and dependability. Such complications necessitate the development of new tools and approaches for providing successful services, management and operation. Predictive network analytics will play a critical role in insight generation, process automation required for adapting and scaling to new demands, resolving issues before they impact operational performance (e.g., preventing network failures and anticipating capacity requirements) and overall network decision‑making. To increase user experience and service quality, data mining and analytic techniques for inferring quality of experience (QoE) signals are required.AI, IoT, machine learning, reinforcement learning and network data analytics innovations open new possibilities in areas such as channel modeling and estimation, cognitive communications, interference alignment, mobility management, resource allocation, network control and management, network tomography, multi‑agent systems and network ultra‑broadband deployment prioritization. These new analytic platforms will aid in the transformation of our networks and user experience. Future networks will enable unparalleled automation and optimization by intelligently gathering, analyzing, learning and controlling huge volumes of information.
Information as Receptive Relation
by Xi Wang Tianen WangThis book aims to revolutionize information research by introducing a receptive relation understanding of information, which systematically unveils its fundamental characteristics: created ex nihilo, emergence, reciprocity and shareability.Through a thorough exploration of organismic and sensory receptivity, the book establishes a mechanistic foundation for understanding the nature of information. It navigates the origins of biological information and leads readers into a new era of information studies. Offering a fresh perspective on the nature of information, it delves into its physical, digital, and ideational encodings, as well as the ideational system built upon them. The book sheds light on critical issues such as quantum manifestation of information and the fundamental laws governing the relationship between information and matter/energy. It also dispels common misconceptions about information and its role in the evolution of information civilization.The book provides valuable insights into understanding artificial general intelligence and the mysteries of consciousness and life. It will be of interest to researchers and students of information philosophy, information science, and artificial intelligence.
Information as Receptive Relation
by Xi Wang Tianen WangThis book aims to revolutionize information research by introducing a receptive relation understanding of information, which systematically unveils its fundamental characteristics: created ex nihilo, emergence, reciprocity and shareability.Through a thorough exploration of organismic and sensory receptivity, the book establishes a mechanistic foundation for understanding the nature of information. It navigates the origins of biological information and leads readers into a new era of information studies. Offering a fresh perspective on the nature of information, it delves into its physical, digital, and ideational encodings, as well as the ideational system built upon them. The book sheds light on critical issues such as quantum manifestation of information and the fundamental laws governing the relationship between information and matter/energy. It also dispels common misconceptions about information and its role in the evolution of information civilization.The book provides valuable insights into understanding artificial general intelligence and the mysteries of consciousness and life. It will be of interest to researchers and students of information philosophy, information science, and artificial intelligence.
Software Project Management: Methods and Techniques
by Lawrence J. PetersThe management of a software project has been shown to be the number one factor in determining a software development project’s success. It has been found that most software projects fail because of poor management. Not surprisingly, most software development managers have not been trained in project management. Software Project Management: Methods and Techniques aims to remedy this situation in two ways: familiarizing software developers with the elements of the project management discipline and providing fact-based resources on practicing software project management.Much like the checklist pilots go through prior to a flight, this book provides a pre-project checklist which enables the software engineering team to review and evaluate an extensive set of technical and sociopolitical risks which will help the software project manager and the team determine the project team’s chances of success. This same list and the individual question responses can be used later as part of the project’s closeout process helping team members to improve their individual and collective abilities to assess risk.Intended for both students and software project managers, the book is organized along the lines of the five major functions of a software project manager: planning; scheduling and costing; controlling; staffing; and motivating. The basics of each of these functions are presented in a single chapter. These are followed by a series of narrow topic presentations in the form of appendices that are intended to help solve specific problems that may occur during the conduct of a software project. As in the main portion of the text, the appendices include references that provide an avenue into further detail on the topic. Designed to promote project success, this approach has been taken because software projects are each unique undertakings such that providing a "one size fits all" approach will fail most of the time.
Software Project Management: Methods and Techniques
by Lawrence J. PetersThe management of a software project has been shown to be the number one factor in determining a software development project’s success. It has been found that most software projects fail because of poor management. Not surprisingly, most software development managers have not been trained in project management. Software Project Management: Methods and Techniques aims to remedy this situation in two ways: familiarizing software developers with the elements of the project management discipline and providing fact-based resources on practicing software project management.Much like the checklist pilots go through prior to a flight, this book provides a pre-project checklist which enables the software engineering team to review and evaluate an extensive set of technical and sociopolitical risks which will help the software project manager and the team determine the project team’s chances of success. This same list and the individual question responses can be used later as part of the project’s closeout process helping team members to improve their individual and collective abilities to assess risk.Intended for both students and software project managers, the book is organized along the lines of the five major functions of a software project manager: planning; scheduling and costing; controlling; staffing; and motivating. The basics of each of these functions are presented in a single chapter. These are followed by a series of narrow topic presentations in the form of appendices that are intended to help solve specific problems that may occur during the conduct of a software project. As in the main portion of the text, the appendices include references that provide an avenue into further detail on the topic. Designed to promote project success, this approach has been taken because software projects are each unique undertakings such that providing a "one size fits all" approach will fail most of the time.
Reflective Assessment for Deep Learning and Knowledge Building: An Empirical Case in China
by Chunlin LeiKnowledge building aims to transform schools into learning communities and bring knowledge creation into schools. The book therefore elaborates on how learning, technology, and assessment can be aligned both online and offline to facilitate such a process.Adopting a quasi-experimental design and drawing on rich data from forum discussions, questionnaires, interviews, learning outcomes, and classroom presentations, this book shows that the knowledge building environment, augmented by reflective assessment and principles, helped Chinese students to develop a deeper approach to learning, improved academic performance, and promoted collective knowledge advances. The book also discusses the potentials and challenges of designing technology-supported, assessment- and principle-based learning environments in tertiary contexts, especially when deep learning and knowledge building capacity are greatly emphasised in the knowledge era.The book will be of interest to scholars and educators working in learning sciences and computer-supported collaborative learning.
Reflective Assessment for Deep Learning and Knowledge Building: An Empirical Case in China
by Chunlin LeiKnowledge building aims to transform schools into learning communities and bring knowledge creation into schools. The book therefore elaborates on how learning, technology, and assessment can be aligned both online and offline to facilitate such a process.Adopting a quasi-experimental design and drawing on rich data from forum discussions, questionnaires, interviews, learning outcomes, and classroom presentations, this book shows that the knowledge building environment, augmented by reflective assessment and principles, helped Chinese students to develop a deeper approach to learning, improved academic performance, and promoted collective knowledge advances. The book also discusses the potentials and challenges of designing technology-supported, assessment- and principle-based learning environments in tertiary contexts, especially when deep learning and knowledge building capacity are greatly emphasised in the knowledge era.The book will be of interest to scholars and educators working in learning sciences and computer-supported collaborative learning.
Early Warning Mechanisms for Online Learning Behaviors Driven by Educational Big Data
by Xiaona Xia Wanxue QiThe book aims to design and construct early warning mechanisms based on the dynamic temporal tracking technology for online learning behaviors, driven by educational big data.By studying a massive amount of learning behavior instances generated in various interactive learning environments worldwide, the book explores the continuous sequences of correlated learning behaviors and characteristics. From various angles, the authors have devised a series of early warning measures that could effectively solve multiple issues in learning behaviors driven by educational big data. Additionally, the book predicts patterns and identifies risks by analyzing the temporal sequences of the entire learning process. While presenting a range of theoretical achievements and technical solutions to improve and design new online learning mode, it also provides relevant technical ideas and methodologies for research on similar problems.The book will attract scholars and students working on learning analytics and educational big data worldwide.
Early Warning Mechanisms for Online Learning Behaviors Driven by Educational Big Data
by Xiaona Xia Wanxue QiThe book aims to design and construct early warning mechanisms based on the dynamic temporal tracking technology for online learning behaviors, driven by educational big data.By studying a massive amount of learning behavior instances generated in various interactive learning environments worldwide, the book explores the continuous sequences of correlated learning behaviors and characteristics. From various angles, the authors have devised a series of early warning measures that could effectively solve multiple issues in learning behaviors driven by educational big data. Additionally, the book predicts patterns and identifies risks by analyzing the temporal sequences of the entire learning process. While presenting a range of theoretical achievements and technical solutions to improve and design new online learning mode, it also provides relevant technical ideas and methodologies for research on similar problems.The book will attract scholars and students working on learning analytics and educational big data worldwide.
Open Data for Everybody: Using Open Data for Social Good
by Nathan CoyleWhat if I told you something that could empower our third sector and activists to enhance their capacity? From gathering evidence for funding tenders to campaigning for crucial social issues and much more? It's called open data, yet many in social action remain unaware of it. Primarily shaped by corporate entities, open data seems tailored only for technologists, alienating the third sector. But in reality, it's a powerful tool for social change, bolstering civil society, and creating resilient communities.This book argues a simple point: if open data and the digital aspects that support it aren't accessible to all, then what is the point of it? In an age where technology should be seen as a fundamental human right, it's time to rethink outreach. Deeply rooted in grassroots social activism, this book explores a journey that led to collaborations with governments globally, based on real hands-on work, aiming to democratize open data. Through narrative storytelling, we share insights, best practices, procedures, and community-driven approaches. Regardless of your skill set or organization size, from grassroots workers to third-sector professionals and government officers, join us to reshape the perception of open data, fostering change in neighborhoods.Open Data for Everybody: Using Open Data for Social Good is a love letter to open data's transformative power. To create solutions, understanding the problem is crucial. This book seeks to return control to the real experts—those living and working within our communities.
Open Data for Everybody: Using Open Data for Social Good
by Nathan CoyleWhat if I told you something that could empower our third sector and activists to enhance their capacity? From gathering evidence for funding tenders to campaigning for crucial social issues and much more? It's called open data, yet many in social action remain unaware of it. Primarily shaped by corporate entities, open data seems tailored only for technologists, alienating the third sector. But in reality, it's a powerful tool for social change, bolstering civil society, and creating resilient communities.This book argues a simple point: if open data and the digital aspects that support it aren't accessible to all, then what is the point of it? In an age where technology should be seen as a fundamental human right, it's time to rethink outreach. Deeply rooted in grassroots social activism, this book explores a journey that led to collaborations with governments globally, based on real hands-on work, aiming to democratize open data. Through narrative storytelling, we share insights, best practices, procedures, and community-driven approaches. Regardless of your skill set or organization size, from grassroots workers to third-sector professionals and government officers, join us to reshape the perception of open data, fostering change in neighborhoods.Open Data for Everybody: Using Open Data for Social Good is a love letter to open data's transformative power. To create solutions, understanding the problem is crucial. This book seeks to return control to the real experts—those living and working within our communities.
Far-Right Extremism Online: Beyond the Fringe (Routledge Studies in Digital Extremism)
by Tine MunkBy imparting crucial insights into the digital evolution of far-right extremism and its challenges, this book explores how far-right extremism has transformed, utilising digital spaces for communication and employing coded language to evade detection.Far-right extremism has spread extensively across online platforms. Flourishing within echo chambers, these groups propagate different types of online and offline actions and advance their hateful ideologies to a wide-ranging audience. This book highlights the issues surrounding far-right extremism, which distinguishing it from terrorism and examining its contemporary digital manifestations. Importantly, it sheds light on how far-right groups utilise online platforms for communication, radicalisation, and on-ground actions, relying on alternative truths, misinformation, conspiracy theories, fashion, and memes to connect with like-minded individuals. The book also addresses content moderation challenges and the impact of rising populism in today’s political climate, which fuels societal divisions and uncertainty.Far-Right Extremism Online is a valuable resource for academics, students, analysts, and professionals working in counter-extremism, cybersecurity, digital communication, and national security. It is also an indispensable guide for those concerned about far-right extremism in the digital age.
Far-Right Extremism Online: Beyond the Fringe (Routledge Studies in Digital Extremism)
by Tine MunkBy imparting crucial insights into the digital evolution of far-right extremism and its challenges, this book explores how far-right extremism has transformed, utilising digital spaces for communication and employing coded language to evade detection.Far-right extremism has spread extensively across online platforms. Flourishing within echo chambers, these groups propagate different types of online and offline actions and advance their hateful ideologies to a wide-ranging audience. This book highlights the issues surrounding far-right extremism, which distinguishing it from terrorism and examining its contemporary digital manifestations. Importantly, it sheds light on how far-right groups utilise online platforms for communication, radicalisation, and on-ground actions, relying on alternative truths, misinformation, conspiracy theories, fashion, and memes to connect with like-minded individuals. The book also addresses content moderation challenges and the impact of rising populism in today’s political climate, which fuels societal divisions and uncertainty.Far-Right Extremism Online is a valuable resource for academics, students, analysts, and professionals working in counter-extremism, cybersecurity, digital communication, and national security. It is also an indispensable guide for those concerned about far-right extremism in the digital age.
Mental Fatigue Assessment in Demanding Marine Operations
by Houxiang Zhang Thiago Gabriel MonteiroThis book investigates how human mental fatigue (MF) can be objectively measured during demanding maritime operations. The maritime domain is characterized by demanding operations. These operations can be especially complex and dangerous when they require coordination between different maritime vessels and several maritime operators. The best approach to quantify MF is through the use of physiological sensors including electroencephalogram (EEG), electrocardiogram, electromyogram, temperature sensor, and eye tracker can be applied, individually or in conjunction, in order to collect relevant data that can be mapped to an MF scale. More than simpler sensor fusion, this book bridges the gap between relevant sensor data and a quantifiable MF level using both data-driven and model-based approaches. Data-driven part investigates the use of different NNs combined for the MF assessment (MFA) task. Among the different architectures tested, convolutional neural networks (CNN) showed the best performance when dealing with multiple physiological data channels. Optimization was used to improve the performance of CNN in the cross-subject MFA task. Testing different combinations of physiological sensors indicated a setup consisting of EEG sensor only was the best option, due to the trade-off between assessment precision and sensor framework complexity. These two factors are of great importance when considering an MFA system that could be implemented in real-life scenarios. The model-based discussion applies the current knowledge about the use of EEG data to characterize MF to develop an MF approach to quantify the progression of MF in maritime operators. In the research presented in this book, realistic vessel simulators were used as a platform for experimenting with different operational scenarios and sensor setups.
System Dependability - Theory and Applications: Proceedings of the Nineteenth International Conference on Dependability of Computer Systems DepCoS-RELCOMEX. July 1–5, 2024, Brunów, Poland (Lecture Notes in Networks and Systems #1026)
by Janusz Kacprzyk Wojciech Zamojski Jacek Mazurkiewicz Jarosław Sugier Tomasz WalkowiakThis book presents a selection of papers about problems which arise in dependability studies of contemporary computer systems and networks. Their collection should be an interesting and inspiring source material for scientists, researchers, engineers, and students who must consider diverse dependability characteristics in design, analysis, or maintenance of computer systems and networks. The papers were presented during the 19th DepCoS-RELCOMEX conference which was the next event in a series organized annually since 2006. Originating as a scientific platform for discussions of reliability aspects in computer engineering, the topical scope of the conference has been constantly expanded to incorporate new dependability challenges brought by recent advances in systems and information technologies. Currently, dependable operation in the context of computer processing means obtaining reliable (true and timely) results in the conditions of processing both quantitative and qualitative data, using precise or fuzzy (often: imitating) models and algorithms. With increasing use of artificial intelligence algorithms and tools, dependability in contemporary information technology and computer engineering calls for methods based on cognitive systems and deep learning techniques. Topical variety of the papers included in these proceedings proves that almost all applications of modern computer systems and networks must take into account the aspect of dependability and also illustrates a wide diversity of multidisciplinary subjects which needs to be considered in this context.
Machine Intelligence: Computer Vision and Natural Language Processing
by Pethuru Raj P. Beaulah Soundarabai D. Peter AugustineMachines are being systematically empowered to be interactive and intelligent in their operations, offerings. and outputs. There are pioneering Artificial Intelligence (AI) technologies and tools. Machine and Deep Learning (ML/DL) algorithms, along with their enabling frameworks, libraries, and specialized accelerators, find particularly useful applications in computer and machine vision, human machine interfaces (HMIs), and intelligent machines. Machines that can see and perceive can bring forth deeper and decisive acceleration, automation, and augmentation capabilities to businesses as well as people in their everyday assignments. Machine vision is becoming a reality because of advancements in the computer vision and device instrumentation spaces. Machines are increasingly software-defined. That is, vision-enabling software and hardware modules are being embedded in new-generation machines to be self-, surroundings, and situation-aware.Machine Intelligence: Computer Vision and Natural Language Processing emphasizes computer vision and natural language processing as drivers of advances in machine intelligence. The book examines these technologies from the algorithmic level to the applications level. It also examines the integrative technologies enabling intelligent applications in business and industry.Features: Motion images object detection over voice using deep learning algorithms Ubiquitous computing and augmented reality in HCI Learning and reasoning in Artificial Intelligence Economic sustainability, mindfulness, and diversity in the age of artificial intelligence and machine learning Streaming analytics for healthcare and retail domains Covering established and emerging technologies in machine vision, the book focuses on recent and novel applications and discusses state-of-the-art technologies and tools.
Information Systems: What Every Business Student Needs to Know (Chapman & Hall/CRC Textbooks in Computing)
by Efrem G. MallachMost information systems (IS) texts overwhelm business students with overly technical information they may not need in their careers. This textbook takes a new approach to the required IS course for business majors. For each topic covered, the text highlights key "Take-Aways" that alert students to material they will need to remember during their careers. Sections titled "Where You Fit In" and "Why This Chapter Matters" explain how the topics being covered will impact students once they are on the job. Review questions, discussion questions, and summaries are included in each chapter.
The Art of Fluid Animation
by Jos StamThis book presents techniques for creating fluid-like animations with no required advanced physics and mathematical skills. It describes how to create fluid animations like water, smoke, fire, and explosions through computer code in a fun manner. It includes a historical background of the computation of fluids as well as concepts that drive fluid animations, and also provides computer code that readers can download and run on several platforms to create their own programs using fluid animation.
Cybersecurity in the Transportation Industry
by Noor Zaman Jhanjhi Imdad Ali ShahThis book offers crucial solutions and insights on how transportation companies can enhance their cybersecurity management and protect their corporate reputation and revenue from the increasing risk of cyberattacks. The movement of people and goods from one location to another has always been essential to human development and survival. People are now exploring new methods of carrying goods. Transportation infrastructure is critical to the growth of a global community that is more united and connected. The presented cybersecurity framework is an example of a risk-based method for managing cybersecurity risk. An organisation can find opportunities to strengthen and explain its management of cybersecurity risk by using its existing procedures and leveraging the framework. The framework can provide a foundation for businesses that do not currently have a formal cybersecurity program. However, there is a strong temptation to give in when a transportation company is facing a loss of millions of dollars and the disruption of the worldwide supply chain. Automobile production, sales, trucking, and shipping are high-value industries for transportation enterprises. Scammers know that these corporations stand to lose much more in terms of corporate revenue and reputation than even the highest ransom demands, making them appealing targets for their schemes. This book will address the increasing risk of cyberattacks and offer solutions and insight on the safety and security of passengers, cargo, and transportation infrastructure to enhance the security concepts of communication systems and the dynamic vendor ecosystem.