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| fog data science website: Handbook of Research on Cloud and Fog Computing Infrastructures for Data Science Raj, Pethuru, Raman, Anupama, 2018-05-18 Fog computing is quickly increasing its applications and uses to the next level. As it continues to grow, different types of virtualization technologies can thrust this branch of computing further into mainstream use. The Handbook of Research on Cloud and Fog Computing Infrastructures for Data Science is a key reference volume on the latest research on the role of next-generation systems and devices that are capable of self-learning and how those devices will impact society. Featuring wide-ranging coverage across a variety of relevant views and themes such as cognitive analytics, data mining algorithms, and the internet of things, this publication is ideally designed for programmers, IT professionals, students, researchers, and engineers looking for innovative research on software-defined cloud infrastructures and domain-specific analytics. |
| fog data science website: Data Science and Security Dharm Singh Jat, Samiksha Shukla, Aynur Unal, Durgesh Kumar Mishra, 2020-07-31 This book presents best selected papers presented at the International Conference on Data Science for Computational Security (IDSCS 2020), organized by the Department of Data Science, CHRIST (Deemed to be University), Pune Lavasa Campus, India, during 13–14 March 2020. The proceeding will be targeting the current research works in the areas of data science, data security, data analytics, artificial intelligence, machine learning, computer vision, algorithms design, computer networking, data mining, big data, text mining, knowledge representation, soft computing and cloud computing. |
| fog data science website: Fog Computing, Deep Learning and Big Data Analytics-Research Directions C.S.R. Prabhu, 2019-01-04 This book provides a comprehensive picture of fog computing technology, including of fog architectures, latency aware application management issues with real time requirements, security and privacy issues and fog analytics, in wide ranging application scenarios such as M2M device communication, smart homes, smart vehicles, augmented reality and transportation management. This book explores the research issues involved in the application of traditional shallow machine learning and deep learning techniques to big data analytics. It surveys global research advances in extending the conventional unsupervised or clustering algorithms, extending supervised and semi-supervised algorithms and association rule mining algorithms to big data Scenarios. Further it discusses the deep learning applications of big data analytics to fields of computer vision and speech processing, and describes applications such as semantic indexing and data tagging. Lastly it identifies 25 unsolved research problems and research directions in fog computing, as well as in the context of applying deep learning techniques to big data analytics, such as dimensionality reduction in high-dimensional data and improved formulation of data abstractions along with possible directions for their solutions. |
| fog data science website: Predictive Analytics in Cloud, Fog, and Edge Computing Hiren Kumar Thakkar, Chinmaya Kumar Dehury, Prasan Kumar Sahoo, Bharadwaj Veeravalli, 2022-12-16 This book covers the relationship of recent technologies (such as Blockchain, IoT, and 5G) with the cloud computing as well as fog computing, and mobile edge computing. The relationship will not be limited to only architecture proposal, trends, and technical advancements. However, the book also explores the possibility of predictive analytics in cloud computing with respect to Blockchain, IoT, and 5G. The recent advancements in the internet-supported distributed computing i.e. cloud computing, has made it possible to process the bulk amount of data in a parallel and distributed. This has made it a lucrative technology to process the data generated from technologies such as Blockchain, IoT, and 5G. However, there are several issues a Cloud Service Provider (CSP) encounters, such as Blockchain security in cloud, IoT elasticity and scalability management in cloud, Service Level Agreement (SLA) compliances for 5G, Resource management, Load balancing, and Fault-tolerance. This edited book will discuss the aforementioned issues in connection with Blockchain, IoT, and 5G. Moreover, the book discusses how the cloud computing is not sufficient and one needs to use fog computing, and edge computing to efficiently process the data generated from IoT, and 5G. Moreover, the book shows how smart city, smart healthcare system, and smart communities are few of the most relevant IoT applications where fog computing plays a significant role. The book discusses the limitation of fog computing and the need for the edge computing to further reduce the network latency to process streaming data from IoT devices. The book also explores power of predictive analytics of Blockchain, IoT, and 5G data in cloud computing with its sister technologies. Since, the amount of resources increases day-by day, artificial intelligence (AI) tools are becoming more popular due to their capability which can be used in solving wide variety of issues, such as minimize the energy consumption of physical servers, optimize the service cost, improve the quality of experience, increase the service availability, efficiently handle the huge data flow, manages the large number of IoT devices, etc. |
| fog data science website: Roundtable on Data Science Postsecondary Education National Academies of Sciences, Engineering, and Medicine, Division of Behavioral and Social Sciences and Education, Division on Engineering and Physical Sciences, Board on Science Education, Computer Science and Telecommunications Board, Committee on Applied and Theoretical Statistics, Board on Mathematical Sciences and Analytics, 2020-09-02 Established in December 2016, the National Academies of Sciences, Engineering, and Medicine's Roundtable on Data Science Postsecondary Education was charged with identifying the challenges of and highlighting best practices in postsecondary data science education. Convening quarterly for 3 years, representatives from academia, industry, and government gathered with other experts from across the nation to discuss various topics under this charge. The meetings centered on four central themes: foundations of data science; data science across the postsecondary curriculum; data science across society; and ethics and data science. This publication highlights the presentations and discussions of each meeting. |
| fog data science website: Data Science Tools Christopher Greco, 2020-05-14 In the world of data science there are myriad tools available to analyze data. This book describes some of the popular software application tools along with the processes for downloading and using them in the most optimum fashion. The content includes data analysis using Microsoft Excel, KNIME, R, and OpenOffice (Spreadsheet). Each of these tools will be used to apply statistical concepts including confidence intervals, normal distribution, T-Tests, linear regression, histograms, and geographic analysis using real data from Federal Government sources. Features: Analyzes data using popular applications such as Excel, R, KNIME, and OpenOffice Covers statistical concepts including confidence intervals, normal distribution, T-Tests, linear regression, histograms, and geographic analysis Capstone exercises analyze data using the different software packages |
| fog data science website: Data Science and Intelligent Systems Radek Silhavy, Petr Silhavy, Zdenka Prokopova, 2021-11-16 This book constitutes the second part of refereed proceedings of the 5th Computational Methods in Systems and Software 2021 (CoMeSySo 2021) proceedings. The real-world problems related to data science and algorithm design related to systems and software engineering are presented in this papers. Furthermore, the basic research’ papers that describe novel approaches in the data science, algorithm design and in systems and software engineering are included. The CoMeSySo 2021 conference is breaking the barriers, being held online. CoMeSySo 2021 intends to provide an international forum for the discussion of the latest high-quality research results |
| fog data science website: Data Science and Machine Learning with Python Gurpreet Singh Josan, Jagroop Kaur, 2024-04-06 Data Science and Machine Learning are two interconnected fields that play a pivotal role in modern technological advancements. Data science involves extracting insights and knowledge from vast amounts of data using various tools and techniques. This includes data collection, cleaning, analysis, and interpretation to uncover valuable patterns and trends. On the other hand, machine learning is a subset of artificial intelligence (AI) that focuses on developing algorithms and models capable of learning from data to make predictions and decisions. Machine learning algorithms can automatically improve their performance over time by learning from new data, making them crucial for tasks such as image recognition, natural language processing, and predictive analytics. Together, data science and machine learning empower businesses and researchers to leverage data-driven insights for informed decision-making and innovation across diverse domains. This book is intended for the first course in Data Science and Machine Learning and covers the required topics in sufficient depth to meet the requirements of the readers. |
| fog data science website: Cloud Computing Enabled Big-Data Analytics in Wireless Ad-hoc Networks Sanjoy Das, Ram Shringar Rao, Indrani Das, Vishal Jain, Nanhay Singh, 2022-03-20 This book discusses intelligent computing through the Internet of Things (IoT) and Big-Data in vehicular environments in a single volume. It covers important topics, such as topology-based routing protocols, heterogeneous wireless networks, security risks, software-defined vehicular ad-hoc networks, vehicular delay tolerant networks, and energy harvesting for WSNs using rectenna. FEATURES Covers applications of IoT in Vehicular Ad-hoc Networks (VANETs) Discusses use of machine learning and other computing techniques for enhancing performance of networks Explains game theory-based vertical handoffs in heterogeneous wireless networks Examines monitoring and surveillance of vehicles through the vehicular sensor network Investigates theoretical approaches on software-defined VANET The book is aimed at graduate students and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer science, and engineering. |
| fog data science website: Data Science Jing He, Philip S. Yu, Yong Shi, Xingsen Li, Zhijun Xie, Guangyan Huang, Jie Cao, Fu Xiao, 2020-02-01 This book constitutes the refereed proceedings of the 6th International Conference on Data Science, ICDS 2019, held in Ningbo, China, during May 2019. The 64 revised full papers presented were carefully reviewed and selected from 210 submissions. The research papers cover the areas of Advancement of Data Science and Smart City Applications, Theory of Data Science, Data Science of People and Health, Web of Data, Data Science of Trust and Internet of Things. |
| fog data science website: Data Science and Security Samiksha Shukla, Xiao-Zhi Gao, Joseph Varghese Kureethara, Durgesh Mishra, 2022-07-01 This book presents best selected papers presented at the International Conference on Data Science for Computational Security (IDSCS 2022), organized by the Department of Data Science, CHRIST (Deemed to be University), Pune Lavasa Campus, India, during 11 – 12 February 2022. The book proposes new technologies and discusses future solutions and applications of data science, data analytics and security. The book targets current research works in the areas of data science, data security, data analytics, artificial intelligence, machine learning, computer vision, algorithms design, computer networking, data mining, big data, text mining, knowledge representation, soft computing and cloud computing. |
| fog data science website: Computational Intelligence, Data Analytics and Applications Fausto Pedro García Márquez, Akhtar Jamil, Süleyman Eken, Alaa Ali Hameed, 2023-03-14 This book is a compilation of accepted papers presented at the International Conference on Computing, Intelligence and Data Analytics (ICCIDA) in 2022 organized by Information Systems Engineering of the Kocaeli University, Turkey on September 16-17, 2022. The book highlights some of the latest research advances and cutting-edge analyses of real-world problems related to Computing, Intelligence and Data Analytics and their applications in various domains. This includes state of the art models and methods used on benchmark datasets. |
| fog data science website: Fog and Edge Computing Rajkumar Buyya, Satish Narayana Srirama, 2018-12-31 A comprehensive guide to Fog and Edge applications, architectures, and technologies Recent years have seen the explosive growth of the Internet of Things (IoT): the internet-connected network of devices that includes everything from personal electronics and home appliances to automobiles and industrial machinery. Responding to the ever-increasing bandwidth demands of the IoT, Fog and Edge computing concepts have developed to collect, analyze, and process data more efficiently than traditional cloud architecture. Fog and Edge Computing: Principles and Paradigms provides a comprehensive overview of the state-of-the-art applications and architectures driving this dynamic field of computing while highlighting potential research directions and emerging technologies. Exploring topics such as developing scalable architectures, moving from closed systems to open systems, and ethical issues rising from data sensing, this timely book addresses both the challenges and opportunities that Fog and Edge computing presents. Contributions from leading IoT experts discuss federating Edge resources, middleware design issues, data management and predictive analysis, smart transportation and surveillance applications, and more. A coordinated and integrated presentation of topics helps readers gain thorough knowledge of the foundations, applications, and issues that are central to Fog and Edge computing. This valuable resource: Provides insights on transitioning from current Cloud-centric and 4G/5G wireless environments to Fog Computing Examines methods to optimize virtualized, pooled, and shared resources Identifies potential technical challenges and offers suggestions for possible solutions Discusses major components of Fog and Edge computing architectures such as middleware, interaction protocols, and autonomic management Includes access to a website portal for advanced online resources Fog and Edge Computing: Principles and Paradigms is an essential source of up-to-date information for systems architects, developers, researchers, and advanced undergraduate and graduate students in fields of computer science and engineering. |
| fog data science website: Data Science and Big Data Analytics in Smart Environments Marta Chinnici, Florin Pop, Catalin Negru, 2021-07-28 Most applications generate large datasets, like social networking and social influence programs, smart cities applications, smart house environments, Cloud applications, public web sites, scientific experiments and simulations, data warehouse, monitoring platforms, and e-government services. Data grows rapidly, since applications produce continuously increasing volumes of both unstructured and structured data. Large-scale interconnected systems aim to aggregate and efficiently exploit the power of widely distributed resources. In this context, major solutions for scalability, mobility, reliability, fault tolerance and security are required to achieve high performance and to create a smart environment. The impact on data processing, transfer and storage is the need to re-evaluate the approaches and solutions to better answer the user needs. A variety of solutions for specific applications and platforms exist so a thorough and systematic analysis of existing solutions for data science, data analytics, methods and algorithms used in Big Data processing and storage environments is significant in designing and implementing a smart environment. Fundamental issues pertaining to smart environments (smart cities, ambient assisted leaving, smart houses, green houses, cyber physical systems, etc.) are reviewed. Most of the current efforts still do not adequately address the heterogeneity of different distributed systems, the interoperability between them, and the systems resilience. This book will primarily encompass practical approaches that promote research in all aspects of data processing, data analytics, data processing in different type of systems: Cluster Computing, Grid Computing, Peer-to-Peer, Cloud/Edge/Fog Computing, all involving elements of heterogeneity, having a large variety of tools and software to manage them. The main role of resource management techniques in this domain is to create the suitable frameworks for development of applications and deployment in smart environments, with respect to high performance. The book focuses on topics covering algorithms, architectures, management models, high performance computing techniques and large-scale distributed systems. |
| fog data science website: Big Data Analytics and Intelligent Techniques for Smart Cities Kolla Bhanu Prakash, Janmenjoy Nayak, B tp Madhhav, Sanjeevikumar Padmanaban, Valentina Emilia Balas, 2021-09-20 Big Data Analytics and Intelligent Techniques for Smart Cities covers fundamentals, advanced concepts, and applications of big data analytics for smart cities in a single volume. This comprehensive reference text discusses big data theory modeling and simulation for smart cities and examines case studies in a single volume. The text discusses how to develop a smart city and state-of-the-art system design, system verification, real-time control and adaptation, Internet of Things, and testbeds. It covers applications of smart cities as they relate to smart transportation/connected vehicle (CV) and intelligent transportation systems (ITS) for improved mobility, safety, and environmental protection. It will be useful as a reference text for graduate students in different areas including electrical engineering, computer science engineering, civil engineering, and electronics and communications engineering. Features: Technologies and algorithms associated with the application of big data for smart cities Discussions on big data theory modeling and simulation for smart cities Applications of smart cities as they relate to smart transportation and intelligent transportation systems (ITS) Discussions on concepts including smart education, smart culture, and smart transformation management for social and societal changes |
| fog data science website: Data Science and Big Data Analytics in Smart Environments Marta Chinnici, Florin Pop, Catalin Negru, 2021-07-27 Most applications generate large datasets, like social networking and social influence programs, smart cities applications, smart house environments, Cloud applications, public web sites, scientific experiments and simulations, data warehouse, monitoring platforms, and e-government services. Data grows rapidly, since applications produce continuously increasing volumes of both unstructured and structured data. Large-scale interconnected systems aim to aggregate and efficiently exploit the power of widely distributed resources. In this context, major solutions for scalability, mobility, reliability, fault tolerance and security are required to achieve high performance and to create a smart environment. The impact on data processing, transfer and storage is the need to re-evaluate the approaches and solutions to better answer the user needs. A variety of solutions for specific applications and platforms exist so a thorough and systematic analysis of existing solutions for data science, data analytics, methods and algorithms used in Big Data processing and storage environments is significant in designing and implementing a smart environment. Fundamental issues pertaining to smart environments (smart cities, ambient assisted leaving, smart houses, green houses, cyber physical systems, etc.) are reviewed. Most of the current efforts still do not adequately address the heterogeneity of different distributed systems, the interoperability between them, and the systems resilience. This book will primarily encompass practical approaches that promote research in all aspects of data processing, data analytics, data processing in different type of systems: Cluster Computing, Grid Computing, Peer-to-Peer, Cloud/Edge/Fog Computing, all involving elements of heterogeneity, having a large variety of tools and software to manage them. The main role of resource management techniques in this domain is to create the suitable frameworks for development of applications and deployment in smart environments, with respect to high performance. The book focuses on topics covering algorithms, architectures, management models, high performance computing techniques and large-scale distributed systems. |
| fog data science website: Rational Fog M. Susan Lindee, 2020-09-15 A thought-provoking examination of the intersections of knowledge and violence, and the quandaries and costs of modern, technoscientific warfare. Science and violence converge in modern warfare. While the finest minds of the twentieth century have improved human life, they have also produced human injury. They engineered radar, developed electronic computers, and helped mass produce penicillin all in the context of military mobilization. Scientists also developed chemical weapons, atomic bombs, and psychological warfare strategies. Rational Fog explores the quandary of scientific and technological productivity in an era of perpetual war. Science is, at its foundation, an international endeavor oriented toward advancing human welfare. At the same time, it has been nationalistic and militaristic in times of crisis and conflict. As our weapons have become more powerful, scientists have struggled to reconcile these tensions, engaging in heated debates over the problems inherent in exploiting science for military purposes. M. Susan Lindee examines this interplay between science and state violence and takes stock of researchers’ efforts to respond. Many scientists who wanted to distance their work from killing have found it difficult and have succumbed to the exigencies of war. Indeed, Lindee notes that scientists who otherwise oppose violence have sometimes been swept up in the spirit of militarism when war breaks out. From the first uses of the gun to the mass production of DDT and the twenty-first-century battlefield of the mind, the science of war has achieved remarkable things at great human cost. Rational Fog reminds us that, for scientists and for us all, moral costs sometimes mount alongside technological and scientific advances. |
| fog data science website: The Smart Cyber Ecosystem for Sustainable Development Pardeep Kumar, Vishal Jain, Vasaki Ponnusamy, 2021-10-12 The Smart Cyber Ecosystem for Sustainable Development As the entire ecosystem is moving towards a sustainable goal, technology driven smart cyber system is the enabling factor to make this a success, and the current book documents how this can be attained. The cyber ecosystem consists of a huge number of different entities that work and interact with each other in a highly diversified manner. In this era, when the world is surrounded by many unseen challenges and when its population is increasing and resources are decreasing, scientists, researchers, academicians, industrialists, government agencies and other stakeholders are looking toward smart and intelligent cyber systems that can guarantee sustainable development for a better and healthier ecosystem. The main actors of this cyber ecosystem include the Internet of Things (IoT), artificial intelligence (AI), and the mechanisms providing cybersecurity. This book attempts to collect and publish innovative ideas, emerging trends, implementation experiences, and pertinent user cases for the purpose of serving mankind and societies with sustainable societal development. The 22 chapters of the book are divided into three sections: Section I deals with the Internet of Things, Section II focuses on artificial intelligence and especially its applications in healthcare, whereas Section III investigates the different cyber security mechanisms. Audience This book will attract researchers and graduate students working in the areas of artificial intelligence, blockchain, Internet of Things, information technology, as well as industrialists, practitioners, technology developers, entrepreneurs, and professionals who are interested in exploring, designing and implementing these technologies. |
| fog data science website: Cognitive Analytics: Concepts, Methodologies, Tools, and Applications Management Association, Information Resources, 2020-03-06 Due to the growing use of web applications and communication devices, the use of data has increased throughout various industries, including business and healthcare. It is necessary to develop specific software programs that can analyze and interpret large amounts of data quickly in order to ensure adequate usage and predictive results. Cognitive Analytics: Concepts, Methodologies, Tools, and Applications provides emerging perspectives on the theoretical and practical aspects of data analysis tools and techniques. It also examines the incorporation of pattern management as well as decision-making and prediction processes through the use of data management and analysis. Highlighting a range of topics such as natural language processing, big data, and pattern recognition, this multi-volume book is ideally designed for information technology professionals, software developers, data analysts, graduate-level students, researchers, computer engineers, software engineers, IT specialists, and academicians. |
| fog data science website: COVID-19: Integrating Artificial Intelligence, Data Science, Mathematics, Medicine and Public Health, Epidemiology, Neuroscience, Neurorobotics, and Biomedical Science in Pandemic Management, volume II Atefeh Abedini, Reza Lashgari, 2024-02-29 |
| fog data science website: Web Analytics 2.0 Avinash Kaushik, 2009-12-30 Adeptly address today’s business challenges with this powerful new book from web analytics thought leader Avinash Kaushik. Web Analytics 2.0 presents a new framework that will permanently change how you think about analytics. It provides specific recommendations for creating an actionable strategy, applying analytical techniques correctly, solving challenges such as measuring social media and multichannel campaigns, achieving optimal success by leveraging experimentation, and employing tactics for truly listening to your customers. The book will help your organization become more data driven while you become a super analysis ninja! |
| fog data science website: Proceedings of the International Joint Conference on Science and Engineering 2022 (IJCSE 2022) Hapsari Peni Agustin, Alexandre Maniçoba De Oliveira, Yeni Anistyasari, Kiyoshi Ueda, Arie Wardhono, Imami A. T. Rahayu, 2023-02-10 This is an open access book. This joint conference features three international conferences: International Conference on Research and Academic Community Services (ICRACOS); Mathematics, Informatics, Science, and Education International Conference (MISEIC), and International Conference on Vocational Education and Electrical Engineering (ICVEE). It encourages dissemination of ideas in Computer Science, Applied science on engineering, and Engineering and provides a forum for intellectuals from all over the world to discuss and present their research findings on the research areas. This conference will be held in Surabaya, East Java, Indonesia on September 10, 2022 – September 11, 2022. We are inviting academics, researchers, and practitioners to submit research-based papers that address any topics within the broad areas of Computer Science, Applied science on engineering, and Engineering . |
| fog data science website: AI-Centric Modeling and Analytics Alex Khang, Vugar Abdullayev, Babasaheb Jadhav, Shashi Kant Gupta, Gilbert Morris, 2023-12-06 This book shares new methodologies, technologies, and practices for resolving issues associated with leveraging AI-centric modeling, data analytics, machine learning-aided models, Internet of Things-driven applications, and cybersecurity techniques in the era of Industrial Revolution 4.0. AI-Centric Modeling and Analytics: Concepts, Technologies, and Applications focuses on how to implement solutions using models and techniques to gain insights, predict outcomes, and make informed decisions. This book presents advanced AI-centric modeling and analysis techniques that facilitate data analytics and learning in various applications. It offers fundamental concepts of advanced techniques, technologies, and tools along with the concept of real-time analysis systems. It also includes AI-centric approaches for the overall innovation, development, and implementation of business development and management systems along with a discussion of AI-centric robotic process automation systems that are useful in many government and private industries. This reference book targets a mixed audience of engineers and business analysts, researchers, professionals, and students from various fields. |
| fog data science website: Data Science in Chemistry Thorsten Gressling, 2020-11-23 The ever-growing wealth of information has led to the emergence of a fourth paradigm of science. This new field of activity – data science – includes computer science, mathematics and a given specialist domain. This book focuses on chemistry, explaining how to use data science for deep insights and take chemical research and engineering to the next level. It covers modern aspects like Big Data, Artificial Intelligence and Quantum computing. |
| fog data science website: Recent Trends in Electronics and Communication Amit Dhawan, Vijay Shanker Tripathi, Karm Veer Arya, Kshirasagar Naik, 2021-12-13 This book comprises select proceedings of the International Conference on VLSI, Communication and Signal processing (VCAS 2020). The contents are broadly divided into three topics – VLSI, Communication, and Signal Processing. The book focuses on the latest innovations, trends, and challenges encountered in the different areas of electronics and communication, especially in the area of microelectronics and VLSI design, communication systems and networks, and image and signal processing. It also offers potential solutions and provides an insight into various emerging areas such as Internet of Things (IoT), System on a Chip (SoC), Sensor Networks, underwater and underground communication networks etc. This book will be useful for academicians and professionals alike. |
| fog data science website: Fog Data Analytics for IoT Applications Sudeep Tanwar, 2020-08-25 This book discusses the unique nature and complexity of fog data analytics (FDA) and develops a comprehensive taxonomy abstracted into a process model. The exponential increase in sensors and smart gadgets (collectively referred as smart devices or Internet of things (IoT) devices) has generated significant amount of heterogeneous and multimodal data, known as big data. To deal with this big data, we require efficient and effective solutions, such as data mining, data analytics and reduction to be deployed at the edge of fog devices on a cloud. Current research and development efforts generally focus on big data analytics and overlook the difficulty of facilitating fog data analytics (FDA). This book presents a model that addresses various research challenges, such as accessibility, scalability, fog nodes communication, nodal collaboration, heterogeneity, reliability, and quality of service (QoS) requirements, and includes case studies demonstrating its implementation. Focusing on FDA in IoT and requirements related to Industry 4.0, it also covers all aspects required to manage the complexity of FDA for IoT applications and also develops a comprehensive taxonomy. |
| fog data science website: Adoption of Data Analytics in Higher Education Learning and Teaching Dirk Ifenthaler, David Gibson, 2020-08-10 The book aims to advance global knowledge and practice in applying data science to transform higher education learning and teaching to improve personalization, access and effectiveness of education for all. Currently, higher education institutions and involved stakeholders can derive multiple benefits from educational data mining and learning analytics by using different data analytics strategies to produce summative, real-time, and predictive or prescriptive insights and recommendations. Educational data mining refers to the process of extracting useful information out of a large collection of complex educational datasets while learning analytics emphasizes insights and responses to real-time learning processes based on educational information from digital learning environments, administrative systems, and social platforms. This volume provides insight into the emerging paradigms, frameworks, methods and processes of managing change to better facilitate organizational transformation toward implementation of educational data mining and learning analytics. It features current research exploring the (a) theoretical foundation and empirical evidence of the adoption of learning analytics, (b) technological infrastructure and staff capabilities required, as well as (c) case studies that describe current practices and experiences in the use of data analytics in higher education. |
| fog data science website: Research Anthology on Edge Computing Protocols, Applications, and Integration Management Association, Information Resources, 2022-04-01 Edge computing is quickly becoming an important technology throughout a number of fields as businesses and industries alike embrace the benefits it can have in their companies. The streamlining of data is crucial for the development and evolution of businesses in order to keep up with competition and improve functions overall. In order to appropriately utilize edge computing to its full potential, further study is required to examine the potential pitfalls and opportunities of this innovative technology. The Research Anthology on Edge Computing Protocols, Applications, and Integration establishes critical research on the current uses, innovations, and challenges of edge computing across disciplines. The text highlights the history of edge computing and how it has been adapted over time to improve industries. Covering a range of topics such as bandwidth, data centers, and security, this major reference work is ideal for industry professionals, computer scientists, engineers, practitioners, researchers, academicians, scholars, instructors, and students. |
| fog data science website: Behind the Fog Lisa Martino-Taylor, 2017-07-28 Behind the Fog is the first in-depth, comprehensive examination of the United States’ Cold War radiological weapons program. The book examines controversial military-sponsored studies and field trials using radioactive simulants that exposed American civilians to radiation and other hazardous substances without their knowledge or consent during the Cold War. Although Western biological and chemical weapons programs have been analyzed by a number of scholars, Behind the Fog is a strong departure from the rest in that the United States radiological weapons program has been generally unknown to the public. Martino-Taylor documents the coordinated efforts of a small group of military scientists who advanced a four-pronged secret program of human-subject radiation studies that targeted unsuspecting Americans for Cold War military purposes. Officials enabled such projects to advance through the layering of secrecy, by embedding classified studies in other studies, and through outright deception. Agency and academic partnerships advanced, supported, and concealed the studies from the public at large who ultimately served as unwitting test subjects. Martino-Taylor’s comprehensive research illuminates a dark chapter of government secrecy, the military-industrial-academic complex, and large-scale organizational deviance in American history. In its critical approach, Behind the Fog effectively examines the mechanisms that allow large-scale elite deviance to take place in modern society. |
| fog data science website: Cloud Computing and Services Science Donald Ferguson, Víctor Méndez Muñoz, Claus Pahl, Markus Helfert, 2020-06-03 This book constitutes extended, revised and selected papers from the 9th International Conference on Cloud Computing and Services Science, CLOSER 2019, held in Heraklion, Greece, in May 2019.The 11 papers presented in this volume were carefully reviewed and selected from a total of 102 submissions. CLOSER 2019 focuses on the emerging area of Cloud Computing, inspired by some latest advances that concern the infrastructure, operations, and available servicesthrough the global network. |
| fog data science website: ICDSMLA 2020 Amit Kumar, Sabrina Senatore, Vinit Kumar Gunjan, 2021-11-08 This book gathers selected high-impact articles from the 2nd International Conference on Data Science, Machine Learning & Applications 2020. It highlights the latest developments in the areas of artificial intelligence, machine learning, soft computing, human–computer interaction and various data science and machine learning applications. It brings together scientists and researchers from different universities and industries around the world to showcase a broad range of perspectives, practices and technical expertise. |
| fog data science website: Feel the Fog April Pulley Sayre, 2020-09-15 Discover the wonder and science behind fog in this stunning and immersive nonfiction picture book from award-winning author and photographer April Pulley Sayre. Damp and drippy, misty and mysterious…fog is fascinating. Step inside this natural phenomenon and see how fog is formed, how it clears away, and why it feels chilly. Young readers will love this lyrical and gorgeously photo-illustrated exploration of these clouds that come to visit. |
| fog data science website: Big Scientific Data Management Jianhui Li, Xiaofeng Meng, Ying Zhang, Wenjuan Cui, Zhihui Du, 2019-08-06 This book constitutes the refereed proceedings of the First International Conference on Big Scientific Data Management, BigSDM 2018, held in Beijing, Greece, in November/December 2018. The 24 full papers presented together with 7 short papers were carefully reviewed and selected from 86 submissions. The topics involved application cases in the big scientific data management, paradigms for enhancing scientific discovery through big data, data management challenges posed by big scientific data, machine learning methods to facilitate scientific discovery, science platforms and storage systems for large scale scientific applications, data cleansing and quality assurance of science data, and data policies. |
| fog data science website: Big Data Demystified David Stephenson, 2018-02-14 The full text downloaded to your computer With eBooks you can: search for key concepts, words and phrases make highlights and notes as you study share your notes with friends eBooks are downloaded to your computer and accessible either offline through the Bookshelf (available as a free download), available online and also via the iPad and Android apps. Upon purchase, you'll gain instant access to this eBook. Time limit The eBooks products do not have an expiry date. You will continue to access your digital ebook products whilst you have your Bookshelf installed. 'Big Data' refers to a new class of data, to which 'big' doesn't quite do it justice. Much like an ocean is more than simply a deeper swimming pool, big data is fundamentally different to traditional data and needs a whole new approach. Packed with examples and case studies, this clear, comprehensive book will show you how to accumulate and utilise 'big data' in order to develop your business strategy. Big Data Demystified is your practical guide to help you draw deeper insights from the vast information at your fingertips; you will be able to understand customer motivations, speed up production lines, and even offer personalised experiences to each and every customer. With 20 years of industry experience, David Stephenson shows how big data can give you the best competitive edge, and why it is integral to the future of your business. |
| fog data science website: Fog/Edge Computing For Security, Privacy, and Applications Wei Chang, Jie Wu, 2021-01-04 This book provides the state-of-the-art development on security and privacy for fog/edge computing, together with their system architectural support and applications. This book is organized into five parts with a total of 15 chapters. Each area corresponds to an important snapshot. The first part of this book presents an overview of fog/edge computing, focusing on its relationship with cloud technology and the future with the use of 5G communication. Several applications of edge computing are discussed. The second part of this book considers several security issues in fog/edge computing, including the secure storage and search services, collaborative intrusion detection method on IoT-fog computing, and the feasibility of deploying Byzantine agreement protocols in untrusted environments. The third part of this book studies the privacy issues in fog/edge computing. It first investigates the unique privacy challenges in fog/edge computing, and then discusses a privacy-preserving framework for the edge-based video analysis, a popular machine learning application on fog/edge. This book also covers the security architectural design of fog/edge computing, including a comprehensive overview of vulnerabilities in fog/edge computing within multiple architectural levels, the security and intelligent management, the implementation of network-function-virtualization-enabled multicasting in part four. It explains how to use the blockchain to realize security services. The last part of this book surveys applications of fog/edge computing, including the fog/edge computing in Industrial IoT, edge-based augmented reality, data streaming in fog/edge computing, and the blockchain-based application for edge-IoT. This book is designed for academics, researchers and government officials, working in the field of fog/edge computing and cloud computing. Practitioners, and business organizations (e.g., executives, system designers, and marketing professionals), who conduct teaching, research, decision making, and designing fog/edge technology will also benefit from this book The content of this book will be particularly useful for advanced-level students studying computer science, computer technology, and information systems, but also applies to students in business, education, and economics, who would benefit from the information, models, and case studies therein. |
| fog data science website: Advanced Practical Approaches to Web Mining Techniques and Application Obaid, Ahmed J., Polkowski, Zdzislaw, Bhushan, Bharat, 2022-03-18 The rapid increase of web pages has introduced new challenges for many organizations as they attempt to extract information from a massive corpus of web pages. Finding relevant information, eliminating irregular content, and retrieving accurate results has become extremely difficult in today’s world where there is a surplus of information available. It is crucial to further understand and study web mining in order to discover the best ways to connect users with appropriate information in a timely manner. Advanced Practical Approaches to Web Mining Techniques and Application aims to illustrate all the concepts of web mining and fosters transformative, multidisciplinary, and novel approaches that introduce the practical method of analyzing various web data sources and extracting knowledge by taking into consideration the unique challenges present in the environment. Covering a range of topics such as data science and security threats, this reference work is ideal for industry professionals, researchers, academicians, practitioners, scholars, instructors, and students. |
| fog data science website: Handbook of Research on Managerial Practices and Disruptive Innovation in Asia Ordoñez de Pablos, Patricia, Zhang, Xi, Chui, Kwok Tai, 2019-08-30 Collaboration in business allows for equitable opportunities and inclusive growth as the economy rises while also permitting partnering organizations to adopt and utilize the latest successful practices and management. However, a market in stasis may require a displacement in order to allow businesses to grow and create new alliances and partnerships toward a shared economy. There is a need for studies that seek to understand the necessity of market disruption and the best supervisory methods for remaining relevant and profitable in a time of change. The Handbook of Research on Managerial Practices and Disruptive Innovation in Asia is an essential reference source that explores successful executive behavior and business operations striving toward a more inclusive economy. Featuring research on topics such as employee welfare, brand orientation, and entrepreneurship, this publication is ideally designed for human resources developers, policymakers, IT specialists, economists, executives, managers, corporate directors, information technologists, and academicians seeking current research focusing on innovative business factors and sustainable economies in Asia. |
| fog data science website: Smart Data Kuan-Ching Li, Beniamino Di Martino, Laurence T. Yang, Qingchen Zhang, 2019-03-19 Smart Data: State-of-the-Art Perspectives in Computing and Applications explores smart data computing techniques to provide intelligent decision making and prediction services support for business, science, and engineering. It also examines the latest research trends in fields related to smart data computing and applications, including new computing theories, data mining and machine learning techniques. The book features contributions from leading experts and covers cutting-edge topics such as smart data and cloud computing, AI for networking, smart data deep learning, Big Data capture and representation, AI for Big Data applications, and more. Features Presents state-of-the-art research in big data and smart computing Provides a broad coverage of topics in data science and machine learning Combines computing methods with domain knowledge and a focus on applications in science, engineering, and business Covers data security and privacy, including AI techniques Includes contributions from leading researchers |
| fog data science website: Computational Intelligence in Oncology Khalid Raza, 2022-03-01 This book encapsulates recent applications of CI methods in the field of computational oncology, especially cancer diagnosis, prognosis, and its optimized therapeutics. The cancer has been known as a heterogeneous disease categorized in several different subtypes. According to WHO’s recent report, cancer is a leading cause of death worldwide, accounting for over 10 million deaths in the year 2020. Therefore, its early diagnosis, prognosis, and classification to a subtype have become necessary as it facilitates the subsequent clinical management and therapeutics plan. Computational intelligence (CI) methods, including artificial neural networks (ANNs), fuzzy logic, evolutionary computations, various machine learning and deep learning, and nature-inspired algorithms, have been widely utilized in various aspects of oncology research, viz. diagnosis, prognosis, therapeutics, and optimized clinical management. Appreciable progress has been made toward the understanding the hallmarks of cancer development, progression, and its effective therapeutics. However, notwithstanding the extrinsic and intrinsic factors which lead to drastic increment in incidence cases, the detection, diagnosis, prognosis, and therapeutics remain an apex challenge for the medical fraternity. With the advent in CI-based approaches, including nature-inspired techniques, and availability of clinical data from various high-throughput experiments, medical consultants, researchers, and oncologists have seen a hope to devise and employ CI in various aspects of oncology. The main aim of the book is to occupy state-of-the-art applications of CI methods which have been derived from core computer sciences to back medical oncology. This edited book covers artificial neural networks, fuzzy logic and fuzzy inference systems, evolutionary algorithms, various nature-inspired algorithms, and hybrid intelligent systems which are widely appreciated for the diagnosis, prognosis, and optimization of therapeutics of various cancers. Besides, this book also covers multi-omics exploration, gene expression analysis, gene signature identification of cancers, genomic characterization of tumors, anti-cancer drug design and discovery, drug response prediction by means of CI, and applications of IoT, IoMT, and blockchain technology in cancer research. |
| fog data science website: Cloud Reliability Engineering Rathnakar Achary, Pethuru Raj, 2021-04-11 Coud reliability engineering is a leading issue of cloud services. Cloud service providers guarantee computation, storage and applications through service-level agreements (SLAs) for promised levels of performance and uptime. Cloud Reliability Engineering: Technologies and Tools presents case studies examining cloud services, their challenges, and the reliability mechanisms used by cloud service providers. These case studies provide readers with techniques to harness cloud reliability and availability requirements in their own endeavors. Both conceptual and applied, the book explains reliability theory and the best practices used by cloud service companies to provide high availability. It also examines load balancing, and cloud security. Written by researchers and practitioners, the book’s chapters are a comprehensive study of cloud reliability and availability issues and solutions. Various reliability class distributions and their effects on cloud reliability are discussed. An important aspect of reliability block diagrams is used to categorize poor reliability of cloud infrastructures, where enhancement can be made to lower the failure rate of the system. This technique can be used in design and functional stages to determine poor reliability of a system and provide target improvements. Load balancing for reliability is examined as a migrating process or performed by using virtual machines. The approach employed to identify the lightly loaded destination node to which the processes/virtual machines migrate can be optimized by employing a genetic algorithm. To analyze security risk and reliability, a novel technique for minimizing the number of keys and the security system is presented. The book also provides an overview of testing methods for the cloud, and a case study discusses testing reliability, installability, and security. A comprehensive volume, Cloud Reliability Engineering: Technologies and Tools combines research, theory, and best practices used to engineer reliable cloud availability and performance. |
Fog - Wikipedia
Fog is a visible aerosol consisting of tiny water droplets or ice crystals suspended in the air at or near the Earth's surface. [1] [2] Fog can be considered a type of low-lying cloud usually …
How Fog Forms - National Weather Service
Evaporation or Mixing Fog. This type of fog forms when sufficient water vapor is added to the air by evaporation and the moist air mixes with cooler, relatively drier air. The two common types are …
Fog | Definition, Formation, Types, & Facts | Britannica
May 30, 2025 · Fog, cloud of small water droplets that is near ground level and sufficiently dense to reduce horizontal visibility to less than 1,000 metres (3,281 feet). The word fog also may refer to …
How Does Fog Form? | Weather.com - The Weather Channel
Oct 14, 2013 · The most common form of fog, known as radiation fog, typically occurs on clear nights as the earth's surface cools moist air immediately above it.
6 Different Types of Fog - Farmers' Almanac
Jan 31, 2024 · While ground fog is caused by cool, moist air rising from the ground, advection fog forms when warm, damp air flows over cold ground. You can distinguish between ground fog and …
Fog – Definition, Types, Formation - Science Notes and Projects
Oct 19, 2024 · Fog plays a crucial role in many ecosystems, particularly in regions with limited rainfall. Fog acts as a water source for plants, animals, and even human communities. Fog as a …
The 6 Types Of Fog - Boldmethod
Jun 15, 2024 · Here's what you should know about the 6 most common types of fog. How Does Fog Form? Fog may be present when a small temperature/dew-point spread exists (usually within 5 …
What is Fog? - Earth Networks
Fog is a visible aerosol comprising tiny water droplets or ice crystals suspended in the air at or near the Earth’s surface. Nearby bodies of water, topography, and weather conditions are three …
Fog
Feb 18, 2025 · Fog is a cloud that touches the ground. Fog can be thin or thick, meaning people have difficulty seeing through it. In some conditions, fog can be so thick that it makes it hard to …
fog - Glossary of Meteorology
Mar 30, 2024 · According to international definition, fog reduces visibility below 1 km (0.62 miles). Fog differs from cloud only in that the base of fog is at the earth's surface while clouds are above …
Fog - Wikipedia
Fog is a visible aerosol consisting of tiny water droplets or ice crystals suspended in the air at or near the Earth's surface. [1] [2] Fog can be considered a type of low-lying cloud usually …
How Fog Forms - National Weather Service
Evaporation or Mixing Fog. This type of fog forms when sufficient water vapor is added to the air by evaporation and the moist air mixes with cooler, relatively drier air. The two common types …
Fog | Definition, Formation, Types, & Facts | Britannica
May 30, 2025 · Fog, cloud of small water droplets that is near ground level and sufficiently dense to reduce horizontal visibility to less than 1,000 metres (3,281 feet). The word fog also may …
How Does Fog Form? | Weather.com - The Weather Channel
Oct 14, 2013 · The most common form of fog, known as radiation fog, typically occurs on clear nights as the earth's surface cools moist air immediately above it.
6 Different Types of Fog - Farmers' Almanac
Jan 31, 2024 · While ground fog is caused by cool, moist air rising from the ground, advection fog forms when warm, damp air flows over cold ground. You can distinguish between ground fog …
Fog – Definition, Types, Formation - Science Notes and Projects
Oct 19, 2024 · Fog plays a crucial role in many ecosystems, particularly in regions with limited rainfall. Fog acts as a water source for plants, animals, and even human communities. Fog as …
The 6 Types Of Fog - Boldmethod
Jun 15, 2024 · Here's what you should know about the 6 most common types of fog. How Does Fog Form? Fog may be present when a small temperature/dew-point spread exists (usually …
What is Fog? - Earth Networks
Fog is a visible aerosol comprising tiny water droplets or ice crystals suspended in the air at or near the Earth’s surface. Nearby bodies of water, topography, and weather conditions are …
Fog
Feb 18, 2025 · Fog is a cloud that touches the ground. Fog can be thin or thick, meaning people have difficulty seeing through it. In some conditions, fog can be so thick that it makes it hard to …
fog - Glossary of Meteorology
Mar 30, 2024 · According to international definition, fog reduces visibility below 1 km (0.62 miles). Fog differs from cloud only in that the base of fog is at the earth's surface while clouds are …
