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Regression Testing In Era Of Internet Of Things And Machine Learning
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Book Synopsis Regression Testing in Era of Internet of Things and Machine Learning by : Abhinandan H. Patil
Download or read book Regression Testing in Era of Internet of Things and Machine Learning written by Abhinandan H. Patil and published by Lulu.com. This book was released on 2020-03 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is for Software Engineering enthusiasts working in the field of Regression test suite design and implementation. Test Architects who are keen to apply Machine Learning to test suite data will find this book useful
Book Synopsis Regression Testing in Era of Internet of Things and Machine Learning by : Abhinandan H Patil M Tech
Download or read book Regression Testing in Era of Internet of Things and Machine Learning written by Abhinandan H Patil M Tech and published by . This book was released on 2019-11-23 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is for enthusiasts in Machine Learning applied to software testing, Regression testing, combinatorial testing, Internet of Things (IoT) Operating System (OS) test designers and implementer and everyone who is interested in Software Engineering.
Book Synopsis Regression Testing in Era of Internet of Things and Machine Learning: a Practical Approach by : Abhinandan H. Patil
Download or read book Regression Testing in Era of Internet of Things and Machine Learning: a Practical Approach written by Abhinandan H. Patil and published by . This book was released on 2019-11-24 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The book re-visits Regression testing in the light of Internet of Things Operating System testing. Book explores Machine Learning concepts applied to generic Regression test data. The book is for Software Engineering enthusiasts, test Architects who want to explore applying Machine Learning concepts to testing. As a case study, to demonstrate Internet of Things Operating System testing one of the Operating System is taken as case study. Regression test suites are written from scratch and re-engineered using leading test design tool. Automation of test script generation is explored. To demonstrate the Machine Learning concepts applied to testing Weka is used.
Book Synopsis Artificial Intelligence Systems and the Internet of Things in the Digital Era by : Abdalmuttaleb M.A Musleh Al-Sartawi
Download or read book Artificial Intelligence Systems and the Internet of Things in the Digital Era written by Abdalmuttaleb M.A Musleh Al-Sartawi and published by Springer Nature. This book was released on 2021-05-28 with total page 536 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book brings together intelligence systems and the Internet of Things, with special attention given to the opportunities, challenges, for education, business growth, and economic progression of nations which will help societies (economists, financial managers, engineers, ICT specialists, digital managers, data managers, policymakers, regulators, researchers, academics, and students) to better understand, use, and control AI and IoT to develop future strategies and to achieve sustainability goals. EAMMIS 2021 was organized by the Bridges Foundation in cooperation with the Istanbul Medeniyet University, Istanbul, Turkey, on March 19–20, 2021. EAMMIS 2021 theme was Artificial Intelligence Systems and the Internet of Things in the digital era. The papers presented at the conference provide a holistic view of AI education, MIS, cybersecurity, blockchain, Internet of Ideas (IoI), and knowledge management.
Book Synopsis Forthcoming Networks and Sustainability in the AIoT Era by : Jawad Rasheed
Download or read book Forthcoming Networks and Sustainability in the AIoT Era written by Jawad Rasheed and published by Springer Nature. This book was released on 2024 with total page 468 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces a groundbreaking approach to enhancing IoT device security, providing a comprehensive overview of its applications and methodologies. Covering a wide array of topics, from crime prediction to cyberbullying detection, from facial recognition to analyzing email spam, it addresses diverse challenges in contemporary society. Aimed at researchers, practitioners, and policymakers, this book equips readers with practical tools to tackle real-world issues using advanced machine learning algorithms. Whether you're a data scientist, law enforcement officer, or urban planner, this book is a valuable resource for implementing predictive models and enhancing public safety measures. It is a comprehensive guide for implementing machine learning solutions across various domains, ensuring optimal performance and reliability. Whether you're delving into IoT security or exploring the potential of AI in urban landscapes, this book provides invaluable insights and tools to navigate the evolving landscape of technology and data science. The book provides a comprehensive overview of the challenges and solutions in contemporary cybersecurity. Through case studies and practical examples, readers gain a deeper understanding of the security concerns surrounding IoT devices and learn how to mitigate risks effectively. The book's interdisciplinary approach caters to a diverse audience, including academics, industry professionals, and government officials, who seek to address the growing cybersecurity threats in IoT environments. Key uses of this book include implementing robust security measures for IoT devices, conducting research on machine learning algorithms for attack detection, and developing policies to enhance cybersecurity in IoT ecosystems. By leveraging advanced machine learning techniques, readers can effectively detect and mitigate cyber threats, ensuring the integrity and reliability of IoT systems. Overall, this book is a valuable resource for anyone involved in designing, implementing, or regulating IoT devices and systems.
Book Synopsis Proceedings of the 2023 5th International Conference on Hydraulic, Civil and Construction Engineering (HCCE 2023) by : Ping Xiang
Download or read book Proceedings of the 2023 5th International Conference on Hydraulic, Civil and Construction Engineering (HCCE 2023) written by Ping Xiang and published by Springer Nature. This book was released on 2024 with total page 905 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Next Generation of Internet of Things by : Raghvendra Kumar
Download or read book Next Generation of Internet of Things written by Raghvendra Kumar and published by Springer Nature. This book was released on 2022-09-26 with total page 708 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes selected papers from the International Conference on Next Generation of Internet of Things (ICNGIoT 2022), organized by Department of Computer Science and Engineering, School of Engineering, GIET University, Gunupur, Odisha, India, during February 3–4, 2022. The book covers topics such as IoT network design and architecture, IoT network virtualization, IoT sensors, privacy and security for IoT, SMART environment, social networks, data science and data analytics, cognitive intelligence and augmented intelligence, and case studies and applications.
Book Synopsis Computational Intelligence in Internet of Agricultural Things by : M. G. Sumithra
Download or read book Computational Intelligence in Internet of Agricultural Things written by M. G. Sumithra and published by Springer Nature. This book was released on with total page 464 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Building Apps for the Universal Windows Platform by : Ayan Chatterjee
Download or read book Building Apps for the Universal Windows Platform written by Ayan Chatterjee and published by Apress. This book was released on 2017-06-30 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: Develop Windows 10 applications faster and more efficiently using the Universal Windows Platform. You will use Xamarin to create apps for macOS, iOS, and Android devices. Building Apps for the Universal Windows Platform is a complete guide covering PCs, tablets, phones, and other devices such as HoloLens. You will use Windows 10 to develop apps for desktop, mobile, holographic, wearable, and IoT devices. You will reuse code to easily create cross-platform apps. What You Will Learn Design and develop apps using Visual Studio and Blend Create Cortana-enabled apps for a hands-free experience Build IoT apps and apps for wearables such as the Microsoft HoloLens Monitor apps post-publication to gain insights from actionable data using Windows Store Analytics and Azure Who This Book Is For Professional developers working independently or in a team on Windows 10 applications, and students coming into the world of software development
Book Synopsis Microelectronics, Communication Systems, Machine Learning and Internet of Things by : Vijay Nath
Download or read book Microelectronics, Communication Systems, Machine Learning and Internet of Things written by Vijay Nath and published by Springer Nature. This book was released on 2022-07-11 with total page 698 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume presents peer-reviewed papers of the First International Conference on Microelectronics, Communication Systems, Machine Learning, and the Internet of Things (MCMI-2020). This book discusses recent trends in technology and advancement in microelectronics, nano-electronics, VLSI design, IC technologies, wireless communications, optical communications, SoC, advanced instrumentations, signal processing, internet of things, machine learning, image processing, green energy, hybrid vehicles, weather forecasting, cloud computing, renewable energy, CMOS sensors, actuators, RFID, transducers, real-time embedded system, sensor network and applications, EDA design tools and techniques, fuzzy logic & artificial intelligence, high-performance computer architecture, AI-based robotics & applications, brain-computer interface, deep learning, advanced operating systems, supply chain development & monitoring, physical systems design, ICT applications, e-farming, information security, etc. It includes original papers based on theoretical, practical, experimental, simulations, development, application, measurement, and testing. The applications and solutions discussed in the book will serve as good reference material for young scholars, researchers, and academics.
Book Synopsis AI-POWERED SOFTWARE QUALITY ASSURANCE: TRANSFORMING TESTING WITH AI AND MACHINE LEARNING by : Amit Bhanushali
Download or read book AI-POWERED SOFTWARE QUALITY ASSURANCE: TRANSFORMING TESTING WITH AI AND MACHINE LEARNING written by Amit Bhanushali and published by Xoffencerpublication. This book was released on 2023-10-30 with total page 191 pages. Available in PDF, EPUB and Kindle. Book excerpt: New challenges have arisen for the construction of contemporary AI-based systems as a result of recent developments in artificial intelligence (AI), in particular machine learning (ML) and deep learning (DL), and their incorporation into software-based systems utilized in all sectors of the economy. These systems place a heavy reliance on data, are constantly evolving and bettering themselves, and display a degree of intrinsic nondeterminism. As a consequence, their behavior displays a degree of uncertainty that is universally acknowledged. As a result of these characteristics, the field of software engineering has to devise adaptable and innovative approaches to quality assurance (QA) that are capable of both constructive and in-depth analysis. This is essential in order to guarantee the product's high quality throughout the whole development process as well as while it is being put to use in actual settings. On the other hand, as Borg has pointed out, the concept of "quality" in AI-based systems does not yet have a definitive definition at this time. As was noted before, the terminology that is utilized in the field of artificial intelligence and software engineering is distinct from one another. When developing AI-based systems, the knowledge and experiences of a wide variety of organizations are combined and utilized in the construction process. While this does lead to new and creative ways, exciting breakthroughs, and a major advancement in what can be done with current AI-based systems, it also encourages the babel of language, concepts, perceptions, and underlying assumptions and principles. While this does lead to new and creative methods, exciting breakthroughs, and a substantial advancement in what can be done with current AI-based systems, this does lead to new and creative approaches. While this does result in novel and creative methods, exciting discoveries, and a significant leap forward in terms of what can be accomplished with contemporary AI-based systems, it does so in spite of the fact that. For instance, in the field of machine learning (ML), the term "regression" may be used to refer to regression models or regression analysis, but in the field of software engineering (SE), the term "regression" is used to refer to regression testing. However, in the context of machine learning (ML), the term "testing" refers to the evaluation of performance characteristics (such as accuracy) of a trained model using a holdout validation dataset. In the context of software engineering (SE), "testing" is described as the activity of executing the system in order to uncover errors. As a consequence of this, there is an increasing amount of confusion, as well as the potential of solutions that are in contradiction with one another, about how to approach quality assurance for AI-based systems and how to deal with the challenges that are associated with it. This is because of the fact that there are a growing number of solutions that are based on AI. Although the authors of this study begin their investigation from the perspective of software engineering, their ultimate goal is to include and talk about a wide variety of different points of view, all of which will eventually come together to provide a multi-dimensional picture of quality assurance for AI-based systems. While the authors of this study begin their investigation from the perspective of software engineering, their ultimate goal is to include and talk about a wide variety of different points of view. In the first part of this study project, our primary focus is on defining the terminologies related with artificial intelligence quality assurance. In the following section, Section 3, we will discuss the challenges that are involved with QA for AI. In the last part of the inquiry, we will summarize what we found and form our conclusions.
Book Synopsis Design and Implementation of Combinatorial Testing based Test Suites for Operating Systems used for Internet of Things by : Abhinandan H. Patil
Download or read book Design and Implementation of Combinatorial Testing based Test Suites for Operating Systems used for Internet of Things written by Abhinandan H. Patil and published by Lulu.com. This book was released on 2019-07-28 with total page 170 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is for Software Engineering enthusiasts. Regression testers, IoT OS testers and Combinatorial testers can get hint on how to apply Machine learning and Data Science to software testing which are left as an exercise and future work.
Book Synopsis Emerging Trends in Data Science Machine Learning, IoT and Artificial Intelligence by : Shaweta Narula
Download or read book Emerging Trends in Data Science Machine Learning, IoT and Artificial Intelligence written by Shaweta Narula and published by Leilani Katie Publication. This book was released on 2024-03-11 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: Shaweta Narula, Assistant Professor, Department of Electronics and Communication, Nutan College of Engineering and Research, Talegaon Dabhade, Pune Maharashtra,India. Vivek Narula, Quality Manager, Multinational Company, Automotive Industry, Pune, Maharashtra, India.
Book Synopsis Convergence of Artificial Intelligence and the Internet of Things by : George Mastorakis
Download or read book Convergence of Artificial Intelligence and the Internet of Things written by George Mastorakis and published by Springer Nature. This book was released on 2020-05-06 with total page 446 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers recent research work on emerging Artificial Intelligence (AI) methods for processing and storing data generated by cloud-based Internet of Things (IoT) infrastructures. Major topics covered include the analysis and development of AI-powered mechanisms in future IoT applications and architectures. Further, the book addresses new technological developments, current research trends, and industry needs. Presenting case studies, experience and evaluation reports, and best practices in utilizing AI applications in IoT networks, it strikes a good balance between theoretical and practical issues. It also provides technical/scientific information on various aspects of AI technologies, ranging from basic concepts to research grade material, including future directions. The book is intended for researchers, practitioners, engineers and scientists involved in the design and development of protocols and AI applications for IoT-related devices. As the book covers a wide range of mobile applications and scenarios where IoT technologies can be applied, it also offers an essential introduction to the field.
Book Synopsis Internet of Things-Based Machine Learning in Healthcare by : Prasenjit Dey
Download or read book Internet of Things-Based Machine Learning in Healthcare written by Prasenjit Dey and published by CRC Press. This book was released on 2024-06-10 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Internet of Medical Things (IoMT) is a system that collects data from patients with the help of different sensory inputs, e.g., an accelerometer, electrocardiography, and electroencephalography. This text presents both theoretical and practical concepts related to the application of machine learning and Internet of Things (IoT) algorithms in analyzing data generated through healthcare systems. Illustrates the latest technologies in the healthcare domain and the Internet of Things infrastructure for storing smart electronic health records Focuses on the importance of machine learning algorithms and the significance of Internet of Things infrastructure for healthcare systems Showcases the application of fog computing architecture and edge computing in novel aspects of modern healthcare services Discusses unsupervised genetic algorithm-based automatic heart disease prediction Covers Internet of Things–based hardware mechanisms and machine learning algorithms to predict the stress level of patients The text is primarily written for graduate students and academic researchers in the fields of computer science and engineering, biomedical engineering, electrical engineering, and information technology.
Book Synopsis Self-Powered Internet of Things by : Muhammad Moid Sandhu
Download or read book Self-Powered Internet of Things written by Muhammad Moid Sandhu and published by Springer Nature. This book was released on 2023-06-16 with total page 175 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers cutting edge advancements on self-powered Internet of Things, where sensing devices can be energy-positive while capturing context from the physical world. It provides new mechanisms for activity recognition without the need of conventional inertial sensors, which demand significant energy during their operation and thus quickly deplete the batteries of internet-of-things (IoT) devices. The book offers new solutions by employing energy harvesters as activity sensors as well as power sources to enable the autonomous and self-powered operation of IoT devices without the need of human intervention. It provides useful content for graduate students as well as researchers to understand the nascent technologies of human activity, fitness and health monitoring using autonomous sensors. In particular, this book is very useful for people working on pervasive computing, activity recognition, wearable IoT, fitness/healthcare and autonomous systems. This book covers a broad range of topics related to self-powered activity recognition. The main topics of this book include wearables, IoT, energy harvesting, energy harvesters as sensors, activity recognition and self-powered operation of IoT devices. This book starts with the introduction of wearable IoT devices and activity recognition and then highlights the conventional activity recognition mechanisms. After that, it describes the use of energy harvesters to power the IoT devices. Later, it explores the use of various energy harvesters as activity sensors. It also proposes the use of energy harvesters as simultaneous source of energy and context information and defines the emerging concept of energy-positive sensing compared to conventional energy-negative sensing. Finally, it explores sensor/signal fusion to enhance the performance using multiple energy harvesters and charts a way forward for future research in this area. This book covers all important and emerging topics that have significance in the design and implementation of autonomous wearable IoT devices. We believe that this book will lay the foundation for designing self-powered IoT devices which can ultimately replace the conventional wearable IoT devices which need regular recharging and replacement.
Book Synopsis Applications of Deep Learning and Big IoT on Personalized Healthcare Services by : Wason, Ritika
Download or read book Applications of Deep Learning and Big IoT on Personalized Healthcare Services written by Wason, Ritika and published by IGI Global. This book was released on 2020-02-07 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: Healthcare is an industry that has seen great advancements in personalized services through big data analytics. Despite the application of smart devices in the medical field, the mass volume of data that is being generated makes it challenging to correctly diagnose patients. This has led to the implementation of precise algorithms that can manage large amounts of information and successfully use smart living in medical environments. Professionals worldwide need relevant research on how to successfully implement these smart technologies within their own personalized healthcare processes. Applications of Deep Learning and Big IoT on Personalized Healthcare Services is a pivotal reference source that provides a collection of innovative research on the analytical methods and applications of smart algorithms for the personalized treatment of patients. While highlighting topics including cognitive computing, natural language processing, and supply chain optimization, this book is ideally designed for network designers, analysts, technology specialists, medical professionals, developers, researchers, academicians, and post-graduate students seeking relevant information on smart developments within individualized healthcare.
