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Applications of Machine Learning and Deep Learning on Biological Data
The automated learning of machines characterizes machine learning (ML). It focuses on making data-driven predictions using programmed algorithms. ML has several applications, including bioinformatics, which is a discipline of study and practice that deals with applying computational derivations to obtain biological data. It involves the collection, retrieval, storage, manipulation, and modeling of data for analysis or prediction made using customized software. Previously, comprehensive programming of bioinformatical algorithms was an extremely laborious task for such applications as predicting protein structures. Now, algorithms using ML and deep learning (DL) have increased the speed and ef...
Computational Intelligence in Industry 4.0 and 5.0 Applications
Industry 4.0 and 5.0 applications will revolutionize production, enabling smart manufacturing machines to interact with their environments. These machines will become self-aware, self-learning, and capable of real-time data interpretation for self-diagnosis and prevention of production issues. They will also self-calibrate and prioritize tasks to enhance production quality and efficiency. Computational Intelligence in Industry 4.0 and 5.0 Applications examines applications that merge three key disciplines: computational intelligence (CI), Industry 4.0, and Industry 5.0. It presents solutions using Industrial Internet of Things (IIoT) technologies, augmented by CI-based techniques, modeling, ...
Inventive Systems and Control
This book presents selected papers from the 6th International Conference on Inventive Systems and Control (ICISC 2022), held on 6–7 January 2022 at JCT College of Engineering and Technology, Coimbatore, India. The conference proceedings of ICISC 2022 includes an analysis of the class of intelligent systems and control techniques that utilizes various artificial intelligence technologies, where there is no mathematical models and system available to make them remain controlled. Inspired by various existing intelligent techniques, the primary goal of ICISC 2022 proceedings is to present the emerging innovative models to tackle the challenges faced by the existing computing and communication technologies.
Navigating the Future of Finance in the Age of AI
The financial landscape is rapidly evolving, and professionals must keep pace with the complex relationship between traditional financial practices and cutting-edge technologies. The integration of Artificial Intelligence (AI) and Machine Learning (ML) into finance presents a transformative shift that requires a deep understanding and strategic approach. Navigating the Future of Finance in the Age of AI offers a comprehensive exploration of AI's impact on the financial sector, from predictive analytics to algorithmic trading strategies. Each chapter is written by experts in the field, and they provide practical insights and real-world examples to make complex concepts accessible and actionab...
Integration and Implementation of the Internet of Things Through Cloud Computing
The internet of things (IoT) has drawn great attention from both academia and industry, since it offers a challenging notion of creating a world where all things around us are connected to the internet and communicate with each other with minimal human intervention. Another component for helping IoT to succeed is cloud computing. The combination of cloud computing and IoT will enable new monitoring services and powerful processing of sensory data streams. These applications, alongside implementation details and challenges, should also be explored for successful mainstream adoption. IoT is also fueled by the advancement of digital technologies, and the next generation era will be cloud-based ...
A Biologist’s Guide to Artificial Intelligence
A Biologist’s Guide to Artificial Intelligence: Building the Foundations of Artificial Intelligence and Machine Learning for Achieving Advancements in Life Sciences provides an overview of the basics of Artificial Intelligence for life science biologists. In 14 chapters/sections, readers will find an introduction to Artificial Intelligence from a biologist’s perspective, including coverage of AI in precision medicine, disease detection, and drug development. The book also gives insights into the AI techniques used in biology and the applications of AI in food, and in environmental, evolutionary, agricultural, and bioinformatic sciences. Final chapters cover ethical issues surrounding AI ...
Edge Computational Intelligence for AI-Enabled IoT Systems
Edge computational intelligence is an interface between edge computing and artificial intelligence (AI) technologies. This interfacing represents a paradigm shift in the world of work by enabling a broad application areas and customer-friendly solutions. Edge computational intelligence technologies are just in their infancy. Edge Computational Intelligence for AI-Enabled IoT Systems looks at the trends and advances in edge computing and edge AI, the services rendered by them, related security and privacy issues, training algorithms, architectures, and sustainable AI-enabled IoT systems. Together, these technologies benefit from ultra-low latency, faster response times, lower bandwidth costs ...
Technologies for Sustainable Global Higher Education
Digital technologies are influencing the way we learn, live, work, and exist in different contexts of society in the digital age. There are a variety of learning systems that support innovative digital approaches, and universities and organizations around the world are investing in building their own e-learning platforms. Digital technologies are enabling wider access to education and new markets for student recruitment, resulting in increased income prospects for global higher education institutions. Technology enables numerous data and information sources, which give greater access to information and data. It also enables highly virtual environments, which impact teaching and the classroom...
Data-Driven Modelling and Predictive Analytics in Business and Finance
Data-driven and AI-aided applications are next-generation technologies that can be used to visualize and realize intelligent transactions in finance, banking, and business. These transactions will be enabled by powerful data-driven solutions, IoT technologies, AI-aided techniques, data analytics, and visualization tools. To implement these solutions, frameworks will be needed to support human control of intelligent computing and modern business systems. The power and consistency of data-driven competencies are a critical challenge, and so is developing explainable AI (XAI) to make data-driven transactions transparent. Data- Driven Modelling and Predictive Analytics in Business and Finance co...
Blockchain Technology Applications in Knowledge Management
The emergence of blockchain technology is revolutionizing knowledge management by introducing unprecedented levels of security, transparency, and efficiency. Traditional knowledge management systems often struggle with issues of data integrity, access control, and collaboration among stakeholders. Blockchain addresses these challenges through its decentralized and immutable nature, enabling organizations to securely share and store knowledge assets. This transformation allows for real-time tracking of knowledge contributions, enhancing accountability and trust among users. As a result, blockchain technology not only streamlines knowledge management processes but also fosters a culture of inn...
