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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...
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...
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, ...
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...
Deep Learning Applications in Operations Research
The model-based approach for carrying out the classification and identification of tasks has led to progression of the machine learning paradigm in diversified fields of technology. Deep Learning Applications in Operations Research presents the varied applications of this model-based approach. Apart from the classification process, the machine learning (ML) model has become effective enough to predict future trends of any sort of phenomenon. Such fields as object classification, speech recognition, and face detection have sought extensive applications of artificial intelligence (AI) and machine learning as well. The application of AI and ML has also become increasingly common in the domains ...
Artificial Intelligence Techniques in Power Systems Operations and Analysis
An electrical power system consists of a large number of generation, transmission, and distribution subsystems. It is a very large and complex system; hence, its installation and management are very difficult tasks. An electrical system is essentially a very large network with very large data sets. Handling these data sets can require much time to analyze and subsequently implement. An electrical system is necessary but also potentially very dangerous if not operated and controlled properly. The demand for electricity is ever increasing, so maintaining load demand without overloading the system poses challenges and difficulties. Thus, planning, installing, operating, and controlling such a l...
Sustainable and Responsible Entrepreneurship and Key Drivers of Performance
Today’s entrepreneurial practices operate in a continuously challenging, highly dynamic, and everchanging environment. In these times of change, it is important to examine up-to-date theoretical infrastructure on the most powerful and representative approaches to sustainable and responsible entrepreneurship. Sustainable and Responsible Entrepreneurship and Key Drivers of Performance covers an updated view of the newest trends, novel practices, and latest tendencies concerning sustainable and responsible entrepreneurship in a world dominated by insecurity and dramatic economic, political, and managerial changes. The book presents theoretical infrastructure on approaches to sustainable and responsible entrepreneurship as well as empirical results that make a tremendous contribution to the analysis of organizations’ performance key drivers. Elaborating on topics such as greening economy, intellectual capital, knowledge management, sustainable entrepreneurial ecosystems, and social responsibility, this text is essential for entrepreneurs, managers, executives, academicians, scientists, researchers, students, practitioners, and policymakers worldwide.
Mobile Radio Communications and 5G Networks
This book features selected high-quality papers from the Third International Conference on Mobile Radio Communications and 5G Networks (MRCN 2022), held at University Institute of Engineering and Technology, Kurukshetra University, Kurukshetra, India, during June 10–12, 2022. The book features original papers by active researchers presented at the International Conference on Mobile Radio Communications and 5G Networks. It includes recent advances and upcoming technologies in the field of cellular systems, 2G/2.5G/3G/4G/5G, and beyond, LTE, WiMAX, WMAN, and other emerging broadband wireless networks, WLAN, WPAN, and various home/personal networking technologies, pervasive and wearable computing and networking, small cells and femtocell networks, wireless mesh networks, vehicular wireless networks, cognitive radio networks and their applications, wireless multimedia networks, green wireless networks, standardization of emerging wireless technologies, power management and energy conservation techniques.
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 ...
