Social networking has increased drastically in recent years, resulting in an increased amount of data being created daily. Furthermore, diversity of issues and complexity of the social networks pose a challenge in social network mining. Traditional algorithm software cannot deal with such complex and vast amounts of data, necessitating the development of novel analytic approaches and tools.
This reference work deals with social network aspects of big data analytics. It covers theory, practices and challenges in social networking. The book spans numerous disciplines like neural networking, deep learning, artificial intelligence, visualization, e-learning in higher education, e-healthcare, security and intrusion detection.
This book is a collection of best selected research papers presented at International Conference on Intelligent and Smart Computing in Data Analytics (ISCDA 2020), held at K L University, Guntur, Andhra Pradesh, India. The primary focus is to address issues and developments in advanced computing, intelligent models and applications, smart technologies and applications. It includes topics such as artificial intelligence and machine learning, pattern recognition and analysis, computational intelligence, signal and image processing, bioinformatics, ubiquitous computing, genetic fuzzy systems, hybrid evolutionary algorithms, nature-inspired smart hybrid systems, Internet of things, industrial IoT, health informatics, human-computer interaction and social network analysis. The book presents innovative work by leading academics, researchers and experts from industry.
This book presents a collection of state-of-the-art approaches for deep-learning-based biomedical and health-related applications. The aim of healthcare informatics is to ensure high-quality, efficient health care, and better treatment and quality of life by efficiently analyzing abundant biomedical and healthcare data, including patient data and electronic health records (EHRs), as well as lifestyle problems. In the past, it was common to have a domain expert to develop a model for biomedical or health care applications; however, recent advances in the representation of learning algorithms (deep learning techniques) make it possible to automatically recognize the patterns and represent the given data for the development of such model.
This book allows new researchers and practitioners working in the field to quickly understand the best-performing methods. It also enables them to compare different approaches and carry forward their research in an important area that has a direct impact on improving the human life and health.
It is intended for researchers, academics, industry professionals, and those at technical institutes and R&D organizations, as well as students working in the fields of machine learning, deep learning, biomedical engineering, health informatics, and related fields.
AI, Edge and IoT Smart Agriculture integrates applications of IoT and edge computing and data analytics for sustainable agricultural development. It introduces Edge of Thing-based data analytics along with IoT for predictability of crop, soil and plant disease occurrence for improved sustainability and increased profitability. The book also addresses precision irrigation, precision horticulture, greenhouse IoT, livestock monitoring, IoT ecosystem for agriculture, mobile robot for precision agriculture, energy monitoring, storage management along with smart farming. It provides an overarching focuse on sustainable environment and sustainable economic development through smart and e-agriculture.
Providing a medium for the exchange of expertise and inspiration, contributions from both smart agriculture as well as data mining researchers from around the world provide foundational insights. Including contributions from the Data mining, data analytics, Edge of Things and cloud research communities working in the farming production sector the book provides practical application opportunities for the resolution of real-world problems.
AI, Edge and IoT Smart Agriculture provides the reader with a broad coverage of the concepts, themes, and instruments of this important and evolving area of IOT based agriculture, Edge of Things and cloud based farming, Greenhouse IOT, mobile agriculture, sustainable agriculture, and big data analytics in agriculture towards smart farming.
This book gathers high-quality research papers presented at the International Conference on Computing in Engineering and Technology (ICCET 2020) [formerly ICCASP], a flagship event in the area of engineering and emerging next-generation technologies jointly organized by the Dr. Babasaheb Ambedkar Technological University and MGM's College of Engineering in Nanded, India, on 9-11 January 2020. Focusing on next-generation information processing systems, this second volume of the proceedings includes papers on cloud computing and information systems, artificial intelligence and the Internet of Things, hardware design and communication, and front-end design.
It is intended for researchers, academics, industry professionals, and those at technical institutes and R & D organizations, as well as students working in the fields of machine learning, deep learning, biomedical engineering, health informatics, and related fields.
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