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Artificial Intelligence Technologies for Computational Biology
This text emphasizes the importance of artificial intelligence techniques in the field of biological computation. It also discusses fundamental principles that can be applied beyond bio-inspired computing. It comprehensively covers important topics including data integration, data mining, machine learning, genetic algorithms, evolutionary computation, evolved neural networks, nature-inspired algorithms, and protein structure alignment. The text covers the application of evolutionary computations for fractal visualization of sequence data, artificial intelligence, and automatic image interpretation in modern biological systems. The text is primarily written for graduate students and academic ...
Forthcoming Networks and Sustainability in the IoT Era
This book aims to provide a platform to the researchers and practitioners from both academia and industry to meet and share their experience and knowledge. Forthcoming Networks and Sustainability in the IoT Era (FoNeS-IoT), Volume 1 & 2, aims to bring together researchers and professionals to exchange ideas on the advancements in technology, application areas for advanced communication systems and development of new services, and facilitate a tremendous growth of new devices and smart things that need to be connected to the Internet through a variety of wireless technologies. Parallel to this, new capabilities such as pervasive sensing, multimedia sensing, machine learning, deep learning, un...
Sentiment Analysis and Deep Learning
This book gathers selected papers presented at International Conference on Sentimental Analysis and Deep Learning (ICSADL 2022), jointly organized by Tribhuvan University, Nepal and Prince of Songkla University, Thailand during 16 – 17 June, 2022. The volume discusses state-of-the-art research works on incorporating artificial intelligence models like deep learning techniques for intelligent sentiment analysis applications. Emotions and sentiments are emerging as the most important human factors to understand the prominent user-generated semantics and perceptions from the humongous volume of user-generated data. In this scenario, sentiment analysis emerges as a significant breakthrough technology, which can automatically analyze the human emotions in the data-driven applications. Sentiment analysis gains the ability to sense the existing voluminous unstructured data and delivers a real-time analysis to efficiently automate the business processes.
Forthcoming Networks and Sustainability in the IoT Era
This book aims to provide a platform to the researchers and practitioners from both academia and industry to meet and share their experience and knowledge. Forthcoming Networks and Sustainability in the IoT Era (FoNeS-IoT), Volume 1 & 2, aims to bring together researchers and professionals to exchange ideas on the advancements in technology, application areas for advanced communication systems and development of new services, and facilitate a tremendous growth of new devices and smart things that need to be connected to the Internet through a variety of wireless technologies. Parallel to this, new capabilities such as pervasive sensing, multimedia sensing, machine learning, deep learning, un...
Forthcoming Networks and Sustainability in the AIoT Era
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. I...
Advances in Networks, Intelligence and Computing
The year 2023 marks the 100th birth anniversary of E.F. Codd (19 August 1923 - 18 April 2003), a computer scientist, who while working for IBM invented the relational model for database management, the theoretical basis for relational databases and relational database management systems. He made other valuable contributions to computer science but the relational model, a very influential general theory of data management, remains his most mentioned, analyzed, and celebrated achievement. School of Computer Application, under the aegis of Lovely Professional University, pays homage to this great scientist of all times by hosting “CODD100 – International Conference on Networks, Intelligence and Computing (ICONIC-2023)”.
Pattern Recognition and Artificial Intelligence
This book constitutes the refereed proceedings of the 4th Mediterranean Conference on Pattern Recognition and Artificial Intelligence, MedPRAI 2020, held in Hammamet, Tunisia, in December 2020. Due to the COVID-19 pandemic the conference was held online. The 24 revised papers presented were thoroughly reviewed and selected from 72 submissions. The papers are covering the topics of recent advancements in different areas of pattern recognition and artificial intelligence, such as statistical, structural and syntactic pattern recognition, machine learning, data mining, neural networks, computer vision, multimedia systems, information retrieval, etc.
Data Intelligence and Cognitive Informatics
The book is a collection of peer-reviewed best selected research papers presented at the International Conference on Data Intelligence and Cognitive Informatics (ICDICI 2023), organized by SCAD College of Engineering and Technology, Tirunelveli, India, during June 27–28, 2023. This book discusses new cognitive informatics tools, algorithms and methods that mimic the mechanisms of the human brain which lead to an impending revolution in understating a large amount of data generated by various smart applications. The book includes novel work in data intelligence domain which combines with the increasing efforts of artificial intelligence, machine learning, deep learning and cognitive science to study and develop a deeper understanding of the information processing systems.
