Today’s businesses face the pressing challenge of how to effectively engage and build lasting relationships with customers in an increasingly crowded and competitive online space. Traditional marketing tactics are no longer sufficient to capture the attention and loyalty of modern consumers who demand personalized experiences and sustainable practices from the brands they support. This shifting paradigm necessitates innovative solutions that leverage cutting-edge technologies to enhance customer engagement and foster meaningful connections. Leveraging AI for Effective Digital Relationship Marketing addresses this critical dilemma by exploring the transformative potential of artificial intelligence (AI) in revolutionizing customer relationships. By harnessing the power of AI-driven strategies, businesses can gain deeper insights into individual customer behaviors and preferences, enabling them to deliver personalized interactions and anticipate customer needs with unparalleled accuracy. Through the implementation of AI-powered solutions, companies can navigate the complexities of digital marketing with confidence, positioning themselves as leaders in building sustainable and mutually beneficial relationships with their customers.

At the dawn of the 4th Industrial Revolution, the field of Deep Learning (a sub-field of Artificial Intelligence and Machine Learning) is growing continuously and rapidly, developing both theoretically and towards applications in increasingly many and diverse other disciplines. The book at hand aims at exposing its reader to some of the most significant recent advances in deep learning-based technological applications and consists of an editorial note and an additional fifteen (15) chapters. All chapters in the book were invited from authors who work in the corresponding chapter theme and are recognized for their significant research contributions. In more detail, the chapters in the book are organized into six parts, namely (1) Deep Learning in Sensing, (2) Deep Learning in Social Media and IOT, (3) Deep Learning in the Medical Field, (4) Deep Learning in Systems Control, (5) Deep Learning in Feature Vector Processing, and (6) Evaluation of Algorithm Performance. This research book is directed towards professors, researchers, scientists, engineers and students in computer science-related disciplines. It is also directed towards readers who come from other disciplines and are interested in becoming versed in some of the most recent deep learning-based technological applications. An extensive list of bibliographic references at the end of each chapter guides the readers to probe deeper into their application areas of interest.

This book aims at updating the relevant computer science-related research communities, including professors, researchers, scientists, engineers and students, as well as the general reader from other disciplines, on the most recent advances in applications of methods based on Fusing Machine Learning Paradigms. Integrated or Hybrid Machine Learning methodologies combine together two or more Machine Learning approaches achieving higher performance and better efficiency when compared to those of their constituent components and promising major impact in science, technology and the society. The book consists of an editorial note and an additional eight chapters and is organized into two parts, namely: (i) Recent Application Areas of Fusion of Machine Learning Paradigms and (ii) Applications that can clearly benefit from Fusion of Machine Learning Paradigms. This book is directed toward professors, researchers, scientists, engineers and students in Machine Learning-related disciplines, as the hybridism presented, and the case studies described provide researchers with successful approaches and initiatives to efficiently address complex classification or regression problems. It is also directed toward readers who come from other disciplines, including Engineering, Medicine or Education Sciences, and are interested in becoming versed in some of the most recent Machine Learning-based technologies. Extensive lists of bibliographic references at the end of each chapter guide the readers to probe further into the application areas of interest to them.

This book constitutes the proceedings of the 14th International Symposium on Recent Advances in Intrusion Detection, RAID 2011, held in Menlo Park, CA, USA in September 2011. The 20 papers presented were carefully reviewed and selected from 87 submissions. The papers are organized in topical sections on application security; malware; anomaly detection; Web security and social networks; and sandboxing and embedded environments.

This book includes original research findings in the field of memetic algorithms for image processing applications. It gathers contributions on theory, case studies, and design methods pertaining to memetic algorithms for image processing applications ranging from defence, medical image processing, and surveillance, to computer vision, robotics, etc. The content presented here provides new directions for future research from both theoretical and practical viewpoints, and will spur further advances in the field.

Recent Advances in Gastroenterology: 14 is the ideal resource for keeping abreast of new developments within this fast moving field. Written by expert authors and featuring topics such as new therapies for IBD, eoisinophilic gastroenteritis, gut mucus, polyp detection, and neurological complications of liver diseases, each chapter introduces important principles that can be implemented into day to day treatment of GI disorders. Recent Advances in Gastroenterology: 14 is an invaluable revision tool for trainees, and a useful companion for practising gastroenterologists wishing to stay current in all aspects of this field. Key points 14 chapters summarising important recent advances in the field of gastroenterology All topics written in a practical and clinically relevant manner, further enhanced by ‘key clinical points for practice’ sections at the end of each chapter Provides an effective exam revision tool for the gastroenterology portion of the MRCP (UK) and the SCE in Gastroenterology All chapters written by expert authors ensuring authoritative and accurate content Full colour photographs throughout

Artificial intelligence in all its forms is increasingly interwoven into all our lives, and remains one of the most lively areas of discussion and interest in technology today. This book presents the proceedings of the 20th International Conference of the Catalan Association for Artificial Intelligence (CCIA’2017): ‘Recent Advances in Artificial Intelligence Research and Development’, held in Deltebre, Terres de l'Ebre, Spain, in October 2017. Despite its title, this annual conference is not only for researchers from the Catalan Countries, but is an international event which attracts participants from countries all around the world. In total, 41 original contributions were submitted to CCIA’2017. Of these, 21 were accepted as long papers for oral presentation and 13 were accepted as short papers to be presented as posters. These 34 submissions appear in this book organized around a number of different topics including: agents and multi-agent systems; artificial vision and image processing; machine learning; artificial neural networks; cognitive modeling; fuzzy logic and reasoning; robotics; and AI applications. The book also includes abstracts of the 3 presentations by invited speakers. The book offers a representative sample of the current state of the art in the artificial intelligence community, and will be of interest to all those working with AI worldwide.

A simulation is the imitation of the operation of a real-world process or system over time. Simulations require the use of models in which a model represents the key characteristics or behaviors of the selected system or process and the simulation represents the evolution of the model over time. Computers are often used to execute simulations. This book provides a comprehensive overview of simulation modeling and explores its use to solve a large set of problems. It is a useful resource for scholars, researchers, and undergraduate and graduate students in pure and applied mathematics, physical sciences, engineering and technology, computer science, numerical analysis, scientific computing, and science in general.