Amin Beheshti – författare

Artificial Intelligence and Data Science in Environmental Sensing provides state-of-the-art information on the inexpensive mass-produced sensors that are used as inputs to artificial intelligence systems. The book discusses the advances of AI and Machine Learning technologies in material design for environmental areas. It is an excellent resource for researchers and professionals who work in the field of data processing, artificial intelligence sensors and environmental applications. Presents tools, connections and proactive solutions to take sustainability programs to the next level Offers a practical guide for making students proficient in modern electronic data analysis and graphics Provides knowledge and background to develop specific platforms related to environmental sensing, including control water, air and soil quality, water and wastewater treatment, desalination, pollution mitigation/control, and resource management and recovery

This book is an introduction to social data analytics along with its challenges and opportunities in the age of Big Data and Artificial Intelligence. It focuses primarily on concepts, techniques and methods for organizing, curating, processing, analyzing, and visualizing big social data: from text to image and video analytics. It provides novel techniques in storytelling with social data to facilitate the knowledge and fact discovery. The book covers a large body of knowledge that will help practitioners and researchers in understanding the underlying concepts, problems, methods, tools and techniques involved in modern social data analytics. It also provides real-world applications of social data analytics, including: Sales and Marketing, Influence Maximization, Situational Awareness, customer success and Segmentation, and performance analysis of the industry. It provides a deep knowledge in social data analytics by comprehensively classifying the current state of research, by describing in-depth techniques and methods, and by highlighting future research directions. Lecturers will find a wealth of material to choose from for a variety of courses, ranging from undergraduate courses in data science to graduate courses in data analytics.

This book is an introduction to social data analytics along with its challenges and opportunities in the age of Big Data and Artificial Intelligence. It focuses primarily on concepts, techniques and methods for organizing, curating, processing, analyzing, and visualizing big social data: from text to image and video analytics. It provides novel techniques in storytelling with social data to facilitate the knowledge and fact discovery. The book covers a large body of knowledge that will help practitioners and researchers in understanding the underlying concepts, problems, methods, tools and techniques involved in modern social data analytics. It also provides real-world applications of social data analytics, including: Sales and Marketing, Influence Maximization, Situational Awareness, customer success and Segmentation, and performance analysis of the industry. It provides a deep knowledge in social data analytics by comprehensively classifying the current state of research, by describing in-depth techniques and methods, and by highlighting future research directions. Lecturers will find a wealth of material to choose from for a variety of courses, ranging from undergraduate courses in data science to graduate courses in data analytics.

This book constitutes revised and selected papers from the scientific satellite events held in conjunction with the18th International Conference on Service-Oriented Computing, ICSOC 2020. The conference was held virtually during December 14-17, 2020.A total of 125 submissions were received for the satellite events. The volume includes 9 papers from the PhD Symposium Track,4 papers from the Demonstration Track, and 45 papers from the following workshops:International Workshop on Artificial Intelligence for IT Operations (AIOps)International Workshop on Cyber Forensics and Threat Investigations Challenges in Emerging Infrastructures (CFTIC 2020)2nd Workshop on Smart Data Integration and Processing (STRAPS 2020)International Workshop on AI-enabled Process Automation (AI-PA 2020)International Workshop on Artificial Intelligence in the IoT Security Services (AI-IOTS 2020)

• International Workshop on Artificial Intelligence for IT Operations (AIOps)• 3rd Workshop on Smart Data Integration and Processing (STRAPS 2021)• International Workshop on AI-enabled Process Automation (AI-PA 2021)

This volume constitutes short papers and DEITS 2023 workshop papers, presented during the 12th International Conference on Model and Data Engineering, MEDI 2023, held in Sousse, Tunisia, in November 2023.The 12 short papers presented were selected from the total of 99 submissions. This volume also contains the 7 accepted papers from the DEITS 2023 workshop, held at MEDI 2023. The volume focuses on machine learning and optimization; natural language processing; modeling and data management; healthcare applications; data engineering in IoT systems.