This book constitutes the refereed proceedings of the scientific track of the 7th Congress of the Italian Association for Artificial Intelligence, AI*IA 2001, held in Bari, Italy, in September 2001. The 25 revised long papers and 16 revised short papers were carefully reviewed and selected for inclusion in the volume. The papers are organized in topical sections on machine learning; automated reasoning; knowledge representation; multi-agent systems; natural language processing; perception, vision, and robotics; and planning and scheduling.

This book constitutes the refereed proceedings of the scientific track of the 7th Congress of the Italian Association for Artificial Intelligence, AI*IA 2001, held in Bari, Italy, in September 2001. The 25 revised long papers and 16 revised short papers were carefully reviewed and selected for inclusion in the volume. The papers are organized in topical sections on machine learning; automated reasoning; knowledge representation; multi-agent systems; natural language processing; perception, vision, and robotics; and planning and scheduling.

This book presents a variety of perspectives on vision-based applications. These contributions are focused on optoelectronic sensors, 3D & 2D machine vision technologies, robot navigation, control schemes, motion controllers, intelligent algorithms and vision systems. The authors focus on applications of unmanned aerial vehicles, autonomous and mobile robots, industrial inspection applications and structural health monitoring. Recent advanced research in measurement and others areas where 3D & 2D machine vision and machine control play an important role, as well as surveys and reviews about vision-based applications. These topics are of interest to readers from diverse areas, including electrical, electronics and computer engineering, technologists, students and non-specialist readers. • Presents current research in image and signal sensors, methods, and 3D & 2D technologies in vision-based theories and applications; • Discusses applications such as daily use devices including robotics, detection, tracking and stereoscopic vision systems, pose estimation, avoidance of objects, control and data exchange for navigation, and aerial imagery processing; • Includes research contributions in scientific, industrial, and civil applications.

This compilation probably looks like one of the craziest things a human being could spend his or her time on. Yet nobody would wonder at someone taking a short walk every day - after twenty five years that person would have covered a surprisingly long distance. This is exactly the story behind this list, which appeared first as a few pages within the directory StarGuides (or whatever name it had at that time) and as a distinct sister publication since 1990. The idea behind this dictionary is to offer astronomers and related space scientists practical assistance in decoding the numerous abbreviations, acronyms, contractions and symbols which they might encounter in all aspects of the vast range of their professional activities, including traveling. Perhaps it is a bit paradoxical, but if scientists quickly grasp the meaning of an acronym solely in their own specific discipline, they will probably encounter more difficulties when dealing with adjacent fields. It is for this purpose that this dictionary might be most often used. Scientists might also refer to this compilation in order to avoid identifying a project by an acronym which already has too many meanings or confused definitions.

This book constitutes the refereed proceedings of the 7th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2003, held in Seoul, Korea in April/Mai 2003. The 38 revised full papers and 20 revised short papers presented together with two invited industrial contributions were carefully reviewed and selected from 215 submissions. The papers are presented in topical sections on stream mining, graph mining, clustering, text mining, Bayesian networks, association rules, semi-structured data mining, classification, data analysis, and feature selection.

Ontology, originally a fundamental part of philosophical enquiry, is concerned with the analysis and categorization of what exists. The advent of complex information systems which rely on robust and coherent formal representations of their subject matter has led to a renewed focus on ontological enquiry, and the systematic study of such representations are at the center of the modern discipline of formal ontology. This is now a research focus in domains as diverse as conceptual modeling, database design, software engineering, artificial intelligence, computational linguistics, the life sciences, bioinformatics, geographic information science, knowledge engineering, information retrieval and the semantic web. This book presents the proceedings of the 9th edition of the Formal Ontology in Information Systems conference (FOIS 2016) held in Annecy, France, in July 2016. It contains the 25 full papers delivered at the conference (an acceptance rate of 30.9% for the main track), as well as the abstracts of the 3 keynotes by Gilberto Câmara, Stephen Mumford and Friederike Moltmann. The remainder of the book is divided into the sections: Foundations; Space, Time and Change; Cognition, Language and Semantics; Empiricism and Measurement; Ontology for Engineering; Biomedical Ontologies; and Ontology of Social Reality. The domains addressed by the papers include geography, biomedicine, economics, social reality and engineering, and the book will be of interest to all those working in these fields, as well as to anybody with an interest in formal ontology.

This book constitutes the Selected Papers of the 8th International Workshop on Graphics Recognition, Achievements, Challenges and Evolution, held in La Rochelle, France, in July 2009.

In the field of finance, the pervasive influence of algorithms has transformed the very fabric of the industry. Today, over 75% of trades are orchestrated by algorithms, making them the linchpin for trade automation, predictions, and decision-making. This algorithmic reliance, while propelling financial services into unprecedented efficiency, has also ushered in a host of challenges. As the financial sector becomes increasingly algorithm-driven, concerns about risk assessment, market manipulation, and the ethical implications of automated decision-making have taken center stage. Artificial Intelligence and Machine Learning-Powered Smart Finance, meticulously examines the intersection of computational finance and advanced algorithms and the challenges associated with this technology. As algorithms permeate various facets of financial services, the book takes a deep dive into their applications, spanning forecasting, portfolio optimization, market trends analysis, and cryptoanalysis. It sheds light on the role of AI-based algorithms in personnel selection, implementing trusted financial services, developing recommendation systems for financial platforms, and detecting fraud, presenting a compelling case for the integration of innovative solutions in the financial sector. As the book unravels the intricate tapestry of algorithmic applications in finance, it also illuminates the ethical considerations and governance frameworks essential for navigating the delicate balance between technological innovation and responsible financial practices.