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In the modern science and technology there are some research directions and ch- lenges which are at the forefront of world wide research activities because of their relevance. This relevance may be related to different aspects. First, from a point of view of researchers it can be implied by just an analytic or algorithmic difficulty in the solution of problems within an area. From a broader perspective, this re- vance can be related to how important problems and challenges in a particular area are to society, corporate or national competitiveness, etc. Needless to say that the latter, more global challenges are probably more decisive a driving force for s- ence seen from a global perspective. One of such “meta-challenges” in the present world is that of intelligent s- tems. For a long time it has been obvious that the complexity of our world and the speed of changes we face in virtually all processes that have impact on our life imply a need to automate many tasks and processes that have been so far limited to human beings because they require some sort of intelligence.
This accessible and classroom-tested textbook/reference presents an introduction to the fundamentals of the emerging and interdisciplinary field of data science. The coverage spans key concepts adopted from statistics and machine learning, useful techniques for graph analysis and parallel programming, and the practical application of data science for such tasks as building recommender systems or performing sentiment analysis. Topics and features: provides numerous practical case studies using real-world data throughout the book; supports understanding through hands-on experience of solving data science problems using Python; describes techniques and tools for statistical analysis, machine learning, graph analysis, and parallel programming; reviews a range of applications of data science, including recommender systems and sentiment analysis of text data; provides supplementary code resources and data at an associated website.
An incisive account of modern Spain, from the death of Franco to the Catalan referendum and beyond “Comprehensive and engaging.”—Gideon Rachman, Financial Times Spain’s transition to democracy after Franco’s long dictatorship was widely hailed as a success, ushering in three decades of unprecedented progress and prosperity. Yet over the past decade its political consensus has been under severe strain. A stable two-party system has splintered, with disruptive new parties on the far left and far right. No government has had a majority since 2015. Michael Reid overturns the stereotypical view of Spain as a country haunted by its Francoist past. From Catalan separatism and the indignados movement to the Spanish economy’s overdependence on tourism and small business, Spain’s challenges can often seem unique. But Reid is careful to emphasize the many pressures it faces in common with its European neighbors—such as austerity, populism, and increasing polarization. The result is a penetrating yet rounded portrait of a vibrant country—one that is more often visited than understood.
This book is a collection of 45 accepted papers originally submitted for the 12th International Conference of the Catalan Association for Artificial Intelligence (ACIA). It also includes a brief summary of two papers from invited speakers. The Catalan Association for Artificial Intelligence was founded in 1994 with the aim of fostering cooperation among researchers from the Catalan-speaking AI research community. Collaboration between ACIA members and the wider international AI community has also been wel-established now for many years. The papers in these proceedings reflect this collaboration and include contributions not only from the Catalan-speaking regions of Spain, but also from France and Italy, and from as far afield as Mexico and Australia. Of al the fields in computer science, AI is the one most intertwined with all sorts of disciplines dealt with in the human experience, often employing lessons learnt in one discipline to implement a task in another. The papers in this volume reflect the rich iversity in AI, covering areas such as logics, natural language, machine learning, computer vision, robotics and multi-agent systems.
This book contains the extended papers presented at the 3rd Workshop on Supervised and Unsupervised Ensemble Methods and their Applications (SUEMA) that was held in conjunction with the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD 2010, Barcelona, Catalonia, Spain). As its two predecessors, its main theme was ensembles of supervised and unsupervised algorithms – advanced machine learning and data mining technique. Unlike a single classification or clustering algorithm, an ensemble is a group of algorithms, each of which first independently solves the task at hand by assigning a class or cluster label (voting) to instance...
Diagnostic and Therapeutic Ultrasound has recently taken an explosive growth for better safer, economic, mobile and high quality healthcare. This technology is very appealing for medical applications because it is non-ionizing, non-invasive and it is available in most of the medical and clinical facilities. Its low cost, when compared with other medical image modalities, makes it one of the preferred tools for medical monitoring, follow-up and diagnosis. Besides the traditional fields of Cardiology and Obstetrics, where it is extensively used for long time, it has became also very useful in the diagnosis of diseases of the prostate, liver and coronaries and carotids atherosclerosis. However,...
The field covered by Artificial Intelligence (AI) is multiform and gathers subjects as various as the engineering of knowledge, the automatic treatment of the language, the training and the systems multiagents, and more. This book focuses on subjects including Machine Learning, Reasoning, Neural Networks, Computer Vision, and Multiagent Systems.
Antonio Di Tecco’s research study focused on creating intelligent systems to improve user experience. Indeed, during his academic journey, he proved how to detect various human states with high accuracy. His results can be applied in healthcare, social support, education, and industry. In particular, they can enhance human-machine interaction and so increase human well-being. Hence, this dissertation presents how to design and develop intelligent systems to reach this goal.
First of all, we want to congratulate two new research communities from M- ico and Brazil that have recently joined the Iberoamerican community and the International Association for Pattern Recognition. We believe that the series of congresses that started as the “Taller Iberoamericano de Reconocimiento de Patrones (TIARP)”, and later became the “Iberoamerican Congress on Pattern Recognition (CIARP)”, has contributed to these groupconsolidatione?orts. We hope that in the near future all the Iberoamerican countries will have their own groups and associations to promote our areas of interest; and that these congresses will serve as the forum for scienti?c research exchange, sharing of ...
Artificial intelligence is no longer solely the preserve of computer scientists and researchers; it is now a part of all our lives, and hardly a day goes by without discussion and debate about the implications of its many applications in the mainstream media. This book presents the proceedings of CCIA 2023, the 25th International Conference of the Catalan Association for Artificial Intelligence, held from 25 - 27 October 2023 in Barcelona, Spain. CCIA serves as an annual forum welcoming participants from around the globe. The theme of the 2023 conference was Supportive AI, the main goals of which are to strengthen collaboration between research and industry by sharing the latest advances in ...