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Integrated Sensing and Communications
The coming generations of wireless network technologies will serve, not only as a means of connecting physical and digital environments, but also to set the foundation for an intelligent world in which all aspects are interconnected, sensed, and endowed with intelligence. Beyond merely providing communication capabilities, future networks will have the capacity to "see" and interpret the physical world. This development compels us to re-imagine the design of current communication infrastructures and terminals, taking into account crucial aspects such as fundamental constraints and tradeoffs, information extraction and processing technologies, issues of public security and privacy, as well as...
Machine Learning and Knowledge Discovery in Databases. Research Track
The multi-volume set LNAI 12975 until 12979 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2021, which was held during September 13-17, 2021. The conference was originally planned to take place in Bilbao, Spain, but changed to an online event due to the COVID-19 pandemic. The 210 full papers presented in these proceedings were carefully reviewed and selected from a total of 869 submissions. The volumes are organized in topical sections as follows: Research Track: Part I: Online learning; reinforcement learning; time series, streams, and sequence models; transfer and multi-task learning; semi-supervised and f...
Biomedical Engineering
Biomedical Engineering can be seen as a mix of Medicine, Engineering and Science. In fact, this is a natural connection, as the most complicated engineering masterpiece is the human body. And it is exactly to help our “body machine” that Biomedical Engineering has its niche. This book brings the state-of-the-art of some of the most important current research related to Biomedical Engineering. I am very honored to be editing such a valuable book, which has contributions of a selected group of researchers describing the best of their work. Through its 36 chapters, the reader will have access to works related to ECG, image processing, sensors, artificial intelligence, and several other exciting fields.
Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track
The multi-volume set LNAI 12975 until 12979 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2021, which was held during September 13-17, 2021. The conference was originally planned to take place in Bilbao, Spain, but changed to an online event due to the COVID-19 pandemic. The 210 full papers presented in these proceedings were carefully reviewed and selected from a total of 869 submissions. The volumes are organized in topical sections as follows: Research Track: Part I: Online learning; reinforcement learning; time series, streams, and sequence models; transfer and multi-task learning; semi-supervised and f...
Machine Learning and Knowledge Discovery in Databases
Chapters “On the Current State of Reproducibility and Reporting of Uncertainty for Aspect-Based SentimentAnalysis” and “Contextualized Graph Embeddings for Adverse Drug Event Detection” are licensed under theterms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/). For further details see license information in the chapter.
Vehicular Technologies
This book provides an insight for students, researchers and practitioners on the area of vehicular communications explaining and presenting solutions for some of the most critical issues in this field and, hopefully, inspiring new research directions. The book is organized in Sections, which respond to different layers and aspects of the vehicular technology: infrastructures, cells deployment and its integration with the V2V part, access procedures, advanced services and applications as localization, spectrum sensing, relay-based cooperative networks.
ECAI 2020
This book presents the proceedings of the 24th European Conference on Artificial Intelligence (ECAI 2020), held in Santiago de Compostela, Spain, from 29 August to 8 September 2020. The conference was postponed from June, and much of it conducted online due to the COVID-19 restrictions. The conference is one of the principal occasions for researchers and practitioners of AI to meet and discuss the latest trends and challenges in all fields of AI and to demonstrate innovative applications and uses of advanced AI technology. The book also includes the proceedings of the 10th Conference on Prestigious Applications of Artificial Intelligence (PAIS 2020) held at the same time. A record number of ...
Short-Term Load Forecasting using Machine Learning Methods
Maintaining the balance between generation and consumption is at the heart of electricity grid operation. A disruption to this balance can lead to grid overloads, outages, system damage, rising electricity costs or wasted electricity. For this reason, accurate forecasting of load behavior is crucial. In this work, two classes of ML-based algorithms were used for load forecasting: the Hidden Markov Models (HMMs) and the Deep Neural Networks (DNNs), both of which provide stable and more accurate results than the considered benchmark methods. HMMs could be successfully used as a stand-alone predictor with a training based on Maximum Likelihood Estimation (MLE) in combination with a clustering o...
Connectivity Prediction in Mobile Ad Hoc Networks for Real-Time Control
Cyber-physical systems are the next step in realizing the centuries old ubiquitous computing idea by focusing on open real-time systems design and device connectivity. Mobile ad hoc networks offer the flexible, local connectivity that cyber-physical systems require, if the connectivity can be realized dependably. One aspect of the dependability is the prediction of connectivity in the mobile ad hoc network. The presented research contributes to the connectivity prediction in mobile ad hoc networks with moving network participants in two ways: It systematically analyses the influence of scenario parameters on a set of connectivity metrics and it proposes and evaluates three classes of prediction models for these metrics.
