Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks

Future wireless networks have a substantial potential in terms of supporting a broad range of complex compelling applications both in military and civilian fields, where the users are able to enjoy high-rate, low-latency, low-cost and reliable information services. Achieving this ambitious goal requires new radio techniques for adaptive learning and intelligent decision making because of the complex heterogeneous nature of the network structures and wireless services. Machine learning (ML) algorithms have great success in supporting big data analytics, efficient parameter estimation and interactive decision making. Hence, in this article, we review the thirty-year history of ML by elaborating on supervised learning, unsupervised learning, reinforcement learning and deep learning. Furthermore, we investigate their employment in the compelling applications of wireless networks, including heterogeneous networks (HetNets), cognitive radios (CR), Internet of things (IoT), machine to machine networks (M2M), and so on. This article aims for assisting the readers in clarifying the motivation and methodology of the various ML algorithms, so as to invoke them for hitherto unexplored services as well as scenarios of future wireless networks.Comment: 46 pages, 22 fig

Open Educational Resources and Practices

In the last few years, Open Educational Resources (OER) have gained much attention. From January 2006 to December 2007 the Open e-Learning Content Observatory Services (OLCOS), a project co-funded by the European Commission under the eLearning Programme, explored how OER can make a difference in teaching and learning. The project aimed at promoting OER through different activities and products such as a European OER roadmap and OER tutorials. In this paper we present some results of the roadmap which provides an overview of the OER landscape and describes possible pathways towards a higher level of production, sharing and usage of OER. Moreover, the roadmap provides recommendations on required measures and actions to support decision making at the level of educational policy and institutions.The roadmap emphasises that the knowledge society demands competencies and skills that require innovative educational practices based on open sharing and the evaluation of ideas, fostering creativity and teamwork among the learners. Collaborative creation and sharing among learning communities of OER is regarded as an important catalyst of such educational innovations.The OLCOS project also developed free online tutorials for practitioners. The objective of these tutorials is supporting students and teachers in the creation, re-use and sharing of OER. To promote hands-on work, the tutorials advise on questions such as the following: How to search for OER? Which materials may be re-used and modified? How to produce and license own OER? The tutorials will be accessible and, potentially, will evolve beyond the end of the OLCOS project, because they are published on an open and successful Wiki based platform (Wikieducator.org) and can be updated by anybody.Originally published in eLearning Papers, No 7. ISSN 1887-1542. www.elearningpapers.eu

Pilot interaction with automated airborne decision making systems

Two project areas were pursued: the intelligent cockpit and human problem solving. The first area involves an investigation of the use of advanced software engineering methods to aid aircraft crews in procedure selection and execution. The second area is focused on human problem solving in dynamic environments, particulary in terms of identification of rule-based models land alternative approaches to training and aiding. Progress in each area is discussed

On the Use of XML in Medical Imaging Web-Based Applications

The rapid growth of digital technology in medical fields over recent years has increased the need for applications able to manage patient medical records, imaging data, and chart information. Web-based applications are implemented with the purpose to link digital databases, storage and transmission protocols, management of large volumes of data and security concepts, allowing the possibility to read, analyze, and even diagnose remotely from the medical center where the information was acquired. The objective of this paper is to analyze the use of the Extensible Markup Language (XML) language in web-based applications that aid in diagnosis or treatment of patients, considering how this protocol allows indexing and exchanging the huge amount of information associated with each medical case. The purpose of this paper is to point out the main advantages and drawbacks of the XML technology in order to provide key ideas for future web-based applicationsPeer ReviewedPostprint (author's final draft