Reduction of greenhouse gas emissions and energy use is necessary to stop the progress of climate warming, which may have a serious impact on the human environment and the ecosystem. To achieve this reduction, it is essential ...

Recent developments in sensor networks, social media, process management and data analysis envisions interlinked devices, people, processes and data, constituting an Internet-of-Everything. These networks can be used to ...

As Advanced Driver Assist Systems (ADAS) increase in complexity, it becomes essential to be able to rapidly prototype and test these systems in a reproducible and reliable way. This work explores the problem of simulating ...

The advent of the Internet enabled the sharing of information between people all around the world. Projects like Wikipedia have made human knowledge accessible to anybody with a simple mouse click. The Linked Data movement ...

Multi-Agent Reinforcement Learning (MARL) is a powerful Machine Learning paradigm, where multiple autonomous agents can learn to improve the performance of a system through experience. The majority of MARL implementations ...

There is substantial opportunity in the development of wind and tidal current turbines to help decarbonise national energy systems and to expand the economic potential of the European Union. However, well-documented cases ...

Entities such as people, locations, organizations play a key role in natural language understanding. Most of the approaches that deal with natural language processing tasks, require a method to measure the relatedness ...

Microwave imaging is an emerging imaging modality for the early detection of breast cancer. Early-time artifact removal and imaging algorithm are the two most important signal processing components of any Confocal Microwave ...

This thesis aims to examine and investigate methods that could potentially utilize images captured by consumer cameras such as smartphones to estimate depth and generate a 3D structure. After more than a century of ...

Evolutionary neural networks combine two of the most powerful areas of computing, evolutionary algorithms and neural networks. There are a number of benefits of using evolutionary algorithms to train a network over traditional ...