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In a method and a mobile communications receiver for performing signal measurements, signal measurement data is received from at least one base station during at least part of a measurement period. Each measurement period comprises a number of non-equidistant snapshot measurement windows during which the receiver receives signal measurement data. At least one average signal strength value of the s

Neutron radiation produces high-energy gamma radiation through (n,gamma) reactions in matter. This can be used to detect neutron sources indirectly using gamma spectrometers. The sensitivity of a gamma spectrometer to neutrons can be amplified by surrounding it with polyvinyl chloride (PVC). The hydrogen in the PVC acts as a moderator and the chlorine emits prompt gammas when a neutron is captured

Connectivity between and within places is one of the cornerstones of geography. However, the data and methodologies used to capture connectivity are limited due to the difficulty in gathering and analysing detailed observations in time and space. Mobile phone data potentially offer a rich and unprecedented source of data, which is exhaustive in time and space following movements and communication

Globally, 500 million smallholder farmers require finance to secure a more productive, efficient, sustainable, and inclusive food system. Thus far, traditional financial services have been unsuccessful in reaching these farmers. Yet, mobile money services are proposed as a potential tool for enabling smallholder farmers access to financial services. Nonetheless, this proposed impact of mobile mone

Background. Search and selection of primary studies in Systematic Literature Reviews (SLR) is labour intensive, and hard to replicate and update. Aims. We explore a machine learning approach to support semi-automated search and selection in SLRs to address these weaknesses. Method. We 1) train a classi er on an initial set of papers, 2) extend this set of papers by automated search and snowballing

The focus of this work is detecting pedestrians, captured in a surveillance setting, and locating them in world coordinates. Commonly adopted search strategies operate in the image plane to address the object detection problem with machine learning, for example using scale-space pyramid with the sliding windows methodology or object proposals. In contrast, here a new search space is presented, whi

Bayesian optimization is a widely used method for optimizing expensive black-box functions, with Expected Improvement being one of the most commonly used acquisition functions. In contrast, information-theoretic acquisition functions aim to reduce uncertainty about the function’s optimum and are often considered fundamentally distinct from EI. In this work, we challenge this prevailing perspective