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This study aimed to disentangle the influence of information status and referential form on the distribution of gestures in sustained discourse. Previous research shows that new/less accessible rather than old/more accessible information, expressed by rich rather than lean referential forms, is more likely to be accompanied by gestures. However, earlier studies have drawn on correlational results.
This paper shows how a channel sounder can be built with National Instruments (NI) Universal Software Radio Peripheral (USRP) equipment, featuring onboard FPGA processing and utilizing open-source tools. Compared to other USPR-based channel sounders, our design eases the requirements on the data link between the USRP and the host, limits the measurement data size, and increases the signal-to-noise
This thesis studies two families of methods for finding zeros of finite sums of monotone operators, the first being variance-reduced stochastic gradient (VRSG) methods. This is a large family of algorithms that use random sampling to improve the convergence rate compared to more traditional approaches. We examine the optimal sampling distributions and their interaction with the epoch length. Speci
Cloud computing has quickly grown to become an essential component in many modern-day software applications. It allows consumers, such as a provider of some web service, to quickly and on demand obtain the necessary computational resources to run their applications. It is desirable for these service providers to keep the running cost of their cloud application low while adhering to various perform
In order to keep up with the constant demand for higher data rates, the fifth generation of mobile communication (5G) introduced the use of mm-wave carrier frequencies from 24 to 71 GHz. Plenty of new frequency spectrum then became available, which has allowed for channel bandwidths of several hundreds of MHz. 6G is projected to continue this trend with even higher carrier frequencies and wider ba
Alpha masked geometry such as foliage has long been one of the trickier things to render efficiently, both for rasterization based approaches and for hardware accelerated ray-tracing. Recently, a new type of primitive was introduced to the Vulkan® and DirectX® ray-tracing APIs that promises to alleviate this issue: Opacity Micromaps, a structure that uses a bit of extra memory as hints to the pipe
Digital Twins are realistic digital representations of the physical world, frequently characterised by a two way link between digital and physical. Originating in manufacturing, they are now expanding to city and national scales. In this paper we explore connections between Geographic Information Science and National Digital Twins. Six different viewpoints and perspectives are presented on the top
We investigate frugal splitting operators for finite sum monotone inclusion problems. These operators utilize exactly one direct or resolvent evaluation of each operator of the sum, and the splitting operator's output is dictated by linear combinations of these evaluations' inputs and outputs. To facilitate analysis, we introduce a novel representation of frugal splitting operators via a generaliz
Cholesterol is an essential membrane component enriched in plasma membranes, growth cones, and synapses. The brain normally synthesizes all cholesterol locally, but the contribution of individual cell types to brain cholesterol metabolism is unknown. To investigate whether cortical projection neurons in vivo essentially require cholesterol biosynthesis and which cell types support neurons, we have
This thesis presents five papers on minimax adaptive control and estimation. Minimax adaptive estimation is a framework for output prediction and state estimation that provides a priori computable performance bounds for esti- mators. Minimax adaptive controllers ensure that the closed loop has finite gain, maintaining stability and performance under model class uncertainty. The contributions of t
Proof logging in constraint programming is an approach to certifying a conclusion reached by a solver. To allow for this, different propagators must be augmented to produce justifications for any inferences they make, so that an independent proof checker can certify correctness. The Circuit constraint is used to enforce a Hamiltonian cycle on a set of vertices, e.g. for vehicle routing. Maintainin
Symmetry and dominance breaking can be crucial for solving hard combinatorial search and optimisation problems, but the correctness of these techniques sometimes relies on subtle arguments. For this reason, it is desirable to produce efficient, machine-verifiable certificates that solutions have been computed correctly. Building on the cutting planes proof system, we develop a certification method
We propose a method for sensor array self-localization using a set of sources at unknown locations. The sources produce signals whose times of arrival are registered at the sensors. We look at the general case where neither the emission times of the sources nor the reference time frames of the receivers are known. Unlike previous work, our method directly recovers the array geometry, instead of fi
The dramatic improvements in Boolean satisfiability (SAT) solving since the turn of the millennium have made it possible to leverage conflict-driven clause learning (CDCL) solvers for many combinatorial problems in academia and industry, and the use of proof logging has played a crucial role in increasing the confidence that the results these solvers produce are correct. However, the fact that SAT
Salts affect the solvation thermodynamics of molecules of all sizes; the Hofmeister series is a prime example in which different ions lead to salting-in or salting-out of aqueous proteins. Early work of Tanford led to the discovery that the solvation of molecular surface motifs is proportional to the solvent accessible surface area (SASA), and later studies have shown that the proportionality cons
We study a controlled evolutionary dynamics that models the spread of a novel state in a network where the exogenous control aims to quickly spread the novel state. We estimate the performance of the system by analytically establishing upper and lower bounds on the expected time needed for the novel state to replace the original one. Such bounds are expressed as functions of the control policy ado
In this work, we present a method for acquiring, storing, and using scene data to enable realistic shading of virtual objects in an augmented reality application. Our method allows for sparse sampling of the environment’s lighting condition while still delivering a convincing shading to the rendered objects. We use common camera parameters, provided by a head-mounted camera, to get lighting inform
This article discusses theoretical and practical aspects of real-time brain computer interface control methods based on Bayesian statistics. The theoretical aspects include how the data from the brain computer interface can be translated into a Gaussian mixture model that is used in the Bayesian statistics-based control methods. The practical aspects include how the control methods improve the per
This article discusses practical and theoretical aspects of real-time brain computer interface control methods based on Bayesian statistics. We investigate and improve the performance of automatic control and feedback algorithms of a reactive brain computer interface based on a visual oddball paradigm for faster statistical convergence. We introduce transfer learning using Gaussian mixture models,
