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Revisiting Rotation Averaging : Uncertainties and Robust Losses

In this paper, we revisit the rotation averaging problem applied in global Structure-from-Motion pipelines. We argue that the main problem of current methods is the minimized cost function that is only weakly connected with the input data via the estimated epipolar geometries. We propose to better model the underlying noise distributions by directly propagating the uncertainty from the point corre

Interactive HPC and the LUNARC Desktop Environment

Since 2011, LUNARC has aimed to provide an interactive HPC environment for its resource users. Several different architectures have been used, but since 2013, we have been using a remote desktop environment based on Cendio's ThinLinc [1] combined with a custom backend framework, GfxLauncher [2], supporting hardware-accelerated graphics applications and Jupyter Notebooks [3] submitted to the backen

Natural marine aerosols : A study on atmospheric chemistry, new particle formation and particle growth

The role of natural marine aerosols in the global climate system remains understudied and uncertain. This is true for the emissions of natural volatile compounds over the ocean, the oxidation of said compounds and their impact on particle formation and particle growth. In this thesis, the emission, chemistry and aerosol particle processes relating to these compounds were studied using different pr

A Lyapunov Approach to Stochastic Interaction Dynamics Over Large-Scale Networks

We study stochastic interaction network models whereby a finite population of agents, identified with the nodes of a graph, update their states in response to pairwise interactions with their neighbors as well as spontaneous mutations. These include the main epidemic models, such as the Susceptible-Infected -Susceptible, the Susceptible-Infected-Recovered, and the Susceptible-Infected-Recovered-Su

Demystifying AMD SEV Performance Penalty for NFV Deployment

Network Function Virtualization (NFV) has shifted communication networks towards more adaptable software solutions, but this transition raises new security concerns, particularly in public cloud deployments. While Intel’s Software Guard Extensions (SGX) offers a potential remedy, it requires complex application adaptations. This paper investigates AMD’s Secure Encrypted Virtualization (SEV) as an

Learn to relax : Integrating 0-1 integer linear programming with pseudo-Boolean conflict-driven search

Conflict-driven pseudo-Boolean solvers optimize 0-1 integer linear programs by extending the conflict-driven clause learning (CDCL) paradigm from SAT solving. Though pseudo-Boolean solvers have the potential to be exponentially more efficient than CDCL solvers in theory, in practice they can sometimes get hopelessly stuck even when the linear programming (LP) relaxation is infeasible over the real

Partitioning and Optimization of High-Level Stream Applications for Multi-Clock-Domain Architectures

In this paper we propose a design methodology to partition dataflow applications on a multi clock domain architecture. This work shows how starting from a high level dataflow representation of a dynamic program it is possible to reduce the overall power consumption without impacting the performances. Two different approaches are illustrated, both based on the post-processing and analysis of the ca

Sensing and Classification Using Massive MIMO : A Tensor Decomposition-Based Approach

Wireless-based activity sensing has gained significant attention due to its wide range of applications. We investigate radio-based multi-class classification of human activities using massive multiple-input multiple-output (MIMO) channel measurements in line-of-sight and non line-of-sight scenarios. We propose a tensor decomposition-based algorithm to extract features by exploiting the complex cor

Generalized Two-Magnitude Check Node Updating with Self Correction for 5G LDPC Codes Decoding

The min-sum (MS) and approximate-min* (a-min*) algorithms are alternatives of the belief propagation (BP) algorithm for decoding low-density parity-check (LDPC) codes. To lower the BP decoding complexity, both algorithms compute two magnitudes at each check node (CN) and pass them to the neighboring variable nodes (VNs).In this work we propose a new algorithm, ga-min*, that generalizes the MS and

27.5-29.5 GHz Switched Array Sounder for Dynamic Channel Characterization: Design, Implementation and Measurements

A pre-requisite for the design of wireless systems is the understanding of the propagation channel. While a wealth of propagation knowledge exists for bands below 6 GHz, the same can not be said for bands approaching millimeter-wave frequencies. In this paper, we present the design, implementation and measurement-based verification of a re-configurable 27.5-29.5 GHz channel sounder for measuring d

Initial Analysis of Dynamic Panel Activation for Large Intelligent Surfaces

Large intelligent surfaces (LIS) have the potential to be the beyond-massive-MIMO solution, even further improving spectral efficiency, coverage, reliability and other performance measures. They also open up for entirely new services, such as precise localization, environment sensing, and wireless energy transfer. By constructing larger surfaces as a grid of panels, we can activate and deactivate

Limitations of field-theory simulation for exploring phase separation: The role of repulsion in a lattice protein model

Field-theory simulation by the complex Langevin method offers an alternative to conventional sampling techniques for exploring the forces driving biomolecular liquid–liquid phase separation. Such simulations have recently been used to study several polyampholyte systems. Here, we formulate a field theory corresponding to the hydrophobic/polar (HP) lattice protein model, with finite same-site repul

Clique Is Hard on Average for Unary Sherali-Adams

We prove that unary Sherali-Adams requires proofs of size nΩ(d) to rule out the existence of an nΘ(1)-clique in Erdős-Rényi random graphs whose maximum clique is of size d ≤ 2 log n. This lower bound is tight up to the multiplicative constant in the exponent. We obtain this result by introducing a technique inspired by pseudo-calibration which may be of independent interest. The technique involves

The Inverted Wish : Towards Walter Benjamin’s Notion of Time

Walter Benjamin’s complex notion of time, permeating much of his historical, political, and cultural-critical thought, has been the subject of considerable discussion. In particular, the interaction between the two opposing categories of historical time and messianic time poses a great difficulty: how do messianic moments of cessation act within the homogeneous continuum of history? To propose one

Hybrid elicitation and quantile-parametrized likelihood

This paper extends the application of quantile-based Bayesian inference to probability distributions defined in terms of quantiles of observable quantities. Quantile-parameterized distributions are characterized by high shape flexibility and parameter interpretability, making them useful for eliciting information about observables. To encode uncertainty in the quantiles elicited from experts, we p

Functional and molecular profiling of hematopoietic stem cells during regeneration

Hematopoietic stem cells (HSCs) enable hematopoietic stem cell transplantation (HCT) through their ability to replenish the entire blood system. Proliferation of HSCs is linked to decreased reconstitution potential, and a precise regulation of actively dividing HSCs is thus essential to ensure long-term functionality. This regulation becomes important in the transplantation setting where HSCs unde

Estimation of Spherical Wave Coefficients from 3D Positioner Channel Measurements

Electromagnetic vector spherical waves have been used recently to model antenna-channel interaction and the available degrees of freedom in multiple-input-multiple-output (MIMO) systems. However, there are no previous accounts of a method to estimate spherical wave coefficients from channel measurements. One approach for this, using a 3-D positioner, is presented and analyzed in this letter. Measu

Information Design in Bayesian Routing Games

We study optimal information provision in transportation networks when users are strategic and the network state is uncertain. An omniscient planner observes the network state and discloses information to the users with the goal of minimizing the expected travel time at the user equilibrium. Public signal policies, including full-information disclosure, are known to be inefficient in achieving opt