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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
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
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
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
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
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
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
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
We prove that polynomial calculus (and hence also Nullstellensatz) over any field requires linear degree to refute that sparse random regular graphs, as well as sparse Erdős-Rényi random graphs, are 3-colourable.
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
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
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
Software development is a complex activity that needs a lot of tool assistance. Over the years there has been a lot of effort put into development of automated assistance to help with activities such as detection of issues via program analysis, or refactoring of code. Recently, the landscape of developer tool assistance is being disrupted with the entry of AI tools, such as Copilot and ChatGPT, po
The widespread availability of large language models (LLMs) has presented the opportunity for novice programmers to make use of them for the purpose of understanding and synthesising code. In this paper, we discuss a small pilot study intended to explore the user experience of doing so in a limited way, and the attitudes of a group of novice programmers towards this style of programming. We also d
This contribution presents a novel offline dynamic multi-objective optimization framework for high-pressure liquid chromatographic (HPLC) processes in batch elution mode. The framework allows for optimization of general elution trajectories parametrized with piecewise constant control signals. It is based on a simultaneous method where both the control and state variables are fully discretized in
Abstract in UndeterminedDataflow descriptions have been used ina wide range of Digital Signal Processing (DSP)applications, such as multi-media processing, andwireless communications. Among various forms ofdataflow modeling, Synchronous Dataflow (SDF) isgeared towards static scheduling of computationalmodules, which improves system performance andpredictability. However, many DSP applicationsdo no
Homogeneous charge compression ignition (HCCI) holds promise for reduced emissions and increased efficiency compared to conventional internal combustion engines. As HCCI lacks direct actuation over the combustion phasing, much work has been devoted to designing controllers capable of set-point tracking and disturbance rejection. This paper presents results on model predictive control (MPC) of the
The oxidation of biogenic volatile organic compounds (BVOCs) gives a range of products, from semi-volatile to extremely low-volatility compounds. To treat the interaction of these secondary organic vapours with the particle phase, global aerosol microphysics models generally use either a thermodynamic partitioning approach (assuming instant equilibrium between semi-volatile oxidation products and
