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This thesis investigates scalable control design for networked dynamical systems, which are of great importance due to their wide range of practical applications, including large-scale formation control. A central challenge in such systems is enabling agents to coordinate effectively based only on local and relative information, particularly as the system size increases. To address this, the thesi
The Restricted Syndrome Decoding Problem (RSDP) is a variant of the well-known syndrome decoding problem. It has been recently turned into a post-quantum signature scheme named CROSS by Baldi et al.. It is a scheme highlighted for being computationally friendly and providing a compact signature and public key size. This paper investigates an Oracle-based definition of the RSDP that has already pro
We study the problem of obtaining lower bounds for polynomial calculus (PC) and polynomial calculus resolution (PCR) on proof degree, and hence by [Impagliazzo et al.'99] also on proof size. [Alekhnovich and Razborov'03] established that if the clause-variable incidence graph of a conjunctive normal form (CNF) formula F is a good enough expander, then proving that F is unsatisfiable requires high
We study the notion of (additive) separability of a function of several variables with respect to a hypergraph (H-graph). We prove the existence of a unique minimal H-graph with respect to which a function is separable and show that the corresponding minimal decomposition of the function can be obtained through a recursive algorithm. We then focus on (strategic form) games and propose a concept of
Significant behavioral changes will need to be implemented to prevent the energy supply sector from tripling CO2 emissions by the midcentury. However, within the academic research, behavior changes remain primarily focused on the individual level, while the behavior of companies that are responsible for elevated greenhouse gas emissions falls behind. This master’s thesis analyses the core values
This paper serves as a first identification step in a two-step model-based control synthesis problem of switched linear systems (SLSs). More precisely, we present an algorithm that addresses the realization of the multi-input/multi-output MIMO-SLSs from Markov parameters under mild assumptions on the dwell-times and the submodels. A key point of the proposed approach is the introduction of the for
In this paper, we propose a framework to iden-tify discrete-time, multi-input/multi-output (MIMO), switched-linear systems (SLSs) from input-output data. The key step is an observer-based transformation to a switched auto-regressive with exogenous input (SARX) model. This transformation has a nontrivial kernel complicating identification, but converts the state-space identification problem to SARX
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,
As the Hamming Quasi-Cyclic (HQC) cryptosystem was recently selected by NIST for standardization, a thorough evaluation of its implementation security is critical before its widespread deployment. This paper presents single-trace side-channel attacks that recover the full long-term secret key of HQC, experimentally evaluated on a protected Cortex-M4 implementation. We introduce two distinct attack
It is a common practice for symmetric-key ciphers is to encode a cryptanalysis problem as an instance of the Mixed Integer Linear Programming (MILP) and then run the instance with an efficient solver. For this purpose, it is essential to model the components in a way that is compatible with the MILP formulation while preserving the characteristics of the cipher. In this work, we look at the proble
Quantum computing has attracted substantial attention from researchers across various fields. In case of the symmetric key cryptography, the main problem is posed by the application of Grover’s search. In this work, we focus on quantum analysis of the lightweight block cipher LED. This paper proposes an optimized quantum circuit for LED, minimizing the required number of qubits, quantum gates, and
In this paper, we investigate a Multi-layer Aerial system for GenAI inference at the Edge (MAGE). Therein, ground user equipments (UEs) request image synthesis services from a remote base station (BS) that leverages the Latent Diffusion Model (LDM) for image generation. Multiple Unmanned Aerial Vehicles (UAVs) are deployed to serve the UEs for relaying their images and prompts to the BS. To reduce
We explore mission assignment and task offloading in Open Radio Access Network (Open RAN)-enabled intelligent transportation systems (ITS), where autonomous vehicles utilize mobile edge computing for efficient processing. Existing studies often overlook mission dependencies and offloading costs, leading to suboptimal decisions. To address this, we formulate a novel optimization problem that integr
In computer graphics, there are numerous aspects that must be considered when rendering images of virtual scenes:What physical light-generating phenomena do we care about? How should object and material surfaces be described? And how should these be stored to ensure as fast and efficient image rendering as possible?As a part of this thesis, a method for rendering images of scenes lit by virtual at
Line segments are powerful features complementary to points. They offer structural cues, robust to drastic viewpoint and illumination changes, and can be present even in texture-less areas. However, describing and matching them is more challenging compared to points due to partial occlusions, lack of texture, or repetitiveness. This paper introduces a new matching paradigm, where points, lines, an
In this paper we introduce the Tangent Sampson error, which is a generalization of the classical Sampson error in two-view geometry that allows for arbitrary central camera models. It only requires local gradients of the distortion map at the original correspondences (allowing for pre-computation) resulting in a negligible increase in computational cost when used in RANSAC or local refinement. The
In contrast to sparse keypoints, a handful of line segments can concisely encode the high-level scene layout, as they often delineate the main structural elements. In addition to offering strong geometric cues, they are also omnipresent in urban landscapes and indoor scenes. Despite their apparent advantages, current line-based reconstruction methods are far behind their point-based counterparts.
Finding the optimal subset of individuals to observe in order to obtain the best estimate of the average opinion of a society is a crucial problem in a wide range of applications, including policy-making, strategic business decisions, and the analysis of sociological trends. We consider the opinion vector X to be updated according to a DeGroot opinion dynamical model with stubborn agents, subject
Software applications can be described using a computational model. These Models of Computation (MoCs) define rules governing application behaviour and properties that are enforced during execution. This thesis focuses on an actor-based MoC, known as dataflow-with-firing, where applications are modelled as actors connected by buffered channels. This model yields a concurrent application descriptio
