Tootfinder

A tunnelled road underneath Ontario's Highway 401 would be an expensive and very short term solution to congestion. A high speed train subway would be cheaper, move many more people and cost less.
A better Toronto, for all.
A Real Solution to Highway 401 Congestion — the Express Subway.
A subway to Pickering makes much more sense than a 401 Tunnel.

A Real Solution to Highway 401 Congestion — the Express Subway.
A subway to Pickering makes much more sense than a 401 Tunnel.

Evaluating the Impact of Privacy-Preserving Federated Learning on CAN Intrusion Detection
Gabriele Digregorio, Elisabetta Cainazzo, Stefano Longari, Michele Carminati, Stefano Zanero
https://arxiv.org/abs/2506.04978

Evaluating the Impact of Privacy-Preserving Federated Learning on CAN Intrusion Detection
The challenges derived from the data-intensive nature of machine learning in conjunction with technologies that enable novel paradigms such as V2X and the potential offered by 5G communication, allow and justify the deployment of Federated Learning (FL) solutions in the vehicular intrusion detection domain. In this paper, we investigate the effects of integrating FL strategies into the machine learning-based intrusion detection process for on-board vehicular networks. Accordingly, we propose a …

Effects of lower floating-point precision on scale-resolving numerical simulations of turbulence
Martin Karp, Ronith Stanly, Timofey Mukha, Luca Galimberti, Siavash Toosi, Hang Song, Lissandro Dalcin, Saleh Rezaeiravesh, Niclas Jansson, Stefano Markidis, Matteo Parsani, Sanjeeb Bose, Sanjiva Lele, Philipp Schlatter
https://arxiv…

Effects of lower floating-point precision on scale-resolving numerical simulations of turbulence
Modern computing clusters offer specialized hardware for reduced-precision arithmetic that can speed up the time to solution significantly. This is possible due to a decrease in data movement, as well as the ability to perform arithmetic operations at a faster rate. However, for high-fidelity simulations of turbulence, such as direct and large-eddy simulation, the impact of reduced precision on the computed solution and the resulting uncertainty across flow solvers and different flow cases have…

Traveling waves for a two-phase Stefan problem with radiation
Elena Dematt\`e, Juan J. L. Vel\'azquez
https://arxiv.org/abs/2506.01821 https://

Traveling waves for a two-phase Stefan problem with radiation
In this paper we study the existence of traveling wave solutions for a free-boundary problem modeling the phase transition of a material where the heat is transported by both conduction and radiation. Specifically, we consider a one-dimensional two-phase Stefan problem with an additional non-local non-linear integral term describing the situation in which the heat is transferred in the solid phase also by radiation, while the liquid phase is completely transparent, not interacting with radiatio…

Parametric formal Gevrey asymptotic expansions in two complex time variable problems
Guoting Chen, Alberto Lastra, Stephane Malek
https://arxiv.org/abs/2506.00916

Parametric formal Gevrey asymptotic expansions in two complex time variable problems
The analytic and formal solutions to a family of singularly perturbed partial differential equations in the complex domain involving two complex time variables are considered. The analytic continuation properties of the solution of an auxiliary problem in the Borel plane overcomes the absence of adequate domains which would guarantee summability of the formal solution. Moreover, several exponential decay rates of the difference of analytic solutions with respect to the perturbation parameter …

A variable dimension sketching strategy for nonlinear least-squares
Stefania Bellavia, Greta Malaspina, Benedetta Morini
https://arxiv.org/abs/2506.03965 h…

A variable dimension sketching strategy for nonlinear least-squares
We present a stochastic inexact Gauss-Newton method for the solution of nonlinear least-squares. To reduce the computational cost with respect to the classical method, at each iteration the proposed algorithm approximately minimizes the local model on a random subspace. The dimension of the subspace varies along the iterations, and two strategies are considered for its update: the first is based solely on the Armijo condition, the latter is based on information from the true Gauss-Newton model.…

On Loss-Minimal Radial Topologies in MV Systems
Anton Hinneck, Mathias Duckheim, Michael Metzger, Stefan Niessen
https://arxiv.org/abs/2506.03422 https://

On Loss-Minimal Radial Topologies in MV Systems
Distribution system reconfiguration (DSR) means optimizing the topology of a distribution grid using switching actions. Switching actions are a degrees of freedom available to distribution system operators, e.g. to manage planned and unplanned outages. DSR is a NP-hard combinatorial problem. Finding good or even optimal solutions is computationally expensive. While transmission and high-voltage grids are generally operated in a meshed state, MV distribution systems are commonly operated as radi…

Analytical solution for dynamic evaporation of liquid in isothermal condition
Luiz Eduardo Czelusniak, Tim Niklas Bingert, Stephan Simonis, Alexander J. Wagner, Mathias J. Krause
https://arxiv.org/abs/2506.02270

Analytical solution for dynamic evaporation of liquid in isothermal condition
An analytical solution based on a diffuse interface model is presented for an isothermal evaporation problem under sub-saturation pressure. The macroscopic equations are derived from the free-energy method, widely recognized in the lattice Boltzmann literature, distinguishing our approach from conventional evaporation models that rely on jump conditions or pure kinetic theory. The interface behavior is fully described by differential equations, eliminating the need for assumptions such as local…

Tarallo: Evading Behavioral Malware Detectors in the Problem Space
Gabriele Digregorio, Salvatore Maccarrone, Mario D'Onghia, Luigi Gallo, Michele Carminati, Mario Polino, Stefano Zanero
https://arxiv.org/abs/2506.02660

Tarallo: Evading Behavioral Malware Detectors in the Problem Space
Machine learning algorithms can effectively classify malware through dynamic behavior but are susceptible to adversarial attacks. Existing attacks, however, often fail to find an effective solution in both the feature and problem spaces. This issue arises from not addressing the intrinsic nondeterministic nature of malware, namely executing the same sample multiple times may yield significantly different behaviors. Hence, the perturbations computed for a specific behavior may be ineffective for…

Gravity driven traveling bore wave solutions to the free boundary incompressible Navier-Stokes equations
Noah Stevenson, Ian Tice
https://arxiv.org/abs/2505.24562

Gravity driven traveling bore wave solutions to the free boundary incompressible Navier-Stokes equations
We give the first mathematical construction of two-dimensional traveling bore wave solutions to the free boundary incompressible Navier-Stokes equations for a single finite depth layer of constant density fluid. Our construction is based on a rigorous justification of the formal shallow water limit, which postulates that in a certain scaling regime the full free boundary traveling Navier-Stokes system of PDEs reduces to a governing system of ODEs. We find heteroclinic orbits solving these ODEs …