04b Atto di convegno in volume

Consistent Query Answering over Existential Rules with Open and Closed Predicates

We study Consistent Query Answering (CQA) over knowledge bases with existential rules. Specifically, we propose a novel framework for CQA that combines previous approaches, allowing for the simultaneous presence of both open and closed predicates, i.e. predicates interpreted under open- and closed-...
Trust Nobody: Privacy-Preserving Proofs for Edited Photos with Your Laptop

The Internet has plenty of images that are transformations (e.g., resize, blur) of confidential original images. Several scenarios (e.g., selling images over the Internet, fighting disinformation, detecting deep fakes) would highly benefit from systems allowing to verify that an image is the result...
Regular Clocks for Temporal Task Specifications in Reinforcement Learning

Several recent approaches in reinforcement learning are studying a conceptual architecture where the environment is simultaneously represented at two (or more) levels of abstraction, with the environment providing two traces of data/events/features/fluents, one at a lower-level/finer grain and one...
A deep learning approach to EEG subcortical source localization

Electroencephalography (EEG) offers high temporal resolution but struggles to accurately localize subcortical activity, partly due to the ill-posed nature of the inverse problem and the weak signals from deep structures. Traditional regularized inverse methods are computationally efficient yet...
Towards brain state classification with functional ultrasound imaging

This study investigates the potential of functional ultrasound imaging (fUSI) as a promising, non-invasive, and cost-effective tool for identifying brain states and detecting pathological changes. We simulated brain activity using a Wilson-Cowan mass model, converting electrophysiological signals...
Functional ultrasound imaging in simulated brain state analysis

Functional ultrasound imaging (fUSI) has emerged as a promising non-invasive neuroimaging modality that leverages neurovascular coupling to capture hemodynamic changes associated with neuronal activity. This study investigates the feasibility of fUSI for brain state classification in both healthy...
A Deep Learning Framework for Multi-Source EEG Localization

Electroencephalography (EEG) provides millisecond-scale resolution of neural activity but struggles to accurately localize multiple concurrent sources, especially in spatially close regions. Classical linear inverse methods, such as MNE, sLORETA, and dSPM, address the ill-posed inverse problem...
Decomposition Frequency Optimization in wavelet-Based Template Matching Algorithms to Manage P300 Latency Jitter

Event Related Potentials (ERPs) are modifications of the brain activity in response to external sensory stimulation. P300 is a positive ERP component occurring 300 ms after the presentation of a rare stimulus and indicating the conscious perception of an unexpected change in sensory stimulation....
QMSan: Efficiently Detecting Uninitialized Memory Errors During Fuzzing

Fuzzing evolved into the most popular technique to detect bugs in software. Its combination with sanitizers has shown tremendous efficacy in uncovering memory safety errors, such as buffer overflows, that haunt C and C++ programmers. However, an important class of such issues, the so-called use-of-...
On the Lack of Robustness of Binary Function Similarity Systems

Binary function similarity, which often relies on learning-based algorithms to identify what functions in a pool are most similar to a given query function, is a soughtafter topic in different communities, including machine learning, software engineering, and security. Its importance stems from the...