Trending
Supernova remnants (SNRs) are key tracers of stellar feedback and the chemical and dynamical evolution of the interstellar medium. However, identifying SNRs in complex regions remains challenging, particularly when only archival…
While automated content-moderation systems have become essential for screening harmful content at scale, conventional task-specific classifiers often provide limited policy cov- erage and contextual understanding. Recently, commercial…
Existing farmland remote sensing image (FRSI) segmentation follows a "Think with Intra-Image" paradigm, assuming that the current image contains sufficient visual evidence for reliable segmentation. Yet farmland appearance varies with…
Oversmoothing is a fundamental limitation of deep graph neural networks (GNNs), where repeated message passing causes node representations to become increasingly similar, eventually collapsing toward a low-dimensional subspace. This…
Promising implementations of first generation quantum repeaters are predicted to require atomic-based quantum memory systems interfaced with photonic sources. Integrated photonics provides a promising solution for fibre-based,…
This thesis studies $4d$ massless higher-spin interactions in the Light-Front approach by analysing the closure of the Poincar\'e algebra at quartic order. We first solve the light-cone quartic holomorphic constraint in flat space and show…
E-commerce platforms must allocate fixed marketing budgets across multiple channels to maximize business utility. However, standard predict-then-optimize (PTO) paradigms fail in this compositional space due to observational confounding and…
Operators invariant under a symmetry group are also invariant under any finite-index subgroup. The equivariant indices of such operators must be consistent under symmetry breaking. We use this principle to establish a canonical weak/strong…
Although Low Surface Brightness (LSB) galaxies are increasingly well studied, considerable uncertainty still exists as to both their range in properties and their evolutionary history. LSB galaxies provide a fascinating extreme in galaxy…
This innovative practice full paper examines the integration of technology-enhanced tabletop exercises (TTXs) into computing education, focusing on cybersecurity curricula. The motivation is to better prepare students for complex,…
Probabilistic forecast evaluation is inherently multi-objective, yet existing proper scoring rules reduce predictive performance to a single scalar value, potentially obscuring the trade-off between forecast concentration and predictive…
We investigate a bias correction procedure based on sieve bootstrapping to estimate the long-memory parameter d in stationary or nonstationary fractionally integrated processes. The resampling method implements a sieve bootstrap method on…
The rapid adoption of generative Artificial Intelligence (AI) in software engineering (SE) practice creates a need for pedagogically grounded approaches to AI integration in SE education, especially in conceptually intensive subjects such…
Automatic speech recognition (ASR) has achieved substantial gains in transcription accuracy, yet verbatim transcription does not necessarily produce readily usable text. It retains fillers, repetitions, false starts, and self-corrections…
We use numerical experiments to explore two possibilities: (i) that Bipolar H II Regions are the result of Cloud-Cloud Collisions (CCCs), and (ii) that -- when allowance is made for the chaotic nature of such collisions, the short duration…
In the daily practice of Machine Learning, fully labeled datasets are a luxury: labels demand expensive and time-consuming human annotation, whereas raw, unlabeled data can be harvested automatically and in bulk. Semi-supervised learning,…
The paper examines the features of critical evolution in an active medium modeled by a cellular automaton. The system evolves according to stochastic rules, exhibiting two qualitatively distinct dynamical regimes: one of fading activity and…
We study a finite-horizon workforce planning problem in which staff turnover in each period follows a binomial distribution whose parameters depend on the post-hiring workforce level. The model incorporates a fixed hiring cost that is…
Optimal decision trees (ODTs) are compact, interpretable machine learning models that globally optimize a given objective, but their scalability remains challenging. While recent work has proposed a variety of search strategies to improve…
In this work, we theoretically investigate the decay mechanism of $D_s^+ \to \pi^+ \pi^0 \pi^0 \eta$ based on BESIII data, considering two mechanisms: the production of two dynamically generated resonances, $D_s^+ \to a_0(980)^+…