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Behavioral ransomware detection often achieves high accuracy in standard evaluations; however, these results frequently fail to generalize under distribution shifts or when encountering previously unseen families. This study evaluates detection performance on the MLRan dataset (4,880 samples across 64 families) using four rigorous evaluation protocols: stratified, temporal, family-disjoint, and open-set. To ensure a strict separation of learned features, the family-disjoint and open-set splits were executed at the family level. We propose the Hierarchical Sparse Neural Network (HSNN), a […]

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In this paper, the general moment form of Green’s Theorem curve integral, for the calculation of the area and moments values of the planar region enclosed by arbitrary curve, is derived from the numerical version of its belonging moment integrals that are obtained from discrete vector product and differential vector product properties. Then, all six area and moments integrals are derived in a new, uniform integral form, for calculation of: area itself, its static moments, area centroids and […]

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We study the degree-d Jensen polynomials Jd,n(X) built from the moment sequence Mn=∫0∞Φ1(u)u2ndu of the Riemann Ξ-function, which coincides with the classical Pólya–Jensen family. Using bridge coordinates, the staircase law, and Plancherel–Rotach asymptotics, we prove that Jd,nγ is hyperbolic for all n≥C0∞d4 (C0∞≈0.020, proved); combined with the GORZ theorem for d≤8, this covers the entire asymptotic regime. We identify a phase-transition law n*(d)=C0∞d4+αd3+β(−1)dd2+O(d) (Conjecture 3.5): the leading constant C0∞≈0.0195 is proved analytically; the formula for α is derived; […]

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Learning with large-scale datasets and information-critical applications, such as in High Energy Physics (HEP), demands highly complex, large-scale models that are both robust and accurate. To tackle this issue and cater to the learning requirements, we envision using a federated learning framework with a quantum-enhanced model. Specifically, we design a hybrid quantum-classical long-shot-term-memory model (QLSTM) for local training at distributed nodes. It combines the representative power of quantum models in understanding complex relationships within the feature space, and […]

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Large-scale Unmanned Aerial Vehicle (UAV) failures can split an unmanned aerial vehicle swarm network into disconnected sub-networks, making decentralized recovery both urgent and difficult. Centralized recovery methods depend on global topology information and become communication-heavy after severe fragmentation. Decentralized heuristics and multi-agent reinforcement learning methods are easier to deploy, but their performance often degrades when the swarm scale and damage severity vary. We present Physics-informed Graph Adversarial Imitation Learning algorithm (PhyGAIL) that adopts centralized training with decentralized execution. […]

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This research note identifies a previously overlooked distinction between multi-objective reinforcement learning (MORL), and more conventional single-objective reinforcement learning (RL). It has previously been noted that the optimal policy for an MORL agent with a non-linear utility function is required to be conditioned on both the current environmental state and on some measure of the previously accrued reward. This is generally implemented by concatenating the observed state of the environment with the discounted sum of previous rewards to […]

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How are you, hacker? 🪐Want to know what’s trending right now?: The Techbeat by HackerNoon has got you covered with fresh content from our trending stories of the day! Set email preference here. ## 12 OpenCode Skills Every Dev Team Should Steal By @bezgin [ 4 Min read ] A practical guide to coding agent skills and commands from OpenCode and beyond, with reusable patterns for debugging, planning, review, and repo memory. Read More. Pretext Does What CSS […]

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5G‑connected mobile respiratory units introduce a paradigm shift in acute crisis management for lung cancer patients by merging portable ventilatory support with ultra‑low‑latency, high‑bandwidth connectivity. These units integrate on‑board ventilators, non‑invasive and invasive respiratory interfaces, vital‑sign monitors, and 5G modems to enable real‑time transmission of flows, pressures, oxygen saturation, and high‑definition video to remote critical‑care hubs. During transport or in‑field deployment, intensivists and respiratory specialists can guide airway management, titrate ventilator settings, and override parameters via cloud‑based control […]

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Visual speaker recognition based on lip motion offers a silent, hands-free, and behavior-driven biometric solution that remains effective even when acoustic cues are unavailable. Compared to traditional methods that rely heavily on appearance-dependent representations, lip motion encodes subject-specific behavioral dynamics driven by consistent articulation patterns and muscle coordination, offering inherent stability across environmental changes. However, capturing these robust, fine-grained dynamics is challenging for conventional frame-based cameras due to motion blur and low dynamic range. To exploit the intrinsic […]

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