**Abstract:** This paper introduces a novel approach to few-shot anomaly detection within industrial sensor networks, leveraging hyperdimensional computing (HDC) and kernel alignment techniques. The…
**Abstract:** This paper introduces a novel approach to few-shot anomaly detection within industrial sensor networks, leveraging hyperdimensional computing (HDC) and kernel alignment techniques. The…
**Abstract:** Early and accurate melanoma detection from scalp biopsies remains challenging due to inter-observer variability and the subtle visual cues indicative…
**Abstract:** Early and accurate melanoma detection from scalp biopsies remains challenging due to inter-observer variability and the subtle visual cues indicative…
**Abstract:** This research proposes a novel framework for accurate prediction of drug candidate tissue penetration and metabolic behavior within the body using a hybrid approach…
**Abstract:** This research proposes a novel framework for accurate prediction of drug candidate tissue penetration and metabolic behavior within the body using a hybrid approach…
**Abstract:** This paper proposes a novel framework for characterizing structural relaxation dynamics in amorphous semiconductors (a-Si, a-Ge, a-Te) employing a…
**Abstract:** This paper proposes a novel framework for characterizing structural relaxation dynamics in amorphous semiconductors (a-Si, a-Ge, a-Te) employing a…
**Abstract:** This paper introduces a novel approach to generating causal reasoning graphs (CRGs) from sequential data streams, specifically tailored for…
**Abstract:** This paper introduces a novel approach to generating causal reasoning graphs (CRGs) from sequential data streams, specifically tailored for…
**Abstract:** This paper presents a novel approach to autonomously optimizing de-orbit trajectories for defunct satellites, addressing a critical challenge in…
**Abstract:** This paper presents a novel approach to autonomously optimizing de-orbit trajectories for defunct satellites, addressing a critical challenge in…
**Abstract:** This paper introduces a novel framework for validating and inferring causal relationships within single-cell RNA-sequencing (scRNA-seq) data, addressing a critical…
**Abstract:** This paper introduces a novel framework for validating and inferring causal relationships within single-cell RNA-sequencing (scRNA-seq) data, addressing a critical…
**Abstract:** This paper proposes a novel framework, HyperScore-DP (Differential Privacy Enhanced HyperScore), for embedding differential privacy guarantees within genetic…
**Abstract:** This paper proposes a novel framework, HyperScore-DP (Differential Privacy Enhanced HyperScore), for embedding differential privacy guarantees within genetic…
**Abstract:** This research introduces a novel approach to optimizing photoelectron emission (PEE) characteristics from metal surfaces by dynamically tailoring surface…
**Abstract:** This research introduces a novel approach to optimizing photoelectron emission (PEE) characteristics from metal surfaces by dynamically tailoring surface…
**Abstract:** This paper proposes a novel approach to automated kinetic resolution (AKR) of chiral phosphine ligands – critical precursors in…
**Abstract:** This paper proposes a novel approach to automated kinetic resolution (AKR) of chiral phosphine ligands – critical precursors in…
**Abstract:** Current epigenetic clocks, while demonstrating remarkable accuracy in age estimation, exhibit variability influenced by environmental factors. This paper proposes a novel…
**Abstract:** Current epigenetic clocks, while demonstrating remarkable accuracy in age estimation, exhibit variability influenced by environmental factors. This paper proposes a novel…
**Abstract:** The mechanism of inhibitor-induced step-growth retardation in thin-film deposition remains a critical challenge for achieving precise control over film morphology and…
**Abstract:** The mechanism of inhibitor-induced step-growth retardation in thin-film deposition remains a critical challenge for achieving precise control over film morphology and…
**1. Introduction** The persistent current carried by Majorana zero modes (MZMs) in topological superconductors (TSC) promises fault-tolerant quantum computation.…
**1. Introduction** The persistent current carried by Majorana zero modes (MZMs) in topological superconductors (TSC) promises fault-tolerant quantum computation.…
**Abstract:** Accurate prediction of solar flares is crucial for protecting space-based assets and mitigating terrestrial disruptions. This paper proposes a novel…
**Abstract:** Accurate prediction of solar flares is crucial for protecting space-based assets and mitigating terrestrial disruptions. This paper proposes a novel…
**Abstract:** This paper introduces a novel framework for automating the parameter calibration and device optimization process within Gallium Nitride High…
**Abstract:** This paper introduces a novel framework for automating the parameter calibration and device optimization process within Gallium Nitride High…
**Abstract:** This research introduces a novel framework for reconstructing and analyzing chaotic attractors within quantum systems, termed the Quantum-Enhanced Markovian Cascade Model (QEMCM). Leveraging controlled…
**Abstract:** This research introduces a novel framework for reconstructing and analyzing chaotic attractors within quantum systems, termed the Quantum-Enhanced Markovian Cascade Model (QEMCM). Leveraging controlled…
**Abstract:** This paper introduces a novel method for dynamically calibrating quantum processors to achieve significantly improved coherence times and gate fidelities. Existing calibration…
**Abstract:** This paper introduces a novel method for dynamically calibrating quantum processors to achieve significantly improved coherence times and gate fidelities. Existing calibration…
**Abstract:** This paper proposes a novel framework, Dynamic Cognitive Graph Calibration (DCGC), for enhanced diagnostic accuracy and personalized remediation in mathematics learning…
**Abstract:** This paper proposes a novel framework, Dynamic Cognitive Graph Calibration (DCGC), for enhanced diagnostic accuracy and personalized remediation in mathematics learning…
**Abstract:** This research introduces a novel approach to optimizing material synthesis processes through hyperdimensional cognitive mapping (HDCM). By transforming process parameters and material properties into…
**Abstract:** This research introduces a novel approach to optimizing material synthesis processes through hyperdimensional cognitive mapping (HDCM). By transforming process parameters and material properties into…
**Abstract:** Catalyst discovery is a computationally expensive and experimentally iterative process. This paper introduces a novel framework for accelerating…
**Abstract:** Catalyst discovery is a computationally expensive and experimentally iterative process. This paper introduces a novel framework for accelerating…
**Abstract:** Predicting peptide folding remains a grand challenge in computational biology. Current methods often struggle to account for the intricate…
**Abstract:** Predicting peptide folding remains a grand challenge in computational biology. Current methods often struggle to account for the intricate…
**Abstract:** This paper introduces a novel framework for automated synthesis of meta-analyses, termed Automated Meta-Analysis Synthesis Engine (AMESE). AMESE leverages a multi-modal…
**Abstract:** This paper introduces a novel framework for automated synthesis of meta-analyses, termed Automated Meta-Analysis Synthesis Engine (AMESE). AMESE leverages a multi-modal…
**Abstract:** This research proposes a novel signal processing technique, Sparse Temporal Filtering (STF), for mitigating the pervasive issue of noise interference within electrocardiographic (ECG)…
**Abstract:** This research proposes a novel signal processing technique, Sparse Temporal Filtering (STF), for mitigating the pervasive issue of noise interference within electrocardiographic (ECG)…
Following random selection, we've narrowed the research domain to **Bayesian Optimization of Question-Driven Knowledge Graph Traversal for Strategic Foresight.** This…
Following random selection, we've narrowed the research domain to **Bayesian Optimization of Question-Driven Knowledge Graph Traversal for Strategic Foresight.** This…
**Abstract:** This paper proposes a novel framework for real-time predictive maintenance of conveyor belt systems within industrial facilities. Leveraging…
**Abstract:** This paper proposes a novel framework for real-time predictive maintenance of conveyor belt systems within industrial facilities. Leveraging…