**Abstract:** This paper proposes a novel method for characterizing battery electrode-electrolyte interfaces under…
**Abstract:** This paper proposes a novel method for characterizing battery electrode-electrolyte interfaces under…
**Abstract:** Traditional time series anomaly detection methods struggle with dynamic normal patterns, often requiring frequent retraining and parameter tuning. This paper presents a novel…
**Abstract:** Traditional time series anomaly detection methods struggle with dynamic normal patterns, often requiring frequent retraining and parameter tuning. This paper presents a novel…
**Abstract:** The successful commercialization of lithium-metal batteries (LMBs) hinges on overcoming the challenges of dendrite formation…
**Abstract:** The successful commercialization of lithium-metal batteries (LMBs) hinges on overcoming the challenges of dendrite formation…
**Abstract:** Predicting the transient lifetimes of surface intermediates is paramount for rational catalyst design in ethylene epoxidation, yet…
**Abstract:** Predicting the transient lifetimes of surface intermediates is paramount for rational catalyst design in ethylene epoxidation, yet…
**Abstract:** The increasing prevalence of autonomous vehicles (AVs) introduces novel challenges in accident reconstruction and liability attribution. Traditional approaches struggle to…
**Abstract:** The increasing prevalence of autonomous vehicles (AVs) introduces novel challenges in accident reconstruction and liability attribution. Traditional approaches struggle to…
**Abstract:** This paper introduces a novel methodology for automated fault diagnosis and predictive maintenance in cryogenic vacuum pumps used in semiconductor…
**Abstract:** This paper introduces a novel methodology for automated fault diagnosis and predictive maintenance in cryogenic vacuum pumps used in semiconductor…
**Abstract:** This paper proposes a novel framework, Adaptive Sparse Temporal Sampling and Latent Space Refinement (ASTSLSR), for dynamic volumetric reconstruction…
**Abstract:** This paper proposes a novel framework, Adaptive Sparse Temporal Sampling and Latent Space Refinement (ASTSLSR), for dynamic volumetric reconstruction…
**Abstract:** This research proposes a novel Federated Gaussian Mechanism (FGM) with Adaptive Clipping (AC) tailored for enhanced differential privacy (DP) in Internet of Things (IoT)…
**Abstract:** This research proposes a novel Federated Gaussian Mechanism (FGM) with Adaptive Clipping (AC) tailored for enhanced differential privacy (DP) in Internet of Things (IoT)…
**Abstract:** This paper introduces a novel approach to simulating quantum dynamics, leveraging Adaptive Ensemble Variational Autoencoders (AQD-EVA) to drastically improve computational efficiency and…
**Abstract:** This paper introduces a novel approach to simulating quantum dynamics, leveraging Adaptive Ensemble Variational Autoencoders (AQD-EVA) to drastically improve computational efficiency and…
**Abstract:** This paper introduces a novel Adaptive Meta-Reinforcement Learning (AMRL) framework addressing the challenge of hierarchical tool manipulation in robotic systems operating…
**Abstract:** This paper introduces a novel Adaptive Meta-Reinforcement Learning (AMRL) framework addressing the challenge of hierarchical tool manipulation in robotic systems operating…
**Abstract:** The correlation between protein structural stability and solubility remains a crucial challenge in biotechnology and drug discovery. Current predictive models often rely on single data…
**Abstract:** The correlation between protein structural stability and solubility remains a crucial challenge in biotechnology and drug discovery. Current predictive models often rely on single data…
**Abstract:** This paper introduces a novel approach for characterizing and predicting quantum channel decoherence in single-molecule magnets (SMMs). Leveraging hyperdimensional…
**Abstract:** This paper introduces a novel approach for characterizing and predicting quantum channel decoherence in single-molecule magnets (SMMs). Leveraging hyperdimensional…
**Abstract:** Single-cell RNA sequencing (scRNA-seq) data offers unprecedented insights into cellular heterogeneity. However, analysis of rare…
**Abstract:** Single-cell RNA sequencing (scRNA-seq) data offers unprecedented insights into cellular heterogeneity. However, analysis of rare…
**Abstract:** This research proposes a novel methodology for dynamically modulating the magnetic anisotropy of spin-crossover (SCO) molecules by employing an autonomous, machine-learning…
**Abstract:** This research proposes a novel methodology for dynamically modulating the magnetic anisotropy of spin-crossover (SCO) molecules by employing an autonomous, machine-learning…
**Abstract:** This paper details a novel system, Automated Optimization of AuNP Core Size and Shape via Peptide-Directed Templating and Real-Time Spectroscopic…
**Abstract:** This paper details a novel system, Automated Optimization of AuNP Core Size and Shape via Peptide-Directed Templating and Real-Time Spectroscopic…
**Abstract:** This paper introduces a novel platform for dynamically optimizing nano-adjuvant formulations for enhanced CD8+ T cell responses in viral…
**Abstract:** This paper introduces a novel platform for dynamically optimizing nano-adjuvant formulations for enhanced CD8+ T cell responses in viral…
**Originality:** This research proposes a novel federated learning framework integrating genomic, proteomic, and imaging data (MRI, CT) from diverse institutions to identify…
**Originality:** This research proposes a novel federated learning framework integrating genomic, proteomic, and imaging data (MRI, CT) from diverse institutions to identify…
**Abstract:** This research introduces a novel, highly accurate method for measuring diffusion coefficient anisotropy within electrochemical double layers (EDLs) by…
**Abstract:** This research introduces a novel, highly accurate method for measuring diffusion coefficient anisotropy within electrochemical double layers (EDLs) by…
**Abstract:** This paper introduces a novel framework, Dynamic Hyper-Dimensional Embedding for Landscape Optimization (DHE-LO), for efficiently exploring and optimizing fitness landscapes across…
**Abstract:** This paper introduces a novel framework, Dynamic Hyper-Dimensional Embedding for Landscape Optimization (DHE-LO), for efficiently exploring and optimizing fitness landscapes across…
**Abstract:** This paper introduces a novel approach to entanglement swapping in quantum communication networks, addressing the challenges posed by dynamic network topologies and fluctuating channel conditions. Our…
**Abstract:** This paper introduces a novel approach to entanglement swapping in quantum communication networks, addressing the challenges posed by dynamic network topologies and fluctuating channel conditions. Our…
**Abstract:** This paper proposes a novel federated learning framework, Federated Knowledge Graph Enhancement for Personalized Healthcare (FKG-PH), to…
**Abstract:** This paper proposes a novel federated learning framework, Federated Knowledge Graph Enhancement for Personalized Healthcare (FKG-PH), to…
**Abstract:** This research presents an adaptive Kalman filtering (AKF) framework for enhancing the precision and robustness of dynamic robotic manipulation tasks. The system…
**Abstract:** This research presents an adaptive Kalman filtering (AKF) framework for enhancing the precision and robustness of dynamic robotic manipulation tasks. The system…
**Abstract:** Accurate and timely prediction of Mesoscale Convective System (MCS) initiation remains a significant challenge in operational weather…
**Abstract:** Accurate and timely prediction of Mesoscale Convective System (MCS) initiation remains a significant challenge in operational weather…
**Abstract:** Traditional characterization of electrochemical interfaces relies on indirect methods, limiting the detailed understanding of surface phonon…
**Abstract:** Traditional characterization of electrochemical interfaces relies on indirect methods, limiting the detailed understanding of surface phonon…
**Abstract:** This research proposes a novel framework for optimizing polymer blends of polyethylene (PE) and polypropylene (PP) via reactive extrusion, employing a Multi-Modal Evaluation…
**Abstract:** This research proposes a novel framework for optimizing polymer blends of polyethylene (PE) and polypropylene (PP) via reactive extrusion, employing a Multi-Modal Evaluation…