Results 71 to 80 of about 30,621 (198)
In this study we employed support vector regressor and quantum support vector regressor to predict the hydrogen storage capacity of metal–organic frameworks using structural and physicochemical descriptors. This study presents a comparative analysis of classical support vector regression (SVR) and quantum support vector regression (QSVR) in predicting ...
Chandra Chowdhury
wiley +1 more source
Several simulation techniques are used to explore static and dynamic behavior in polyanion sodium cathode materials. The study reveals that universal machine learning interatomic potentials (MLIPs) struggle with system‐specific chemistry, emphasizing the need for tailored datasets.
Martin Hoffmann Petersen +5 more
wiley +1 more source
Capacitive, charge‐domain compute‐in‐memory (CIM) stores weights as capacitance,eliminating DC sneak paths and IR‐drop, yielding near‐zero standbypower. In this perspective, we present a device to systems level performance analysis of most promising architectures and predict apathway for upscaling capacitive CIM for sustainable edge computing ...
Kapil Bhardwaj +2 more
wiley +1 more source
Chat computational fluid dynamics (CFD) introduces an large language model (LLM)‐driven agent that automates OpenFOAM simulations end‐to‐end, attaining 82.1% execution success and 68.12% physical fidelity across 315 benchmarks—far surpassing prior systems.
E Fan +8 more
wiley +1 more source
The authors evaluated six machine‐learned interatomic potentials for simulating threshold displacement energies and tritium diffusion in LiAlO2 essential for tritium production. Trained on the same density functional theory data and benchmarked against traditional models for accuracy, stability, displacement energies, and cost, Moment Tensor Potential ...
Ankit Roy +8 more
wiley +1 more source
We propose a residual‐based adversarial‐gradient moving sample (RAMS) method for scientific machine learning that treats samples as trainable variables and updates them to maximize the physics residual, thereby effectively concentrating samples in inadequately learned regions.
Weihang Ouyang +4 more
wiley +1 more source
Feature Extraction Method Based on Social Network Analysis
Due to rapid development of Internet technology and electronic business, fraudulent activities have increased. One of the ways to cope with damages of them is fraud detection. In this field, there is a need for methods accurate and fast.
Zahra Karimi Zandian +1 more
doaj +1 more source
Crater Observing Bioinspired Rolling Articulator (COBRA)
Crater Observing Bio‐inspired Rolling Articulator (COBRA) is a modular, snake‐inspired robot that addresses the mobility challenges of extraterrestrial exploration sites such as Shackleton Crater. Incorporating snake‐like gaits and tumbling locomotion, COBRA navigates both uneven surfaces and steep crater walls.
Adarsh Salagame +4 more
wiley +1 more source
Memory‐Reduced Convolutional Neural Network for Fast Phase Hologram Generation
This article reports a lightweight convolutional neural network framework using INT8 quantization to efficiently generate 3D computer‐generated holograms from a single 2D image. The quantized model reduces memory usage and computational cost, accelerates inference speed, and maintains high output quality, enabling real‐time holographic display on low ...
Chenliang Chang +6 more
wiley +1 more source
Hunting for quantum-classical crossover in condensed matter problems
The intensive pursuit for quantum advantage in terms of computational complexity has further led to a modernized crucial question of when and how will quantum computers outperform classical computers.
Nobuyuki Yoshioka +4 more
doaj +1 more source

