Results 241 to 250 of about 637,276 (316)
Generalized Moment Method for Gap Estimation and Quantum Monte Carlo Level Spectroscopy
Hidemaro Suwa, Synge Todo
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This article provides an overview of recent advancements in bulk processing of rare‐earth‐free hard magnetic materials. It also addresses related simulation approaches at different scales. The research on rare‐earth‐free magnetic materials has increased significantly in recent years, driven by supply chain issues, environmental and social concerns, and
Daniel Scheiber, Andrea Bachmaier
wiley +1 more source
Abstract Background Computed tomography (CT) is an essential imaging modality for disease diagnosis, treatment efficacy, and image‐based guidance of various medical procedures. The locally deposited radiation dose in tissues, as estimated by the computed tomography dose index (CTDI), can vary considerably across exposures delivered by CT scanners from ...
Laura E. Dinwiddie +13 more
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Quantum Monte Carlo Method for Fermions, Free of Discretization Errors [PDF]
S. Rombouts, K. Heyde, N. Jachowicz
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Machine Learning Assisted Fluorescent Sensor Array for Sensing Applications
Chemical analysis is being revolutionized by the combination of the high‐dimensional, multi‐channel signals generated by fluorescent sensor arrays and the powerful data analysis enabled by machine learning. This review covers state‐of‐the‐art studies that use machine learning techniques for the identification and quantification of fluorescent sensor ...
Haobo Guo +2 more
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Investigation of the full configuration interaction quantum Monte Carlo method using homogeneous electron gas models [PDF]
James J. Shepherd +2 more
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Generative Deep Learning for Advanced Battery Materials
This review explores the role of generative deep learning (DL) in battery materials analysis and highlights the fundamental principles of generative DL and its applications in designing battery materials. The importance of using multimodal data is underscored to effectively address the challenges faced during the development of battery materials across
Deepalaxmi Rajagopal +3 more
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Use of Automation Technologies and Data Mining in Speech Recognition for Autism
Pipeline analyzes clinical and naturalistic speech using LENA, wav2vec 2.0, and foundation‐model ASR (Whisper) to enable scalable ASD detection and severity estimation. Future work integrates benchmarking, privacy‐preserving collaboration (federated learning), and explainable, edge‐ready AI for clinically credible assessment and longitudinal monitoring.
Rongjie Mao, Yuncheng Zhu
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