Results 171 to 180 of about 55,131 (288)

Enhancing SILCS-MC via GPU Acceleration and Ligand Conformational Optimization with Genetic and Parallel Tempering Algorithms. [PDF]

J Phys Chem B
Zhao M, Yu W, MacKerell AD.
europepmc   +1 more source

Overcoming the Nyquist Limit in Molecular Hyperspectral Imaging by Reinforcement Learning

Advanced Intelligent Discovery, EarlyView.
Explorative spectral acquisition guide automatically selects informative spectral bands to optimize downstream tasks, outperforming full‐spectrum acquisition. The selected hyperspectral data are used for tasks such as unmixing and segmentation. BandOptiNet encodes selection states and outputs optimal bands to guide spectral acquisition. Recent advances
Xiaobin Tang, Yongqing Zhang, Xinyu Deng, Hyeon Jeong Lee, Delong Zhang   +4 more
wiley   +1 more source

Automated Bacterial Identification and Morphological Feature Analysis in Low‐Dose Cryo‐EM Using YOLOv11

Advanced Intelligent Discovery, EarlyView.
AI‐based tools enable rapid characterization of bacterial ultrastructure in low‐dose cryogenic transmission electron microscopy. The envelope thickness tool quantifies membrane thickness and anisotropy. The flagella module analyzes filament morphology and detects cell‐flagella contacts.
Sita Sirisha Madugula, Lynnicia N. Massenburg, Spenser R. Brown, Amber N. Bible, Chanda R. Harris, Lance X. Zhang, Kiara Parker, Scott T. Retterer, Jennifer L. Morrell‐Falvey, Rama K. Vasudevan, Alexis N. Williams   +10 more
wiley   +1 more source

Multi-GPU Acceleration of Branchless Distance Driven Projection and Backprojection for Clinical Helical CT. [PDF]

J Imaging Sci Technol, 2017
Mitra A, Politte DG, Whiting BR, Williamson JF, O'Sullivan JA.   +4 more
europepmc   +1 more source

Roadmap on Artificial Intelligence‐Augmented Additive Manufacturing

Advanced Intelligent Systems, EarlyView.
This Roadmap outlines the transformative role of artificial intelligence‐augmented additive manufacturing, highlighting advances in design, monitoring, and product development. By integrating tools such as generative design, computer vision, digital twins, and closed‐loop control, it presents pathways toward smart, scalable, and autonomous additive ...
Ali Zolfagharian, Liuchao Jin, Qi Ge, Wei‐Hsin Liao, Andrés Díaz Lantada, Francisco Franco Martínez, Tianyu Zhang, Tao Liu, Charlie C. L. Wang, Mohammad Hossein Mosallanejad, Reza Ghanavati, Abdollah Saboori, Alejandro De Blas De Miguel, William Solórzano‐Requejo, Yi Cai, Xiangyang Dong, Huangyi Qu, Najmeh Samadiani, Guangyan Huang, Austin Downey, Yanzhou Fu, Lang Yuan, Tsz‐Kwan (Glory) Lee, Arbind Agrahari Baniya, Eisha Waseem, Abdul Rahman Sani, Abbas Z. Kouzani, Yijia Wu, Markus P. Nemitz, Masoud Shirzad, Dageon Oh, Seung Yun Nam, Amedeo Franco Bonatti, Irene Chiesa, Gabriele Maria Fortunato, Giovanni Vozzi, Carmelo De Maria, Mahdi Bodaghi   +37 more
wiley   +1 more source

Hardware acceleration of number theoretic transform for zk‐SNARK

Engineering Reports, EarlyView., 2023
An FPGA‐based hardware accelerator with a multi‐level pipeline is designed to support the large‐bitwidth and large‐scale NTT tasks in zk‐SNARK. It can be flexibly scaled to different scales of FPGAs and has been equipped in the heterogeneous acceleration system with the help of HLS and OpenCL.
Haixu Zhao, Dong Ding, Feng Wang, Pengcheng Hua, Ning Wang, Qin Wu, Zhilei Chai   +6 more
wiley   +1 more source

Automated Discovery of Multicellular Behavior for Optimized Plant Growth and Climate Resilience

Advanced Intelligent Systems, EarlyView.
An automated robotic system is described for rapid scientific experimentation with multicellular organisms. By enhancing a robotic liquid handler with a custom developed deep learning algorithm and camera module, samples and data are prepared with minimal human intervention.
Mark A. DeAngelis, Philip R. LeDuc, Warren C. Ruder   +2 more
wiley   +1 more source

tomoCAM: fast model-based iterative reconstruction via GPU acceleration and non-uniform fast Fourier transforms. [PDF]

J Synchrotron Radiat
Kumar D, Parkinson DY, Donatelli JJ.
europepmc   +1 more source

VAE+DDPG: An Attention‐Enhanced Variational Autoencoder for Deep Reinforcement Learning‐Based Autonomous Navigation in Low‐Light Environments

Advanced Intelligent Systems, EarlyView.
Variational Autoencoder+Deep Deterministic Policy Gradient addresses low‐light failures of infrared depth sensing for indoor robot navigation. Stage 1 pretrains an attention‐enhanced Variational Autoencoder (Convolutional Block Attention Module+Feature Pyramid Network) to map dark depth frames to a well‐lit reconstruction, yielding a 128‐D latent code ...
Uiseok Lee, Chanhong Hwang, Hyunseok Kang, Yechan Park, Hangwoo Jin, Tuan Anh Nguyen, Eunmi Choi, Dugki Min   +7 more
wiley   +1 more source

Real‐Time Sampling‐Based Model Predictive Control Based on Reverse Kullback–Leibler Divergence and Its Adaptive Acceleration

Advanced Intelligent Systems, EarlyView.
This study presents a new sampling‐based model predictive control minimizing reverse Kullback‐Leibler divergence to quickly find a local optimum. In addition, a modified Nesterov's acceleration method is introduced for faster convergence. The method is effective for real‐time simulations and real‐world operability improvement on a force‐driven mobile ...
Taisuke Kobayashi, Kota Fukumoto
wiley   +1 more source