Results 71 to 80 of about 308,375 (218)

Data‐Driven Bulldozer Blade Control for Autonomous Terrain Leveling

Advanced Robotics Research, EarlyView.
A simulation‐driven framework for autonomous bulldozer leveling is presented, combining high‐fidelity terramechanics simulation with a neural‐network‐based reduced‐order model. Gradient‐based optimization enables efficient, low‐level blade control that balances leveling quality and operation time.
Harry Zhang, Ganesh Arivoli, Huzaifa Unjhawala, Luning Bakke, Radu Serban, Dan Negrut   +5 more
wiley   +1 more source

Miniaturized Magnetic Tip Design for Endoluminal Vine Robot Navigation

Advanced Robotics Research, EarlyView.
A magnetic tip mount is designed for a miniaturized 7 mm soft‐growing vine robot to enable wireless magnetic steering and onboard imaging, while preserving a 3 mm working channel. The internal–external ring magnets design balances magnetic attachment with low eversion pressure. Experiments demonstrate ±90° steering, 34 mm bending radius, and successful
Andrea Yanez Trujillo, Joshua Davy, James H. Chandler, James Avery, Pietro Valdastri   +4 more
wiley   +1 more source

Deep Contrastive Learning for High‐Throughput Prediction of Drug Resistance Mutations from Sequences

Advanced Science, EarlyView.
This study presents DeepMutDTA, a deep learning framework aimed at predicting mutation‐induced changes in protein‐drug interactions and prioritizing variants potentially linked to drug resistance. Trained on large‐scale data, it incorporates SimSiam‐MuTF, a label‐aware contrastive fine‐tuning strategy that encourages separation between WT and MT ...
Xiaowen Hu, Pan Zhang, Shangqian Wu, Hao Sun, Minwei Li, Sophia Tsoka, Zizhang Sheng, Lei Deng   +7 more
wiley   +1 more source

Neural Fields for Highly Accelerated 2D Cine Phase Contrast MRI

Advanced Science, EarlyView.
ABSTRACT 2D cine phase contrast (CPC) MRI provides quantitative information on blood velocity and flow within the human vasculature. However, data acquisition is time‐consuming, motivating the reconstruction of the velocity field from undersampled measurements to reduce scan times. In this work, neural fields are proposed as a continuous spatiotemporal
Pablo Arratia, Martin J. Graves, Mary McLean, Carolin Pirkl, Carola‐Bibiane Schönlieb, Timo Schirmer, Florian Wiesinger, Matthias J. Ehrhardt   +7 more
wiley   +1 more source

Optimizing Indonesian-Sundanese Bilingual Translation with Adam-Based Neural Machine Translation

Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)
This research seeks to construct an automatic translation between Indonesian and Sundanese languages based on the Neural Machine Translation (NMT) method.
Anita Qotrun Nada, Aji Prasetya Wibawa, Dhea Fanny Putri Syarifa, Erliana Fajarwati, Fadia Irsania Putri   +4 more
doaj   +1 more source

Physics‐Embedded Neural Network: A Novel Approach to Design Polymeric Materials

Advanced Science, EarlyView.
Traditional black‐box models for polymer mechanics rely solely on data and lack physical interpretability. This work presents a physics‐embedded neural network (PENN) that integrates constitutive equations into machine learning. The approach ensures reliable stress predictions, provides interpretable parameters, and enables performance‐driven, inverse ...
Siqi Zhan, Hengheng Zhao, Haotian Wang, Zhanjie Liu, Qian Li, Weifeng Zhang, Qingsong Zhao, Liqun Zhang, Jun Liu   +8 more
wiley   +1 more source

Personalized Network‐Guided Neuromodulation Enhances Human Working Memory

Advanced Science, EarlyView.
A personalized neuromodulation framework combining individualized functional brain network targeting with real‐time neural decoding is introduced. Using concurrent TMS–fMRI, participant‐specific stimulation targets and optimal frequencies are identified. Only optimal‐frequency stimulation improves working memory across sessions.
Ahsan Khan, Hongming Li, Camille Blaine, Julie Grier, Ethan Hammett, Almaris Figueroa‐Gonzalez, Sarai Garcia, Romain Duprat, Justin Reber, Joseph Deluisi, Christos Davatzikos, Theodore D. Satterthwaite, Yong Fan, Desmond J. Oathes   +13 more
wiley   +1 more source

ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals

Advanced Science, EarlyView.
The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray, Andrew R. Castillo, Manoj Kolel‐Veetil, Surya R. Kalidindi   +3 more
wiley   +1 more source

Unifying Composition and Process Design: A Heterogeneous Graph Neural Network for Discovering High‐Performance Cu Alloys

Advanced Science, EarlyView.
By overcoming the fixed‐path limitations of conventional machine learning, a heterogeneous graph neural network fundamentally reconstructs material data representation. Integrating variable processing sequences with intrinsic elemental features, this framework enables exploratory optimization across high‐dimensional spaces.
Jie Yin, Qian Lei, Wei Yan, Yue Li, Tong Xie, Shuang Zhou, Chong Wang, Bram Hoex, Qiang Long, Caoyang Jiang, Min Song, Zhou Li, Zhangwei Wang   +12 more
wiley   +1 more source

HARPUT'LU ABDULHAMIT HAMDiEFENDi (1830-1902) VE HZ. PEYGAMBER'iN BILGiSiNE DAiR BiR RiSALESi "Safvetu Efkari'I-Uiema fi isbati Ilmi Nebiyyina bi'I-Esma"

Fırat Üniversitesi İlahiyat Fakültesi Dergisi, 2001
HARPUTI ABDULHAMİT HAMDİ EFENDi and his epistle "Safwatu Afkari'l Ulama fi Isbliti Ilmi Nabiyyina bi'l-Asma", which is on the Prophet's knowledge: An Ottornan scholar A.
Bünyamin Erul
doaj