Results 181 to 190 of about 959 (264)

A Novel Parameter Estimation Method for Pneumatic Soft Hand Control Applying Logarithmic Decrement for Pseudo‐Rigid Body Modeling

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
In this research, a paradigm of parameter estimation method for pneumatic soft hand control is proposed. The method includes the following: 1) sampling harmonic damping waves, 2) applying pseudo‐rigid body modeling and the logarithmic decrement method, and 3) deriving position and force control.
Haiyun Zhang, Kelvin HoLam Heung, Gabrielle J. Naquila, Ashwin Hingwe, Ashish D. Deshpande   +4 more
wiley   +1 more source

Stellar Kinematics and Spiral Arms.

The Astronomical Journal, 1961
openaire   +2 more sources

Strong Lensing by Galaxies. [PDF]

Space Sci Rev
Shajib AJ, Vernardos G, Collett TE, Motta V, Sluse D, Williams LLR, Saha P, Birrer S, Spiniello C, Treu T.   +9 more
europepmc   +1 more source

Calibration‐Free Electromyography Motor Intent Decoding Using Large‐Scale Supervised Pretraining

Advanced Intelligent Systems, EarlyView.
Calibration‐free electromyography motor intent decoding is enabled through large‐scale supervised pretraining across heterogeneous datasets. A Spatially Aware Feature‐learning Transformer processes variable channel counts and electrode geometries, allowing transfer across users and recording setups. On a held‐out benchmark, fine‐tuned cross‐user models
Alexander E. Olsson, Nebojša Maleševic, Anders Björkman, Christian Antfolk   +3 more
wiley   +1 more source

Neutron capture measurements for s-process nucleosynthesis: A review about CERN n_TOF developments and contributions. [PDF]

Eur Phys J A Hadron Nucl
Domingo-Pardo C, Aberle O, Alcayne V, Alpar G, Halabi MA, Amaducci S, Babiano V, Bacak M, Balibrea-Correa J, Bartolomé J, Bernardes AP, Gameiro BB, Berthoumieux E, Beyer R, Birch M, Boromiza M, Bosnar D, Brusasco B, Caamaño M, Cahuzac A, Calviño F, Calviani M, Cano-Ott D, Casanovas A, Castelluccio DM, Catlett D, Cerutti F, Cescutti G, Chiaveri E, Claps G, Colombetti P, Colonna N, Camprini PC, Cortés G, Cortés-Giraldo MA, Cosentino L, Cristallo S, D'Ottavi A, de la Fuente Rosales G, Dellmann SF, Diakaki M, Di Castro M, Di Chicco A, Dietz M, Dupont E, Durán I, Eleme Z, Eslami M, Fargier S, Fernández-Domínguez B, Finocchiaro P, Flanagan W, Furman V, Gandhi A, García-Infantes F, Gawlik-Ramiega A, Gervino G, Gilardoni S, González-Romero E, Goula S, Griesmayer E, Guerrero C, Gunsing F, Gustavino C, Heyse J, Hillman W, Jenkins DG, Jericha E, Junghans A, Kadi Y, Kaperoni K, Kelly I, Kokkoris M, Kopatch Y, Krtička M, Kyritsis N, Lederer-Woods C, Lerendegui-Marco J, Manna A, Martínez T, Martínez-Cañada M, Masi A, Massimi C, Mastinu P, Mastromarco M, Maugeri EA, Mazzone A, Mendoza E, Mengoni A, Michalopoulou V, Milazzo PM, Moldenhauer J, Mucciola R, González EM, Musumarra A, Negret A, Odusina E, Papanikolaou D, Patronis N, Pavón-Rodríguez JA, Pellegriti MG, Pérez-Maroto P, de Rada Fiol AP, Perfetto G, Perkowski J, Petrone C, Pieretti N, Piersanti L, Pirovano E, Porras I, Praena J, Quesada JM, Reifarth R, Rochman D, Romanets Y, Rooney A, Rovira G, Rubbia C, Sánchez-Caballero A, Sahoo RN, Scarpa D, Schillebeeckx P, Smith AG, Sosnin NV, Spelta M, Stamati ME, Stasiak K, Tagliente G, Tarifeño-Saldivia A, Tarrío D, Torres-Sánchez P, Tosi S, Tsiledakis G, Valenta S, Vaz P, Vecchio G, Vescovi D, Vlachoudis V, Vlastou R, Wallner A, Weiss C, Woods PJ, Wright T, Wu R, Žugec P, The n_TOF Collaboration.   +145 more
europepmc   +1 more source

Adaptive Autonomy in Microrobot Motion Control via Deep Reinforcement Learning and Path Planning Synergy

Advanced Intelligent Systems, EarlyView.
This study introduces a data‐driven framework that combines deep reinforcement learning with classical path planning to achieve adaptive microrobot navigation. By training a surrogate neural network to emulate microrobot dynamics, the approach improves learning efficiency, reduces training time, and enables robust real‐time obstacle avoidance in ...
Amar Salehi, Bairong Zhu, Haoyu Liu, Tingting Yu   +3 more
wiley   +1 more source

Background-free ¹²C(<i>α</i>, <i>γ</i>) angular distribution measurements with a time projection chamber operating in Gamma beams. [PDF]

Commun Phys
Haverson KCZ, Smith R, Gai M, Schweitzer DK, Stern SR, Finch SW.   +5 more
europepmc   +1 more source

Enhancing Atomic‐Resolution in Electron Microscopy: A Deep Learning Denoiser Operating in the Frequency Domain

Advanced Intelligent Systems, EarlyView.
The newly developed AI‐automated Fast Fourier Transform denoising algorithm surpasses conventional real‐space methods by revealing even light atoms otherwise hidden in noisy backgrounds. Atomic resolution electron microscopy has become an essential tool for many scientific fields, when direct visualization of atomic arrangements and defects is needed ...
Ivan Pinto‐Huguet, Marc Botifoll, Xuli Chen, Martin Børstad Eriksen, Jing Yu, Giovanni Isella, Andreu Cabot, Gonzalo Merino, Jordi Arbiol   +8 more
wiley   +1 more source

EMG‐Driven Telemetry and Inference System for Fish: Pose Reconstruction and Flow Sensing

Advanced Intelligent Systems, EarlyView.
This work introduces an electromyography (EMG)‐driven telemetry framework that reconstructs body pose and infers hydrodynamic conditions in freely swimming fish. A custom 16‐channel archival system records intramuscular EMG, enabling deep‐learning models to decode joint kinematics, classify flow regimes, and reveal channel‐efficient sensing strategies.
Rahdar Hussain Afridi, Waqar Hussain Afridi, Muhammad Hamza, Ahsan Tanveer, Mingxin Wu, Xingwen Zheng, Liang Li, Guangming Xie   +7 more
wiley   +1 more source

Direct evidence for magnetohydrodynamic disk winds driving rotating outflows in protostar HOPS 358. [PDF]

Nat Commun
Kim CH, Lee JE, Johnstone D, Herczeg GJ, Lee CF, Francis L, Sheehan PD.   +6 more
europepmc   +1 more source