Results 131 to 140 of about 1,139,985 (300)

Compact Modeling of Volatile‐Switching Electrochemical Metallization Memory Cells by Means of the Electromotive Force

open access: yesAdvanced Intelligent Systems, EarlyView.
A volatile‐switching compact model of electrochemical metallization memory cells for neuromorphic architecture is developed and validated by reliable reproduction of device characterization measurements: I−V sweeps, SET kinetics, relaxation dynamics.
Rana Walied Ahmad   +4 more
wiley   +1 more source

RELATIONSHIPS OF ADJUSTING PARAMETERS OF ASYNCHRONOUS MOTORS INSTALLED IN INDUSTRIAL ENTERPRISES WITH PHASE ROTOR ASYNCHRONOUS MOTORS.

open access: yesJournal of new century innovations
The article analyzes the relationship between the values that coordinate induction motors installed in industrial enterprises with asynchronous phase rotor motors. In the analysis, the asynchronous motor of the phase rotor mainly changes the stator current with increasing rotor current, rotor speed, efficiency and the optimal value of the rotor ...
openaire   +1 more source

Collaborative Visual Localization for Modular Self‐Reconfigurable Robots

open access: yesAdvanced Intelligent Systems, EarlyView.
Relative localization in modular self‐reconfigurable robots is challenged by hardware limitations, constrained fields of view, and sensor faults. This paper, based on the SnailBot platform, presents a vision‐based collaborative localization method that combines ArUco markers with learning‐based algorithms to enable robust pose estimation from ...
Guanqi Liang   +4 more
wiley   +1 more source

The Mechanical Transient Process at Asynchronous Motor Oscillating Mode

open access: yes
The research object is squirrel-cage asynchronous motor connected to single-phase sinusoidal. There are shown, that by connecting to the stator windings a certain sequence of half-period positive and negative voltage, a motor rotor is rotated, but three ...
Antonovičs, Uldis   +2 more
core  

Detailed statement of motor vehicle registrations (in dollars)

open access: yes, 2006
Annual; Description based on: 2000; title from caption (viewed Aug.

core  

Physics‐Grounded Probabilistic Bits for Hardware‐Efficient Intelligent Inference and Optimization

open access: yesAdvanced Intelligent Systems, EarlyView.
Si–SiNx interface traps are harnessed as a complementary metal–oxide–semiconductor‐compatible source of controllable randomness for probabilistic bits. Pulse‐width‐programmed stochastic capture converts nanoscale defect dynamics into Boltzmann‐consistent binary outputs, while a physics‐based Simulation Program with Integrated Circuit Emphasis model ...
Dokyoung Lee   +3 more
wiley   +1 more source

Characterization and Selection of Contractile Actuators for Soft Robotics Operating in the Quasistatic Regime

open access: yesAdvanced Intelligent Systems, EarlyView.
We developed methods to characterize soft contractile actuators using force–displacement measurements in the passive state and the total force in the active state and define the operational range of thermal, electrothermal, and pneumatic muscles. A graphical method enables the selection of an actuator based on the required mechanical force–displacement
Qiong Wang   +5 more
wiley   +1 more source

Direct Access to Chiral Piperidines by Enantioselective HAT‐Initiated C(sp3)─H Oxidation

open access: yesAngewandte Chemie, EarlyView.
The direct desymmetrization of piperidines is achieved through manganese‐catalyzed enantioselective α‐C(sp3)─H oxidation with hydrogen peroxide, affording versatile chiral N,O‐acetals in good yields and with high enantio‐ and diastereoselectivity. These intermediates provide access to diverse functionalized piperidines with retention of chirality ...
Sethuraman Muthuramalingam   +5 more
wiley   +2 more sources

Detailed statement of motor vehicle registrations (in dollars)

open access: yes, 2001
Annual; Description based on: 2000; title from caption (viewed Aug.

core  

Ecoefficiency Analysis and Regression in Data Conversion for Spiking Neural Network Training

open access: yesAdvanced Intelligent Systems, EarlyView.
The environmental footprint of spiking neural networks is quantified during dataset encoding and training for autonomous driving regression across three benchmarks. Temporal depth emerges as the dominant driver of energy consumption and CO2 emissions, while the accuracy–energy trade‐off proves dataset‐dependent. On conventional hardware, spiking models
Fernando S. Martínez   +3 more
wiley   +1 more source

Home - About - Disclaimer - Privacy