Supporting Animation Models for Teaching Embedded Microcontrollers Peripherals
Richard Balogh, Krisztián Lipták
openalex +1 more source
Benchmarks to Find the Optimal Microcontroller-Architecture
Klaus-Dietrich Kramer +2 more
openalex +2 more sources
Tunable Plug‐and‐Play Meta‐Nanogenerator Materials for Multi‐Range Force Measurements
The multifunctional and tunable meta‐nanogenerator material system combines a mechanical metamaterial and a triboelectric nanogenerator enabling self‐powered, real‐time force sensing across application‐specific ranges. Geometrical tuning adjusts stiffness and the force sensing range, while modular integration streamlines assembly.
Roshira Premadasa +6 more
wiley +1 more source
An optimized stacking-based TinyML model for attack detection in IoT networks. [PDF]
Sharma A, Rani S, Shabaz M.
europepmc +1 more source
RANCANG BANGUN HYBRID ENERGY SOLAR CELL DAN PEMBANGKIT LISTRIK TENAGA BAYU BERBASIS MICROCONTROLLER
Aulia Randy Permadi, Achmad Imam Agung
openalex +1 more source
Polylactic acid (PLA) embedded in 3D anodic aluminum oxide (3D‐AAO) yields triboelectric nanogenerators (TENGs) with ɛeff = 5.1, delivering 20V and 108µW both per cm2. These agglomeration‐resistant, compostable/biocompatible devices retain 95% output after 104 cycles, enabling robust self‐powered Internet of Things (IoT) sensing.
Carlos G. Cobos +5 more
wiley +1 more source
FastKAN-DDD: A novel fast Kolmogorov-Arnold network-based approach for driver drowsiness detection optimized for TinyML deployment. [PDF]
Essahraui S +7 more
europepmc +1 more source
Neuromorphic Motor Control with Electrolyte‐Gated Organic Synaptic Transistors
Electrolyte‐gated organic synaptic transistor (EGOST)‐based neuromorphic motor control systems integrate sensing, processing, and actuation by mimicking biological synapses. With advantages such as low power consumption, tunable synaptic plasticity, and mechanical flexibility, they are emerging as next‐generation core technologies for real‐time ...
Sung‐Hwan Kim +3 more
wiley +1 more source
TinyML with CTGAN based smart industry power load usage prediction with original and synthetic data visualization towards industry 5.0. [PDF]
Muthusamy M +5 more
europepmc +1 more source

