Results 211 to 220 of about 8,591 (298)
This article reviews the current state of bioinspired soft robotics. The article discusses soft actuators, soft sensors, materials selection, and control methods used in bioinspired soft robotics. It also highlights the challenges and future prospects of this field.
Abhirup Sarker +2 more
wiley +1 more source
Cybersecurity Baseline and Risk Mitigation for Open Data in IoT-Enabled Smart City Systems: A Case Study of the Hradec Kralove Region. [PDF]
Sobeslav V, Horalek J.
europepmc +1 more source
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 +4 more
wiley +1 more source
A deep reinforcement learning framework for influence maximization problem on large-scale social networks. [PDF]
Yang F +5 more
europepmc +1 more source
Musculoskeletal humanoids exhibit rich biomechanical properties that remain insufficiently unified in prior discussions. This article systematically categorizes muscle characteristics into five properties: redundancy, independency, anisotropy, variable moment arm, and nonlinear elasticity, and analyzes their combined effects on control.
Kento Kawaharazuka +2 more
wiley +1 more source
Integer programming for learning directed acyclic graphs from nonidentifiable Gaussian models. [PDF]
Xu T +3 more
europepmc +1 more source
Calibration‐Free Electromyography Motor Intent Decoding Using Large‐Scale Supervised Pretraining
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 +3 more
wiley +1 more source
Rate-Splitting-Based Resource Allocation in FANETs: Joint Optimization of Beam Direction, Node Pairing, Power and Time Slot. [PDF]
Zhao F, Song C, Li X, Liu Y, Liang Y.
europepmc +1 more source
A data‐efficient artificial intelligence‐assisted framework, which integrates experimental data with machine learning, is developed for the design of bimodal networked dielectric elastomers (DEs) as advanced artificial muscles. It adopts neural networks to predict DEs’ mechanical properties and support vector machines to classify electromechanical ...
Ofoq Normahmedov +8 more
wiley +1 more source
An optimization framework for hierarchical clustering. [PDF]
Gilad G, Sharan R.
europepmc +1 more source

