Towards Advanced Intelligent and Perceptive Soft Grippers
Advanced Intelligent Systems, EarlyView.Implementing soft yet strong and intelligent soft grippers request innovative and creative solutions in designing soft bodies and seamlessly integrating actuated systems with hierarchical sensing. This review systematically analyses soft grippers with a deep understanding of core components, from fundamental design principles to actuation and sensing ...
Haneul Kim +4 more
wiley +1 more source
Dynamic Bayesian Networks, Elicitation, and Data Embedding for Secure Environments. [PDF]
Entropy (Basel)Drury K, Smith JQ.
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Advanced Intelligent Systems, EarlyView.A physics‐guided deep learning framework, ParamNet, is introduced for the intelligent self‐inversion of vacuum optical tweezers. By fuzing dual‐branch time–frequency features with physical dynamical constraints, it achieves high‐accuracy calibration of trap parameters from short‐window, low‐frequency trajectories, outperforming traditional methods ...
Qi Zheng +4 more
wiley +1 more source
Behavioral Analysis of Postgraduate Education Satisfaction: Unveiling Key Influencing Factors with Bayesian Networks and Feature Importance. [PDF]
Behav Sci (Basel)Li S, Wang T, Yin H, Ding S, Cai Z.
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Exploiting Ferroelectric and Spintronic Dynamics for Neural Network Computation
Advanced Intelligent Systems, EarlyView.Ferroelectric and spintronic devices, relying on the control of polarization and magnetization, offer intrinsically fast, durable, energy‐efficient, and low‐latency building blocks for analog in‐memory computing. The hysteretic dynamics of an order parameter are leveraged to provide nonvolatile, multistate memory and nonlinear switching. Brain‐inspired
Dashiell Harrison +4 more
wiley +1 more source
Acute Myeloid Leukemia Genome Characterization Study and Subtype Classification Employing Feature Selection and Bayesian Networks. [PDF]
BiomedicinesLi Z, Li J, Li S, Wang Y, Wang J.
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Advanced Intelligent Systems, EarlyView.The phase discontinuity problem—where the cyclic nature of phase angles causes catastrophic errors near the ±π boundary—is a fundamental obstacle in learning‐based reconfigurable intelligent surface (RIS) optimization. A phase‐aware hybrid CNN–LSTM framework resolves this by decomposing phase predictions into sine–cosine components, mapping circular ...
Seda Savaşçı Şen +3 more
wiley +1 more source
Clinicopathological characteristics associated with intrapulmonary metastasis rather than single primary lung cancer at first diagnosis: a study based on the Surveillance, Epidemiology, and End Results database using Bayesian networks and structural equation modeling. [PDF]
Transl Lung Cancer ResLiu W +6 more
europepmc +1 more source