Results 181 to 190 of about 5,989,884 (327)

A Robotic Urinary Bladder Enabling Volume Monitoring and Assisted Micturition

Advanced Intelligent Systems, EarlyView.
An implantable robotic bladder is presented that can store urine in an origami‐designed enclosure. An inductance sensing principle can monitor and transfer the urine volume in real‐time. It can actively expand based on the amount of urine collected from kidneys and apply on‐demand mechanical compression to assist urination.
Izadyar Tamadon, Michele Ibrahimi, Federica Semproni, Veronica Iacovacci, Arianna Menciassi   +4 more
wiley   +1 more source

Elastic Fast Marching Learning from Demonstration

Advanced Intelligent Systems, EarlyView.
This article presents Elastic Fast Marching Learning (EFML), a novel approach for learning from demonstration that combines velocity‐based planning with elastic optimization. EFML enables smooth, precise, and adaptable robot trajectories in both position and orientation spaces.
Adrian Prados, Brendan Hertel, Ramon Barber, Reza Azadeh   +3 more
wiley   +1 more source

Automated Discovery of Multicellular Behavior for Optimized Plant Growth and Climate Resilience

Advanced Intelligent Systems, EarlyView.
An automated robotic system is described for rapid scientific experimentation with multicellular organisms. By enhancing a robotic liquid handler with a custom developed deep learning algorithm and camera module, samples and data are prepared with minimal human intervention.
Mark A. DeAngelis, Philip R. LeDuc, Warren C. Ruder   +2 more
wiley   +1 more source

Online teaching emotion analysis based on GRU and nonlinear transformer algorithm. [PDF]

PeerJ Comput Sci, 2023
Ding L.
europepmc   +1 more source

IMPLEMENTASI PEMBELAJARAN BLENDED LEARNING BERBASIS APLIKASI WHATSAPP KELAS 5 SDN GEDANGAN 7 KABUPATEN MALANG [PDF]

This blended learning model is a model that combines teaching models, ways of presenting material, learning styles and media used for support. This model is done by combining face-to-face learning and online learning.
Rahmawati, Anisa Dwi
core  

Teacher emotions and agency enactment in online teaching

Teaching and Teacher Education : An International Journal of Research and Studies
Jian Tao, Yueting Xu, X. Gao
semanticscholar   +1 more source

Hierarchical Language Models for Semantic Navigation and Manipulation in an Aerial‐Ground Robotic System

Advanced Intelligent Systems, EarlyView.
A hierarchical multimodal framework coupling a large language model for task decomposition and semantic mapping with a fine‐tuned vision‐language model for semantic perception, enhanced by GridMask, is presented. An aerial‐ground robot team exploits the semantic map for global and local planning.
Haokun Liu, Zhaoqi Ma, Yunong Li, Junichiro Sugihara, Yicheng Chen, Jinjie Li, Moju Zhao   +6 more
wiley   +1 more source

Bridging High‐Fidelity Simulations and Physics‐Based Learning using a Surrogate Model for Soft Robot Control

Advanced Intelligent Systems, EarlyView.
A surrogate‐model‐based framework is proposed for combining high‐fidelity finite element method and efficient physics simulations to enable fast, accurate soft robot simulation for reinforcement learning, validated through sim‐to‐real experiments. Soft robotics holds immense promise for applications requiring adaptability and compliant interactions ...
Taehwa Hong, Jungjae Lee, Byung‐Hyun Song, Yong‐Lae Park   +3 more
wiley   +1 more source

Characteristics, Management, and Utilization of Muscles in Musculoskeletal Humanoids: Empirical Study on Kengoro and Musashi

Advanced Intelligent Systems, EarlyView.
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, Kei Okada, Masayuki Inaba   +2 more
wiley   +1 more source

How effective is online teaching of physiology modules? perception of Rwandan health sciences students. [PDF]

Curr Res Physiol
Alagbonsi AI, Gbadamosi MA, Nemerimana M, Olubiyi MV, Onaadepo O, Ime AU, Feyitimi AA, Mungai RW, Rutagarama F, Zambrano DM, Omeiza NA, Elias SO.   +11 more
europepmc   +1 more source