Results 141 to 150 of about 67,103 (261)

Multimodal Engagement Assessment in Children During Invented Story Paradigm With a Social Robot

Advanced Robotics Research, EarlyView.
A multimodal framework is proposed to assess children's engagement during storytelling interactions with a social robot. Gaze, physiological, and behavioral data are combined and validated against observer ratings. An automated gaze‐labeling strategy is introduced, and supervised classifiers achieve high accuracy. The study supports scalable engagement
Laura Fiorini, Elena Adelucci, Stefano Scatigna, Lorenzo Pugi, Alice Bruni, Benedetta Carotenuto, Chiara Pecini, Filippo Cavallo   +7 more
wiley   +1 more source

PanForest: predicting genes in genomes using random forests. [PDF]

Bioinformatics
Beavan AJS, Domingo-Sananes MR, McInerney JO.   +2 more
europepmc   +1 more source

ChicGrasp: Imitation‐Learning‐Based Customized Dual‐Jaw Gripper Control for Manipulation of Delicate, Irregular Bio‐Products

Advanced Robotics Research, EarlyView.
Automated poultry processing lines still rely on humans to lift slippery, easily bruised carcasses onto a shackle conveyor. Deformability, anatomical variance, and hygiene rules make conventional suction and scripted motions unreliable. We present ChicGrasp, an end‐to‐end hardware‐software co‐designed imitation learning framework, to offer a ...
Amirreza Davar, Zhengtong Xu, Siavash Mahmoudi, Pouya Sohrabipour, Chaitanya Pallerla, Yu She, Wan Shou, Philip Glen Crandall, Dongyi Wang   +8 more
wiley   +1 more source

Indirect state-level estimation of sexual minority adolescent populations by sex, age, and race/ethnicity using random forests. [PDF]

PLoS One
Alves-Maciel B, Pampati S, Fodeman A, Van Handel M, Zheng L, Ye Z, Yaesoubi R, Salomon JA.   +7 more
europepmc   +1 more source

Modular, Textile‐Based Soft Robotic Grippers for Agricultural Produce Handling

Advanced Robotics Research, EarlyView.
This article introduces textile‐based pneumatic grippers that transform simple textiles into robust bending actuators. Detailed experiments uncover how cut geometry and fabric selection shape performance. Successful handling of fragile agricultural items showcases the potential of textile robotics for safe, scalable automation in food processing and ...
Zeyu Hou, Eran Beeri Bamani, Joao Buzzatto, Bryan Busby, Lucas Ferrari Gerez   +4 more
wiley   +1 more source

Retraction Note: Optimizing credit card fraud detection with random forests and SMOTE. [PDF]

Sci Rep
Sundaravadivel P, Isaac RA, Elangovan D, KrishnaRaj D, Rahul VVL, Raja R.   +5 more
europepmc   +1 more source

EFFNet: A skin cancer classification model based on feature fusion and random forests. [PDF]

PLoS One, 2023
Ma X, Shan J, Ning F, Li W, Li H.
europepmc   +1 more source

Task‐Oriented Path Planning Towards Autonomous Sensor Network Deployment in Rainforest Canopies

Advanced Robotics Research, EarlyView.
An informative path planner for drone‐based deployment of wireless sensor networks in rainforest canopies is presented, addressing key challenges in large‐scale biodiversity monitoring. By integrating canopy surface detection with connectivity‐aware sampling under strict flight constraints, the approach enables efficient and reliable aerial sensor ...
Rita Santos Raminhos, Salua Hamaza
wiley   +1 more source

Determining the relative importance of risk and protective factors for adjustment disorder symptoms during the COVID-19 pandemic by mixed-effects random forests. [PDF]

Psychol Med
Lotzin A, Finne E, Schildbach G, Acquarini E, Ajdukovic D, Ajdukovic M, Anastassiou-Hadjicharalambous X, Ardino V, Hensler I, Arnberg FK, Böttche M, Dragan M, Figueiredo-Braga M, Gelezelyte O, Grajewski P, Groen S, van Hoof MJ, Javakhishvili JD, Kazlauskas E, Lioupi C, Lueger-Schuster B, Sales L, Tsiskarishvili L, Zrnic Novakovic I, Schäfer I, ADJUST Study Consortium.   +25 more
europepmc   +1 more source

Intelligent Maintenance Review for Robots: Multimodal Information, Deep Diagnosis and Embodied Artificial Intelligence

Advanced Robotics Research, EarlyView.
This review maps the methods to monitor robots’ health by fusing vibration, sound, control signals, vision, force, and oil information with artificial intelligence. It identifies deep learning, transfer learning, digital twins, and physics‐informed models as key methodological pathways enabling earlier diagnosis, safer human–robot collaboration, and ...
Yuting Qiao, Hongbo Wang, Naipeng Li, Shuo Wang, Yaguo Lei, Tonghai Wu, Junyi Cao   +6 more
wiley   +1 more source