Results 111 to 120 of about 1,563,284 (329)

Identifying Physical Interactions in Contact‐Based Robot Manipulation for Learning from Demonstration

Advanced Robotics Research, EarlyView.
Robots can learn manipulation tasks from human demonstrations. This work proposes a versatile method to identify the physical interactions that occur in a demonstration, such as sequences of different contacts and interactions with mechanical constraints.
Alex Harm Gert‐Jan Overbeek, Herman van der Kooij, Douwe Dresscher, Mark Vlutters   +3 more
wiley   +1 more source

Accounting for model structure, parameter and input forcing uncertainty in flood inundation modeling using Bayesian model averaging

Journal of Hydrology, 2018
Reliability of flood stage and inundation extent predictions are affected by the performance of a hydraulic model. However, uncertainties at all times exist in the model setup process.
Zhuo Liu, V. Merwade
semanticscholar   +1 more source

Continual Learning for Multimodal Data Fusion of a Soft Gripper

Advanced Robotics Research, EarlyView.
Models trained on a single data modality often struggle to generalize when exposed to a different modality. This work introduces a continual learning algorithm capable of incrementally learning different data modalities by leveraging both class‐incremental and domain‐incremental learning scenarios in an artificial environment where labeled data is ...
Nilay Kushawaha, Egidio Falotico
wiley   +1 more source

Compliant Pneumatic Feet with Real‐Time Stiffness Adaptation for Humanoid Locomotion

Advanced Robotics Research, EarlyView.
A compliant pneumatic foot with real‐time variable stiffness enables humanoid robots to adapt to changing terrains. Using onboard vision and pressure control, the foot modulates stiffness within each gait cycle, reducing impact forces and improving balance. The design, cast in soft silicone with embedded air chambers and Kevlar wrapping, offers durable,
Irene Frizza, Hiroshi Kaminaga, Philippe Fraisse, Gentiane Venture   +3 more
wiley   +1 more source

Developing a Clinician‐Friendly Online Dynamic Nomogram for Survival Prediction in Colon Cancer Patients

Annals of Gastroenterological Surgery
Aim This study used Bayesian model averaging to develop an online dynamic nomogram for predicting colon cancer survival, showcasing its value in integrating key prognostic factors for clinical use. Methods This retrospective study analysed surgical colon
Mohammad Asghari‐Jafarabadi, Simon Wilkins, John Paul Plazzer, Raymond Yap, Paul J. McMurrick   +4 more
doaj   +1 more source

Decoding Human Placental Cellular and Molecular Responses to Obesity and Fetal Growth

Advanced Science, EarlyView.
Women with obesity often deliver large‐for‐gestational‐age (LGA) infants. Single‐nucleus RNA sequencing of term placenta reveals that hypoxia and TNF‐α signaling in syncytiotrophoblasts are featured in maternal obesity, but inflammatory signatures in Hofbauer cells and response to lipid or carbohydrate metabolism in fibroblasts are specific to LGA.
Hong Jiang, Emilie Derisoud, Denise Parreira, Nayere Taebnia, Paulo R. Jannig, Reza Zandi Shafagh, Allan Zhao, Congru Li, Macarena Ortiz, Manuel Alejandro Maliqueo, Elisabet Stener‐Victorin, Volker M. Lauschke, Qiaolin Deng   +12 more
wiley   +1 more source

Forecasting using Bayesian and Information Theoretic Model Averaging: An Application to UK Inflation [PDF]

In recent years there has been increasing interest in forecasting methods that utilise large datasets, driven partly by the recognition that policymaking institutions need to process large quantities of information.
George Kapetanios, Simon Price, Vincent Labhard   +2 more
core  

Hierarchical Summary Statistics Encoding Across Primary Visual and Posterior Parietal Cortices

Advanced Science, EarlyView.
This study shows that mouse V1 simultaneously encodes the ensemble mean and variance of motion, providing a robust summary‐statistic representation that persists despite single‐neuron variability. These signals propagate to PPC, where they are transformed into abstract category representations during decision making.
Young‐Beom Lee, Oliver James, Gaeun Jung, Doyun Lee, Yee‐Joon Kim   +4 more
wiley   +1 more source

Modified Bayesian D-Optimality for Accelerated Degradation Test Design With Model Uncertainty

IEEE Access, 2019
Accelerated degradation test (ADT) has become the main method to assess system reliability. In ADT, Bayesian D-optimality criterion is an effective objective function to deal with the model parameter uncertainty in designing an ADT plan.
Yong Yu, Changhua Hu, Xiaosheng Si, Jianxun Zhang   +3 more
doaj   +1 more source

Improving Estimation of Cropland Evapotranspiration by the Bayesian Model Averaging Method with Surface Energy Balance Models

Atmosphere, 2019
Evapotranspiration (ET) is one of the key components of the global hydrological cycle. Many models have been established to obtain an accurate estimation of ET, but the uncertainty of each model has not been satisfactorily addressed, and the weight ...
Huaiwei Sun, Yong Yang, Ruiying Wu, D. Gui, J. Xue, Yi Liu, Dong Yan   +6 more
semanticscholar   +1 more source