Results 51 to 60 of about 86,937 (263)
Background Pediatric obesity is one of the most important health challenges of the twenty-first century. Primary prevention of childhood obesity, can lessen its consequences. This study aims to assess childhood obesity prevention policies in Iran through
Shahnaz Taghizadeh +2 more
doaj +1 more source
This review explores advances in wearable and lab‐on‐chip technologies for breast cancer detection. Covering tactile, thermal, ultrasound, microwave, electrical impedance tomography, electrochemical, microelectromechanical, and optical systems, it highlights innovations in flexible electronics, nanomaterials, and machine learning.
Neshika Wijewardhane +4 more
wiley +1 more source
Scalable Task Planning via Large Language Models and Structured World Representations
This work efficiently combines graph‐based world representations with the commonsense knowledge in Large Language Models to enhance planning techniques for the large‐scale environments that modern robots will need to face. Planning methods often struggle with computational intractability when solving task‐level problems in large‐scale environments ...
Rodrigo Pérez‐Dattari +4 more
wiley +1 more source
Does Monetary Policy Matter for Economic Growth in Tanzania? A Critical Analysis
This paper examines monetary policy's influence on Tanzania's economic growth by utilizing the Autoregressive Distributed Lag model (ARDL). Analysing yearly time series data from 1970 to 2022, the study offers empirical insights into whether monetary ...
Miku G. Benjamine , Tumaini M. Katunzi
doaj +1 more source
Economic policy uncertainty and housing returns in Germany: Evidence from a bootstrap rolling window [PDF]
The purpose of this investigation is to research the causal link between economic policy uncertainty (EPU) and the housing returns (HR) in Germany. In the estimated vector autoregressive models, we test its stability and find the short-run relationship
David Su +3 more
doaj +1 more source
Grounding Large Language Models for Robot Task Planning Using Closed‐Loop State Feedback
BrainBody‐Large Language Model (LLM) introduces a hierarchical, feedback‐driven planning framework where two LLMs coordinate high‐level reasoning and low‐level control for robotic tasks. By grounding decisions in real‐time state feedback, it reduces hallucinations and improves task reliability.
Vineet Bhat +4 more
wiley +1 more source
Uncertainty-Aware Adaptive Replanning: Bridging Distributional RL and Dynamic Window Approach
Path planning for mobile robots in industrial environments is frequently compromised by pseudo-static obstacles with uncertain positional drift and strict kinematic constraints.
Xiaohan Liu, Youbing Feng
doaj +1 more source
Real-time Optimization of Instant Meal Delivery Based on Deep Reinforcement Learning [PDF]
To address the challenges of tight capacity and high delayed rate of meal delivery tasks during peak dining period, a real-time optimization policy based on Deep Reinforcement Learning (DRL) for instant meal delivery is proposed to improve the long-term ...
CHEN Yanru, LIU Keliang, RAN Maoliang
doaj +1 more source
Auditory–Tactile Congruence for Synthesis of Adaptive Pain Expressions in RoboPatients
In this work, we explore auditory–tactile congruence for synthesizing adaptive vocal pain expressions in robopatients. Using a robopatient platform that integrates vocal pain sounds with palpation forces, we conducted 7680 trials across 20 participants.
Saitarun Nadipineni +4 more
wiley +1 more source
Introduction: The implementation of a publicly-funded immunization program results from a complex decision-making process. John Kingdon’s ‘Multiple Streams Framework’ has been extensively used to analyze how and why governmental policies were adopted ...
Philippe De Wals +2 more
doaj +1 more source

