Results 81 to 90 of about 615,232 (315)

A Robust Deep Temporal Causal Discovery Platform for Single‐Cell Gene Regulatory Network Reconstruction

Advanced Intelligent Discovery, EarlyView.
scTIGER2.0 is a deep‐learning framework that infers gene regulatory networks from single‐cell RNA sequencing data. By integrating correlation, pseudotime ordering, deep learning and bootstrap‐based significance testing, it reduces false positives and reveals directional gene interactions.
Nishi Gupta, Madison Dautle, Shaoqiang Zhang, Yong Chen   +3 more
wiley   +1 more source

Simulating river flow velocity on global scale [PDF]

, 2005
Flow velocity in rivers has a major impact on residence time of water and thus on high and low water as well as on water quality. For global scale hydrological modeling only very limited information is available for simulating flow velocity. Based on the
Döll, Petra, Hunger, Martin, Schulze, Kerstin   +2 more
core   +2 more sources

VAE+DDPG: An Attention‐Enhanced Variational Autoencoder for Deep Reinforcement Learning‐Based Autonomous Navigation in Low‐Light Environments

Advanced Intelligent Systems, EarlyView.
Variational Autoencoder+Deep Deterministic Policy Gradient addresses low‐light failures of infrared depth sensing for indoor robot navigation. Stage 1 pretrains an attention‐enhanced Variational Autoencoder (Convolutional Block Attention Module+Feature Pyramid Network) to map dark depth frames to a well‐lit reconstruction, yielding a 128‐D latent code ...
Uiseok Lee, Chanhong Hwang, Hyunseok Kang, Yechan Park, Hangwoo Jin, Tuan Anh Nguyen, Eunmi Choi, Dugki Min   +7 more
wiley   +1 more source

Ending Hunger in Montgomery County [PDF]

, 2012
Though Montgomery County is listed as the 20th wealthiest county in the United States and has been ranked the 9th Best Place to Raise a Family by Forbes Magazine, it has seen an extraordinary increase in eligibility for food stamps.
Mariana Chilton, Vanesa Karamanian
core  

A Flexible and Energy‐Efficient Compute‐in‐Memory Accelerator for Kolmogorov–Arnold Networks

Advanced Intelligent Systems, EarlyView.
This article presents KA‐CIM, a compute‐in‐memory accelerator for Kolmogorov–Arnold Networks (KANs). It enables flexible and efficient computation of arbitrary nonlinear functions through cross‐layer co‐optimization from algorithm to device. KA‐CIM surpasses CPU, ASIC, VMM‐CIM, and prior KAN accelerators by 1–3 orders of magnitude in energy‐delay ...
Chirag Sudarshan, Oliver Artner, Paul‐Philipp Manea, Sebastian Siegel, Susanne Hoffmann‐Eifert, Regina Dittmann, John Paul Strachan   +6 more
wiley   +1 more source

The poorest and hungry: Looking below the line [PDF]

Poverty reduction, Poverty dynamics, Hunger, Trends in global hunger, MDGs, Development assistance,
Ahmed, Akhter, Hill, Ruth Vargas, Wiesmann, Doris   +2 more
core  

Hunger Games

Acta Medica Philippina
Undernutrition among children has always been a major concern in the Philippines. According to the Philippine 2018- 2019 Expanded National Nutrition Survey (ENNS) reported in 2022, the prevalence of underweight among children less than five years old was 18.8% among males and 19.3% among females.
openaire   +2 more sources

Retinal Vessel Segmentation: A Comprehensive Review From Classical Methods to Deep Learning Advances (1982–2025)

Advanced Intelligent Systems, EarlyView.
Four decades of retinal vessel segmentation research (1982–2025) are synthesized, spanning classical image processing, machine learning, and deep learning paradigms. A meta‐analysis of 428 studies establishes a unified taxonomy and highlights performance trends, generalization capabilities, and clinical relevance.
Avinash Bansal, Jan Kubíček, Jana Bahrová, Alice Varyšová, Martin Augustýnek, Marek Penhaker, Juraj Timkovič   +6 more
wiley   +1 more source

Risk factors for food contamination among children discharged from community management of acute malnutrition programmes in South Sudan: A cross‐sectional study and hazard analysis critical control point approach

Maternal and Child Nutrition
Children under‐5 years of age are particularly vulnerable to severe acute malnutrition (SAM), and the risk factors associated with relapse to SAM are poorly understood.
Joseph Wells, David Gama Abugo, John Angong, Nancy Grace Lamwaka, Karin Gallandat, Jackson Lwate Hassan, Lino Deng, Dimple Save, Laura Braun, Mesfin Gose, Jacob Amanya, Khamisa Ayoub, Sarah King, Heather Stobaugh, Oliver Cumming, Lauren D'Mello‐Guyett   +15 more
doaj   +1 more source

AI‐Assisted IoT‐Enabled ECG Monitoring: Integrating Foundational and Generative AI Tools for Sustainable Smart Healthcare—Recent Trends

AI &Innovation, EarlyView.
ABSTRACT The rapid evolution of the Internet of Things (IoT) has significantly advanced the field of electrocardiogram (ECG) monitoring, enabling real‐time, remote, and patient‐centric cardiac care. This paper presents a comprehensive survey of AI assisted IoT‐based ECG monitoring systems, focusing on the integration of emerging technologies such as ...
Amrita Choudhury, Kandarpa Kumar Sarma, Lachit Dutta   +2 more
wiley   +1 more source