Results 131 to 140 of about 354,413 (309)

AN APPLICATION OF NON-LINEAR PROGRAMMING TO TRAIN RECURRENT NEURAL NETWORKS IN TIME SERIES PREDICTION PROBLEMS

, 2005
M. P. Cuéllar, Miguel Delgado‐Rodríguez, M.C. Pegalajar   +2 more
openalex   +1 more source

Comparing the Effect of Semi‐Immersive Virtual Reality, Computerized Cognitive Training, and Traditional Rehabilitation on Cognitive Function in Multiple Sclerosis: A Randomized Clinical Trial

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Cognitive impairment is a common non‐motor symptom in Multiple Sclerosis (MS), negatively affecting autonomy and Quality of Life (QoL). Innovative rehabilitation strategies, such as semi‐immersive virtual reality (VR) and computerized cognitive training (CCT), may offer advantages over traditional cognitive rehabilitation (TCR ...
Maria Grazia Maggio, Desiree Latella, Lilla Bonanno, Paulo Cezar Rocha dos Santos, Marcos Maldonado‐Díaz, Meir Plotnik, Rosaria De Luca, Angelo Quartarone, Rocco Salvatore Calabrò   +8 more
wiley   +1 more source

Simplified Gating in Long Short-term Memory (LSTM) Recurrent Neural Networks [PDF]

, 2017
Yuzhen Lu, Fathi M. Salem
openalex   +1 more source

Artificial Intelligence in Systemic Sclerosis: Clinical applications, challenges, and future directions

Arthritis Care &Research, Accepted Article.
Systemic sclerosis (SSc) is a rare autoimmune disease defined by immune dysregulation, vasculopathy, and progressive fibrosis of the skin and internal organs. Despite advances in care, major complications such as interstitial lung disease (ILD) and myocardial involvement remain the leading causes of morbidity and mortality.
Cristiana Sieiro Santos, José Miguel Sequí‐Sabater, Diego Benavent   +2 more
wiley   +1 more source

Design of Kids-specific URL Classifier using Recurrent Convolutional Neural Network

, 2020
R. Rajalakshmi, Hans Tiwari, Jay Patel, Ankit Kumar, R. Karthik   +4 more
openalex   +1 more source

Deep Diabetologist: Learning to Prescribe Hyperglycemia Medications with Hierarchical Recurrent Neural Networks [PDF]

, 2018
Jing Mei, Shiwan Zhao, Feng Jin, Eryu Xia, Haifeng Liu, Xiang Li   +5 more
openalex   +1 more source

Harnessing Fungal Biowelding for Constructing Mycelium‐Engineered Materials

Advanced Engineering Materials, EarlyView.
Mycelium‐bound composites (MBCs) offer low‐carbon alternatives for construction, yet interfacial bonding remains a critical challenge. This review examines fungal biowelding as a biocompatible adhesive, elucidating mycelium‐mediated interfacial mechanisms and their role in material assembly. Strategies to optimize biowelding are discussed, highlighting
Xue Brenda Bai, Xinrui Sarah Niu, Zhao Qin   +2 more
wiley   +1 more source

Online Predicting Conformance of Business Process with Recurrent Neural Networks

, 2020
Jiaojiao Wang, Dingguo Yu, Xiaoyu Ma, Chang Liu, Victor Chang, Xuewen Shen   +5 more
openalex   +1 more source

Packaging of Macroscopic Material Payloads: Needs, Challenges, Concepts, and Future Directions

Advanced Engineering Materials, EarlyView.
This review introduces a unified framework that decomposes any macroscopic packaging system into the payload, packaging material, and packaging strategy and combines them into a conceptual packaging equation: packaging strategy = payload + packaging material.
Venkata S. R. Jampani, Manos Anyfantakis
wiley   +1 more source

Prediction of Surface Topography Parameters in Direct Laser Interference Patterning of Stainless Steel Using Infrared Monitoring and Convolutional Neural Networks

Advanced Engineering Materials, EarlyView.
This study presents an infrared monitoring approach for direct laser interference patterning (DLIP) combined with a convolutional neural network (CNN). Thermal emission data captured during structuring are used to predict surface topography parameters.
Lukas Olawsky, Marcelo Sallese, Leander Kläber, Clemens Kuhn, Keming Du, Andrés Fabián Lasagni   +5 more
wiley   +1 more source