Results 51 to 60 of about 14,128,135 (294)

Digital Cognitive Phenotyping for Differential Diagnosis and Monitoring in Neurological Conditions

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To assess the utility, accessibility, and equivalence to supervised scales of online cognitive assessment in older individuals with cognitive impairment. Methods Patients with Alzheimer's disease (AD, n = 31), idiopathic normal pressure hydrocephalus (iNPH, n = 26), and traumatic brain injury (TBI, n = 23) completed online cognitive ...
Martina Del Giovane, Valentina Giunchiglia, Michael C. B. David, Magdalena A. Kolanko, William R. Trender, Peter J. Hellyer, Harmeena Kaur, David J. Sharp, Christopher Carswell, Paresh A. Malhotra, Adam Hampshire   +10 more
wiley   +1 more source

Smoking cessation advice from healthcare professionals helps those in the contemplation and preparation stage: An application with transtheoretical model underpinning in a community-based program

Tobacco Induced Diseases, 2020
Introduction The efficacy of smoking cessation intervention has been proven with randomized controlled trials. Our study aims to elucidate the effects of the delivery method of smoking cessation advice on the process of stage of changes with ...
Pallop Siewchaisakul, Dih-Ling Luh, Sherry Y. H. Chiu, Amy M. F. Yen, Chih-Dao Chen, Hsiu-Hsi Chen   +5 more
doaj   +1 more source

Design and Practical Implementation of a New Markov Model Predictive Controller for Variable Communication Packet Loss in Network Control Systems [PDF]

Iranian Journal of Oil & Gas Science and Technology, 2016
The current paper investigates the influence of packet losses in network control systems (NCS’s) using the model predictive control (MPC) strategy. The study focuses on two main network packet losses due to sensor to controller and controller to actuator
Karim Salahshoor, Babak Roshanipour, Iman Karimi   +2 more
doaj   +1 more source

Logical Hidden Markov Models

Journal of Artificial Intelligence Research, 2006
Logical hidden Markov models (LOHMMs) upgrade traditional hidden Markov models to deal with sequences of structured symbols in the form of logical atoms, rather than flat characters. This note formally introduces LOHMMs and presents solutions to the three central inference problems for LOHMMs: evaluation, most likely hidden state sequence and ...
Kersting, K., De Raedt, Luc, Raiko, T.
openaire   +3 more sources

Observer‐Based Adaptive Event‐Triggered Tracking Control for Fuzzy TS Systems With Premise Mismatch

International Journal of Adaptive Control and Signal Processing, EarlyView.
This paper presents an adaptive logistic event‐triggered observer‐based tracking controller for Takagi‐Sugeno fuzzy systems under constrained inputs and network delays. Leveraging a hybrid LMI and Secretary Bird Optimization approach, this strategy significantly minimizes communication overhead and computational burden while ensuring optimal reference ...
Oussama Djadane, Salama Makni, Mourad Kchaou, Ahmed El Hajjaji   +3 more
wiley   +1 more source

Cost Effectiveness of Emollients in the Prevention of Relapses in Atopic Dermatitis

Clinical, Cosmetic and Investigational Dermatology, 2020
Elise Cabout,1 Sebastien Eymere,1 Robert Launois,1 Flavia Aslanian,2 Charles Taïeb,3,4 Sophie Seité5 1Réseau d’évaluation en Économie de la Santé (REES), Paris, France; 2Epsom and St Helier University ...
Cabout E, Eymere S, Launois R, Aslanian F, Taïeb C, Seité S   +5 more
doaj  

Fostering Innovation: Streamlining Magnetocaloric Materials Research by Digitalization

Advanced Engineering Materials, EarlyView.
Magnetocaloric cooling (MCE) is an environmentally friendly refrigeration method with great potential. Optimizing MCE materials involves the preparation and screening of large quantities of samples, which in turn generates a large amount of data. A digitalization approach is presented that uses ontologies, knowledge graphs, and digital workflows to ...
Simon Bekemeier, Moritz Blum, Luana Caron, Alisa Chirkova, Philipp Cimiano, Basil Ell, Inga Ennen, Michael Feige, Maik Gaerner, Thomas Hilbig, Andreas Hütten, Günter Reiss, Tapas Samanta, Sonja Schöning, Christian Schröder, Lennart Schwan, Chris Taake, Martin Wortmann   +17 more
wiley   +1 more source

Leveraging Symbolic Artificial Intelligence and Fuzzy Logic for Materials Science: A Review of Methods, Challenges, and Applications to Scarce and Imperfect Experimental Data

Advanced Engineering Materials, EarlyView.
This article explores the transformative potential of symbolic artificial intelligence (AI) in the field of materials science, particularly in leveraging experimental data. The article presents several symbolic AI models and discusses their applications in materials science.
Ahmed Amrani, Mohamed‐Ali Belloum, Laurence Boudet, Valentin Fouillard, Edwin Friedmann, Guillaume Lacharme, Ali Mahmoud, Jean‐Philippe Poli   +7 more
wiley   +1 more source

Designing Vanadium‐Based Oxide Electrocatalysts for Water Splitting: Experimental and Mechanistic Insights with Machine Learning

Advanced Functional Materials, EarlyView.
This review establishes structure‐property‐mechanism relationships across six modification strategies for V‐based oxide water‐splitting electrocatalysts: lattice engineering, heteroatom doping, interface engineering, carbon‐based hybridization, morphology engineering, and surface reconstruction and pre‐catalyst design, where dissolution is reframed as ...
Youness El Issmaeli, Amina Lahrichi, Hoje Chun, Rafael Gómez‐Bombarelli, Bruno G. Pollet   +4 more
wiley   +1 more source

Evaluation of Machinery Readiness Using Semi-Markov Processes

Applied Sciences, 2020
This article uses Markov and semi-Markov models as some of the most popular tools to estimate readiness and reliability. They allow to evaluate of both individual elements as well as entire systems—including production systems—as multi-state ...
Andrzej Świderski, Anna Borucka, Małgorzata Grzelak, Leszek Gil   +3 more
doaj   +1 more source