Results 111 to 120 of about 24,485,484 (328)

On the phenomenological modelling of physical phenomena [PDF]

Proceedings of the Estonian Academy of Sciences
Mathematical modelling of physical phenomena is based on the laws of physics, but for complicated processes, phenomenological models could enhance the descriptive and prescriptive power of the analysis.
Jüri Engelbrecht, Kert Tamm, Tanel Peets   +2 more
doaj   +1 more source

A comparison of corporate distress prediction models in Brazil: hybrid neural networks, logit models and discriminant analysis [PDF]

This paper looks at the ability of a relatively new technique, hybrid ANN's, to predict corporate distress in Brazil. These models are compared with traditional statistical techniques and conventional ANN models.
Heather Mitchell, Juliana Yim
core  

Feasibility and Tolerability of Performing Portable MRI for Neurological Disorders in an Outpatient Neurology Clinic: A Prospective Cohort

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Accessing brain magnetic resonance imaging (MRI) can be challenging, especially for underserved patients, which may lead to disparities in neurological diagnosis. Method This mixed‐methods study enrolled adults with one of four neurological disorders: mild cognitive impairment or dementia of the Alzheimer type, multiple sclerosis ...
Maya L. Mastick, Nomin Enkhtsetseg, Joseph Sadok, Matheus Mochetti, Annabel Sorby Adams, Jennifer Guo, Cristina Trapaga Hacker, Isabella Gomez Hjerthen, Seungwon Lee, Siddharth Satish, Andrew S. Ham, Justin Hill, Denis Balaban, Kevin Kyle, Rebecca L. Gillani, Marcelo Matiello, Aleksandar Videnovic, Eric C. Klawiter, W. Taylor Kimberly, Farrah J. Mateen   +19 more
wiley   +1 more source

A Survey of Traditional and Emerging Deep Learning Techniques for Non-Intrusive Load Monitoring

AI
To cope with the increasing global demand of energy and significant energy wastage caused by the use of different home appliances, smart load monitoring is considered a promising solution to promote proper activation and scheduling of devices and reduce ...
Annysha Huzzat, Ahmed S. Khwaja, Ali A. Alnoman, Bhagawat Adhikari, Alagan Anpalagan, Isaac Woungang   +5 more
doaj   +1 more source

Hybrid Models Combining EMD/EEMD and ARIMA for Long-Term Streamflow Forecasting

Water, 2018
: Long-term streamflow forecast is of great significance for water resource application and management. However, accurate monthly streamflow forecasting is challenging due to its non-stationarity and uncertainty.
Zhi-yu Wang, Jun Qiu, Fangfang Li
semanticscholar   +1 more source

Virtual or In‐Person: Does It Matter? Comparing Pain, Function, Quality of Life, Self‐Efficacy, and Physical Function Outcomes of Virtual, Hybrid, and In‐Person Education and Exercise Program Participants

Arthritis Care &Research, EarlyView.
Objective This study aimed to determine if program format (in‐person, virtual, or hybrid) results in differences in 3‐month outcomes of pain, function, quality of life, self‐efficacy, and chair stands in a hip/knee osteoarthritis‐management program. Methods A secondary analysis of the Good Life with osteoArthritis in Denmark (GLA:D) Canada database was
Jill Van Damme, Vanina Dal Bello‐Haas, Ayse Kuspinar, Patricia Strachan, Michael Zywiel, James Young, Rhona McGlasson, Lisa C. Carlesso   +7 more
wiley   +1 more source

A systematic review of the hybrid machine learning models for brain tumour segmentation and detection in medical images

Frontiers in Artificial Intelligence
Early and accurate detection of brain tumours using Magnetic Resonance Imaging (MRI) is critical for effective treatment and improved patient outcomes. This systematic review investigates the application of hybrid machine learning (ML) and deep learning (
Ndivhuwo Netshamutshedzi, Rendani Netshikweta, Jean-Claude Ndogmo, Ibidun Christiana Obagbuwa   +3 more
doaj   +1 more source

State of the Art of Machine Learning Models in Energy Systems, a Systematic Review

Energies, 2019
Machine learning (ML) models have been widely used in the modeling, design and prediction in energy systems. During the past two decades, there has been a dramatic increase in the advancement and application of various types of ML models for energy ...
Amir Mosavi, Mohsen Salimi, Sina Faizollahzadeh Ardabili, Timon Rabczuk, Shahaboddin Shamshirband, Annamaria R. Varkonyi-Koczy   +5 more
doaj   +1 more source

Trace Nickel Activated Biphasic Core‐CuOii/Shell‐CuOi Secondary Microspheres Enable Room Temperature Parts‐Per‐Trillion‐Level NO2 Detection

Advanced Engineering Materials, EarlyView.
An idea of designing novel sensors is proposed by creating appropriate Schottky barriers and vacancies between isomorphous Core‐CuOii/ Shell‐CuOi secondary microspheres and enhancing catalytic and spill‐over effects, and electronegativity via spontaneous biphasic separation, self‐assembly, and trace‐Ni‐doping.
Bala Ismail Adamu, Peipei Chen, Shafia Mukhtar Ibrahim, Mukhtar Lawan Adam, Attia Falak, Mokhotjwa Simon Dhlamini, Hanfu Wang, Lingxiang Jiang, Weiguo Chu   +8 more
wiley   +1 more source

Explainable AI for Brain Tumor Classification Using Cross-Gated Multi-Path Attention Fusion and Gate-Consistency Loss

IEEE Access
Accurate and early classification of brain tumors using magnetic resonance imaging (MRI) plays a vital role in guiding timely diagnosis and therapeutic intervention.
Ahmad Muhammad, Qi Jin, Muhammad Hammad Musaddiq, Mohammad Shuaib Mir, Mohannad Alkanan, Yonis Gulzar   +5 more
doaj   +1 more source