Academic Articles & Research Papers

Machine learning and data-driven prediction of pore pressure from geophysical logs: A case study for the Mangahewa gas field, New Zealand

Pore pressure is an essential parameter for establishing reservoir conditions, geological interpretation and drilling programs. Pore pressure prediction depends on information from various geophysical logs, seismic, and direct down-hole pre...

Prospective assessment of intraoperative renal perfusion with transit time flow measurements (TTFM) in deceased and living donor kidney transplantation.

Machine learning insight in quality control and maintenance management of drilling mud pumps

Abstract This study proposes a machine learning-based framework for predictive maintenance and quality control of drilling mud pumps, targeting critical operational challenges such as equipment failure, downtime, and high maintenance costs....

Individual-Tree DBH Estimation from Airborne LiDAR Data Using MSFS–XGBoost

Diameter at breast height (DBH) is a fundamental structural parameter for forest inventory and ecological analysis. However, field-based measurements (e.g., diameter tape surveys) are labor-intensive and inefficient for large-scale applicat...

Bayesian machine learning-based method for prediction of slope failure time

The data-driven phenomenological models based on deformation measurements have been widely utilized to predict the slope failure time (SFT). The observational and model uncertainties could lead the predicted SFT calculated from the phenomen...

Human behavior analysis on political retweets using machine learning algorithms

The exponential rise in the use of social media has resulted in a massive increase in the volume of unstructured text created. This content is presented through messages, conversations, postings, and blogs. Microblogging has become a popula...

Empirical Asset Pricing via Machine Learning

We perform a comparative analysis of machine learning methods for the canonical problem of empirical asset pricing: measuring asset risk premia.We demonstrate large economic gains to investors using machine learning forecasts, in some cases...

Generative-Adversarial-Network-Based Image Reconstruction for the Capacitively Coupled Electrical Impedance Tomography of Stroke

This study investigated the potential of machine-learning-based stroke image reconstruction in capacitively coupled electrical impedance tomography. The quality of brain images reconstructed using the adversarial neural network (cGAN) was e...

Hybrid-Timescale Physics-Informed Neural Network for Electrical Equivalent Impedance Identification in Induction Heating Systems

This article introduces a hybrid variant of a physics-informed neural network (PINN) that is designed to effectively capture both the rapid dynamics of electrical variables and the slower dynamics of state parameters in a domestic induction...

Machine learning in pain research

1. Introduction Pain and pain chronification are incompletely understood and unresolved medical problems that continue to have a high prevalence.14 It has been accepted that pain is a complex phenomenon.2,32,72 Contemporary methods of compu...

Machine-learning reprogrammable metasurface imager

Conventional microwave imagers usually require either time-consuming data acquisition, or complicated reconstruction algorithms for data post-processing, making them largely ineffective for complex in-situ sensing and monitoring. Here, we e...

Fatigue Monitoring Through Wearables: A State-of-the-Art Review

The objective measurement of fatigue is of critical relevance in areas such as occupational health and safety as fatigue impairs cognitive and motor performance, thus reducing productivity and increasing the risk of injury. Wearable systems...

MATCHA, a novel regional hydroclimate-chemical reanalysis: System description and evaluation

We present MATCHA (Model for Atmospheric Transport and Chemistry in Asia), a 17-year (2003–2019) regional hydroclimate-chemical reanalysis for Asia (58–140° E, 4– 40° N) at 12 km resolution. MATCHA couples the Weather Research and Forecasti...

Towards a physics informed digital twin to predict cerebral blood flow and cerebral vascular regulation

Abstract Cerebral blood flow is essential for brain function and is governed by cerebral perfusion pressure and physiological mechanisms collectively referred to as cerebral vascular regulation (CVR). Direct measurement of cerebral blood fl...

Applications of Machine Learning in Cancer Prediction and Prognosis

Machine learning is a branch of artificial intelligence that employs a variety of statistical, probabilistic and optimization techniques that allows computers to "learn" from past examples and to detect hard-to-discern patterns from large, ...

Machine learning for combustion

Combustion science is an interdisciplinary study that involves nonlinear physical and chemical phenomena in time and length scales, including complex chemical reactions and fluid flows. Combustion widely supplies energy for powering vehicle...

Computer Vision-Based Assessment of Motor Functioning in Schizophrenia: Use of Smartphones for Remote Measurement of Schizophrenia Symptomatology

Introduction: Motor abnormalities have been shown to be a distinct component of schizophrenia symptomatology. However, objective and scalable methods for assessment of motor functioning in schizophrenia are lacking. Advancements in machine ...

Machine Learning for Fluid Mechanics

The field of fluid mechanics is rapidly advancing, driven by unprecedented volumes of data from experiments, field measurements, and large-scale simulations at multiple spatiotemporal scales. Machine learning (ML) offers a wealth of techniq...

Enhancing host-pathogen phenotyping dynamics: early detection of tomato bacterial diseases using hyperspectral point measurement and predictive modeling

Early diagnosis of plant diseases is needed to promote sustainable plant protection strategies. Applied predictive modeling over hyperspectral spectroscopy (HS) data can be an effective, fast, cost-effective approach for improving plant dis...

Design and Pilot Feasibility of a Low-Cost Wearable for Mexican Sign Language in Inclusive Higher Education

A substantial number of students with hearing impairments are enrolled in higher education, motivating the development of inclusive assistive technologies that reduce communication barriers. This study developed and evaluated a prototype el...