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Now showing items 81-90 of 90
Audio-Based Drone Detection and Identification Using Deep Learning Techniques with Dataset Enhancement through Generative Adversarial Networks
(
MDPI
, 2021 , Article)
Drones are becoming increasingly popular not only for recreational purposes but in day-to-day applications in engineering, medicine, logistics, security and others. In addition to their useful applications, an alarming ...
Exploration and analysis of On-Surface and In-Air handwriting attributes to improve dysgraphia disorder diagnosis in children based on machine learning methods
(
Elsevier
, 2023 , Article)
Dysgraphia is a type of learning disorder that affects children’s writing skills. Poor writing skills can obstruct students’ academic growth if it is undiagnosed and untreated properly in the early stages. The irregularity ...
Revolutionizing chronic lymphocytic leukemia diagnosis: A deep dive into the diverse applications of machine learning
(
Elsevier
, 2023 , Article)
Chronic lymphocytic leukemia (CLL) is a B cell neoplasm characterized by the accumulation of aberrant monoclonal B lymphocytes. CLL is the predominant type of leukemia in Western countries, accounting for 25% of cases. ...
Machine learning techniques for the identification of risk factors associated with food insecurity among adults in Arab countries during the COVID-19 pandemic
(
Springer Nature
, 2023 , Article)
Background: A direct consequence of global warming, and strongly correlated with poor physical and mental health, food insecurity is a rising global concern associated with low dietary intake. The Coronavirus pandemic has ...
A machine learning-based optimization approach for pre-copy live virtual machine migration
(
Springer
, 2023 , Article)
Organizations widely use cloud computing to outsource their computing needs. One crucial issue of cloud computing is that services must be available to clients at all times. However, the cloud services may be temporarily ...
Performance of artificial intelligence models in estimating blood glucose level among diabetic patients using non-invasive wearable device data
(
Elsevier
, 2023 , Article)
Introduction: Diabetes Mellitus (DM) is characterized by impaired ability to metabolize glucose for use in cells for energy, resulting in high blood sugar (hyperglycemia). DM impacted 463 million individuals worldwide in ...
Development of a stacked machine learning model to compute the capability of ZnO-based sensors for hydrogen detection
(
Elsevier
, 2024 , Article)
Zinc oxide (ZnO) nanocomposite sensors decorated with various dopants are popular tools for detecting even low hydrogen (H2) concentrations. The nanocomposite's chemistry, temperature, and H2 concentration impact the success ...
Performance evaluation of time-frequency image feature sets for improved classification and analysis of non-stationary signals: Application to newborn EEG seizure detection
(
Elsevier B.V.
, 2017 , Article)
This study demonstrates that a time-frequency (TF) image pattern recognition approach offers significant advantages over standard signal classification methods that use t-domain only or f-domain only features. Two approaches ...
Enhancing vulnerability assessment through spatially explicit modeling of mountain social-ecological systems exposed to multiple environmental hazards
(
Elsevier
, 2024 , Article)
The evaluation of the vulnerability of coupled socio-ecological systems is critical for addressing and preventing the adverse impacts of various environmental hazards and devising strategies for climate change adaptation. ...
Analysis of mode choice affects from the introduction of Doha Metro using machine learning and statistical analysis
(
Elsevier
, 2023 , Article)
The aim of this study was to investigate the possible influences of the operation of the new Doha Metro on the travel mode choice behavior in Doha City, Qatar. Revealed preference (RP) and stated preference (SP) survey ...