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Conceptualization of Artificial Intelligence in Airway Management
(
Hamad bin Khalifa University Press (HBKU Press)
, 2022 , Article)
Background: Failed intubation is the single most important cause of patient morbidity and mortality during anesthesia for surgery. The incidence of difficult intubation could be as high as 12% while failed intubation is ...
Structural Damage Detection in Civil Engineering with Machine Learning: Current State of the Art
(
Springer
, 2022 , Conference Paper)
This paper presents a brief overview of vibration-based structural damage detection studies that are based on machine learning (ML) in civil engineering structures. The review includes both parametric and nonparametric ...
Detecting anomalies within smart buildings using do-it-yourself internet of things
(
Springer
, 2022 , Article)
Detecting anomalies at the time of happening is vital in environments like buildings and homes to identify potential cyber-attacks. This paper discussed the various mechanisms to detect anomalies as soon as they occur. We ...
Generative Adversarial Network Approach to Future Sermonizing of Housing Dispersal in Emerging Cities
(
American Society of Civil Engineers (ASCE)
, 2022 , Article)
This study aims to visualize the future housing dispersal of expatriates, based on the predicted urban growth in emerging cities. Generalized adversarial networks (GANs) will be utilized to predict the future urban growth ...
ML-Based Handover Prediction and AP Selection in Cognitive Wi-Fi Networks
(
Springer
, 2022 , Article)
Device mobility in dense Wi-Fi networks offers several challenges. Two well-known problems related to device mobility are handover prediction and access point selection. Due to the complex nature of the radio environment, ...
Machine learning and discriminant function analysis in the formulation of generic models for sex prediction using patella measurements
(
Springer Nature
, 2022 , Article)
Sex prediction from bone measurements that display sexual dimorphism is one of the most important aspects of forensic anthropology. Some bones like the skull and pelvis display distinct morphological traits that are based ...
Shear capacity prediction of FRP-RC beams using single and ensenble ExPlainable Machine learning models
(
Elsevier
, 2022 , Article)
Corrosion in steel reinforcement is a central issue behind the severe deterioration of existing reinforced concrete (RC) structures. Nowadays, fiber-reinforced polymer (FRP) is increasingly being used as a viable alternative ...
Explainable machine learning model and reliability analysis for flexural capacity prediction of RC beams strengthened in flexure with FRCM
(
Elsevier
, 2022 , Article)
This paper presents a data-driven approach to determine the load and flexural capacities of reinforced concrete (RC) beams strengthened with fabric reinforced cementitious matrix (FRCM) composites in flexure. A total of ...
FAI: Fast, accurate, and intelligent approach and prediction tool for flexural capacity of FRP-RC beams based on super-learner machine learning model
(
Elsevier
, 2022 , Article)
Fiber-reinforced polymer (FRP) composites have recently been considered in the field of structural engineering as one of the best alternatives to conventional steel reinforcement due to their high tensile strength, ...
Machine learning-based shear capacity prediction and reliability analysis of shear-critical RC beams strengthened with inorganic composites
(
Elsevier
, 2022 , Article)
The application of inorganic composites has proven to be an effective strengthening technique for shear-critical reinforced concrete (RC) beams. However, accurate prediction of the shear capacity of RC beams strengthened ...