Optimizing machine learning algorithms for improving prediction of bridge deck deterioration: A case study of Ohio bridges

A Rashidi Nasab, H Elzarka - Buildings, 2023 - mdpi.com
The deterioration of a bridge's deck endangers its safety and serviceability. Ohio has
approximately 45,000 bridges that need to be monitored to ensure their structural integrity …

Machine learning in precision agriculture: a survey on trends, applications and evaluations over two decades

S Condran, M Bewong, MZ Islam, L Maphosa… - IEEE …, 2022 - ieeexplore.ieee.org
Precision agriculture represents the new age of conventional agriculture. This is made
possible by the advancement of various modern technologies such as the internet of things …

Bridge infrastructure asset management system: Comparative computational machine learning approach for evaluating and predicting deck deterioration conditions

R Assaad, IH El-Adaway - Journal of Infrastructure Systems, 2020 - ascelibrary.org
Bridge infrastructure asset management system is a prevailing approach toward having an
effective and efficient procedure for monitoring bridges through their different development …

Synthetic Minority Over-sampling TEchnique (SMOTE) and Logistic Model Tree (LMT)-Adaptive Boosting algorithms for classifying imbalanced datasets of nutrient and …

AD Amirruddin, FM Muharam, MH Ismail… - … and Electronics in …, 2022 - Elsevier
The conventional method to quantify leaf biochemical properties (nutrients and chlorophylls)
is tedious, labour-intensive, and impractical for vast oil palm plantation areas. Spectral …

Automated identification of substantial changes in construction projects of airport improvement program: Machine learning and natural language processing …

R Khalef, IH El-adaway - Journal of management in engineering, 2021 - ascelibrary.org
Contractual changes—mainly substantial changes—within airport improvement program
(AIP) projects represent a critical risk that could result in severe negative time and cost …

SMOTE-CD: SMOTE for compositional data

T Nguyen, K Mengersen, D Sous, B Liquet - Plos one, 2023 - journals.plos.org
Compositional data are a special kind of data, represented as a proportion carrying relative
information. Although this type of data is widely spread, no solution exists to deal with the …

Mathematical modeling of BCG-based bladder cancer treatment using socio-demographics

E Savchenko, A Rosenfeld… - Scientific Reports, 2023 - nature.com
Cancer is one of the most widespread diseases around the world with millions of new
patients each year. Bladder cancer is one of the most prevalent types of cancer affecting all …

Convolutional neural networks and temporal CNNs for COVID-19 forecasting in France

L Mohimont, A Chemchem, F Alin, M Krajecki… - Applied …, 2021 - Springer
This paper focus on multiple CNN-based (Convolutional Neural Network) models for COVID-
19 forecast developed by our research team during the first French lockdown. In an effort to …

Rapid measurement of classification levels of primary macronutrients in durian (Durio zibethinus Murray CV. Mon Thong) leaves using FT-NIR spectrometer and …

T Phanomsophon, N Jaisue, A Worphet, N Tawinteung… - Measurement, 2022 - Elsevier
For durian growth to produce high-quality fruit, plants should receive sufficient nutrients.
Currently, farmers apply various fertilisers to produce a large quantity and quality of durian …

Assessment of soybean lodging using UAV imagery and machine learning

S Sarkar, J Zhou, A Scaboo, J Zhou, N Aloysius, TT Lim - Plants, 2023 - mdpi.com
Plant lodging is one of the most essential phenotypes for soybean breeding programs.
Soybean lodging is conventionally evaluated visually by breeders, which is time-consuming …