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Deep neural network-based prediction of tsunami wave attenuation by mangrove forests

Didit Adytia, Dede Tarwidi, Deni Saepudin, Semeidi Husrin et al. • MethodsX (2024)

The goal of this research is to develop a model employing deep neural networks (DNNs) to predict the effectiveness of mangrove forests in attenuating the impact of tsunami waves. The dataset for the DNN model is obtained by simulating tsuna...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.mex.2024.102791

Convolutional Neural Network Based Approval Prediction of Enhancement Reports

Jun Cheng, Mazhar Sadiq, Olga A. Kalugina, Sadeem Ahmad Nafees et al. • IEEE Access (2021)

For a given software enhancement report, identifying its possible approval status could help software developers by suggesting feature enhancements to compete in the software industry. An automatic solution for the approval prediction of en...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2021.3108624

A new system for assessment of growth using mandibular canine calcification stages and its correlation with modified MP3 stages

Gautham Hegde, Nanditha Hegde, Anil Kumar, Keshavaraj • Journal of Pharmacy and Bioallied Sciences (2014)

Objective: Orthodontic diagnosis and treatment planning for growing children must involve growth prediction, especially in the treatment of skeletal problems. Studies have shown that a strong association exists between skeletal maturity and...

DOAJ Open Access (DOAJ) DOI: 10.4103/0975-7406.137389

Comparing Large-Eddy Simulation and Gaussian Plume Model to Sensor Measurements of an Urban Smoke Plume

Dominic Clements, Matthew Coburn, Simon J. Cox, Florentin M. J. Bulot et al. • Atmosphere (2024)

The fast prediction of the extent and impact of accidental air pollution releases is important to enable a quick and informed response, especially in cities. Despite this importance, only a small number of case studies are available studyin...

DOAJ Open Access (DOAJ) DOI: 10.3390/atmos15091089