Business email compromise phishing detection based on machine learning: a systematic literature review

HF Atlam, O Oluwatimilehin - Electronics, 2022 - mdpi.com
The risk of cyberattacks against businesses has risen considerably, with Business Email
Compromise (BEC) schemes taking the lead as one of the most common phishing attack …

On the performance of deep transfer learning networks for brain tumor detection using MR images

S Ahmad, PK Choudhury - IEEE Access, 2022 - ieeexplore.ieee.org
A brain tumor need to be identified in its early stage, otherwise it may cause severe
condition that cannot be cured once it is progressed. A precise diagnosis of brain tumor can …

Combining machine learning and metal–organic frameworks research: Novel modeling, performance prediction, and materials discovery

C Li, L Bao, Y Ji, Z Tian, M Cui, Y Shi, Z Zhao… - Coordination Chemistry …, 2024 - Elsevier
Abstract Machine learning (ML) is the science of making computers learn and behave like
humans, autonomously improving their learning by providing them with data and information …

Surrogate modeling of nonlinear dynamic systems: a comparative study

Y Zhao, C Jiang, MA Vega… - … of Computing and …, 2023 - asmedigitalcollection.asme.org
Surrogate models play a vital role in overcoming the computational challenge in designing
and analyzing nonlinear dynamic systems, especially in the presence of uncertainty. This …

Quantifying plant species α-diversity using normalized difference vegetation index and climate data in alpine grasslands

Y Tian, G Fu - Remote Sensing, 2022 - mdpi.com
Quantitative plant species α-diversity of grasslands at multiple spatial and temporal scales is
important for investigating the responses of biodiversity to global change and protecting …

Design of comprehensive evaluation index system for P2P credit risk of “three rural” borrowers

C Rao, H Lin, M Liu - Soft Computing, 2020 - Springer
In the emerging peer-to-peer (P2P) lending industry, risks such as credit risk and default risk
will bring huge losses to online lending platforms and investors. Therefore, it is necessary to …

Double verification and quantitative traceability: A solution for mixed mine water sources

Y Zeng, A Mei, Q Wu, S Meng, D Zhao, Z Hua - Journal of Hydrology, 2024 - Elsevier
Accurate identification of mine water sources is one of the keys to safe coal mining.
However, conventional water source identification methods rely on groundwater-level …

Global estimates of 500 m daily aerodynamic roughness length from MODIS data

Z Peng, R Tang, Y Jiang, M Liu, ZL Li - ISPRS Journal of Photogrammetry …, 2022 - Elsevier
Aerodynamic roughness length (z 0 m) is a key parameter in the characterization of land
surface turbulent heat fluxes and widely used in many surface and climate-related process …

A comparative study on contemporary intrusion detection datasets for machine learning research

S Dwibedi, M Pujari, W Sun - 2020 IEEE International …, 2020 - ieeexplore.ieee.org
In the modern world, Machine Learning (ML) touches our day-to-day routine in various ways.
Researchers have been actively working on adding intelligence to Intrusion Detection …

Prediction of fundraising outcomes for crowdfunding projects based on deep learning: a multimodel comparative study

W Wang, H Zheng, YJ Wu - Soft Computing, 2020 - Springer
As a new financing model, crowdfunding has been developed rapidly in recent years and
has attracted the attention of investors and small-and medium-sized enterprises and …