Predicting aggregate morphology of sequence-defined macromolecules with recurrent neural networks

D Bhattacharya, DC Kleeblatt, A Statt, WF Reinhart - Soft Matter, 2022 - pubs.rsc.org
Self-assembly of dilute sequence-defined macromolecules is a complex phenomenon in
which the local arrangement of chemical moieties can lead to the formation of long-range …

Predicting cost of defects for segmented products and customers using ensemble learning

G Sariyer, SK Mangla, Y Kazancoglu, L Xu… - Computers & Industrial …, 2022 - Elsevier
Due to technological advances, Big Data Analytics (BDA) has become increasingly
important over the last few years. This has led companies to evolve BDA capabilities (BDAC) …

An open source-based real-time data processing architecture framework for manufacturing sustainability

M Syafrudin, NL Fitriyani, D Li, G Alfian, J Rhee… - Sustainability, 2017 - mdpi.com
Currently, the manufacturing industry is experiencing a data-driven revolution. There are
multiple processes in the manufacturing industry and will eventually generate a large …

An integrated machine learning: Utility theory framework for real-time predictive maintenance in pumping systems

RM Khorsheed, OF Beyca - Proceedings of the Institution of …, 2021 - journals.sagepub.com
Bearings are the most widely used mechanical parts in rotating machinery under high load
and high rotational speeds. Operating continuously under such harsh conditions, wear and …

Computational statistics and machine learning techniques for effective decision making on student's employment for real-time

D Kumar, C Verma, PK Singh, MS Raboaca… - Mathematics, 2021 - mdpi.com
The present study accentuated a hybrid approach to evaluate the impact, association and
discrepancies of demographic characteristics on a student's job placement. The present …

An optimum tea fermentation detection model based on deep convolutional neural networks

G Kimutai, A Ngenzi, RN Said, A Kiprop, A Förster - Data, 2020 - mdpi.com
Tea is one of the most popular beverages in the world, and its processing involves a number
of steps which includes fermentation. Tea fermentation is the most important step in …

Combined transfer and active learning for high accuracy music genre classification method

C Chen, X Steven - 2021 IEEE 2nd international conference on …, 2021 - ieeexplore.ieee.org
Music genre classification system has been widely used by commercial music apps or
professional music systems. At the same time, the growing complexity of genres and the …

Prediction of fatigue crack damage using in-situ scanning electron microscopy and machine learning

J Zhou, Y Zhang, N Wang, W Gao, L Tang… - International Journal of …, 2025 - Elsevier
Nickel-based single crystal superalloys, as engine blade materials, are prone to fatigue
damage due to repeated startups and shutdowns. Therefore, monitoring and quantitatively …

Assessment of Porosity Defects in Ingot Using Machine Learning Methods during Electro Slag Remelting Process

G Zhang, Y Hu, D Hou, D Yang, Q Zhang, Y Hu, X Liu - Metals, 2022 - mdpi.com
The porosity defects in the ingot, which are caused by moisture absorption in slag during the
electroslag remelting process, deserve the researcher's attention in the summer wet season …

(SDGFI) Student's Demographic and Geographic Feature Identification Using Machine Learning Techniques for Real-Time Automated Web Applications

C Verma, Z Illés, D Kumar - Mathematics, 2022 - mdpi.com
Nowadays, Google Forms is becoming a cutting-edge tool for gathering research data in the
educational domain. Several researchers are using real-time web applications to collect the …