Results 81 to 90 of about 346,286 (280)

Information Dense and Industry Scalable Accelerated Formation

Advanced Intelligent Discovery, EarlyView.
Pulsed formation can reduce lithium‐ion battery formation time by over 50% while maintaining or enhancing performance. Validated on 25 Ah prismatic cells, this industry‐scalable method yields thinner, more homogeneous solid electrolyte interphases (SEIs).
Leon Merker, Markus Blessing, Bojing Zhang, Helge Sören Stein   +3 more
wiley   +1 more source

A Solution for Exosome‐Based Analysis: Surface‐Enhanced Raman Spectroscopy and Artificial Intelligence

Advanced Intelligent Discovery, EarlyView.
Exosomes are emerging as powerful biomarkers for disease diagnosis and monitoring. This review highlights the integration of surface‐enhanced Raman spectroscopy with artificial intelligence to enhance molecular fingerprinting of exosomes. Machine learning and deep learning techniques improve spectral interpretation, enabling accurate classification of ...
Munevver Akdeniz, Zakarya Al‐Shaebi, Omer Aydin   +2 more
wiley   +1 more source

Analyzing students' academic performance using educational data mining

Computers and Education: Artificial Intelligence
Educational Data Mining (EDM) is the process of extracting useful information and knowledge from educational data. EDM identifies patterns and trends from educational data, which can be used to improve academic curriculum, teaching and assessment methods,
Sazol Sarker, Mahit Kumar Paul, Sheikh Tasnimul Hasan Thasin, Md. Al Mehedi Hasan   +3 more
doaj   +1 more source

Data Mining Applications in Higher Education and Academic Intelligence Management [PDF]

Higher education institutions are nucleus of research and future development acting in a competitive environment, with the prerequisite mission to generate, accumulate and share knowledge.
Bresfelean, Vasile Paul
core   +1 more source

opXRD: Open Experimental Powder X‐Ray Diffraction Database

Advanced Intelligent Discovery, EarlyView.
We introduce the Open Experimental Powder X‐ray Diffraction Database, the largest openly accessible collection of experimental powder diffractograms, comprising over 92,000 patterns collected across diverse material classes and experimental setups. Our ongoing effort aims to guide machine learning research toward fully automated analysis of pXRD data ...
Daniel Hollarek, Henrik Schopmans, Jona Östreicher, Jonas Teufel, Bin Cao, Adie Alwen, Simon Schweidler, Mriganka Singh, Tim Kodalle, Hanlin Hu, Gregoire Heymans, Maged Abdelsamie, Arthur Hardiagon, Alexander Wieczorek, Siarhei Zhuk, Ruth Schwaiger, Sebastian Siol, François‐Xavier Coudert, Moritz Wolf, Carolin M. Sutter‐Fella, Ben Breitung, Andrea M. Hodge, Tong‐yi Zhang, Pascal Friederich   +23 more
wiley   +1 more source

Educational Data Mining for Personalized Learning: A Sentiment Analysis and Process Control Perspective

Proceedings
Context: Educational data mining (EDM) is a growing field that utilizes machine learning, statistics, and data mining to analyze data from educational settings [...]
Sourav Sahu, Neelamadhab Padhy, Satyam Mohapatra, Amrutansu Patra, Anurag Kumar, Rajiv Kumar Choudhary   +5 more
doaj   +1 more source

Comparing Different Resampling Methods in Predicting Students’ Performance Using Machine Learning Techniques

IEEE Access, 2020
In today's world, due to the advancement of technology, predicting the students' performance is among the most beneficial and essential research topics.
Ramin Ghorbani, Rouzbeh Ghousi
doaj   +1 more source

Experiences and opportunities in teaching ukrainian students at the faculty of mining and geoengineering in AGH University of Science and Technology [PDF]

, 2018
The paper presents the influence of various factors on the process of internationalisation of higher education in Poland, and particularly in AGH University of Science and Technology from the perspective of the Faculty of Mining and ...
Borowski, M., Сala, M.
core  

A Machine Learning Perspective on the Brønsted–Evans–Polanyi Relation in Water‐Gas Shift Catalysis on MXenes

Advanced Intelligent Discovery, EarlyView.
Machine learning predicts activation energies for key steps in the water‐gas shift reaction on 92 MXenes. Random Forest is identified as the most accurate model. Reaction energy and reactant LogP emerge as key descriptors. The approach provides a predictive framework for catalyst design, grounded in density functional theory data and validated through ...
Kais Iben Nassar, Tiago L. P. Galvão, José D. Gouveia, José R. B. Gomes   +3 more
wiley   +1 more source

Sequence Modelling For Analysing Student Interaction with Educational Systems

, 2017
The analysis of log data generated by online educational systems is an important task for improving the systems, and furthering our knowledge of how students learn.
Alstrup, Stephen, Hansen, Casper, Hansen, Christian, Hjuler, Niklas, Lioma, Christina   +4 more
core