Results 151 to 160 of about 605,297 (308)
Machine Learning‐Driven Variability Analysis of Process Parameters for Semiconductor Manufacturing
This research presents a machine learning approach that integrates nonlinear variation decomposition (NLVD) with statistical techniques to quantify the contribution of individual unit processes to performance and variance of figure of merit (FoM) at the LOT level.
Sinyeong Kang +6 more
wiley +1 more source
What causes differences in achievement in Zimbabwe's secondary schools? [PDF]
The authors found that students who attended high-fee-paying (trust) schools, elite urban governments schools, and mission schools scored better in mathematics and English achievement than did students in the less-well-endowed government schools and ...
Nyagura, Levi Martin +1 more
core
Improving classroom assessment in primary mathematics education
The main goal of this PhD research was to provide insight into primary school teachers’ classroom assessment practice in mathematics in the Netherlands. Classroom assessment is assessment that teachers can use to get access to their students’ skills and understanding, in an effort to tailor their instruction to students’ needs and thus move learning ...
openaire +2 more sources
Data‐Driven Review and Machine Learning Prediction of Diamond Vacancy Center Synthesis
A machine learning framework is applied to photoluminescence spectra to extract linewidths and uncover how NV, SiV, GeV, and SnV centers evolve with growth and processing conditions. Unified normalization and k‐fold validation reveal cross‐method trends and enable rapid prediction of defect size and fabrication parameters, offering a data‐driven route ...
Zhi Jiang +3 more
wiley +1 more source
Student performance and school costs in the Philippines'high schools [PDF]
A key consideration in the policy debate on the appropriate role of private schools in predominantly public school systems is cost effectiveness. The questions are: Do private school students learn more than their counterparts, and is it more or less ...
de Vera, Ma. Lourdes +2 more
core
This study provides an introduction to Bayesian optimisation targeted for experimentalists. It explains core concepts, surrogate modelling, and acquisition strategies, and addresses common real‐world challenges such as noise, constraints, mixed variables, scalability, and automation.
Chuan He +2 more
wiley +1 more source
What did you do all day ? maternal education and child outcomes [PDF]
Female education levels are very low in many developing countries. Does maternal education have a causal impact on children's educational outcomes even at these very low levels of education?
Andrabi, Tahir +2 more
core
This review explores the transformative impact of artificial intelligence on multiscale modeling in materials research. It highlights advancements such as machine learning force fields and graph neural networks, which enhance predictive capabilities while reducing computational costs in various applications.
Artem Maevskiy +2 more
wiley +1 more source
A Flexible and Energy‐Efficient Compute‐in‐Memory Accelerator for Kolmogorov–Arnold Networks
This article presents KA‐CIM, a compute‐in‐memory accelerator for Kolmogorov–Arnold Networks (KANs). It enables flexible and efficient computation of arbitrary nonlinear functions through cross‐layer co‐optimization from algorithm to device. KA‐CIM surpasses CPU, ASIC, VMM‐CIM, and prior KAN accelerators by 1–3 orders of magnitude in energy‐delay ...
Chirag Sudarshan +6 more
wiley +1 more source
MusicSwarm: Biologically Inspired Intelligence for Music Composition
Biologically inspired swarms of frozen foundation models self‐organize to compose complex music without fine‐tuning. By coordinating through stigmergic signals, decentralized agents dynamically evolve specialized roles and adapt to solve complex tasks.
Markus J. Buehler
wiley +1 more source

