Results 41 to 50 of about 329 (133)

ML@ChemE: Past, Present, and Future of Machine Learning in Chemical Engineering

ChemBioEng Reviews, Volume 12, Issue 4, August 2025.
Although the initial machine learning (ML) applications were mainly on fault detection, signal processing, and process modeling, they extended to new areas like property estimation and material screening in later years; energy technologies, environmental issues, health, and new materials will likely be more important in future with the use of larger ...
Pınar Özdemir, Ramazan Yıldırım
wiley   +1 more source

SHAtropE—A Regional Gridded ZTD Model for China and the Surrounding Areas

Remote Sensing, 2020
A regional zenith tropospheric delay (ZTD) empirical model, referred to as SHAtropE (SHanghai Astronomical observatory tropospheric delay model—Extended), is developed and provides tropospheric propagation delay corrections for users in China and ...
Junping Chen, Jungang Wang, Ahao Wang, Junsheng Ding, Yize Zhang   +4 more
doaj   +1 more source

Optimizing PPP Performance by Incorporating ZWD Constraints Derived From Data Assimilation

Earth and Space Science, Volume 12, Issue 8, August 2025.
Abstract One of the primary error sources limiting the performance of the Precise Point Positioning (PPP) technique is the atmospheric wet delay, caused by the presence of water vapor in the lower atmosphere. Accurately representing this parameter is crucial for improving the initialization and accuracy of satellite‐based positioning techniques ...
Masoud Dehvari, Saeed Farzaneh, Ehsan Forootan   +2 more
wiley   +1 more source

Regional Tropospheric Delay Prediction Model Based on LSTM-Enhanced Encoder Network

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Precise modeling of zenith tropospheric delay (ZTD) is essential for real-time high-precision positioning in global navigation satellite systems. Due to the stochastic variability of atmospheric water vapor across different regions, tropospheric delay ...
Yuanfang Peng, Chenglin Cai, Zexian Li, Kaihui Lv, Xue Zhang, Yihao Cai   +5 more
doaj   +1 more source

Artificial Intelligence on Campus: Revisiting Understanding as an Aim of Higher Education

Educational Theory, Volume 75, Issue 4, Page 603-625, August 2025.
Abstract The launch of the powerful generative AI tool ChatGPT in November 2022 sparked a wave of fear across higher education. The tool could seemingly be used to write essays and do other work without students putting in the effort expected of them. In this paper, Jamie Herman and Henry Lara‐Steidel posit a way of addressing the concerns over ChatGPT
Jamie Herman, Henry Lara‐Steidel
wiley   +1 more source

ChatGPT's Performance Evaluation in Spreadsheets Modelling to Inform Assessments Redesign

Journal of Computer Assisted Learning, Volume 41, Issue 3, June 2025.
ABSTRACT Background Increasingly, students are using ChatGPT to assist them in learning and even completing their assessments, raising concerns of academic integrity and loss of critical thinking skills. Many articles suggested educators redesign assessments that are more ‘Generative‐AI‐resistant’ and to focus on assessing students on higher order ...
Michelle Cheong
wiley   +1 more source

Is There a Future for Stochastic Modeling in Business and Industry in the Era of Machine Learning and Artificial Intelligence?

Applied Stochastic Models in Business and Industry, Volume 41, Issue 2, March/April 2025.
ABSTRACT The paper arises from the experience of Applied Stochastic Models in Business and Industry which has seen, over the years, more and more contributions related to Machine Learning rather than to what was intended as a stochastic model. The very notion of a stochastic model (e.g., a Gaussian process or a Dynamic Linear Model) can be subject to ...
Fabrizio Ruggeri, David Banks, William S. Cleveland, Nicholas I. Fisher, Marcos Escobar‐Anel, Paolo Giudici, Emanuela Raffinetti, Roger W. Hoerl, Dennis K. J. Lin, Ron S. Kenett, Wai Keung Li, Philip L. H. Yu, Jean‐Michel Poggi, Marco S. Reis, Gilbert Saporta, Piercesare Secchi, Rituparna Sen, Ansgar Steland, Zhanpan Zhang   +18 more
wiley   +1 more source

Intelligent Grouping Method of Science and Technology Projects Based on Data Augmentation and SMOTE

Applied Artificial Intelligence, 2022
The current evaluation of science and technology projects is mainly completed by peer review, and in the process of evaluation, dividing projects into different groups is a crucial step.
Can Zhou, Mengting Li, Sha Yu
doaj   +1 more source

Scaling Laws for Discriminative Classification in Large Language Models

Applied AI Letters, Volume 6, Issue 1, February 2025.
ABSTRACT Modern large language models (LLMs) represent a paradigm shift in what can plausibly be expected of machine learning models. The fact that LLMs can effectively generate sensible answers to a diverse range of queries suggests that they would be useful in customer support applications.
Dean Wyatte, Fatemeh Tahmasbi, Ming Li, Thomas Markovich   +3 more
wiley   +1 more source

You're (Not) My Type‐ Can LLMs Generate Feedback of Specific Types for Introductory Programming Tasks?

Journal of Computer Assisted Learning, Volume 41, Issue 1, February 2025.
ABSTRACT Background Feedback as one of the most influential factors for learning has been subject to a great body of research. It plays a key role in the development of educational technology systems and is traditionally rooted in deterministic feedback defined by experts and their experience.
Dominic Lohr, Hieke Keuning, Natalie Kiesler   +2 more
wiley   +1 more source