Results 31 to 40 of about 27,643 (149)

Large Language Model‐Based Chatbots in Higher Education

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
The use of large language models (LLMs) in higher education can facilitate personalized learning experiences, advance asynchronized learning, and support instructors, students, and researchers across diverse fields. The development of regulations and guidelines that address ethical and legal issues is essential to ensure safe and responsible adaptation
Defne Yigci, Merve Eryilmaz, Ail K. Yetisen, Savas Tasoglu, Aydogan Ozcan   +4 more
wiley   +1 more source

Advancements in Machine Learning for Microrobotics in Biomedicine

Advanced Intelligent Systems, EarlyView.
Microrobotics is an innovative technology with great potential for noninvasive medical interventions. However, controlling and imaging microrobots pose significant challenges in complex environments and in living organisms. This review explores how machine learning algorithms can address these issues, offering solutions for adaptive motion control and ...
Amar Salehi, Soleiman Hosseinpour, Nasrollah Tabatabaei, Mahmoud Soltani Firouz, Niloufar Zadebana, Richard Nauber, Mariana Medina‐Sánchez   +6 more
wiley   +1 more source

A High‐Precision Dynamic Movement Recognition Algorithm Using Multimodal Biological Signals for Human–Machine Interaction

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
This article describes a multimodal fusion data acquisition and processing system about electromyography for dynamic movement recognition and bioelectrical impedance for key posture recognition. In addition, a new dynamic–static fusion algorithm strategy is designed.
Chenhao Cao, Gang Ma, Zelin Chen, Yiming Ouyang, Hu Jin, Shiwu Zhang   +5 more
wiley   +1 more source

A Hybrid Transfer Learning Framework for Brain Tumor Diagnosis

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
A novel hybrid transfer learning approach for brain tumor classification achieves 99.47% accuracy using magnetic resonance imaging (MRI) images. By combining image preprocessing, ensemble deep learning, and explainable artificial intelligence (XAI) techniques like gradient‐weighted class activation mapping and SHapley Additive exPlanations (SHAP), the ...
Sadia Islam Tonni, Md. Alif Sheakh, Mst. Sazia Tahosin, Md. Zahid Hasan, Taslima Ferdaus Shuva, Touhid Bhuiyan, Muhammad Ali Abdullah Almoyad, Nabil Anan Orka, Md. Tanvir Rahman, Risala Tasin Khan, M. Shamim Kaiser, Mohammad Ali Moni   +11 more
wiley   +1 more source

Artificial Intelligence‐Enhanced, Closed‐Loop Wearable Systems Toward Next‐Generation Diabetes Management

Advanced Intelligent Systems, EarlyView.
Recent advancements in wearable healthcare have brought accessible continuous glucose monitoring systems (CGMs) for diabetes management. To address the limitations of CGMs, closed‐loop systems utilizing monitored glucose levels for insulin dosing are being developed.
Wei Huang, Ivo Pang, Jing Bai, Binbin Cui, Xiaojuan Qi, Shiming Zhang   +5 more
wiley   +1 more source

Redshift‐Agnostic Machine Learning Classification: Unveiling Peak Performance in Galaxy, Star, and Quasar Classification (Using SDSS DR17)

Astronomische Nachrichten, EarlyView.
ABSTRACT Classification of galaxies, stars, and quasars using spectral data is fundamental to astronomy, but often relies heavily on redshift. This study evaluates the performance of 10 machine learning algorithms on SDSS data to classify these objects, with a particular focus on scenarios where redshift information is unavailable.
Debashis Chatterjee, Prithwish Ghosh
wiley   +1 more source

The potential of deep learning in improving K‐12 students' writing skills: A systematic review

British Educational Research Journal, EarlyView.
Abstract The purpose of this study is to examine the relationship between technology‐supported writing instruction at the K‐12 level and deep learning approaches and to understand the trends in this field. In the study, 12 articles selected from Web of Science, Scopus, ERIC and EBSCO databases were systematically analysed.
Mazhar Bal, Emre Öztürk
wiley   +1 more source

Localized EIS Data for Capacity and SOH Prediction With Neural Networks

Battery Energy, EarlyView.
This study showed a higher accurate capacity and state of health predictions using solely the most correlated frequencies for a neural network model. Findings showed that the charge transfer region is essential for battery prognosis studies, reducing the time needed for battery characterization using impedance.
Hakeem Thomas, Mark H. Weatherspoon, Ruben Nelson   +2 more
wiley   +1 more source

Optimization of Power System Flexibility Through AI‐Driven Dynamic Load Management and Renewable Integration

Battery Energy, EarlyView.
This study presents an AI‐driven framework for power system flexibility, integrating renewable energy and dynamic load management. Using a transformer‐based model and IEEE 14‐bus simulations, it achieves a 44% reduction in power losses, enhanced voltage stability, and superior forecasting accuracy, demonstrating AI's potential for resilient and ...
Saad Hayat, Aamir Nawaz, Aftab Ahmed Almani, Zahid Javid, William Holderbaum   +4 more
wiley   +1 more source

A recurrent neural network for soft sensor development using CHO stable pools in fed‐batch process for SARS‐CoV‐2 spike protein production as a vaccine antigen

Biotechnology Progress, EarlyView.
Abstract Fed‐batch recombinant therapeutic protein (RTP) production processes utilizing Chinese Hamster Ovary (CHO) cells can take a long period of time (>10 days). Within this period, not all critical features may be measured routinely, and in fact, some are only measured once the process is terminated, complicating decision making.
Sebastian‐Juan Reyes, Robert Voyer, Yves Durocher, Olivier Henry, Phuong Lan Pham   +4 more
wiley   +1 more source