Results 171 to 180 of about 8,339 (216)

Innovative Metasurface Colorimetric Cell‐on‐a‐Chip Sensor for Continuous, Label‐Free, Non‐Destructive Assessment of Intestinal Barrier Dynamics

Advanced Science, EarlyView.
We developed a real‐time, label‐free, high‐throughput cell‐on‐a‐chip system based on a metasurface plasmon resonance colorimetric sensor (MetaSPRCS) to evaluate intestinal barrier function. This platform enables continuous monitoring of cell adhesion, proliferation, and barrier layer formation, disruption, and repair.
Youqian Chen, Wen Li, Jiaying Feng, Yue Shu, Yihui Yang, Yuyan Wang, Rui Li, Hanlin Zhou, Xinfan Yang, Yuxue Guo, Mingqian Chen, Wenjun Hu, Gang Logan Liu, Liping Huang, Yanan Li   +14 more
wiley   +1 more source

Magneto‐X Effects in Magnetic Soft Materials and Their Applications

Advanced Science, EarlyView.
This review systematically explores magnetic soft materials (MSMs), a novel class of composites that transform under magnetic fields. It catalogs fundamental “Magneto‐X” effects, classifies materials by their matrix and magnetic fillers, and highlights transformative applications in soft robotics, biomedical devices, flexible electronics, etc. Finally,
Ziyin Xiang, Xiangling Xia, Benjamin Ducharne, Yujie Ye, Jie Shang, Run‐Wei Li   +5 more
wiley   +1 more source

Highly Aligned Bacteria Cellulose Yarn Aggregation for Energy Generation and Strain Sensing

Advanced Science, EarlyView.
Although high‐performance bacterial cellulose fibers have attracted significant interest for wearable electronics, a self‐powered and high‐mechanosensitive design is still scarce for achieving an intelligent integrated system. Here, we demonstrate an innovative bio‐fabrication strategy to develop a core‐sheath yarn that features the ordered network and
Chong Gao, Duo Xu, Hui Sun, Sun Ping, Zongxue Gu, Keshuai Liu, Zhiqiang Zhou, Bin Yu, Jian Fang, Weilin Xu   +9 more
wiley   +1 more source

Learning Processes & multimodal Representations

, 2009
Åström, Lena, Danielsson, Helena
openaire   +2 more sources

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Deep Multimodal Complementarity Learning

IEEE Transactions on Neural Networks and Learning Systems, 2023
Complementarity plays a significant role in the synergistic effect created by different components of a complex data object. Complementarity learning on multimodal data has fundamental challenges of representation learning because the complementarity exists along with multiple modalities and one or multiple items of each modality.
Daheng Wang, Tong Zhao, Wenhao Yu, Nitesh V. Chawla, Meng Jiang   +4 more
openaire   +2 more sources

Learning Multimodal Latent Attributes

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2014
The rapid development of social media sharing has created a huge demand for automatic media classification and annotation techniques. Attribute learning has emerged as a promising paradigm for bridging the semantic gap and addressing data sparsity via transferring attribute knowledge in object recognition and relatively simple action classification. In
Fu, Y, Hospedales, TM, Xiang, T, Gong, S
openaire   +3 more sources

Multimodal Learning Hub: A Tool for Capturing Customizable Multimodal Learning Experiences

2018
Studies in Learning Analytics provide concrete examples of how the analysis of direct interactions with learning management systems can be used to optimize and understand the learning process. Learning, however, does not necessarily only occur when the learner is directly interacting with such systems. With the use of sensors, it is possible to collect
Schneider, Jan, Di Mitri, Daniele, Limbu, Bibeg, Drachsler, Hendrik; id_orcid 0000-0001-8407-5314   +3 more
openaire   +2 more sources

Multimodal learning analytics

Proceedings of the Third International Conference on Learning Analytics and Knowledge, 2013
New high-frequency data collection technologies and machine learning analysis techniques could offer new insights into learning, especially in tasks in which students have ample space to generate unique, personalized artifacts, such as a computer program, a robot, or a solution to an engineering challenge. To date most of the work on learning analytics
Sharon Oviatt, Adrienne Cohen, Nadir Weibel   +2 more
openaire   +2 more sources

Multimodal Learning

PCE Official Conference Proceedings, 2022
Josefina Bengoechea, Alex Bell
openaire   +1 more source

Hierarchical Multimodal Metric Learning for Multimodal Classification

2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017
Multimodal classification arises in many computer vision tasks such as object classification and image retrieval. The idea is to utilize multiple sources (modalities) measuring the same instance to improve the overall performance compared to using a single source (modality). The varying characteristics exhibited by multiple modalities make it necessary
Heng Zhang, Vishal M. Patel, Rama Chellappa   +2 more
openaire   +1 more source