Results 11 to 20 of about 547,727 (260)

Brain-Inspired Spatio-Temporal Associative Memories for Neuroimaging Data Classification: EEG and fMRI

Bioengineering, 2023
Humans learn from a lot of information sources to make decisions. Once this information is learned in the brain, spatio-temporal associations are made, connecting all these sources (variables) in space and time represented as brain connectivity.
Nikola K. Kasabov, Helena Bahrami, Maryam Doborjeh, Alan Wang   +3 more
doaj   +1 more source

Potential of Point-of-Care and At-Home Assessment of Immune Status via Rapid Cytokine Detection and Questionnaire-Based Anamnesis

Sensors, 2021
Monitoring the immune system’s status has emerged as an urgent demand in critical health conditions. The circulating cytokine levels in the blood reflect a thorough insight into the immune system status.
Noor Jamaludeen, Christian Beyer, Ulrike Billing, Katrin Vogel, Monika Brunner-Weinzierl, Myra Spiliopoulou   +5 more
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A framework for conceptual product-service-systems design based on design experiment

Nihon Kikai Gakkai ronbunshu, 2016
Product-Service-Systems (PSS), systems which forces on generating higher value by integrating physical products and services have been attracting much attention in manufacturing. To design PSS business model, it is important to select best business model
Keita MUTO, Koji KIMITA, Hiroki TANAKA, Eriko NUMATA, Shigeru HOSONO, Sayaka IZUKURA, Takashi SAKAKI, Yoshiki SHIMOMURA   +7 more
doaj   +1 more source

Exploring Bi-Directional Context for Improved Chatbot Response Generation Using Deep Reinforcement Learning

Applied Sciences, 2023
The development of conversational agents that can generate relevant and meaningful replies is a challenging task in the field of natural language processing.
Quoc-Dai Luong Tran, Anh-Cuong Le
doaj   +1 more source

Constrained neuro fuzzy inference methodology for explainable personalised modelling with applications on gene expression data

Scientific Reports, 2023
Interpretable machine learning models for gene expression datasets are important for understanding the decision-making process of a classifier and gaining insights on the underlying molecular processes of genetic conditions.
Balkaran Singh, Maryam Doborjeh, Zohreh Doborjeh, Sugam Budhraja, Samuel Tan, Alexander Sumich, Wilson Goh, Jimmy Lee, Edmund Lai, Nikola Kasabov   +9 more
doaj   +1 more source

Juxtaposing Medical Centers Using Different Questionnaires Through Score Predictors

Frontiers in Neuroscience, 2022
BackgroundChronic tinnitus is a clinically multidimensional phenomenon that entails audiological, psychological and somatosensory components. Previous research has demonstrated age and female gender as potential risk factors, although studies to this ...
Clara Puga, Miro Schleicher, Uli Niemann, Vishnu Unnikrishnan, Benjamin Boecking, Petra Brueggemann, Jorge Simoes, Berthold Langguth, Winfried Schlee, Birgit Mazurek, Myra Spiliopoulou   +10 more
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A Retinotopic Spiking Neural Network System for Accurate Recognition of Moving Objects Using NeuCube and Dynamic Vision Sensors

Frontiers in Computational Neuroscience, 2018
This paper introduces a new system for dynamic visual recognition that combines bio-inspired hardware with a brain-like spiking neural network. The system is designed to take data from a dynamic vision sensor (DVS) that simulates the functioning of the ...
Lukas Paulun, Lukas Paulun, Anne Wendt, Nikola Kasabov   +3 more
doaj   +1 more source

A Method of Chinese-Vietnamese Bilingual Corpus Construction for Machine Translation

IEEE Access, 2022
A bilingual corpus is vital for natural language processing problems, especially in machine translation. The larger and better quality the corpus is, the higher the efficiency of the resulting machine translation is.
Phuoc Tran, Thien Nguyen, Dinh-Hong Vu, Huu-Anh Tran, Bay Vo   +4 more
doaj   +1 more source

Improving Transformer-Based Neural Machine Translation with Prior Alignments

Complexity, 2021
Transformer is a neural machine translation model which revolutionizes machine translation. Compared with traditional statistical machine translation models and other neural machine translation models, the recently proposed transformer model radically ...
Thien Nguyen, Lam Nguyen, Phuoc Tran, Huu Nguyen   +3 more
doaj   +1 more source

Sequence-Based Explainable Hybrid Song Recommendation

Frontiers in Big Data, 2021
Despite advances in deep learning methods for song recommendation, most existing methods do not take advantage of the sequential nature of song content.
Khalil Damak, Olfa Nasraoui, William Scott Sanders   +2 more
doaj   +1 more source