Results 61 to 70 of about 349,230 (288)

Universal approximation property of stochastic configuration networks for time series

Industrial Artificial Intelligence
For the purpose of processing sequential data, such as time series, and addressing the challenge of manually tuning the architecture of traditional recurrent neural networks (RNNs), this paper introduces a novel approach-the Recurrent Stochastic ...
Jin-Xi Zhang, Hangyi Zhao, Xuefeng Zhang
doaj   +1 more source

Artificial Intelligence Image Recognition Method Based on Convolutional Neural Network Algorithm

IEEE Access, 2020
As an algorithm with excellent performance, convolutional neural network has been widely used in the field of image processing and achieved good results by relying on its own local receptive fields, weight sharing, pooling, and sparse connections.
Youhui Tian
doaj   +1 more source

Signal demodulator based on in‐phase and quadrature interference‐robust feature

Electronics Letters, 2023
This letter examines the issue of mitigating strong co‐channel interference in communication systems is addressed. Unlike conventional model‐based methods, a novel data‐driven scheme is proposed.
Wen Deng, Xin Cai, Xiang Wang, Zhitao Huang   +3 more
doaj   +1 more source

Exploiting metabolic adaptations to overcome dabrafenib treatment resistance in melanoma cells

Molecular Oncology, EarlyView.
We show that dabrafenib‐resistant melanoma cells undergo mitochondrial remodeling, leading to elevated respiration and ROS production balanced by stronger antioxidant defenses. This altered redox state promotes survival despite mitochondrial damage but renders resistant cells highly vulnerable to ROS‐inducing compounds such as PEITC, highlighting redox
Silvia Eller, Susanne Ebner, Carmen Haselrieder, Julia K. Günther, Astrid Drasche, Sophie Strich, Chiara Volani, Andrea Medici, Aleksandar Nikolajevic, Alex Deltedesco, Johannes E. Sigmund, Michael J. Blumer, Martin Hermann, Johanna Vanacker, Gerald Brandacher, Eduard Stefan, Omar Torres‐Quesada, Jakob Troppmair   +17 more
wiley   +1 more source

Dammarenediol II enhances etoposide‐induced apoptosis by targeting O‐GlcNAc transferase and Akt/GSK3β/mTOR signaling in liver cancer

Molecular Oncology, EarlyView.
Etoposide induces DNA damage, activating p53‐dependent apoptosis via caspase‐3/7, which cleaves PARP1. Dammarenediol II enhances this apoptotic pathway by suppressing O‐GlcNAc transferase activity, further decreasing O‐GlcNAcylation. The reduction in O‐GlcNAc levels boosts p53‐driven apoptosis and influences the Akt/GSK3β/mTOR signaling pathway ...
Jaehoon Lee, Byung‐Cheol Han, Gi‐Bang Koo, Jihye Park, Mijin Kwon, Young Bin Park, Jae‐Mun Choi, Seung‐Ho Lee, Sangho Roh   +8 more
wiley   +1 more source

Tumour–host interactions in Drosophila: mechanisms in the tumour micro‐ and macroenvironment

Molecular Oncology, EarlyView.
This review examines how tumour–host crosstalk takes place at multiple levels of biological organisation, from local cell competition and immune crosstalk to organism‐wide metabolic and physiological collapse. Here, we integrate findings from Drosophila melanogaster studies that reveal conserved mechanisms through which tumours hijack host systems to ...
José Teles‐Reis, Tor Erik Rusten
wiley   +1 more source

Finite Size Effects in Separable Recurrent Neural Networks

, 1998
We perform a systematic analytical study of finite size effects in separable recurrent neural network models with sequential dynamics, away from saturation.
, A C C Coolen, A Castellanos, Castellanos A, Coolen A C C, Coolen A C C, Cugliandolo L F, Domany E, Gardiner C W, Hopfield J J, Horner H, Kohring G A, L Viana, Laughton S N, Ohira T, Rieger H, Van Kampen N G, Viana L   +17 more
core   +2 more sources

RaMBat: Accurate identification of medulloblastoma subtypes from diverse data sources with severe batch effects

Molecular Oncology, EarlyView.
To integrate multiple transcriptomics data with severe batch effects for identifying MB subtypes, we developed a novel and accurate computational method named RaMBat, which leveraged subtype‐specific gene expression ranking information instead of absolute gene expression levels to address batch effects of diverse data sources.
Mengtao Sun, Jieqiong Wang, Shibiao Wan
wiley   +1 more source

Study of emotion recognition based on fusion multi-modal bio-signal with SAE and LSTM recurrent neural network

Tongxin xuebao, 2017
In order to achieve more accurate emotion recognition accuracy from multi-modal bio-signal features，a novel method to extract and fuse the signal with the stacked auto-encoder and LSTM recurrent neural networks was proposed.The stacked auto-encoder ...
You-jun LI, Jia-jin HUANG, Hai-yuan WANG, Ning ZHONG   +3 more
doaj   +2 more sources

Polynomial Based Functional Link Artificial Recurrent Neural Network adaptive System for predicting Indian Stocks [PDF]

International Journal of Computational Intelligence Systems, 2015
A low complexity Polynomial Functional link Artificial Recurrent Neural Network (PFLARNN) has been proposed for the prediction of financial time series data.
D. K. Bebarta, Birendra Biswal, P. K. Dash   +2 more
doaj   +1 more source