Results 61 to 70 of about 49,842 (269)

Predicting the ingredients of self compacting concrete using artificial neural network

Alexandria Engineering Journal, 2017
Self compacting concrete (SCC) is a highly flowable type of concrete that spreads into form without the need of mechanical vibration. This paper presents a comparative study between two methodologies which have been applied on two different data sets of ...
Mahmoud Abu Yaman, Metwally Abd Elaty, Mohamed Taman   +2 more
doaj   +1 more source

A Brain‐Wide Atlas of Astrocytic Oxytocin Receptors Reveals a Glial Basis for Nucleus Accumbens Modulation of Affiliative Behavior

Advanced Science, EarlyView.
The cellular actors of oxytocin signaling are under intense scrutiny. A brain‐wide anatomical and functional analysis in mice and rats reveals widespread expression of oxytocin receptors in astrocytes. These receptors are functionally active and, in the nucleus accumbens, selectively regulate male social affiliation.
Clémence Denis, Stefan Stojilkovic, Kai‐Yi Wang, Cristina Márquez, Annabel C. Kleinwächter, Angel Baudon, Yuval Podpecan, Aurélia Ces, Mélanie Kremer, Isabelle Arnoux, Nathalie Rouach, Jemima Helen, Sophie Trender, Andreas Wallkum, Selina Wunsch, Franziska Schommer, Moritz C. Wimmer, Tim Schubert, Felix Franke, Jabir Aliyu Muhammad, Eva M. Eisemann, Ingrid Camila Possa‐Paranhos, Cassandra Baumann, Pierre‐Alexis Derrien, Quirin Krabichler, Cosmo Garcia, Henning Fröhlich, Matthew K. Kirchner, Valery Grinevich, Pascal Darbon, Javier E. Stern, Ferdinand Althammer, Alexandre Charlet   +32 more
wiley   +1 more source

An On‐Demand Neuromorphic Vision System Enabled by a Multi‐Paradigm Neuromorphic Device and Hierarchical Reconfigurability Designed from Device to System Level

Advanced Science, EarlyView.
An on‐demand ultra‐reconfigurable intelligent vision system with hierarchical reconfigurability from device to system levels is demonstrated. Through co‐design of a multi‐paradigm device, reconfigurable circuits, and adaptive system architecture/algorithms, the system enables seamless switching among spiking, non‐spiking, neuromorphic imaging (NI), and
Biyi Jiang, Jiayi Xu, Liang Ran, Xinhe Feng, Khalil Harrabi, Yida Li, Longyang Lin, Feichi Zhou   +7 more
wiley   +1 more source

A new protection scheme for PQ events prediction and classification in distribution system: A SSO-ANN strategy

Measurement + Control, 2019
Increased utilization of nonlinear loads and fault event on the power system have resulted in a decline in the quality of power provided to the customers.
K Karthikumar, V Senthil Kumar, M Karuppiah   +2 more
doaj   +1 more source

A Computer Vision System Based on Majority-Voting Ensemble Neural Network for the Automatic Classification of Three Chickpea Varieties

Foods, 2020
Since different varieties of crops have specific applications, it is therefore important to properly identify each cultivar, in order to avoid fake varieties being sold as genuine, i.e., fraud. Despite that properly trained human experts might accurately
Razieh Pourdarbani, Sajad Sabzi, Davood Kalantari, José Luis Hernández-Hernández, Juan Ignacio Arribas   +4 more
doaj   +1 more source

Modeling a Petrochemical Unit with Artificial Neural Networks (ANN)

, 2023
The purpose of this chapter is to model a petrochemical unit by neural networks to estimate the product flow rate of the plant by it. Multilayer perceptron and RBF neural networks have been used in this work, and finally, the outputs of both types of networks have been compared to choose the more accurate network.
Shafaati Akbar, Pourazad Hamidreza
openaire   +1 more source

Physics‐Embedded Neural Network: A Novel Approach to Design Polymeric Materials

Advanced Science, EarlyView.
Traditional black‐box models for polymer mechanics rely solely on data and lack physical interpretability. This work presents a physics‐embedded neural network (PENN) that integrates constitutive equations into machine learning. The approach ensures reliable stress predictions, provides interpretable parameters, and enables performance‐driven, inverse ...
Siqi Zhan, Hengheng Zhao, Haotian Wang, Zhanjie Liu, Qian Li, Weifeng Zhang, Qingsong Zhao, Liqun Zhang, Jun Liu   +8 more
wiley   +1 more source

ReS2 Charge Trapping Synaptic Device for Face Recognition Application

Nanoscale Research Letters, 2020
Synaptic devices are necessary to meet the growing demand for the smarter and more efficient system. In this work, the anisotropic rhenium disulfide (ReS2) is used as a channel material to construct a synaptic device and successfully emulate the long ...
Ze-Hui Fan, Min Zhang, Lu-Rong Gan, Lin Chen, Hao Zhu, Qing-Qing Sun, David Wei Zhang   +6 more
doaj   +1 more source

Unifying Composition and Process Design: A Heterogeneous Graph Neural Network for Discovering High‐Performance Cu Alloys

Advanced Science, EarlyView.
By overcoming the fixed‐path limitations of conventional machine learning, a heterogeneous graph neural network fundamentally reconstructs material data representation. Integrating variable processing sequences with intrinsic elemental features, this framework enables exploratory optimization across high‐dimensional spaces.
Jie Yin, Qian Lei, Wei Yan, Yue Li, Tong Xie, Shuang Zhou, Chong Wang, Bram Hoex, Qiang Long, Caoyang Jiang, Min Song, Zhou Li, Zhangwei Wang   +12 more
wiley   +1 more source

Transient stability Assessment using Artificial Neural Network Considering Fault Location [PDF]

Iraqi Journal for Electrical and Electronic Engineering, 2010
This paper describes the capability of artificial neural network for predicting the critical clearing time of power system. It combines the advantages of time domain integration schemes with artificial neural network for real time transient ...
P.K.Olulope, K.A.Folly, S.Chowdhury, S.P.Chowdhury   +3 more
doaj