Results 101 to 110 of about 4,712,882 (251)

Two Coexisting Pathways to Volatility in Valence‐Change Memory Devices

Advanced Functional Materials, EarlyView.
Volatile VCM‐type memristive devices exhibit current relaxation after resistive switching, but their microscopic origin remains debated. Using pulsed measurements and a new Tunnel‐DLTS approach on Pt/SrTiO3/Nb:SrTiO3 devices, we show that post‐SET volatility is predominantly ionic, while electronic contributions—arising from quasi‐Fermi‐level ...
Johannes Hellwig, Clemens Wittberg, Dimitrios Spithouris, Regina Dittmann   +3 more
wiley   +1 more source

Tutorial on artificial neural network

, 2023
It is undoubtful that artificial intelligence (AI) is being the trend of computer science and this trend is still ongoing in the far future even though technologies are being developed suddenly fast because computer science does not reach the limitation of approaching biological world yet.
openaire   +1 more source

Reconfigurable Au Nanoparticle Monolayers on Regenerated Cellulose Hydrogels: Highly Sensitive SERS Detection of Polystyrene Micro/Nanoplastics With Interpretable Deep Learning

Advanced Functional Materials, EarlyView.
A regenerated cellulose (RC) hydrogel‐based SERS substrate integrating a Marangoni‐transferred gold nanoparticle self‐assembled monolayer (Au‐SAM) is fabricated. Reswelling‐induced hotspot formation enhances polystyrene micro/nanoplastics (PS MNPs) detection in complex matrices, providing reproducible, high‐throughput SERS signals across diverse ...
Youngho Jeon, Yu‐Jin Jeon, Suji Lee, Jeseong Kim, Dae‐Hyun Jung, Jungmok You   +5 more
wiley   +1 more source

Introducing a New Genetic Operator Based on Differential Evolution for the Effective Training of Neural Networks

Computers
Artificial neural networks are widely established models used to solve a variety of real-world problems in the fields of physics, chemistry, etc. These machine learning models contain a series of parameters that must be appropriately tuned by various ...
Ioannis G. Tsoulos, Vasileios Charilogis, Dimitrios Tsalikakis   +2 more
doaj   +1 more source

USING NEURAL NETWORKS AND DEEP LEARNING ALGORITHMS IN ELECTRICAL IMPEDANCE TOMOGRAPHY

Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska, 2017
This paper refers to the cases of the use of Artificial Neural Networks and Convolutional Neural Networks in impedance tomography. Machine Learning methods can be used to teach computers different technical problems.
Grzegorz Kłosowski, Tomasz Rymarczyk
doaj   +1 more source

Artificial Heart Neural Networks An Idea [PDF]

, 2021
Artificial Neural Networks Field (ANN Field) is an exciting field of research. ANN field took its inspiration from Human Brain. The heart and Brain are very important for the survival of Humans.
Baby Supriya Sri Valikala, Arun Kumar, Satish Gajawada, Dr. Maria Celestina Vanaja   +3 more
core  

Light‐Induced Field‐Tunneling Synapses in Solution‐Processed Van Der Waals Heterostructures for Scalable, Retina‐Inspired Optical Sensing

Advanced Functional Materials, EarlyView.
A scalable, solution‐processed WSe2/ZrO2‐x van der Waals heterostructure realizes a light‐induced field‐tunneling synapse (LIFTS) that activates exclusively under bright illumination, emulating the photopic adaptation of the human retina at the device level.
Kijeong Nam, Jihyun Kim, Soobeen Ji, In Soo Kim, Sejin Kim, Eungseon Yeon, Do Kyung Hwang, Iva Plutnarová, Zdeněk Sofer, Sang Min Won, Joohoon Kang   +10 more
wiley   +1 more source

Using artificial intelligence in analyzing principal components

Sustainable Engineering and Innovation
In this research, the basic concepts of both principal component analysis and artificial neural networks were reviewed, let alone tackling breast cancer, its most important causes and early detection. To add more, obtaining the principal components of a
Hasanain Jalil Neamah Alsaedi
doaj   +1 more source

Emerging Post‐CMOS Hardware Neurons for Brain‐Inspired Computing: Devices, Circuits, and System Integration

Advanced Functional Materials, EarlyView.
The physical realization of artificial neurons is a critical challenge for energy‐efficient neuromorphic computing. This review presents a comprehensive analysis of the evolution of artificial neuron implementations from conventional CMOS to emerging post‐CMOS technologies.
Kannan Udaya Mohanan, Hocheon Yoo, Benoît H. Lessard, Ioannis Kymissis, Chang‐Hyun Kim   +4 more
wiley   +1 more source

Artificial intelligence used in genome analysis studies

The EuroBiotech Journal, 2018
Next Generation Sequencing (NGS) or deep sequencing technology enables parallel reading of multiple individual DNA fragments, thereby enabling the identification of millions of base pairs in several hours.
D’Agaro Edo
doaj   +1 more source