Results 91 to 100 of about 848,733 (323)

Exploiting Two‐Photon Lithography, Deposition, and Processing to Realize Complex 3D Magnetic Nanostructures

Advanced Functional Materials, EarlyView.
Two‐photon lithography (TPL) enables 3D magnetic nanostructures with unmatched freedom in geometry and material choice. Advances in voxel control, deposition, and functionalization open pathways to artificial spin ices, racetracks, microrobots, and a number of additional technological applications.
Joseph Askey, Arjen van den Berg, Sandra Ruiz Gomez, Claire Donnelly, Dirk Grundler, Sam Ladak   +5 more
wiley   +1 more source

Ultrahigh‐Yield, Multifunctional, and High‐Performance Organic Memory for Seamless In‐Sensor Computing Operation

Advanced Functional Materials, EarlyView.
Molecular engineering of a nonconjugated radical polymer enables a significant enhancement of the glass transition temperature. The amorphous nature and tunability of the polymer, arising from its nonconjugated backbone, facilitates the fabrication of organic memristive devices with an exceptionally high yield (>95%), as well as substantial ...
Daeun Kim, Jaehyoung Ko, Namju Kim, Quynh H. Nguyen, Hoyeon Lee, Joohwan Eo, Seongeon Jin, Ji Eon Kwon, Seung‐Yeol Jeon, Youngdo Jeong, Dongseok Kwon, Sung Gap Im, Sanghan Lee, Byung Chul Jang, Yongho Joo   +14 more
wiley   +1 more source

Artificial Neural Networks [PDF]

Journal of the Royal Society of Medicine, 1999
D, Partridge, S, Rae, W J, Wang
openaire   +2 more sources

Crack‐Growing Interlayer Design for Deep Crack Propagation and Ultrahigh Sensitivity Strain Sensing

Advanced Functional Materials, EarlyView.
A crack‐growing semi‐cured polyimide interlayer enabling deep cracks for ultrahigh sensitivity in low‐strain regimes is presented. The sensor achieves a gauge factor of 100 000 at 2% strain and detects subtle deformations such as nasal breathing, highlighting potential for minimally obstructive biomedical and micromechanical sensing applications ...
Minho Kim, Taewi Kim, Jieun Park, Insic Hong, Myungrae Hong, Seonggyeong Park, Beomjin Kim, Sehyuk Ahn, Siwoo Jang, Seungyong Han, Je‐Sung Koh, Daeshik Kang   +11 more
wiley   +1 more source

Prediction of the optimal dosage of coagulants in water treatment plants through developing models based on artificial neural network fuzzy inference system (ANFIS)

, 2021
Shakeri Narges, Ghorban Asgari, Hassan Khotanlou, Mohammad Khazaei   +3 more
openalex   +2 more sources

A Smart Magnetically Actuated Flip‐Disc Programmable Metasurface with Ultralow Power Consumption for Real‐Time Channel Control

Advanced Functional Materials, EarlyView.
The study proposes a 1‐bit programmable metasurface based on flip‐disc display, named flip‐disc metasurface (FD‐MTS). This new design enables ultralow energy consumption while maintaining coding patterns. It also exhibits high scalability and multifunctional flexibility.
Jiang Han Bao, Che Liu, Jia Cheng Li, Zhen Hao Fu, Yi Su Huang, Si Qi Huang, Lei Zhang, Jian Wei You, Tie Jun Cui   +8 more
wiley   +1 more source

Modelling and evaluating customer loyalty using neural networks: Evidence from startup insurance companies

Future Business Journal, 2016
The purpose of this study is to investigate the customer–service provider relationship in the insurance industry using artificial neural networks and linear regression. Using a sample of 389 customers from 10 different startup insurance companies, it was
Azarnoush Ansari, Arash Riasi
doaj   +1 more source

Universal Neuromorphic Element: NbOx Memristor with Co‐Existing Volatile, Non‐Volatile, and Threshold Switching

Advanced Functional Materials, EarlyView.
A W/NbOx/Pt memristor demonstrates the coexistence of volatile, non‐volatile, and threshold switching characteristics. Volatile switching serves as a reservoir computing layer, providing dynamic short‐term processing. Non‐volatile switching, stabilized through ISPVA, improves reliable long‐term readout. Threshold switching operates as a leaky integrate
Ungbin Byun, Hyesung Na, Sungjun Kim
wiley   +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

A Van der Waals Optoelectronic Synapse with Tunable Positive and Negative Post‐Synaptic Current for Highly Accurate Spiking Neural Networks

Advanced Functional Materials, EarlyView.
A van der Waals optoelectronic synaptic device based on a ReS2/WSe2 heterostructure and oxygen‐treated h‐BN is presented, which enables both positive and negative PSCs through photocarrier polarity reversal. Bidirectional plasticity arises from gate‐tunable band bending and charge trapping‐induced quasi‐doping.
Hyejin Yoon, Soeun Park, Yeong Kwon Kim, Juhwan Baek, Ki Han Kim, Seongil Yun, Hyeonchang Son, Jeongeun Choi, Byung Chul Jang, Dong‐Ho Kang   +9 more
wiley   +1 more source