Results 101 to 110 of about 302,002 (276)

NbOx Mott Memristor‐Based Oscillatory P‐trit for Ternary Potts Machine

Advanced Science, EarlyView.
A ternary Potts machine utilizing NbOx‐based probabilistic trits (p‐trits) is demonstrated for efficient combinatorial optimization. By leveraging the electro‐thermal switching dynamics of NbOx memristors, this architecture generates three‐state stochastic fluctuations.
Hakseung Rhee, Seoeun Jang, Tae Wook Go, Woojoon Park, Gwangmin Kim, Do Hoon Kim, Hanchan Song, Younghyun Lee, Junmo Kang, Daehee Kim, Kyung Min Kim   +10 more
wiley   +1 more source

Deep Learning Prediction of O‐Glycopeptide Tandem Mass Spectra Enhances O‐Glycoproteomics

Advanced Science, EarlyView.
DeepGPO integrates Transformer and graph neural networks with tailored training strategies, including data augmentation, loss re‐weighting, and pre‐training, to achieve high‐quality O‐glycopeptide MS/MS spectra prediction. The predicted MS/MS spectra are used to localize O‐glycosylation sites from HCD MS/MS data, enhancing O‐glycoproteomics analysis ...
Yu Zong, Yuxin Wang, Liang Qiao
wiley   +1 more source

Prediksi Jangka Panjang Solar Irradiance Pada Permukaan Pulau Jawa Menggunakan Ensemble Learning

Komputika
Energi surya menjadi solusi strategis untuk memenuhi permintaan energi di Pulau Jawa, namun pemanfaatannya terkendala oleh variabilitas radiasi matahari.
Muhammad Zulfikar, Suryani Alifah
doaj   +1 more source

Physics‐Aware Machine‐Learning‐Driven Inverse Design of Broadband Ultra‐Open Acoustic Metamaterials

Advanced Science, EarlyView.
A physics‐aware machine‐learning framework enables inverse design of ultra‐open acoustic silencers by decoupling spectral and radial design spaces. The approach rapidly identifies broadband, compact, and highly ventilated architectures, while revealing hidden linear design rules that link geometry, impedance matching, and acoustic performance.
Zhiwei Yang, Mengyu Li, Xiaohang Xie, Ao Chen, Thomas G. Bifano, Xin Zhang   +5 more
wiley   +1 more source

Comparison of AI Models for Predicting Shelf Life of Roasted Coffee Drink

Transactions on Informatics and Data Science
This paper explores the application of artificial intelligence (AI), specifically artificial neural networks (ANN), to predict the shelf life of roasted coffee beverages. The research focuses on two advanced AI models: a competitive neural network based
Sumit Goyal
doaj   +1 more source

CoSP: Reconfigurable Metamaterial Inverse Design via Contrastive Pretrained Large Language Model

Advanced Science, EarlyView.
In this work, CoSP (contrastive multi‐state pretrain), an intelligent inverse design method for reconfigurable metamaterials based on a contrastive pretrained large language model, is proposed. Numerical experiments demonstrate that CoSP can design reconfigurable metamaterial structures for multi‐state, multi‐band optical responses, showing great ...
Shujie Yang, Yuqi Zhang, Xuzhe Zhao, Yansong Tang, Kaichen Dong   +4 more
wiley   +1 more source

Transforming oil market analysis: A novel GAN + LSTM predictive framework

Next Energy
A novel method of predicting the crude oil WTI futures prices based on a data set covering April 12, 2009 through January 7, 2024. To capture complex market dynamics more precisely, it incorporates key market factors such as open, high, and low price ...
Prity Kumari, G.Y. Chandan, Satish Kumar M   +2 more
doaj   +1 more source

EndoTac: An Endoscopic Camera‐Based Tactile Sensor with High Sensitivity for Minimally Invasive Surgery

Advanced Science, EarlyView.
EndoTac presents a trocar‐compatible endoscopic vision‐based tactile sensor that uses a convex mirror to enlarge side‐facing tactile coverage during minimally invasive vessel palpation. Distorted tactile images are unwarped and processed by a learning model to estimate vascular deformation, enabling sensitive, spatially distributed tactile perception ...
Yupeng Wang, Nicolas Raison, Xuyang Zhang, Aijia Yang, Lukas Lindenroth, Shan Luo   +5 more
wiley   +1 more source

Optimal strategy for improved estimation of population mean of sensitive variable using non-sensitive auxiliary variable

Journal of Big Data
To improve the transformed ratio type estimators, this study uses new population parameters that are derived from extra information using a randomized response technique (RRT).
Abdullah A. Zaagan, Dinesh K. Sharma, Ali M. Mahnashi, Mutum Zico Meetei, Subhash Kumar Yadav, Aakriti Sharma, Pranav Sharma   +6 more
doaj   +1 more source

Data‐Driven Design of Self‐Adhesive Epidermal Electrodes and Sensors

Advanced Science, EarlyView.
This work presents self‐adhesive, stretchable epidermal electrodes and sensors developed through a data‐driven design framework that integrates artificial neural networks with genetic algorithms. By tailoring optimization objectives, either maximizing electrical conductivity and adhesion or enhancing piezoresistive sensitivity, the study enables the ...
Xuan Li, Shilei Wang, Milad Razbin, Danish Tahir, Chen Sang, Shuhua Peng, Markus Müllner, Wenlong Cheng, Wei Chen, Chun Hui Wang, Shuying Wu   +10 more
wiley   +1 more source