Results 281 to 290 of about 21,934,771 (354)

Uncovering the Top Nonadvertising Weight Loss Websites on Google: A Data-Mining Approach. [PDF]

JMIR Infodemiology
Almenara CA, Gulec H.
europepmc   +1 more source

Inverse Engineering of Mg Alloys Using Guided Oversampling and Semi‐Supervised Learning

Advanced Intelligent Discovery, EarlyView.
End‐to‐end design of engineering materials such as Mg alloys must include the properties, structure, and post‐synthesis processing methods. However, this is challenging when destructive mechanical testing is needed to annotate unseen data, and the processing methods for hypothetical alloys are unknown.
Amanda S. Barnard
wiley   +1 more source

Data mining of adverse drug event signals with Nirmatrelvir/Ritonavir from FAERS. [PDF]

PLoS One
Sun J, Deng X, Huang J, He G, Huang S.
europepmc   +1 more source

Enhancing Synaptic Plasticity in Strontium Titanate‐Based Sensory Processing Devices: A Study on Oxygen Vacancy Modulation and Performance in Artificial Neural Networks

Advanced Intelligent Discovery, EarlyView.
This article presents the artificial synapse based on strontium titanate thin films via spin‐coating followed by forming gas annealing to introduce oxygen vacancies. Characterizations (X‐ray photoelectron spectroscopy, electron paramagnetic resonance, Ultraviolet photoelectron spectroscopy (UPS)) confirm increased oxygen vacancies and downward energy ...
Fandi Chen, Zijian Feng, Shuo Zhang, Jie Min, Long Hu, Tianxu Huang, Tingting Mei, Jiyun Kim, Beining Dong, Xinyu Ma, Tao Yin, Jintao Wang, Peiyuan Guan, Tao Wan, Chun‐Ho Lin, Zhi Li, Dewei Chu   +16 more
wiley   +1 more source

Revisiting the <i>Plasmodium falciparum</i> druggable genome using predicted structures and data mining. [PDF]

NPJ Drug Discov
Godinez-Macias KP, Chen D, Wallis JL, Siegel MG, Adam A, Bopp S, Carolino K, Coulson LB, Durst G, Thathy V, Esherick L, Farringer MA, Flannery EL, Forte B, Liu T, Godoy Magalhaes L, Gupta AK, Istvan ES, Jiang T, Kumpornsin K, Lobb K, McLean KJ, Moura IMR, Okombo J, Payne NC, Plater A, Rao SPS, Siqueira-Neto JL, Somsen BA, Summers RL, Zhang R, Gilson MK, Gamo FJ, Campo B, Baragaña B, Duffy J, Gilbert IH, Lukens AK, Dechering KJ, Niles JC, McNamara CW, Cheng X, Birkholtz LM, Bronkhorst AW, Fidock DA, Wirth DF, Goldberg DE, Lee MCS, Winzeler EA.   +48 more
europepmc   +1 more source

Identification of LIMK1 as a biomarker in clear cell renal cell carcinoma: from data mining to validation. [PDF]

J Cancer Res Clin Oncol
Li Y, Fan C, Jiang F, Zhang J, Li Y, Jiang Y, Zhang R, Yu Z, Wang S.   +8 more
europepmc   +1 more source

Deep Q‐Network‐Based Hierarchical Path Planning of a Biped Wall‐Climbing Robot for Window Cleaning

Advanced Intelligent Systems, EarlyView.
This article presents a biped wall‐cleaning climbing robotic system for the maintenance of multi‐isolated areas on exoskeleton‐structured windows (ESWs). A full coverage cleaning approach is proposed by integrating a deep Q‐network‐based method with the robotic system to address the complete coverage cleaning path planning problem.
Weijian Zhang, Zikang Li, Lap Mou Tam, Qingsong Xu   +3 more
wiley   +1 more source

Utilizing IoT Sensors and Spatial Data Mining for Analysis of Urban Space Actors' Behavior in University Campus Space Design. [PDF]

Sensors (Basel)
Koszewski K, Olszewski R, Pałka P, Walczak R, Korpas P, Dąbrowska-Żółtak K, Wyszomirski M, Czeranowska-Panufnik O, Manujło A, Szczepankowska-Bednarek U, Kuźmicz-Kubiś J, Szalwa A, Ejsmont K, Czernic P.   +13 more
europepmc   +1 more source

Knowledge Distillation‐Based Zero‐Shot Learning for Process Fault Diagnosis

Advanced Intelligent Systems, EarlyView.
Process and image data are equivalent with the teacher model pretrained on image data. Knowledge distillation transfers normal condition data to the student model. When an unknown fault occurs, differences between the teacher and student models are quantified via gradients to isolate the fault. Data‐driven deep learning is effective in diagnosing known
Yi Liu, Jiajun Huang, Mingwei Jia
wiley   +1 more source