Results 51 to 60 of about 605,541 (277)
A Link Quality Estimation Method Based on Improved Weighted Extreme Learning Machine
IEEE Access, 2021 The link quality of wireless sensor networks is the basis for selecting communication links in routing protocols. Effective link quality estimation is helpful to select high-quality links for communication and to improve network stability.
Linlan Liu, Hui Lv, Jiangbo Xu, Jian Shu
doaj +1 more source
On the Machine Learning Techniques for Side-channel Analysis [PDF]
, 2016 Side-channel attacks represent one of the most powerful category of attacks on cryptographic devices with profiled attacks in a prominent place as the most powerful among them.
Guilley, Sylvain +2 more
core
Molecular Oncology, EarlyView.Aldehyde dehydrogenase 1A1 (ALDH1A1) is a cancer stem cell marker in several malignancies. We established a novel epithelial cell line from rectal adenocarcinoma with unique overexpression of this enzyme. Genetic attenuation of ALDH1A1 led to increased invasive capacity and metastatic potential, the inhibition of proliferation activity, and ultimately ...
Martina Poturnajova +25 more
wiley +1 more source
International Journal of Distributed Sensor Networks, 2017 The research of localization technology based on received signal strength and machine learning has recently attracted a lot of attentions, since with the help of enough labeled training data this technology is able to achieve high positioning accuracy ...
Fagui Liu, Hengrui Qin, Xin Yang, Yi Yu
doaj +1 more source
What does fault tolerant Deep Learning need from MPI?
, 2017 Deep Learning (DL) algorithms have become the de facto Machine Learning (ML) algorithm for large scale data analysis. DL algorithms are computationally expensive - even distributed DL implementations which use MPI require days of training (model learning)
Amatya, Vinay +3 more
core +1 more source
Advanced Engineering Materials, EarlyView.Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt +8 more
wiley +1 more source
An FPGA-Based On-Device Reinforcement Learning Approach using Online Sequential Learning
, 2021 DQN (Deep Q-Network) is a method to perform Q-learning for reinforcement learning using deep neural networks. DQNs require a large buffer and batch processing for an experience replay and rely on a backpropagation based iterative optimization, making ...
Matsutani, Hiroki +2 more
core
A Workflow to Accelerate Microstructure‐Sensitive Fatigue Life Predictions
Advanced Engineering Materials, EarlyView.This study introduces a workflow to accelerate predictions of microstructure‐sensitive fatigue life. Results from frameworks with varying levels of simplification are benchmarked against published reference results. The analysis reveals a trade‐off between accuracy and model complexity, offering researchers a practical guide for selecting the optimal ...
Luca Loiodice +2 more
wiley +1 more source
Inverse-Matrix-Free Online Sequential Extreme Learning Machine
Jisuanji kexue yu tansuo, 2020 Since the existing inverse-matrix-free extreme learning machine (IF-ELM) only works well in batched way, this paper extends it into its inverse-matrix-free online sequential version called the inverse-matrix-free online sequential extreme learning ...
ZUO Pengyu, WANG Shitong
doaj +1 more source
Advanced Engineering Materials, EarlyView.Geometry‐driven thermal behavior in wire‐arc additive manufacturing (WAAM) influences microstructural evolution during nonequilibrium solidification of a chemically complex Fe–Cr–Nb–W–Mo–C nanocomposite system. By comparing different deposits configurations, distinct entropy–cooling rate correlations, segregation, and carbide evolution are revealed ...
Blanca Palacios +5 more
wiley +1 more source